system

Abstract

We provide the system. [Solution] A means of presenting the user with questions about their hobbies, A means of receiving and analyzing user response data, A method for recommending hobbies that suit the user based on the analysis results, A means of generating information on the tools needed for a recommended hobby, A system that includes means for providing generated tool information to the user.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, many people want to have new hobbies, but there is a problem that it is difficult to find a hobby suitable for themselves. In addition, the means to easily obtain the tools and related information necessary to start a hobby are limited. As a result, it has become difficult to start a new hobby. There is a need to provide a system that solves this problem and makes it easy for users to find and start a hobby suitable for themselves.

Means for Solving the Problems

[0005] This invention provides a system that includes means for presenting users with questions about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the equipment necessary for the recommended hobbies, and means for providing the generated equipment information to the user. Furthermore, by using an artificial intelligence model for recommending hobbies based on the user's response data, more accurate hobby recommendations become possible. In addition, by providing manufacturer information and purchase links related to the equipment information necessary for the recommended hobbies, an environment is created in which users can easily obtain the necessary equipment. As a result, users can more easily find the hobby that is right for them, and the barrier to starting a hobby can be lowered.

[0006] A "user" refers to an individual who wishes to use this system to find a hobby.

[0007] A "question" refers to a question posed to a user to ascertain their interests and preferences regarding their hobbies.

[0008] "Response data" refers to the information about the answers that users enter in response to questions.

[0009] "Analysis" refers to the process of evaluating response data and identifying the most suitable hobbies for the user.

[0010] A "hobby" refers to an activity or interest that a user can pursue in their free time.

[0011] "Recommendation" refers to showing users suitable hobbies based on analysis results.

[0012] "Equipment information" refers to information about the tools and supplies that a user needs to start a particular hobby.

[0013] "Manufacturer information" refers to information about companies and brands that manufacture or sell tools and supplies.

[0014] "Purchase link" refers to the URL for users to purchase the recommended tools and supplies online.

[0015] "Means" refers to the specific methods or devices for the system of the present invention to execute specific functions.

[0016] "System" refers to the technical combination with the overall structure and functions provided by the present invention.

[0017] "Artificial intelligence model" refers to the algorithms and data models for recommending the optimal hobbies for users through large-scale data analysis and machine learning.

Brief Description of the Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of the data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of the data processing device and the smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of the data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of the data processing device and the smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of the data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of the data processing device and the headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of the data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of the data processing device and the robot according to the fourth embodiment. [Figure 9] It shows an emotion map where multiple emotions are mapped. [Figure 10] It shows an emotion map where multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] This invention is a system that provides users with the necessary information and tools to find a hobby that suits them and to start it. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, and generating and providing tool information.

[0040] User Interface

[0041] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0042] question presentation

[0043] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences.

[0044] Receiving response data

[0045] The user answers each question and sends the answers to their device. The answers are sent as structured data, such as in JSON format.

[0046] Data Analysis

[0047] The server uses a pre-trained artificial intelligence model to analyze the response data received from the terminal. Based on the user's responses, this model identifies hobbies that are likely to be most suitable for the user.

[0048] Hobby Recommendation

[0049] The server recommends several hobbies based on the analysis results. The recommended hobbies are suggested as being best suited to the user's interests and lifestyle.

[0050] Generating tool information

[0051] The server collects and generates information on the tools needed to start a recommended hobby. This information includes a list of necessary tools, recommended manufacturers, and links to purchase them.

[0052] Information provision

[0053] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0054] Specific example

[0055] For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this response data is sent to the server. The server inputs this data into an artificial intelligence model and suggests "running," "cycling," and "hiking" as optimal hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information related to that equipment (e.g., Nike, Garmin) and purchase links.

[0056] In this way, the present invention is a system that enables users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it.

[0057] The following describes the processing flow.

[0058] Step 1:

[0059] The user accesses the web application or smartphone application and clicks the button to start the hobby diagnosis.

[0060] Step 2:

[0061] The terminal retrieves the question data from the server.

[0062] Step 3:

[0063] Based on the question data acquired by the device, a series of questions about the user's hobbies are displayed.

[0064] Step 4:

[0065] The user answers each question and sends the answers to their device.

[0066] Step 5:

[0067] The device sends the user's response data to the server.

[0068] Step 6:

[0069] The server inputs the received response data into an artificial intelligence model for analysis.

[0070] Step 7:

[0071] The server generates a list of suitable hobbies for the user based on the analysis results of the artificial intelligence model.

[0072] Step 8:

[0073] The server generates information about the necessary tools for each recommended hobby (specific tool lists, recommended manufacturers, and purchase links).

[0074] Step 9:

[0075] The server generates a list of hobby recommendations and sends related equipment information to the terminal.

[0076] Step 10:

[0077] The terminal displays information received from the server to the user and provides options.

[0078] Step 11:

[0079] The user reviews the displayed list of hobbies and tools and selects a hobby that interests them.

[0080] Step 12:

[0081] Users can purchase tools by clicking the displayed purchase link as needed.

[0082] (Example 1)

[0083] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0084] In modern society, finding a hobby is an important element in improving the quality of life, but finding the right hobby is not easy. In our busy daily lives, it is difficult to find a hobby that is best suited to our individual interests and lifestyles, and to acquire the necessary tools and information all in one place. To solve this problem, there is a need for a system that recommends the most suitable hobby based on the user's preferences and lifestyle, and provides the necessary tools and information quickly and accurately.

[0085] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0086] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for conducting questions and answers via a user interface, means for transmitting the user's responses as structured data, and means for displaying detailed information about the recommended hobbies. This makes it possible for the user to easily find the hobby that is best suited to them and obtain all the necessary information and tools to start it in one place.

[0087] "User" refers to an individual who uses this system.

[0088] A "server" refers to a central processing unit that processes requests from users and performs data analysis and provides information.

[0089] A "terminal" refers to a device, such as a computer or smartphone, that a user uses to access this system.

[0090] "Means of presenting questions related to hobbies" refers to a function that displays questions in order to understand the user's preferences and lifestyle.

[0091] "Means for receiving and analyzing response data" refers to the function of a system that receives and analyzes response data collected from users.

[0092] "Methods for recommending hobbies based on analysis results" refers to a function that suggests the most suitable hobbies to the user based on analyzed data.

[0093] "Means for generating tool information" refers to a function that collects information on the tools necessary to start a recommended hobby and compiles it into a list.

[0094] "Means of providing generated tool information" refers to a function that displays or notifies the user of the generated tool information.

[0095] "User interface" refers to a screen layout that includes visual and operational elements for a user to interact with a system.

[0096] "Structured data" refers to data that is organized according to a specific format and prepared in a way that makes it easy to handle in databases, spreadsheets, and other similar applications.

[0097] An "artificial intelligence model" refers to a program that uses machine learning algorithms to analyze data and recommend the most suitable hobbies to users.

[0098] "Means of displaying detailed information" refers to a function that displays additional information about recommended hobbies to the user.

[0099] "Manufacturer information" refers to information about companies that manufacture tools.

[0100] A "purchase link" refers to a link to a webpage where the tool can be purchased.

[0101] This invention relates to a system that provides users with the necessary information and tools to find a hobby that suits them and to start it. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, and generating and providing tool information.

[0102] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0103] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. The user answers each question and sends the responses to the device. The answers are sent as structured data, such as in JSON format.

[0104] The server uses a pre-trained generative AI model to analyze the response data received from the terminal. This model is built, for example, using the Python library TENSORFLOW®. Based on the user's responses, the model identifies hobbies that are likely to be most suitable for the user.

[0105] Based on the analysis results, the server recommends several hobbies. These recommended hobbies are suggested as being best suited to the user's interests and lifestyle. Furthermore, the server collects and generates information on the equipment needed to start the recommended hobbies. This includes a list of necessary equipment, recommended manufacturers, and purchase links.

[0106] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most. For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this answer data is sent to the server. The server inputs this data into an artificial intelligence model and suggests "running," "cycling," and "hiking" as the most suitable hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment.

[0107] Examples of prompts for a generative AI model include the following:

[0108] "Please recommend the most suitable hobby based on the user's response data. The data is as follows: 'How would you like to spend your free time?': 'Actively exercise.'"

[0109] In this way, the present invention is a system that enables users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it.

[0110] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0111] Step 1: Accessing the System

[0112] The user launches a browser or smartphone app, and the login screen is displayed. The user enters their username and password to log in. For new users, they enter the required information on the sign-up screen to create an account. This is the initial step to accessing the system. The input requires login information, and the output is a state where the user can access the system.

[0113] Step 2: Start the hobby assessment

[0114] The user clicks the "Start Hobby Diagnosis" button on the home screen. This action sends an API call to the server requesting diagnostic questions. The server returns pre-stored question data to the device. The input is the user's click operation, and the output is the question data sent to the device.

[0115] Step 3: Presenting the Question

[0116] The terminal retrieves question data from the server and displays questions in an interactive format on the user interface. For example, a question like "How would you like to spend your holidays?" might be displayed. The user can answer by selecting the appropriate option or by typing a free response. The input is question data from the server, and the output is the question displayed on the user interface.

[0117] Step 4: Submit your response data

[0118] Once the user has finished answering all the questions, the device converts these answers into JSON format. For example, {"question1": "I exercise actively", "question2": "I like nature"}. This data is then sent to the server. The input is the user's answer data, and the output is structured JSON data sent to the server.

[0119] Step 5: Data Analysis

[0120] The server analyzes the JSON-formatted response data it receives. This analysis uses an AI model powered by a GPU (for example, one using the TensorFlow library in Python). The input is the response data in JSON format, and the AI ​​model performs the data processing and calculations. The output is the analysis results.

[0121] Step 6: Recommend a hobby

[0122] The server selects several hobbies that it deems most suitable for the user based on the analysis results returned by the AI ​​model. For example, hobbies such as "running," "cycling," and "hiking" might be selected. This list is then sent to the terminal. The input is the analysis results from the AI ​​model, and the output is a list of recommended hobbies.

[0123] Step 7: Tool Information Generation

[0124] The server collects information on the necessary equipment for each recommended hobby. It generates a list of the equipment needed for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with recommended manufacturers and purchase links. The input is a list of recommended hobbies, and the output is a list of equipment information.

[0125] Step 8: Displaying Information

[0126] The terminal displays information about hobbies and equipment sent from the server in the user interface. The user reviews the detailed information about the displayed hobbies and related equipment and selects the hobby that interests them most. The selection is saved in the user profile. The input is the information about hobbies and equipment from the server, and the output is the information displayed in the user interface.

[0127] This process allows users to easily find the perfect hobby for them and obtain the necessary information and tools to get started.

[0128] (Application Example 1)

[0129] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0130] Traditional hobby recommendation systems were only accessible to users through web or smartphone applications and were not designed for use in physical stores. Therefore, it was difficult to provide users with immediate hobby-related information in stores and enable them to make quick purchase decisions. Furthermore, the delay in fulfilling users' interest in hobbies could potentially lead to a loss of purchasing intent.

[0131] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0132] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for presenting questions to the user and inputting answers through a terminal installed in a physical store, means for transmitting the input response data to the server, and means for visually displaying the recommendations and tool information returned from the server. This makes it possible to quickly provide users with information on hobbies and necessary tools even in physical stores.

[0133] A "user" refers to a person who uses the system to receive hobby-related assessments and information about equipment.

[0134] "Hobbies" refer to activities and pursuits recommended based on the user's interests and lifestyle.

[0135] "Means of presenting questions" refers to methods or devices for displaying questions related to a user's hobbies.

[0136] "Means for receiving and analyzing response data" refers to methods and devices for receiving user responses and analyzing that data.

[0137] "Means of recommending hobbies that suit the user based on analysis results" refers to methods and devices that use analysis results to suggest hobbies that are suitable for the user.

[0138] "Means for generating tool information" refers to methods and devices for collecting and organizing information about the tools necessary for a recommended hobby.

[0139] "Means of providing tool information to the user" refers to methods or devices for displaying generated tool information to the user.

[0140] "Terminals installed in physical stores" refers to devices installed within physical stores that users can access and use.

[0141] A "server" refers to a central computer system that receives and analyzes user response data.

[0142] "Means of visual display" refers to methods and devices for displaying information in a way that can be seen by the user.

[0143] This invention is a system that recommends the most suitable hobby to a user and provides information on the necessary equipment through a terminal installed in a physical store. Specific embodiments for carrying out this invention are described below.

[0144] User Interface

[0145] This time, we will use tablet devices installed in physical stores. The diagnostic process starts when the user accesses the device and clicks a button to begin the hobby diagnosis. The interface must be intuitive and visually clear. For example, colorful buttons and visually appealing icons should be used.

[0146] question presentation

[0147] Terminals installed in physical stores display a series of questions about the user's hobbies, based on question data retrieved from a server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. Users answer the questions displayed on the tablet and input their answers.

[0148] Receiving response data

[0149] The terminal receives the user's response and sends that data to the server as structured data, such as in JSON format.

[0150] Data Analysis

[0151] The server uses a pre-trained generative AI model to analyze the response data received from the terminal. This model identifies hobbies that are likely to be most suitable for the user based on their responses. Specifically, the generative AI model processes the data and selects several hobbies that best match the user's interests.

[0152] Hobby Recommendation

[0153] The server recommends several hobbies based on the analysis results. The recommended hobbies are suggested as being best suited to the user's interests and lifestyle.

[0154] Generating tool information

[0155] The server collects and generates information on the equipment needed to start a recommended hobby. This information includes a list of necessary equipment, recommended manufacturers, and purchase links. For example, it might provide information on running shoes, cycling bikes, hiking boots, etc.

[0156] Information provision

[0157] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0158] Specific example

[0159] For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this response data is sent to the server. The server inputs this data into a generating AI model and suggests "running," "cycling," and "hiking" as optimal hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment.

[0160] Example of a prompt:

[0161] "{'user_profile': {'interests': 'exercise', 'lifestyle': 'active'}, 'questions': [{'id': 1, 'answer': 'How do you like to spend your holidays?: Exercise actively'}, ...]}"

[0162] The above describes a specific embodiment for carrying out the present invention. With this system, users can quickly obtain information on the most suitable hobbies and equipment, even in physical stores.

[0163] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0164] Step 1:

[0165] The user accesses a terminal installed in a physical store and clicks a button to start the hobby diagnosis. The terminal then retrieves hobby-related question data from a server and displays it on the user interface. The input is the user clicking a button, and the output is the question data displayed on the user interface.

[0166] Step 2:

[0167] The user answers questions displayed on their device. For example, to the question "How would you like to spend your holidays?", the user might answer "I would like to exercise actively." The input is the user's answer, which is stored on the device as structured data in JSON format. The output is the answer data, which is prepared to be sent to the server later.

[0168] Step 3:

[0169] The terminal sends the user's response data to the server. The user's response data is sent to the server in JSON format. The input is the response data stored on the terminal, and the output is the data that will be sent to the server.

[0170] Step 4:

[0171] The server inputs the received response data into a generating AI model for data analysis. The input consists of user responses, which the generating AI model uses for analysis. The data calculation analyzes the user's interests and lifestyle, and then selects hobbies based on this analysis. The output is a list of recommended hobbies.

[0172] Step 5:

[0173] The server recommends multiple hobbies based on the analysis results. The input is the analysis results of a generating AI model, and the output is a list of hobbies recommended for the user. Specifically, the server organizes the analysis results and selects the hobby best suited to the user.

[0174] Step 6:

[0175] The server generates information on the tools needed to start a recommended hobby. This includes a list of necessary tools, recommended manufacturers, and purchase links. The input is a list of selected hobbies, and the output is data containing tool information. Specifically, the server collects and organizes information on the necessary tools and their details for each hobby.

[0176] Step 7:

[0177] The terminal displays hobby and equipment information received from the server in a visually easy-to-understand user interface. Input includes data returned from the server, and output includes visual information displayed to the user. Specifically, the terminal analyzes the data and displays the information in a user-friendly format.

[0178] Through the above processing steps, users can quickly obtain optimal hobby and equipment information at physical stores.

[0179] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0180] This invention is a system that helps users find the hobby best suited to them and provides them with the necessary information and tools to start that hobby. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, generating and providing tool information, and acquiring emotional data by combining an emotional engine.

[0181] User Interface

[0182] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0183] question presentation

[0184] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences.

[0185] Receiving response data

[0186] The user answers each question and sends the answers to their device. The answers are sent as structured data, such as in JSON format.

[0187] Acquisition of emotional data

[0188] The device uses an emotion engine to acquire user emotion data. This is done by collecting and analyzing in real time the user's facial expressions, tone of voice, and other emotion indicators as they answer questions.

[0189] Data Analysis

[0190] The server inputs the response data and sentiment data received from the terminal into an artificial intelligence model for analysis. Based on the user's responses and sentiment data, this model identifies hobbies that are likely to be most suitable for the user.

[0191] Hobby Recommendation

[0192] The server recommends multiple hobbies based on the analysis results. The recommended hobbies are optimized by considering not only the user's interests and lifestyle, but also their emotional data, enabling more personalized suggestions.

[0193] Generating tool information

[0194] The server collects and generates information on the tools needed to start a recommended hobby. This information includes a list of necessary tools, recommended manufacturers, and links to purchase them.

[0195] Information provision

[0196] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0197] Specific example

[0198] For example, when a user starts a hobby assessment and answers "I'd like to exercise actively" to the question "How would you like to spend your holidays?", the emotion engine detects the user's facial expressions and tone of voice. This response data and emotion data are sent to a server and analyzed by an artificial intelligence model. The server suggests hobbies such as "running," "cycling," and "hiking," and generates information on the necessary equipment for each hobby (running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment. This information is then sent to the device, which displays it to the user. If the user selects "running" and clicks on the link to purchase the recommended equipment, they can easily obtain the necessary gear.

[0199] In this way, the present invention is a system that allows users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it. Furthermore, by using an emotion engine, it becomes possible to provide more personalized suggestions that take the user's emotions into account.

[0200] The following describes the processing flow.

[0201] Step 1:

[0202] The user accesses the web application or smartphone application and clicks the button to start the hobby diagnosis.

[0203] Step 2:

[0204] The terminal retrieves the question data from the server.

[0205] Step 3:

[0206] Based on the question data acquired by the device, a series of questions about the user's hobbies are displayed.

[0207] Step 4:

[0208] The user answers each question and sends the answers to their device.

[0209] Step 5:

[0210] The device sends the user's response data to the server.

[0211] Step 6:

[0212] The device activates an emotion engine and analyzes the user's facial expressions and tone of voice in real time as they answer questions. Based on this, emotion data is collected.

[0213] Step 7:

[0214] The device sends the collected emotional data to the server.

[0215] Step 8:

[0216] The server inputs response data and sentiment data into an artificial intelligence model for analysis.

[0217] Step 9:

[0218] The server generates a list of suitable hobbies for the user based on the analysis results.

[0219] Step 10:

[0220] The server generates information about the necessary tools (tool list, recommended manufacturers, purchase links) for each recommended hobby.

[0221] Step 11:

[0222] The server generates a list of hobby recommendations and sends related equipment information to the terminal.

[0223] Step 12:

[0224] The terminal displays information received from the server to the user in a visually easy-to-understand manner.

[0225] Step 13:

[0226] The user reviews the displayed list of hobbies and tools and selects a hobby that interests them.

[0227] Step 14:

[0228] Users can purchase tools by clicking the displayed purchase link as needed.

[0229] Step 15:

[0230] After the user selects a hobby and purchases the necessary equipment, the emotion engine re-analyzes the user's reactions and evaluates their satisfaction level.

[0231] Step 16:

[0232] The server inputs the satisfaction rating results as feedback into the artificial intelligence model, which then uses this data to improve the accuracy of future recommendations.

[0233] (Example 2)

[0234] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0235] In modern society, many people seek stress relief and the discovery of new hobbies, but finding a suitable hobby is not easy. Furthermore, gathering the necessary equipment to start a hobby can be time-consuming. Additionally, existing systems lack personalized recommendations that take user emotions into account. An effective system is needed to address these challenges.

[0236] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0237] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for acquiring the user's emotional data, and means for using the emotional data for analysis. This makes it possible for the user to easily find the hobby that is best suited to them and easily obtain the information and tools needed to start it. Furthermore, by receiving personalized recommendations that take emotional data into consideration, it becomes possible to choose a hobby that is more satisfying.

[0238] 1. A "question presentation means" is a means of providing an interface that displays questions about the user's hobbies and prompts them to answer.

[0239] 2. "Response data receiving means" refers to a means of receiving responses entered by a user and sending the data to a server.

[0240] 3. "Analysis means" refers to a method of performing data analysis based on received response data to identify the user's interests and needs and recommend the most suitable hobbies.

[0241] 4. A "hobby recommendation method" is a method that lists and suggests the most suitable hobbies for a user based on data obtained from analysis methods.

[0242] 5. "Tool information generation means" refers to a means of collecting, listing, and providing information on the tools necessary to start a recommended hobby.

[0243] 6. "Information provision means" refers to means of visually displaying generated tool information and purchase links to users in an easy-to-understand manner.

[0244] 7. "Methods for acquiring emotional data" refer to methods for acquiring and analyzing emotional indicators such as the user's facial expressions and tone of voice.

[0245] 8. "Emotional data analysis means" refers to a means of analyzing acquired emotional data to understand the user's emotional state and reflecting it in recommendations.

[0246] 9. A "generative artificial intelligence model" is an artificial intelligence algorithm designed to learn from large amounts of data and recommend the most suitable hobbies based on user responses.

[0247] 10. A "prompt" is text data consisting of questions or instructions that are input into a generative artificial intelligence model.

[0248] This invention is a system that helps users find the hobby best suited to them and provides them with the necessary information and tools to start that hobby. This system incorporates means for presenting questions to the user, means for receiving response data, means for acquiring emotion data, means for analysis, means for recommending hobbies, means for generating tool information, and means for providing information.

[0249] 1. User Interface

[0250] Users access the system using a dedicated web application or smartphone application. The application includes a button for users to start the hobby diagnosis; clicking this button initiates the diagnostic process. The interface must be simple and visually easy to understand.

[0251] 2. Question presentation

[0252] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. Specifically, questions such as "How would you like to spend your holidays?" might be displayed.

[0253] 3. Receiving response data

[0254] The user answers each question and sends the answers to their device. The answers are sent to the server as structured data, such as in JSON format. For example, if the user answers, "I want to exercise actively on my days off," that data will be sent.

[0255] 4. Acquisition of emotional data

[0256] The device acquires user emotion data using an emotion engine (e.g., Amazon Rekognition or Microsoft Azure's emotion analysis API). This allows for the real-time collection and analysis of the user's facial expressions, tone of voice, and other emotion indicators as they answer questions.

[0257] 5. Data Analysis

[0258] The server inputs the response data and sentiment data sent from the terminal into an artificial intelligence model (e.g., OpenAI's GPT-3 or ChatGPT) for analysis. Based on the response data and sentiment data, this model identifies the most suitable hobby for the user. For example, the response analysis might conclude that "running" is the most suitable hobby.

[0259] 6. Hobby Recommendation

[0260] The server recommends several hobbies based on the analysis results. These recommendations include "running," "cycling," and "hiking," and are optimized considering the user's interests, lifestyle, and emotional data.

[0261] 7. Generating tool information

[0262] The server collects and generates information on the equipment needed to start a recommended hobby. This information includes the type of equipment, recommended manufacturers, and purchase links. For example, equipment such as "running shoes," "cycling bikes," and "hiking boots" may be listed.

[0263] 8. Provision of Information

[0264] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this information and select hobbies and equipment that interest them. For example, by selecting "running" and clicking a link to purchase recommended equipment, they can easily acquire the necessary gear.

[0265] Specific example

[0266] For example, if a user starts a hobby assessment and answers "I'd like to exercise actively" to the question "How would you like to spend your holidays?", the emotion engine analyzes the user's facial expressions and tone of voice. This response data and emotion data are sent to a server, where an artificial intelligence model performs analysis. The server suggests hobbies such as "running," "cycling," and "hiking," and generates information on the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots), as well as manufacturer information and purchase links related to that equipment. This information is sent to the device and displayed to the user. If the user selects "running" and clicks on the link to purchase the recommended equipment, they can easily obtain the necessary gear.

[0267] Example prompt: "What would a 20-year-old university student like to do on their day off?"

[0268] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0269] Step 1:

[0270] System Access

[0271] Users access the system using a dedicated web application or smartphone application.

[0272] Specific actions:

[0273] The user launches the application on their smartphone or computer and logs in. Then, when the user clicks the "Start Hobby Diagnosis" button, the application begins the diagnostic process.

[0274] input:

[0275] User access to the system and button clicks.

[0276] output:

[0277] The diagnostic process begins.

[0278] Step 2:

[0279] question presentation

[0280] The terminal displays a series of questions about the user's hobbies based on question data retrieved from the server.

[0281] Specific actions:

[0282] The device sends a GET request to the server to retrieve the question data. The retrieved data is then analyzed to generate a question form to display to the user.

[0283] Input:

[0284] Question data obtained from the server.

[0285] Output:

[0286] Question form to be displayed to the user. For example, a question like "How do you want to spend your holidays?"

[0287] Step 3:

[0288] Receiving response data

[0289] The user answers each question and sends the answer to the terminal.

[0290] Specific operation:

[0291] The user enters an answer in the question form and presses the send button. The terminal sends the response data to the server in JSON format.

[0292] Input:

[0293] Answer entered by the user in the question form.

[0294] Output:

[0295] Response data structured in JSON format.

[0296] Step 4:

[0297] Obtaining sentiment data

[0298] The terminal obtains the user's sentiment data using the sentiment engine.

[0299] Specific operation:

[0300] The terminal uses the built-in camera and microphone to monitor the user's expression and voice tone in real time. The collected data is analyzed by the emotion engine to generate emotion data.

[0301] Input:

[0302] The user's expression and voice tone.

[0303] Output:

[0304] Analyzed emotion data.

[0305] Step 5:

[0306] Data analysis

[0307] The server inputs the response data and emotion data received from the terminal into the artificial intelligence model for analysis. This model uses a generative AI model.

[0308] Specific operations:

[0309] The server receives the data sent from the terminal and inputs it into the artificial intelligence model. It performs analysis to identify the optimal hobbies for the user.

[0310] Input:

[0311] Response data and emotion data received from the terminal.

[0312] Output:

[0313] Identification of optimal hobbies as the analysis result.

[0314] Step 6:

[0315] Hobby recommendation

[0316] The server recommends multiple hobbies based on the analysis results.

[0317] Specific operations:

[0318] The server lists and recommends hobbies derived from the analysis results. For example, hobbies such as "running," "cycling," and "hiking" may be suggested.

[0319] input:

[0320] Results of data analysis.

[0321] output:

[0322] A list of recommended hobbies.

[0323] Step 7:

[0324] Generating tool information

[0325] The server collects and generates information about the tools needed to start the recommended hobby.

[0326] Specific actions:

[0327] The server collects information on the tools needed for each hobby from databases and external APIs. Based on the collected information, it generates a list of necessary tools, recommended manufacturers, and purchase links.

[0328] input:

[0329] A list of recommended hobbies.

[0330] output:

[0331] A list of tool information, recommended manufacturers, and purchase links.

[0332] Step 8:

[0333] Information provision

[0334] The terminal displays hobby and equipment information received from the server in a visually easy-to-understand manner for the user.

[0335] Specific actions:

[0336] The server sends the generated hobby and equipment information to the terminal. The terminal then displays the information visually to the user.

[0337] input:

[0338] Hobby and equipment information received from the server.

[0339] output:

[0340] Information about hobbies and equipment is displayed visually. For example, for "running," equipment such as "running shoes" and "smartwatch" are listed, and corresponding purchase links are displayed.

[0341] (Application Example 2)

[0342] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0343] This invention relates to a system for suggesting optimal hobbies to factory workers, thereby improving their skills and reducing stress. To maintain workers' productivity and mental health, it is necessary to recommend appropriate hobbies based on their individual emotional states and provide information on necessary tools.

[0344] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for presenting questions about hobbies to the user, means for receiving and analyzing the user's response data, means for recommending hobbies that suit the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for providing a hobby suggestion function aimed at improving workers' skills and reducing stress, means for presenting questions and receiving answers using a smart device, means for acquiring and analyzing emotional index data, and means for correcting hobby recommendations using the acquired emotional index data. This makes it possible to suggest hobbies that highly reflect the user's emotions and interests, and to provide the tools and information necessary to start them.

[0345] "Means of presenting users with questions about their hobbies" refers to an interface in which a system presents a series of questions related to a user's hobbies, allowing the user to answer those questions.

[0346] "Means for receiving and analyzing user response data" refers to a function in which the system receives data provided by users, analyzes that data, and identifies the user's interests and tendencies.

[0347] "A means of recommending hobbies that suit the user based on analysis results" refers to a function that selects and proposes hobbies that best fit the user's interests based on the analyzed data.

[0348] "Means for generating information on equipment needed for a recommended hobby" refers to a function that collects and generates information on the equipment needed to start a hobby recommended to the user, and provides that information to the user.

[0349] "Means of providing generated tool information to users" refers to an interface that visually and clearly presents the tool information and purchase links generated by the system to the user.

[0350] "A means of providing a hobby suggestion function aimed at improving workers' skills and reducing stress" refers to a function that suggests the most suitable hobby for each individual worker in order to improve their skills and reduce stress within the factory.

[0351] "Means of presenting questions and receiving answers using smart devices" refers to a function that presents questions to users and receives answers using devices such as smart glasses or smartphones.

[0352] "Means for acquiring and analyzing emotional indicator data" refers to a function that analyzes emotions from a user's facial expressions, tone of voice, etc., and collects that data.

[0353] "Means for correcting hobby recommendations using acquired emotional indicator data" refers to a function that incorporates acquired emotional data into the analysis results to recommend the most suitable hobby to the user.

[0354] This invention is a system designed to suggest optimal hobbies to factory workers, aiming to improve their skills and reduce stress through those hobbies. The system uses smart devices to present questions, analyzes the response data and emotional indicator data, and then recommends the most suitable hobby for the worker, providing information on the necessary tools to begin that hobby.

[0355] Hardware and software to be used

[0356] Hardware:

[0357] Smart devices (e.g., smart glasses, smartphones)

[0358] software:

[0359] Flask (Web application framework)

[0360] EmotionEngine (an engine for analyzing facial expressions and voice)

[0361] HobbyRecommendationModel (AI model for hobby recommendations)

[0362] System Configuration

[0363] 1. The terminal uses a smart device to present questions to the user and receive answers. The questions are in the form of multiple choices related to hobbies.

[0364] 2. The terminal sends the user's response data to the question to the server as structured data, such as in JSON format.

[0365] 3. When the user answers a question, the device uses EmotionEngine to acquire emotional data such as the user's facial expressions and tone of voice in real time and analyze it.

[0366] 4. The server inputs the received response data and sentiment data into the HobbyRecommendationModel, and analyzes and identifies the most suitable hobby based on this data.

[0367] 5. Based on the analysis results, the server recommends multiple hobbies and also generates information on the tools needed to start each hobby (e.g., a list of tools, recommended manufacturers, and purchase links).

[0368] 6. The terminal visually displays hobby recommendations and equipment information received from the server to the user. The user can review this information and select hobbies and equipment that interest them.

[0369] Specific example

[0370] For example, when a factory worker puts on smart glasses and starts a hobby assessment, the question "How would you like to spend your days off?" appears on the glasses' screen. If the worker answers "I want to relax," the EmotionEngine then obtains the user's emotional data from their facial expressions and tone of voice. This response data and emotional data are sent to a server and analyzed by the HobbyRecommendationModel. The server suggests hobbies such as "yoga," "meditation," and "reading," and generates and provides information on the necessary equipment for each hobby (e.g., yoga mat, meditation cushion, reading light) and purchase links.

[0371] Example of a prompt

[0372] User response: "I want to relax."

[0373] Emotional data: High stress level, low excitement level

[0374] Recommended hobbies: "Yoga," "Meditation," "Reading"

[0375] Required equipment: "Yoga mat, meditation cushion, reading light"

[0376] In this way, the present invention is a system that enables factory workers to easily find suitable hobbies and readily obtain information and tools to improve their skills and reduce stress.

[0377] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0378] Step 1:

[0379] The device presents the user with questions about their hobbies. When the user answers a question, the device receives the answer data. The input is the answer selected or entered by the user on the screen, and the output is the answer data (in JSON format, etc.).

[0380] Step 2:

[0381] The device uses EmotionEngine to acquire user emotion data. It collects real-time information such as the user's facial expressions and tone of voice when they answer questions. The input is the user's video and audio data, and the output is the analyzed emotion data.

[0382] Step 3:

[0383] The terminal sends response data and sentiment data to the server. The input is response data and sentiment data, and the output is the transmission of data to the server.

[0384] Step 4:

[0385] The server inputs the received response data and sentiment data into the HobbyRecommendationModel. The input is the received data, which is then analyzed by the HobbyRecommendationModel. The output is hobby recommendation data as a result of the analysis.

[0386] Step 5:

[0387] The server recommends multiple hobbies based on the analysis results and generates information on the necessary tools for each. The input is hobby recommendation data, and the output is tool information (list, manufacturer information, purchase links).

[0388] Step 6:

[0389] The server sends the generated hobby recommendation and equipment information from the server to the terminal. The input is the generated hobby recommendation data and equipment information, and the output is the transmission of data to the terminal.

[0390] Step 7:

[0391] The terminal visually displays received hobby recommendations and equipment information to the user. Input is data received from the server, and output is the display on the user interface.

[0392] Step 8:

[0393] The user reviews the displayed recommended hobbies and equipment information and selects the hobbies and equipment that interest them. The input is the information displayed on the terminal, and the output is the user's selection.

[0394] Specific example

[0395] For example, a user using smart glasses answers the question "How would you like to spend your holidays?" with "I want to relax" (Step 1). EmotionEngine analyzes the user's facial expressions and tone of voice and obtains emotional data indicating a high stress level (Step 2). The device sends this response data and emotional data to the server (Step 3). The server inputs the data into HobbyRecommendationModel, which analyzes and identifies the most suitable hobby for the user (Step 4). Based on the analysis results, it recommends hobbies such as "yoga," "meditation," and "reading," and generates information on the necessary equipment for each hobby (yoga mat, meditation cushion, reading light) (Step 5). This information is sent to the device (Step 6). The device displays the hobby recommendations and equipment information to the user (Step 7). Finally, the user selects the hobby and equipment that interests them most (Step 8).

[0396] Example of a prompt:

[0397] User response: "I want to relax."

[0398] Emotional data: High stress level, low excitement level

[0399] Recommended hobbies: "Yoga," "Meditation," "Reading"

[0400] Required equipment: "Yoga mat, meditation cushion, reading light"

[0401] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0402] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0403] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0404] [Second Embodiment]

[0405] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0406] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0407] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0408] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0409] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0410] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0411] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0412] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0413] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0414] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0415] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0416] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0417] This invention is a system that provides users with the necessary information and tools to find a hobby that suits them and to start it. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, and generating and providing tool information.

[0418] User Interface

[0419] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0420] question presentation

[0421] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences.

[0422] Receiving response data

[0423] The user answers each question and sends the answers to their device. The answers are sent as structured data, such as in JSON format.

[0424] Data Analysis

[0425] The server uses a pre-trained artificial intelligence model to analyze the response data received from the terminal. Based on the user's responses, this model identifies hobbies that are likely to be most suitable for the user.

[0426] Hobby Recommendation

[0427] The server recommends several hobbies based on the analysis results. The recommended hobbies are suggested as being best suited to the user's interests and lifestyle.

[0428] Generating tool information

[0429] The server collects and generates information on the tools needed to start a recommended hobby. This information includes a list of necessary tools, recommended manufacturers, and links to purchase them.

[0430] Information provision

[0431] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0432] Specific example

[0433] For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this response data is sent to the server. The server inputs this data into an artificial intelligence model and suggests "running," "cycling," and "hiking" as optimal hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information related to that equipment (e.g., Nike, Garmin) and purchase links.

[0434] In this way, the present invention is a system that enables users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it.

[0435] The following describes the processing flow.

[0436] Step 1:

[0437] The user accesses the web application or smartphone application and clicks the button to start the hobby diagnosis.

[0438] Step 2:

[0439] The terminal retrieves the question data from the server.

[0440] Step 3:

[0441] Based on the question data acquired by the device, a series of questions about the user's hobbies are displayed.

[0442] Step 4:

[0443] The user answers each question and sends the answers to their device.

[0444] Step 5:

[0445] The device sends the user's response data to the server.

[0446] Step 6:

[0447] The server inputs the received response data into an artificial intelligence model for analysis.

[0448] Step 7:

[0449] The server generates a list of suitable hobbies for the user based on the analysis results of the artificial intelligence model.

[0450] Step 8:

[0451] The server generates information about the necessary tools for each recommended hobby (specific tool lists, recommended manufacturers, and purchase links).

[0452] Step 9:

[0453] The server generates a list of hobby recommendations and sends related equipment information to the terminal.

[0454] Step 10:

[0455] The terminal displays information received from the server to the user and provides options.

[0456] Step 11:

[0457] The user reviews the displayed list of hobbies and tools and selects a hobby that interests them.

[0458] Step 12:

[0459] Users can purchase tools by clicking the displayed purchase link as needed.

[0460] (Example 1)

[0461] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0462] In modern society, finding a hobby is an important element in improving the quality of life, but finding the right hobby is not easy. In our busy daily lives, it is difficult to find a hobby that is best suited to our individual interests and lifestyles, and to acquire the necessary tools and information all in one place. To solve this problem, there is a need for a system that recommends the most suitable hobby based on the user's preferences and lifestyle, and provides the necessary tools and information quickly and accurately.

[0463] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0464] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for conducting questions and answers via a user interface, means for transmitting the user's responses as structured data, and means for displaying detailed information about the recommended hobbies. This makes it possible for the user to easily find the hobby that is best suited to them and obtain all the necessary information and tools to start it in one place.

[0465] "User" refers to an individual who uses this system.

[0466] A "server" refers to a central processing unit that processes requests from users and performs data analysis and provides information.

[0467] A "terminal" refers to a device, such as a computer or smartphone, that a user uses to access this system.

[0468] "Means of presenting questions related to hobbies" refers to a function that displays questions in order to understand the user's preferences and lifestyle.

[0469] "Means for receiving and analyzing response data" refers to the function of a system that receives and analyzes response data collected from users.

[0470] "Methods for recommending hobbies based on analysis results" refers to a function that suggests the most suitable hobbies to the user based on analyzed data.

[0471] "Means for generating tool information" refers to a function that collects information on the tools necessary to start a recommended hobby and compiles it into a list.

[0472] "Means of providing generated tool information" refers to a function that displays or notifies the user of the generated tool information.

[0473] "User interface" refers to a screen layout that includes visual and operational elements for a user to interact with a system.

[0474] "Structured data" refers to data that is organized according to a specific format and prepared in a way that makes it easy to handle in databases, spreadsheets, and other similar applications.

[0475] An "artificial intelligence model" refers to a program that uses machine learning algorithms to analyze data and recommend the most suitable hobbies to users.

[0476] "Means of displaying detailed information" refers to a function that displays additional information about recommended hobbies to the user.

[0477] "Manufacturer information" refers to information about companies that manufacture tools.

[0478] A "purchase link" refers to a link to a webpage where the tool can be purchased.

[0479] This invention relates to a system that provides users with the necessary information and tools to find a hobby that suits them and to start it. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, and generating and providing tool information.

[0480] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0481] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. The user answers each question and sends the responses to the device. The answers are sent as structured data, such as in JSON format.

[0482] The server uses a pre-trained generative AI model to analyze the response data received from the terminal. This model is built, for example, using the TensorFlow library in Python. Based on the user's responses, the model identifies hobbies that are likely to be most suitable for the user.

[0483] Based on the analysis results, the server recommends several hobbies. These recommended hobbies are suggested as being best suited to the user's interests and lifestyle. Furthermore, the server collects and generates information on the equipment needed to start the recommended hobbies. This includes a list of necessary equipment, recommended manufacturers, and purchase links.

[0484] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most. For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this answer data is sent to the server. The server inputs this data into an artificial intelligence model and suggests "running," "cycling," and "hiking" as the most suitable hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment.

[0485] Examples of prompts for a generative AI model include the following:

[0486] "Please recommend the most suitable hobby based on the user's response data. The data is as follows: 'How would you like to spend your free time?': 'Actively exercise.'"

[0487] In this way, the present invention is a system that enables users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it.

[0488] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0489] Step 1: Accessing the System

[0490] The user launches a browser or smartphone app, and the login screen is displayed. The user enters their username and password to log in. For new users, they enter the required information on the sign-up screen to create an account. This is the initial step to accessing the system. The input requires login information, and the output is a state where the user can access the system.

[0491] Step 2: Start the hobby assessment

[0492] The user clicks the "Start Hobby Diagnosis" button on the home screen. This action sends an API call to the server requesting diagnostic questions. The server returns pre-stored question data to the device. The input is the user's click operation, and the output is the question data sent to the device.

[0493] Step 3: Presenting the Question

[0494] The terminal retrieves question data from the server and displays questions in an interactive format on the user interface. For example, a question like "How would you like to spend your holidays?" might be displayed. The user can answer by selecting the appropriate option or by typing a free response. The input is question data from the server, and the output is the question displayed on the user interface.

[0495] Step 4: Submit your response data

[0496] Once the user has finished answering all the questions, the device converts these answers into JSON format. For example, {"question1": "I exercise actively", "question2": "I like nature"}. This data is then sent to the server. The input is the user's answer data, and the output is structured JSON data sent to the server.

[0497] Step 5: Data Analysis

[0498] The server analyzes the JSON-formatted response data it receives. This analysis uses an AI model powered by a GPU (for example, one using the TensorFlow library in Python). The input is the response data in JSON format, and the AI ​​model performs the data processing and calculations. The output is the analysis results.

[0499] Step 6: Recommend a hobby

[0500] The server selects several hobbies that it deems most suitable for the user based on the analysis results returned by the AI ​​model. For example, hobbies such as "running," "cycling," and "hiking" might be selected. This list is then sent to the terminal. The input is the analysis results from the AI ​​model, and the output is a list of recommended hobbies.

[0501] Step 7: Tool Information Generation

[0502] The server collects information on the necessary equipment for each recommended hobby. It generates a list of the equipment needed for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with recommended manufacturers and purchase links. The input is a list of recommended hobbies, and the output is a list of equipment information.

[0503] Step 8: Displaying Information

[0504] The terminal displays information about hobbies and equipment sent from the server in the user interface. The user reviews the detailed information about the displayed hobbies and related equipment and selects the hobby that interests them most. The selection is saved in the user profile. The input is the information about hobbies and equipment from the server, and the output is the information displayed in the user interface.

[0505] This process allows users to easily find the perfect hobby for them and obtain the necessary information and tools to get started.

[0506] (Application Example 1)

[0507] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0508] Traditional hobby recommendation systems were only accessible to users through web or smartphone applications and were not designed for use in physical stores. Therefore, it was difficult to provide users with immediate hobby-related information in stores and enable them to make quick purchase decisions. Furthermore, the delay in fulfilling users' interest in hobbies could potentially lead to a loss of purchasing intent.

[0509] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0510] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for presenting questions to the user and inputting answers through a terminal installed in a physical store, means for transmitting the input response data to the server, and means for visually displaying the recommendations and tool information returned from the server. This makes it possible to quickly provide users with information on hobbies and necessary tools even in physical stores.

[0511] A "user" refers to a person who uses the system to receive hobby-related assessments and information about equipment.

[0512] "Hobbies" refer to activities and pursuits recommended based on the user's interests and lifestyle.

[0513] "Means of presenting questions" refers to methods or devices for displaying questions related to a user's hobbies.

[0514] "Means for receiving and analyzing response data" refers to methods and devices for receiving user responses and analyzing that data.

[0515] "Means of recommending hobbies that suit the user based on analysis results" refers to methods and devices that use analysis results to suggest hobbies that are suitable for the user.

[0516] "Means for generating tool information" refers to methods and devices for collecting and organizing information about the tools necessary for a recommended hobby.

[0517] "Means of providing tool information to the user" refers to methods or devices for displaying generated tool information to the user.

[0518] "Terminals installed in physical stores" refers to devices installed within physical stores that users can access and use.

[0519] A "server" refers to a central computer system that receives and analyzes user response data.

[0520] "Means of visual display" refers to methods and devices for displaying information in a way that can be seen by the user.

[0521] This invention is a system that recommends the most suitable hobby to a user and provides information on the necessary equipment through a terminal installed in a physical store. Specific embodiments for carrying out this invention are described below.

[0522] User Interface

[0523] This time, we will use tablet devices installed in physical stores. The diagnostic process starts when the user accesses the device and clicks a button to begin the hobby diagnosis. The interface must be intuitive and visually clear. For example, colorful buttons and visually appealing icons should be used.

[0524] question presentation

[0525] Terminals installed in physical stores display a series of questions about the user's hobbies, based on question data retrieved from a server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. Users answer the questions displayed on the tablet and input their answers.

[0526] Receiving response data

[0527] The terminal receives the user's response and sends that data to the server as structured data, such as in JSON format.

[0528] Data Analysis

[0529] The server uses a pre-trained generative AI model to analyze the response data received from the terminal. This model identifies hobbies that are likely to be most suitable for the user based on their responses. Specifically, the generative AI model processes the data and selects several hobbies that best match the user's interests.

[0530] Hobby Recommendation

[0531] The server recommends several hobbies based on the analysis results. The recommended hobbies are suggested as being best suited to the user's interests and lifestyle.

[0532] Generating tool information

[0533] The server collects and generates information on the equipment needed to start a recommended hobby. This information includes a list of necessary equipment, recommended manufacturers, and purchase links. For example, it might provide information on running shoes, cycling bikes, hiking boots, etc.

[0534] Information provision

[0535] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0536] Specific example

[0537] For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this response data is sent to the server. The server inputs this data into a generating AI model and suggests "running," "cycling," and "hiking" as optimal hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment.

[0538] Example of a prompt:

[0539] "{'user_profile': {'interests': 'exercise', 'lifestyle': 'active'}, 'questions': [{'id': 1, 'answer': 'How do you like to spend your holidays?: Exercise actively'}, ...]}"

[0540] The above describes a specific embodiment for carrying out the present invention. With this system, users can quickly obtain information on the most suitable hobbies and equipment, even in physical stores.

[0541] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0542] Step 1:

[0543] The user accesses a terminal installed in a physical store and clicks a button to start the hobby diagnosis. The terminal then retrieves hobby-related question data from a server and displays it on the user interface. The input is the user clicking a button, and the output is the question data displayed on the user interface.

[0544] Step 2:

[0545] The user answers questions displayed on their device. For example, to the question "How would you like to spend your holidays?", the user might answer "I would like to exercise actively." The input is the user's answer, which is stored on the device as structured data in JSON format. The output is the answer data, which is prepared to be sent to the server later.

[0546] Step 3:

[0547] The terminal sends the user's response data to the server. The user's response data is sent to the server in JSON format. The input is the response data stored on the terminal, and the output is the data that will be sent to the server.

[0548] Step 4:

[0549] The server inputs the received response data into a generating AI model for data analysis. The input consists of user responses, which the generating AI model uses for analysis. The data calculation analyzes the user's interests and lifestyle, and then selects hobbies based on this analysis. The output is a list of recommended hobbies.

[0550] Step 5:

[0551] The server recommends multiple hobbies based on the analysis results. The input is the analysis results of a generating AI model, and the output is a list of hobbies recommended for the user. Specifically, the server organizes the analysis results and selects the hobby best suited to the user.

[0552] Step 6:

[0553] The server generates information on the tools needed to start a recommended hobby. This includes a list of necessary tools, recommended manufacturers, and purchase links. The input is a list of selected hobbies, and the output is data containing tool information. Specifically, the server collects and organizes information on the necessary tools and their details for each hobby.

[0554] Step 7:

[0555] The terminal displays hobby and equipment information received from the server in a visually easy-to-understand user interface. Input includes data returned from the server, and output includes visual information displayed to the user. Specifically, the terminal analyzes the data and displays the information in a user-friendly format.

[0556] Through the above processing steps, users can quickly obtain optimal hobby and equipment information at physical stores.

[0557] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0558] This invention is a system that helps users find the hobby best suited to them and provides them with the necessary information and tools to start that hobby. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, generating and providing tool information, and acquiring emotional data by combining an emotional engine.

[0559] User Interface

[0560] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0561] question presentation

[0562] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences.

[0563] Receiving response data

[0564] The user answers each question and sends the answers to their device. The answers are sent as structured data, such as in JSON format.

[0565] Acquisition of emotional data

[0566] The device uses an emotion engine to acquire user emotion data. This is done by collecting and analyzing in real time the user's facial expressions, tone of voice, and other emotion indicators as they answer questions.

[0567] Data Analysis

[0568] The server inputs the response data and sentiment data received from the terminal into an artificial intelligence model for analysis. Based on the user's responses and sentiment data, this model identifies hobbies that are likely to be most suitable for the user.

[0569] Hobby Recommendation

[0570] The server recommends multiple hobbies based on the analysis results. The recommended hobbies are optimized by considering not only the user's interests and lifestyle, but also their emotional data, enabling more personalized suggestions.

[0571] Generating tool information

[0572] The server collects and generates information on the tools needed to start a recommended hobby. This information includes a list of necessary tools, recommended manufacturers, and links to purchase them.

[0573] Information provision

[0574] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0575] Specific example

[0576] For example, when a user starts a hobby assessment and answers "I'd like to exercise actively" to the question "How would you like to spend your holidays?", the emotion engine detects the user's facial expressions and tone of voice. This response data and emotion data are sent to a server and analyzed by an artificial intelligence model. The server suggests hobbies such as "running," "cycling," and "hiking," and generates information on the necessary equipment for each hobby (running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment. This information is then sent to the device, which displays it to the user. If the user selects "running" and clicks on the link to purchase the recommended equipment, they can easily obtain the necessary gear.

[0577] In this way, the present invention is a system that allows users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it. Furthermore, by using an emotion engine, it becomes possible to provide more personalized suggestions that take the user's emotions into account.

[0578] The following describes the processing flow.

[0579] Step 1:

[0580] The user accesses the web application or smartphone application and clicks the button to start the hobby diagnosis.

[0581] Step 2:

[0582] The terminal retrieves the question data from the server.

[0583] Step 3:

[0584] Based on the question data acquired by the device, a series of questions about the user's hobbies are displayed.

[0585] Step 4:

[0586] The user answers each question and sends the answers to their device.

[0587] Step 5:

[0588] The device sends the user's response data to the server.

[0589] Step 6:

[0590] The device activates an emotion engine and analyzes the user's facial expressions and tone of voice in real time as they answer questions. Based on this, emotion data is collected.

[0591] Step 7:

[0592] The device sends the collected emotional data to the server.

[0593] Step 8:

[0594] The server inputs response data and sentiment data into an artificial intelligence model for analysis.

[0595] Step 9:

[0596] The server generates a list of suitable hobbies for the user based on the analysis results.

[0597] Step 10:

[0598] The server generates information about the necessary tools (tool list, recommended manufacturers, purchase links) for each recommended hobby.

[0599] Step 11:

[0600] The server generates a list of hobby recommendations and sends related equipment information to the terminal.

[0601] Step 12:

[0602] The terminal displays information received from the server to the user in a visually easy-to-understand manner.

[0603] Step 13:

[0604] The user reviews the displayed list of hobbies and tools and selects a hobby that interests them.

[0605] Step 14:

[0606] Users can purchase tools by clicking the displayed purchase link as needed.

[0607] Step 15:

[0608] After the user selects a hobby and purchases the necessary equipment, the emotion engine re-analyzes the user's reactions and evaluates their satisfaction level.

[0609] Step 16:

[0610] The server inputs the satisfaction rating results as feedback into the artificial intelligence model, which then uses this data to improve the accuracy of future recommendations.

[0611] (Example 2)

[0612] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0613] In modern society, many people seek stress relief and the discovery of new hobbies, but finding a suitable hobby is not easy. Furthermore, gathering the necessary equipment to start a hobby can be time-consuming. Additionally, existing systems lack personalized recommendations that take user emotions into account. An effective system is needed to address these challenges.

[0614] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0615] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for acquiring the user's emotional data, and means for using the emotional data for analysis. This makes it possible for the user to easily find the hobby that is best suited to them and easily obtain the information and tools needed to start it. Furthermore, by receiving personalized recommendations that take emotional data into consideration, it becomes possible to choose a hobby that is more satisfying.

[0616] 1. A "question presentation means" is a means of providing an interface that displays questions about the user's hobbies and prompts them to answer.

[0617] 2. "Response data receiving means" refers to a means of receiving responses entered by a user and sending the data to a server.

[0618] 3. "Analysis means" refers to a method of performing data analysis based on received response data to identify the user's interests and needs and recommend the most suitable hobbies.

[0619] 4. A "hobby recommendation method" is a method that lists and suggests the most suitable hobbies for a user based on data obtained from analysis methods.

[0620] 5. "Tool information generation means" refers to a means of collecting, listing, and providing information on the tools necessary to start a recommended hobby.

[0621] 6. "Information provision means" refers to means of visually displaying generated tool information and purchase links to users in an easy-to-understand manner.

[0622] 7. "Methods for acquiring emotional data" refer to methods for acquiring and analyzing emotional indicators such as the user's facial expressions and tone of voice.

[0623] 8. "Emotional data analysis means" refers to a means of analyzing acquired emotional data to understand the user's emotional state and reflecting it in recommendations.

[0624] 9. A "generative artificial intelligence model" is an artificial intelligence algorithm designed to learn from large amounts of data and recommend the most suitable hobbies based on user responses.

[0625] 10. A "prompt" is text data consisting of questions or instructions that are input into a generative artificial intelligence model.

[0626] This invention is a system that helps users find the hobby best suited to them and provides them with the necessary information and tools to start that hobby. This system incorporates means for presenting questions to the user, means for receiving response data, means for acquiring emotion data, means for analysis, means for recommending hobbies, means for generating tool information, and means for providing information.

[0627] 1. User Interface

[0628] Users access the system using a dedicated web application or smartphone application. The application includes a button for users to start the hobby diagnosis; clicking this button initiates the diagnostic process. The interface must be simple and visually easy to understand.

[0629] 2. Question presentation

[0630] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. Specifically, questions such as "How would you like to spend your holidays?" might be displayed.

[0631] 3. Receiving response data

[0632] The user answers each question and sends the answers to their device. The answers are sent to the server as structured data, such as in JSON format. For example, if the user answers, "I want to exercise actively on my days off," that data will be sent.

[0633] 4. Acquisition of emotional data

[0634] The device uses an emotion engine (e.g., Amazon Rekognition or Microsoft Azure's emotion analysis API) to acquire user emotion data. This allows for the real-time collection and analysis of the user's facial expressions, tone of voice, and other emotion indicators as they answer questions.

[0635] 5. Data Analysis

[0636] The server inputs the response data and sentiment data sent from the terminal into an artificial intelligence model (e.g., OpenAI's GPT-3 or ChatGPT) for analysis. Based on the response data and sentiment data, this model identifies the most suitable hobby for the user. For example, the response analysis might conclude that "running" is the most suitable hobby.

[0637] 6. Hobby Recommendation

[0638] The server recommends several hobbies based on the analysis results. These recommendations include "running," "cycling," and "hiking," and are optimized considering the user's interests, lifestyle, and emotional data.

[0639] 7. Generating tool information

[0640] The server collects and generates information on the equipment needed to start a recommended hobby. This information includes the type of equipment, recommended manufacturers, and purchase links. For example, equipment such as "running shoes," "cycling bikes," and "hiking boots" may be listed.

[0641] 8. Provision of Information

[0642] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this information and select hobbies and equipment that interest them. For example, by selecting "running" and clicking a link to purchase recommended equipment, they can easily acquire the necessary gear.

[0643] Specific example

[0644] For example, if a user starts a hobby assessment and answers "I'd like to exercise actively" to the question "How would you like to spend your holidays?", the emotion engine analyzes the user's facial expressions and tone of voice. This response data and emotion data are sent to a server, where an artificial intelligence model performs analysis. The server suggests hobbies such as "running," "cycling," and "hiking," and generates information on the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots), as well as manufacturer information and purchase links related to that equipment. This information is sent to the device and displayed to the user. If the user selects "running" and clicks on the link to purchase the recommended equipment, they can easily obtain the necessary gear.

[0645] Example prompt: "What would a 20-year-old university student like to do on their day off?"

[0646] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0647] Step 1:

[0648] System Access

[0649] Users access the system using a dedicated web application or smartphone application.

[0650] Specific actions:

[0651] The user launches the application on their smartphone or computer and logs in. Then, when the user clicks the "Start Hobby Diagnosis" button, the application begins the diagnostic process.

[0652] input:

[0653] User access to the system and button clicks.

[0654] output:

[0655] The diagnostic process begins.

[0656] Step 2:

[0657] question presentation

[0658] The terminal displays a series of questions about the user's hobbies based on question data retrieved from the server.

[0659] Specific actions:

[0660] The device sends a GET request to the server to retrieve the question data. The retrieved data is then analyzed to generate a question form to display to the user.

[0661] input:

[0662] Question data retrieved from the server.

[0663] output:

[0664] A question form displayed to the user. For example, a question like, "How would you like to spend your holidays?"

[0665] Step 3:

[0666] Receiving response data

[0667] The user answers each question and sends the answers to their device.

[0668] Specific actions:

[0669] The user enters their answers into the question form and presses the submit button. The device sends the answer data to the server in JSON format.

[0670] input:

[0671] The user's response entered into the question form.

[0672] output:

[0673] Response data structured in JSON format.

[0674] Step 4:

[0675] Acquisition of emotional data

[0676] The device uses an emotion engine to acquire user emotion data.

[0677] Specific actions:

[0678] The device uses its built-in camera and microphone to monitor the user's facial expressions and voice tone in real time. The collected data is analyzed by an emotion engine to generate emotion data.

[0679] input:

[0680] The user's facial expressions and tone of voice.

[0681] output:

[0682] Analyzed emotion data.

[0683] Step 5:

[0684] Data Analysis

[0685] The server inputs the response data and sentiment data received from the terminal into an artificial intelligence model for analysis. This model uses a generative AI model.

[0686] Specific actions:

[0687] The server receives data sent from the terminal and inputs it into an artificial intelligence model. It then performs analysis to identify the user's most suitable hobbies.

[0688] input:

[0689] Response data and sentiment data received from the device.

[0690] output:

[0691] Identifying the optimal hobby based on the analysis results.

[0692] Step 6:

[0693] Hobby Recommendation

[0694] The server recommends several hobbies based on the analysis results.

[0695] Specific actions:

[0696] The server lists and recommends hobbies derived from the analysis results. For example, hobbies such as "running," "cycling," and "hiking" may be suggested.

[0697] input:

[0698] Results of data analysis.

[0699] output:

[0700] A list of recommended hobbies.

[0701] Step 7:

[0702] Generating tool information

[0703] The server collects and generates information about the tools needed to start the recommended hobby.

[0704] Specific actions:

[0705] The server collects information on the tools needed for each hobby from databases and external APIs. Based on the collected information, it generates a list of necessary tools, recommended manufacturers, and purchase links.

[0706] input:

[0707] A list of recommended hobbies.

[0708] output:

[0709] A list of tool information, recommended manufacturers, and purchase links.

[0710] Step 8:

[0711] Information provision

[0712] The terminal displays hobby and equipment information received from the server in a visually easy-to-understand manner for the user.

[0713] Specific actions:

[0714] The server sends the generated hobby and equipment information to the terminal. The terminal then displays the information visually to the user.

[0715] input:

[0716] Hobby and equipment information received from the server.

[0717] output:

[0718] Information about hobbies and equipment is displayed visually. For example, for "running," equipment such as "running shoes" and "smartwatch" are listed, and corresponding purchase links are displayed.

[0719] (Application Example 2)

[0720] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0721] This invention relates to a system for suggesting optimal hobbies to factory workers, thereby improving their skills and reducing stress. To maintain workers' productivity and mental health, it is necessary to recommend appropriate hobbies based on their individual emotional states and provide information on necessary tools.

[0722] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for presenting questions about hobbies to the user, means for receiving and analyzing the user's response data, means for recommending hobbies that suit the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for providing a hobby suggestion function aimed at improving workers' skills and reducing stress, means for presenting questions and receiving answers using a smart device, means for acquiring and analyzing emotional index data, and means for correcting hobby recommendations using the acquired emotional index data. This makes it possible to suggest hobbies that highly reflect the user's emotions and interests, and to provide the tools and information necessary to start them.

[0723] "Means of presenting users with questions about their hobbies" refers to an interface in which a system presents a series of questions related to a user's hobbies, allowing the user to answer those questions.

[0724] "Means for receiving and analyzing user response data" refers to a function in which the system receives data provided by users, analyzes that data, and identifies the user's interests and tendencies.

[0725] "A means of recommending hobbies that suit the user based on analysis results" refers to a function that selects and proposes hobbies that best fit the user's interests based on the analyzed data.

[0726] "Means for generating information on equipment needed for a recommended hobby" refers to a function that collects and generates information on the equipment needed to start a hobby recommended to the user, and provides that information to the user.

[0727] "Means of providing generated tool information to users" refers to an interface that visually and clearly presents the tool information and purchase links generated by the system to the user.

[0728] "A means of providing a hobby suggestion function aimed at improving workers' skills and reducing stress" refers to a function that suggests the most suitable hobby for each individual worker in order to improve their skills and reduce stress within the factory.

[0729] "Means of presenting questions and receiving answers using smart devices" refers to a function that presents questions to users and receives answers using devices such as smart glasses or smartphones.

[0730] "Means for acquiring and analyzing emotional indicator data" refers to a function that analyzes emotions from a user's facial expressions, tone of voice, etc., and collects that data.

[0731] "Means for correcting hobby recommendations using acquired emotional indicator data" refers to a function that incorporates acquired emotional data into the analysis results to recommend the most suitable hobby to the user.

[0732] This invention is a system designed to suggest optimal hobbies to factory workers, aiming to improve their skills and reduce stress through those hobbies. The system uses smart devices to present questions, analyzes the response data and emotional indicator data, and then recommends the most suitable hobby for the worker, providing information on the necessary tools to begin that hobby.

[0733] Hardware and software to be used

[0734] Hardware:

[0735] Smart devices (e.g., smart glasses, smartphones)

[0736] software:

[0737] Flask (Web application framework)

[0738] EmotionEngine (an engine for analyzing facial expressions and voice)

[0739] HobbyRecommendationModel (AI model for hobby recommendations)

[0740] System Configuration

[0741] 1. The terminal uses a smart device to present questions to the user and receive answers. The questions are in the form of multiple choices related to hobbies.

[0742] 2. The terminal sends the user's response data to the question to the server as structured data, such as in JSON format.

[0743] 3. When the user answers a question, the device uses EmotionEngine to acquire emotional data such as the user's facial expressions and tone of voice in real time and analyze it.

[0744] 4. The server inputs the received response data and sentiment data into the HobbyRecommendationModel, and analyzes and identifies the most suitable hobby based on this data.

[0745] 5. Based on the analysis results, the server recommends multiple hobbies and also generates information on the tools needed to start each hobby (e.g., a list of tools, recommended manufacturers, and purchase links).

[0746] 6. The terminal visually displays hobby recommendations and equipment information received from the server to the user. The user can review this information and select hobbies and equipment that interest them.

[0747] Specific example

[0748] For example, when a factory worker puts on smart glasses and starts a hobby assessment, the question "How would you like to spend your days off?" appears on the glasses' screen. If the worker answers "I want to relax," the EmotionEngine then obtains the user's emotional data from their facial expressions and tone of voice. This response data and emotional data are sent to a server and analyzed by the HobbyRecommendationModel. The server suggests hobbies such as "yoga," "meditation," and "reading," and generates and provides information on the necessary equipment for each hobby (e.g., yoga mat, meditation cushion, reading light) and purchase links.

[0749] Example of a prompt

[0750] User response: "I want to relax."

[0751] Emotional data: High stress level, low excitement level

[0752] Recommended hobbies: "Yoga," "Meditation," "Reading"

[0753] Required equipment: "Yoga mat, meditation cushion, reading light"

[0754] In this way, the present invention is a system that enables factory workers to easily find suitable hobbies and readily obtain information and tools to improve their skills and reduce stress.

[0755] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0756] Step 1:

[0757] The device presents the user with questions about their hobbies. When the user answers a question, the device receives the answer data. The input is the answer selected or entered by the user on the screen, and the output is the answer data (in JSON format, etc.).

[0758] Step 2:

[0759] The device uses EmotionEngine to acquire user emotion data. It collects real-time information such as the user's facial expressions and tone of voice when they answer questions. The input is the user's video and audio data, and the output is the analyzed emotion data.

[0760] Step 3:

[0761] The terminal sends response data and sentiment data to the server. The input is response data and sentiment data, and the output is the transmission of data to the server.

[0762] Step 4:

[0763] The server inputs the received response data and sentiment data into the HobbyRecommendationModel. The input is the received data, which is then analyzed by the HobbyRecommendationModel. The output is hobby recommendation data as a result of the analysis.

[0764] Step 5:

[0765] The server recommends multiple hobbies based on the analysis results and generates information on the necessary tools for each. The input is hobby recommendation data, and the output is tool information (list, manufacturer information, purchase links).

[0766] Step 6:

[0767] The server sends the generated hobby recommendation and equipment information from the server to the terminal. The input is the generated hobby recommendation data and equipment information, and the output is the transmission of data to the terminal.

[0768] Step 7:

[0769] The terminal visually displays received hobby recommendations and equipment information to the user. Input is data received from the server, and output is the display on the user interface.

[0770] Step 8:

[0771] The user reviews the displayed recommended hobbies and equipment information and selects the hobbies and equipment that interest them. The input is the information displayed on the terminal, and the output is the user's selection.

[0772] Specific example

[0773] For example, a user using smart glasses answers the question "How would you like to spend your holidays?" with "I want to relax" (Step 1). EmotionEngine analyzes the user's facial expressions and tone of voice and obtains emotional data indicating a high stress level (Step 2). The device sends this response data and emotional data to the server (Step 3). The server inputs the data into HobbyRecommendationModel, which analyzes and identifies the most suitable hobby for the user (Step 4). Based on the analysis results, it recommends hobbies such as "yoga," "meditation," and "reading," and generates information on the necessary equipment for each hobby (yoga mat, meditation cushion, reading light) (Step 5). This information is sent to the device (Step 6). The device displays the hobby recommendations and equipment information to the user (Step 7). Finally, the user selects the hobby and equipment that interests them most (Step 8).

[0774] Example of a prompt:

[0775] User response: "I want to relax."

[0776] Emotional data: High stress level, low excitement level

[0777] Recommended hobbies: "Yoga," "Meditation," "Reading"

[0778] Required equipment: "Yoga mat, meditation cushion, reading light"

[0779] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0780] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0781] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0782] [Third Embodiment]

[0783] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0784] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0785] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0786] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0787] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0788] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0789] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0790] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0791] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0792] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0793] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0794] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0795] This invention is a system that provides users with the necessary information and tools to find a hobby that suits them and to start it. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, and generating and providing tool information.

[0796] User Interface

[0797] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0798] question presentation

[0799] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences.

[0800] Receiving response data

[0801] The user answers each question and sends the answers to their device. The answers are sent as structured data, such as in JSON format.

[0802] Data Analysis

[0803] The server uses a pre-trained artificial intelligence model to analyze the response data received from the terminal. Based on the user's responses, this model identifies hobbies that are likely to be most suitable for the user.

[0804] Hobby Recommendation

[0805] The server recommends several hobbies based on the analysis results. The recommended hobbies are suggested as being best suited to the user's interests and lifestyle.

[0806] Generating tool information

[0807] The server collects and generates information on the tools needed to start a recommended hobby. This information includes a list of necessary tools, recommended manufacturers, and links to purchase them.

[0808] Information provision

[0809] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0810] Specific example

[0811] For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this response data is sent to the server. The server inputs this data into an artificial intelligence model and suggests "running," "cycling," and "hiking" as optimal hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information related to that equipment (e.g., Nike, Garmin) and purchase links.

[0812] In this way, the present invention is a system that enables users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it.

[0813] The following describes the processing flow.

[0814] Step 1:

[0815] The user accesses the web application or smartphone application and clicks the button to start the hobby diagnosis.

[0816] Step 2:

[0817] The terminal retrieves the question data from the server.

[0818] Step 3:

[0819] Based on the question data acquired by the device, a series of questions about the user's hobbies are displayed.

[0820] Step 4:

[0821] The user answers each question and sends the answers to their device.

[0822] Step 5:

[0823] The device sends the user's response data to the server.

[0824] Step 6:

[0825] The server inputs the received response data into an artificial intelligence model for analysis.

[0826] Step 7:

[0827] The server generates a list of suitable hobbies for the user based on the analysis results of the artificial intelligence model.

[0828] Step 8:

[0829] The server generates information about the necessary tools for each recommended hobby (specific tool lists, recommended manufacturers, and purchase links).

[0830] Step 9:

[0831] The server generates a list of hobby recommendations and sends related equipment information to the terminal.

[0832] Step 10:

[0833] The terminal displays information received from the server to the user and provides options.

[0834] Step 11:

[0835] The user reviews the displayed list of hobbies and tools and selects a hobby that interests them.

[0836] Step 12:

[0837] Users can purchase tools by clicking the displayed purchase link as needed.

[0838] (Example 1)

[0839] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0840] In modern society, finding a hobby is an important element in improving the quality of life, but finding the right hobby is not easy. In our busy daily lives, it is difficult to find a hobby that is best suited to our individual interests and lifestyles, and to acquire the necessary tools and information all in one place. To solve this problem, there is a need for a system that recommends the most suitable hobby based on the user's preferences and lifestyle, and provides the necessary tools and information quickly and accurately.

[0841] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0842] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for conducting questions and answers via a user interface, means for transmitting the user's responses as structured data, and means for displaying detailed information about the recommended hobbies. This makes it possible for the user to easily find the hobby that is best suited to them and obtain all the necessary information and tools to start it in one place.

[0843] "User" refers to an individual who uses this system.

[0844] A "server" refers to a central processing unit that processes requests from users and performs data analysis and provides information.

[0845] A "terminal" refers to a device, such as a computer or smartphone, that a user uses to access this system.

[0846] "Means of presenting questions related to hobbies" refers to a function that displays questions in order to understand the user's preferences and lifestyle.

[0847] "Means for receiving and analyzing response data" refers to the function of a system that receives and analyzes response data collected from users.

[0848] "Methods for recommending hobbies based on analysis results" refers to a function that suggests the most suitable hobbies to the user based on analyzed data.

[0849] "Means for generating tool information" refers to a function that collects information on the tools necessary to start a recommended hobby and compiles it into a list.

[0850] "Means of providing generated tool information" refers to a function that displays or notifies the user of the generated tool information.

[0851] "User interface" refers to a screen layout that includes visual and operational elements for a user to interact with a system.

[0852] "Structured data" refers to data that is organized according to a specific format and prepared in a way that makes it easy to handle in databases, spreadsheets, and other similar applications.

[0853] An "artificial intelligence model" refers to a program that uses machine learning algorithms to analyze data and recommend the most suitable hobbies to users.

[0854] "Means of displaying detailed information" refers to a function that displays additional information about recommended hobbies to the user.

[0855] "Manufacturer information" refers to information about companies that manufacture tools.

[0856] A "purchase link" refers to a link to a webpage where the tool can be purchased.

[0857] This invention relates to a system that provides users with the necessary information and tools to find a hobby that suits them and to start it. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, and generating and providing tool information.

[0858] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0859] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. The user answers each question and sends the responses to the device. The answers are sent as structured data, such as in JSON format.

[0860] The server uses a pre-trained generative AI model to analyze the response data received from the terminal. This model is built, for example, using the TensorFlow library in Python. Based on the user's responses, the model identifies hobbies that are likely to be most suitable for the user.

[0861] Based on the analysis results, the server recommends several hobbies. These recommended hobbies are suggested as being best suited to the user's interests and lifestyle. Furthermore, the server collects and generates information on the equipment needed to start the recommended hobbies. This includes a list of necessary equipment, recommended manufacturers, and purchase links.

[0862] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most. For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this answer data is sent to the server. The server inputs this data into an artificial intelligence model and suggests "running," "cycling," and "hiking" as the most suitable hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment.

[0863] Examples of prompts for a generative AI model include the following:

[0864] "Please recommend the most suitable hobby based on the user's response data. The data is as follows: 'How would you like to spend your free time?': 'Actively exercise.'"

[0865] In this way, the present invention is a system that enables users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it.

[0866] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0867] Step 1: Accessing the System

[0868] The user launches a browser or smartphone app, and the login screen is displayed. The user enters their username and password to log in. For new users, they enter the required information on the sign-up screen to create an account. This is the initial step to accessing the system. The input requires login information, and the output is a state where the user can access the system.

[0869] Step 2: Start the hobby assessment

[0870] The user clicks the "Start Hobby Diagnosis" button on the home screen. This action sends an API call to the server requesting diagnostic questions. The server returns pre-stored question data to the device. The input is the user's click operation, and the output is the question data sent to the device.

[0871] Step 3: Presenting the Question

[0872] The terminal retrieves question data from the server and displays questions in an interactive format on the user interface. For example, a question like "How would you like to spend your holidays?" might be displayed. The user can answer by selecting the appropriate option or by typing a free response. The input is question data from the server, and the output is the question displayed on the user interface.

[0873] Step 4: Submit your response data

[0874] Once the user has finished answering all the questions, the device converts these answers into JSON format. For example, {"question1": "I exercise actively", "question2": "I like nature"}. This data is then sent to the server. The input is the user's answer data, and the output is structured JSON data sent to the server.

[0875] Step 5: Data Analysis

[0876] The server analyzes the JSON-formatted response data it receives. This analysis uses an AI model powered by a GPU (for example, one using the TensorFlow library in Python). The input is the response data in JSON format, and the AI ​​model performs the data processing and calculations. The output is the analysis results.

[0877] Step 6: Recommend a hobby

[0878] The server selects several hobbies that it deems most suitable for the user based on the analysis results returned by the AI ​​model. For example, hobbies such as "running," "cycling," and "hiking" might be selected. This list is then sent to the terminal. The input is the analysis results from the AI ​​model, and the output is a list of recommended hobbies.

[0879] Step 7: Tool Information Generation

[0880] The server collects information on the necessary equipment for each recommended hobby. It generates a list of the equipment needed for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with recommended manufacturers and purchase links. The input is a list of recommended hobbies, and the output is a list of equipment information.

[0881] Step 8: Displaying Information

[0882] The terminal displays information about hobbies and equipment sent from the server in the user interface. The user reviews the detailed information about the displayed hobbies and related equipment and selects the hobby that interests them most. The selection is saved in the user profile. The input is the information about hobbies and equipment from the server, and the output is the information displayed in the user interface.

[0883] This process allows users to easily find the perfect hobby for them and obtain the necessary information and tools to get started.

[0884] (Application Example 1)

[0885] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0886] Traditional hobby recommendation systems were only accessible to users through web or smartphone applications and were not designed for use in physical stores. Therefore, it was difficult to provide users with immediate hobby-related information in stores and enable them to make quick purchase decisions. Furthermore, the delay in fulfilling users' interest in hobbies could potentially lead to a loss of purchasing intent.

[0887] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0888] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for presenting questions to the user and inputting answers through a terminal installed in a physical store, means for transmitting the input response data to the server, and means for visually displaying the recommendations and tool information returned from the server. This makes it possible to quickly provide users with information on hobbies and necessary tools even in physical stores.

[0889] A "user" refers to a person who uses the system to receive hobby-related assessments and information about equipment.

[0890] "Hobbies" refer to activities and pursuits recommended based on the user's interests and lifestyle.

[0891] "Means of presenting questions" refers to methods or devices for displaying questions related to a user's hobbies.

[0892] "Means for receiving and analyzing response data" refers to methods and devices for receiving user responses and analyzing that data.

[0893] "Means of recommending hobbies that suit the user based on analysis results" refers to methods and devices that use analysis results to suggest hobbies that are suitable for the user.

[0894] "Means for generating tool information" refers to methods and devices for collecting and organizing information about the tools necessary for a recommended hobby.

[0895] "Means of providing tool information to the user" refers to methods or devices for displaying generated tool information to the user.

[0896] "Terminals installed in physical stores" refers to devices installed within physical stores that users can access and use.

[0897] A "server" refers to a central computer system that receives and analyzes user response data.

[0898] "Means of visual display" refers to methods and devices for displaying information in a way that can be seen by the user.

[0899] This invention is a system that recommends the most suitable hobby to a user and provides information on the necessary equipment through a terminal installed in a physical store. Specific embodiments for carrying out this invention are described below.

[0900] User Interface

[0901] This time, we will use tablet devices installed in physical stores. The diagnostic process starts when the user accesses the device and clicks a button to begin the hobby diagnosis. The interface must be intuitive and visually clear. For example, colorful buttons and visually appealing icons should be used.

[0902] question presentation

[0903] Terminals installed in physical stores display a series of questions about the user's hobbies, based on question data retrieved from a server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. Users answer the questions displayed on the tablet and input their answers.

[0904] Receiving response data

[0905] The terminal receives the user's response and sends that data to the server as structured data, such as in JSON format.

[0906] Data Analysis

[0907] The server uses a pre-trained generative AI model to analyze the response data received from the terminal. This model identifies hobbies that are likely to be most suitable for the user based on their responses. Specifically, the generative AI model processes the data and selects several hobbies that best match the user's interests.

[0908] Hobby Recommendation

[0909] The server recommends several hobbies based on the analysis results. The recommended hobbies are suggested as being best suited to the user's interests and lifestyle.

[0910] Generating tool information

[0911] The server collects and generates information on the equipment needed to start a recommended hobby. This information includes a list of necessary equipment, recommended manufacturers, and purchase links. For example, it might provide information on running shoes, cycling bikes, hiking boots, etc.

[0912] Information provision

[0913] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0914] Specific example

[0915] For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this response data is sent to the server. The server inputs this data into a generating AI model and suggests "running," "cycling," and "hiking" as optimal hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment.

[0916] Example of a prompt:

[0917] "{'user_profile': {'interests': 'exercise', 'lifestyle': 'active'}, 'questions': [{'id': 1, 'answer': 'How do you like to spend your holidays?: Exercise actively'}, ...]}"

[0918] The above describes a specific embodiment for carrying out the present invention. With this system, users can quickly obtain information on the most suitable hobbies and equipment, even in physical stores.

[0919] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0920] Step 1:

[0921] The user accesses a terminal installed in a physical store and clicks a button to start the hobby diagnosis. The terminal then retrieves hobby-related question data from a server and displays it on the user interface. The input is the user clicking a button, and the output is the question data displayed on the user interface.

[0922] Step 2:

[0923] The user answers questions displayed on their device. For example, to the question "How would you like to spend your holidays?", the user might answer "I would like to exercise actively." The input is the user's answer, which is stored on the device as structured data in JSON format. The output is the answer data, which is prepared to be sent to the server later.

[0924] Step 3:

[0925] The terminal sends the user's response data to the server. The user's response data is sent to the server in JSON format. The input is the response data stored on the terminal, and the output is the data that will be sent to the server.

[0926] Step 4:

[0927] The server inputs the received response data into a generating AI model for data analysis. The input consists of user responses, which the generating AI model uses for analysis. The data calculation analyzes the user's interests and lifestyle, and then selects hobbies based on this analysis. The output is a list of recommended hobbies.

[0928] Step 5:

[0929] The server recommends multiple hobbies based on the analysis results. The input is the analysis results of a generating AI model, and the output is a list of hobbies recommended for the user. Specifically, the server organizes the analysis results and selects the hobby best suited to the user.

[0930] Step 6:

[0931] The server generates information on the tools needed to start a recommended hobby. This includes a list of necessary tools, recommended manufacturers, and purchase links. The input is a list of selected hobbies, and the output is data containing tool information. Specifically, the server collects and organizes information on the necessary tools and their details for each hobby.

[0932] Step 7:

[0933] The terminal displays hobby and equipment information received from the server in a visually easy-to-understand user interface. Input includes data returned from the server, and output includes visual information displayed to the user. Specifically, the terminal analyzes the data and displays the information in a user-friendly format.

[0934] Through the above processing steps, users can quickly obtain optimal hobby and equipment information at physical stores.

[0935] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0936] This invention is a system that helps users find the hobby best suited to them and provides them with the necessary information and tools to start that hobby. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, generating and providing tool information, and acquiring emotional data by combining an emotional engine.

[0937] User Interface

[0938] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[0939] question presentation

[0940] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences.

[0941] Receiving response data

[0942] The user answers each question and sends the answers to their device. The answers are sent as structured data, such as in JSON format.

[0943] Acquisition of emotional data

[0944] The device uses an emotion engine to acquire user emotion data. This is done by collecting and analyzing in real time the user's facial expressions, tone of voice, and other emotion indicators as they answer questions.

[0945] Data Analysis

[0946] The server inputs the response data and sentiment data received from the terminal into an artificial intelligence model for analysis. Based on the user's responses and sentiment data, this model identifies hobbies that are likely to be most suitable for the user.

[0947] Hobby Recommendation

[0948] The server recommends multiple hobbies based on the analysis results. The recommended hobbies are optimized by considering not only the user's interests and lifestyle, but also their emotional data, enabling more personalized suggestions.

[0949] Generating tool information

[0950] The server collects and generates information on the tools needed to start a recommended hobby. This information includes a list of necessary tools, recommended manufacturers, and links to purchase them.

[0951] Information provision

[0952] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[0953] Specific example

[0954] For example, when a user starts a hobby assessment and answers "I'd like to exercise actively" to the question "How would you like to spend your holidays?", the emotion engine detects the user's facial expressions and tone of voice. This response data and emotion data are sent to a server and analyzed by an artificial intelligence model. The server suggests hobbies such as "running," "cycling," and "hiking," and generates information on the necessary equipment for each hobby (running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment. This information is then sent to the device, which displays it to the user. If the user selects "running" and clicks on the link to purchase the recommended equipment, they can easily obtain the necessary gear.

[0955] In this way, the present invention is a system that allows users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it. Furthermore, by using an emotion engine, it becomes possible to provide more personalized suggestions that take the user's emotions into account.

[0956] The following describes the processing flow.

[0957] Step 1:

[0958] The user accesses the web application or smartphone application and clicks the button to start the hobby diagnosis.

[0959] Step 2:

[0960] The terminal retrieves the question data from the server.

[0961] Step 3:

[0962] Based on the question data acquired by the device, a series of questions about the user's hobbies are displayed.

[0963] Step 4:

[0964] The user answers each question and sends the answers to their device.

[0965] Step 5:

[0966] The device sends the user's response data to the server.

[0967] Step 6:

[0968] The device activates an emotion engine and analyzes the user's facial expressions and tone of voice in real time as they answer questions. Based on this, emotion data is collected.

[0969] Step 7:

[0970] The device sends the collected emotional data to the server.

[0971] Step 8:

[0972] The server inputs response data and sentiment data into an artificial intelligence model for analysis.

[0973] Step 9:

[0974] The server generates a list of suitable hobbies for the user based on the analysis results.

[0975] Step 10:

[0976] The server generates information about the necessary tools (tool list, recommended manufacturers, purchase links) for each recommended hobby.

[0977] Step 11:

[0978] The server generates a list of hobby recommendations and sends related equipment information to the terminal.

[0979] Step 12:

[0980] The terminal displays information received from the server to the user in a visually easy-to-understand manner.

[0981] Step 13:

[0982] The user reviews the displayed list of hobbies and tools and selects a hobby that interests them.

[0983] Step 14:

[0984] Users can purchase tools by clicking the displayed purchase link as needed.

[0985] Step 15:

[0986] After the user selects a hobby and purchases the necessary equipment, the emotion engine re-analyzes the user's reactions and evaluates their satisfaction level.

[0987] Step 16:

[0988] The server inputs the satisfaction rating results as feedback into the artificial intelligence model, which then uses this data to improve the accuracy of future recommendations.

[0989] (Example 2)

[0990] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0991] In modern society, many people seek stress relief and the discovery of new hobbies, but finding a suitable hobby is not easy. Furthermore, gathering the necessary equipment to start a hobby can be time-consuming. Additionally, existing systems lack personalized recommendations that take user emotions into account. An effective system is needed to address these challenges.

[0992] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0993] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for acquiring the user's emotional data, and means for using the emotional data for analysis. This makes it possible for the user to easily find the hobby that is best suited to them and easily obtain the information and tools needed to start it. Furthermore, by receiving personalized recommendations that take emotional data into consideration, it becomes possible to choose a hobby that is more satisfying.

[0994] 1. A "question presentation means" is a means of providing an interface that displays questions about the user's hobbies and prompts them to answer.

[0995] 2. "Response data receiving means" refers to a means of receiving responses entered by a user and sending the data to a server.

[0996] 3. "Analysis means" refers to a method of performing data analysis based on received response data to identify the user's interests and needs and recommend the most suitable hobbies.

[0997] 4. A "hobby recommendation method" is a method that lists and suggests the most suitable hobbies for a user based on data obtained from analysis methods.

[0998] 5. "Tool information generation means" refers to a means of collecting, listing, and providing information on the tools necessary to start a recommended hobby.

[0999] 6. "Information provision means" refers to means of visually displaying generated tool information and purchase links to users in an easy-to-understand manner.

[1000] 7. "Methods for acquiring emotional data" refer to methods for acquiring and analyzing emotional indicators such as the user's facial expressions and tone of voice.

[1001] 8. "Emotional data analysis means" refers to a means of analyzing acquired emotional data to understand the user's emotional state and reflecting it in recommendations.

[1002] 9. A "generative artificial intelligence model" is an artificial intelligence algorithm designed to learn from large amounts of data and recommend the most suitable hobbies based on user responses.

[1003] 10. A "prompt" is text data consisting of questions or instructions that are input into a generative artificial intelligence model.

[1004] This invention is a system that helps users find the hobby best suited to them and provides them with the necessary information and tools to start that hobby. This system incorporates means for presenting questions to the user, means for receiving response data, means for acquiring emotion data, means for analysis, means for recommending hobbies, means for generating tool information, and means for providing information.

[1005] 1. User Interface

[1006] Users access the system using a dedicated web application or smartphone application. The application includes a button for users to start the hobby diagnosis; clicking this button initiates the diagnostic process. The interface must be simple and visually easy to understand.

[1007] 2. Question presentation

[1008] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. Specifically, questions such as "How would you like to spend your holidays?" might be displayed.

[1009] 3. Receiving response data

[1010] The user answers each question and sends the answers to their device. The answers are sent to the server as structured data, such as in JSON format. For example, if the user answers, "I want to exercise actively on my days off," that data will be sent.

[1011] 4. Acquisition of emotional data

[1012] The device uses an emotion engine (e.g., Amazon Rekognition or Microsoft Azure's emotion analysis API) to acquire user emotion data. This allows for the real-time collection and analysis of the user's facial expressions, tone of voice, and other emotion indicators as they answer questions.

[1013] 5. Data Analysis

[1014] The server inputs the response data and sentiment data sent from the terminal into an artificial intelligence model (e.g., OpenAI's GPT-3 or ChatGPT) for analysis. Based on the response data and sentiment data, this model identifies the most suitable hobby for the user. For example, the response analysis might conclude that "running" is the most suitable hobby.

[1015] 6. Hobby Recommendation

[1016] The server recommends several hobbies based on the analysis results. These recommendations include "running," "cycling," and "hiking," and are optimized considering the user's interests, lifestyle, and emotional data.

[1017] 7. Generating tool information

[1018] The server collects and generates information on the equipment needed to start a recommended hobby. This information includes the type of equipment, recommended manufacturers, and purchase links. For example, equipment such as "running shoes," "cycling bikes," and "hiking boots" may be listed.

[1019] 8. Provision of Information

[1020] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this information and select hobbies and equipment that interest them. For example, by selecting "running" and clicking a link to purchase recommended equipment, they can easily acquire the necessary gear.

[1021] Specific example

[1022] For example, if a user starts a hobby assessment and answers "I'd like to exercise actively" to the question "How would you like to spend your holidays?", the emotion engine analyzes the user's facial expressions and tone of voice. This response data and emotion data are sent to a server, where an artificial intelligence model performs analysis. The server suggests hobbies such as "running," "cycling," and "hiking," and generates information on the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots), as well as manufacturer information and purchase links related to that equipment. This information is sent to the device and displayed to the user. If the user selects "running" and clicks on the link to purchase the recommended equipment, they can easily obtain the necessary gear.

[1023] Example prompt: "What would a 20-year-old university student like to do on their day off?"

[1024] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1025] Step 1:

[1026] System Access

[1027] Users access the system using a dedicated web application or smartphone application.

[1028] Specific actions:

[1029] The user launches the application on their smartphone or computer and logs in. Then, when the user clicks the "Start Hobby Diagnosis" button, the application begins the diagnostic process.

[1030] input:

[1031] User access to the system and button clicks.

[1032] output:

[1033] The diagnostic process begins.

[1034] Step 2:

[1035] question presentation

[1036] The terminal displays a series of questions about the user's hobbies based on question data retrieved from the server.

[1037] Specific actions:

[1038] The device sends a GET request to the server to retrieve the question data. The retrieved data is then analyzed to generate a question form to display to the user.

[1039] input:

[1040] Question data retrieved from the server.

[1041] output:

[1042] A question form displayed to the user. For example, a question like, "How would you like to spend your holidays?"

[1043] Step 3:

[1044] Receiving response data

[1045] The user answers each question and sends the answers to their device.

[1046] Specific actions:

[1047] The user enters their answers into the question form and presses the submit button. The device sends the answer data to the server in JSON format.

[1048] input:

[1049] The user's response entered into the question form.

[1050] output:

[1051] Response data structured in JSON format.

[1052] Step 4:

[1053] Acquisition of emotional data

[1054] The device uses an emotion engine to acquire user emotion data.

[1055] Specific actions:

[1056] The device uses its built-in camera and microphone to monitor the user's facial expressions and voice tone in real time. The collected data is analyzed by an emotion engine to generate emotion data.

[1057] input:

[1058] The user's facial expressions and tone of voice.

[1059] output:

[1060] Analyzed emotion data.

[1061] Step 5:

[1062] Data Analysis

[1063] The server inputs the response data and sentiment data received from the terminal into an artificial intelligence model for analysis. This model uses a generative AI model.

[1064] Specific actions:

[1065] The server receives data sent from the terminal and inputs it into an artificial intelligence model. It then performs analysis to identify the user's most suitable hobbies.

[1066] input:

[1067] Response data and sentiment data received from the device.

[1068] output:

[1069] Identifying the optimal hobby based on the analysis results.

[1070] Step 6:

[1071] Hobby Recommendation

[1072] The server recommends several hobbies based on the analysis results.

[1073] Specific actions:

[1074] The server lists and recommends hobbies derived from the analysis results. For example, hobbies such as "running," "cycling," and "hiking" may be suggested.

[1075] input:

[1076] Results of data analysis.

[1077] output:

[1078] A list of recommended hobbies.

[1079] Step 7:

[1080] Generating tool information

[1081] The server collects and generates information about the tools needed to start the recommended hobby.

[1082] Specific actions:

[1083] The server collects information on the tools needed for each hobby from databases and external APIs. Based on the collected information, it generates a list of necessary tools, recommended manufacturers, and purchase links.

[1084] input:

[1085] A list of recommended hobbies.

[1086] output:

[1087] A list of tool information, recommended manufacturers, and purchase links.

[1088] Step 8:

[1089] Information provision

[1090] The terminal displays hobby and equipment information received from the server in a visually easy-to-understand manner for the user.

[1091] Specific actions:

[1092] The server sends the generated hobby and equipment information to the terminal. The terminal then displays the information visually to the user.

[1093] input:

[1094] Hobby and equipment information received from the server.

[1095] output:

[1096] Information about hobbies and equipment is displayed visually. For example, for "running," equipment such as "running shoes" and "smartwatch" are listed, and corresponding purchase links are displayed.

[1097] (Application Example 2)

[1098] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1099] This invention relates to a system for suggesting optimal hobbies to factory workers, thereby improving their skills and reducing stress. To maintain workers' productivity and mental health, it is necessary to recommend appropriate hobbies based on their individual emotional states and provide information on necessary tools.

[1100] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for presenting questions about hobbies to the user, means for receiving and analyzing the user's response data, means for recommending hobbies that suit the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for providing a hobby suggestion function aimed at improving workers' skills and reducing stress, means for presenting questions and receiving answers using a smart device, means for acquiring and analyzing emotional index data, and means for correcting hobby recommendations using the acquired emotional index data. This makes it possible to suggest hobbies that highly reflect the user's emotions and interests, and to provide the tools and information necessary to start them.

[1101] "Means of presenting users with questions about their hobbies" refers to an interface in which a system presents a series of questions related to a user's hobbies, allowing the user to answer those questions.

[1102] "Means for receiving and analyzing user response data" refers to a function in which the system receives data provided by users, analyzes that data, and identifies the user's interests and tendencies.

[1103] "A means of recommending hobbies that suit the user based on analysis results" refers to a function that selects and proposes hobbies that best fit the user's interests based on the analyzed data.

[1104] "Means for generating information on equipment needed for a recommended hobby" refers to a function that collects and generates information on the equipment needed to start a hobby recommended to the user, and provides that information to the user.

[1105] "Means of providing generated tool information to users" refers to an interface that visually and clearly presents the tool information and purchase links generated by the system to the user.

[1106] "A means of providing a hobby suggestion function aimed at improving workers' skills and reducing stress" refers to a function that suggests the most suitable hobby for each individual worker in order to improve their skills and reduce stress within the factory.

[1107] "Means of presenting questions and receiving answers using smart devices" refers to a function that presents questions to users and receives answers using devices such as smart glasses or smartphones.

[1108] "Means for acquiring and analyzing emotional indicator data" refers to a function that analyzes emotions from a user's facial expressions, tone of voice, etc., and collects that data.

[1109] "Means for correcting hobby recommendations using acquired emotional indicator data" refers to a function that incorporates acquired emotional data into the analysis results to recommend the most suitable hobby to the user.

[1110] This invention is a system designed to suggest optimal hobbies to factory workers, aiming to improve their skills and reduce stress through those hobbies. The system uses smart devices to present questions, analyzes the response data and emotional indicator data, and then recommends the most suitable hobby for the worker, providing information on the necessary tools to begin that hobby.

[1111] Hardware and software to be used

[1112] Hardware:

[1113] Smart devices (e.g., smart glasses, smartphones)

[1114] software:

[1115] Flask (Web application framework)

[1116] EmotionEngine (an engine for analyzing facial expressions and voice)

[1117] HobbyRecommendationModel (AI model for hobby recommendations)

[1118] System Configuration

[1119] 1. The terminal uses a smart device to present questions to the user and receive answers. The questions are in the form of multiple choices related to hobbies.

[1120] 2. The terminal sends the user's response data to the question to the server as structured data, such as in JSON format.

[1121] 3. When the user answers a question, the device uses EmotionEngine to acquire emotional data such as the user's facial expressions and tone of voice in real time and analyze it.

[1122] 4. The server inputs the received response data and sentiment data into the HobbyRecommendationModel, and analyzes and identifies the most suitable hobby based on this data.

[1123] 5. Based on the analysis results, the server recommends multiple hobbies and also generates information on the tools needed to start each hobby (e.g., a list of tools, recommended manufacturers, and purchase links).

[1124] 6. The terminal visually displays hobby recommendations and equipment information received from the server to the user. The user can review this information and select hobbies and equipment that interest them.

[1125] Specific example

[1126] For example, when a factory worker puts on smart glasses and starts a hobby assessment, the question "How would you like to spend your days off?" appears on the glasses' screen. If the worker answers "I want to relax," the EmotionEngine then obtains the user's emotional data from their facial expressions and tone of voice. This response data and emotional data are sent to a server and analyzed by the HobbyRecommendationModel. The server suggests hobbies such as "yoga," "meditation," and "reading," and generates and provides information on the necessary equipment for each hobby (e.g., yoga mat, meditation cushion, reading light) and purchase links.

[1127] Example of a prompt

[1128] User response: "I want to relax."

[1129] Emotional data: High stress level, low excitement level

[1130] Recommended hobbies: "Yoga," "Meditation," "Reading"

[1131] Required equipment: "Yoga mat, meditation cushion, reading light"

[1132] In this way, the present invention is a system that enables factory workers to easily find suitable hobbies and readily obtain information and tools to improve their skills and reduce stress.

[1133] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1134] Step 1:

[1135] The device presents the user with questions about their hobbies. When the user answers a question, the device receives the answer data. The input is the answer selected or entered by the user on the screen, and the output is the answer data (in JSON format, etc.).

[1136] Step 2:

[1137] The device uses EmotionEngine to acquire user emotion data. It collects real-time information such as the user's facial expressions and tone of voice when they answer questions. The input is the user's video and audio data, and the output is the analyzed emotion data.

[1138] Step 3:

[1139] The terminal sends response data and sentiment data to the server. The input is response data and sentiment data, and the output is the transmission of data to the server.

[1140] Step 4:

[1141] The server inputs the received response data and sentiment data into the HobbyRecommendationModel. The input is the received data, which is then analyzed by the HobbyRecommendationModel. The output is hobby recommendation data as a result of the analysis.

[1142] Step 5:

[1143] The server recommends multiple hobbies based on the analysis results and generates information on the necessary tools for each. The input is hobby recommendation data, and the output is tool information (list, manufacturer information, purchase links).

[1144] Step 6:

[1145] The server sends the generated hobby recommendation and equipment information from the server to the terminal. The input is the generated hobby recommendation data and equipment information, and the output is the transmission of data to the terminal.

[1146] Step 7:

[1147] The terminal visually displays received hobby recommendations and equipment information to the user. Input is data received from the server, and output is the display on the user interface.

[1148] Step 8:

[1149] The user reviews the displayed recommended hobbies and equipment information and selects the hobbies and equipment that interest them. The input is the information displayed on the terminal, and the output is the user's selection.

[1150] Specific example

[1151] For example, a user using smart glasses answers the question "How would you like to spend your holidays?" with "I want to relax" (Step 1). EmotionEngine analyzes the user's facial expressions and tone of voice and obtains emotional data indicating a high stress level (Step 2). The device sends this response data and emotional data to the server (Step 3). The server inputs the data into HobbyRecommendationModel, which analyzes and identifies the most suitable hobby for the user (Step 4). Based on the analysis results, it recommends hobbies such as "yoga," "meditation," and "reading," and generates information on the necessary equipment for each hobby (yoga mat, meditation cushion, reading light) (Step 5). This information is sent to the device (Step 6). The device displays the hobby recommendations and equipment information to the user (Step 7). Finally, the user selects the hobby and equipment that interests them most (Step 8).

[1152] Example of a prompt:

[1153] User response: "I want to relax."

[1154] Emotional data: High stress level, low excitement level

[1155] Recommended hobbies: "Yoga," "Meditation," "Reading"

[1156] Required equipment: "Yoga mat, meditation cushion, reading light"

[1157] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1158] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1159] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1160] [Fourth Embodiment]

[1161] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1162] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1163] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1164] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1165] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1166] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1167] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1168] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1169] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1170] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1171] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1172] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1173] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1174] This invention is a system that provides users with the necessary information and tools to find a hobby that suits them and to start it. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, and generating and providing tool information.

[1175] User Interface

[1176] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[1177] question presentation

[1178] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences.

[1179] Receiving response data

[1180] The user answers each question and sends the answers to their device. The answers are sent as structured data, such as in JSON format.

[1181] Data Analysis

[1182] The server uses a pre-trained artificial intelligence model to analyze the response data received from the terminal. Based on the user's responses, this model identifies hobbies that are likely to be most suitable for the user.

[1183] Hobby Recommendation

[1184] The server recommends several hobbies based on the analysis results. The recommended hobbies are suggested as being best suited to the user's interests and lifestyle.

[1185] Generating tool information

[1186] The server collects and generates information on the tools needed to start a recommended hobby. This information includes a list of necessary tools, recommended manufacturers, and links to purchase them.

[1187] Information provision

[1188] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[1189] Specific example

[1190] For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this response data is sent to the server. The server inputs this data into an artificial intelligence model and suggests "running," "cycling," and "hiking" as optimal hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information related to that equipment (e.g., Nike, Garmin) and purchase links.

[1191] In this way, the present invention is a system that enables users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it.

[1192] The following describes the processing flow.

[1193] Step 1:

[1194] The user accesses the web application or smartphone application and clicks the button to start the hobby diagnosis.

[1195] Step 2:

[1196] The terminal retrieves the question data from the server.

[1197] Step 3:

[1198] Based on the question data acquired by the device, a series of questions about the user's hobbies are displayed.

[1199] Step 4:

[1200] The user answers each question and sends the answers to their device.

[1201] Step 5:

[1202] The device sends the user's response data to the server.

[1203] Step 6:

[1204] The server inputs the received response data into an artificial intelligence model for analysis.

[1205] Step 7:

[1206] The server generates a list of suitable hobbies for the user based on the analysis results of the artificial intelligence model.

[1207] Step 8:

[1208] The server generates information about the necessary tools for each recommended hobby (specific tool lists, recommended manufacturers, and purchase links).

[1209] Step 9:

[1210] The server generates a list of hobby recommendations and sends related equipment information to the terminal.

[1211] Step 10:

[1212] The terminal displays information received from the server to the user and provides options.

[1213] Step 11:

[1214] The user reviews the displayed list of hobbies and tools and selects a hobby that interests them.

[1215] Step 12:

[1216] Users can purchase tools by clicking the displayed purchase link as needed.

[1217] (Example 1)

[1218] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1219] In modern society, finding a hobby is an important element in improving the quality of life, but finding the right hobby is not easy. In our busy daily lives, it is difficult to find a hobby that is best suited to our individual interests and lifestyles, and to acquire the necessary tools and information all in one place. To solve this problem, there is a need for a system that recommends the most suitable hobby based on the user's preferences and lifestyle, and provides the necessary tools and information quickly and accurately.

[1220] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1221] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for conducting questions and answers via a user interface, means for transmitting the user's responses as structured data, and means for displaying detailed information about the recommended hobbies. This makes it possible for the user to easily find the hobby that is best suited to them and obtain all the necessary information and tools to start it in one place.

[1222] "User" refers to an individual who uses this system.

[1223] A "server" refers to a central processing unit that processes requests from users and performs data analysis and provides information.

[1224] A "terminal" refers to a device, such as a computer or smartphone, that a user uses to access this system.

[1225] "Means of presenting questions related to hobbies" refers to a function that displays questions in order to understand the user's preferences and lifestyle.

[1226] "Means for receiving and analyzing response data" refers to the function of a system that receives and analyzes response data collected from users.

[1227] "Methods for recommending hobbies based on analysis results" refers to a function that suggests the most suitable hobbies to the user based on analyzed data.

[1228] "Means for generating tool information" refers to a function that collects information on the tools necessary to start a recommended hobby and compiles it into a list.

[1229] "Means of providing generated tool information" refers to a function that displays or notifies the user of the generated tool information.

[1230] "User interface" refers to a screen layout that includes visual and operational elements for a user to interact with a system.

[1231] "Structured data" refers to data that is organized according to a specific format and prepared in a way that makes it easy to handle in databases, spreadsheets, and other similar applications.

[1232] An "artificial intelligence model" refers to a program that uses machine learning algorithms to analyze data and recommend the most suitable hobbies to users.

[1233] "Means of displaying detailed information" refers to a function that displays additional information about recommended hobbies to the user.

[1234] "Manufacturer information" refers to information about companies that manufacture tools.

[1235] A "purchase link" refers to a link to a webpage where the tool can be purchased.

[1236] This invention relates to a system that provides users with the necessary information and tools to find a hobby that suits them and to start it. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, and generating and providing tool information.

[1237] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[1238] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. The user answers each question and sends the responses to the device. The answers are sent as structured data, such as in JSON format.

[1239] The server uses a pre-trained generative AI model to analyze the response data received from the terminal. This model is built, for example, using the TensorFlow library in Python. Based on the user's responses, the model identifies hobbies that are likely to be most suitable for the user.

[1240] Based on the analysis results, the server recommends several hobbies. These recommended hobbies are suggested as being best suited to the user's interests and lifestyle. Furthermore, the server collects and generates information on the equipment needed to start the recommended hobbies. This includes a list of necessary equipment, recommended manufacturers, and purchase links.

[1241] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most. For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this answer data is sent to the server. The server inputs this data into an artificial intelligence model and suggests "running," "cycling," and "hiking" as the most suitable hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment.

[1242] Examples of prompts for a generative AI model include the following:

[1243] "Please recommend the most suitable hobby based on the user's response data. The data is as follows: 'How would you like to spend your free time?': 'Actively exercise.'"

[1244] In this way, the present invention is a system that enables users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it.

[1245] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1246] Step 1: Accessing the System

[1247] The user launches a browser or smartphone app, and the login screen is displayed. The user enters their username and password to log in. For new users, they enter the required information on the sign-up screen to create an account. This is the initial step to accessing the system. The input requires login information, and the output is a state where the user can access the system.

[1248] Step 2: Start the hobby assessment

[1249] The user clicks the "Start Hobby Diagnosis" button on the home screen. This action sends an API call to the server requesting diagnostic questions. The server returns pre-stored question data to the device. The input is the user's click operation, and the output is the question data sent to the device.

[1250] Step 3: Presenting the Question

[1251] The terminal retrieves question data from the server and displays questions in an interactive format on the user interface. For example, a question like "How would you like to spend your holidays?" might be displayed. The user can answer by selecting the appropriate option or by typing a free response. The input is question data from the server, and the output is the question displayed on the user interface.

[1252] Step 4: Submit your response data

[1253] Once the user has finished answering all the questions, the device converts these answers into JSON format. For example, {"question1": "I exercise actively", "question2": "I like nature"}. This data is then sent to the server. The input is the user's answer data, and the output is structured JSON data sent to the server.

[1254] Step 5: Data Analysis

[1255] The server analyzes the JSON-formatted response data it receives. This analysis uses an AI model powered by a GPU (for example, one using the TensorFlow library in Python). The input is the response data in JSON format, and the AI ​​model performs the data processing and calculations. The output is the analysis results.

[1256] Step 6: Recommend a hobby

[1257] The server selects several hobbies that it deems most suitable for the user based on the analysis results returned by the AI ​​model. For example, hobbies such as "running," "cycling," and "hiking" might be selected. This list is then sent to the terminal. The input is the analysis results from the AI ​​model, and the output is a list of recommended hobbies.

[1258] Step 7: Tool Information Generation

[1259] The server collects information on the necessary equipment for each recommended hobby. It generates a list of the equipment needed for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with recommended manufacturers and purchase links. The input is a list of recommended hobbies, and the output is a list of equipment information.

[1260] Step 8: Displaying Information

[1261] The terminal displays information about hobbies and equipment sent from the server in the user interface. The user reviews the detailed information about the displayed hobbies and related equipment and selects the hobby that interests them most. The selection is saved in the user profile. The input is the information about hobbies and equipment from the server, and the output is the information displayed in the user interface.

[1262] This process allows users to easily find the perfect hobby for them and obtain the necessary information and tools to get started.

[1263] (Application Example 1)

[1264] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1265] Traditional hobby recommendation systems were only accessible to users through web or smartphone applications and were not designed for use in physical stores. Therefore, it was difficult to provide users with immediate hobby-related information in stores and enable them to make quick purchase decisions. Furthermore, the delay in fulfilling users' interest in hobbies could potentially lead to a loss of purchasing intent.

[1266] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1267] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for presenting questions to the user and inputting answers through a terminal installed in a physical store, means for transmitting the input response data to the server, and means for visually displaying the recommendations and tool information returned from the server. This makes it possible to quickly provide users with information on hobbies and necessary tools even in physical stores.

[1268] A "user" refers to a person who uses the system to receive hobby-related assessments and information about equipment.

[1269] "Hobbies" refer to activities and pursuits recommended based on the user's interests and lifestyle.

[1270] "Means of presenting questions" refers to methods or devices for displaying questions related to a user's hobbies.

[1271] "Means for receiving and analyzing response data" refers to methods and devices for receiving user responses and analyzing that data.

[1272] "Means of recommending hobbies that suit the user based on analysis results" refers to methods and devices that use analysis results to suggest hobbies that are suitable for the user.

[1273] "Means for generating tool information" refers to methods and devices for collecting and organizing information about the tools necessary for a recommended hobby.

[1274] "Means of providing tool information to the user" refers to methods or devices for displaying generated tool information to the user.

[1275] "Terminals installed in physical stores" refers to devices installed within physical stores that users can access and use.

[1276] A "server" refers to a central computer system that receives and analyzes user response data.

[1277] "Means of visual display" refers to methods and devices for displaying information in a way that can be seen by the user.

[1278] This invention is a system that recommends the most suitable hobby to a user and provides information on the necessary equipment through a terminal installed in a physical store. Specific embodiments for carrying out this invention are described below.

[1279] User Interface

[1280] This time, we will use tablet devices installed in physical stores. The diagnostic process starts when the user accesses the device and clicks a button to begin the hobby diagnosis. The interface must be intuitive and visually clear. For example, colorful buttons and visually appealing icons should be used.

[1281] question presentation

[1282] Terminals installed in physical stores display a series of questions about the user's hobbies, based on question data retrieved from a server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. Users answer the questions displayed on the tablet and input their answers.

[1283] Receiving response data

[1284] The terminal receives the user's response and sends that data to the server as structured data, such as in JSON format.

[1285] Data Analysis

[1286] The server uses a pre-trained generative AI model to analyze the response data received from the terminal. This model identifies hobbies that are likely to be most suitable for the user based on their responses. Specifically, the generative AI model processes the data and selects several hobbies that best match the user's interests.

[1287] Hobby Recommendation

[1288] The server recommends several hobbies based on the analysis results. The recommended hobbies are suggested as being best suited to the user's interests and lifestyle.

[1289] Generating tool information

[1290] The server collects and generates information on the equipment needed to start a recommended hobby. This information includes a list of necessary equipment, recommended manufacturers, and purchase links. For example, it might provide information on running shoes, cycling bikes, hiking boots, etc.

[1291] Information provision

[1292] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[1293] Specific example

[1294] For example, if a user starts a hobby assessment and answers "I want to exercise actively" to the question "How would you like to spend your holidays?", this response data is sent to the server. The server inputs this data into a generating AI model and suggests "running," "cycling," and "hiking" as optimal hobbies. It then provides the user with the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment.

[1295] Example of a prompt:

[1296] "{'user_profile': {'interests': 'exercise', 'lifestyle': 'active'}, 'questions': [{'id': 1, 'answer': 'How do you like to spend your holidays?: Exercise actively'}, ...]}"

[1297] The above describes a specific embodiment for carrying out the present invention. With this system, users can quickly obtain information on the most suitable hobbies and equipment, even in physical stores.

[1298] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1299] Step 1:

[1300] The user accesses a terminal installed in a physical store and clicks a button to start the hobby diagnosis. The terminal then retrieves hobby-related question data from a server and displays it on the user interface. The input is the user clicking a button, and the output is the question data displayed on the user interface.

[1301] Step 2:

[1302] The user answers questions displayed on their device. For example, to the question "How would you like to spend your holidays?", the user might answer "I would like to exercise actively." The input is the user's answer, which is stored on the device as structured data in JSON format. The output is the answer data, which is prepared to be sent to the server later.

[1303] Step 3:

[1304] The terminal sends the user's response data to the server. The user's response data is sent to the server in JSON format. The input is the response data stored on the terminal, and the output is the data that will be sent to the server.

[1305] Step 4:

[1306] The server inputs the received response data into a generating AI model for data analysis. The input consists of user responses, which the generating AI model uses for analysis. The data calculation analyzes the user's interests and lifestyle, and then selects hobbies based on this analysis. The output is a list of recommended hobbies.

[1307] Step 5:

[1308] The server recommends multiple hobbies based on the analysis results. The input is the analysis results of a generating AI model, and the output is a list of hobbies recommended for the user. Specifically, the server organizes the analysis results and selects the hobby best suited to the user.

[1309] Step 6:

[1310] The server generates information on the tools needed to start a recommended hobby. This includes a list of necessary tools, recommended manufacturers, and purchase links. The input is a list of selected hobbies, and the output is data containing tool information. Specifically, the server collects and organizes information on the necessary tools and their details for each hobby.

[1311] Step 7:

[1312] The terminal displays hobby and equipment information received from the server in a visually easy-to-understand user interface. Input includes data returned from the server, and output includes visual information displayed to the user. Specifically, the terminal analyzes the data and displays the information in a user-friendly format.

[1313] Through the above processing steps, users can quickly obtain optimal hobby and equipment information at physical stores.

[1314] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1315] This invention is a system that helps users find the hobby best suited to them and provides them with the necessary information and tools to start that hobby. This system includes means for presenting questions to the user, receiving and analyzing response data, recommending hobbies, generating and providing tool information, and acquiring emotional data by combining an emotional engine.

[1316] User Interface

[1317] Users access the system using a dedicated web application or smartphone application. The diagnostic process begins when the user clicks a button to start the hobby assessment. The interface must be user-friendly and visually clear.

[1318] question presentation

[1319] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences.

[1320] Receiving response data

[1321] The user answers each question and sends the answers to their device. The answers are sent as structured data, such as in JSON format.

[1322] Acquisition of emotional data

[1323] The device uses an emotion engine to acquire user emotion data. This is done by collecting and analyzing in real time the user's facial expressions, tone of voice, and other emotion indicators as they answer questions.

[1324] Data Analysis

[1325] The server inputs the response data and sentiment data received from the terminal into an artificial intelligence model for analysis. Based on the user's responses and sentiment data, this model identifies hobbies that are likely to be most suitable for the user.

[1326] Hobby Recommendation

[1327] The server recommends multiple hobbies based on the analysis results. The recommended hobbies are optimized by considering not only the user's interests and lifestyle, but also their emotional data, enabling more personalized suggestions.

[1328] Generating tool information

[1329] The server collects and generates information on the tools needed to start a recommended hobby. This information includes a list of necessary tools, recommended manufacturers, and links to purchase them.

[1330] Information provision

[1331] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this display and select the hobby and equipment that interests them most.

[1332] Specific example

[1333] For example, when a user starts a hobby assessment and answers "I'd like to exercise actively" to the question "How would you like to spend your holidays?", the emotion engine detects the user's facial expressions and tone of voice. This response data and emotion data are sent to a server and analyzed by an artificial intelligence model. The server suggests hobbies such as "running," "cycling," and "hiking," and generates information on the necessary equipment for each hobby (running shoes, cycling bikes, hiking boots, etc.), along with manufacturer information and purchase links related to that equipment. This information is then sent to the device, which displays it to the user. If the user selects "running" and clicks on the link to purchase the recommended equipment, they can easily obtain the necessary gear.

[1334] In this way, the present invention is a system that allows users to easily find the hobby that is best suited to them and obtain the information and tools necessary to start it. Furthermore, by using an emotion engine, it becomes possible to provide more personalized suggestions that take the user's emotions into account.

[1335] The following describes the processing flow.

[1336] Step 1:

[1337] The user accesses the web application or smartphone application and clicks the button to start the hobby diagnosis.

[1338] Step 2:

[1339] The terminal retrieves the question data from the server.

[1340] Step 3:

[1341] Based on the question data acquired by the device, a series of questions about the user's hobbies are displayed.

[1342] Step 4:

[1343] The user answers each question and sends the answers to their device.

[1344] Step 5:

[1345] The device sends the user's response data to the server.

[1346] Step 6:

[1347] The device activates an emotion engine and analyzes the user's facial expressions and tone of voice in real time as they answer questions. Based on this, emotion data is collected.

[1348] Step 7:

[1349] The device sends the collected emotional data to the server.

[1350] Step 8:

[1351] The server inputs response data and sentiment data into an artificial intelligence model for analysis.

[1352] Step 9:

[1353] The server generates a list of suitable hobbies for the user based on the analysis results.

[1354] Step 10:

[1355] The server generates information about the necessary tools (tool list, recommended manufacturers, purchase links) for each recommended hobby.

[1356] Step 11:

[1357] The server generates a list of hobby recommendations and sends related equipment information to the terminal.

[1358] Step 12:

[1359] The terminal displays information received from the server to the user in a visually easy-to-understand manner.

[1360] Step 13:

[1361] The user reviews the displayed list of hobbies and tools and selects a hobby that interests them.

[1362] Step 14:

[1363] Users can purchase tools by clicking the displayed purchase link as needed.

[1364] Step 15:

[1365] After the user selects a hobby and purchases the necessary equipment, the emotion engine re-analyzes the user's reactions and evaluates their satisfaction level.

[1366] Step 16:

[1367] The server inputs the satisfaction rating results as feedback into the artificial intelligence model, which then uses this data to improve the accuracy of future recommendations.

[1368] (Example 2)

[1369] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1370] In modern society, many people seek stress relief and the discovery of new hobbies, but finding a suitable hobby is not easy. Furthermore, gathering the necessary equipment to start a hobby can be time-consuming. Additionally, existing systems lack personalized recommendations that take user emotions into account. An effective system is needed to address these challenges.

[1371] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1372] In this invention, the server includes means for presenting questions to the user about their hobbies, means for receiving and analyzing the user's response data, means for recommending hobbies suitable for the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for acquiring the user's emotional data, and means for using the emotional data for analysis. This makes it possible for the user to easily find the hobby that is best suited to them and easily obtain the information and tools needed to start it. Furthermore, by receiving personalized recommendations that take emotional data into consideration, it becomes possible to choose a hobby that is more satisfying.

[1373] 1. A "question presentation means" is a means of providing an interface that displays questions about the user's hobbies and prompts them to answer.

[1374] 2. "Response data receiving means" refers to a means of receiving responses entered by a user and sending the data to a server.

[1375] 3. "Analysis means" refers to a method of performing data analysis based on received response data to identify the user's interests and needs and recommend the most suitable hobbies.

[1376] 4. A "hobby recommendation method" is a method that lists and suggests the most suitable hobbies for a user based on data obtained from analysis methods.

[1377] 5. "Tool information generation means" refers to a means of collecting, listing, and providing information on the tools necessary to start a recommended hobby.

[1378] 6. "Information provision means" refers to means of visually displaying generated tool information and purchase links to users in an easy-to-understand manner.

[1379] 7. "Methods for acquiring emotional data" refer to methods for acquiring and analyzing emotional indicators such as the user's facial expressions and tone of voice.

[1380] 8. "Emotional data analysis means" refers to a means of analyzing acquired emotional data to understand the user's emotional state and reflecting it in recommendations.

[1381] 9. A "generative artificial intelligence model" is an artificial intelligence algorithm designed to learn from large amounts of data and recommend the most suitable hobbies based on user responses.

[1382] 10. A "prompt" is text data consisting of questions or instructions that are input into a generative artificial intelligence model.

[1383] This invention is a system that helps users find the hobby best suited to them and provides them with the necessary information and tools to start that hobby. This system incorporates means for presenting questions to the user, means for receiving response data, means for acquiring emotion data, means for analysis, means for recommending hobbies, means for generating tool information, and means for providing information.

[1384] 1. User Interface

[1385] Users access the system using a dedicated web application or smartphone application. The application includes a button for users to start the hobby diagnosis; clicking this button initiates the diagnostic process. The interface must be simple and visually easy to understand.

[1386] 2. Question presentation

[1387] The device displays a series of questions about the user's hobbies based on question data retrieved from the server. The questions cover a wide range of topics, including the user's interests, current lifestyle, and desired experiences. Specifically, questions such as "How would you like to spend your holidays?" might be displayed.

[1388] 3. Receiving response data

[1389] The user answers each question and sends the answers to their device. The answers are sent to the server as structured data, such as in JSON format. For example, if the user answers, "I want to exercise actively on my days off," that data will be sent.

[1390] 4. Acquisition of emotional data

[1391] The device uses an emotion engine (e.g., Amazon Rekognition or Microsoft Azure's emotion analysis API) to acquire user emotion data. This allows for the real-time collection and analysis of the user's facial expressions, tone of voice, and other emotion indicators as they answer questions.

[1392] 5. Data Analysis

[1393] The server inputs the response data and sentiment data sent from the terminal into an artificial intelligence model (e.g., OpenAI's GPT-3 or ChatGPT) for analysis. Based on the response data and sentiment data, this model identifies the most suitable hobby for the user. For example, the response analysis might conclude that "running" is the most suitable hobby.

[1394] 6. Hobby Recommendation

[1395] The server recommends several hobbies based on the analysis results. These recommendations include "running," "cycling," and "hiking," and are optimized considering the user's interests, lifestyle, and emotional data.

[1396] 7. Generating tool information

[1397] The server collects and generates information on the equipment needed to start a recommended hobby. This information includes the type of equipment, recommended manufacturers, and purchase links. For example, equipment such as "running shoes," "cycling bikes," and "hiking boots" may be listed.

[1398] 8. Provision of Information

[1399] The terminal displays hobby and equipment information received from the server in an easy-to-understand visual format for the user. The user can review this information and select hobbies and equipment that interest them. For example, by selecting "running" and clicking a link to purchase recommended equipment, they can easily acquire the necessary gear.

[1400] Specific example

[1401] For example, if a user starts a hobby assessment and answers "I'd like to exercise actively" to the question "How would you like to spend your holidays?", the emotion engine analyzes the user's facial expressions and tone of voice. This response data and emotion data are sent to a server, where an artificial intelligence model performs analysis. The server suggests hobbies such as "running," "cycling," and "hiking," and generates information on the necessary equipment for each hobby (e.g., running shoes, cycling bikes, hiking boots), as well as manufacturer information and purchase links related to that equipment. This information is sent to the device and displayed to the user. If the user selects "running" and clicks on the link to purchase the recommended equipment, they can easily obtain the necessary gear.

[1402] Example prompt: "What would a 20-year-old university student like to do on their day off?"

[1403] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1404] Step 1:

[1405] System Access

[1406] Users access the system using a dedicated web application or smartphone application.

[1407] Specific actions:

[1408] The user launches the application on their smartphone or computer and logs in. Then, when the user clicks the "Start Hobby Diagnosis" button, the application begins the diagnostic process.

[1409] input:

[1410] User access to the system and button clicks.

[1411] output:

[1412] The diagnostic process begins.

[1413] Step 2:

[1414] question presentation

[1415] The terminal displays a series of questions about the user's hobbies based on question data retrieved from the server.

[1416] Specific actions:

[1417] The device sends a GET request to the server to retrieve the question data. The retrieved data is then analyzed to generate a question form to display to the user.

[1418] input:

[1419] Question data retrieved from the server.

[1420] output:

[1421] A question form displayed to the user. For example, a question like, "How would you like to spend your holidays?"

[1422] Step 3:

[1423] Receiving response data

[1424] The user answers each question and sends the answers to their device.

[1425] Specific actions:

[1426] The user enters their answers into the question form and presses the submit button. The device sends the answer data to the server in JSON format.

[1427] input:

[1428] The user's response entered into the question form.

[1429] output:

[1430] Response data structured in JSON format.

[1431] Step 4:

[1432] Acquisition of emotional data

[1433] The device uses an emotion engine to acquire user emotion data.

[1434] Specific actions:

[1435] The device uses its built-in camera and microphone to monitor the user's facial expressions and voice tone in real time. The collected data is analyzed by an emotion engine to generate emotion data.

[1436] input:

[1437] The user's facial expressions and tone of voice.

[1438] output:

[1439] Analyzed emotion data.

[1440] Step 5:

[1441] Data Analysis

[1442] The server inputs the response data and sentiment data received from the terminal into an artificial intelligence model for analysis. This model uses a generative AI model.

[1443] Specific actions:

[1444] The server receives data sent from the terminal and inputs it into an artificial intelligence model. It then performs analysis to identify the user's most suitable hobbies.

[1445] input:

[1446] Response data and sentiment data received from the device.

[1447] output:

[1448] Identifying the optimal hobby based on the analysis results.

[1449] Step 6:

[1450] Hobby Recommendation

[1451] The server recommends several hobbies based on the analysis results.

[1452] Specific actions:

[1453] The server lists and recommends hobbies derived from the analysis results. For example, hobbies such as "running," "cycling," and "hiking" may be suggested.

[1454] input:

[1455] Results of data analysis.

[1456] output:

[1457] A list of recommended hobbies.

[1458] Step 7:

[1459] Generating tool information

[1460] The server collects and generates information about the tools needed to start the recommended hobby.

[1461] Specific actions:

[1462] The server collects information on the tools needed for each hobby from databases and external APIs. Based on the collected information, it generates a list of necessary tools, recommended manufacturers, and purchase links.

[1463] input:

[1464] A list of recommended hobbies.

[1465] output:

[1466] A list of tool information, recommended manufacturers, and purchase links.

[1467] Step 8:

[1468] Information provision

[1469] The terminal displays hobby and equipment information received from the server in a visually easy-to-understand manner for the user.

[1470] Specific actions:

[1471] The server sends the generated hobby and equipment information to the terminal. The terminal then displays the information visually to the user.

[1472] input:

[1473] Hobby and equipment information received from the server.

[1474] output:

[1475] Information about hobbies and equipment is displayed visually. For example, for "running," equipment such as "running shoes" and "smartwatch" are listed, and corresponding purchase links are displayed.

[1476] (Application Example 2)

[1477] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1478] This invention relates to a system for suggesting optimal hobbies to factory workers, thereby improving their skills and reducing stress. To maintain workers' productivity and mental health, it is necessary to recommend appropriate hobbies based on their individual emotional states and provide information on necessary tools.

[1479] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for presenting questions about hobbies to the user, means for receiving and analyzing the user's response data, means for recommending hobbies that suit the user based on the analysis results, means for generating information on the tools necessary for the recommended hobbies, means for providing the generated tool information to the user, means for providing a hobby suggestion function aimed at improving workers' skills and reducing stress, means for presenting questions and receiving answers using a smart device, means for acquiring and analyzing emotional index data, and means for correcting hobby recommendations using the acquired emotional index data. This makes it possible to suggest hobbies that highly reflect the user's emotions and interests, and to provide the tools and information necessary to start them.

[1480] "Means of presenting users with questions about their hobbies" refers to an interface in which a system presents a series of questions related to a user's hobbies, allowing the user to answer those questions.

[1481] "Means for receiving and analyzing user response data" refers to a function in which the system receives data provided by users, analyzes that data, and identifies the user's interests and tendencies.

[1482] "A means of recommending hobbies that suit the user based on analysis results" refers to a function that selects and proposes hobbies that best fit the user's interests based on the analyzed data.

[1483] "Means for generating information on equipment needed for a recommended hobby" refers to a function that collects and generates information on the equipment needed to start a hobby recommended to the user, and provides that information to the user.

[1484] "Means of providing generated tool information to users" refers to an interface that visually and clearly presents the tool information and purchase links generated by the system to the user.

[1485] "A means of providing a hobby suggestion function aimed at improving workers' skills and reducing stress" refers to a function that suggests the most suitable hobby for each individual worker in order to improve their skills and reduce stress within the factory.

[1486] "Means of presenting questions and receiving answers using smart devices" refers to a function that presents questions to users and receives answers using devices such as smart glasses or smartphones.

[1487] "Means for acquiring and analyzing emotional indicator data" refers to a function that analyzes emotions from a user's facial expressions, tone of voice, etc., and collects that data.

[1488] "Means for correcting hobby recommendations using acquired emotional indicator data" refers to a function that incorporates acquired emotional data into the analysis results to recommend the most suitable hobby to the user.

[1489] This invention is a system designed to suggest optimal hobbies to factory workers, aiming to improve their skills and reduce stress through those hobbies. The system uses smart devices to present questions, analyzes the response data and emotional indicator data, and then recommends the most suitable hobby for the worker, providing information on the necessary tools to begin that hobby.

[1490] Hardware and software to be used

[1491] Hardware:

[1492] Smart devices (e.g., smart glasses, smartphones)

[1493] software:

[1494] Flask (Web application framework)

[1495] EmotionEngine (an engine for analyzing facial expressions and voice)

[1496] HobbyRecommendationModel (AI model for hobby recommendations)

[1497] System Configuration

[1498] 1. The terminal uses a smart device to present questions to the user and receive answers. The questions are in the form of multiple choices related to hobbies.

[1499] 2. The terminal sends the user's response data to the question to the server as structured data, such as in JSON format.

[1500] 3. When the user answers a question, the device uses EmotionEngine to acquire emotional data such as the user's facial expressions and tone of voice in real time and analyze it.

[1501] 4. The server inputs the received response data and sentiment data into the HobbyRecommendationModel, and analyzes and identifies the most suitable hobby based on this data.

[1502] 5. Based on the analysis results, the server recommends multiple hobbies and also generates information on the tools needed to start each hobby (e.g., a list of tools, recommended manufacturers, and purchase links).

[1503] 6. The terminal visually displays hobby recommendations and equipment information received from the server to the user. The user can review this information and select hobbies and equipment that interest them.

[1504] Specific example

[1505] For example, when a factory worker puts on smart glasses and starts a hobby assessment, the question "How would you like to spend your days off?" appears on the glasses' screen. If the worker answers "I want to relax," the EmotionEngine then obtains the user's emotional data from their facial expressions and tone of voice. This response data and emotional data are sent to a server and analyzed by the HobbyRecommendationModel. The server suggests hobbies such as "yoga," "meditation," and "reading," and generates and provides information on the necessary equipment for each hobby (e.g., yoga mat, meditation cushion, reading light) and purchase links.

[1506] Example of a prompt

[1507] User response: "I want to relax."

[1508] Emotional data: High stress level, low excitement level

[1509] Recommended hobbies: "Yoga," "Meditation," "Reading"

[1510] Required equipment: "Yoga mat, meditation cushion, reading light"

[1511] In this way, the present invention is a system that enables factory workers to easily find suitable hobbies and readily obtain information and tools to improve their skills and reduce stress.

[1512] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1513] Step 1:

[1514] The device presents the user with questions about their hobbies. When the user answers a question, the device receives the answer data. The input is the answer selected or entered by the user on the screen, and the output is the answer data (in JSON format, etc.).

[1515] Step 2:

[1516] The device uses EmotionEngine to acquire user emotion data. It collects real-time information such as the user's facial expressions and tone of voice when they answer questions. The input is the user's video and audio data, and the output is the analyzed emotion data.

[1517] Step 3:

[1518] The terminal sends response data and sentiment data to the server. The input is response data and sentiment data, and the output is the transmission of data to the server.

[1519] Step 4:

[1520] The server inputs the received response data and sentiment data into the HobbyRecommendationModel. The input is the received data, which is then analyzed by the HobbyRecommendationModel. The output is hobby recommendation data as a result of the analysis.

[1521] Step 5:

[1522] The server recommends multiple hobbies based on the analysis results and generates information on the necessary tools for each. The input is hobby recommendation data, and the output is tool information (list, manufacturer information, purchase links).

[1523] Step 6:

[1524] The server sends the generated hobby recommendation and equipment information from the server to the terminal. The input is the generated hobby recommendation data and equipment information, and the output is the transmission of data to the terminal.

[1525] Step 7:

[1526] The terminal visually displays received hobby recommendations and equipment information to the user. Input is data received from the server, and output is the display on the user interface.

[1527] Step 8:

[1528] The user reviews the displayed recommended hobbies and equipment information and selects the hobbies and equipment that interest them. The input is the information displayed on the terminal, and the output is the user's selection.

[1529] Specific example

[1530] For example, a user using smart glasses answers the question "How would you like to spend your holidays?" with "I want to relax" (Step 1). EmotionEngine analyzes the user's facial expressions and tone of voice and obtains emotional data indicating a high stress level (Step 2). The device sends this response data and emotional data to the server (Step 3). The server inputs the data into HobbyRecommendationModel, which analyzes and identifies the most suitable hobby for the user (Step 4). Based on the analysis results, it recommends hobbies such as "yoga," "meditation," and "reading," and generates information on the necessary equipment for each hobby (yoga mat, meditation cushion, reading light) (Step 5). This information is sent to the device (Step 6). The device displays the hobby recommendations and equipment information to the user (Step 7). Finally, the user selects the hobby and equipment that interests them most (Step 8).

[1531] Example of a prompt:

[1532] User response: "I want to relax."

[1533] Emotional data: High stress level, low excitement level

[1534] Recommended hobbies: "Yoga," "Meditation," "Reading"

[1535] Required equipment: "Yoga mat, meditation cushion, reading light"

[1536] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1537] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1538] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1539] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1540] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1541] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1542] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1543] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1544] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1545] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1546] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1547] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1548] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1549] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1550] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1551] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1552] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1553] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1554] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1555] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1556] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1557] The following is further disclosed regarding the embodiments described above.

[1558] (Claim 1)

[1559] A means of presenting users with questions about their hobbies,

[1560] A means of receiving and analyzing user response data,

[1561] A method for recommending hobbies that suit the user based on the analysis results,

[1562] A means of generating information on the tools needed for a recommended hobby,

[1563] A system that includes means for providing generated tool information to the user.

[1564] (Claim 2)

[1565] The system according to claim 1, which uses an artificial intelligence model to recommend hobbies based on user response data.

[1566] (Claim 3)

[1567] The system according to claim 1, which provides manufacturer information and purchase links related to the equipment necessary for a recommended hobby.

[1568] "Example 1"

[1569] (Claim 1)

[1570] A means of presenting users with questions about their hobbies,

[1571] A means of receiving and analyzing user response data,

[1572] A method for recommending hobbies that suit the user based on the analysis results,

[1573] A means of generating information on the tools needed for a recommended hobby,

[1574] A means of providing the generated tool information to the user,

[1575] A means of asking and answering questions via a user interface,

[1576] A means of submitting user responses as structured data,

[1577] A means of displaying detailed information about the recommended hobby,

[1578] A system that includes this.

[1579] (Claim 2)

[1580] The system according to claim 1, which uses an artificial intelligence model to recommend hobbies based on user response data.

[1581] (Claim 3)

[1582] The system according to claim 1, which provides manufacturer information and purchase links related to the equipment necessary for a recommended hobby.

[1583] "Application Example 1"

[1584] (Claim 1)

[1585] A means of presenting users with questions about their hobbies,

[1586] A means of receiving and analyzing user response data,

[1587] A method for recommending hobbies that suit the user based on the analysis results,

[1588] A means of generating information on the tools needed for a recommended hobby,

[1589] A means of providing the generated tool information to the user,

[1590] A means of presenting questions to users through terminals installed in physical stores and having them input their answers,

[1591] A means for sending the entered response data to the server,

[1592] A system including means for visually displaying recommendation and tool information returned from a server.

[1593] (Claim 2)

[1594] The system according to claim 1, which uses a generative AI model to recommend hobbies based on user response data.

[1595] (Claim 3)

[1596] The system according to claim 1, which provides manufacturer information and purchase links related to information on tools necessary for a recommended hobby.

[1597] "Example 2 of combining an emotion engine"

[1598] (Claim 1)

[1599] A means of presenting users with questions about their hobbies,

[1600] A means of receiving and analyzing user response data,

[1601] A method for recommending hobbies that suit the user based on the analysis results,

[1602] A means of generating information on the tools needed for a recommended hobby,

[1603] A means of providing the generated tool information to the user,

[1604] Means for acquiring user sentiment data,

[1605] A system that includes means for using emotional data for analysis.

[1606] (Claim 2)

[1607] The system according to claim 1, which uses a generative artificial intelligence model to recommend hobbies based on user response data.

[1608] (Claim 3)

[1609] The system according to claim 1, which provides manufacturer information and purchase links related to information on tools necessary for a recommended hobby.

[1610] "Application example 2 when combining with an emotional engine"

[1611] (Claim 1)

[1612] A means of presenting users with questions about their hobbies,

[1613] A means of receiving and analyzing user response data,

[1614] A method for recommending hobbies that suit the user based on the analysis results,

[1615] A means of generating information on the tools needed for a recommended hobby,

[1616] A means of providing the generated tool information to the user,

[1617] A means of providing a hobby suggestion function aimed at improving workers' skills and reducing stress,

[1618] A means of presenting questions and receiving answers using a smart device,

[1619] A means of acquiring and analyzing emotional indicator data,

[1620] A system that includes a means for correcting hobby recommendations using acquired sentiment index data.

[1621] (Claim 2)

[1622] The system according to claim 1, which uses an artificial intelligence model to recommend hobbies based on user response data and sentiment index data.

[1623] (Claim 3)

[1624] The system according to claim 1, which provides product information and purchase links related to the equipment needed for a recommended hobby. [Explanation of Symbols]

[1625] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of presenting users with questions about their hobbies, A means of receiving and analyzing user response data, A method for recommending hobbies that suit the user based on the analysis results, A means of generating information on the tools needed for a recommended hobby, A system that includes means for providing generated tool information to the user.

2. The system according to claim 1, which uses an artificial intelligence model to recommend hobbies based on user response data.

3. The system according to claim 1, which provides manufacturer information and purchase links related to the equipment necessary for a recommended hobby.

Images