System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting and storing user's profile information; means for inputting and storing user's current mood and experience type; means for generating random mission based on said profile information and current mood and experience type; means for notifying user of generated random mission; means for inputting and storing user's executed random mission result and feedback; and means for awarding points and badges based on user's mission result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, many people seek freshness and excitement in their daily lives, but lack the time and resources to plan new experiences themselves. Furthermore, when exploring tourist and entertainment destinations, the overwhelming number of options often leaves people unsure of what to choose. Furthermore, there are limited ways to easily enjoy experiences tailored to their preferences and current mood. Given these circumstances, there is a demand for systems that provide individually optimized experiences and encourage new discoveries and activities. [Means for solving the problem]

[0005] The present invention relates to a system that generates customized random missions in real time based on a user's profile information, current mood, and type of experience, thereby providing the user with a new experience. The system includes: a means for inputting and saving a user's profile information; a means for inputting and saving the user's current mood and type of experience; a means for generating random missions based on the profile information, current mood, and type of experience; a means for notifying the user of the generated random missions; a means for inputting and saving results and feedback of the random missions performed by the user; and a means for awarding points and badges based on the user's mission results. This allows users to easily enjoy new experiences tailored to their profile and current situation, bringing a breath of fresh air to their daily lives.

[0006] "Profile Information" refers to information about a user's personal preferences, interests, budget, transportation options, etc.

[0007] "Current mood" refers to the mental or emotional state a user is feeling at a particular point in time.

[0008] "Type of experience" refers to the content and format of the activity the user currently desires, and is classified into categories such as relaxation, adventure, and learning.

[0009] "Random Missions" refer to less predictable experiences and activities that are generated based on the user's profile information and current mood and type of experience.

[0010] "Means for notifying" refers to a technical method or device for notifying the user of the generated random mission.

[0011] "Feedback" refers to the impressions and evaluations of an activity that a user provides to the system after the experience.

[0012] "Points" refer to units of rewards that are added based on a user's activities and mission achievements.

[0013] A "badge" refers to a virtual medal or title given to a user when they meet certain conditions.

[0014] "Database" refers to an information system for efficiently storing and managing profile information and feedback.

[0015] "AI model" refers to the artificial intelligence algorithms and structures used to perform data analysis and predictions based on user profile information and feedback. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] The present invention is a system for providing new experiences to users' daily lives, generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries.

[0038] Program processing

[0039] Creating a profile

[0040] When a user first launches the application, a profile entry screen appears. The user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[0041] Entering the status

[0042] Next, when the user starts the mystery quest, the app displays a screen for inputting their current mood and the type of experience they are looking for. For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0043] Random mission generation

[0044] The server uses an AI model to generate appropriate random missions based on the user's profile information, current mood, and type of experience. For example, the server might generate missions such as "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0045] Receiving instructions for action

[0046] The device displays the random mission received from the server to the user and provides step-by-step instructions for specific actions. For example, it instructs the user on each action, such as "First, head to the XX cafe." It also uses Google Maps APIs and other tools to provide route guidance to the user's destination.

[0047] Share your experiences

[0048] After users complete a mission, the app displays an experience sharing screen, prompting them to review their experience and upload photos. Once users finish sharing their experience, their device sends the information to the server, which stores this feedback in a database and uses it to refine the AI ​​model for future mission generation.

[0049] Rewards and Gamification

[0050] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0051] Specific examples

[0052] The user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and prefer walking and cycling as their means of transportation. When the user inputs their mood and type of experience, "relaxing" and "discovering new places," the server's AI model generates a mission to "go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and earns points and badges. Feedback from the experience is used to generate the next mission.

[0053] The system of the present invention provides new experiences tailored to the individual needs and circumstances of users, bringing a breath of fresh air to everyday life while also achieving a high level of personalization and real-time response.

[0054] The processing flow will be explained below.

[0055] Step 1: Enter and save your profile information

[0056] User: When the app is launched for the first time, a profile entry screen appears, prompting the user to enter information such as preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation.

[0057] Device: Temporarily stores profile information entered by the user.

[0058] Device: Sends profile information to the server.

[0059] Server: Stores the received profile information in a database.

[0060] Step 2: Enter your current mood and type of experience

[0061] User: When starting a Mystery Quest, you input your current mood and the type of experience you are seeking.

[0062] Device: The input mood and type of experience are temporarily stored and sent to the server.

[0063] Server: Stores the received mood and experience type in a database.

[0064] Step 3: Generate a random mission

[0065] Server: Instructs the AI ​​model to generate random missions based on the user's profile information, mood, and type of experience.

[0066] Server (AI model): Analyzes profile information, current mood, and type of experience to generate appropriate random missions, such as "drink a specific coffee at the nearest cafe" or "find hidden art."

[0067] Server: Sends generated random missions to the device.

[0068] Step 4: Mission Notification and Action Instructions

[0069] Terminal: Displays the random mission received from the server to the user. For example, it displays instructions such as "First, go to XX Cafe."

[0070] Terminal: Uses Google Maps API etc. to guide the user to their destination.

[0071] User: Follow instructions and complete the mission.

[0072] Step 5: Complete the mission and provide feedback

[0073] Users: After completing a mission, they will be prompted to share their experience and provide a rating and feedback.

[0074] On your device: The entered feedback is temporarily stored and sent to the server.

[0075] Server: Stores the received feedback in a database and provides it to the AI ​​model as learning data to be used in generating the next mission.

[0076] Step 6: Compensation calculation and notification

[0077] Server: Calculates points and badges based on users' mission completion results.

[0078] Server: Sends calculated points and badge information to the device.

[0079] On the device: Display the received points and badges to the user. For example, display "You've earned XX points!" or "You've earned a new badge!"

[0080] Users: See the rewards and get motivated for the next mission.

[0081] Through these steps, this system provides users with a new, customized experience, bringing a breath of fresh air to everyday life.

[0082] Example 1

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

[0084] In modern society, many people seek new experiences in their daily lives, but finding time for them can be challenging. Furthermore, it is difficult to provide optimal experiences tailored to the needs and circumstances of every individual user. Conventional systems often only offer pre-determined courses and experiences, and do not adequately provide dynamic experiences based on individual users' current moods and interests. In light of these challenges, the present invention aims to provide a system that dynamically generates random missions based on a user's profile information and current moods and interests, thereby providing a highly personalized experience.

[0085] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0086] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions using a generative AI model based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions and providing action instructions, means for inputting and saving the results and feedback of the user's random missions, and means for awarding points and badges based on the user's mission results. This allows users to enjoy new experiences based on their current moods and interests. Furthermore, the system is continuously improved based on feedback, enabling it to provide more accurate experiences.

[0087] Below are definitions of important terms included in the claims we just rewrote.

[0088] "Profile information" is information about a user, including the user's preferences, interests, available budget, transportation options, and the like.

[0089] "Mood" refers to the psychological state the user is feeling at that time and the type of experience they desire.

[0090] "Type of experience" refers to the specific genre of activity or event that the user desires.

[0091] A "generative AI model" is an algorithm that uses machine learning to generate optimal random missions based on a user's profile information and current mood.

[0092] "Random Missions" are tasks and activities that are dynamically generated based on the user's profile information and current mood.

[0093] "Action instructions" is information indicating specific steps and action guidance required for the user to complete the random mission.

[0094] "Feedback" refers to a record of impressions, ratings, photos, etc. provided by a user after completing a random mission.

[0095] "Points" are a type of reward given to users as a result of completing random missions, and are accumulated to function as an incentive.

[0096] "Badges" are digital rewards that visually represent a user's achievements and are awarded for completing specific missions or achieving certain results.

[0097] The present invention is a system for providing new experiences to users' daily lives, generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries.

[0098] This system is composed of two main components: a server and a terminal. The server is responsible for generating random missions using a generative AI model based on the user's profile information, current mood, and type of experience. The terminal is a device directly operated by the user, and is responsible for inputting profile information, displaying random missions, providing action instructions, and inputting feedback after completing a mission.

[0099] Creating a profile

[0100] When a user first launches the application, a profile information entry screen appears on the device. Here, the user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server stores the received profile information in a database.

[0101] Entering the status

[0102] Next, when the user starts the mystery quest, the app displays a screen on the device for inputting their current mood and the type of experience they are looking for. For example, the user can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0103] Random mission generation

[0104] The server uses a generative AI model to generate an appropriate random mission based on the user's profile information, current mood, and type of experience. For example, missions such as "Drink a specific coffee at the nearest cafe" or "Find hidden art in a nearby park" may be generated. An example prompt is, "The user's profile information states that they like to visit cafes and appreciate art, their budget is under 2,000 yen, their transportation method is walking and cycling, their current mood is relaxation, and they want to discover new places. Please generate an appropriate random mission based on this information." The server then sends the generated mission to the device.

[0105] Receiving instructions for action

[0106] The device displays the random mission received from the server to the user and provides step-by-step instructions for specific actions. For example, it instructs the user on each action, such as "First, head to the XX cafe." It also uses Google Maps APIs and other tools to provide route guidance to the user's destination.

[0107] Collecting feedback

[0108] After a user completes a mission, the app displays an experience sharing screen, prompting the user to review the experience and upload photos. Once the user has finished sharing their experience, the device sends the information to the server, which stores this feedback in a database and uses it to refine the generative AI model for future mission generation.

[0109] Rewards and Gamification

[0110] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0111] As a concrete example, consider a user's profile information, which includes preferences for cafe hopping and art appreciation, a budget of less than 2,000 yen, and transportation methods of walking and cycling. When the user inputs the mood and type of experience, "relaxing" and "discovering new places," the server's generative AI model generates a mission, "Go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and earns points and badges. This feedback is used to generate the next mission.

[0112] The system of the present invention provides new experiences tailored to the individual needs and circumstances of users, bringing a breath of fresh air to everyday life while also achieving a high level of personalization and real-time response.

[0113] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0114] Step 1: Enter and save your profile information

[0115] When a user launches the application, the device displays a profile entry screen where the user can enter information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car).

[0116] The entered profile information is temporarily stored in the terminal's memory, and then the terminal transmits this information to the server.

[0117] The server stores the received profile information in a database. The input here is the user's profile information, and the output is the profile information stored in the database. The server uses this information as the basis for generating random missions later.

[0118] Step 2: Enter and save your mood and experience type

[0119] When a user starts a mystery quest, the device displays a screen for inputting the mood and type of experience.

[0120] For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation."

[0121] The input information is temporarily stored on the terminal, which then transmits it to the server.

[0122] The server stores the received information in a database, where the input is the mood and experience type entered by the user, and the output is the mood and experience type stored in the database.

[0123] Step 3: Generate a random mission

[0124] The server generates random missions using a generative AI model based on the user's profile information and their current mood and type of experience.

[0125] Specifically, the generative AI model is given the following prompt: "The user's profile information states that they like to visit cafes and appreciate art, their budget is under 2000 yen, their preferred mode of transportation is walking and cycling, their current mood is relaxation, and they want to discover new places. Based on this information, please generate an appropriate random mission."

[0126] The generative AI model performs data calculations based on this prompt sentence and generates a random mission.

[0127] The server sends the generated random mission to the device, where the input is the profile information and the type of mood and experience, and the output is the generated random mission.

[0128] Step 4: View and receive action instructions

[0129] The terminal displays the random mission received from the server to the user.

[0130] Furthermore, it provides step-by-step, specific instructions for each action, such as "First, go to the XX cafe."

[0131] The device also provides users with route guidance to their destination using Google Maps API etc. The input here is a random mission sent from the server, and the output is action instructions displayed to the user.

[0132] Step 5: Mission Accomplishment

[0133] The user carries out the mission by following the action instructions provided by the terminal.

[0134] For example, the user completes the mission by arriving at a certain cafe and ordering a latte. Here, the input is an action instruction, and the output is the completion of the mission.

[0135] Step 6: Collect and store feedback

[0136] After completing a mission, the device displays an experience sharing screen where users can review their experience and upload photos.

[0137] For example, you could enter, "The latte at XX Cafe was very delicious." Once the user has finished entering their feedback, the device sends the information to the server.

[0138] The server stores this feedback in a database and uses it as data to refine the generative AI model for future mission generation. The input here is the user's feedback information, and the output is the feedback information stored in the database.

[0139] Step 7: Rewards and Gamification

[0140] The server calculates points and badges based on the user's mission results.

[0141] For example, a user can be awarded 50 points for the achievement of "finding a hidden art." The server sends this to the device, which then displays "You've earned 50 points!" or "You've earned a new badge!" to the user. The input here is the user's mission result, and the output is the calculated points or badge information.

[0142] Through the above processing steps, the system can provide a new experience that suits the user's current mood and interests.

[0143] (Application example 1)

[0144] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0145] The present invention aims to provide users with new experiences in their daily lives. Specifically, it aims to generate customized random missions based on the user's profile information, current emotions, and type of experience, and present them to the user, allowing them to experience new discoveries and excitement. It is also desirable to improve the quality of future missions based on the results and feedback of the missions completed by the user.

[0146] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0147] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current emotions and types of experiences, means for acquiring user location information, means for generating optimal random missions based on the profile information, the current emotions and types of experiences, and the location information, means for notifying the user of the generated random missions, means for inputting and saving the results of the random missions performed by the user and feedback, means for awarding points and certificates based on the user's mission results, and means for creating training data to improve the random mission generation means using user feedback. This allows users to have a new, customized experience, promoting use of physical stores and providing opportunities for new discoveries.

[0148] "User profile information" is information about a user's preferences, interests, available budget, and transportation options.

[0149] "Current Emotion" is information about the user's mood at the time they start the mystery quest and the type of experience they are seeking.

[0150] "Random Missions" are tasks and activities customized based on a user's profile information, current emotions, and type of experience.

[0151] "Information storage device" is a general term for hardware and software for storing information, including databases.

[0152] "Score" refers to points that a user can earn by completing a mission.

[0153] A "certificate" is a badge or title that proves that a user has completed a mission.

[0154] "Location information" is information about the latitude and longitude of the user's current location.

[0155] "Training data" is learning data used to improve the random mission generation means based on user feedback.

[0156] The present invention is a system for providing new experiences to users' daily lives. This system generates customized random missions based on the user's profile information, current emotions, and type of experience, and encourages new discoveries by having the user carry out the missions.

[0157] Main system components

[0158] The main components include the following:

[0159] User device: Smartphone

[0160] Server: Contains the database and AI model

[0161] Geographic information acquisition systems: Libraries such as geopy

[0162] Random mission generation system: uses generative AI models

[0163] Program processing explanation

[0164] 1. Enter and save your user profile information

[0165] When a user device first launches the application, the user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, budget, and transportation. This information is temporarily stored and sent to the server, which stores the profile information in a database.

[0166] 2. Input and save the current emotion and type of experience

[0167] When starting a mystery quest, the user's device will prompt them to input their current emotions and the type of experience they are seeking. For example, they can input "I want to relax" or "I want to discover new places." This input is also temporarily stored and sent to the server.

[0168] 3. Obtaining location information

[0169] The user device uses the geopy library to obtain the current location information (latitude and longitude) and sends it to the server.

[0170] 4. Random mission generation

[0171] The server uses a generative AI model based on profile information, current emotions, type of experience, and location information to generate an appropriate random mission, such as "drink a specific coffee at the nearest cafe."

[0172] 5. Mission Notification and Instructions

[0173] The system notifies the user of the randomly generated mission and provides specific instructions for action. It also provides route guidance using Google Maps APIs and other tools.

[0174] 6. Gather feedback after completing the mission

[0175] After users complete a mission, they are presented with a shared experience screen where they can review their experience and upload photos. This feedback is sent to the server and stored in a database.

[0176] 7. Awarding of Scores and Certificates

[0177] The server calculates the score and certificate based on the user's mission results and notifies the user's terminal, allowing the user to feel a sense of accomplishment.

[0178] Specific examples

[0179] The user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and use walking and cycling as their means of transportation. When the user inputs the emotions and experience type of "relaxation" and "discover new places," the server's AI model generates a mission to "go to the nearest cafe and order a latte." The user's device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and receives points and a certificate. Feedback from the experience is used to generate the next mission.

[0180] Prompt Sentence Examples

[0181] User Input:

[0182] Please enter your user profile information.

[0183] Enter your current mood and type of experience:

[0184] "What is your current mood? (e.g., I want to relax)"

[0185] "What kind of experience are you looking for? (e.g., discovering new places)"

[0186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0187] Step 1:

[0188] When a user launches the application, the device displays a profile information input screen. Here, the user enters their preferences, interests, available budget, and mode of transportation. This information is temporarily stored on the device and then sent to the server. The server stores the received profile information in a database. The input data is the profile information, and the output data is the profile information stored in the database.

[0189] Step 2:

[0190] When a user attempts to start a mystery quest, the device displays a screen for inputting their current emotions and the type of experience they are seeking. The user may enter, for example, "I want to relax" or "I want to discover new places." This is also temporarily stored on the device and sent to the server. The server stores the received emotions and types of experiences in a database. The input data is the emotion and experience information, and the output data is the emotion and experience information stored in the database.

[0191] Step 3:

[0192] The device uses the geopy library to obtain the user's current location. The device obtains the latitude and longitude information and sends it to the server. The server temporarily stores this location information and uses it in the next step of random mission generation. The input data is the current location, and the output data is the location information sent to the server.

[0193] Step 4:

[0194] The server combines the user's profile information, current emotion, type of experience, and location information to generate an optimal random mission using a generative AI model. For example, a mission such as "drink a specific coffee at the nearest cafe" may be generated. The generated mission is stored on the server and used in the next step. The input data is the profile information, emotion, experience, and location information, and the output data is the generated random mission.

[0195] Step 5:

[0196] The server notifies the device of the generated random mission. The device then displays specific instructions to the user. For example, "Please head to the XX cafe." The device also uses the Google Maps API to provide navigation to the user's destination. The input data is the mission information from the server, and the output data is the instructions notified to the user.

[0197] Step 6:

[0198] After the user completes the mission, the device displays a screen for sharing their experience. The user can review their experience and upload photos. This information is temporarily stored on the device and then sent to the server. The server stores this data in a database. The input data is the user's feedback, and the output data is the feedback information stored in the database.

[0199] Step 7:

[0200] The server calculates the score and certificate based on the user's mission results. The calculation results are sent to the device, which notifies the user. For example, the user can earn XX points or get a new badge. The input data is the user's mission results, and the output data is score and certificate information.

[0201] Step 8:

[0202] The server uses user feedback to create training data to improve the random mission generation method, thereby increasing the accuracy of the next mission generation. The input data is feedback information, and the output data is training data.

[0203] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0204] The present invention is a system for providing new experiences to users' daily lives by generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, making it possible to provide experiences that take the user's emotional state into consideration.

[0205] Program processing

[0206] Creating a profile

[0207] When a user first launches the application, a profile entry screen appears. The user enters information about their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[0208] Entering the status

[0209] Next, when the user starts the mystery quest, the app displays a screen for inputting their current mood and the type of experience they are looking for. For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0210] Random mission generation

[0211] The server uses an AI model based on the user's profile information, current mood, and type of experience, and combines it with an emotion engine to generate random missions. The emotion engine collects emotional data from the user's past feedback, analyzes it, and uses it to generate missions. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0212] Receiving instructions for action

[0213] The device displays the random mission received from the server to the user and provides specific step-by-step instructions. For example, it may provide instructions such as "First, head to the XX cafe," and uses Google Maps APIs to guide the user to their destination. The user follows the instructions to complete the mission.

[0214] Emotion analysis during missions

[0215] The emotion engine analyzes the user's facial expressions and voice in real time while they are completing a mission, recognizing changes in their emotions and allowing it to adjust the difficulty and content of the mission as needed.

[0216] Share your experiences

[0217] After users complete a mission, the app displays an experience sharing screen, prompting them to review their experience and upload photos. Once users finish sharing their experience, their device sends the information to the server, which stores this feedback in a database and uses it as training data for the AI ​​model and emotion engine to generate future missions.

[0218] Rewards and Gamification

[0219] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0220] Specific examples

[0221] Assume that a user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and use walking and cycling as their means of transportation. When the user inputs their mood and experience type, "relaxing" and "discovering new places," the server's AI model uses an emotion engine to generate a mission, "Go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. The emotion engine analyzes the user's facial expressions and voice in real time to monitor the user's emotional state. After completing the mission, the user can share their experience and earn points and badges. Feedback from the experience is used to generate the next mission.

[0222] The system of the present invention provides users with a new personalized experience through the above steps, and by adding an emotion engine, achieves even higher levels of personalization and real-time responses.

[0223] The processing flow will be explained below.

[0224] Step 1: Enter and save your profile information

[0225] User: When the app is launched for the first time, a profile entry screen appears, prompting the user to enter their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (walking, cycling, car, etc.).

[0226] Device: Temporarily stores profile information entered by the user.

[0227] Device: Sends profile information to the server.

[0228] Server: Stores the received profile information in a database.

[0229] Step 2: Enter your current mood and type of experience

[0230] Users: When starting a mystery quest, they input their current mood and the type of experience they are looking for, such as "relaxing" or "seeking an adventurous experience," or "cafe-hopping" or "art appreciation."

[0231] Device: The input mood and type of experience are temporarily stored and sent to the server.

[0232] Server: Stores the received mood and experience type in a database.

[0233] Step 3: Generate a random mission

[0234] Server: Generates random missions using an emotion engine and AI models based on the user's profile information, mood, and type of experience.

[0235] Server (AI model): Analyzes profile information, current mood, and type of experience, and also takes into account emotional data from the emotion engine to generate appropriate random missions, such as "drink a specific latte at the nearest cafe" or "find hidden art in a nearby park."

[0236] Server: Sends generated random missions to the device.

[0237] Step 4: Mission Notification and Action Instructions

[0238] Terminal: Displays the random mission received from the server to the user. For example, it displays instructions such as "First, go to XX Cafe."

[0239] Terminal: Uses Google Maps API etc. to guide the user to their destination.

[0240] User: Follow instructions and complete the mission.

[0241] Step 5: Emotion analysis during the mission

[0242] Emotion engine: Analyzes the user's facial expressions and voice in real time while they are completing a mission, recognizing changes in their emotions.

[0243] Server: Receives the analysis results from the emotion engine and adjusts the difficulty and content of the mission as needed.

[0244] Step 6: Complete the mission and provide feedback

[0245] Users: After completing a mission, they are prompted to review their experience and provide their thoughts and ratings about the experience.

[0246] On your device: The entered feedback is temporarily stored and sent to the server.

[0247] Server: Stores the received feedback in a database and provides it to the AI ​​model and emotion engine as learning data to be used in generating the next mission.

[0248] Step 7: Compensation calculation and notification

[0249] Server: Calculates points and badges based on users' mission completion results.

[0250] Server: Sends calculated points and badge information to the device.

[0251] On the device: Display the received points and badges to the user. For example, display "You've earned XX points!" or "You've earned a new badge!"

[0252] Users: See the rewards and get motivated for the next mission.

[0253] Through these steps, the system of the present invention provides users with a new personalized experience, and by adding an emotion engine, it achieves even higher levels of personalization and real-time responses.

[0254] Example 2

[0255] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0256] Conventional user experience provision systems lack the ability to customize the experience to take into account the user's emotional state and real-time feedback, making it difficult to provide the optimal experience for the user. Furthermore, there is a need to automatically generate new experiences tailored to individual users by effectively utilizing user profile information and feedback.

[0257] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions using a generation AI model based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions, means for inputting and saving results and feedback of the random missions performed by the user, means for awarding points and badges based on the user's mission results, means for analyzing the user's facial expressions, voice, etc. to recognize the user's emotional state in real time and adjust the missions, and means for creating learning data for improving the random mission generation means using user feedback. This makes it possible to provide an optimal, customized experience for each user, taking into account the user's emotional state and real-time feedback.

[0258] "Profile information" is personal information such as a user's preferences, budget, mode of transportation, etc.

[0259] "Mood" refers to the emotions and psychological state that a user is currently experiencing.

[0260] "Experience type" means the specific activity or category of activity that a user is seeking.

[0261] A "generative AI model" is an algorithm or program that uses artificial intelligence to generate missions based on a user's profile information, mood, and type of experience.

[0262] "Random missions" refer to specific activities or tasks provided to users by generative AI models.

[0263] "Notification" refers to the method or means for informing the user of the generated random mission.

[0264] "Feedback" refers to the evaluation, impressions, and reactions provided by the user regarding the random mission they have completed.

[0265] "Points" refer to points or scores that a user receives as a reward for completing a mission.

[0266] A "badge" is a recognition or award that a user can earn by completing a specific mission.

[0267] An "emotion engine" is a technology or program that analyzes a user's facial expressions and voice to recognize their emotional state.

[0268] "Real-time recognition" means detecting and analyzing the user's emotional state instantly.

[0269] "Training data" refers to data that the system uses to improve its AI model based on user feedback.

[0270] A "database" is a digital warehouse for organizing and storing information such as profile information and feedback.

[0271] The present invention is a system for providing new experiences to users' daily lives by generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, making it possible to provide experiences that take the user's emotional state into consideration.

[0272] The system of the present invention begins when a user launches the application on a device such as a smartphone or tablet. The device first displays a profile information input screen, and the user enters information such as their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). This information is temporarily stored on the device and then sent to the server. The server stores the received information in a database.

[0273] Next, when the user starts the mystery quest, the device displays a screen for inputting their current mood and the type of experience they are looking for. The user can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." This information is also temporarily stored on the device and sent to the server.

[0274] The server uses a generative AI model based on the received profile information, current mood, and type of experience to generate random missions in combination with the emotion engine. The emotion engine analyzes emotional data collected from past feedback and generates missions based on this. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0275] The device displays the random mission received from the server to the user. It provides specific step-by-step instructions, such as "First, head to the XX cafe." The device uses the Google Maps API to guide the user to their destination. The user then follows these instructions to complete the mission.

[0276] While the user is completing a mission, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. The difficulty and content of the mission can be adjusted as needed. After the mission is completed, the device displays an experience sharing screen, prompting the user to review their experience and upload photos. Once the user has finished sharing their experience, the device sends the information to the server. The server stores the received feedback in a database and uses it to generate future missions.

[0277] Furthermore, the server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the points and badges to the user, giving them a sense of accomplishment. For example, it displays "You've earned XX points!" or "You've earned a new badge!"

[0278] Specific examples

[0279] If a user's profile information indicates that they like cafe hopping and art appreciation, their budget is under 2,000 yen, and their transportation methods are walking and cycling, and the user enters "relax" and "discover new places," the server's generative AI model uses this information to generate a mission using an emotion engine: "Go to the nearest cafe and order a latte." The device displays this mission and uses the Google Maps API to provide directions to the cafe. While the user is completing the mission, the emotion engine analyzes the user's emotional state in real time. After completing the mission, the user reviews their experience and earns points and badges. This post-experience feedback is used to generate the next mission.

[0280] Prompt Sentence Examples

[0281] An example of a prompt is:

[0282] User profile information:

[0283] Hobbies: Cafe hopping, art appreciation

[0284] Budget: Under 2,000 yen

[0285] Transportation: walking, cycling

[0286] Current mood: Relaxed

[0287] Experience you're looking for: Discover new places

[0288] Please suggest three possible missions to generate.

[0289] As described above, the system of the present invention makes it possible to provide an individually optimized experience based on the user's profile information and real-time emotion analysis.

[0290] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0291] Step 1: Launch the application and enter profile information

[0292] The user launches the application on their smartphone or tablet. The device displays a screen for entering profile information. The user enters information such as their preferences (e.g., cafe hopping, art appreciation), budget (e.g., under 2,000 yen), and mode of transportation (e.g., walking, cycling). This input information is temporarily stored on the device. The device then sends this temporarily stored information to the server. The server stores the received profile information in a database. The input is the user's profile information, and the output is the user information stored in the database.

[0293] Step 2: Enter your current mood and type of experience

[0294] When a user starts a mystery quest, the device displays a screen for inputting their current mood and the type of experience they are seeking. Users input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," and the type of experience, such as "cafe hopping" or "art appreciation." This information is also temporarily stored on the device and sent to the server. The input is the current mood and type of experience, and the output is the state information sent to the server.

[0295] Step 3: Generate a random mission

[0296] The server generates random missions using a generative AI model based on the received profile information, current mood, and type of experience. The emotion engine analyzes emotional data collected from past feedback and reflects this in the generation of missions. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "search for hidden art in a nearby park." The server sends the generated missions to the device. The inputs are the user's profile information, current mood, type of experience, and past feedback, and the output is the generated random mission.

[0297] Step 4: Announce the random mission and provide instructions

[0298] The device displays the random mission received from the server to the user. It provides specific step-by-step instructions, such as "First, head to the XX cafe." The device uses the Google Maps API to guide the user along the route to their destination. The user then follows these instructions to complete the mission. The input is the generated random mission, and the output is the instructions and guidance communicated to the user.

[0299] Step 5: Emotion analysis during the mission

[0300] While the user is completing a mission, the emotion engine analyzes the user's facial expressions and voice in real time to recognize changes in emotion. The emotion engine can adjust the difficulty and content of the mission as needed. The input is the user's emotion data collected in real time, and the output is updated mission content and difficulty.

[0301] Step 6: Share your experience and provide feedback

[0302] When a user completes a mission, the device displays an experience sharing screen and prompts the user to review the experience and upload photos. When the user finishes sharing their experience, the device sends the information to the server. The server stores the received feedback in a database to help generate future missions. The input is the user's experience review and photos, and the output is the feedback stored in the database.

[0303] Step 7: Calculating and notifying rewards

[0304] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the points and badges to the user, giving them a sense of accomplishment. For example, it displays "You've earned XX points!" or "You've earned a new badge!" The input is the user's mission results, and the output is the calculated points and badge information.

[0305] (Application example 2)

[0306] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0307] Conventional systems have had difficulty taking into account users' emotions and real-time information when providing new experiences to users' daily lives. In particular, systems must respond appropriately to dynamic changes in the user's mood and emotions. Furthermore, they lack the ability to provide navigation and specific instructions during the generated mission. These issues result in a decline in the quality of the user's experience and a decrease in satisfaction.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0309] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions, means for inputting and saving results of the random missions performed by the user and feedback, means for awarding points and badges based on the user's mission results, means for performing emotion analysis to recognize the user's emotional state, means for providing guidance while the user is completing the missions in real time, map service means for providing route guidance based on the generated missions, and means for creating data for training the mission generation means using feedback. This makes it possible to provide missions adapted to the user's emotions and current situation, thereby achieving a higher level of personalization and improved quality of experience.

[0310] "Profile information" is information specific to a user, such as preferences, budget, and mode of transportation, and is the basic data that allows the system to provide the user with an optimal experience.

[0311] "Mood" refers to the user's current emotional state, and is a factor that affects the content of the random missions provided by the system.

[0312] "Type of experience" refers to the category of specific activities or events that the user desires, such as "cafe hopping" or "art appreciation."

[0313] "Random Missions" refer to specific tasks or activities that are generated based on the user's profile information and current mood and type of experience, and are designed to provide the user with new discoveries and experiences.

[0314] "Notification means" refers to the method by which the system notifies the user of the random missions generated, and includes smartphone apps, notification messages, etc.

[0315] "Feedback" refers to the user's evaluation and impressions of the random mission they performed, and is data collected for the system to use in generating the next mission.

[0316] "Points" are a type of reward that users can earn by completing random missions, and form part of the benefits and reward system that can be used within the app.

[0317] A "badge" is a digital medal or symbol awarded to users who achieve certain conditions or missions, and serves to enhance the user's sense of accomplishment as part of gamification.

[0318] "Emotion analysis" is a technology that analyzes a user's facial expressions and voice data in real time to recognize their current emotional state, and is used by the system to dynamically adjust the content of the mission.

[0319] The "map service" is a function that guides users to their destination when they are completing random missions, and uses location information services and navigation systems.

[0320] "Learning data" is data that is used to improve the next random mission generation method based on feedback collected from users, and is used to improve the accuracy of the AI ​​model.

[0321] A "server" is a computer system that stores and processes various data such as user profile information, feedback, and mission generation.

[0322] The system for implementing the present invention has functions for providing new experiences to users in their daily lives. This system has the following main functions in particular:

[0323] 1. Create a profile

[0324] When a user uses the system for the first time, they enter profile information through their smartphone. The input items include preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[0325] 2. Enter your mood and experience type

[0326] When a user starts a mission, they are prompted to enter their current mood (e.g., "I want to relax") and the type of experience (e.g., "cafe hopping"). The device temporarily stores this information and sends it to the server.

[0327] 3. Random mission generation

[0328] The server generates random missions using a generative AI model and sentiment analysis engine based on the user's profile information, current mood, and type of experience. For example, a specific task such as "Go to the nearest cafe and order a latte" is automatically generated.

[0329] 4. Mission Notification and Navigation

[0330] The device notifies the user of the random mission received from the server and provides route guidance to the destination using Google Maps API. The device guides the user step by step and assists the user in completing the mission.

[0331] 5. Emotion analysis

[0332] While the user is completing a mission, the emotion analysis engine analyzes the user's facial expressions and voice via the device's camera and microphone, recognizing their emotional state in real time. This makes it possible to adjust the content and difficulty of the mission according to the user's emotional state.

[0333] 6. Share your experiences

[0334] After users complete a mission, they are shown an experience sharing screen where they can review their experience and upload photos. This information is sent to the server and stored in a database. The feedback is used to generate the next mission.

[0335] 7. Rewards and Gamification

[0336] The server calculates points and badges based on the user's mission results and sends them to the device, allowing the user to visually check their progress and sense of accomplishment.

[0337] Hardware and software used

[0338] Hardware

[0339] Smartphone (iOS / Android)

[0340] software

[0341] Flask: a server-side web framework

[0342] Firestore: Used as a database

[0343] Google Cloud Translation API: For multilingual support

[0344] Google Maps API: for navigation

[0345] Emotion analysis engine: Analyzes the user's facial expressions and voice data

[0346] Specific examples

[0347] For example, if a user's profile information states "I like cafe hopping and art appreciation, my budget is under 2,000 yen, and my transportation methods are walking and cycling," and the user inputs the mood and experience type of "relaxation" and "discover new places," the server's generative AI model and sentiment analysis engine will generate a mission of "go to the nearest cafe and order a latte." The device will display this mission and use the Google Maps API to guide the user to the cafe. After completing the mission, the user can share their experience and earn points and badges.

[0348] Prompt Sentence Examples

[0349] Generate the perfect mission for a user who likes "cafe hopping" and is in the mood to "relax." For example, a mission to go to the nearest cafe and order a latte. What other missions would you generate?

[0350] The present invention allows users to enjoy an experience that is individually customized, and is expected to provide a more engaging experience through real-time responses and reward systems that respond to emotions.

[0351] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0352] Step 1:

[0353] A user downloads and launches a smartphone app. First, the user is guided to a screen where they can enter their profile information. Here, they enter information such as their preferences, budget, and mode of transportation. The device temporarily stores this information, formats the input data, and sends it to the server. The server stores the received profile information in a database and returns the results. The input to this step is the user's profile information, and the output is the profile information stored in the database.

[0354] Step 2:

[0355] When a user starts "Discovery Mode," a screen appears asking them to enter their current mood and the type of experience they are looking for. For example, they can enter information such as "I want to relax," "I'm looking for an adventurous experience," "I want to go café-hopping," or "I want to appreciate art." The device collects this information and sends it to the server. The server processes this information and stores it as base data for generating random missions. The input for this step is the user's current mood and the type of experience, and the output is base data for generating random missions.

[0356] Step 3:

[0357] The server uses a generative AI model based on the profile information, current mood, and experience type, combined with a sentiment analysis engine, to generate a random mission. For example, a specific mission such as "Go to the nearest cafe and order a latte" is generated. The server generates this random mission and sends it to the device. The input of this step is the profile information, mood, and experience type, and the output is the generated random mission.

[0358] Step 4:

[0359] The device notifies the user of the random mission received from the server. Specifically, it displays the details of the mission on the screen and provides the user with specific instructions. For example, instructions such as "First, go to the nearest cafe" are displayed. The device uses the Google Maps API to guide the user to their destination. The input of this step is the generated random mission, and the output is a notification of the mission and navigation instructions to the user.

[0360] Step 5:

[0361] While the user is performing the mission, the device collects facial expressions and voice data through a camera and microphone, and analyzes the user's emotional state in real time using an emotion analysis engine. The server uses this emotional data to adjust the content and difficulty of the mission. The input for this step is the user's facial and voice data, and the output is the real-time emotion analysis results.

[0362] Step 6:

[0363] After the user completes the mission, an experience sharing screen appears. The user reviews the mission experience and uploads photos. The device collects this feedback data and sends it to the server. The server stores it in a database and uses it as learning data for the next random mission generation. The input of this step is the user's feedback, and the output is the feedback data stored in the database.

[0364] Step 7:

[0365] The server calculates points and badges based on the user's mission results and sends the information to the device. The device displays information about the points and badges to the user, giving them a sense of accomplishment. For example, messages such as "You've earned XX points!" or "You've earned a new badge!" are displayed. The input of this step is the user's mission results, and the output is point and badge information.

[0366] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0367] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0368] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0369] [Second embodiment]

[0370] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0371] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0372] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0373] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0374] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0375] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0376] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0377] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0378] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0379] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0380] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0381] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0382] The present invention is a system for providing new experiences to users' daily lives, generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries.

[0383] Program processing

[0384] Creating a profile

[0385] When a user first launches the application, a profile entry screen appears. The user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[0386] Entering the status

[0387] Next, when the user starts the mystery quest, the app displays a screen for inputting their current mood and the type of experience they are looking for. For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0388] Random mission generation

[0389] The server uses an AI model to generate appropriate random missions based on the user's profile information, current mood, and type of experience. For example, the server might generate missions such as "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0390] Receiving instructions for action

[0391] The device displays the random mission received from the server to the user and provides step-by-step instructions for specific actions. For example, it instructs the user on each action, such as "First, head to the XX cafe." It also uses Google Maps APIs and other tools to provide route guidance to the user's destination.

[0392] Share your experiences

[0393] After users complete a mission, the app displays an experience sharing screen, prompting them to review their experience and upload photos. Once users finish sharing their experience, their device sends the information to the server, which stores this feedback in a database and uses it to refine the AI ​​model for future mission generation.

[0394] Rewards and Gamification

[0395] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0396] Specific examples

[0397] The user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and prefer walking and cycling as their means of transportation. When the user inputs their mood and type of experience, "relaxing" and "discovering new places," the server's AI model generates a mission to "go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and earns points and badges. Feedback from the experience is used to generate the next mission.

[0398] The system of the present invention provides new experiences tailored to the individual needs and circumstances of users, bringing a breath of fresh air to everyday life while also achieving a high level of personalization and real-time response.

[0399] The processing flow will be explained below.

[0400] Step 1: Enter and save your profile information

[0401] User: When the app is launched for the first time, a profile entry screen appears, prompting the user to enter information such as preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation.

[0402] Device: Temporarily stores profile information entered by the user.

[0403] Device: Sends profile information to the server.

[0404] Server: Stores the received profile information in a database.

[0405] Step 2: Enter your current mood and type of experience

[0406] User: When starting a Mystery Quest, you input your current mood and the type of experience you are seeking.

[0407] Device: The input mood and type of experience are temporarily stored and sent to the server.

[0408] Server: Stores the received mood and experience type in a database.

[0409] Step 3: Generate a random mission

[0410] Server: Instructs the AI ​​model to generate random missions based on the user's profile information, mood, and type of experience.

[0411] Server (AI model): Analyzes profile information, current mood, and type of experience to generate appropriate random missions, such as "drink a specific coffee at the nearest cafe" or "find hidden art."

[0412] Server: Sends generated random missions to the device.

[0413] Step 4: Mission Notification and Action Instructions

[0414] Terminal: Displays the random mission received from the server to the user. For example, it displays instructions such as "First, go to XX Cafe."

[0415] Terminal: Uses Google Maps API etc. to guide the user to their destination.

[0416] User: Follow instructions and complete the mission.

[0417] Step 5: Complete the mission and provide feedback

[0418] Users: After completing a mission, they will be prompted to share their experience and provide a rating and feedback.

[0419] On your device: The entered feedback is temporarily stored and sent to the server.

[0420] Server: Stores the received feedback in a database and provides it to the AI ​​model as learning data to be used in generating the next mission.

[0421] Step 6: Compensation calculation and notification

[0422] Server: Calculates points and badges based on users' mission completion results.

[0423] Server: Sends calculated points and badge information to the device.

[0424] On the device: Display the received points and badges to the user. For example, display "You've earned XX points!" or "You've earned a new badge!"

[0425] Users: See the rewards and get motivated for the next mission.

[0426] Through these steps, this system provides users with a new, customized experience, bringing a breath of fresh air to everyday life.

[0427] Example 1

[0428] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0429] In modern society, many people seek new experiences in their daily lives, but finding time for them can be challenging. Furthermore, it is difficult to provide optimal experiences tailored to the needs and circumstances of every individual user. Conventional systems often only offer pre-determined courses and experiences, and do not adequately provide dynamic experiences based on individual users' current moods and interests. In light of these challenges, the present invention aims to provide a system that dynamically generates random missions based on a user's profile information and current moods and interests, thereby providing a highly personalized experience.

[0430] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0431] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions using a generative AI model based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions and providing action instructions, means for inputting and saving the results and feedback of the user's random missions, and means for awarding points and badges based on the user's mission results. This allows users to enjoy new experiences based on their current moods and interests. Furthermore, the system is continuously improved based on feedback, enabling it to provide more accurate experiences.

[0432] Below are definitions of important terms included in the claims we just rewrote.

[0433] "Profile information" is information about a user, including the user's preferences, interests, available budget, transportation options, and the like.

[0434] "Mood" refers to the psychological state the user is feeling at that time and the type of experience they desire.

[0435] "Type of experience" refers to the specific genre of activity or event that the user desires.

[0436] A "generative AI model" is an algorithm that uses machine learning to generate optimal random missions based on a user's profile information and current mood.

[0437] "Random Missions" are tasks and activities that are dynamically generated based on the user's profile information and current mood.

[0438] "Action instructions" is information indicating specific steps and action guidance required for the user to complete the random mission.

[0439] "Feedback" refers to a record of impressions, ratings, photos, etc. provided by a user after completing a random mission.

[0440] "Points" are a type of reward given to users as a result of completing random missions, and are accumulated to function as an incentive.

[0441] "Badges" are digital rewards that visually represent a user's achievements and are awarded for completing specific missions or achieving certain results.

[0442] The present invention is a system for providing new experiences to users' daily lives, generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries.

[0443] This system is composed of two main components: a server and a terminal. The server is responsible for generating random missions using a generative AI model based on the user's profile information, current mood, and type of experience. The terminal is a device directly operated by the user, and is responsible for inputting profile information, displaying random missions, providing action instructions, and inputting feedback after completing a mission.

[0444] Creating a profile

[0445] When a user first launches the application, a profile information entry screen appears on the device. Here, the user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server stores the received profile information in a database.

[0446] Entering the status

[0447] Next, when the user starts the mystery quest, the app displays a screen on the device for inputting their current mood and the type of experience they are looking for. For example, the user can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0448] Random mission generation

[0449] The server uses a generative AI model to generate an appropriate random mission based on the user's profile information, current mood, and type of experience. For example, missions such as "Drink a specific coffee at the nearest cafe" or "Find hidden art in a nearby park" may be generated. An example prompt is, "The user's profile information states that they like to visit cafes and appreciate art, their budget is under 2,000 yen, their transportation method is walking and cycling, their current mood is relaxation, and they want to discover new places. Please generate an appropriate random mission based on this information." The server then sends the generated mission to the device.

[0450] Receiving instructions for action

[0451] The device displays the random mission received from the server to the user and provides step-by-step instructions for specific actions. For example, it instructs the user on each action, such as "First, head to the XX cafe." It also uses Google Maps APIs and other tools to provide route guidance to the user's destination.

[0452] Collecting feedback

[0453] After a user completes a mission, the app displays an experience sharing screen, prompting the user to review the experience and upload photos. Once the user has finished sharing their experience, the device sends the information to the server, which stores this feedback in a database and uses it to refine the generative AI model for future mission generation.

[0454] Rewards and Gamification

[0455] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0456] As a concrete example, consider a user's profile information, which includes preferences for cafe hopping and art appreciation, a budget of less than 2,000 yen, and transportation methods of walking and cycling. When the user inputs the mood and type of experience, "relaxing" and "discovering new places," the server's generative AI model generates a mission, "Go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and earns points and badges. This feedback is used to generate the next mission.

[0457] The system of the present invention provides new experiences tailored to the individual needs and circumstances of users, bringing a breath of fresh air to everyday life while also achieving a high level of personalization and real-time response.

[0458] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0459] Step 1: Enter and save your profile information

[0460] When a user launches the application, the device displays a profile entry screen where the user can enter information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car).

[0461] The entered profile information is temporarily stored in the terminal's memory, and then the terminal transmits this information to the server.

[0462] The server stores the received profile information in a database. The input here is the user's profile information, and the output is the profile information stored in the database. The server uses this information as the basis for generating random missions later.

[0463] Step 2: Enter and save your mood and experience type

[0464] When a user starts a mystery quest, the device displays a screen for inputting the mood and type of experience.

[0465] For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation."

[0466] The input information is temporarily stored on the terminal, which then transmits it to the server.

[0467] The server stores the received information in a database, where the input is the mood and experience type entered by the user, and the output is the mood and experience type stored in the database.

[0468] Step 3: Generate a random mission

[0469] The server generates random missions using a generative AI model based on the user's profile information and their current mood and type of experience.

[0470] Specifically, the generative AI model is given the following prompt: "The user's profile information states that they like to visit cafes and appreciate art, their budget is under 2000 yen, their preferred mode of transportation is walking and cycling, their current mood is relaxation, and they want to discover new places. Based on this information, please generate an appropriate random mission."

[0471] The generative AI model performs data calculations based on this prompt sentence and generates a random mission.

[0472] The server sends the generated random mission to the device, where the input is the profile information and the type of mood and experience, and the output is the generated random mission.

[0473] Step 4: View and receive action instructions

[0474] The terminal displays the random mission received from the server to the user.

[0475] Furthermore, it provides step-by-step, specific instructions for each action, such as "First, go to the XX cafe."

[0476] The device also provides users with route guidance to their destination using Google Maps API etc. The input here is a random mission sent from the server, and the output is action instructions displayed to the user.

[0477] Step 5: Mission Accomplishment

[0478] The user carries out the mission by following the action instructions provided by the terminal.

[0479] For example, the user completes the mission by arriving at a certain cafe and ordering a latte. Here, the input is an action instruction, and the output is the completion of the mission.

[0480] Step 6: Collect and store feedback

[0481] After completing a mission, the device displays an experience sharing screen where users can review their experience and upload photos.

[0482] For example, you could enter, "The latte at XX Cafe was very delicious." Once the user has finished entering their feedback, the device sends the information to the server.

[0483] The server stores this feedback in a database and uses it as data to refine the generative AI model for future mission generation. The input here is the user's feedback information, and the output is the feedback information stored in the database.

[0484] Step 7: Rewards and Gamification

[0485] The server calculates points and badges based on the user's mission results.

[0486] For example, a user can be awarded 50 points for the achievement of "finding a hidden art." The server sends this to the device, which then displays "You've earned 50 points!" or "You've earned a new badge!" to the user. The input here is the user's mission result, and the output is the calculated points or badge information.

[0487] Through the above processing steps, the system can provide a new experience that suits the user's current mood and interests.

[0488] (Application example 1)

[0489] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0490] The present invention aims to provide users with new experiences in their daily lives. Specifically, it aims to generate customized random missions based on the user's profile information, current emotions, and type of experience, and present them to the user, allowing them to experience new discoveries and excitement. It is also desirable to improve the quality of future missions based on the results and feedback of the missions completed by the user.

[0491] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0492] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current emotions and types of experiences, means for acquiring user location information, means for generating optimal random missions based on the profile information, the current emotions and types of experiences, and the location information, means for notifying the user of the generated random missions, means for inputting and saving the results of the random missions performed by the user and feedback, means for awarding points and certificates based on the user's mission results, and means for creating training data to improve the random mission generation means using user feedback. This allows users to have a new, customized experience, promoting use of physical stores and providing opportunities for new discoveries.

[0493] "User profile information" is information about a user's preferences, interests, available budget, and transportation options.

[0494] "Current Emotion" is information about the user's mood at the time they start the mystery quest and the type of experience they are seeking.

[0495] "Random Missions" are tasks and activities customized based on a user's profile information, current emotions, and type of experience.

[0496] "Information storage device" is a general term for hardware and software for storing information, including databases.

[0497] "Score" refers to points that a user can earn by completing a mission.

[0498] A "certificate" is a badge or title that proves that a user has completed a mission.

[0499] "Location information" is information about the latitude and longitude of the user's current location.

[0500] "Training data" is learning data used to improve the random mission generation means based on user feedback.

[0501] The present invention is a system for providing new experiences to users' daily lives. This system generates customized random missions based on the user's profile information, current emotions, and type of experience, and encourages new discoveries by having the user carry out the missions.

[0502] Main system components

[0503] The main components include the following:

[0504] User device: Smartphone

[0505] Server: Contains the database and AI model

[0506] Geographic information acquisition systems: Libraries such as geopy

[0507] Random mission generation system: uses generative AI models

[0508] Program processing explanation

[0509] 1. Enter and save your user profile information

[0510] When a user device first launches the application, the user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, budget, and transportation. This information is temporarily stored and sent to the server, which stores the profile information in a database.

[0511] 2. Input and save the current emotion and type of experience

[0512] When starting a mystery quest, the user's device will prompt them to input their current emotions and the type of experience they are seeking. For example, they can input "I want to relax" or "I want to discover new places." This input is also temporarily stored and sent to the server.

[0513] 3. Obtaining location information

[0514] The user device uses the geopy library to obtain the current location information (latitude and longitude) and sends it to the server.

[0515] 4. Random mission generation

[0516] The server uses a generative AI model based on profile information, current emotions, type of experience, and location information to generate an appropriate random mission, such as "drink a specific coffee at the nearest cafe."

[0517] 5. Mission Notification and Instructions

[0518] The system notifies the user of the randomly generated mission and provides specific instructions for action. It also provides route guidance using Google Maps APIs and other tools.

[0519] 6. Gather feedback after completing the mission

[0520] After users complete a mission, they are presented with a shared experience screen where they can review their experience and upload photos. This feedback is sent to the server and stored in a database.

[0521] 7. Awarding of Scores and Certificates

[0522] The server calculates the score and certificate based on the user's mission results and notifies the user's terminal, allowing the user to feel a sense of accomplishment.

[0523] Specific examples

[0524] The user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and use walking and cycling as their means of transportation. When the user inputs the emotions and experience type of "relaxation" and "discover new places," the server's AI model generates a mission to "go to the nearest cafe and order a latte." The user's device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and receives points and a certificate. Feedback from the experience is used to generate the next mission.

[0525] Prompt Sentence Examples

[0526] User Input:

[0527] Please enter your user profile information.

[0528] Enter your current mood and type of experience:

[0529] "What is your current mood? (e.g., I want to relax)"

[0530] "What kind of experience are you looking for? (e.g., discovering new places)"

[0531] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0532] Step 1:

[0533] When a user launches the application, the device displays a profile information input screen. Here, the user enters their preferences, interests, available budget, and mode of transportation. This information is temporarily stored on the device and then sent to the server. The server stores the received profile information in a database. The input data is the profile information, and the output data is the profile information stored in the database.

[0534] Step 2:

[0535] When a user attempts to start a mystery quest, the device displays a screen for inputting their current emotions and the type of experience they are seeking. The user may enter, for example, "I want to relax" or "I want to discover new places." This is also temporarily stored on the device and sent to the server. The server stores the received emotions and types of experiences in a database. The input data is the emotion and experience information, and the output data is the emotion and experience information stored in the database.

[0536] Step 3:

[0537] The device uses the geopy library to obtain the user's current location. The device obtains the latitude and longitude information and sends it to the server. The server temporarily stores this location information and uses it in the next step of random mission generation. The input data is the current location, and the output data is the location information sent to the server.

[0538] Step 4:

[0539] The server combines the user's profile information, current emotion, type of experience, and location information to generate an optimal random mission using a generative AI model. For example, a mission such as "drink a specific coffee at the nearest cafe" may be generated. The generated mission is stored on the server and used in the next step. The input data is the profile information, emotion, experience, and location information, and the output data is the generated random mission.

[0540] Step 5:

[0541] The server notifies the device of the generated random mission. The device then displays specific instructions to the user. For example, "Please head to the XX cafe." The device also uses the Google Maps API to provide navigation to the user's destination. The input data is the mission information from the server, and the output data is the instructions notified to the user.

[0542] Step 6:

[0543] After the user completes the mission, the device displays a screen for sharing their experience. The user can review their experience and upload photos. This information is temporarily stored on the device and then sent to the server. The server stores this data in a database. The input data is the user's feedback, and the output data is the feedback information stored in the database.

[0544] Step 7:

[0545] The server calculates the score and certificate based on the user's mission results. The calculation results are sent to the device, which notifies the user. For example, the user can earn XX points or get a new badge. The input data is the user's mission results, and the output data is score and certificate information.

[0546] Step 8:

[0547] The server uses user feedback to create training data to improve the random mission generation method, thereby increasing the accuracy of the next mission generation. The input data is feedback information, and the output data is training data.

[0548] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0549] The present invention is a system for providing new experiences to users' daily lives by generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, making it possible to provide experiences that take the user's emotional state into consideration.

[0550] Program processing

[0551] Creating a profile

[0552] When a user first launches the application, a profile entry screen appears. The user enters information about their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[0553] Entering the status

[0554] Next, when the user starts the mystery quest, the app displays a screen for inputting their current mood and the type of experience they are looking for. For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0555] Random mission generation

[0556] The server uses an AI model based on the user's profile information, current mood, and type of experience, and combines it with an emotion engine to generate random missions. The emotion engine collects emotional data from the user's past feedback, analyzes it, and uses it to generate missions. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0557] Receiving instructions for action

[0558] The device displays the random mission received from the server to the user and provides specific step-by-step instructions. For example, it may provide instructions such as "First, head to the XX cafe," and uses Google Maps APIs to guide the user to their destination. The user follows the instructions to complete the mission.

[0559] Emotion analysis during missions

[0560] The emotion engine analyzes the user's facial expressions and voice in real time while they are completing a mission, recognizing changes in their emotions and allowing it to adjust the difficulty and content of the mission as needed.

[0561] Share your experiences

[0562] After users complete a mission, the app displays an experience sharing screen, prompting them to review their experience and upload photos. Once users finish sharing their experience, their device sends the information to the server, which stores this feedback in a database and uses it as training data for the AI ​​model and emotion engine to generate future missions.

[0563] Rewards and Gamification

[0564] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0565] Specific examples

[0566] Assume that a user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and use walking and cycling as their means of transportation. When the user inputs their mood and experience type, "relaxing" and "discovering new places," the server's AI model uses an emotion engine to generate a mission, "Go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. The emotion engine analyzes the user's facial expressions and voice in real time to monitor the user's emotional state. After completing the mission, the user can share their experience and earn points and badges. Feedback from the experience is used to generate the next mission.

[0567] The system of the present invention provides users with a new personalized experience through the above steps, and by adding an emotion engine, achieves even higher levels of personalization and real-time responses.

[0568] The processing flow will be explained below.

[0569] Step 1: Enter and save your profile information

[0570] User: When the app is launched for the first time, a profile entry screen appears, prompting the user to enter their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (walking, cycling, car, etc.).

[0571] Device: Temporarily stores profile information entered by the user.

[0572] Device: Sends profile information to the server.

[0573] Server: Stores the received profile information in a database.

[0574] Step 2: Enter your current mood and type of experience

[0575] Users: When starting a mystery quest, they input their current mood and the type of experience they are looking for, such as "relaxing" or "seeking an adventurous experience," or "cafe-hopping" or "art appreciation."

[0576] Device: The input mood and type of experience are temporarily stored and sent to the server.

[0577] Server: Stores the received mood and experience type in a database.

[0578] Step 3: Generate a random mission

[0579] Server: Generates random missions using an emotion engine and AI models based on the user's profile information, mood, and type of experience.

[0580] Server (AI model): Analyzes profile information, current mood, and type of experience, and also takes into account emotional data from the emotion engine to generate appropriate random missions, such as "drink a specific latte at the nearest cafe" or "find hidden art in a nearby park."

[0581] Server: Sends generated random missions to the device.

[0582] Step 4: Mission Notification and Action Instructions

[0583] Terminal: Displays the random mission received from the server to the user. For example, it displays instructions such as "First, go to XX Cafe."

[0584] Terminal: Uses Google Maps API etc. to guide the user to their destination.

[0585] User: Follow instructions and complete the mission.

[0586] Step 5: Emotion analysis during the mission

[0587] Emotion engine: Analyzes the user's facial expressions and voice in real time while they are completing a mission, recognizing changes in their emotions.

[0588] Server: Receives the analysis results from the emotion engine and adjusts the difficulty and content of the mission as needed.

[0589] Step 6: Complete the mission and provide feedback

[0590] Users: After completing a mission, they are prompted to review their experience and provide their thoughts and ratings about the experience.

[0591] On your device: The entered feedback is temporarily stored and sent to the server.

[0592] Server: Stores the received feedback in a database and provides it to the AI ​​model and emotion engine as learning data to be used in generating the next mission.

[0593] Step 7: Compensation calculation and notification

[0594] Server: Calculates points and badges based on users' mission completion results.

[0595] Server: Sends calculated points and badge information to the device.

[0596] On the device: Display the received points and badges to the user. For example, display "You've earned XX points!" or "You've earned a new badge!"

[0597] Users: See the rewards and get motivated for the next mission.

[0598] Through these steps, the system of the present invention provides users with a new personalized experience, and by adding an emotion engine, it achieves even higher levels of personalization and real-time responses.

[0599] Example 2

[0600] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0601] Conventional user experience provision systems lack the ability to customize the experience to take into account the user's emotional state and real-time feedback, making it difficult to provide the optimal experience for the user. Furthermore, there is a need to automatically generate new experiences tailored to individual users by effectively utilizing user profile information and feedback.

[0602] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions using a generation AI model based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions, means for inputting and saving results and feedback of the random missions performed by the user, means for awarding points and badges based on the user's mission results, means for analyzing the user's facial expressions, voice, etc. to recognize the user's emotional state in real time and adjust the missions, and means for creating learning data for improving the random mission generation means using user feedback. This makes it possible to provide an optimal, customized experience for each user, taking into account the user's emotional state and real-time feedback.

[0603] "Profile information" is personal information such as a user's preferences, budget, mode of transportation, etc.

[0604] "Mood" refers to the emotions and psychological state that a user is currently experiencing.

[0605] "Experience type" means the specific activity or category of activity that a user is seeking.

[0606] A "generative AI model" is an algorithm or program that uses artificial intelligence to generate missions based on a user's profile information, mood, and type of experience.

[0607] "Random missions" refer to specific activities or tasks provided to users by generative AI models.

[0608] "Notification" refers to the method or means for informing the user of the generated random mission.

[0609] "Feedback" refers to the evaluation, impressions, and reactions provided by the user regarding the random mission they have completed.

[0610] "Points" refer to points or scores that a user receives as a reward for completing a mission.

[0611] A "badge" is a recognition or award that a user can earn by completing a specific mission.

[0612] An "emotion engine" is a technology or program that analyzes a user's facial expressions and voice to recognize their emotional state.

[0613] "Real-time recognition" means detecting and analyzing the user's emotional state instantly.

[0614] "Training data" refers to data that the system uses to improve its AI model based on user feedback.

[0615] A "database" is a digital warehouse for organizing and storing information such as profile information and feedback.

[0616] The present invention is a system for providing new experiences to users' daily lives by generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, making it possible to provide experiences that take the user's emotional state into consideration.

[0617] The system of the present invention begins when a user launches the application on a device such as a smartphone or tablet. The device first displays a profile information input screen, and the user enters information such as their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). This information is temporarily stored on the device and then sent to the server. The server stores the received information in a database.

[0618] Next, when the user starts the mystery quest, the device displays a screen for inputting their current mood and the type of experience they are looking for. The user can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." This information is also temporarily stored on the device and sent to the server.

[0619] The server uses a generative AI model based on the received profile information, current mood, and type of experience to generate random missions in combination with the emotion engine. The emotion engine analyzes emotional data collected from past feedback and generates missions based on this. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0620] The device displays the random mission received from the server to the user. It provides specific step-by-step instructions, such as "First, head to the XX cafe." The device uses the Google Maps API to guide the user to their destination. The user then follows these instructions to complete the mission.

[0621] While the user is completing a mission, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. The difficulty and content of the mission can be adjusted as needed. After the mission is completed, the device displays an experience sharing screen, prompting the user to review their experience and upload photos. Once the user has finished sharing their experience, the device sends the information to the server. The server stores the received feedback in a database and uses it to generate future missions.

[0622] Furthermore, the server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the points and badges to the user, giving them a sense of accomplishment. For example, it displays "You've earned XX points!" or "You've earned a new badge!"

[0623] Specific examples

[0624] If a user's profile information indicates that they like cafe hopping and art appreciation, their budget is under 2,000 yen, and their transportation methods are walking and cycling, and the user enters "relax" and "discover new places," the server's generative AI model uses this information to generate a mission using an emotion engine: "Go to the nearest cafe and order a latte." The device displays this mission and uses the Google Maps API to provide directions to the cafe. While the user is completing the mission, the emotion engine analyzes the user's emotional state in real time. After completing the mission, the user reviews their experience and earns points and badges. This post-experience feedback is used to generate the next mission.

[0625] Prompt Sentence Examples

[0626] An example of a prompt is:

[0627] User profile information:

[0628] Hobbies: Cafe hopping, art appreciation

[0629] Budget: Under 2,000 yen

[0630] Transportation: walking, cycling

[0631] Current mood: Relaxed

[0632] Experience you're looking for: Discover new places

[0633] Please suggest three possible missions to generate.

[0634] As described above, the system of the present invention makes it possible to provide an individually optimized experience based on the user's profile information and real-time emotion analysis.

[0635] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0636] Step 1: Launch the application and enter profile information

[0637] The user launches the application on their smartphone or tablet. The device displays a screen for entering profile information. The user enters information such as their preferences (e.g., cafe hopping, art appreciation), budget (e.g., under 2,000 yen), and mode of transportation (e.g., walking, cycling). This input information is temporarily stored on the device. The device then sends this temporarily stored information to the server. The server stores the received profile information in a database. The input is the user's profile information, and the output is the user information stored in the database.

[0638] Step 2: Enter your current mood and type of experience

[0639] When a user starts a mystery quest, the device displays a screen for inputting their current mood and the type of experience they are seeking. Users input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," and the type of experience, such as "cafe hopping" or "art appreciation." This information is also temporarily stored on the device and sent to the server. The input is the current mood and type of experience, and the output is the state information sent to the server.

[0640] Step 3: Generate a random mission

[0641] The server generates random missions using a generative AI model based on the received profile information, current mood, and type of experience. The emotion engine analyzes emotional data collected from past feedback and reflects this in the generation of missions. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "search for hidden art in a nearby park." The server sends the generated missions to the device. The inputs are the user's profile information, current mood, type of experience, and past feedback, and the output is the generated random mission.

[0642] Step 4: Announce the random mission and provide instructions

[0643] The device displays the random mission received from the server to the user. It provides specific step-by-step instructions, such as "First, head to the XX cafe." The device uses the Google Maps API to guide the user along the route to their destination. The user then follows these instructions to complete the mission. The input is the generated random mission, and the output is the instructions and guidance communicated to the user.

[0644] Step 5: Emotion analysis during the mission

[0645] While the user is completing a mission, the emotion engine analyzes the user's facial expressions and voice in real time to recognize changes in emotion. The emotion engine can adjust the difficulty and content of the mission as needed. The input is the user's emotion data collected in real time, and the output is updated mission content and difficulty.

[0646] Step 6: Share your experience and provide feedback

[0647] When a user completes a mission, the device displays an experience sharing screen and prompts the user to review the experience and upload photos. When the user finishes sharing their experience, the device sends the information to the server. The server stores the received feedback in a database to help generate future missions. The input is the user's experience review and photos, and the output is the feedback stored in the database.

[0648] Step 7: Calculating and notifying rewards

[0649] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the points and badges to the user, giving them a sense of accomplishment. For example, it displays "You've earned XX points!" or "You've earned a new badge!" The input is the user's mission results, and the output is the calculated points and badge information.

[0650] (Application example 2)

[0651] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0652] Conventional systems have had difficulty taking into account users' emotions and real-time information when providing new experiences to users' daily lives. In particular, systems must respond appropriately to dynamic changes in the user's mood and emotions. Furthermore, they lack the ability to provide navigation and specific instructions during the generated mission. These issues result in a decline in the quality of the user's experience and a decrease in satisfaction.

[0653] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0654] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions, means for inputting and saving results of the random missions performed by the user and feedback, means for awarding points and badges based on the user's mission results, means for performing emotion analysis to recognize the user's emotional state, means for providing guidance while the user is completing the missions in real time, map service means for providing route guidance based on the generated missions, and means for creating data for training the mission generation means using feedback. This makes it possible to provide missions adapted to the user's emotions and current situation, thereby achieving a higher level of personalization and improved quality of experience.

[0655] "Profile information" is information specific to a user, such as preferences, budget, and mode of transportation, and is the basic data that allows the system to provide the user with an optimal experience.

[0656] "Mood" refers to the user's current emotional state, and is a factor that affects the content of the random missions provided by the system.

[0657] "Type of experience" refers to the category of specific activities or events that the user desires, such as "cafe hopping" or "art appreciation."

[0658] "Random Missions" refer to specific tasks or activities that are generated based on the user's profile information and current mood and type of experience, and are designed to provide the user with new discoveries and experiences.

[0659] "Notification means" refers to the method by which the system notifies the user of the random missions generated, and includes smartphone apps, notification messages, etc.

[0660] "Feedback" refers to the user's evaluation and impressions of the random mission they performed, and is data collected for the system to use in generating the next mission.

[0661] "Points" are a type of reward that users can earn by completing random missions, and form part of the benefits and reward system that can be used within the app.

[0662] A "badge" is a digital medal or symbol awarded to users who achieve certain conditions or missions, and serves to enhance the user's sense of accomplishment as part of gamification.

[0663] "Emotion analysis" is a technology that analyzes a user's facial expressions and voice data in real time to recognize their current emotional state, and is used by the system to dynamically adjust the content of the mission.

[0664] The "map service" is a function that guides users to their destination when they are completing random missions, and uses location information services and navigation systems.

[0665] "Learning data" is data that is used to improve the next random mission generation method based on feedback collected from users, and is used to improve the accuracy of the AI ​​model.

[0666] A "server" is a computer system that stores and processes various data such as user profile information, feedback, and mission generation.

[0667] The system for implementing the present invention has functions for providing new experiences to users in their daily lives. This system has the following main functions in particular:

[0668] 1. Create a profile

[0669] When a user uses the system for the first time, they enter profile information through their smartphone. The input items include preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[0670] 2. Enter your mood and experience type

[0671] When a user starts a mission, they are prompted to enter their current mood (e.g., "I want to relax") and the type of experience (e.g., "cafe hopping"). The device temporarily stores this information and sends it to the server.

[0672] 3. Random mission generation

[0673] The server generates random missions using a generative AI model and sentiment analysis engine based on the user's profile information, current mood, and type of experience. For example, a specific task such as "Go to the nearest cafe and order a latte" is automatically generated.

[0674] 4. Mission Notification and Navigation

[0675] The device notifies the user of the random mission received from the server and provides route guidance to the destination using Google Maps API. The device guides the user step by step and assists the user in completing the mission.

[0676] 5. Emotion analysis

[0677] While the user is completing a mission, the emotion analysis engine analyzes the user's facial expressions and voice via the device's camera and microphone, recognizing their emotional state in real time. This makes it possible to adjust the content and difficulty of the mission according to the user's emotional state.

[0678] 6. Share your experiences

[0679] After users complete a mission, they are shown an experience sharing screen where they can review their experience and upload photos. This information is sent to the server and stored in a database. The feedback is used to generate the next mission.

[0680] 7. Rewards and Gamification

[0681] The server calculates points and badges based on the user's mission results and sends them to the device, allowing the user to visually check their progress and sense of accomplishment.

[0682] Hardware and software used

[0683] Hardware

[0684] Smartphone (iOS / Android)

[0685] software

[0686] Flask: a server-side web framework

[0687] Firestore: Used as a database

[0688] Google Cloud Translation API: For multilingual support

[0689] Google Maps API: for navigation

[0690] Emotion analysis engine: Analyzes the user's facial expressions and voice data

[0691] Specific examples

[0692] For example, if a user's profile information states "I like cafe hopping and art appreciation, my budget is under 2,000 yen, and my transportation methods are walking and cycling," and the user inputs the mood and experience type of "relaxation" and "discover new places," the server's generative AI model and sentiment analysis engine will generate a mission of "go to the nearest cafe and order a latte." The device will display this mission and use the Google Maps API to guide the user to the cafe. After completing the mission, the user can share their experience and earn points and badges.

[0693] Prompt Sentence Examples

[0694] Generate the perfect mission for a user who likes "cafe hopping" and is in the mood to "relax." For example, a mission to go to the nearest cafe and order a latte. What other missions would you generate?

[0695] The present invention allows users to enjoy an experience that is individually customized, and is expected to provide a more engaging experience through real-time responses and reward systems that respond to emotions.

[0696] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0697] Step 1:

[0698] A user downloads and launches a smartphone app. First, the user is guided to a screen where they can enter their profile information. Here, they enter information such as their preferences, budget, and mode of transportation. The device temporarily stores this information, formats the input data, and sends it to the server. The server stores the received profile information in a database and returns the results. The input to this step is the user's profile information, and the output is the profile information stored in the database.

[0699] Step 2:

[0700] When a user starts "Discovery Mode," a screen appears asking them to enter their current mood and the type of experience they are looking for. For example, they can enter information such as "I want to relax," "I'm looking for an adventurous experience," "I want to go café-hopping," or "I want to appreciate art." The device collects this information and sends it to the server. The server processes this information and stores it as base data for generating random missions. The input for this step is the user's current mood and the type of experience, and the output is base data for generating random missions.

[0701] Step 3:

[0702] The server uses a generative AI model based on the profile information, current mood, and experience type, combined with a sentiment analysis engine, to generate a random mission. For example, a specific mission such as "Go to the nearest cafe and order a latte" is generated. The server generates this random mission and sends it to the device. The input of this step is the profile information, mood, and experience type, and the output is the generated random mission.

[0703] Step 4:

[0704] The device notifies the user of the random mission received from the server. Specifically, it displays the details of the mission on the screen and provides the user with specific instructions. For example, instructions such as "First, go to the nearest cafe" are displayed. The device uses the Google Maps API to guide the user to their destination. The input of this step is the generated random mission, and the output is a notification of the mission and navigation instructions to the user.

[0705] Step 5:

[0706] While the user is performing the mission, the device collects facial expressions and voice data through a camera and microphone, and analyzes the user's emotional state in real time using an emotion analysis engine. The server uses this emotional data to adjust the content and difficulty of the mission. The input for this step is the user's facial and voice data, and the output is the real-time emotion analysis results.

[0707] Step 6:

[0708] After the user completes the mission, an experience sharing screen appears. The user reviews the mission experience and uploads photos. The device collects this feedback data and sends it to the server. The server stores it in a database and uses it as learning data for the next random mission generation. The input of this step is the user's feedback, and the output is the feedback data stored in the database.

[0709] Step 7:

[0710] The server calculates points and badges based on the user's mission results and sends the information to the device. The device displays information about the points and badges to the user, giving them a sense of accomplishment. For example, messages such as "You've earned XX points!" or "You've earned a new badge!" are displayed. The input of this step is the user's mission results, and the output is point and badge information.

[0711] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0712] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0713] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0714] [Third embodiment]

[0715] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0716] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0717] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0718] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0719] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0720] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0721] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0722] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0723] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0724] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0725] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0726] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0727] The present invention is a system for providing new experiences to users' daily lives, generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries.

[0728] Program processing

[0729] Creating a profile

[0730] When a user first launches the application, a profile entry screen appears. The user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[0731] Entering the status

[0732] Next, when the user starts the mystery quest, the app displays a screen for inputting their current mood and the type of experience they are looking for. For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0733] Random mission generation

[0734] The server uses an AI model to generate appropriate random missions based on the user's profile information, current mood, and type of experience. For example, the server might generate missions such as "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0735] Receiving instructions for action

[0736] The device displays the random mission received from the server to the user and provides step-by-step instructions for specific actions. For example, it instructs the user on each action, such as "First, head to the XX cafe." It also uses Google Maps APIs and other tools to provide route guidance to the user's destination.

[0737] Share your experiences

[0738] After users complete a mission, the app displays an experience sharing screen, prompting them to review their experience and upload photos. Once users finish sharing their experience, their device sends the information to the server, which stores this feedback in a database and uses it to refine the AI ​​model for future mission generation.

[0739] Rewards and Gamification

[0740] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0741] Specific examples

[0742] The user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and prefer walking and cycling as their means of transportation. When the user inputs their mood and type of experience, "relaxing" and "discovering new places," the server's AI model generates a mission to "go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and earns points and badges. Feedback from the experience is used to generate the next mission.

[0743] The system of the present invention provides new experiences tailored to the individual needs and circumstances of users, bringing a breath of fresh air to everyday life while also achieving a high level of personalization and real-time response.

[0744] The processing flow will be explained below.

[0745] Step 1: Enter and save your profile information

[0746] User: When the app is launched for the first time, a profile entry screen appears, prompting the user to enter information such as preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation.

[0747] Device: Temporarily stores profile information entered by the user.

[0748] Device: Sends profile information to the server.

[0749] Server: Stores the received profile information in a database.

[0750] Step 2: Enter your current mood and type of experience

[0751] User: When starting a Mystery Quest, you input your current mood and the type of experience you are seeking.

[0752] Device: The input mood and type of experience are temporarily stored and sent to the server.

[0753] Server: Stores the received mood and experience type in a database.

[0754] Step 3: Generate a random mission

[0755] Server: Instructs the AI ​​model to generate random missions based on the user's profile information, mood, and type of experience.

[0756] Server (AI model): Analyzes profile information, current mood, and type of experience to generate appropriate random missions, such as "drink a specific coffee at the nearest cafe" or "find hidden art."

[0757] Server: Sends generated random missions to the device.

[0758] Step 4: Mission Notification and Action Instructions

[0759] Terminal: Displays the random mission received from the server to the user. For example, it displays instructions such as "First, go to XX Cafe."

[0760] Terminal: Uses Google Maps API etc. to guide the user to their destination.

[0761] User: Follow instructions and complete the mission.

[0762] Step 5: Complete the mission and provide feedback

[0763] Users: After completing a mission, they will be prompted to share their experience and provide a rating and feedback.

[0764] On your device: The entered feedback is temporarily stored and sent to the server.

[0765] Server: Stores the received feedback in a database and provides it to the AI ​​model as learning data to be used in generating the next mission.

[0766] Step 6: Compensation calculation and notification

[0767] Server: Calculates points and badges based on users' mission completion results.

[0768] Server: Sends calculated points and badge information to the device.

[0769] On the device: Display the received points and badges to the user. For example, display "You've earned XX points!" or "You've earned a new badge!"

[0770] Users: See the rewards and get motivated for the next mission.

[0771] Through these steps, this system provides users with a new, customized experience, bringing a breath of fresh air to everyday life.

[0772] Example 1

[0773] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0774] In modern society, many people seek new experiences in their daily lives, but finding time for them can be challenging. Furthermore, it is difficult to provide optimal experiences tailored to the needs and circumstances of every individual user. Conventional systems often only offer pre-determined courses and experiences, and do not adequately provide dynamic experiences based on individual users' current moods and interests. In light of these challenges, the present invention aims to provide a system that dynamically generates random missions based on a user's profile information and current moods and interests, thereby providing a highly personalized experience.

[0775] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0776] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions using a generative AI model based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions and providing action instructions, means for inputting and saving the results and feedback of the user's random missions, and means for awarding points and badges based on the user's mission results. This allows users to enjoy new experiences based on their current moods and interests. Furthermore, the system is continuously improved based on feedback, enabling it to provide more accurate experiences.

[0777] Below are definitions of important terms included in the claims we just rewrote.

[0778] "Profile information" is information about a user, including the user's preferences, interests, available budget, transportation options, and the like.

[0779] "Mood" refers to the psychological state the user is feeling at that time and the type of experience they desire.

[0780] "Type of experience" refers to the specific genre of activity or event that the user desires.

[0781] A "generative AI model" is an algorithm that uses machine learning to generate optimal random missions based on a user's profile information and current mood.

[0782] "Random Missions" are tasks and activities that are dynamically generated based on the user's profile information and current mood.

[0783] "Action instructions" is information indicating specific steps and action guidance required for the user to complete the random mission.

[0784] "Feedback" refers to a record of impressions, ratings, photos, etc. provided by a user after completing a random mission.

[0785] "Points" are a type of reward given to users as a result of completing random missions, and are accumulated to function as an incentive.

[0786] "Badges" are digital rewards that visually represent a user's achievements and are awarded for completing specific missions or achieving certain results.

[0787] The present invention is a system for providing new experiences to users' daily lives, generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries.

[0788] This system is composed of two main components: a server and a terminal. The server is responsible for generating random missions using a generative AI model based on the user's profile information, current mood, and type of experience. The terminal is a device directly operated by the user, and is responsible for inputting profile information, displaying random missions, providing action instructions, and inputting feedback after completing a mission.

[0789] Creating a profile

[0790] When a user first launches the application, a profile information entry screen appears on the device. Here, the user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server stores the received profile information in a database.

[0791] Entering the status

[0792] Next, when the user starts the mystery quest, the app displays a screen on the device for inputting their current mood and the type of experience they are looking for. For example, the user can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0793] Random mission generation

[0794] The server uses a generative AI model to generate an appropriate random mission based on the user's profile information, current mood, and type of experience. For example, missions such as "Drink a specific coffee at the nearest cafe" or "Find hidden art in a nearby park" may be generated. An example prompt is, "The user's profile information states that they like to visit cafes and appreciate art, their budget is under 2,000 yen, their transportation method is walking and cycling, their current mood is relaxation, and they want to discover new places. Please generate an appropriate random mission based on this information." The server then sends the generated mission to the device.

[0795] Receiving instructions for action

[0796] The device displays the random mission received from the server to the user and provides step-by-step instructions for specific actions. For example, it instructs the user on each action, such as "First, head to the XX cafe." It also uses Google Maps APIs and other tools to provide route guidance to the user's destination.

[0797] Collecting feedback

[0798] After a user completes a mission, the app displays an experience sharing screen, prompting the user to review the experience and upload photos. Once the user has finished sharing their experience, the device sends the information to the server, which stores this feedback in a database and uses it to refine the generative AI model for future mission generation.

[0799] Rewards and Gamification

[0800] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0801] As a concrete example, consider a user's profile information, which includes preferences for cafe hopping and art appreciation, a budget of less than 2,000 yen, and transportation methods of walking and cycling. When the user inputs the mood and type of experience, "relaxing" and "discovering new places," the server's generative AI model generates a mission, "Go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and earns points and badges. This feedback is used to generate the next mission.

[0802] The system of the present invention provides new experiences tailored to the individual needs and circumstances of users, bringing a breath of fresh air to everyday life while also achieving a high level of personalization and real-time response.

[0803] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0804] Step 1: Enter and save your profile information

[0805] When a user launches the application, the device displays a profile entry screen where the user can enter information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car).

[0806] The entered profile information is temporarily stored in the terminal's memory, and then the terminal transmits this information to the server.

[0807] The server stores the received profile information in a database. The input here is the user's profile information, and the output is the profile information stored in the database. The server uses this information as the basis for generating random missions later.

[0808] Step 2: Enter and save your mood and experience type

[0809] When a user starts a mystery quest, the device displays a screen for inputting the mood and type of experience.

[0810] For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation."

[0811] The input information is temporarily stored on the terminal, which then transmits it to the server.

[0812] The server stores the received information in a database, where the input is the mood and experience type entered by the user, and the output is the mood and experience type stored in the database.

[0813] Step 3: Generate a random mission

[0814] The server generates random missions using a generative AI model based on the user's profile information and their current mood and type of experience.

[0815] Specifically, the generative AI model is given the following prompt: "The user's profile information states that they like to visit cafes and appreciate art, their budget is under 2000 yen, their preferred mode of transportation is walking and cycling, their current mood is relaxation, and they want to discover new places. Based on this information, please generate an appropriate random mission."

[0816] The generative AI model performs data calculations based on this prompt sentence and generates a random mission.

[0817] The server sends the generated random mission to the device, where the input is the profile information and the type of mood and experience, and the output is the generated random mission.

[0818] Step 4: View and receive action instructions

[0819] The terminal displays the random mission received from the server to the user.

[0820] Furthermore, it provides step-by-step, specific instructions for each action, such as "First, go to the XX cafe."

[0821] The device also provides users with route guidance to their destination using Google Maps API etc. The input here is a random mission sent from the server, and the output is action instructions displayed to the user.

[0822] Step 5: Mission Accomplishment

[0823] The user carries out the mission by following the action instructions provided by the terminal.

[0824] For example, the user completes the mission by arriving at a certain cafe and ordering a latte. Here, the input is an action instruction, and the output is the completion of the mission.

[0825] Step 6: Collect and store feedback

[0826] After completing a mission, the device displays an experience sharing screen where users can review their experience and upload photos.

[0827] For example, you could enter, "The latte at XX Cafe was very delicious." Once the user has finished entering their feedback, the device sends the information to the server.

[0828] The server stores this feedback in a database and uses it as data to refine the generative AI model for future mission generation. The input here is the user's feedback information, and the output is the feedback information stored in the database.

[0829] Step 7: Rewards and Gamification

[0830] The server calculates points and badges based on the user's mission results.

[0831] For example, a user can be awarded 50 points for the achievement of "finding a hidden art." The server sends this to the device, which then displays "You've earned 50 points!" or "You've earned a new badge!" to the user. The input here is the user's mission result, and the output is the calculated points or badge information.

[0832] Through the above processing steps, the system can provide a new experience that suits the user's current mood and interests.

[0833] (Application example 1)

[0834] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0835] The present invention aims to provide users with new experiences in their daily lives. Specifically, it aims to generate customized random missions based on the user's profile information, current emotions, and type of experience, and present them to the user, allowing them to experience new discoveries and excitement. It is also desirable to improve the quality of future missions based on the results and feedback of the missions completed by the user.

[0836] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0837] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current emotions and types of experiences, means for acquiring user location information, means for generating optimal random missions based on the profile information, the current emotions and types of experiences, and the location information, means for notifying the user of the generated random missions, means for inputting and saving the results of the random missions performed by the user and feedback, means for awarding points and certificates based on the user's mission results, and means for creating training data to improve the random mission generation means using user feedback. This allows users to have a new, customized experience, promoting use of physical stores and providing opportunities for new discoveries.

[0838] "User profile information" is information about a user's preferences, interests, available budget, and transportation options.

[0839] "Current Emotion" is information about the user's mood at the time they start the mystery quest and the type of experience they are seeking.

[0840] "Random Missions" are tasks and activities customized based on a user's profile information, current emotions, and type of experience.

[0841] "Information storage device" is a general term for hardware and software for storing information, including databases.

[0842] "Score" refers to points that a user can earn by completing a mission.

[0843] A "certificate" is a badge or title that proves that a user has completed a mission.

[0844] "Location information" is information about the latitude and longitude of the user's current location.

[0845] "Training data" is learning data used to improve the random mission generation means based on user feedback.

[0846] The present invention is a system for providing new experiences to users' daily lives. This system generates customized random missions based on the user's profile information, current emotions, and type of experience, and encourages new discoveries by having the user carry out the missions.

[0847] Main system components

[0848] The main components include the following:

[0849] User device: Smartphone

[0850] Server: Contains the database and AI model

[0851] Geographic information acquisition systems: Libraries such as geopy

[0852] Random mission generation system: uses generative AI models

[0853] Program processing explanation

[0854] 1. Enter and save your user profile information

[0855] When a user device first launches the application, the user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, budget, and transportation. This information is temporarily stored and sent to the server, which stores the profile information in a database.

[0856] 2. Input and save the current emotion and type of experience

[0857] When starting a mystery quest, the user's device will prompt them to input their current emotions and the type of experience they are seeking. For example, they can input "I want to relax" or "I want to discover new places." This input is also temporarily stored and sent to the server.

[0858] 3. Obtaining location information

[0859] The user device uses the geopy library to obtain the current location information (latitude and longitude) and sends it to the server.

[0860] 4. Random mission generation

[0861] The server uses a generative AI model based on profile information, current emotions, type of experience, and location information to generate an appropriate random mission, such as "drink a specific coffee at the nearest cafe."

[0862] 5. Mission Notification and Instructions

[0863] The system notifies the user of the randomly generated mission and provides specific instructions for action. It also provides route guidance using Google Maps APIs and other tools.

[0864] 6. Gather feedback after completing the mission

[0865] After users complete a mission, they are presented with a shared experience screen where they can review their experience and upload photos. This feedback is sent to the server and stored in a database.

[0866] 7. Awarding of Scores and Certificates

[0867] The server calculates the score and certificate based on the user's mission results and notifies the user's terminal, allowing the user to feel a sense of accomplishment.

[0868] Specific examples

[0869] The user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and use walking and cycling as their means of transportation. When the user inputs the emotions and experience type of "relaxation" and "discover new places," the server's AI model generates a mission to "go to the nearest cafe and order a latte." The user's device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and receives points and a certificate. Feedback from the experience is used to generate the next mission.

[0870] Prompt Sentence Examples

[0871] User Input:

[0872] Please enter your user profile information.

[0873] Enter your current mood and type of experience:

[0874] "What is your current mood? (e.g., I want to relax)"

[0875] "What kind of experience are you looking for? (e.g., discovering new places)"

[0876] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0877] Step 1:

[0878] When a user launches the application, the device displays a profile information input screen. Here, the user enters their preferences, interests, available budget, and mode of transportation. This information is temporarily stored on the device and then sent to the server. The server stores the received profile information in a database. The input data is the profile information, and the output data is the profile information stored in the database.

[0879] Step 2:

[0880] When a user attempts to start a mystery quest, the device displays a screen for inputting their current emotions and the type of experience they are seeking. The user may enter, for example, "I want to relax" or "I want to discover new places." This is also temporarily stored on the device and sent to the server. The server stores the received emotions and types of experiences in a database. The input data is the emotion and experience information, and the output data is the emotion and experience information stored in the database.

[0881] Step 3:

[0882] The device uses the geopy library to obtain the user's current location. The device obtains the latitude and longitude information and sends it to the server. The server temporarily stores this location information and uses it in the next step of random mission generation. The input data is the current location, and the output data is the location information sent to the server.

[0883] Step 4:

[0884] The server combines the user's profile information, current emotion, type of experience, and location information to generate an optimal random mission using a generative AI model. For example, a mission such as "drink a specific coffee at the nearest cafe" may be generated. The generated mission is stored on the server and used in the next step. The input data is the profile information, emotion, experience, and location information, and the output data is the generated random mission.

[0885] Step 5:

[0886] The server notifies the device of the generated random mission. The device then displays specific instructions to the user. For example, "Please head to the XX cafe." The device also uses the Google Maps API to provide navigation to the user's destination. The input data is the mission information from the server, and the output data is the instructions notified to the user.

[0887] Step 6:

[0888] After the user completes the mission, the device displays a screen for sharing their experience. The user can review their experience and upload photos. This information is temporarily stored on the device and then sent to the server. The server stores this data in a database. The input data is the user's feedback, and the output data is the feedback information stored in the database.

[0889] Step 7:

[0890] The server calculates the score and certificate based on the user's mission results. The calculation results are sent to the device, which notifies the user. For example, the user can earn XX points or get a new badge. The input data is the user's mission results, and the output data is score and certificate information.

[0891] Step 8:

[0892] The server uses user feedback to create training data to improve the random mission generation method, thereby increasing the accuracy of the next mission generation. The input data is feedback information, and the output data is training data.

[0893] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0894] The present invention is a system for providing new experiences to users' daily lives by generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, making it possible to provide experiences that take the user's emotional state into consideration.

[0895] Program processing

[0896] Creating a profile

[0897] When a user first launches the application, a profile entry screen appears. The user enters information about their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[0898] Entering the status

[0899] Next, when the user starts the mystery quest, the app displays a screen for inputting their current mood and the type of experience they are looking for. For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[0900] Random mission generation

[0901] The server uses an AI model based on the user's profile information, current mood, and type of experience, and combines it with an emotion engine to generate random missions. The emotion engine collects emotional data from the user's past feedback, analyzes it, and uses it to generate missions. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0902] Receiving instructions for action

[0903] The device displays the random mission received from the server to the user and provides specific step-by-step instructions. For example, it may provide instructions such as "First, head to the XX cafe," and uses Google Maps APIs to guide the user to their destination. The user follows the instructions to complete the mission.

[0904] Emotion analysis during missions

[0905] The emotion engine analyzes the user's facial expressions and voice in real time while they are completing a mission, recognizing changes in their emotions and allowing it to adjust the difficulty and content of the mission as needed.

[0906] Share your experiences

[0907] After users complete a mission, the app displays an experience sharing screen, prompting them to review their experience and upload photos. Once users finish sharing their experience, their device sends the information to the server, which stores this feedback in a database and uses it as training data for the AI ​​model and emotion engine to generate future missions.

[0908] Rewards and Gamification

[0909] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[0910] Specific examples

[0911] Assume that a user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and use walking and cycling as their means of transportation. When the user inputs their mood and experience type, "relaxing" and "discovering new places," the server's AI model uses an emotion engine to generate a mission, "Go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. The emotion engine analyzes the user's facial expressions and voice in real time to monitor the user's emotional state. After completing the mission, the user can share their experience and earn points and badges. Feedback from the experience is used to generate the next mission.

[0912] The system of the present invention provides users with a new personalized experience through the above steps, and by adding an emotion engine, achieves even higher levels of personalization and real-time responses.

[0913] The processing flow will be explained below.

[0914] Step 1: Enter and save your profile information

[0915] User: When the app is launched for the first time, a profile entry screen appears, prompting the user to enter their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (walking, cycling, car, etc.).

[0916] Device: Temporarily stores profile information entered by the user.

[0917] Device: Sends profile information to the server.

[0918] Server: Stores the received profile information in a database.

[0919] Step 2: Enter your current mood and type of experience

[0920] Users: When starting a mystery quest, they input their current mood and the type of experience they are looking for, such as "relaxing" or "seeking an adventurous experience," or "cafe-hopping" or "art appreciation."

[0921] Device: The input mood and type of experience are temporarily stored and sent to the server.

[0922] Server: Stores the received mood and experience type in a database.

[0923] Step 3: Generate a random mission

[0924] Server: Generates random missions using an emotion engine and AI models based on the user's profile information, mood, and type of experience.

[0925] Server (AI model): Analyzes profile information, current mood, and type of experience, and also takes into account emotional data from the emotion engine to generate appropriate random missions, such as "drink a specific latte at the nearest cafe" or "find hidden art in a nearby park."

[0926] Server: Sends generated random missions to the device.

[0927] Step 4: Mission Notification and Action Instructions

[0928] Terminal: Displays the random mission received from the server to the user. For example, it displays instructions such as "First, go to XX Cafe."

[0929] Terminal: Uses Google Maps API etc. to guide the user to their destination.

[0930] User: Follow instructions and complete the mission.

[0931] Step 5: Emotion analysis during the mission

[0932] Emotion engine: Analyzes the user's facial expressions and voice in real time while they are completing a mission, recognizing changes in their emotions.

[0933] Server: Receives the analysis results from the emotion engine and adjusts the difficulty and content of the mission as needed.

[0934] Step 6: Complete the mission and provide feedback

[0935] Users: After completing a mission, they are prompted to review their experience and provide their thoughts and ratings about the experience.

[0936] On your device: The entered feedback is temporarily stored and sent to the server.

[0937] Server: Stores the received feedback in a database and provides it to the AI ​​model and emotion engine as learning data to be used in generating the next mission.

[0938] Step 7: Compensation calculation and notification

[0939] Server: Calculates points and badges based on users' mission completion results.

[0940] Server: Sends calculated points and badge information to the device.

[0941] On the device: Display the received points and badges to the user. For example, display "You've earned XX points!" or "You've earned a new badge!"

[0942] Users: See the rewards and get motivated for the next mission.

[0943] Through these steps, the system of the present invention provides users with a new personalized experience, and by adding an emotion engine, it achieves even higher levels of personalization and real-time responses.

[0944] Example 2

[0945] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0946] Conventional user experience provision systems lack the ability to customize the experience to take into account the user's emotional state and real-time feedback, making it difficult to provide the optimal experience for the user. Furthermore, there is a need to automatically generate new experiences tailored to individual users by effectively utilizing user profile information and feedback.

[0947] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions using a generation AI model based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions, means for inputting and saving results and feedback of the random missions performed by the user, means for awarding points and badges based on the user's mission results, means for analyzing the user's facial expressions, voice, etc. to recognize the user's emotional state in real time and adjust the missions, and means for creating learning data for improving the random mission generation means using user feedback. This makes it possible to provide an optimal, customized experience for each user, taking into account the user's emotional state and real-time feedback.

[0948] "Profile information" is personal information such as a user's preferences, budget, mode of transportation, etc.

[0949] "Mood" refers to the emotions and psychological state that a user is currently experiencing.

[0950] "Experience type" means the specific activity or category of activity that a user is seeking.

[0951] A "generative AI model" is an algorithm or program that uses artificial intelligence to generate missions based on a user's profile information, mood, and type of experience.

[0952] "Random missions" refer to specific activities or tasks provided to users by generative AI models.

[0953] "Notification" refers to the method or means for informing the user of the generated random mission.

[0954] "Feedback" refers to the evaluation, impressions, and reactions provided by the user regarding the random mission they have completed.

[0955] "Points" refer to points or scores that a user receives as a reward for completing a mission.

[0956] A "badge" is a recognition or award that a user can earn by completing a specific mission.

[0957] An "emotion engine" is a technology or program that analyzes a user's facial expressions and voice to recognize their emotional state.

[0958] "Real-time recognition" means detecting and analyzing the user's emotional state instantly.

[0959] "Training data" refers to data that the system uses to improve its AI model based on user feedback.

[0960] A "database" is a digital warehouse for organizing and storing information such as profile information and feedback.

[0961] The present invention is a system for providing new experiences to users' daily lives by generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, making it possible to provide experiences that take the user's emotional state into consideration.

[0962] The system of the present invention begins when a user launches the application on a device such as a smartphone or tablet. The device first displays a profile information input screen, and the user enters information such as their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). This information is temporarily stored on the device and then sent to the server. The server stores the received information in a database.

[0963] Next, when the user starts the mystery quest, the device displays a screen for inputting their current mood and the type of experience they are looking for. The user can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." This information is also temporarily stored on the device and sent to the server.

[0964] The server uses a generative AI model based on the received profile information, current mood, and type of experience to generate random missions in combination with the emotion engine. The emotion engine analyzes emotional data collected from past feedback and generates missions based on this. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[0965] The device displays the random mission received from the server to the user. It provides specific step-by-step instructions, such as "First, head to the XX cafe." The device uses the Google Maps API to guide the user to their destination. The user then follows these instructions to complete the mission.

[0966] While the user is completing a mission, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. The difficulty and content of the mission can be adjusted as needed. After the mission is completed, the device displays an experience sharing screen, prompting the user to review their experience and upload photos. Once the user has finished sharing their experience, the device sends the information to the server. The server stores the received feedback in a database and uses it to generate future missions.

[0967] Furthermore, the server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the points and badges to the user, giving them a sense of accomplishment. For example, it displays "You've earned XX points!" or "You've earned a new badge!"

[0968] Specific examples

[0969] If a user's profile information indicates that they like cafe hopping and art appreciation, their budget is under 2,000 yen, and their transportation methods are walking and cycling, and the user enters "relax" and "discover new places," the server's generative AI model uses this information to generate a mission using an emotion engine: "Go to the nearest cafe and order a latte." The device displays this mission and uses the Google Maps API to provide directions to the cafe. While the user is completing the mission, the emotion engine analyzes the user's emotional state in real time. After completing the mission, the user reviews their experience and earns points and badges. This post-experience feedback is used to generate the next mission.

[0970] Prompt Sentence Examples

[0971] An example of a prompt is:

[0972] User profile information:

[0973] Hobbies: Cafe hopping, art appreciation

[0974] Budget: Under 2,000 yen

[0975] Transportation: walking, cycling

[0976] Current mood: Relaxed

[0977] Experience you're looking for: Discover new places

[0978] Please suggest three possible missions to generate.

[0979] As described above, the system of the present invention makes it possible to provide an individually optimized experience based on the user's profile information and real-time emotion analysis.

[0980] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0981] Step 1: Launch the application and enter profile information

[0982] The user launches the application on their smartphone or tablet. The device displays a screen for entering profile information. The user enters information such as their preferences (e.g., cafe hopping, art appreciation), budget (e.g., under 2,000 yen), and mode of transportation (e.g., walking, cycling). This input information is temporarily stored on the device. The device then sends this temporarily stored information to the server. The server stores the received profile information in a database. The input is the user's profile information, and the output is the user information stored in the database.

[0983] Step 2: Enter your current mood and type of experience

[0984] When a user starts a mystery quest, the device displays a screen for inputting their current mood and the type of experience they are seeking. Users input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," and the type of experience, such as "cafe hopping" or "art appreciation." This information is also temporarily stored on the device and sent to the server. The input is the current mood and type of experience, and the output is the state information sent to the server.

[0985] Step 3: Generate a random mission

[0986] The server generates random missions using a generative AI model based on the received profile information, current mood, and type of experience. The emotion engine analyzes emotional data collected from past feedback and reflects this in the generation of missions. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "search for hidden art in a nearby park." The server sends the generated missions to the device. The inputs are the user's profile information, current mood, type of experience, and past feedback, and the output is the generated random mission.

[0987] Step 4: Announce the random mission and provide instructions

[0988] The device displays the random mission received from the server to the user. It provides specific step-by-step instructions, such as "First, head to the XX cafe." The device uses the Google Maps API to guide the user along the route to their destination. The user then follows these instructions to complete the mission. The input is the generated random mission, and the output is the instructions and guidance communicated to the user.

[0989] Step 5: Emotion analysis during the mission

[0990] While the user is completing a mission, the emotion engine analyzes the user's facial expressions and voice in real time to recognize changes in emotion. The emotion engine can adjust the difficulty and content of the mission as needed. The input is the user's emotion data collected in real time, and the output is updated mission content and difficulty.

[0991] Step 6: Share your experience and provide feedback

[0992] When a user completes a mission, the device displays an experience sharing screen and prompts the user to review the experience and upload photos. When the user finishes sharing their experience, the device sends the information to the server. The server stores the received feedback in a database to help generate future missions. The input is the user's experience review and photos, and the output is the feedback stored in the database.

[0993] Step 7: Calculating and notifying rewards

[0994] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the points and badges to the user, giving them a sense of accomplishment. For example, it displays "You've earned XX points!" or "You've earned a new badge!" The input is the user's mission results, and the output is the calculated points and badge information.

[0995] (Application example 2)

[0996] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0997] Conventional systems have had difficulty taking into account users' emotions and real-time information when providing new experiences to users' daily lives. In particular, systems must respond appropriately to dynamic changes in the user's mood and emotions. Furthermore, they lack the ability to provide navigation and specific instructions during the generated mission. These issues result in a decline in the quality of the user's experience and a decrease in satisfaction.

[0998] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0999] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions, means for inputting and saving results of the random missions performed by the user and feedback, means for awarding points and badges based on the user's mission results, means for performing emotion analysis to recognize the user's emotional state, means for providing guidance while the user is completing the missions in real time, map service means for providing route guidance based on the generated missions, and means for creating data for training the mission generation means using feedback. This makes it possible to provide missions adapted to the user's emotions and current situation, thereby achieving a higher level of personalization and improved quality of experience.

[1000] "Profile information" is information specific to a user, such as preferences, budget, and mode of transportation, and is the basic data that allows the system to provide the user with an optimal experience.

[1001] "Mood" refers to the user's current emotional state, and is a factor that affects the content of the random missions provided by the system.

[1002] "Type of experience" refers to the category of specific activities or events that the user desires, such as "cafe hopping" or "art appreciation."

[1003] "Random Missions" refer to specific tasks or activities that are generated based on the user's profile information and current mood and type of experience, and are designed to provide the user with new discoveries and experiences.

[1004] "Notification means" refers to the method by which the system notifies the user of the random missions generated, and includes smartphone apps, notification messages, etc.

[1005] "Feedback" refers to the user's evaluation and impressions of the random mission they performed, and is data collected for the system to use in generating the next mission.

[1006] "Points" are a type of reward that users can earn by completing random missions, and form part of the benefits and reward system that can be used within the app.

[1007] A "badge" is a digital medal or symbol awarded to users who achieve certain conditions or missions, and serves to enhance the user's sense of accomplishment as part of gamification.

[1008] "Emotion analysis" is a technology that analyzes a user's facial expressions and voice data in real time to recognize their current emotional state, and is used by the system to dynamically adjust the content of the mission.

[1009] The "map service" is a function that guides users to their destination when they are completing random missions, and uses location information services and navigation systems.

[1010] "Learning data" is data that is used to improve the next random mission generation method based on feedback collected from users, and is used to improve the accuracy of the AI ​​model.

[1011] A "server" is a computer system that stores and processes various data such as user profile information, feedback, and mission generation.

[1012] The system for implementing the present invention has functions for providing new experiences to users in their daily lives. This system has the following main functions in particular:

[1013] 1. Create a profile

[1014] When a user uses the system for the first time, they enter profile information through their smartphone. The input items include preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[1015] 2. Enter your mood and experience type

[1016] When a user starts a mission, they are prompted to enter their current mood (e.g., "I want to relax") and the type of experience (e.g., "cafe hopping"). The device temporarily stores this information and sends it to the server.

[1017] 3. Random mission generation

[1018] The server generates random missions using a generative AI model and sentiment analysis engine based on the user's profile information, current mood, and type of experience. For example, a specific task such as "Go to the nearest cafe and order a latte" is automatically generated.

[1019] 4. Mission Notification and Navigation

[1020] The device notifies the user of the random mission received from the server and provides route guidance to the destination using Google Maps API. The device guides the user step by step and assists the user in completing the mission.

[1021] 5. Emotion analysis

[1022] While the user is completing a mission, the emotion analysis engine analyzes the user's facial expressions and voice via the device's camera and microphone, recognizing their emotional state in real time. This makes it possible to adjust the content and difficulty of the mission according to the user's emotional state.

[1023] 6. Share your experiences

[1024] After users complete a mission, they are shown an experience sharing screen where they can review their experience and upload photos. This information is sent to the server and stored in a database. The feedback is used to generate the next mission.

[1025] 7. Rewards and Gamification

[1026] The server calculates points and badges based on the user's mission results and sends them to the device, allowing the user to visually check their progress and sense of accomplishment.

[1027] Hardware and software used

[1028] Hardware

[1029] Smartphone (iOS / Android)

[1030] software

[1031] Flask: a server-side web framework

[1032] Firestore: Used as a database

[1033] Google Cloud Translation API: For multilingual support

[1034] Google Maps API: for navigation

[1035] Emotion analysis engine: Analyzes the user's facial expressions and voice data

[1036] Specific examples

[1037] For example, if a user's profile information states "I like cafe hopping and art appreciation, my budget is under 2,000 yen, and my transportation methods are walking and cycling," and the user inputs the mood and experience type of "relaxation" and "discover new places," the server's generative AI model and sentiment analysis engine will generate a mission of "go to the nearest cafe and order a latte." The device will display this mission and use the Google Maps API to guide the user to the cafe. After completing the mission, the user can share their experience and earn points and badges.

[1038] Prompt Sentence Examples

[1039] Generate the perfect mission for a user who likes "cafe hopping" and is in the mood to "relax." For example, a mission to go to the nearest cafe and order a latte. What other missions would you generate?

[1040] The present invention allows users to enjoy an experience that is individually customized, and is expected to provide a more engaging experience through real-time responses and reward systems that respond to emotions.

[1041] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1042] Step 1:

[1043] A user downloads and launches a smartphone app. First, the user is guided to a screen where they can enter their profile information. Here, they enter information such as their preferences, budget, and mode of transportation. The device temporarily stores this information, formats the input data, and sends it to the server. The server stores the received profile information in a database and returns the results. The input to this step is the user's profile information, and the output is the profile information stored in the database.

[1044] Step 2:

[1045] When a user starts "Discovery Mode," a screen appears asking them to enter their current mood and the type of experience they are looking for. For example, they can enter information such as "I want to relax," "I'm looking for an adventurous experience," "I want to go café-hopping," or "I want to appreciate art." The device collects this information and sends it to the server. The server processes this information and stores it as base data for generating random missions. The input for this step is the user's current mood and the type of experience, and the output is base data for generating random missions.

[1046] Step 3:

[1047] The server uses a generative AI model based on the profile information, current mood, and experience type, combined with a sentiment analysis engine, to generate a random mission. For example, a specific mission such as "Go to the nearest cafe and order a latte" is generated. The server generates this random mission and sends it to the device. The input of this step is the profile information, mood, and experience type, and the output is the generated random mission.

[1048] Step 4:

[1049] The device notifies the user of the random mission received from the server. Specifically, it displays the details of the mission on the screen and provides the user with specific instructions. For example, instructions such as "First, go to the nearest cafe" are displayed. The device uses the Google Maps API to guide the user to their destination. The input of this step is the generated random mission, and the output is a notification of the mission and navigation instructions to the user.

[1050] Step 5:

[1051] While the user is performing the mission, the device collects facial expressions and voice data through a camera and microphone, and analyzes the user's emotional state in real time using an emotion analysis engine. The server uses this emotional data to adjust the content and difficulty of the mission. The input for this step is the user's facial and voice data, and the output is the real-time emotion analysis results.

[1052] Step 6:

[1053] After the user completes the mission, an experience sharing screen appears. The user reviews the mission experience and uploads photos. The device collects this feedback data and sends it to the server. The server stores it in a database and uses it as learning data for the next random mission generation. The input of this step is the user's feedback, and the output is the feedback data stored in the database.

[1054] Step 7:

[1055] The server calculates points and badges based on the user's mission results and sends the information to the device. The device displays information about the points and badges to the user, giving them a sense of accomplishment. For example, messages such as "You've earned XX points!" or "You've earned a new badge!" are displayed. The input of this step is the user's mission results, and the output is point and badge information.

[1056] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1057] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1058] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1059] [Fourth embodiment]

[1060] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1061] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1062] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1063] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1064] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1065] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1066] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1067] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1068] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1069] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1070] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1071] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1072] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1073] The present invention is a system for providing new experiences to users' daily lives, generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries.

[1074] Program processing

[1075] Creating a profile

[1076] When a user first launches the application, a profile entry screen appears. The user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[1077] Entering the status

[1078] Next, when the user starts the mystery quest, the app displays a screen for inputting their current mood and the type of experience they are looking for. For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[1079] Random mission generation

[1080] The server uses an AI model to generate appropriate random missions based on the user's profile information, current mood, and type of experience. For example, the server might generate missions such as "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[1081] Receiving instructions for action

[1082] The device displays the random mission received from the server to the user and provides step-by-step instructions for specific actions. For example, it instructs the user on each action, such as "First, head to the XX cafe." It also uses Google Maps APIs and other tools to provide route guidance to the user's destination.

[1083] Share your experiences

[1084] After users complete a mission, the app displays an experience sharing screen, prompting them to review their experience and upload photos. Once users finish sharing their experience, their device sends the information to the server, which stores this feedback in a database and uses it to refine the AI ​​model for future mission generation.

[1085] Rewards and Gamification

[1086] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[1087] Specific examples

[1088] The user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and prefer walking and cycling as their means of transportation. When the user inputs their mood and type of experience, "relaxing" and "discovering new places," the server's AI model generates a mission to "go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and earns points and badges. Feedback from the experience is used to generate the next mission.

[1089] The system of the present invention provides new experiences tailored to the individual needs and circumstances of users, bringing a breath of fresh air to everyday life while also achieving a high level of personalization and real-time response.

[1090] The processing flow will be explained below.

[1091] Step 1: Enter and save your profile information

[1092] User: When the app is launched for the first time, a profile entry screen appears, prompting the user to enter information such as preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation.

[1093] Device: Temporarily stores profile information entered by the user.

[1094] Device: Sends profile information to the server.

[1095] Server: Stores the received profile information in a database.

[1096] Step 2: Enter your current mood and type of experience

[1097] User: When starting a Mystery Quest, you input your current mood and the type of experience you are seeking.

[1098] Device: The input mood and type of experience are temporarily stored and sent to the server.

[1099] Server: Stores the received mood and experience type in a database.

[1100] Step 3: Generate a random mission

[1101] Server: Instructs the AI ​​model to generate random missions based on the user's profile information, mood, and type of experience.

[1102] Server (AI model): Analyzes profile information, current mood, and type of experience to generate appropriate random missions, such as "drink a specific coffee at the nearest cafe" or "find hidden art."

[1103] Server: Sends generated random missions to the device.

[1104] Step 4: Mission Notification and Action Instructions

[1105] Terminal: Displays the random mission received from the server to the user. For example, it displays instructions such as "First, go to XX Cafe."

[1106] Terminal: Uses Google Maps API etc. to guide the user to their destination.

[1107] User: Follow instructions and complete the mission.

[1108] Step 5: Complete the mission and provide feedback

[1109] Users: After completing a mission, they will be prompted to share their experience and provide a rating and feedback.

[1110] On your device: The entered feedback is temporarily stored and sent to the server.

[1111] Server: Stores the received feedback in a database and provides it to the AI ​​model as learning data to be used in generating the next mission.

[1112] Step 6: Compensation calculation and notification

[1113] Server: Calculates points and badges based on users' mission completion results.

[1114] Server: Sends calculated points and badge information to the device.

[1115] On the device: Display the received points and badges to the user. For example, display "You've earned XX points!" or "You've earned a new badge!"

[1116] Users: See the rewards and get motivated for the next mission.

[1117] Through these steps, this system provides users with a new, customized experience, bringing a breath of fresh air to everyday life.

[1118] Example 1

[1119] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1120] In modern society, many people seek new experiences in their daily lives, but finding time for them can be challenging. Furthermore, it is difficult to provide optimal experiences tailored to the needs and circumstances of every individual user. Conventional systems often only offer pre-determined courses and experiences, and do not adequately provide dynamic experiences based on individual users' current moods and interests. In light of these challenges, the present invention aims to provide a system that dynamically generates random missions based on a user's profile information and current moods and interests, thereby providing a highly personalized experience.

[1121] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1122] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions using a generative AI model based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions and providing action instructions, means for inputting and saving the results and feedback of the user's random missions, and means for awarding points and badges based on the user's mission results. This allows users to enjoy new experiences based on their current moods and interests. Furthermore, the system is continuously improved based on feedback, enabling it to provide more accurate experiences.

[1123] Below are definitions of important terms included in the claims we just rewrote.

[1124] "Profile information" is information about a user, including the user's preferences, interests, available budget, transportation options, and the like.

[1125] "Mood" refers to the psychological state the user is feeling at that time and the type of experience they desire.

[1126] "Type of experience" refers to the specific genre of activity or event that the user desires.

[1127] A "generative AI model" is an algorithm that uses machine learning to generate optimal random missions based on a user's profile information and current mood.

[1128] "Random Missions" are tasks and activities that are dynamically generated based on the user's profile information and current mood.

[1129] "Action instructions" is information indicating specific steps and action guidance required for the user to complete the random mission.

[1130] "Feedback" refers to a record of impressions, ratings, photos, etc. provided by a user after completing a random mission.

[1131] "Points" are a type of reward given to users as a result of completing random missions, and are accumulated to function as an incentive.

[1132] "Badges" are digital rewards that visually represent a user's achievements and are awarded for completing specific missions or achieving certain results.

[1133] The present invention is a system for providing new experiences to users' daily lives, generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries.

[1134] This system is composed of two main components: a server and a terminal. The server is responsible for generating random missions using a generative AI model based on the user's profile information, current mood, and type of experience. The terminal is a device directly operated by the user, and is responsible for inputting profile information, displaying random missions, providing action instructions, and inputting feedback after completing a mission.

[1135] Creating a profile

[1136] When a user first launches the application, a profile information entry screen appears on the device. Here, the user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server stores the received profile information in a database.

[1137] Entering the status

[1138] Next, when the user starts the mystery quest, the app displays a screen on the device for inputting their current mood and the type of experience they are looking for. For example, the user can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[1139] Random mission generation

[1140] The server uses a generative AI model to generate an appropriate random mission based on the user's profile information, current mood, and type of experience. For example, missions such as "Drink a specific coffee at the nearest cafe" or "Find hidden art in a nearby park" may be generated. An example prompt is, "The user's profile information states that they like to visit cafes and appreciate art, their budget is under 2,000 yen, their transportation method is walking and cycling, their current mood is relaxation, and they want to discover new places. Please generate an appropriate random mission based on this information." The server then sends the generated mission to the device.

[1141] Receiving instructions for action

[1142] The device displays the random mission received from the server to the user and provides step-by-step instructions for specific actions. For example, it instructs the user on each action, such as "First, head to the XX cafe." It also uses Google Maps APIs and other tools to provide route guidance to the user's destination.

[1143] Collecting feedback

[1144] After a user completes a mission, the app displays an experience sharing screen, prompting the user to review the experience and upload photos. Once the user has finished sharing their experience, the device sends the information to the server, which stores this feedback in a database and uses it to refine the generative AI model for future mission generation.

[1145] Rewards and Gamification

[1146] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[1147] As a concrete example, consider a user's profile information, which includes preferences for cafe hopping and art appreciation, a budget of less than 2,000 yen, and transportation methods of walking and cycling. When the user inputs the mood and type of experience, "relaxing" and "discovering new places," the server's generative AI model generates a mission, "Go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and earns points and badges. This feedback is used to generate the next mission.

[1148] The system of the present invention provides new experiences tailored to the individual needs and circumstances of users, bringing a breath of fresh air to everyday life while also achieving a high level of personalization and real-time response.

[1149] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1150] Step 1: Enter and save your profile information

[1151] When a user launches the application, the device displays a profile entry screen where the user can enter information about their preferences (e.g., cafe hopping, art appreciation), interests, available budget, and mode of transportation (e.g., walking, cycling, car).

[1152] The entered profile information is temporarily stored in the terminal's memory, and then the terminal transmits this information to the server.

[1153] The server stores the received profile information in a database. The input here is the user's profile information, and the output is the profile information stored in the database. The server uses this information as the basis for generating random missions later.

[1154] Step 2: Enter and save your mood and experience type

[1155] When a user starts a mystery quest, the device displays a screen for inputting the mood and type of experience.

[1156] For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation."

[1157] The input information is temporarily stored on the terminal, which then transmits it to the server.

[1158] The server stores the received information in a database, where the input is the mood and experience type entered by the user, and the output is the mood and experience type stored in the database.

[1159] Step 3: Generate a random mission

[1160] The server generates random missions using a generative AI model based on the user's profile information and their current mood and type of experience.

[1161] Specifically, the generative AI model is given the following prompt: "The user's profile information states that they like to visit cafes and appreciate art, their budget is under 2000 yen, their preferred mode of transportation is walking and cycling, their current mood is relaxation, and they want to discover new places. Based on this information, please generate an appropriate random mission."

[1162] The generative AI model performs data calculations based on this prompt sentence and generates a random mission.

[1163] The server sends the generated random mission to the device, where the input is the profile information and the type of mood and experience, and the output is the generated random mission.

[1164] Step 4: View and receive action instructions

[1165] The terminal displays the random mission received from the server to the user.

[1166] Furthermore, it provides step-by-step, specific instructions for each action, such as "First, go to the XX cafe."

[1167] The device also provides users with route guidance to their destination using Google Maps API etc. The input here is a random mission sent from the server, and the output is action instructions displayed to the user.

[1168] Step 5: Mission Accomplishment

[1169] The user carries out the mission by following the action instructions provided by the terminal.

[1170] For example, the user completes the mission by arriving at a certain cafe and ordering a latte. Here, the input is an action instruction, and the output is the completion of the mission.

[1171] Step 6: Collect and store feedback

[1172] After completing a mission, the device displays an experience sharing screen where users can review their experience and upload photos.

[1173] For example, you could enter, "The latte at XX Cafe was very delicious." Once the user has finished entering their feedback, the device sends the information to the server.

[1174] The server stores this feedback in a database and uses it as data to refine the generative AI model for future mission generation. The input here is the user's feedback information, and the output is the feedback information stored in the database.

[1175] Step 7: Rewards and Gamification

[1176] The server calculates points and badges based on the user's mission results.

[1177] For example, a user can be awarded 50 points for the achievement of "finding a hidden art." The server sends this to the device, which then displays "You've earned 50 points!" or "You've earned a new badge!" to the user. The input here is the user's mission result, and the output is the calculated points or badge information.

[1178] Through the above processing steps, the system can provide a new experience that suits the user's current mood and interests.

[1179] (Application example 1)

[1180] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1181] The present invention aims to provide users with new experiences in their daily lives. Specifically, it aims to generate customized random missions based on the user's profile information, current emotions, and type of experience, and present them to the user, allowing them to experience new discoveries and excitement. It is also desirable to improve the quality of future missions based on the results and feedback of the missions completed by the user.

[1182] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1183] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current emotions and types of experiences, means for acquiring user location information, means for generating optimal random missions based on the profile information, the current emotions and types of experiences, and the location information, means for notifying the user of the generated random missions, means for inputting and saving the results of the random missions performed by the user and feedback, means for awarding points and certificates based on the user's mission results, and means for creating training data to improve the random mission generation means using user feedback. This allows users to have a new, customized experience, promoting use of physical stores and providing opportunities for new discoveries.

[1184] "User profile information" is information about a user's preferences, interests, available budget, and transportation options.

[1185] "Current Emotion" is information about the user's mood at the time they start the mystery quest and the type of experience they are seeking.

[1186] "Random Missions" are tasks and activities customized based on a user's profile information, current emotions, and type of experience.

[1187] "Information storage device" is a general term for hardware and software for storing information, including databases.

[1188] "Score" refers to points that a user can earn by completing a mission.

[1189] A "certificate" is a badge or title that proves that a user has completed a mission.

[1190] "Location information" is information about the latitude and longitude of the user's current location.

[1191] "Training data" is learning data used to improve the random mission generation means based on user feedback.

[1192] The present invention is a system for providing new experiences to users' daily lives. This system generates customized random missions based on the user's profile information, current emotions, and type of experience, and encourages new discoveries by having the user carry out the missions.

[1193] Main system components

[1194] The main components include the following:

[1195] User device: Smartphone

[1196] Server: Contains the database and AI model

[1197] Geographic information acquisition systems: Libraries such as geopy

[1198] Random mission generation system: uses generative AI models

[1199] Program processing explanation

[1200] 1. Enter and save your user profile information

[1201] When a user device first launches the application, the user enters information about their preferences (e.g., cafe hopping, art appreciation), interests, budget, and transportation. This information is temporarily stored and sent to the server, which stores the profile information in a database.

[1202] 2. Input and save the current emotion and type of experience

[1203] When starting a mystery quest, the user's device will prompt them to input their current emotions and the type of experience they are seeking. For example, they can input "I want to relax" or "I want to discover new places." This input is also temporarily stored and sent to the server.

[1204] 3. Obtaining location information

[1205] The user device uses the geopy library to obtain the current location information (latitude and longitude) and sends it to the server.

[1206] 4. Random mission generation

[1207] The server uses a generative AI model based on profile information, current emotions, type of experience, and location information to generate an appropriate random mission, such as "drink a specific coffee at the nearest cafe."

[1208] 5. Mission Notification and Instructions

[1209] The system notifies the user of the randomly generated mission and provides specific instructions for action. It also provides route guidance using Google Maps APIs and other tools.

[1210] 6. Gather feedback after completing the mission

[1211] After users complete a mission, they are presented with a shared experience screen where they can review their experience and upload photos. This feedback is sent to the server and stored in a database.

[1212] 7. Awarding of Scores and Certificates

[1213] The server calculates the score and certificate based on the user's mission results and notifies the user's terminal, allowing the user to feel a sense of accomplishment.

[1214] Specific examples

[1215] The user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and use walking and cycling as their means of transportation. When the user inputs the emotions and experience type of "relaxation" and "discover new places," the server's AI model generates a mission to "go to the nearest cafe and order a latte." The user's device displays this mission and guides the user to the cafe. After completing the mission, the user shares their experience and receives points and a certificate. Feedback from the experience is used to generate the next mission.

[1216] Prompt Sentence Examples

[1217] User Input:

[1218] Please enter your user profile information.

[1219] Enter your current mood and type of experience:

[1220] "What is your current mood? (e.g., I want to relax)"

[1221] "What kind of experience are you looking for? (e.g., discovering new places)"

[1222] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1223] Step 1:

[1224] When a user launches the application, the device displays a profile information input screen. Here, the user enters their preferences, interests, available budget, and mode of transportation. This information is temporarily stored on the device and then sent to the server. The server stores the received profile information in a database. The input data is the profile information, and the output data is the profile information stored in the database.

[1225] Step 2:

[1226] When a user attempts to start a mystery quest, the device displays a screen for inputting their current emotions and the type of experience they are seeking. The user may enter, for example, "I want to relax" or "I want to discover new places." This is also temporarily stored on the device and sent to the server. The server stores the received emotions and types of experiences in a database. The input data is the emotion and experience information, and the output data is the emotion and experience information stored in the database.

[1227] Step 3:

[1228] The device uses the geopy library to obtain the user's current location. The device obtains the latitude and longitude information and sends it to the server. The server temporarily stores this location information and uses it in the next step of random mission generation. The input data is the current location, and the output data is the location information sent to the server.

[1229] Step 4:

[1230] The server combines the user's profile information, current emotion, type of experience, and location information to generate an optimal random mission using a generative AI model. For example, a mission such as "drink a specific coffee at the nearest cafe" may be generated. The generated mission is stored on the server and used in the next step. The input data is the profile information, emotion, experience, and location information, and the output data is the generated random mission.

[1231] Step 5:

[1232] The server notifies the device of the generated random mission. The device then displays specific instructions to the user. For example, "Please head to the XX cafe." The device also uses the Google Maps API to provide navigation to the user's destination. The input data is the mission information from the server, and the output data is the instructions notified to the user.

[1233] Step 6:

[1234] After the user completes the mission, the device displays a screen for sharing their experience. The user can review their experience and upload photos. This information is temporarily stored on the device and then sent to the server. The server stores this data in a database. The input data is the user's feedback, and the output data is the feedback information stored in the database.

[1235] Step 7:

[1236] The server calculates the score and certificate based on the user's mission results. The calculation results are sent to the device, which notifies the user. For example, the user can earn XX points or get a new badge. The input data is the user's mission results, and the output data is score and certificate information.

[1237] Step 8:

[1238] The server uses user feedback to create training data to improve the random mission generation method, thereby increasing the accuracy of the next mission generation. The input data is feedback information, and the output data is training data.

[1239] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1240] The present invention is a system for providing new experiences to users' daily lives by generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, making it possible to provide experiences that take the user's emotional state into consideration.

[1241] Program processing

[1242] Creating a profile

[1243] When a user first launches the application, a profile entry screen appears. The user enters information about their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[1244] Entering the status

[1245] Next, when the user starts the mystery quest, the app displays a screen for inputting their current mood and the type of experience they are looking for. For example, users can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." The device temporarily stores this information and sends it to the server.

[1246] Random mission generation

[1247] The server uses an AI model based on the user's profile information, current mood, and type of experience, and combines it with an emotion engine to generate random missions. The emotion engine collects emotional data from the user's past feedback, analyzes it, and uses it to generate missions. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[1248] Receiving instructions for action

[1249] The device displays the random mission received from the server to the user and provides specific step-by-step instructions. For example, it may provide instructions such as "First, head to the XX cafe," and uses Google Maps APIs to guide the user to their destination. The user follows the instructions to complete the mission.

[1250] Emotion analysis during missions

[1251] The emotion engine analyzes the user's facial expressions and voice in real time while they are completing a mission, recognizing changes in their emotions and allowing it to adjust the difficulty and content of the mission as needed.

[1252] Share your experiences

[1253] After users complete a mission, the app displays an experience sharing screen, prompting them to review their experience and upload photos. Once users finish sharing their experience, their device sends the information to the server, which stores this feedback in a database and uses it as training data for the AI ​​model and emotion engine to generate future missions.

[1254] Rewards and Gamification

[1255] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the results to the user, giving them a sense of accomplishment. For example, the app displays "You've earned XX points!" or "You've earned a new badge!"

[1256] Specific examples

[1257] Assume that a user's profile information indicates that they like cafe hopping and art appreciation, have a budget of less than 2,000 yen, and use walking and cycling as their means of transportation. When the user inputs their mood and experience type, "relaxing" and "discovering new places," the server's AI model uses an emotion engine to generate a mission, "Go to the nearest cafe and order a latte." The device displays this mission and guides the user to the cafe. The emotion engine analyzes the user's facial expressions and voice in real time to monitor the user's emotional state. After completing the mission, the user can share their experience and earn points and badges. Feedback from the experience is used to generate the next mission.

[1258] The system of the present invention provides users with a new personalized experience through the above steps, and by adding an emotion engine, achieves even higher levels of personalization and real-time responses.

[1259] The processing flow will be explained below.

[1260] Step 1: Enter and save your profile information

[1261] User: When the app is launched for the first time, a profile entry screen appears, prompting the user to enter their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (walking, cycling, car, etc.).

[1262] Device: Temporarily stores profile information entered by the user.

[1263] Device: Sends profile information to the server.

[1264] Server: Stores the received profile information in a database.

[1265] Step 2: Enter your current mood and type of experience

[1266] Users: When starting a mystery quest, they input their current mood and the type of experience they are looking for, such as "relaxing" or "seeking an adventurous experience," or "cafe-hopping" or "art appreciation."

[1267] Device: The input mood and type of experience are temporarily stored and sent to the server.

[1268] Server: Stores the received mood and experience type in a database.

[1269] Step 3: Generate a random mission

[1270] Server: Generates random missions using an emotion engine and AI models based on the user's profile information, mood, and type of experience.

[1271] Server (AI model): Analyzes profile information, current mood, and type of experience, and also takes into account emotional data from the emotion engine to generate appropriate random missions, such as "drink a specific latte at the nearest cafe" or "find hidden art in a nearby park."

[1272] Server: Sends generated random missions to the device.

[1273] Step 4: Mission Notification and Action Instructions

[1274] Terminal: Displays the random mission received from the server to the user. For example, it displays instructions such as "First, go to XX Cafe."

[1275] Terminal: Uses Google Maps API etc. to guide the user to their destination.

[1276] User: Follow instructions and complete the mission.

[1277] Step 5: Emotion analysis during the mission

[1278] Emotion engine: Analyzes the user's facial expressions and voice in real time while they are completing a mission, recognizing changes in their emotions.

[1279] Server: Receives the analysis results from the emotion engine and adjusts the difficulty and content of the mission as needed.

[1280] Step 6: Complete the mission and provide feedback

[1281] Users: After completing a mission, they are prompted to review their experience and provide their thoughts and ratings about the experience.

[1282] On your device: The entered feedback is temporarily stored and sent to the server.

[1283] Server: Stores the received feedback in a database and provides it to the AI ​​model and emotion engine as learning data to be used in generating the next mission.

[1284] Step 7: Compensation calculation and notification

[1285] Server: Calculates points and badges based on users' mission completion results.

[1286] Server: Sends calculated points and badge information to the device.

[1287] On the device: Display the received points and badges to the user. For example, display "You've earned XX points!" or "You've earned a new badge!"

[1288] Users: See the rewards and get motivated for the next mission.

[1289] Through these steps, the system of the present invention provides users with a new personalized experience, and by adding an emotion engine, it achieves even higher levels of personalization and real-time responses.

[1290] Example 2

[1291] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1292] Conventional user experience provision systems lack the ability to customize the experience to take into account the user's emotional state and real-time feedback, making it difficult to provide the optimal experience for the user. Furthermore, there is a need to automatically generate new experiences tailored to individual users by effectively utilizing user profile information and feedback.

[1293] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions using a generation AI model based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions, means for inputting and saving results and feedback of the random missions performed by the user, means for awarding points and badges based on the user's mission results, means for analyzing the user's facial expressions, voice, etc. to recognize the user's emotional state in real time and adjust the missions, and means for creating learning data for improving the random mission generation means using user feedback. This makes it possible to provide an optimal, customized experience for each user, taking into account the user's emotional state and real-time feedback.

[1294] "Profile information" is personal information such as a user's preferences, budget, mode of transportation, etc.

[1295] "Mood" refers to the emotions and psychological state that a user is currently experiencing.

[1296] "Experience type" means the specific activity or category of activity that a user is seeking.

[1297] A "generative AI model" is an algorithm or program that uses artificial intelligence to generate missions based on a user's profile information, mood, and type of experience.

[1298] "Random missions" refer to specific activities or tasks provided to users by generative AI models.

[1299] "Notification" refers to the method or means for informing the user of the generated random mission.

[1300] "Feedback" refers to the evaluation, impressions, and reactions provided by the user regarding the random mission they have completed.

[1301] "Points" refer to points or scores that a user receives as a reward for completing a mission.

[1302] A "badge" is a recognition or award that a user can earn by completing a specific mission.

[1303] An "emotion engine" is a technology or program that analyzes a user's facial expressions and voice to recognize their emotional state.

[1304] "Real-time recognition" means detecting and analyzing the user's emotional state instantly.

[1305] "Training data" refers to data that the system uses to improve its AI model based on user feedback.

[1306] A "database" is a digital warehouse for organizing and storing information such as profile information and feedback.

[1307] The present invention is a system for providing new experiences to users' daily lives by generating customized random missions based on the user's profile information, current mood, and type of experience, and encouraging the user to carry out these missions to encourage new discoveries. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, making it possible to provide experiences that take the user's emotional state into consideration.

[1308] The system of the present invention begins when a user launches the application on a device such as a smartphone or tablet. The device first displays a profile information input screen, and the user enters information such as their preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). This information is temporarily stored on the device and then sent to the server. The server stores the received information in a database.

[1309] Next, when the user starts the mystery quest, the device displays a screen for inputting their current mood and the type of experience they are looking for. The user can input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," or the type of experience, such as "cafe hopping" or "art appreciation." This information is also temporarily stored on the device and sent to the server.

[1310] The server uses a generative AI model based on the received profile information, current mood, and type of experience to generate random missions in combination with the emotion engine. The emotion engine analyzes emotional data collected from past feedback and generates missions based on this. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "find hidden art in a nearby park." The server then sends the generated missions to the device.

[1311] The device displays the random mission received from the server to the user. It provides specific step-by-step instructions, such as "First, head to the XX cafe." The device uses the Google Maps API to guide the user to their destination. The user then follows these instructions to complete the mission.

[1312] While the user is completing a mission, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. The difficulty and content of the mission can be adjusted as needed. After the mission is completed, the device displays an experience sharing screen, prompting the user to review their experience and upload photos. Once the user has finished sharing their experience, the device sends the information to the server. The server stores the received feedback in a database and uses it to generate future missions.

[1313] Furthermore, the server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the points and badges to the user, giving them a sense of accomplishment. For example, it displays "You've earned XX points!" or "You've earned a new badge!"

[1314] Specific examples

[1315] If a user's profile information indicates that they like cafe hopping and art appreciation, their budget is under 2,000 yen, and their transportation methods are walking and cycling, and the user enters "relax" and "discover new places," the server's generative AI model uses this information to generate a mission using an emotion engine: "Go to the nearest cafe and order a latte." The device displays this mission and uses the Google Maps API to provide directions to the cafe. While the user is completing the mission, the emotion engine analyzes the user's emotional state in real time. After completing the mission, the user reviews their experience and earns points and badges. This post-experience feedback is used to generate the next mission.

[1316] Prompt Sentence Examples

[1317] An example of a prompt is:

[1318] User profile information:

[1319] Hobbies: Cafe hopping, art appreciation

[1320] Budget: Under 2,000 yen

[1321] Transportation: walking, cycling

[1322] Current mood: Relaxed

[1323] Experience you're looking for: Discover new places

[1324] Please suggest three possible missions to generate.

[1325] As described above, the system of the present invention makes it possible to provide an individually optimized experience based on the user's profile information and real-time emotion analysis.

[1326] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1327] Step 1: Launch the application and enter profile information

[1328] The user launches the application on their smartphone or tablet. The device displays a screen for entering profile information. The user enters information such as their preferences (e.g., cafe hopping, art appreciation), budget (e.g., under 2,000 yen), and mode of transportation (e.g., walking, cycling). This input information is temporarily stored on the device. The device then sends this temporarily stored information to the server. The server stores the received profile information in a database. The input is the user's profile information, and the output is the user information stored in the database.

[1329] Step 2: Enter your current mood and type of experience

[1330] When a user starts a mystery quest, the device displays a screen for inputting their current mood and the type of experience they are seeking. Users input their mood, such as "I want to relax" or "I'm looking for an adventurous experience," and the type of experience, such as "cafe hopping" or "art appreciation." This information is also temporarily stored on the device and sent to the server. The input is the current mood and type of experience, and the output is the state information sent to the server.

[1331] Step 3: Generate a random mission

[1332] The server generates random missions using a generative AI model based on the received profile information, current mood, and type of experience. The emotion engine analyzes emotional data collected from past feedback and reflects this in the generation of missions. Examples of generated missions include "drink a specific coffee at the nearest cafe" or "search for hidden art in a nearby park." The server sends the generated missions to the device. The inputs are the user's profile information, current mood, type of experience, and past feedback, and the output is the generated random mission.

[1333] Step 4: Announce the random mission and provide instructions

[1334] The device displays the random mission received from the server to the user. It provides specific step-by-step instructions, such as "First, head to the XX cafe." The device uses the Google Maps API to guide the user along the route to their destination. The user then follows these instructions to complete the mission. The input is the generated random mission, and the output is the instructions and guidance communicated to the user.

[1335] Step 5: Emotion analysis during the mission

[1336] While the user is completing a mission, the emotion engine analyzes the user's facial expressions and voice in real time to recognize changes in emotion. The emotion engine can adjust the difficulty and content of the mission as needed. The input is the user's emotion data collected in real time, and the output is updated mission content and difficulty.

[1337] Step 6: Share your experience and provide feedback

[1338] When a user completes a mission, the device displays an experience sharing screen and prompts the user to review the experience and upload photos. When the user finishes sharing their experience, the device sends the information to the server. The server stores the received feedback in a database to help generate future missions. The input is the user's experience review and photos, and the output is the feedback stored in the database.

[1339] Step 7: Calculating and notifying rewards

[1340] The server calculates points and badges based on the user's mission results and sends that information to the device. The device displays the points and badges to the user, giving them a sense of accomplishment. For example, it displays "You've earned XX points!" or "You've earned a new badge!" The input is the user's mission results, and the output is the calculated points and badge information.

[1341] (Application example 2)

[1342] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1343] Conventional systems have had difficulty taking into account users' emotions and real-time information when providing new experiences to users' daily lives. In particular, systems must respond appropriately to dynamic changes in the user's mood and emotions. Furthermore, they lack the ability to provide navigation and specific instructions during the generated mission. These issues result in a decline in the quality of the user's experience and a decrease in satisfaction.

[1344] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1345] In this invention, the server includes means for inputting and saving user profile information, means for inputting and saving the user's current mood and type of experience, means for generating random missions based on the profile information, the user's current mood, and the type of experience, means for notifying the user of the generated random missions, means for inputting and saving results of the random missions performed by the user and feedback, means for awarding points and badges based on the user's mission results, means for performing emotion analysis to recognize the user's emotional state, means for providing guidance while the user is completing the missions in real time, map service means for providing route guidance based on the generated missions, and means for creating data for training the mission generation means using feedback. This makes it possible to provide missions adapted to the user's emotions and current situation, thereby achieving a higher level of personalization and improved quality of experience.

[1346] "Profile information" is information specific to a user, such as preferences, budget, and mode of transportation, and is the basic data that allows the system to provide the user with an optimal experience.

[1347] "Mood" refers to the user's current emotional state, and is a factor that affects the content of the random missions provided by the system.

[1348] "Type of experience" refers to the category of specific activities or events that the user desires, such as "cafe hopping" or "art appreciation."

[1349] "Random Missions" refer to specific tasks or activities that are generated based on the user's profile information and current mood and type of experience, and are designed to provide the user with new discoveries and experiences.

[1350] "Notification means" refers to the method by which the system notifies the user of the random missions generated, and includes smartphone apps, notification messages, etc.

[1351] "Feedback" refers to the user's evaluation and impressions of the random mission they performed, and is data collected for the system to use in generating the next mission.

[1352] "Points" are a type of reward that users can earn by completing random missions, and form part of the benefits and reward system that can be used within the app.

[1353] A "badge" is a digital medal or symbol awarded to users who achieve certain conditions or missions, and serves to enhance the user's sense of accomplishment as part of gamification.

[1354] "Emotion analysis" is a technology that analyzes a user's facial expressions and voice data in real time to recognize their current emotional state, and is used by the system to dynamically adjust the content of the mission.

[1355] The "map service" is a function that guides users to their destination when they are completing random missions, and uses location information services and navigation systems.

[1356] "Learning data" is data that is used to improve the next random mission generation method based on feedback collected from users, and is used to improve the accuracy of the AI ​​model.

[1357] A "server" is a computer system that stores and processes various data such as user profile information, feedback, and mission generation.

[1358] The system for implementing the present invention has functions for providing new experiences to users in their daily lives. This system has the following main functions in particular:

[1359] 1. Create a profile

[1360] When a user uses the system for the first time, they enter profile information through their smartphone. The input items include preferences (e.g., cafe hopping, art appreciation), budget, and mode of transportation (e.g., walking, cycling, car). The device temporarily stores this information and sends it to the server. The server then stores the received profile information in a database.

[1361] 2. Enter your mood and experience type

[1362] When a user starts a mission, they are prompted to enter their current mood (e.g., "I want to relax") and the type of experience (e.g., "cafe hopping"). The device temporarily stores this information and sends it to the server.

[1363] 3. Random mission generation

[1364] The server generates random missions using a generative AI model and sentiment analysis engine based on the user's profile information, current mood, and type of experience. For example, a specific task such as "Go to the nearest cafe and order a latte" is automatically generated.

[1365] 4. Mission Notification and Navigation

[1366] The device notifies the user of the random mission received from the server and provides route guidance to the destination using Google Maps API. The device guides the user step by step and assists the user in completing the mission.

[1367] 5. Emotion analysis

[1368] While the user is completing a mission, the emotion analysis engine analyzes the user's facial expressions and voice via the device's camera and microphone, recognizing their emotional state in real time. This makes it possible to adjust the content and difficulty of the mission according to the user's emotional state.

[1369] 6. Share your experiences

[1370] After users complete a mission, they are shown an experience sharing screen where they can review their experience and upload photos. This information is sent to the server and stored in a database. The feedback is used to generate the next mission.

[1371] 7. Rewards and Gamification

[1372] The server calculates points and badges based on the user's mission results and sends them to the device, allowing the user to visually check their progress and sense of accomplishment.

[1373] Hardware and software used

[1374] Hardware

[1375] Smartphone (iOS / Android)

[1376] software

[1377] Flask: a server-side web framework

[1378] Firestore: Used as a database

[1379] Google Cloud Translation API: For multilingual support

[1380] Google Maps API: for navigation

[1381] Emotion analysis engine: Analyzes the user's facial expressions and voice data

[1382] Specific examples

[1383] For example, if a user's profile information states "I like cafe hopping and art appreciation, my budget is under 2,000 yen, and my transportation methods are walking and cycling," and the user inputs the mood and experience type of "relaxation" and "discover new places," the server's generative AI model and sentiment analysis engine will generate a mission of "go to the nearest cafe and order a latte." The device will display this mission and use the Google Maps API to guide the user to the cafe. After completing the mission, the user can share their experience and earn points and badges.

[1384] Prompt Sentence Examples

[1385] Generate the perfect mission for a user who likes "cafe hopping" and is in the mood to "relax." For example, a mission to go to the nearest cafe and order a latte. What other missions would you generate?

[1386] The present invention allows users to enjoy an experience that is individually customized, and is expected to provide a more engaging experience through real-time responses and reward systems that respond to emotions.

[1387] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1388] Step 1:

[1389] A user downloads and launches a smartphone app. First, the user is guided to a screen where they can enter their profile information. Here, they enter information such as their preferences, budget, and mode of transportation. The device temporarily stores this information, formats the input data, and sends it to the server. The server stores the received profile information in a database and returns the results. The input to this step is the user's profile information, and the output is the profile information stored in the database.

[1390] Step 2:

[1391] When a user starts "Discovery Mode," a screen appears asking them to enter their current mood and the type of experience they are looking for. For example, they can enter information such as "I want to relax," "I'm looking for an adventurous experience," "I want to go café-hopping," or "I want to appreciate art." The device collects this information and sends it to the server. The server processes this information and stores it as base data for generating random missions. The input for this step is the user's current mood and the type of experience, and the output is base data for generating random missions.

[1392] Step 3:

[1393] The server uses a generative AI model based on the profile information, current mood, and experience type, combined with a sentiment analysis engine, to generate a random mission. For example, a specific mission such as "Go to the nearest cafe and order a latte" is generated. The server generates this random mission and sends it to the device. The input of this step is the profile information, mood, and experience type, and the output is the generated random mission.

[1394] Step 4:

[1395] The device notifies the user of the random mission received from the server. Specifically, it displays the details of the mission on the screen and provides the user with specific instructions. For example, instructions such as "First, go to the nearest cafe" are displayed. The device uses the Google Maps API to guide the user to their destination. The input of this step is the generated random mission, and the output is a notification of the mission and navigation instructions to the user.

[1396] Step 5:

[1397] While the user is performing the mission, the device collects facial expressions and voice data through a camera and microphone, and analyzes the user's emotional state in real time using an emotion analysis engine. The server uses this emotional data to adjust the content and difficulty of the mission. The input for this step is the user's facial and voice data, and the output is the real-time emotion analysis results.

[1398] Step 6:

[1399] After the user completes the mission, an experience sharing screen appears. The user reviews the mission experience and uploads photos. The device collects this feedback data and sends it to the server. The server stores it in a database and uses it as learning data for the next random mission generation. The input of this step is the user's feedback, and the output is the feedback data stored in the database.

[1400] Step 7:

[1401] The server calculates points and badges based on the user's mission results and sends the information to the device. The device displays information about the points and badges to the user, giving them a sense of accomplishment. For example, messages such as "You've earned XX points!" or "You've earned a new badge!" are displayed. The input of this step is the user's mission results, and the output is point and badge information.

[1402] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1403] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1404] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1405] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1406] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1407] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1408] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1409] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1410] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1411] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1412] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1413] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1414] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1415] 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.

[1416] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1417] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1418] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1419] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1420] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1421] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1422] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1423] The following is further disclosed regarding the above embodiment.

[1424] (Claim 1)

[1425] a means for entering and storing user profile information;

[1426] means for inputting and storing the user's current mood and type of experience;

[1427] means for generating random missions based on the profile information and a current mood and type of experience;

[1428] means for notifying a user of the generated random mission;

[1429] A means for inputting and storing the results and feedback of the random missions executed by the user;

[1430] The system includes a means for awarding points and badges based on a user's mission results.

[1431] (Claim 2)

[1432] 2. The system according to claim 1, wherein the means for storing user profile information uses a database.

[1433] (Claim 3)

[1434] 10. The system of claim 1, further comprising means for generating training data for improving the random mission generator using user feedback.

[1435] "Example 1"

[1436] (Claim 1)

[1437] a means for entering and storing user profile information;

[1438] means for inputting and storing the user's current mood and type of experience;

[1439] means for generating random missions using a generative AI model based on the profile information and a current mood and type of experience;

[1440] means for notifying a user of the generated random mission and providing instructions for action;

[1441] A means for inputting and storing the results and feedback of the random missions executed by the user;

[1442] The system includes a means for awarding points and badges based on a user's mission results.

[1443] (Claim 2)

[1444] 2. The system according to claim 1, wherein the means for storing user profile information uses a database.

[1445] (Claim 3)

[1446] 10. The system of claim 1, further comprising means for generating training data for improving the random mission generator using user feedback.

[1447] "Application Example 1"

[1448] (Claim 1)

[1449] a means for entering and storing user profile information;

[1450] means for inputting and storing the user's current emotions and type of experience;

[1451] means for generating random missions based on the profile information and the current emotion and type of experience;

[1452] means for notifying a user of the generated random mission;

[1453] A means for inputting and storing the results and feedback of the random missions executed by the user;

[1454] means for awarding points and certificates based on the user's mission results;

[1455] A means for acquiring user location information;

[1456] A means for generating an optimal random mission based on user location information;

[1457] A system including:

[1458] (Claim 2)

[1459] 2. The system according to claim 1, wherein the means for storing user profile information uses an information storage device.

[1460] (Claim 3)

[1461] 10. The system of claim 1, further comprising means for generating training data for improving the random mission generator using user feedback.

[1462] "Example 2: Combining Emotion Engines"

[1463] (Claim 1)

[1464] a means for entering and storing user profile information;

[1465] means for inputting and storing the user's current mood and type of experience;

[1466] means for generating random missions using a generative AI model based on the profile information and a current mood and type of experience;

[1467] means for notifying a user of the generated random mission;

[1468] A means for inputting and storing the results and feedback of the random missions executed by the user;

[1469] means for awarding points and badges based on the user's mission results;

[1470] A means to analyze the user's facial expressions, voice, etc. to recognize their emotional state in real time and adjust the mission;

[1471] A system including means for generating training data for improving a random mission generation means using user feedback.

[1472] (Claim 2)

[1473] 2. The system according to claim 1, wherein the means for storing user profile information uses a database.

[1474] (Claim 3)

[1475] 10. The system of claim 1, wherein the system adjusts the difficulty and content of the mission based on real-time sentiment analysis.

[1476] "Application example 2 when combining emotion engines"

[1477] (Claim 1)

[1478] a means for entering and storing user profile information;

[1479] means for inputting and storing the user's current mood and type of experience;

[1480] means for generating random missions based on the profile information and a current mood and type of experience;

[1481] means for notifying a user of the generated random mission;

[1482] A means for inputting and storing the results and feedback of the random missions executed by the user;

[1483] means for awarding points and badges based on the user's mission results;

[1484] means for performing sentiment analysis to recognize the emotional state of a user;

[1485] means for providing guidance to a user while performing a mission in real time;

[1486] a map service means for providing route guidance based on the generated mission;

[1487] A means of generating data to train a mission generator using feedback

[1488] A system including:

[1489] (Claim 2)

[1490] 2. The system according to claim 1, wherein the means for storing user profile information uses a database.

[1491] (Claim 3)

[1492] 10. The system of claim 1, wherein the means for performing emotion analysis analyzes facial and voice data of the user. [Explanation of symbols]

[1493] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for entering and storing user profile information; means for inputting and storing the user's current mood and type of experience; means for generating random missions based on the profile information and a current mood and type of experience; means for notifying a user of the generated random mission; A means for inputting and storing the results and feedback of the random missions executed by the user; The system includes a means for awarding points and badges based on a user's mission results.

2. 2. The system of claim 1, wherein the means for storing user profile information uses a database.

3. 10. The system of claim 1, further comprising means for generating training data for improving the random mission generator using user feedback.

Images