system

Abstract

Provide a system. [Solution] A means for obtaining user location information; The means by which the personal data of the user is obtained; A means of collecting event information from SNS using information collection means; A means of summarizing and organizing the event information collected using generative AI based on the user's personal data; a means for calculating travel times between events using a means for linking with map data and generating a time schedule; The system includes a means for presenting the generated time schedule to a user.

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, users face challenges in finding events and schedules that suit them, and are unable to use them efficiently due to information overload and lack of time. Furthermore, when users search for events and schedules, they must integrate and organize information from multiple sources, which requires considerable effort. As a result, users often end up spending their holidays or free time unscheduled and without a plan. The purpose of this invention is to solve these challenges and provide a system that allows users to easily find events and schedules that suit them. [Means for solving the problem]

[0005] This invention provides a system including means for acquiring a user's location information and personal data, means for collecting event information from SNS, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for linking with map data to calculate travel time between events and generate a time schedule, and means for presenting the generated time schedule to the user (Claim 1).

[0006] Furthermore, by collecting user feedback and including means to improve the data and algorithms, the accuracy of the suggestions will be continuously improved (Claim 2). Also, by including means to select the optimal means of transportation and calculate travel time based on the user's location information (Claim 3), the system will be able to provide more specific and convenient time schedules, allowing users to spend their time efficiently and fulfillingly.

[0007] "User location information" is data that indicates the user's current physical location, and is obtained from GPS, IP address, etc.

[0008] "Personal Data" means information about an individual, such as a user's interests, hobbies, age, gender, etc., that is used to create a user profile.

[0009] "Information collection means" refers to the methods and technologies for obtaining information from social media, websites, etc., and includes scraping tools and APIs.

[0010] "Generative AI" refers to artificial intelligence technologies that analyze and process collected data to provide useful information to users, and includes natural language processing and machine learning models.

[0011] "Map data" refers to data that indicates geographical information and positional relationships on a map, and is used to calculate travel routes and travel times.

[0012] A "time schedule" is a list of activities and plans for a specific period of time, arranged in chronological order, including travel time and activity time.

[0013] "Feedback" refers to ratings and comments provided by users regarding proposed events and services, which are used to improve the system.

[0014] "Transportation" refers to the method a user uses to get from one place to another, including walking, cycling, driving, and public transportation. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] This invention is a system that uses a user's location information and personal data to suggest events and schedules. This system collects information from social media and uses generative AI to summarize and organize it, providing users with the most suitable event information. Below, we will explain the program processing and specific examples of this system in natural language.

[0037] Overall system flow

[0038] 1. User registration and data entry

[0039] Users register using a device and enter their location information and personal data. Location information includes the user's current location (e.g., Shibuya-ku, Tokyo), and personal data includes the user's interests and preferences (e.g., music events, museums, dining, etc.).

[0040] 2. Data storage and initial settings

[0041] The server stores the location and personal data sent by the user in a database, which creates an individual profile for each user.

[0042] 3. Collecting event information from social media

[0043] The server periodically collects event information from online platforms such as social media platforms, using scraping tools and APIs to gather information related to users' interests, such as music events and museum special exhibitions. The collected information includes the event title, location, date and time, and user reviews.

[0044] 4. Summarizing and organizing information using generative AI

[0045] Next, the server uses a generation AI to summarize and organize the collected event information. The generation AI uses natural language processing technology to extract event information that matches the user's interests. This process creates an optimal event list for the user.

[0046] 5. Calculating travel time and generating time schedules

[0047] The server calculates travel time using map data based on the user's current location and selected event information. It uses Google® Maps and other map APIs to determine the optimal travel route between events and creates a time schedule. The created schedule includes the start time and travel time for each event.

[0048] 6. Event information and timetable

[0049] The server sends the generated time schedule to the user's device, which then displays detailed information about the event, including transportation options, travel time, and user reviews, making it easy for users to select events that interest them.

[0050] 7. Collecting User Feedback

[0051] Users provide feedback on the proposed events and actions, including ratings, comments, and usage history, which is then sent to the server.

[0052] 8. System Improvements

[0053] The server improves its data and algorithms based on feedback collected from users, and uses this feedback to continue training the generative AI model to improve the accuracy of future suggestions.

[0054] Specific examples

[0055] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[0056] 1. Registration and Data Entry

[0057] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[0058] 2. Data Collection

[0059] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[0060] 3. Generative AI Processing

[0061] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[0062] 4. Generate a time schedule

[0063] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[0064] 5. Presentation of Information

[0065] The server sends this schedule to the user's terminal, where detailed information is displayed.

[0066] In this way, users can quickly obtain the most suitable event information for them and spend their time in a fulfilling manner.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, art museums) along with their account information. This information is sent to the server.

[0070] Step 2:

[0071] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0072] Step 3:

[0073] The server periodically collects event information from social media sites. It uses scraping tools and APIs to collect data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[0074] Step 4:

[0075] The server stores the collected event information in a database and categorizes and organizes the information as needed.

[0076] Step 5:

[0077] The server uses a generation AI to summarize and organize the collected event information based on the user's personal data. The generation AI automatically uses text summarization technology to extract event information of high interest and create a list containing only the important information.

[0078] Step 6:

[0079] The server creates an optimal event list for the user based on the event information summarized by the generative AI, including rankings and importance.

[0080] Step 7:

[0081] The server uses map data to calculate travel time between events based on the user's current location and the event list, and uses Google Maps and map APIs to determine the optimal route and mode of transportation (walking, cycling, driving, public transportation, etc.).

[0082] Step 8:

[0083] The server generates a detailed time schedule by taking into account the calculated travel time and the event start time. For example, it might be in the format of "14:00 - Live Concert (Shibuya Ward)" -> "15:30 - Travel (15 minutes on foot)" -> "17:00 - Art Exhibition (Shibuya Ward)".

[0084] Step 9:

[0085] The server sends the generated time schedule to the user's device, which displays detailed event information, transportation options, travel times, and user reviews, allowing the user to easily select events that interest them.

[0086] Step 10:

[0087] Users can review the suggested events and provide feedback on their actual events and activities, including ratings, comments, and usage history.

[0088] Step 11:

[0089] The server improves the data and algorithms based on the feedback collected from users, analyzing the feedback information and retraining the generative AI model to improve the accuracy of future suggestions.

[0090] By following the above steps, users can easily obtain the event information and time schedule that best suits them, allowing them to spend their time to the fullest.

[0091] Example 1

[0092] 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."

[0093] Conventional event suggestion systems have difficulty providing optimal event information based on a user's location information and personal data, and the collected information may not perfectly match the user's interests. Furthermore, there is a lack of effective means for quickly organizing the collected information, which results in low accuracy and efficiency of event suggestions to users.

[0094] 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.

[0095] In this invention, the server

[0096] The system includes a means for acquiring user location information, a means for acquiring user personal data, a means for collecting event information from online platforms, a means for summarizing and organizing the collected event information based on the user's personal data using generation AI, a means for calculating travel time between events using linkage with map data to generate a time schedule, a means for presenting the generated time schedule to users, a means for users to register and input their name, email address, and password, and a means for users to input and send feedback, thereby making it possible to efficiently provide optimal event information to each user.

[0097] "User" refers to an individual who uses the System to obtain Event Information.

[0098] "Location information" is data that indicates a user's current location or a specific geographic location.

[0099] "Personal Data" refers to personal information entered by users, such as interests and preferences, name, email address, and password.

[0100] "Information collection means" refers to the technologies and methods used to collect event information from online platforms and social media.

[0101] "Generative AI" refers to a model that uses artificial intelligence technology to summarize and organize collected information and make suggestions to users.

[0102] "Map data" refers to a data set containing information indicating geographic locations and used to calculate travel distances and travel times.

[0103] A "time schedule" is a schedule that includes suggested event start times and travel times for a user.

[0104] "New registration" refers to the act of creating an account by entering a name, email address, password, etc. when a user uses the system for the first time.

[0105] "Feedback" refers to opinions and impressions such as ratings and comments provided by users to the system.

[0106] An "online platform" refers to a service that provides information via the Internet, such as social media, websites, and applications.

[0107] "Integration means" refers to methods and technologies for combining and using different data and services.

[0108] MODE FOR CARRYING OUT THE INVENTION

[0109] This invention is a system that utilizes a user's location information and personal data to optimally suggest events and schedules. This system collects a large amount of information from social media and online platforms, summarizes and organizes it using a generative AI model, and provides event information that is appropriate for the user. Below, we will explain in detail how this system is implemented.

[0110] 1. Hardware and Software

[0111] server

[0112] The server can be a cloud server or an on-premise server (e.g., Amazon Web Services, Google Cloud Platform).A database (e.g., MySQL (registered trademark), PostgreSQL) is installed on the server, and it stores user location information, personal data, and collected event information.

[0113] Terminal

[0114] The user terminal can be a smartphone, tablet, personal computer (PC), or other device. The terminal is provided with an interface for accessing the system through a dedicated application or a web browser.

[0115] Generative AI Models

[0116] The generative AI model uses advanced AI models (e.g., GPT-3 (registered trademark), BERT) that include natural language processing technology, which makes it possible to summarize and organize collected event information based on the user's personal data.

[0117] 2. Program Processing

[0118] The server receives data sent from the user's device and stores it in a database. The server periodically uses scraping tools and APIs to collect event information from social media and other online platforms. The server also uses a generative AI model to summarize and organize the collected event information. The generative AI model extracts the most relevant events based on the user's personal data and incorporates them into a time schedule.

[0119] 3. Specific Examples

[0120] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[0121] 1. User registration and data entry

[0122] The user registers by entering their name, email address, and password. They also enter their address in Shibuya Ward, Tokyo, and their interests as "music events" and "museums."

[0123] 2. Data Collection

[0124] The server collects information from SNS such as "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo." For example, suppose there is a live concert at a live music venue in Shibuya Ward from 2 PM, and a special exhibition at an art museum in Shibuya Ward from 4 PM.

[0125] 3. Generative AI Processing

[0126] The server uses a generative AI model to extract events that match the user's interests from the collected event information, selecting live concerts and art exhibitions.

[0127] 4. Generate a time schedule

[0128] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2 p.m. and an art exhibition at 3:30 p.m.

[0129] 5. Presentation of Information

[0130] The server sends this schedule to the user's terminal, where detailed information is displayed.

[0131] 4. Examples of prompts

[0132] Please enter the user's location and hobby data. If the current location is "Shibuya-ku, Tokyo" and the interests are "music events" and "museums," what kind of event information can you provide?

[0133] In this way, users can quickly obtain the most suitable event information for them and spend their time in a fulfilling manner.

[0134] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0135] Step 1: User registration and data entry

[0136] The user launches the application on their device and proceeds to the new registration screen. They enter their name, email address, password, current location (e.g., Shibuya-ku, Tokyo), and interests and preferences (e.g., music events, art museums). When the user presses the "Register" button, the entered information is sent to the server via the API. The server receives this data and stores it in the appropriate table in the database based on the user index.

[0137] Input: Name, email address, password, location information, interests and preferences

[0138] Output: User profile stored in the database

[0139] Step 2: Save data and set up

[0140] The server stores the location and personal data received from the users in a database and creates an individual profile for each user, which involves inserting the newly received data into the appropriate tables in the database, for example adding new records to the user profile table and the location information table.

[0141] Input: Location and personal data received from the user

[0142] Output: User profile created in the database

[0143] Step 3: Collect event information from social media

[0144] The server periodically collects event information from social media and other online platforms. Specifically, it uses scraping tools and APIs to search for information related to users' interests and obtain the necessary data. The collected information includes the event title, location, date and time, and user reviews. The collected data is temporarily stored.

[0145] Input: Event information from social media and online platforms

[0146] Output: Temporarily saved event information data

[0147] Step 4: Summarizing and organizing information using generative AI

[0148] The server inputs the collected event information into a generative AI model. The generative AI model (e.g., GPT-3) summarizes and organizes the collected information and extracts the event information that best suits the user's interests. This summarized and organized data is extracted and organized based on each user's profile.

[0149] Input: Collected event information

[0150] Output: Summarized and organized event information data

[0151] Step 5: Calculate travel times and generate time schedules

[0152] The server calculates the travel time from the user's current location to the selected event. It uses a map service such as Google Maps API to calculate the appropriate route and travel time. An optimal time schedule is generated along with the calculated travel time. The time schedule includes the start time and travel time of each event.

[0153] Input: User's current location, summary and organized event information

[0154] Output: Generated time schedule

[0155] Step 6: Present the event information and timetable

[0156] The server sends the generated time schedule and event information to the user's device. The device displays the received information on a GUI so that the user can easily check it. The user can view the proposed event information and detailed time schedule.

[0157] Input: Generated time schedule and event information

[0158] Output: Detailed information displayed on the terminal

[0159] Step 7: Gather user feedback

[0160] The user provides feedback on the proposed events and actions from the device. The user inputs feedback such as ratings, comments, and usage history, and presses the send button. The device then sends this feedback information to the server.

[0161] Input: User feedback (ratings, comments, usage history)

[0162] Output: Feedback data sent to the server

[0163] Step 8: Improve your system

[0164] The server stores the received feedback data in a database and uses it to train the existing generative AI model, improving the algorithm and increasing the accuracy of future suggestions.

[0165] Input: Feedback data

[0166] Output: Improved generative AI models and algorithms

[0167] The above is a specific explanation of each processing step of the system, including how the input and output are processed and calculated at each step.

[0168] (Application example 1)

[0169] 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."

[0170] In today's world, there is a growing need for efficient and convenient shopping at brick-and-mortar stores. However, it is difficult for users to plan optimal shopping routes by collecting information on numerous stores, sales, new product arrivals, and other information all at once. Furthermore, finding stores that match one's interests and preferences from the collected information takes time and effort, and users are also required to calculate travel times and select the optimal means of transportation. Conventional systems have had difficulty consistently resolving these issues.

[0171] 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.

[0172] In this invention, the server includes means for acquiring user location information, means for acquiring user personal data, means for collecting physical store information from various online platforms using information collection means, means for summarizing and organizing the collected physical store information based on the user's personal data using a generative AI model, means for calculating optimal travel routes and travel times between physical stores using linkage means with map data to generate a shopping route, and means for presenting the generated shopping route to the user, thereby enabling the user to shop efficiently and have a pleasant shopping experience.

[0173] "User location information" is information that indicates the user's current geographic location.

[0174] "Personal data" is data that includes personal information such as a user's interests and preferences.

[0175] "Information collection means" refers to the means used to collect necessary information from various online platforms.

[0176] "Physical store information" refers to sales information, new product information, business information, etc. related to physical stores.

[0177] A "generative AI model" is a model that uses artificial intelligence to summarize and organize collected information.

[0178] "Map data" refers to data containing geographical information and is used for route calculation and navigation.

[0179] "Travel route" refers to the route a user takes from one point to another.

[0180] "Travel time" refers to the time required to travel from one point to another.

[0181] A "shopping route" refers to a route planned to efficiently visit multiple destinations.

[0182] "Feedback" refers to information such as opinions and ratings provided by users.

[0183] An "algorithm" refers to a procedure or computational method for solving a specific problem.

[0184] "Means for linking with map data" refers to means for calculating travel routes and travel times using geographical information.

[0185] An "online platform" refers to a service that provides information on the Internet, such as a website or social networking site.

[0186] The present invention is a system that uses a user's location information and personal data to provide optimal store information and generate an efficient shopping route. The system includes a means for collecting information from multiple online platforms, summarizing and organizing the information using a generative AI model, and providing the user with the optimal route.

[0187] In one embodiment of the present invention, the process starts when a user uses a smartphone to input their current location and product categories they are interested in. Based on this, the server performs the following process.

[0188] 1. User registration and data entry

[0189] Users access the application from their own devices and register. When registering, they enter their location information (e.g., "Shibuya-ku, Tokyo") and personal data (e.g., "fashion," "electronic devices").

[0190] 2. Data storage and initial settings

[0191] The server stores the location and personal data sent by the user in a database, which creates an individual profile for each user.

[0192] 3. Collection by information gathering means

[0193] The server periodically collects store information from various online platforms, such as social media and store websites. This information includes sales information, new product information, and customer reviews. This information is collected using scraping tools and APIs.

[0194] 4. Summarizing and Organizing Information Using Generative AI Models

[0195] The server uses a generative AI model to summarize and organize the collected store information. The generative AI model uses natural language processing technology to extract the most appropriate information based on the user's personal data and provide useful information to the user.

[0196] 5. Creating shopping routes in conjunction with map data

[0197] Next, the server uses a method to link with map data to calculate the travel time from the user's current location to each store, thereby generating the optimal shopping route. Map services such as Google Maps API can be used.

[0198] 6. Shopping route suggestions

[0199] The generated shopping route and store information is sent to the user's smartphone, where the user can check detailed store information and travel routes through the application and shop efficiently.

[0200] 7. Collecting user feedback and improving the system

[0201] Users can provide feedback about the stores they visit and the products they buy, which is sent to a server to help improve the system's data and algorithms.

[0202] As a concrete example, if a user is located in Shibuya Ward, Tokyo, and is interested in fashion and electronics, the server collects relevant sales and new product information and provides the following prompt sentence as input to the generative AI model: "Based on my current location in Shibuya Ward, Tokyo, please tell me nearby stores where I can purchase the fashion and electronics products I'm interested in. I'd especially like to know about sales and new product information."

[0203] In this way, users can efficiently find stores that suit their interests and plan the optimal shopping route in a short amount of time.

[0204] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0205] Step 1:

[0206] A user registers for the application using a device (e.g., a smartphone). Input includes location information (e.g., "Shibuya-ku, Tokyo") and personal data (e.g., "fashion" and "electronic devices"). The registration data is sent to a server and stored in a database. This creates an individual profile for the user.

[0207] Step 2:

[0208] The server periodically collects information about the physical store from social media and various online platforms (e.g., the store's website) using scraping tools and APIs. The collected information includes sales information, new product information, and reviews. The collected information is stored in the server's database.

[0209] Step 3:

[0210] The server provides the collected store information to a generative AI model, which summarizes and organizes it. The generative AI model uses natural language processing technology to extract the most appropriate information based on the user's personal data. For example, it prioritizes summarizing store information related to specific interests and preferences. The input is the collected store information, and the output is summarized and organized store information. This output is stored in the server's database.

[0211] Step 4:

[0212] The server uses a means of linking with map data to calculate the travel time from the current location to the store. It calculates the travel time and optimal travel route using the Google Maps API, etc. For example, it can give results such as a 10-minute walk to store A and a 15-minute walk to store B. The input is the user's current location and the store's location information, and the output is the travel time and travel route.

[0213] Step 5:

[0214] The server generates a shopping route based on travel time and the optimal travel route, and sends the generated shopping route to the user's terminal. The terminal application receives it and displays detailed store information and the travel route on the user's screen. The user can proceed with shopping along the recommended route. The input is the travel route and summarized store information, and the output is the optimal shopping route.

[0215] Step 6:

[0216] After the user has finished shopping, they provide feedback about the stores they visited and the products they purchased through their device, which is then sent to the server and stored in a database.

[0217] Step 7:

[0218] The server continues to train the generative AI model based on the collected feedback, improving the data and algorithms, which in turn improves the accuracy of future suggestions. The input is the feedback data, and the output is the improved data and algorithms.

[0219] 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.

[0220] This invention is a system that uses a user's location information, personal data, and emotional data to suggest events and schedules, and provides users with the most suitable event information by collecting information from social media, summarizing the data using generative AI, linking it with map data, and using an emotional engine. Below, we will explain the program processing and specific examples of this system in natural language.

[0221] Overall system flow

[0222] 1. User registration and data entry

[0223] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums) along with their account information. This information is sent to the server.

[0224] 2. Data storage and initial settings

[0225] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0226] 3. Collecting event information from social media

[0227] The server periodically collects event information from online platforms such as social media platforms. It uses scraping tools and APIs to collect data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[0228] 4. Summarizing and organizing information using generative AI

[0229] Next, the server uses a generation AI to summarize and organize the collected event information. The generation AI uses natural language processing technology to extract event information that matches the user's interests. This process creates an optimal event list for the user.

[0230] 5. Calculating travel time and generating time schedules

[0231] The server calculates travel time using map data based on the user's current location and selected event information. It uses Google Maps and other map APIs to calculate the optimal travel route between events and create a time schedule. The created schedule includes the start time and travel time for each event.

[0232] 6. Collecting Emotional Data

[0233] The user's device is equipped with an emotion engine to collect emotional data about the proposed event, and understands the user's current emotional state through facial expression recognition and voice analysis.

[0234] 7. Leveraging Emotional Engines

[0235] The server obtains a real-time evaluation of the proposed event based on the collected emotional data. For example, it analyzes whether the user is interested or indifferent to the proposed event information and uses this information to improve the accuracy of future event suggestions.

[0236] 8. Event information and timetable

[0237] The server sends the generated time schedule to the user's device, which displays detailed event information, transportation options, travel time, user reviews, and even feedback on the user's emotional state, allowing the user to easily select events that interest them.

[0238] 9. Collecting User Feedback

[0239] Users provide feedback on proposed events and actions, including ratings, comments, usage history, and even emotional data from the emotion engine. This information is sent to the server.

[0240] 10. System Improvements

[0241] The server improves its data and algorithms based on the feedback and sentiment data collected from users, which is then used to retrain the generative AI model to improve the accuracy of future suggestions.

[0242] Specific examples

[0243] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[0244] 1. Registration and Data Entry

[0245] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[0246] 2. Data Collection

[0247] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[0248] 3. Generative AI Processing

[0249] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[0250] 4. Generate a time schedule

[0251] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[0252] 5. Presentation of Information

[0253] The server sends this schedule to the user's device, where detailed information is displayed. At this time, the emotion engine analyzes the user's emotions in real time and uses them to provide feedback on events.

[0254] 6. User Feedback

[0255] Users participate in the proposed events and provide feedback about their experiences, and emotional data collected by the emotion engine is also sent to the server.

[0256] In this way, the system takes the user's emotional state into consideration and suggests optimal event information and time schedules, allowing users to easily obtain the event information that is best suited to them and spend their time in a fulfilling manner.

[0257] The processing flow will be explained below.

[0258] Step 1:

[0259] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums) along with their account information. This information is sent to the server.

[0260] Step 2:

[0261] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0262] Step 3:

[0263] The server periodically collects event information from social media sites. Using scraping tools and APIs, it collects data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[0264] Step 4:

[0265] The server stores the collected event information in a database and categorizes and organizes the information as needed.

[0266] Step 5:

[0267] The server uses a generation AI to summarize and organize the collected event information based on the user's personal data. The generation AI uses natural language processing technology to extract interesting event information and create a list containing only the important information.

[0268] Step 6:

[0269] The server creates an optimal event list for the user based on the event information summarized by the generative AI, including rankings and importance.

[0270] Step 7:

[0271] The server uses map data to calculate travel time between events based on the user's current location and the event list, and uses Google Maps and map APIs to determine the optimal route and mode of transportation (walking, cycling, driving, public transportation, etc.).

[0272] Step 8:

[0273] The server generates a detailed time schedule by taking into account the calculated travel time and the event start time, for example, "14:00 - Live Concert (Shibuya Ward)" → "15:30 - Travel (15 minutes on foot)" → "17:00 - Art Exhibition (Shibuya Ward)".

[0274] Step 9:

[0275] The user's device uses an emotion engine to analyze the user's emotions in real time. It uses facial expression recognition and voice analysis to understand how the user feels about the proposed event information. This emotion data is then sent to the server.

[0276] Step 10:

[0277] The server receives the emotion data and obtains real-time evaluations of the proposed events. The server classifies the events that the user is interested in and those that the user is not interested in, and reflects this in future event suggestions.

[0278] Step 11:

[0279] The server then sends the generated time schedule and event information based on the results of the emotion analysis to the user's device, which then displays detailed information about the event, transportation methods, travel time, user reviews, and the results of the emotion analysis on the device's display.

[0280] Step 12:

[0281] Users provide additional emotional feedback for the proposed events, including ratings and comments on the events they have actually attended, as well as real-time emotional data from the emotion engine, which is then sent to the server.

[0282] Step 13:

[0283] The server improves its data and algorithms based on the feedback and sentiment data collected from users, analyzing the feedback information and retraining the generative AI model to improve the accuracy of future suggestions.

[0284] Through these steps, the system takes the user's emotional state into consideration and suggests optimal event information and time schedules, allowing users to easily obtain the event information that best suits them and spend their time in a fulfilling manner.

[0285] Example 2

[0286] 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."

[0287] Conventional event suggestion systems have limited means of providing event information based on users' personal data, and it is difficult to make suggestions that take into account travel time and emotional state. Furthermore, there is a lack of mechanisms for improving the system using user feedback and emotional data, making it difficult to improve the accuracy of suggestions.

[0288] 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 acquiring user location information, means for acquiring user personal data, means for collecting event information from online platforms using information collection means, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for calculating travel time between events using map data and generating a time schedule, means for collecting emotion data, means for improving event suggestions based on the collected emotion data, means for presenting the generated time schedule to the user, means for collecting user feedback, and means for improving data and algorithms based on the collected feedback. This makes it possible to generate optimal event suggestions and time schedules taking into account the user's location information and emotion data, and to improve the system based on user feedback.

[0289] "Means for obtaining user location information" refers to a device or software that has the function of determining the user's location and transmitting that location data to the system.

[0290] "Means for obtaining user personal data" refers to devices or software that have the function of collecting specific information such as the user's interests, hobbies, and personal information, and providing it to the system.

[0291] "Means for collecting event information from online platforms using information collection means" refers to tools and technologies for obtaining data about events from social media and other online platforms via the Internet.

[0292] "Means for summarizing and organizing event information collected using generative AI based on user personal data" refers to a technology that uses a generative AI model to summarize and organize large amounts of event information based on user interests and specific information.

[0293] "Means of calculating travel times between events using map data and generating a time schedule" refers to a technology that uses a map service API to calculate travel times from the user's current location to each event location and creates an optimal time schedule based on that.

[0294] "Means for collecting emotional data" refers to a device or software that analyzes the user's emotional state from facial expressions, voice, etc., and collects that data.

[0295] "Means for improving event suggestions based on collected emotional data" refers to technology that analyzes collected emotional data and makes more attractive event suggestions to users.

[0296] "Means for presenting the generated time schedule to the user" refers to a technology for visually displaying the generated time schedule and related information and providing it to the user.

[0297] "Means for collecting user feedback" means any device or software that allows users to input and submit ratings and comments about proposed events.

[0298] "Means for improving data and algorithms based on collected feedback" refers to technology that analyzes feedback collected from users and optimizes and improves the system's database and algorithms based on that feedback.

[0299] The present invention is a system for suggesting events and schedules by utilizing a user's location information, personal data, and emotional data. The system mainly includes the following elements: a means for acquiring a user's location information, a means for acquiring a user's personal data, a means for collecting event information from online platforms using an information collection means, a means for summarizing and organizing the collected event information using a generative AI, a means for calculating travel times between events using map data and generating a time schedule, a means for collecting emotional data, a means for improving event suggestions based on the collected emotional data, a means for presenting the generated time schedule to the user, and a means for collecting user feedback to improve the data and algorithms.

[0300] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, art museums) along with their account information. This information is sent to the server. The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0301] The server periodically collects event information from social media and other online platforms. It uses scraping tools and APIs (e.g., Twitter API, Instagram Graph API) to extract data based on specific keywords (e.g., music events, museums). The collected information includes event titles, locations, dates, and reviews.

[0302] The server then uses a generative AI (e.g., OpenAI's GPT model) to summarize and organize the collected event information. The generative AI uses natural language processing technology to extract event information that matches the user's interests, and this process creates an optimal event list for the user.

[0303] The server then calculates travel time using a map API such as Google Maps based on the user's current location and the selected event information. This process generates the optimal travel route and time schedule between events. Detailed event information, transportation methods, travel time, and customer reviews are then displayed on the user's device.

[0304] The user's device is equipped with an emotion engine (e.g., Face API, voice analysis engine) that grasps the user's current emotional state through facial expression recognition and voice analysis. The server analyzes the user's emotional state based on the collected emotion data and obtains a real-time evaluation of the proposed event. This data is used to improve the accuracy of future event suggestions.

[0305] Users participate in the suggested events and provide ratings and comments about their experiences. Emotional data collected by the emotion engine is also sent to the server. The server uses this collected feedback and emotion data to improve the system's data and algorithms, thereby improving the accuracy of future suggestions.

[0306] Specific examples

[0307] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system works as follows:

[0308] 1. Registration and Data Entry

[0309] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[0310] 2. Data Collection

[0311] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[0312] 3. Generative AI Processing

[0313] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[0314] 4. Generate a time schedule

[0315] The server calculates the travel time from the user's current location to each event and creates a time schedule for live music venues and art museums that are within a 10-minute walk, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[0316] 5. Presentation of Information

[0317] The server sends this schedule to the user's device, where detailed event information is displayed. At this time, the emotion engine analyzes the user's emotions in real time and obtains their feedback.

[0318] 6. User Feedback

[0319] Users participate in the proposed events and provide feedback about their experiences, and emotional data collected by the emotion engine is also sent to the server.

[0320] Prompt Sentence Examples

[0321] The prompt text to explain the system's behavior is:

[0322] "The user lives in Shibuya Ward and is interested in music events and art museums. Please generate the optimal time schedule for the user based on event information collected from social media. Please also provide detailed information about each event and travel times."

[0323] In this way, the present invention provides optimal event information and time schedules while taking into consideration the emotional state of the user, allowing the user to easily obtain event information that is optimal for them and spend a fulfilling time.

[0324] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0325] Step 1: User registration and data entry

[0326] Specific explanation

[0327] The user accesses the new registration screen using their device and enters their account information (such as name, email address, and password) along with their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums). This information is sent to the server.

[0328] input

[0329] User account information, location information, and personal data

[0330] output

[0331] User data sent to the server

[0332] Specific actions

[0333] A user opens a web browser or mobile app and accesses the new registration screen.

[0334] Enter your name, email address, password, location, and interests.

[0335] Press the "Register" button and the device will send the input data to the server.

[0336] ---

[0337] Step 2: Save data and set up

[0338] Specific explanation

[0339] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0340] input

[0341] User location information, personal data

[0342] output

[0343] User profiles stored in a database

[0344] Specific actions

[0345] The server processes the data received from the terminal and stores it in a database.

[0346] A unique user ID is assigned to each user and initial settings are performed.

[0347] Generate a keyword list based on personal data.

[0348] ---

[0349] Step 3: Collect event information from social media

[0350] Specific explanation

[0351] The server periodically collects event information from social media and other online platforms, and uses scraping tools and APIs to extract data based on specific keywords.

[0352] input

[0353] Keyword List

[0354] output

[0355] Event information stored in the database

[0356] Specific actions

[0357] The server calls the SNS API based on the keyword list.

[0358] Get information about the event (title, location, date, time, reviews, etc.).

[0359] The acquired data is saved in the "Event Information" table of the database.

[0360] ---

[0361] Step 4: Summarizing and organizing information using generative AI

[0362] Specific explanation

[0363] The server summarizes and organizes the collected event information using a generation AI, which uses natural language processing technology to extract event information that matches the user's interests.

[0364] input

[0365] Event information collected from SNS

[0366] output

[0367] Abridged Event Listing

[0368] Specific actions

[0369] The server inputs the collected event data into a generative AI model.

[0370] A generative AI model extracts event information relevant to the user's interests.

[0371] The extracted information is organized to create an optimal event list for each user.

[0372] ---

[0373] Step 5: Calculate travel times and generate time schedules

[0374] Specific explanation

[0375] The server uses a map API to calculate travel time based on the user's current location and selected event information, generating the optimal travel route and time schedule between events.

[0376] input

[0377] User's current location, event information

[0378] output

[0379] Time Schedule

[0380] Specific actions

[0381] The server sends the user's current location and the event's location information to the map API.

[0382] Get travel route and travel time.

[0383] A time schedule is generated based on the start time and travel time of each event.

[0384] ---

[0385] Step 6: Collect emotion data

[0386] Specific explanation

[0387] The user's device is equipped with an emotion engine that grasps the user's emotional state through facial expression recognition and voice analysis.

[0388] input

[0389] User facial expression data, voice data

[0390] output

[0391] Emotional Data

[0392] Specific actions

[0393] The device uses the built-in camera and microphone to capture the user's facial expressions and voice.

[0394] The emotion engine analyzes the data and determines the emotional state.

[0395] The determined emotion data is transmitted to the server.

[0396] ---

[0397] Step 7: Leverage your emotional engine

[0398] Specific explanation

[0399] The server uses the collected emotional data to evaluate the user's level of interest in the proposed event and improves the accuracy of future suggestions.

[0400] input

[0401] Emotional Data

[0402] output

[0403] Proposed algorithm with improved accuracy

[0404] Specific actions

[0405] The server receives and analyzes the emotional data and evaluates the user's emotional state.

[0406] We will adjust the suggestion algorithm and reflect this in our next event suggestions.

[0407] ---

[0408] Step 8: Present the event information and timetable

[0409] Specific explanation

[0410] The server sends the generated time schedule and event information to the user's terminal.

[0411] input

[0412] Time schedule and event information

[0413] output

[0414] Event information and schedules displayed on your device

[0415] Specific actions

[0416] The server transmits the event list and time schedule generated for each user to the terminal.

[0417] The device organizes the received information and displays it on a user interface.

[0418] Information displayed includes event details, transportation options, and reviews.

[0419] ---

[0420] Step 9: Gather user feedback

[0421] Specific explanation

[0422] Users attend the suggested events and provide feedback about their experience, including emotional data collected by the emotion engine.

[0423] input

[0424] User feedback comments and sentiment data

[0425] output

[0426] Feedback data sent to the server

[0427] Specific actions

[0428] Users use their device to enter ratings and comments and press the send button.

[0429] The emotion data collected by the emotion engine is also sent to the server in parallel.

[0430] ---

[0431] Step 10: Improve your system

[0432] Specific explanation

[0433] The server uses feedback and sentiment data collected from users to improve the system's data and algorithms.

[0434] input

[0435] Feedback data, emotion data

[0436] output

[0437] Improved algorithms and databases

[0438] Specific actions

[0439] The server analyzes the collected feedback and emotion data.

[0440] Based on the analysis results, the generative AI model is retrained and the proposed algorithm is optimized.

[0441] The improved algorithm will be reflected in the system and used to suggest future events.

[0442] (Application example 2)

[0443] 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."

[0444] Conventional event suggestion systems primarily suggest events based on the user's location information and personal data, but because they do not take into account the user's emotional state, they may not provide completely satisfying suggestions. Furthermore, because individual suggestions are not integrated into a continuous action plan, users must independently secure transportation and routes, which is inconvenient. Furthermore, they lack convenience due to the lack of real-time optimization of event suggestions and efficient transportation management using autonomous vehicles.

[0445] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for acquiring user personal data, means for collecting event information from online platforms using information collection means, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for calculating travel time between events and generating a time schedule using linkage means with map data, means for collecting and analyzing user emotion data, means for presenting the generated time schedule to an autonomous vehicle and presenting it to the user, means for optimizing event suggestions in real time based on the user emotion data, and means for selecting an optimal travel route and automatically adjusting the means of transportation. This makes it possible to optimize event suggestions and means of transportation taking emotion data into consideration.

[0446] "Means for obtaining user location information" refers to a device or system that obtains the user's current location using location information technologies such as GPS, Wi-Fi, or Bluetooth.

[0447] "Means for obtaining user personal data" refers to a device or system that collects personal data about a user, such as the user's categories of interest and past behavioral history.

[0448] "Information collection means" refers to tools and APIs for obtaining data such as event information from online platforms such as social media, blogs, and news sites.

[0449] "Generative AI" is an artificial intelligence technology that analyzes collected information and appropriately summarizes and organizes it based on the user's personal data.

[0450] "Means of linking with map data" refers to the use of map APIs and geographic information systems (GIS) to calculate travel times and routes based on the user's current location and destination.

[0451] The "means for generating a time schedule" is a system for creating an efficient schedule by taking into account the user's travel time and the start time of events.

[0452] "Means for collecting and analyzing user emotional data" refers to a system that uses devices such as cameras and microphones to analyze the user's facial expressions and tone of voice, and grasps the user's current emotional state.

[0453] The "means for presenting to the user" refers to an interface or display that displays the generated time schedule and event proposals on the user's device so that the user can view them.

[0454] The "means for optimizing event suggestions in real time" is a system for adjusting event suggestions in real time according to the user's current emotional state based on collected emotional data.

[0455] "Means for selecting optimal travel routes and automatically adjusting means of transportation" refers to a system that uses autonomous vehicles to optimize travel between events in which a user participates, and automatically selects and adjusts routes and means of transportation.

[0456] overview

[0457] This invention is a system that uses a user's location information, personal data, and emotion data to suggest optimal events and transportation methods. This system is particularly intended for efficient management of travel between events in autonomous vehicles and for providing optimal events to users in real time.

[0458] Required Hardware and Software

[0459] In order to implement this invention, the following hardware and software are required.

[0460] 1. Hardware

[0461] GPS module: To obtain the user's location information

[0462] Camera: To collect user facial expression data

[0463] Microphone: To collect user voice data

[0464] Smartphone or tablet: as the user interface

[0465] Autonomous vehicles: transportation

[0466] 2. Software

[0467] GPS tracking software: To obtain location information

[0468] Facial expression recognition software: To analyze the user's facial expressions and obtain emotional data

[0469] Voice analysis software: To analyze the user's voice and obtain emotional data

[0470] Social media scraping tools: To collect event information from online platforms

[0471] Generative AI model: To summarize the collected event information and extract the most suitable events for the user

[0472] Map APIs (e.g., Google Maps API): for travel time calculations and route optimization

[0473] Autonomous driving systems: as a means of transportation

[0474] Specific example of system operation

[0475] 1. Entering your location and personal data

[0476] Users log in to the system using a smartphone or tablet and enter their location information and personal data (such as categories of interest). This location information is acquired by a GPS module, and the personal data is stored in the system.

[0477] 2. Collecting event information

[0478] The server uses scraping tools to collect event information from social media and online platforms, retrieves event information based on specific keywords, and stores it on the server.

[0479] 3. Summarizing and organizing event information using generative AI

[0480] The server inputs the collected event information into a generative AI model, which then summarizes and organizes appropriate event information based on the user's personal data. As a concrete example, we use the following prompt sentence:

[0481] Summarize the following events and extract those that match the user's interest in music events or museums:

[0482] [Event information collected from social media]

[0483] 4. Generate travel routes and time schedules

[0484] The server uses a map API (such as Google Maps API) to calculate the travel time from the user's current location to each event venue, generates the optimal route, and creates an efficient time schedule taking into account the time slots of the proposed events.

[0485] 5. Emotional Data Collection and Analysis

[0486] Cameras and microphones inside the autonomous vehicle collect user emotional data, which is then analyzed using facial recognition and voice analysis software to understand the user's current emotional state.

[0487] 6. Real-time recommendation optimization

[0488] The server uses a generative AI model based on emotion data to optimize event suggestions in real time: for example, if a user has a positive reaction to a suggested event, the next event will be tailored to elicit a similarly positive reaction.

[0489] 7. Present the final schedule and execute the transfer

[0490] The optimized time schedule and travel route will be displayed on the autonomous vehicle's system and on the user's device, and the autonomous vehicle will then take the user to the next event venue according to the optimal route.

[0491] Through these processes, the present invention can provide users with optimal event information and efficient means of transportation, and improve the accuracy of suggestions in real time by taking into account the user's emotional state.

[0492] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0493] Step 1:

[0494] Users log in to the app using their smartphone or tablet and enter their location and personal data, including their current location (e.g., Shibuya-ku, Tokyo) obtained via a GPS module and categories of interest (e.g., music events, museums). The server receives this information, stores it in a database, and creates an individual profile for the user.

[0495] Step 2:

[0496] The server collects event information from social media and online platforms. It uses information collection tools (scraping tools and APIs) to obtain event information based on specific keywords (e.g., music events, art museums). The collected event information includes the event title, location, date and time, and user reviews. It performs a search based on the entered keyword information and stores the obtained event data in a database.

[0497] Step 3:

[0498] The server uses a generative AI model to summarize and organize the collected event information. A prompt is input to the generative AI model, which then summarizes the event based on specific keywords. For example, the following prompt is given to the generative AI model:

[0499] Summarize the following events and extract those that match the user's interest in music events or museums:

[0500] [Event information collected from social media]

[0501] The generative AI model extracts relevant events based on the prompt and outputs summarized information, which the server stores in a database.

[0502] Step 4:

[0503] The server uses a map API (e.g., Google Maps API) to calculate travel times and generate a time schedule. The user's current location information obtained from the database and summarized event information are input into the map API to calculate travel times and routes. The obtained travel time data is used to optimize the daily schedule. For example, a time schedule is generated that includes a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m. The generated schedule is saved on the server.

[0504] Step 5:

[0505] Cameras and microphones installed inside the autonomous vehicle are used to collect user emotional data. Facial expression recognition software and voice analysis software are used to analyze the user's facial and voice data to determine their current emotional state (e.g., positive, negative). The obtained emotional data is sent to a server and added to the user's profile.

[0506] Step 6:

[0507] The server optimizes event suggestions in real time based on the collected emotional data. It then uses the generative AI model again to suggest the next event, taking into account the emotional data. This process re-extracts the events that are best suited to the user's emotional state (e.g., events that can be expected to provide a similarly positive experience if the user is in a positive state). The optimized event suggestions are then displayed on the user's device.

[0508] Step 7:

[0509] The final timetable and route are presented to the user's device and the autonomous vehicle's system. The autonomous vehicle then selects the optimal route based on this schedule and drives the user to their destination. Emotional data is continuously monitored during the journey, and suggestions are adjusted in real time as needed.

[0510] Through these processes, the system can provide users with the most appropriate event information and efficient transportation methods, and improve the accuracy of suggestions in real time by taking into account the user's emotional state.

[0511] 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.

[0512] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0513] 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.

[0514] [Second embodiment]

[0515] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0516] 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.

[0517] 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).

[0518] 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.

[0519] 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.

[0520] 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).

[0521] 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.

[0522] 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.

[0523] 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.

[0524] 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.

[0525] 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.

[0526] 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."

[0527] This invention is a system that uses a user's location information and personal data to suggest events and schedules. This system collects information from social media and uses generative AI to summarize and organize it, providing users with the most suitable event information. Below, we will explain the program processing and specific examples of this system in natural language.

[0528] Overall system flow

[0529] 1. User registration and data entry

[0530] Users register using a device and enter their location information and personal data. Location information includes the user's current location (e.g., Shibuya-ku, Tokyo), and personal data includes the user's interests and preferences (e.g., music events, museums, dining, etc.).

[0531] 2. Data storage and initial settings

[0532] The server stores the location and personal data sent by the user in a database, which creates an individual profile for each user.

[0533] 3. Collecting event information from social media

[0534] The server periodically collects event information from online platforms such as social media platforms, using scraping tools and APIs to gather information related to users' interests, such as music events and museum special exhibitions. The collected information includes the event title, location, date and time, and user reviews.

[0535] 4. Summarizing and organizing information using generative AI

[0536] Next, the server uses a generation AI to summarize and organize the collected event information. The generation AI uses natural language processing technology to extract event information that matches the user's interests. This process creates an optimal event list for the user.

[0537] 5. Calculating travel time and generating time schedules

[0538] The server calculates travel time using map data based on the user's current location and selected event information. It uses Google Maps and other map APIs to calculate the optimal travel route between events and create a time schedule. The created schedule includes the start time and travel time for each event.

[0539] 6. Event information and timetable

[0540] The server sends the generated time schedule to the user's device, which then displays detailed information about the event, including transportation options, travel time, and user reviews, making it easy for users to select events that interest them.

[0541] 7. Collecting User Feedback

[0542] Users provide feedback on the proposed events and actions, including ratings, comments, and usage history, which is then sent to the server.

[0543] 8. System Improvements

[0544] The server improves its data and algorithms based on feedback collected from users, and uses this feedback to continue training the generative AI model to improve the accuracy of future suggestions.

[0545] Specific examples

[0546] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[0547] 1. Registration and Data Entry

[0548] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[0549] 2. Data Collection

[0550] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[0551] 3. Generative AI Processing

[0552] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[0553] 4. Generate a time schedule

[0554] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[0555] 5. Presentation of Information

[0556] The server sends this schedule to the user's terminal, where detailed information is displayed.

[0557] In this way, users can quickly obtain the most suitable event information for them and spend their time in a fulfilling manner.

[0558] The processing flow will be explained below.

[0559] Step 1:

[0560] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, art museums) along with their account information. This information is sent to the server.

[0561] Step 2:

[0562] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0563] Step 3:

[0564] The server periodically collects event information from social media sites. It uses scraping tools and APIs to collect data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[0565] Step 4:

[0566] The server stores the collected event information in a database and categorizes and organizes the information as needed.

[0567] Step 5:

[0568] The server uses a generation AI to summarize and organize the collected event information based on the user's personal data. The generation AI automatically uses text summarization technology to extract event information of high interest and create a list containing only the important information.

[0569] Step 6:

[0570] The server creates an optimal event list for the user based on the event information summarized by the generative AI, including rankings and importance.

[0571] Step 7:

[0572] The server uses map data to calculate travel time between events based on the user's current location and the event list, and uses Google Maps and map APIs to determine the optimal route and mode of transportation (walking, cycling, driving, public transportation, etc.).

[0573] Step 8:

[0574] The server generates a detailed time schedule by taking into account the calculated travel time and the event start time. For example, it might be in the format of "14:00 - Live Concert (Shibuya Ward)" -> "15:30 - Travel (15 minutes on foot)" -> "17:00 - Art Exhibition (Shibuya Ward)".

[0575] Step 9:

[0576] The server sends the generated time schedule to the user's device, which displays detailed event information, transportation options, travel times, and user reviews, allowing the user to easily select events that interest them.

[0577] Step 10:

[0578] Users can review the suggested events and provide feedback on their actual events and activities, including ratings, comments, and usage history.

[0579] Step 11:

[0580] The server improves the data and algorithms based on the feedback collected from users, analyzing the feedback information and retraining the generative AI model to improve the accuracy of future suggestions.

[0581] By following the above steps, users can easily obtain the event information and time schedule that best suits them, allowing them to spend their time to the fullest.

[0582] Example 1

[0583] 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."

[0584] Conventional event suggestion systems have difficulty providing optimal event information based on a user's location information and personal data, and the collected information may not perfectly match the user's interests. Furthermore, there is a lack of effective means for quickly organizing the collected information, which results in low accuracy and efficiency of event suggestions to users.

[0585] 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.

[0586] In this invention, the server

[0587] The system includes a means for acquiring user location information, a means for acquiring user personal data, a means for collecting event information from online platforms, a means for summarizing and organizing the collected event information based on the user's personal data using generation AI, a means for calculating travel time between events using linkage with map data to generate a time schedule, a means for presenting the generated time schedule to users, a means for users to register and input their name, email address, and password, and a means for users to input and send feedback, thereby making it possible to efficiently provide optimal event information to each user.

[0588] "User" refers to an individual who uses the System to obtain Event Information.

[0589] "Location information" is data that indicates a user's current location or a specific geographic location.

[0590] "Personal Data" refers to personal information entered by users, such as interests and preferences, name, email address, and password.

[0591] "Information collection means" refers to the technologies and methods used to collect event information from online platforms and social media.

[0592] "Generative AI" refers to a model that uses artificial intelligence technology to summarize and organize collected information and make suggestions to users.

[0593] "Map data" refers to a data set containing information indicating geographic locations and used to calculate travel distances and travel times.

[0594] A "time schedule" is a schedule that includes suggested event start times and travel times for a user.

[0595] "New registration" refers to the act of creating an account by entering a name, email address, password, etc. when a user uses the system for the first time.

[0596] "Feedback" refers to opinions and impressions such as ratings and comments provided by users to the system.

[0597] An "online platform" refers to a service that provides information via the Internet, such as social media, websites, and applications.

[0598] "Integration means" refers to methods and technologies for combining and using different data and services.

[0599] MODE FOR CARRYING OUT THE INVENTION

[0600] This invention is a system that utilizes a user's location information and personal data to optimally suggest events and schedules. This system collects a large amount of information from social media and online platforms, summarizes and organizes it using a generative AI model, and provides event information that is appropriate for the user. Below, we will explain in detail how this system is implemented.

[0601] 1. Hardware and Software

[0602] server

[0603] The server can be a cloud server or an on-premise server (e.g. Amazon Web Services, Google Cloud Platform).A database (e.g. MySQL, PostgreSQL) is installed on the server and stores user location information, personal data, and collected event information.

[0604] Terminal

[0605] The user terminal can be a smartphone, tablet, personal computer (PC), or other device. The terminal is provided with an interface for accessing the system through a dedicated application or a web browser.

[0606] Generative AI Models

[0607] The generative AI model uses advanced AI models (e.g., GPT-3, BERT) that include natural language processing technology, which makes it possible to summarize and organize collected event information based on the user's personal data.

[0608] 2. Program Processing

[0609] The server receives data sent from the user's device and stores it in a database. The server periodically uses scraping tools and APIs to collect event information from social media and other online platforms. The server also uses a generative AI model to summarize and organize the collected event information. The generative AI model extracts the most relevant events based on the user's personal data and incorporates them into a time schedule.

[0610] 3. Specific Examples

[0611] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[0612] 1. User registration and data entry

[0613] The user registers by entering their name, email address, and password. They also enter their address in Shibuya Ward, Tokyo, and their interests as "music events" and "museums."

[0614] 2. Data Collection

[0615] The server collects information from SNS such as "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo." For example, suppose there is a live concert at a live music venue in Shibuya Ward from 2 PM, and a special exhibition at an art museum in Shibuya Ward from 4 PM.

[0616] 3. Generative AI Processing

[0617] The server uses a generative AI model to extract events that match the user's interests from the collected event information, selecting live concerts and art exhibitions.

[0618] 4. Generate a time schedule

[0619] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2 p.m. and an art exhibition at 3:30 p.m.

[0620] 5. Presentation of Information

[0621] The server sends this schedule to the user's terminal, where detailed information is displayed.

[0622] 4. Examples of prompts

[0623] Please enter the user's location and hobby data. If the current location is "Shibuya-ku, Tokyo" and the interests are "music events" and "museums," what kind of event information can you provide?

[0624] In this way, users can quickly obtain the most suitable event information for them and spend their time in a fulfilling manner.

[0625] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0626] Step 1: User registration and data entry

[0627] The user launches the application on their device and proceeds to the new registration screen. They enter their name, email address, password, current location (e.g., Shibuya-ku, Tokyo), and interests and preferences (e.g., music events, art museums). When the user presses the "Register" button, the entered information is sent to the server via the API. The server receives this data and stores it in the appropriate table in the database based on the user index.

[0628] Input: Name, email address, password, location information, interests and preferences

[0629] Output: User profile stored in the database

[0630] Step 2: Save data and set up

[0631] The server stores the location and personal data received from the users in a database and creates an individual profile for each user, which involves inserting the newly received data into the appropriate tables in the database, for example adding new records to the user profile table and the location information table.

[0632] Input: Location and personal data received from the user

[0633] Output: User profile created in the database

[0634] Step 3: Collect event information from social media

[0635] The server periodically collects event information from social media and other online platforms. Specifically, it uses scraping tools and APIs to search for information related to users' interests and obtain the necessary data. The collected information includes the event title, location, date and time, and user reviews. The collected data is temporarily stored.

[0636] Input: Event information from social media and online platforms

[0637] Output: Temporarily saved event information data

[0638] Step 4: Summarizing and organizing information using generative AI

[0639] The server inputs the collected event information into a generative AI model. The generative AI model (e.g., GPT-3) summarizes and organizes the collected information and extracts the event information that best suits the user's interests. This summarized and organized data is extracted and organized based on each user's profile.

[0640] Input: Collected event information

[0641] Output: Summarized and organized event information data

[0642] Step 5: Calculate travel times and generate time schedules

[0643] The server calculates the travel time from the user's current location to the selected event. It uses a map service such as Google Maps API to calculate the appropriate route and travel time. An optimal time schedule is generated along with the calculated travel time. The time schedule includes the start time and travel time of each event.

[0644] Input: User's current location, summary and organized event information

[0645] Output: Generated time schedule

[0646] Step 6: Present the event information and timetable

[0647] The server sends the generated time schedule and event information to the user's device. The device displays the received information on a GUI so that the user can easily check it. The user can view the proposed event information and detailed time schedule.

[0648] Input: Generated time schedule and event information

[0649] Output: Detailed information displayed on the terminal

[0650] Step 7: Gather user feedback

[0651] The user provides feedback on the proposed events and actions from the device. The user inputs feedback such as ratings, comments, and usage history, and presses the send button. The device then sends this feedback information to the server.

[0652] Input: User feedback (ratings, comments, usage history)

[0653] Output: Feedback data sent to the server

[0654] Step 8: Improve your system

[0655] The server stores the received feedback data in a database and uses it to train the existing generative AI model, improving the algorithm and increasing the accuracy of future suggestions.

[0656] Input: Feedback data

[0657] Output: Improved generative AI models and algorithms

[0658] The above is a specific explanation of each processing step of the system, including how the input and output are processed and calculated at each step.

[0659] (Application example 1)

[0660] 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."

[0661] In today's world, there is a growing need for efficient and convenient shopping at brick-and-mortar stores. However, it is difficult for users to plan optimal shopping routes by collecting information on numerous stores, sales, new product arrivals, and other information all at once. Furthermore, finding stores that match one's interests and preferences from the collected information takes time and effort, and users are also required to calculate travel times and select the optimal means of transportation. Conventional systems have had difficulty consistently resolving these issues.

[0662] 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.

[0663] In this invention, the server includes means for acquiring user location information, means for acquiring user personal data, means for collecting physical store information from various online platforms using information collection means, means for summarizing and organizing the collected physical store information based on the user's personal data using a generative AI model, means for calculating optimal travel routes and travel times between physical stores using linkage means with map data to generate a shopping route, and means for presenting the generated shopping route to the user, thereby enabling the user to shop efficiently and have a pleasant shopping experience.

[0664] "User location information" is information that indicates the user's current geographic location.

[0665] "Personal data" is data that includes personal information such as a user's interests and preferences.

[0666] "Information collection means" refers to the means used to collect necessary information from various online platforms.

[0667] "Physical store information" refers to sales information, new product information, business information, etc. related to physical stores.

[0668] A "generative AI model" is a model that uses artificial intelligence to summarize and organize collected information.

[0669] "Map data" refers to data containing geographical information and is used for route calculation and navigation.

[0670] "Travel route" refers to the route a user takes from one point to another.

[0671] "Travel time" refers to the time required to travel from one point to another.

[0672] A "shopping route" refers to a route planned to efficiently visit multiple destinations.

[0673] "Feedback" refers to information such as opinions and ratings provided by users.

[0674] An "algorithm" refers to a procedure or computational method for solving a specific problem.

[0675] "Means for linking with map data" refers to means for calculating travel routes and travel times using geographical information.

[0676] An "online platform" refers to a service that provides information on the Internet, such as a website or social networking site.

[0677] The present invention is a system that uses a user's location information and personal data to provide optimal store information and generate an efficient shopping route. The system includes a means for collecting information from multiple online platforms, summarizing and organizing the information using a generative AI model, and providing the user with the optimal route.

[0678] In one embodiment of the present invention, the process starts when a user uses a smartphone to input their current location and product categories they are interested in. Based on this, the server performs the following process.

[0679] 1. User registration and data entry

[0680] Users access the application from their own devices and register. When registering, they enter their location information (e.g., "Shibuya-ku, Tokyo") and personal data (e.g., "fashion," "electronic devices").

[0681] 2. Data storage and initial settings

[0682] The server stores the location and personal data sent by the user in a database, which creates an individual profile for each user.

[0683] 3. Collection by information gathering means

[0684] The server periodically collects store information from various online platforms, such as social media and store websites. This information includes sales information, new product information, and customer reviews. This information is collected using scraping tools and APIs.

[0685] 4. Summarizing and Organizing Information Using Generative AI Models

[0686] The server uses a generative AI model to summarize and organize the collected store information. The generative AI model uses natural language processing technology to extract the most appropriate information based on the user's personal data and provide useful information to the user.

[0687] 5. Creating shopping routes in conjunction with map data

[0688] Next, the server uses a method to link with map data to calculate the travel time from the user's current location to each store, thereby generating the optimal shopping route. Map services such as Google Maps API can be used.

[0689] 6. Shopping route suggestions

[0690] The generated shopping route and store information is sent to the user's smartphone, where the user can check detailed store information and travel routes through the application and shop efficiently.

[0691] 7. Collecting user feedback and improving the system

[0692] Users can provide feedback about the stores they visit and the products they buy, which is sent to a server to help improve the system's data and algorithms.

[0693] As a concrete example, if a user is located in Shibuya Ward, Tokyo, and is interested in fashion and electronics, the server collects relevant sales and new product information and provides the following prompt sentence as input to the generative AI model: "Based on my current location in Shibuya Ward, Tokyo, please tell me nearby stores where I can purchase the fashion and electronics products I'm interested in. I'd especially like to know about sales and new product information."

[0694] In this way, users can efficiently find stores that suit their interests and plan the optimal shopping route in a short amount of time.

[0695] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0696] Step 1:

[0697] A user registers for the application using a device (e.g., a smartphone). Input includes location information (e.g., "Shibuya-ku, Tokyo") and personal data (e.g., "fashion" and "electronic devices"). The registration data is sent to a server and stored in a database. This creates an individual profile for the user.

[0698] Step 2:

[0699] The server periodically collects information about the physical store from social media and various online platforms (e.g., the store's website) using scraping tools and APIs. The collected information includes sales information, new product information, and reviews. The collected information is stored in the server's database.

[0700] Step 3:

[0701] The server provides the collected store information to a generative AI model, which summarizes and organizes it. The generative AI model uses natural language processing technology to extract the most appropriate information based on the user's personal data. For example, it prioritizes summarizing store information related to specific interests and preferences. The input is the collected store information, and the output is summarized and organized store information. This output is stored in the server's database.

[0702] Step 4:

[0703] The server uses a means of linking with map data to calculate the travel time from the current location to the store. It calculates the travel time and optimal travel route using the Google Maps API, etc. For example, it can give results such as a 10-minute walk to store A and a 15-minute walk to store B. The input is the user's current location and the store's location information, and the output is the travel time and travel route.

[0704] Step 5:

[0705] The server generates a shopping route based on travel time and the optimal travel route, and sends the generated shopping route to the user's terminal. The terminal application receives it and displays detailed store information and the travel route on the user's screen. The user can proceed with shopping along the recommended route. The input is the travel route and summarized store information, and the output is the optimal shopping route.

[0706] Step 6:

[0707] After the user has finished shopping, they provide feedback about the stores they visited and the products they purchased through their device, which is then sent to the server and stored in a database.

[0708] Step 7:

[0709] The server continues to train the generative AI model based on the collected feedback, improving the data and algorithms, which in turn improves the accuracy of future suggestions. The input is the feedback data, and the output is the improved data and algorithms.

[0710] 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.

[0711] This invention is a system that uses a user's location information, personal data, and emotional data to suggest events and schedules, and provides users with the most suitable event information by collecting information from social media, summarizing the data using generative AI, linking it with map data, and using an emotional engine. Below, we will explain the program processing and specific examples of this system in natural language.

[0712] Overall system flow

[0713] 1. User registration and data entry

[0714] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums) along with their account information. This information is sent to the server.

[0715] 2. Data storage and initial settings

[0716] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0717] 3. Collecting event information from social media

[0718] The server periodically collects event information from online platforms such as social media platforms. It uses scraping tools and APIs to collect data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[0719] 4. Summarizing and organizing information using generative AI

[0720] Next, the server uses a generation AI to summarize and organize the collected event information. The generation AI uses natural language processing technology to extract event information that matches the user's interests. This process creates an optimal event list for the user.

[0721] 5. Calculating travel time and generating time schedules

[0722] The server calculates travel time using map data based on the user's current location and selected event information. It uses Google Maps and other map APIs to calculate the optimal travel route between events and create a time schedule. The created schedule includes the start time and travel time for each event.

[0723] 6. Collecting Emotional Data

[0724] The user's device is equipped with an emotion engine to collect emotional data about the proposed event, and understands the user's current emotional state through facial expression recognition and voice analysis.

[0725] 7. Leveraging Emotional Engines

[0726] The server obtains a real-time evaluation of the proposed event based on the collected emotional data. For example, it analyzes whether the user is interested or indifferent to the proposed event information and uses this information to improve the accuracy of future event suggestions.

[0727] 8. Event information and timetable

[0728] The server sends the generated time schedule to the user's device, which displays detailed event information, transportation options, travel time, user reviews, and even feedback on the user's emotional state, allowing the user to easily select events that interest them.

[0729] 9. Collecting User Feedback

[0730] Users provide feedback on proposed events and actions, including ratings, comments, usage history, and even emotional data from the emotion engine. This information is sent to the server.

[0731] 10. System Improvements

[0732] The server improves its data and algorithms based on the feedback and sentiment data collected from users, which is then used to retrain the generative AI model to improve the accuracy of future suggestions.

[0733] Specific examples

[0734] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[0735] 1. Registration and Data Entry

[0736] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[0737] 2. Data Collection

[0738] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[0739] 3. Generative AI Processing

[0740] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[0741] 4. Generate a time schedule

[0742] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[0743] 5. Presentation of Information

[0744] The server sends this schedule to the user's device, where detailed information is displayed. At this time, the emotion engine analyzes the user's emotions in real time and uses them to provide feedback on events.

[0745] 6. User Feedback

[0746] Users participate in the proposed events and provide feedback about their experiences, and emotional data collected by the emotion engine is also sent to the server.

[0747] In this way, the system takes the user's emotional state into consideration and suggests optimal event information and time schedules, allowing users to easily obtain the event information that is best suited to them and spend their time in a fulfilling manner.

[0748] The processing flow will be explained below.

[0749] Step 1:

[0750] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums) along with their account information. This information is sent to the server.

[0751] Step 2:

[0752] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0753] Step 3:

[0754] The server periodically collects event information from social media sites. Using scraping tools and APIs, it collects data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[0755] Step 4:

[0756] The server stores the collected event information in a database and categorizes and organizes the information as needed.

[0757] Step 5:

[0758] The server uses a generation AI to summarize and organize the collected event information based on the user's personal data. The generation AI uses natural language processing technology to extract interesting event information and create a list containing only the important information.

[0759] Step 6:

[0760] The server creates an optimal event list for the user based on the event information summarized by the generative AI, including rankings and importance.

[0761] Step 7:

[0762] The server uses map data to calculate travel time between events based on the user's current location and the event list, and uses Google Maps and map APIs to determine the optimal route and mode of transportation (walking, cycling, driving, public transportation, etc.).

[0763] Step 8:

[0764] The server generates a detailed time schedule by taking into account the calculated travel time and the event start time, for example, "14:00 - Live Concert (Shibuya Ward)" → "15:30 - Travel (15 minutes on foot)" → "17:00 - Art Exhibition (Shibuya Ward)".

[0765] Step 9:

[0766] The user's device uses an emotion engine to analyze the user's emotions in real time. It uses facial expression recognition and voice analysis to understand how the user feels about the proposed event information. This emotion data is then sent to the server.

[0767] Step 10:

[0768] The server receives the emotion data and obtains real-time evaluations of the proposed events. The server classifies the events that the user is interested in and those that the user is not interested in, and reflects this in future event suggestions.

[0769] Step 11:

[0770] The server then sends the generated time schedule and event information based on the results of the emotion analysis to the user's device, which then displays detailed information about the event, transportation methods, travel time, user reviews, and the results of the emotion analysis on the device's display.

[0771] Step 12:

[0772] Users provide additional emotional feedback for the proposed events, including ratings and comments on the events they have actually attended, as well as real-time emotional data from the emotion engine, which is then sent to the server.

[0773] Step 13:

[0774] The server improves its data and algorithms based on the feedback and sentiment data collected from users, analyzing the feedback information and retraining the generative AI model to improve the accuracy of future suggestions.

[0775] Through these steps, the system takes the user's emotional state into consideration and suggests optimal event information and time schedules, allowing users to easily obtain the event information that best suits them and spend their time in a fulfilling manner.

[0776] Example 2

[0777] 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."

[0778] Conventional event suggestion systems have limited means of providing event information based on users' personal data, and it is difficult to make suggestions that take into account travel time and emotional state. Furthermore, there is a lack of mechanisms for improving the system using user feedback and emotional data, making it difficult to improve the accuracy of suggestions.

[0779] 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 acquiring user location information, means for acquiring user personal data, means for collecting event information from online platforms using information collection means, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for calculating travel time between events using map data and generating a time schedule, means for collecting emotion data, means for improving event suggestions based on the collected emotion data, means for presenting the generated time schedule to the user, means for collecting user feedback, and means for improving data and algorithms based on the collected feedback. This makes it possible to generate optimal event suggestions and time schedules taking into account the user's location information and emotion data, and to improve the system based on user feedback.

[0780] "Means for obtaining user location information" refers to a device or software that has the function of determining the user's location and transmitting that location data to the system.

[0781] "Means for obtaining user personal data" refers to devices or software that have the function of collecting specific information such as the user's interests, hobbies, and personal information, and providing it to the system.

[0782] "Means for collecting event information from online platforms using information collection means" refers to tools and technologies for obtaining data about events from social media and other online platforms via the Internet.

[0783] "Means for summarizing and organizing event information collected using generative AI based on user personal data" refers to a technology that uses a generative AI model to summarize and organize large amounts of event information based on user interests and specific information.

[0784] "Means of calculating travel times between events using map data and generating a time schedule" refers to a technology that uses a map service API to calculate travel times from the user's current location to each event location and creates an optimal time schedule based on that.

[0785] "Means for collecting emotional data" refers to a device or software that analyzes the user's emotional state from facial expressions, voice, etc., and collects that data.

[0786] "Means for improving event suggestions based on collected emotional data" refers to technology that analyzes collected emotional data and makes more attractive event suggestions to users.

[0787] "Means for presenting the generated time schedule to the user" refers to a technology for visually displaying the generated time schedule and related information and providing it to the user.

[0788] "Means for collecting user feedback" means any device or software that allows users to input and submit ratings and comments about proposed events.

[0789] "Means for improving data and algorithms based on collected feedback" refers to technology that analyzes feedback collected from users and optimizes and improves the system's database and algorithms based on that feedback.

[0790] The present invention is a system for suggesting events and schedules by utilizing a user's location information, personal data, and emotional data. The system mainly includes the following elements: a means for acquiring a user's location information, a means for acquiring a user's personal data, a means for collecting event information from online platforms using an information collection means, a means for summarizing and organizing the collected event information using a generative AI, a means for calculating travel times between events using map data and generating a time schedule, a means for collecting emotional data, a means for improving event suggestions based on the collected emotional data, a means for presenting the generated time schedule to the user, and a means for collecting user feedback to improve the data and algorithms.

[0791] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, art museums) along with their account information. This information is sent to the server. The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0792] The server periodically collects event information from social media and other online platforms. It uses scraping tools and APIs (e.g., Twitter API, Instagram Graph API) to extract data based on specific keywords (e.g., music events, museums). The collected information includes event titles, locations, dates, and reviews.

[0793] The server then uses a generative AI (e.g., OpenAI's GPT model) to summarize and organize the collected event information. The generative AI uses natural language processing technology to extract event information that matches the user's interests, and this process creates an optimal event list for the user.

[0794] The server then calculates travel time using a map API such as Google Maps based on the user's current location and the selected event information. This process generates the optimal travel route and time schedule between events. Detailed event information, transportation methods, travel time, and customer reviews are then displayed on the user's device.

[0795] The user's device is equipped with an emotion engine (e.g., Face API, voice analysis engine) that grasps the user's current emotional state through facial expression recognition and voice analysis. The server analyzes the user's emotional state based on the collected emotion data and obtains a real-time evaluation of the proposed event. This data is used to improve the accuracy of future event suggestions.

[0796] Users participate in the suggested events and provide ratings and comments about their experiences. Emotional data collected by the emotion engine is also sent to the server. The server uses this collected feedback and emotion data to improve the system's data and algorithms, thereby improving the accuracy of future suggestions.

[0797] Specific examples

[0798] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system works as follows:

[0799] 1. Registration and Data Entry

[0800] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[0801] 2. Data Collection

[0802] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[0803] 3. Generative AI Processing

[0804] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[0805] 4. Generate a time schedule

[0806] The server calculates the travel time from the user's current location to each event and creates a time schedule for live music venues and art museums that are within a 10-minute walk, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[0807] 5. Presentation of Information

[0808] The server sends this schedule to the user's device, where detailed event information is displayed. At this time, the emotion engine analyzes the user's emotions in real time and obtains their feedback.

[0809] 6. User Feedback

[0810] Users participate in the proposed events and provide feedback about their experiences, and emotional data collected by the emotion engine is also sent to the server.

[0811] Prompt Sentence Examples

[0812] The prompt text to explain the system's behavior is:

[0813] "The user lives in Shibuya Ward and is interested in music events and art museums. Please generate the optimal time schedule for the user based on event information collected from social media. Please also provide detailed information about each event and travel times."

[0814] In this way, the present invention provides optimal event information and time schedules while taking into consideration the emotional state of the user, allowing the user to easily obtain event information that is optimal for them and spend a fulfilling time.

[0815] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0816] Step 1: User registration and data entry

[0817] Specific explanation

[0818] The user accesses the new registration screen using their device and enters their account information (such as name, email address, and password) along with their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums). This information is sent to the server.

[0819] input

[0820] User account information, location information, and personal data

[0821] output

[0822] User data sent to the server

[0823] Specific actions

[0824] A user opens a web browser or mobile app and accesses the new registration screen.

[0825] Enter your name, email address, password, location, and interests.

[0826] Press the "Register" button and the device will send the input data to the server.

[0827] ---

[0828] Step 2: Save data and set up

[0829] Specific explanation

[0830] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[0831] input

[0832] User location information, personal data

[0833] output

[0834] User profiles stored in a database

[0835] Specific actions

[0836] The server processes the data received from the terminal and stores it in a database.

[0837] A unique user ID is assigned to each user and initial settings are performed.

[0838] Generate a keyword list based on personal data.

[0839] ---

[0840] Step 3: Collect event information from social media

[0841] Specific explanation

[0842] The server periodically collects event information from social media and other online platforms, and uses scraping tools and APIs to extract data based on specific keywords.

[0843] input

[0844] Keyword List

[0845] output

[0846] Event information stored in the database

[0847] Specific actions

[0848] The server calls the SNS API based on the keyword list.

[0849] Get information about the event (title, location, date, time, reviews, etc.).

[0850] The acquired data is saved in the "Event Information" table of the database.

[0851] ---

[0852] Step 4: Summarizing and organizing information using generative AI

[0853] Specific explanation

[0854] The server summarizes and organizes the collected event information using a generation AI, which uses natural language processing technology to extract event information that matches the user's interests.

[0855] input

[0856] Event information collected from SNS

[0857] output

[0858] Abridged Event Listing

[0859] Specific actions

[0860] The server inputs the collected event data into a generative AI model.

[0861] A generative AI model extracts event information relevant to the user's interests.

[0862] The extracted information is organized to create an optimal event list for each user.

[0863] ---

[0864] Step 5: Calculate travel times and generate time schedules

[0865] Specific explanation

[0866] The server uses a map API to calculate travel time based on the user's current location and selected event information, generating the optimal travel route and time schedule between events.

[0867] input

[0868] User's current location, event information

[0869] output

[0870] Time Schedule

[0871] Specific actions

[0872] The server sends the user's current location and the event's location information to the map API.

[0873] Get travel route and travel time.

[0874] A time schedule is generated based on the start time and travel time of each event.

[0875] ---

[0876] Step 6: Collect emotion data

[0877] Specific explanation

[0878] The user's device is equipped with an emotion engine that grasps the user's emotional state through facial expression recognition and voice analysis.

[0879] input

[0880] User facial expression data, voice data

[0881] output

[0882] Emotional Data

[0883] Specific actions

[0884] The device uses the built-in camera and microphone to capture the user's facial expressions and voice.

[0885] The emotion engine analyzes the data and determines the emotional state.

[0886] The determined emotion data is transmitted to the server.

[0887] ---

[0888] Step 7: Leverage your emotional engine

[0889] Specific explanation

[0890] The server uses the collected emotional data to evaluate the user's level of interest in the proposed event and improves the accuracy of future suggestions.

[0891] input

[0892] Emotional Data

[0893] output

[0894] Proposed algorithm with improved accuracy

[0895] Specific actions

[0896] The server receives and analyzes the emotional data and evaluates the user's emotional state.

[0897] We will adjust the suggestion algorithm and reflect this in our next event suggestions.

[0898] ---

[0899] Step 8: Present the event information and timetable

[0900] Specific explanation

[0901] The server sends the generated time schedule and event information to the user's terminal.

[0902] input

[0903] Time schedule and event information

[0904] output

[0905] Event information and schedules displayed on your device

[0906] Specific actions

[0907] The server transmits the event list and time schedule generated for each user to the terminal.

[0908] The device organizes the received information and displays it on a user interface.

[0909] Information displayed includes event details, transportation options, and reviews.

[0910] ---

[0911] Step 9: Gather user feedback

[0912] Specific explanation

[0913] Users attend the suggested events and provide feedback about their experience, including emotional data collected by the emotion engine.

[0914] input

[0915] User feedback comments and sentiment data

[0916] output

[0917] Feedback data sent to the server

[0918] Specific actions

[0919] Users use their device to enter ratings and comments and press the send button.

[0920] The emotion data collected by the emotion engine is also sent to the server in parallel.

[0921] ---

[0922] Step 10: Improve your system

[0923] Specific explanation

[0924] The server uses feedback and sentiment data collected from users to improve the system's data and algorithms.

[0925] input

[0926] Feedback data, emotion data

[0927] output

[0928] Improved algorithms and databases

[0929] Specific actions

[0930] The server analyzes the collected feedback and emotion data.

[0931] Based on the analysis results, the generative AI model is retrained and the proposed algorithm is optimized.

[0932] The improved algorithm will be reflected in the system and used to suggest future events.

[0933] (Application example 2)

[0934] 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."

[0935] Conventional event suggestion systems primarily suggest events based on the user's location information and personal data, but because they do not take into account the user's emotional state, they may not provide completely satisfying suggestions. Furthermore, because individual suggestions are not integrated into a continuous action plan, users must independently secure transportation and routes, which is inconvenient. Furthermore, they lack convenience due to the lack of real-time optimization of event suggestions and efficient transportation management using autonomous vehicles.

[0936] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for acquiring user personal data, means for collecting event information from online platforms using information collection means, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for calculating travel time between events and generating a time schedule using linkage means with map data, means for collecting and analyzing user emotion data, means for presenting the generated time schedule to an autonomous vehicle and presenting it to the user, means for optimizing event suggestions in real time based on the user emotion data, and means for selecting an optimal travel route and automatically adjusting the means of transportation. This makes it possible to optimize event suggestions and means of transportation taking emotion data into consideration.

[0937] "Means for obtaining user location information" refers to a device or system that obtains the user's current location using location information technologies such as GPS, Wi-Fi, or Bluetooth.

[0938] "Means for obtaining user personal data" refers to a device or system that collects personal data about a user, such as the user's categories of interest and past behavioral history.

[0939] "Information collection means" refers to tools and APIs for obtaining data such as event information from online platforms such as social media, blogs, and news sites.

[0940] "Generative AI" is an artificial intelligence technology that analyzes collected information and appropriately summarizes and organizes it based on the user's personal data.

[0941] "Means of linking with map data" refers to the use of map APIs and geographic information systems (GIS) to calculate travel times and routes based on the user's current location and destination.

[0942] The "means for generating a time schedule" is a system for creating an efficient schedule by taking into account the user's travel time and the start time of events.

[0943] "Means for collecting and analyzing user emotional data" refers to a system that uses devices such as cameras and microphones to analyze the user's facial expressions and tone of voice, and grasps the user's current emotional state.

[0944] The "means for presenting to the user" refers to an interface or display that displays the generated time schedule and event proposals on the user's device so that the user can view them.

[0945] The "means for optimizing event suggestions in real time" is a system for adjusting event suggestions in real time according to the user's current emotional state based on collected emotional data.

[0946] "Means for selecting optimal travel routes and automatically adjusting means of transportation" refers to a system that uses autonomous vehicles to optimize travel between events in which a user participates, and automatically selects and adjusts routes and means of transportation.

[0947] overview

[0948] This invention is a system that uses a user's location information, personal data, and emotion data to suggest optimal events and transportation methods. This system is particularly intended for efficient management of travel between events in autonomous vehicles and for providing optimal events to users in real time.

[0949] Required Hardware and Software

[0950] In order to implement this invention, the following hardware and software are required.

[0951] 1. Hardware

[0952] GPS module: To obtain the user's location information

[0953] Camera: To collect user facial expression data

[0954] Microphone: To collect user voice data

[0955] Smartphone or tablet: as the user interface

[0956] Autonomous vehicles: transportation

[0957] 2. Software

[0958] GPS tracking software: To obtain location information

[0959] Facial expression recognition software: To analyze the user's facial expressions and obtain emotional data

[0960] Voice analysis software: To analyze the user's voice and obtain emotional data

[0961] Social media scraping tools: To collect event information from online platforms

[0962] Generative AI model: To summarize the collected event information and extract the most suitable events for the user

[0963] Map APIs (e.g., Google Maps API): for travel time calculations and route optimization

[0964] Autonomous driving systems: as a means of transportation

[0965] Specific example of system operation

[0966] 1. Entering your location and personal data

[0967] Users log in to the system using a smartphone or tablet and enter their location information and personal data (such as categories of interest). This location information is acquired by a GPS module, and the personal data is stored in the system.

[0968] 2. Collecting event information

[0969] The server uses scraping tools to collect event information from social media and online platforms, retrieves event information based on specific keywords, and stores it on the server.

[0970] 3. Summarizing and organizing event information using generative AI

[0971] The server inputs the collected event information into a generative AI model, which then summarizes and organizes appropriate event information based on the user's personal data. As a concrete example, we use the following prompt sentence:

[0972] Summarize the following events and extract those that match the user's interest in music events or museums:

[0973] [Event information collected from social media]

[0974] 4. Generate travel routes and time schedules

[0975] The server uses a map API (such as Google Maps API) to calculate the travel time from the user's current location to each event venue, generates the optimal route, and creates an efficient time schedule taking into account the time slots of the proposed events.

[0976] 5. Emotional Data Collection and Analysis

[0977] Cameras and microphones inside the autonomous vehicle collect user emotional data, which is then analyzed using facial recognition and voice analysis software to understand the user's current emotional state.

[0978] 6. Real-time recommendation optimization

[0979] The server uses a generative AI model based on emotion data to optimize event suggestions in real time: for example, if a user has a positive reaction to a suggested event, the next event will be tailored to elicit a similarly positive reaction.

[0980] 7. Present the final schedule and execute the transfer

[0981] The optimized time schedule and travel route will be displayed on the autonomous vehicle's system and on the user's device, and the autonomous vehicle will then take the user to the next event venue according to the optimal route.

[0982] Through these processes, the present invention can provide users with optimal event information and efficient means of transportation, and improve the accuracy of suggestions in real time by taking into account the user's emotional state.

[0983] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0984] Step 1:

[0985] Users log in to the app using their smartphone or tablet and enter their location and personal data, including their current location (e.g., Shibuya-ku, Tokyo) obtained via a GPS module and categories of interest (e.g., music events, museums). The server receives this information, stores it in a database, and creates an individual profile for the user.

[0986] Step 2:

[0987] The server collects event information from social media and online platforms. It uses information collection tools (scraping tools and APIs) to obtain event information based on specific keywords (e.g., music events, art museums). The collected event information includes the event title, location, date and time, and user reviews. It performs a search based on the entered keyword information and stores the obtained event data in a database.

[0988] Step 3:

[0989] The server uses a generative AI model to summarize and organize the collected event information. A prompt is input to the generative AI model, which then summarizes the event based on specific keywords. For example, the following prompt is given to the generative AI model:

[0990] Summarize the following events and extract those that match the user's interest in music events or museums:

[0991] [Event information collected from social media]

[0992] The generative AI model extracts relevant events based on the prompt and outputs summarized information, which the server stores in a database.

[0993] Step 4:

[0994] The server uses a map API (e.g., Google Maps API) to calculate travel times and generate a time schedule. The user's current location information obtained from the database and summarized event information are input into the map API to calculate travel times and routes. The obtained travel time data is used to optimize the daily schedule. For example, a time schedule is generated that includes a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m. The generated schedule is saved on the server.

[0995] Step 5:

[0996] Cameras and microphones installed inside the autonomous vehicle are used to collect user emotional data. Facial expression recognition software and voice analysis software are used to analyze the user's facial and voice data to determine their current emotional state (e.g., positive, negative). The obtained emotional data is sent to a server and added to the user's profile.

[0997] Step 6:

[0998] The server optimizes event suggestions in real time based on the collected emotional data. It then uses the generative AI model again to suggest the next event, taking into account the emotional data. This process re-extracts the events that are best suited to the user's emotional state (e.g., events that can be expected to provide a similarly positive experience if the user is in a positive state). The optimized event suggestions are then displayed on the user's device.

[0999] Step 7:

[1000] The final timetable and route are presented to the user's device and the autonomous vehicle's system. The autonomous vehicle then selects the optimal route based on this schedule and drives the user to their destination. Emotional data is continuously monitored during the journey, and suggestions are adjusted in real time as needed.

[1001] Through these processes, the system can provide users with the most appropriate event information and efficient transportation methods, and improve the accuracy of suggestions in real time by taking into account the user's emotional state.

[1002] 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.

[1003] 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.

[1004] 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.

[1005] [Third embodiment]

[1006] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1007] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1008] 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).

[1009] 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.

[1010] 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.

[1011] 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).

[1012] 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.

[1013] 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.

[1014] 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.

[1015] 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.

[1016] 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.

[1017] 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."

[1018] This invention is a system that uses a user's location information and personal data to suggest events and schedules. This system collects information from social media and uses generative AI to summarize and organize it, providing users with the most suitable event information. Below, we will explain the program processing and specific examples of this system in natural language.

[1019] Overall system flow

[1020] 1. User registration and data entry

[1021] Users register using a device and enter their location information and personal data. Location information includes the user's current location (e.g., Shibuya-ku, Tokyo), and personal data includes the user's interests and preferences (e.g., music events, museums, dining, etc.).

[1022] 2. Data storage and initial settings

[1023] The server stores the location and personal data sent by the user in a database, which creates an individual profile for each user.

[1024] 3. Collecting event information from social media

[1025] The server periodically collects event information from online platforms such as social media platforms, using scraping tools and APIs to gather information related to users' interests, such as music events and museum special exhibitions. The collected information includes the event title, location, date and time, and user reviews.

[1026] 4. Summarizing and organizing information using generative AI

[1027] Next, the server uses a generation AI to summarize and organize the collected event information. The generation AI uses natural language processing technology to extract event information that matches the user's interests. This process creates an optimal event list for the user.

[1028] 5. Calculating travel time and generating time schedules

[1029] The server calculates travel time using map data based on the user's current location and selected event information. It uses Google Maps and other map APIs to calculate the optimal travel route between events and create a time schedule. The created schedule includes the start time and travel time for each event.

[1030] 6. Event information and timetable

[1031] The server sends the generated time schedule to the user's device, which then displays detailed information about the event, including transportation options, travel time, and user reviews, making it easy for users to select events that interest them.

[1032] 7. Collecting User Feedback

[1033] Users provide feedback on the proposed events and actions, including ratings, comments, and usage history, which is then sent to the server.

[1034] 8. System Improvements

[1035] The server improves its data and algorithms based on feedback collected from users, and uses this feedback to continue training the generative AI model to improve the accuracy of future suggestions.

[1036] Specific examples

[1037] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[1038] 1. Registration and Data Entry

[1039] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[1040] 2. Data Collection

[1041] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[1042] 3. Generative AI Processing

[1043] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[1044] 4. Generate a time schedule

[1045] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[1046] 5. Presentation of Information

[1047] The server sends this schedule to the user's terminal, where detailed information is displayed.

[1048] In this way, users can quickly obtain the most suitable event information for them and spend their time in a fulfilling manner.

[1049] The processing flow will be explained below.

[1050] Step 1:

[1051] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, art museums) along with their account information. This information is sent to the server.

[1052] Step 2:

[1053] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1054] Step 3:

[1055] The server periodically collects event information from social media sites. It uses scraping tools and APIs to collect data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[1056] Step 4:

[1057] The server stores the collected event information in a database and categorizes and organizes the information as needed.

[1058] Step 5:

[1059] The server uses a generation AI to summarize and organize the collected event information based on the user's personal data. The generation AI automatically uses text summarization technology to extract event information of high interest and create a list containing only the important information.

[1060] Step 6:

[1061] The server creates an optimal event list for the user based on the event information summarized by the generative AI, including rankings and importance.

[1062] Step 7:

[1063] The server uses map data to calculate travel time between events based on the user's current location and the event list, and uses Google Maps and map APIs to determine the optimal route and mode of transportation (walking, cycling, driving, public transportation, etc.).

[1064] Step 8:

[1065] The server generates a detailed time schedule by taking into account the calculated travel time and the event start time. For example, it might be in the format of "14:00 - Live Concert (Shibuya Ward)" -> "15:30 - Travel (15 minutes on foot)" -> "17:00 - Art Exhibition (Shibuya Ward)".

[1066] Step 9:

[1067] The server sends the generated time schedule to the user's device, which displays detailed event information, transportation options, travel times, and user reviews, allowing the user to easily select events that interest them.

[1068] Step 10:

[1069] Users can review the suggested events and provide feedback on their actual events and activities, including ratings, comments, and usage history.

[1070] Step 11:

[1071] The server improves the data and algorithms based on the feedback collected from users, analyzing the feedback information and retraining the generative AI model to improve the accuracy of future suggestions.

[1072] By following the above steps, users can easily obtain the event information and time schedule that best suits them, allowing them to spend their time to the fullest.

[1073] Example 1

[1074] 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."

[1075] Conventional event suggestion systems have difficulty providing optimal event information based on a user's location information and personal data, and the collected information may not perfectly match the user's interests. Furthermore, there is a lack of effective means for quickly organizing the collected information, which results in low accuracy and efficiency of event suggestions to users.

[1076] 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.

[1077] In this invention, the server

[1078] The system includes a means for acquiring user location information, a means for acquiring user personal data, a means for collecting event information from online platforms, a means for summarizing and organizing the collected event information based on the user's personal data using generation AI, a means for calculating travel time between events using linkage with map data to generate a time schedule, a means for presenting the generated time schedule to users, a means for users to register and input their name, email address, and password, and a means for users to input and send feedback, thereby making it possible to efficiently provide optimal event information to each user.

[1079] "User" refers to an individual who uses the System to obtain Event Information.

[1080] "Location information" is data that indicates a user's current location or a specific geographic location.

[1081] "Personal Data" refers to personal information entered by users, such as interests and preferences, name, email address, and password.

[1082] "Information collection means" refers to the technologies and methods used to collect event information from online platforms and social media.

[1083] "Generative AI" refers to a model that uses artificial intelligence technology to summarize and organize collected information and make suggestions to users.

[1084] "Map data" refers to a data set containing information indicating geographic locations and used to calculate travel distances and travel times.

[1085] A "time schedule" is a schedule that includes suggested event start times and travel times for a user.

[1086] "New registration" refers to the act of creating an account by entering a name, email address, password, etc. when a user uses the system for the first time.

[1087] "Feedback" refers to opinions and impressions such as ratings and comments provided by users to the system.

[1088] An "online platform" refers to a service that provides information via the Internet, such as social media, websites, and applications.

[1089] "Integration means" refers to methods and technologies for combining and using different data and services.

[1090] MODE FOR CARRYING OUT THE INVENTION

[1091] This invention is a system that utilizes a user's location information and personal data to optimally suggest events and schedules. This system collects a large amount of information from social media and online platforms, summarizes and organizes it using a generative AI model, and provides event information that is appropriate for the user. Below, we will explain in detail how this system is implemented.

[1092] 1. Hardware and Software

[1093] server

[1094] The server can be a cloud server or an on-premise server (e.g. Amazon Web Services, Google Cloud Platform).A database (e.g. MySQL, PostgreSQL) is installed on the server and stores user location information, personal data, and collected event information.

[1095] Terminal

[1096] The user terminal can be a smartphone, tablet, personal computer (PC), or other device. The terminal is provided with an interface for accessing the system through a dedicated application or a web browser.

[1097] Generative AI Models

[1098] The generative AI model uses advanced AI models (e.g., GPT-3, BERT) that include natural language processing technology, which makes it possible to summarize and organize collected event information based on the user's personal data.

[1099] 2. Program Processing

[1100] The server receives data sent from the user's device and stores it in a database. The server periodically uses scraping tools and APIs to collect event information from social media and other online platforms. The server also uses a generative AI model to summarize and organize the collected event information. The generative AI model extracts the most relevant events based on the user's personal data and incorporates them into a time schedule.

[1101] 3. Specific Examples

[1102] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[1103] 1. User registration and data entry

[1104] The user registers by entering their name, email address, and password. They also enter their address in Shibuya Ward, Tokyo, and their interests as "music events" and "museums."

[1105] 2. Data Collection

[1106] The server collects information from SNS such as "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo." For example, suppose there is a live concert at a live music venue in Shibuya Ward from 2 PM, and a special exhibition at an art museum in Shibuya Ward from 4 PM.

[1107] 3. Generative AI Processing

[1108] The server uses a generative AI model to extract events that match the user's interests from the collected event information, selecting live concerts and art exhibitions.

[1109] 4. Generate a time schedule

[1110] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2 p.m. and an art exhibition at 3:30 p.m.

[1111] 5. Presentation of Information

[1112] The server sends this schedule to the user's terminal, where detailed information is displayed.

[1113] 4. Examples of prompts

[1114] Please enter the user's location and hobby data. If the current location is "Shibuya-ku, Tokyo" and the interests are "music events" and "museums," what kind of event information can you provide?

[1115] In this way, users can quickly obtain the most suitable event information for them and spend their time in a fulfilling manner.

[1116] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1117] Step 1: User registration and data entry

[1118] The user launches the application on their device and proceeds to the new registration screen. They enter their name, email address, password, current location (e.g., Shibuya-ku, Tokyo), and interests and preferences (e.g., music events, art museums). When the user presses the "Register" button, the entered information is sent to the server via the API. The server receives this data and stores it in the appropriate table in the database based on the user index.

[1119] Input: Name, email address, password, location information, interests and preferences

[1120] Output: User profile stored in the database

[1121] Step 2: Save data and set up

[1122] The server stores the location and personal data received from the users in a database and creates an individual profile for each user, which involves inserting the newly received data into the appropriate tables in the database, for example adding new records to the user profile table and the location information table.

[1123] Input: Location and personal data received from the user

[1124] Output: User profile created in the database

[1125] Step 3: Collect event information from social media

[1126] The server periodically collects event information from social media and other online platforms. Specifically, it uses scraping tools and APIs to search for information related to users' interests and obtain the necessary data. The collected information includes the event title, location, date and time, and user reviews. The collected data is temporarily stored.

[1127] Input: Event information from social media and online platforms

[1128] Output: Temporarily saved event information data

[1129] Step 4: Summarizing and organizing information using generative AI

[1130] The server inputs the collected event information into a generative AI model. The generative AI model (e.g., GPT-3) summarizes and organizes the collected information and extracts the event information that best suits the user's interests. This summarized and organized data is extracted and organized based on each user's profile.

[1131] Input: Collected event information

[1132] Output: Summarized and organized event information data

[1133] Step 5: Calculate travel times and generate time schedules

[1134] The server calculates the travel time from the user's current location to the selected event. It uses a map service such as Google Maps API to calculate the appropriate route and travel time. An optimal time schedule is generated along with the calculated travel time. The time schedule includes the start time and travel time of each event.

[1135] Input: User's current location, summary and organized event information

[1136] Output: Generated time schedule

[1137] Step 6: Present the event information and timetable

[1138] The server sends the generated time schedule and event information to the user's device. The device displays the received information on a GUI so that the user can easily check it. The user can view the proposed event information and detailed time schedule.

[1139] Input: Generated time schedule and event information

[1140] Output: Detailed information displayed on the terminal

[1141] Step 7: Gather user feedback

[1142] The user provides feedback on the proposed events and actions from the device. The user inputs feedback such as ratings, comments, and usage history, and presses the send button. The device then sends this feedback information to the server.

[1143] Input: User feedback (ratings, comments, usage history)

[1144] Output: Feedback data sent to the server

[1145] Step 8: Improve your system

[1146] The server stores the received feedback data in a database and uses it to train the existing generative AI model, improving the algorithm and increasing the accuracy of future suggestions.

[1147] Input: Feedback data

[1148] Output: Improved generative AI models and algorithms

[1149] The above is a specific explanation of each processing step of the system, including how the input and output are processed and calculated at each step.

[1150] (Application example 1)

[1151] 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."

[1152] In today's world, there is a growing need for efficient and convenient shopping at brick-and-mortar stores. However, it is difficult for users to plan optimal shopping routes by collecting information on numerous stores, sales, new product arrivals, and other information all at once. Furthermore, finding stores that match one's interests and preferences from the collected information takes time and effort, and users are also required to calculate travel times and select the optimal means of transportation. Conventional systems have had difficulty consistently resolving these issues.

[1153] 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.

[1154] In this invention, the server includes means for acquiring user location information, means for acquiring user personal data, means for collecting physical store information from various online platforms using information collection means, means for summarizing and organizing the collected physical store information based on the user's personal data using a generative AI model, means for calculating optimal travel routes and travel times between physical stores using linkage means with map data to generate a shopping route, and means for presenting the generated shopping route to the user, thereby enabling the user to shop efficiently and have a pleasant shopping experience.

[1155] "User location information" is information that indicates the user's current geographic location.

[1156] "Personal data" is data that includes personal information such as a user's interests and preferences.

[1157] "Information collection means" refers to the means used to collect necessary information from various online platforms.

[1158] "Physical store information" refers to sales information, new product information, business information, etc. related to physical stores.

[1159] A "generative AI model" is a model that uses artificial intelligence to summarize and organize collected information.

[1160] "Map data" refers to data containing geographical information and is used for route calculation and navigation.

[1161] "Travel route" refers to the route a user takes from one point to another.

[1162] "Travel time" refers to the time required to travel from one point to another.

[1163] A "shopping route" refers to a route planned to efficiently visit multiple destinations.

[1164] "Feedback" refers to information such as opinions and ratings provided by users.

[1165] An "algorithm" refers to a procedure or computational method for solving a specific problem.

[1166] "Means for linking with map data" refers to means for calculating travel routes and travel times using geographical information.

[1167] An "online platform" refers to a service that provides information on the Internet, such as a website or social networking site.

[1168] The present invention is a system that uses a user's location information and personal data to provide optimal store information and generate an efficient shopping route. The system includes a means for collecting information from multiple online platforms, summarizing and organizing the information using a generative AI model, and providing the user with the optimal route.

[1169] In one embodiment of the present invention, the process starts when a user uses a smartphone to input their current location and product categories they are interested in. Based on this, the server performs the following process.

[1170] 1. User registration and data entry

[1171] Users access the application from their own devices and register. When registering, they enter their location information (e.g., "Shibuya-ku, Tokyo") and personal data (e.g., "fashion," "electronic devices").

[1172] 2. Data storage and initial settings

[1173] The server stores the location and personal data sent by the user in a database, which creates an individual profile for each user.

[1174] 3. Collection by information gathering means

[1175] The server periodically collects store information from various online platforms, such as social media and store websites. This information includes sales information, new product information, and customer reviews. This information is collected using scraping tools and APIs.

[1176] 4. Summarizing and Organizing Information Using Generative AI Models

[1177] The server uses a generative AI model to summarize and organize the collected store information. The generative AI model uses natural language processing technology to extract the most appropriate information based on the user's personal data and provide useful information to the user.

[1178] 5. Creating shopping routes in conjunction with map data

[1179] Next, the server uses a method to link with map data to calculate the travel time from the user's current location to each store, thereby generating the optimal shopping route. Map services such as Google Maps API can be used.

[1180] 6. Shopping route suggestions

[1181] The generated shopping route and store information is sent to the user's smartphone, where the user can check detailed store information and travel routes through the application and shop efficiently.

[1182] 7. Collecting user feedback and improving the system

[1183] Users can provide feedback about the stores they visit and the products they buy, which is sent to a server to help improve the system's data and algorithms.

[1184] As a concrete example, if a user is located in Shibuya Ward, Tokyo, and is interested in fashion and electronics, the server collects relevant sales and new product information and provides the following prompt sentence as input to the generative AI model: "Based on my current location in Shibuya Ward, Tokyo, please tell me nearby stores where I can purchase the fashion and electronics products I'm interested in. I'd especially like to know about sales and new product information."

[1185] In this way, users can efficiently find stores that suit their interests and plan the optimal shopping route in a short amount of time.

[1186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1187] Step 1:

[1188] A user registers for the application using a device (e.g., a smartphone). Input includes location information (e.g., "Shibuya-ku, Tokyo") and personal data (e.g., "fashion" and "electronic devices"). The registration data is sent to a server and stored in a database. This creates an individual profile for the user.

[1189] Step 2:

[1190] The server periodically collects information about the physical store from social media and various online platforms (e.g., the store's website) using scraping tools and APIs. The collected information includes sales information, new product information, and reviews. The collected information is stored in the server's database.

[1191] Step 3:

[1192] The server provides the collected store information to a generative AI model, which summarizes and organizes it. The generative AI model uses natural language processing technology to extract the most appropriate information based on the user's personal data. For example, it prioritizes summarizing store information related to specific interests and preferences. The input is the collected store information, and the output is summarized and organized store information. This output is stored in the server's database.

[1193] Step 4:

[1194] The server uses a means of linking with map data to calculate the travel time from the current location to the store. It calculates the travel time and optimal travel route using the Google Maps API, etc. For example, it can give results such as a 10-minute walk to store A and a 15-minute walk to store B. The input is the user's current location and the store's location information, and the output is the travel time and travel route.

[1195] Step 5:

[1196] The server generates a shopping route based on travel time and the optimal travel route, and sends the generated shopping route to the user's terminal. The terminal application receives it and displays detailed store information and the travel route on the user's screen. The user can proceed with shopping along the recommended route. The input is the travel route and summarized store information, and the output is the optimal shopping route.

[1197] Step 6:

[1198] After the user has finished shopping, they provide feedback about the stores they visited and the products they purchased through their device, which is then sent to the server and stored in a database.

[1199] Step 7:

[1200] The server continues to train the generative AI model based on the collected feedback, improving the data and algorithms, which in turn improves the accuracy of future suggestions. The input is the feedback data, and the output is the improved data and algorithms.

[1201] 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.

[1202] This invention is a system that uses a user's location information, personal data, and emotional data to suggest events and schedules, and provides users with the most suitable event information by collecting information from social media, summarizing the data using generative AI, linking it with map data, and using an emotional engine. Below, we will explain the program processing and specific examples of this system in natural language.

[1203] Overall system flow

[1204] 1. User registration and data entry

[1205] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums) along with their account information. This information is sent to the server.

[1206] 2. Data storage and initial settings

[1207] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1208] 3. Collecting event information from social media

[1209] The server periodically collects event information from online platforms such as social media platforms. It uses scraping tools and APIs to collect data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[1210] 4. Summarizing and organizing information using generative AI

[1211] Next, the server uses a generation AI to summarize and organize the collected event information. The generation AI uses natural language processing technology to extract event information that matches the user's interests. This process creates an optimal event list for the user.

[1212] 5. Calculating travel time and generating time schedules

[1213] The server calculates travel time using map data based on the user's current location and selected event information. It uses Google Maps and other map APIs to calculate the optimal travel route between events and create a time schedule. The created schedule includes the start time and travel time for each event.

[1214] 6. Collecting Emotional Data

[1215] The user's device is equipped with an emotion engine to collect emotional data about the proposed event, and understands the user's current emotional state through facial expression recognition and voice analysis.

[1216] 7. Leveraging Emotional Engines

[1217] The server obtains a real-time evaluation of the proposed event based on the collected emotional data. For example, it analyzes whether the user is interested or indifferent to the proposed event information and uses this information to improve the accuracy of future event suggestions.

[1218] 8. Event information and timetable

[1219] The server sends the generated time schedule to the user's device, which displays detailed event information, transportation options, travel time, user reviews, and even feedback on the user's emotional state, allowing the user to easily select events that interest them.

[1220] 9. Collecting User Feedback

[1221] Users provide feedback on proposed events and actions, including ratings, comments, usage history, and even emotional data from the emotion engine. This information is sent to the server.

[1222] 10. System Improvements

[1223] The server improves its data and algorithms based on the feedback and sentiment data collected from users, which is then used to retrain the generative AI model to improve the accuracy of future suggestions.

[1224] Specific examples

[1225] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[1226] 1. Registration and Data Entry

[1227] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[1228] 2. Data Collection

[1229] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[1230] 3. Generative AI Processing

[1231] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[1232] 4. Generate a time schedule

[1233] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[1234] 5. Presentation of Information

[1235] The server sends this schedule to the user's device, where detailed information is displayed. At this time, the emotion engine analyzes the user's emotions in real time and uses them to provide feedback on events.

[1236] 6. User Feedback

[1237] Users participate in the proposed events and provide feedback about their experiences, and emotional data collected by the emotion engine is also sent to the server.

[1238] In this way, the system takes the user's emotional state into consideration and suggests optimal event information and time schedules, allowing users to easily obtain the event information that is best suited to them and spend their time in a fulfilling manner.

[1239] The processing flow will be explained below.

[1240] Step 1:

[1241] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums) along with their account information. This information is sent to the server.

[1242] Step 2:

[1243] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1244] Step 3:

[1245] The server periodically collects event information from social media sites. Using scraping tools and APIs, it collects data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[1246] Step 4:

[1247] The server stores the collected event information in a database and categorizes and organizes the information as needed.

[1248] Step 5:

[1249] The server uses a generation AI to summarize and organize the collected event information based on the user's personal data. The generation AI uses natural language processing technology to extract interesting event information and create a list containing only the important information.

[1250] Step 6:

[1251] The server creates an optimal event list for the user based on the event information summarized by the generative AI, including rankings and importance.

[1252] Step 7:

[1253] The server uses map data to calculate travel time between events based on the user's current location and the event list, and uses Google Maps and map APIs to determine the optimal route and mode of transportation (walking, cycling, driving, public transportation, etc.).

[1254] Step 8:

[1255] The server generates a detailed time schedule by taking into account the calculated travel time and the event start time, for example, "14:00 - Live Concert (Shibuya Ward)" → "15:30 - Travel (15 minutes on foot)" → "17:00 - Art Exhibition (Shibuya Ward)".

[1256] Step 9:

[1257] The user's device uses an emotion engine to analyze the user's emotions in real time. It uses facial expression recognition and voice analysis to understand how the user feels about the proposed event information. This emotion data is then sent to the server.

[1258] Step 10:

[1259] The server receives the emotion data and obtains real-time evaluations of the proposed events. The server classifies the events that the user is interested in and those that the user is not interested in, and reflects this in future event suggestions.

[1260] Step 11:

[1261] The server then sends the generated time schedule and event information based on the results of the emotion analysis to the user's device, which then displays detailed information about the event, transportation methods, travel time, user reviews, and the results of the emotion analysis on the device's display.

[1262] Step 12:

[1263] Users provide additional emotional feedback for the proposed events, including ratings and comments on the events they have actually attended, as well as real-time emotional data from the emotion engine, which is then sent to the server.

[1264] Step 13:

[1265] The server improves its data and algorithms based on the feedback and sentiment data collected from users, analyzing the feedback information and retraining the generative AI model to improve the accuracy of future suggestions.

[1266] Through these steps, the system takes the user's emotional state into consideration and suggests optimal event information and time schedules, allowing users to easily obtain the event information that best suits them and spend their time in a fulfilling manner.

[1267] Example 2

[1268] 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."

[1269] Conventional event suggestion systems have limited means of providing event information based on users' personal data, and it is difficult to make suggestions that take into account travel time and emotional state. Furthermore, there is a lack of mechanisms for improving the system using user feedback and emotional data, making it difficult to improve the accuracy of suggestions.

[1270] 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 acquiring user location information, means for acquiring user personal data, means for collecting event information from online platforms using information collection means, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for calculating travel time between events using map data and generating a time schedule, means for collecting emotion data, means for improving event suggestions based on the collected emotion data, means for presenting the generated time schedule to the user, means for collecting user feedback, and means for improving data and algorithms based on the collected feedback. This makes it possible to generate optimal event suggestions and time schedules taking into account the user's location information and emotion data, and to improve the system based on user feedback.

[1271] "Means for obtaining user location information" refers to a device or software that has the function of determining the user's location and transmitting that location data to the system.

[1272] "Means for obtaining user personal data" refers to devices or software that have the function of collecting specific information such as the user's interests, hobbies, and personal information, and providing it to the system.

[1273] "Means for collecting event information from online platforms using information collection means" refers to tools and technologies for obtaining data about events from social media and other online platforms via the Internet.

[1274] "Means for summarizing and organizing event information collected using generative AI based on user personal data" refers to a technology that uses a generative AI model to summarize and organize large amounts of event information based on user interests and specific information.

[1275] "Means of calculating travel times between events using map data and generating a time schedule" refers to a technology that uses a map service API to calculate travel times from the user's current location to each event location and creates an optimal time schedule based on that.

[1276] "Means for collecting emotional data" refers to a device or software that analyzes the user's emotional state from facial expressions, voice, etc., and collects that data.

[1277] "Means for improving event suggestions based on collected emotional data" refers to technology that analyzes collected emotional data and makes more attractive event suggestions to users.

[1278] "Means for presenting the generated time schedule to the user" refers to a technology for visually displaying the generated time schedule and related information and providing it to the user.

[1279] "Means for collecting user feedback" means any device or software that allows users to input and submit ratings and comments about proposed events.

[1280] "Means for improving data and algorithms based on collected feedback" refers to technology that analyzes feedback collected from users and optimizes and improves the system's database and algorithms based on that feedback.

[1281] The present invention is a system for suggesting events and schedules by utilizing a user's location information, personal data, and emotional data. The system mainly includes the following elements: a means for acquiring a user's location information, a means for acquiring a user's personal data, a means for collecting event information from online platforms using an information collection means, a means for summarizing and organizing the collected event information using a generative AI, a means for calculating travel times between events using map data and generating a time schedule, a means for collecting emotional data, a means for improving event suggestions based on the collected emotional data, a means for presenting the generated time schedule to the user, and a means for collecting user feedback to improve the data and algorithms.

[1282] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, art museums) along with their account information. This information is sent to the server. The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1283] The server periodically collects event information from social media and other online platforms. It uses scraping tools and APIs (e.g., Twitter API, Instagram Graph API) to extract data based on specific keywords (e.g., music events, museums). The collected information includes event titles, locations, dates, and reviews.

[1284] The server then uses a generative AI (e.g., OpenAI's GPT model) to summarize and organize the collected event information. The generative AI uses natural language processing technology to extract event information that matches the user's interests, and this process creates an optimal event list for the user.

[1285] The server then calculates travel time using a map API such as Google Maps based on the user's current location and the selected event information. This process generates the optimal travel route and time schedule between events. Detailed event information, transportation methods, travel time, and customer reviews are then displayed on the user's device.

[1286] The user's device is equipped with an emotion engine (e.g., Face API, voice analysis engine) that grasps the user's current emotional state through facial expression recognition and voice analysis. The server analyzes the user's emotional state based on the collected emotion data and obtains a real-time evaluation of the proposed event. This data is used to improve the accuracy of future event suggestions.

[1287] Users participate in the suggested events and provide ratings and comments about their experiences. Emotional data collected by the emotion engine is also sent to the server. The server uses this collected feedback and emotion data to improve the system's data and algorithms, thereby improving the accuracy of future suggestions.

[1288] Specific examples

[1289] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system works as follows:

[1290] 1. Registration and Data Entry

[1291] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[1292] 2. Data Collection

[1293] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[1294] 3. Generative AI Processing

[1295] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[1296] 4. Generate a time schedule

[1297] The server calculates the travel time from the user's current location to each event and creates a time schedule for live music venues and art museums that are within a 10-minute walk, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[1298] 5. Presentation of Information

[1299] The server sends this schedule to the user's device, where detailed event information is displayed. At this time, the emotion engine analyzes the user's emotions in real time and obtains their feedback.

[1300] 6. User Feedback

[1301] Users participate in the proposed events and provide feedback about their experiences, and emotional data collected by the emotion engine is also sent to the server.

[1302] Prompt Sentence Examples

[1303] The prompt text to explain the system's behavior is:

[1304] "The user lives in Shibuya Ward and is interested in music events and art museums. Please generate the optimal time schedule for the user based on event information collected from social media. Please also provide detailed information about each event and travel times."

[1305] In this way, the present invention provides optimal event information and time schedules while taking into consideration the emotional state of the user, allowing the user to easily obtain event information that is optimal for them and spend a fulfilling time.

[1306] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1307] Step 1: User registration and data entry

[1308] Specific explanation

[1309] The user accesses the new registration screen using their device and enters their account information (such as name, email address, and password) along with their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums). This information is sent to the server.

[1310] input

[1311] User account information, location information, and personal data

[1312] output

[1313] User data sent to the server

[1314] Specific actions

[1315] A user opens a web browser or mobile app and accesses the new registration screen.

[1316] Enter your name, email address, password, location, and interests.

[1317] Press the "Register" button and the device will send the input data to the server.

[1318] ---

[1319] Step 2: Save data and set up

[1320] Specific explanation

[1321] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1322] input

[1323] User location information, personal data

[1324] output

[1325] User profiles stored in a database

[1326] Specific actions

[1327] The server processes the data received from the terminal and stores it in a database.

[1328] A unique user ID is assigned to each user and initial settings are performed.

[1329] Generate a keyword list based on personal data.

[1330] ---

[1331] Step 3: Collect event information from social media

[1332] Specific explanation

[1333] The server periodically collects event information from social media and other online platforms, and uses scraping tools and APIs to extract data based on specific keywords.

[1334] input

[1335] Keyword List

[1336] output

[1337] Event information stored in the database

[1338] Specific actions

[1339] The server calls the SNS API based on the keyword list.

[1340] Get information about the event (title, location, date, time, reviews, etc.).

[1341] The acquired data is saved in the "Event Information" table of the database.

[1342] ---

[1343] Step 4: Summarizing and organizing information using generative AI

[1344] Specific explanation

[1345] The server summarizes and organizes the collected event information using a generation AI, which uses natural language processing technology to extract event information that matches the user's interests.

[1346] input

[1347] Event information collected from SNS

[1348] output

[1349] Abridged Event Listing

[1350] Specific actions

[1351] The server inputs the collected event data into a generative AI model.

[1352] A generative AI model extracts event information relevant to the user's interests.

[1353] The extracted information is organized to create an optimal event list for each user.

[1354] ---

[1355] Step 5: Calculate travel times and generate time schedules

[1356] Specific explanation

[1357] The server uses a map API to calculate travel time based on the user's current location and selected event information, generating the optimal travel route and time schedule between events.

[1358] input

[1359] User's current location, event information

[1360] output

[1361] Time Schedule

[1362] Specific actions

[1363] The server sends the user's current location and the event's location information to the map API.

[1364] Get travel route and travel time.

[1365] A time schedule is generated based on the start time and travel time of each event.

[1366] ---

[1367] Step 6: Collect emotion data

[1368] Specific explanation

[1369] The user's device is equipped with an emotion engine that grasps the user's emotional state through facial expression recognition and voice analysis.

[1370] input

[1371] User facial expression data, voice data

[1372] output

[1373] Emotional Data

[1374] Specific actions

[1375] The device uses the built-in camera and microphone to capture the user's facial expressions and voice.

[1376] The emotion engine analyzes the data and determines the emotional state.

[1377] The determined emotion data is transmitted to the server.

[1378] ---

[1379] Step 7: Leverage your emotional engine

[1380] Specific explanation

[1381] The server uses the collected emotional data to evaluate the user's level of interest in the proposed event and improves the accuracy of future suggestions.

[1382] input

[1383] Emotional Data

[1384] output

[1385] Proposed algorithm with improved accuracy

[1386] Specific actions

[1387] The server receives and analyzes the emotional data and evaluates the user's emotional state.

[1388] We will adjust the suggestion algorithm and reflect this in our next event suggestions.

[1389] ---

[1390] Step 8: Present the event information and timetable

[1391] Specific explanation

[1392] The server sends the generated time schedule and event information to the user's terminal.

[1393] input

[1394] Time schedule and event information

[1395] output

[1396] Event information and schedules displayed on your device

[1397] Specific actions

[1398] The server transmits the event list and time schedule generated for each user to the terminal.

[1399] The device organizes the received information and displays it on a user interface.

[1400] Information displayed includes event details, transportation options, and reviews.

[1401] ---

[1402] Step 9: Gather user feedback

[1403] Specific explanation

[1404] Users attend the suggested events and provide feedback about their experience, including emotional data collected by the emotion engine.

[1405] input

[1406] User feedback comments and sentiment data

[1407] output

[1408] Feedback data sent to the server

[1409] Specific actions

[1410] Users use their device to enter ratings and comments and press the send button.

[1411] The emotion data collected by the emotion engine is also sent to the server in parallel.

[1412] ---

[1413] Step 10: Improve your system

[1414] Specific explanation

[1415] The server uses feedback and sentiment data collected from users to improve the system's data and algorithms.

[1416] input

[1417] Feedback data, emotion data

[1418] output

[1419] Improved algorithms and databases

[1420] Specific actions

[1421] The server analyzes the collected feedback and emotion data.

[1422] Based on the analysis results, the generative AI model is retrained and the proposed algorithm is optimized.

[1423] The improved algorithm will be reflected in the system and used to suggest future events.

[1424] (Application example 2)

[1425] 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."

[1426] Conventional event suggestion systems primarily suggest events based on the user's location information and personal data, but because they do not take into account the user's emotional state, they may not provide completely satisfying suggestions. Furthermore, because individual suggestions are not integrated into a continuous action plan, users must independently secure transportation and routes, which is inconvenient. Furthermore, they lack convenience due to the lack of real-time optimization of event suggestions and efficient transportation management using autonomous vehicles.

[1427] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for acquiring user personal data, means for collecting event information from online platforms using information collection means, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for calculating travel time between events and generating a time schedule using linkage means with map data, means for collecting and analyzing user emotion data, means for presenting the generated time schedule to an autonomous vehicle and presenting it to the user, means for optimizing event suggestions in real time based on the user emotion data, and means for selecting an optimal travel route and automatically adjusting the means of transportation. This makes it possible to optimize event suggestions and means of transportation taking emotion data into consideration.

[1428] "Means for obtaining user location information" refers to a device or system that obtains the user's current location using location information technologies such as GPS, Wi-Fi, or Bluetooth.

[1429] "Means for obtaining user personal data" refers to a device or system that collects personal data about a user, such as the user's categories of interest and past behavioral history.

[1430] "Information collection means" refers to tools and APIs for obtaining data such as event information from online platforms such as social media, blogs, and news sites.

[1431] "Generative AI" is an artificial intelligence technology that analyzes collected information and appropriately summarizes and organizes it based on the user's personal data.

[1432] "Means of linking with map data" refers to the use of map APIs and geographic information systems (GIS) to calculate travel times and routes based on the user's current location and destination.

[1433] The "means for generating a time schedule" is a system for creating an efficient schedule by taking into account the user's travel time and the start time of events.

[1434] "Means for collecting and analyzing user emotional data" refers to a system that uses devices such as cameras and microphones to analyze the user's facial expressions and tone of voice, and grasps the user's current emotional state.

[1435] The "means for presenting to the user" refers to an interface or display that displays the generated time schedule and event proposals on the user's device so that the user can view them.

[1436] The "means for optimizing event suggestions in real time" is a system for adjusting event suggestions in real time according to the user's current emotional state based on collected emotional data.

[1437] "Means for selecting optimal travel routes and automatically adjusting means of transportation" refers to a system that uses autonomous vehicles to optimize travel between events in which a user participates, and automatically selects and adjusts routes and means of transportation.

[1438] overview

[1439] This invention is a system that uses a user's location information, personal data, and emotion data to suggest optimal events and transportation methods. This system is particularly intended for efficient management of travel between events in autonomous vehicles and for providing optimal events to users in real time.

[1440] Required Hardware and Software

[1441] In order to implement this invention, the following hardware and software are required.

[1442] 1. Hardware

[1443] GPS module: To obtain the user's location information

[1444] Camera: To collect user facial expression data

[1445] Microphone: To collect user voice data

[1446] Smartphone or tablet: as the user interface

[1447] Autonomous vehicles: transportation

[1448] 2. Software

[1449] GPS tracking software: To obtain location information

[1450] Facial expression recognition software: To analyze the user's facial expressions and obtain emotional data

[1451] Voice analysis software: To analyze the user's voice and obtain emotional data

[1452] Social media scraping tools: To collect event information from online platforms

[1453] Generative AI model: To summarize the collected event information and extract the most suitable events for the user

[1454] Map APIs (e.g., Google Maps API): for travel time calculations and route optimization

[1455] Autonomous driving systems: as a means of transportation

[1456] Specific example of system operation

[1457] 1. Entering your location and personal data

[1458] Users log in to the system using a smartphone or tablet and enter their location information and personal data (such as categories of interest). This location information is acquired by a GPS module, and the personal data is stored in the system.

[1459] 2. Collecting event information

[1460] The server uses scraping tools to collect event information from social media and online platforms, retrieves event information based on specific keywords, and stores it on the server.

[1461] 3. Summarizing and organizing event information using generative AI

[1462] The server inputs the collected event information into a generative AI model, which then summarizes and organizes appropriate event information based on the user's personal data. As a concrete example, we use the following prompt sentence:

[1463] Summarize the following events and extract those that match the user's interest in music events or museums:

[1464] [Event information collected from social media]

[1465] 4. Generate travel routes and time schedules

[1466] The server uses a map API (such as Google Maps API) to calculate the travel time from the user's current location to each event venue, generates the optimal route, and creates an efficient time schedule taking into account the time slots of the proposed events.

[1467] 5. Emotional Data Collection and Analysis

[1468] Cameras and microphones inside the autonomous vehicle collect user emotional data, which is then analyzed using facial recognition and voice analysis software to understand the user's current emotional state.

[1469] 6. Real-time recommendation optimization

[1470] The server uses a generative AI model based on emotion data to optimize event suggestions in real time: for example, if a user has a positive reaction to a suggested event, the next event will be tailored to elicit a similarly positive reaction.

[1471] 7. Present the final schedule and execute the transfer

[1472] The optimized time schedule and travel route will be displayed on the autonomous vehicle's system and on the user's device, and the autonomous vehicle will then take the user to the next event venue according to the optimal route.

[1473] Through these processes, the present invention can provide users with optimal event information and efficient means of transportation, and improve the accuracy of suggestions in real time by taking into account the user's emotional state.

[1474] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1475] Step 1:

[1476] Users log in to the app using their smartphone or tablet and enter their location and personal data, including their current location (e.g., Shibuya-ku, Tokyo) obtained via a GPS module and categories of interest (e.g., music events, museums). The server receives this information, stores it in a database, and creates an individual profile for the user.

[1477] Step 2:

[1478] The server collects event information from social media and online platforms. It uses information collection tools (scraping tools and APIs) to obtain event information based on specific keywords (e.g., music events, art museums). The collected event information includes the event title, location, date and time, and user reviews. It performs a search based on the entered keyword information and stores the obtained event data in a database.

[1479] Step 3:

[1480] The server uses a generative AI model to summarize and organize the collected event information. A prompt is input to the generative AI model, which then summarizes the event based on specific keywords. For example, the following prompt is given to the generative AI model:

[1481] Summarize the following events and extract those that match the user's interest in music events or museums:

[1482] [Event information collected from social media]

[1483] The generative AI model extracts relevant events based on the prompt and outputs summarized information, which the server stores in a database.

[1484] Step 4:

[1485] The server uses a map API (e.g., Google Maps API) to calculate travel times and generate a time schedule. The user's current location information obtained from the database and summarized event information are input into the map API to calculate travel times and routes. The obtained travel time data is used to optimize the daily schedule. For example, a time schedule is generated that includes a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m. The generated schedule is saved on the server.

[1486] Step 5:

[1487] Cameras and microphones installed inside the autonomous vehicle are used to collect user emotional data. Facial expression recognition software and voice analysis software are used to analyze the user's facial and voice data to determine their current emotional state (e.g., positive, negative). The obtained emotional data is sent to a server and added to the user's profile.

[1488] Step 6:

[1489] The server optimizes event suggestions in real time based on the collected emotional data. It then uses the generative AI model again to suggest the next event, taking into account the emotional data. This process re-extracts the events that are best suited to the user's emotional state (e.g., events that can be expected to provide a similarly positive experience if the user is in a positive state). The optimized event suggestions are then displayed on the user's device.

[1490] Step 7:

[1491] The final timetable and route are presented to the user's device and the autonomous vehicle's system. The autonomous vehicle then selects the optimal route based on this schedule and drives the user to their destination. Emotional data is continuously monitored during the journey, and suggestions are adjusted in real time as needed.

[1492] Through these processes, the system can provide users with the most appropriate event information and efficient transportation methods, and improve the accuracy of suggestions in real time by taking into account the user's emotional state.

[1493] 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.

[1494] 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.

[1495] 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.

[1496] [Fourth embodiment]

[1497] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1498] 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.

[1499] 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).

[1500] 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.

[1501] 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.

[1502] 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).

[1503] 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.

[1504] 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.

[1505] 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.

[1506] 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.

[1507] 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.

[1508] 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.

[1509] 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."

[1510] This invention is a system that uses a user's location information and personal data to suggest events and schedules. This system collects information from social media and uses generative AI to summarize and organize it, providing users with the most suitable event information. Below, we will explain the program processing and specific examples of this system in natural language.

[1511] Overall system flow

[1512] 1. User registration and data entry

[1513] Users register using a device and enter their location information and personal data. Location information includes the user's current location (e.g., Shibuya-ku, Tokyo), and personal data includes the user's interests and preferences (e.g., music events, museums, dining, etc.).

[1514] 2. Data storage and initial settings

[1515] The server stores the location and personal data sent by the user in a database, which creates an individual profile for each user.

[1516] 3. Collecting event information from social media

[1517] The server periodically collects event information from online platforms such as social media platforms, using scraping tools and APIs to gather information related to users' interests, such as music events and museum special exhibitions. The collected information includes the event title, location, date and time, and user reviews.

[1518] 4. Summarizing and organizing information using generative AI

[1519] Next, the server uses a generation AI to summarize and organize the collected event information. The generation AI uses natural language processing technology to extract event information that matches the user's interests. This process creates an optimal event list for the user.

[1520] 5. Calculating travel time and generating time schedules

[1521] The server calculates travel time using map data based on the user's current location and selected event information. It uses Google Maps and other map APIs to calculate the optimal travel route between events and create a time schedule. The created schedule includes the start time and travel time for each event.

[1522] 6. Event information and timetable

[1523] The server sends the generated time schedule to the user's device, which then displays detailed information about the event, including transportation options, travel time, and user reviews, making it easy for users to select events that interest them.

[1524] 7. Collecting User Feedback

[1525] Users provide feedback on the proposed events and actions, including ratings, comments, and usage history, which is then sent to the server.

[1526] 8. System Improvements

[1527] The server improves its data and algorithms based on feedback collected from users, and uses this feedback to continue training the generative AI model to improve the accuracy of future suggestions.

[1528] Specific examples

[1529] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[1530] 1. Registration and Data Entry

[1531] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[1532] 2. Data Collection

[1533] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[1534] 3. Generative AI Processing

[1535] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[1536] 4. Generate a time schedule

[1537] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[1538] 5. Presentation of Information

[1539] The server sends this schedule to the user's terminal, where detailed information is displayed.

[1540] In this way, users can quickly obtain the most suitable event information for them and spend their time in a fulfilling manner.

[1541] The processing flow will be explained below.

[1542] Step 1:

[1543] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, art museums) along with their account information. This information is sent to the server.

[1544] Step 2:

[1545] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1546] Step 3:

[1547] The server periodically collects event information from social media sites. It uses scraping tools and APIs to collect data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[1548] Step 4:

[1549] The server stores the collected event information in a database and categorizes and organizes the information as needed.

[1550] Step 5:

[1551] The server uses a generation AI to summarize and organize the collected event information based on the user's personal data. The generation AI automatically uses text summarization technology to extract event information of high interest and create a list containing only the important information.

[1552] Step 6:

[1553] The server creates an optimal event list for the user based on the event information summarized by the generative AI, including rankings and importance.

[1554] Step 7:

[1555] The server uses map data to calculate travel time between events based on the user's current location and the event list, and uses Google Maps and map APIs to determine the optimal route and mode of transportation (walking, cycling, driving, public transportation, etc.).

[1556] Step 8:

[1557] The server generates a detailed time schedule by taking into account the calculated travel time and the event start time. For example, it might be in the format of "14:00 - Live Concert (Shibuya Ward)" -> "15:30 - Travel (15 minutes on foot)" -> "17:00 - Art Exhibition (Shibuya Ward)".

[1558] Step 9:

[1559] The server sends the generated time schedule to the user's device, which displays detailed event information, transportation options, travel times, and user reviews, allowing the user to easily select events that interest them.

[1560] Step 10:

[1561] Users can review the suggested events and provide feedback on their actual events and activities, including ratings, comments, and usage history.

[1562] Step 11:

[1563] The server improves the data and algorithms based on the feedback collected from users, analyzing the feedback information and retraining the generative AI model to improve the accuracy of future suggestions.

[1564] By following the above steps, users can easily obtain the event information and time schedule that best suits them, allowing them to spend their time to the fullest.

[1565] Example 1

[1566] 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."

[1567] Conventional event suggestion systems have difficulty providing optimal event information based on a user's location information and personal data, and the collected information may not perfectly match the user's interests. Furthermore, there is a lack of effective means for quickly organizing the collected information, which results in low accuracy and efficiency of event suggestions to users.

[1568] 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.

[1569] In this invention, the server

[1570] The system includes a means for acquiring user location information, a means for acquiring user personal data, a means for collecting event information from online platforms, a means for summarizing and organizing the collected event information based on the user's personal data using generation AI, a means for calculating travel time between events using linkage with map data to generate a time schedule, a means for presenting the generated time schedule to users, a means for users to register and input their name, email address, and password, and a means for users to input and send feedback, thereby making it possible to efficiently provide optimal event information to each user.

[1571] "User" refers to an individual who uses the System to obtain Event Information.

[1572] "Location information" is data that indicates a user's current location or a specific geographic location.

[1573] "Personal Data" refers to personal information entered by users, such as interests and preferences, name, email address, and password.

[1574] "Information collection means" refers to the technologies and methods used to collect event information from online platforms and social media.

[1575] "Generative AI" refers to a model that uses artificial intelligence technology to summarize and organize collected information and make suggestions to users.

[1576] "Map data" refers to a data set containing information indicating geographic locations and used to calculate travel distances and travel times.

[1577] A "time schedule" is a schedule that includes suggested event start times and travel times for a user.

[1578] "New registration" refers to the act of creating an account by entering a name, email address, password, etc. when a user uses the system for the first time.

[1579] "Feedback" refers to opinions and impressions such as ratings and comments provided by users to the system.

[1580] An "online platform" refers to a service that provides information via the Internet, such as social media, websites, and applications.

[1581] "Integration means" refers to methods and technologies for combining and using different data and services.

[1582] MODE FOR CARRYING OUT THE INVENTION

[1583] This invention is a system that utilizes a user's location information and personal data to optimally suggest events and schedules. This system collects a large amount of information from social media and online platforms, summarizes and organizes it using a generative AI model, and provides event information that is appropriate for the user. Below, we will explain in detail how this system is implemented.

[1584] 1. Hardware and Software

[1585] server

[1586] The server can be a cloud server or an on-premise server (e.g. Amazon Web Services, Google Cloud Platform).A database (e.g. MySQL, PostgreSQL) is installed on the server and stores user location information, personal data, and collected event information.

[1587] Terminal

[1588] The user terminal can be a smartphone, tablet, personal computer (PC), or other device. The terminal is provided with an interface for accessing the system through a dedicated application or a web browser.

[1589] Generative AI Models

[1590] The generative AI model uses advanced AI models (e.g., GPT-3, BERT) that include natural language processing technology, which makes it possible to summarize and organize collected event information based on the user's personal data.

[1591] 2. Program Processing

[1592] The server receives data sent from the user's device and stores it in a database. The server periodically uses scraping tools and APIs to collect event information from social media and other online platforms. The server also uses a generative AI model to summarize and organize the collected event information. The generative AI model extracts the most relevant events based on the user's personal data and incorporates them into a time schedule.

[1593] 3. Specific Examples

[1594] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[1595] 1. User registration and data entry

[1596] The user registers by entering their name, email address, and password. They also enter their address in Shibuya Ward, Tokyo, and their interests as "music events" and "museums."

[1597] 2. Data Collection

[1598] The server collects information from SNS such as "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo." For example, suppose there is a live concert at a live music venue in Shibuya Ward from 2 PM, and a special exhibition at an art museum in Shibuya Ward from 4 PM.

[1599] 3. Generative AI Processing

[1600] The server uses a generative AI model to extract events that match the user's interests from the collected event information, selecting live concerts and art exhibitions.

[1601] 4. Generate a time schedule

[1602] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2 p.m. and an art exhibition at 3:30 p.m.

[1603] 5. Presentation of Information

[1604] The server sends this schedule to the user's terminal, where detailed information is displayed.

[1605] 4. Examples of prompts

[1606] Please enter the user's location and hobby data. If the current location is "Shibuya-ku, Tokyo" and the interests are "music events" and "museums," what kind of event information can you provide?

[1607] In this way, users can quickly obtain the most suitable event information for them and spend their time in a fulfilling manner.

[1608] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1609] Step 1: User registration and data entry

[1610] The user launches the application on their device and proceeds to the new registration screen. They enter their name, email address, password, current location (e.g., Shibuya-ku, Tokyo), and interests and preferences (e.g., music events, art museums). When the user presses the "Register" button, the entered information is sent to the server via the API. The server receives this data and stores it in the appropriate table in the database based on the user index.

[1611] Input: Name, email address, password, location information, interests and preferences

[1612] Output: User profile stored in the database

[1613] Step 2: Save data and set up

[1614] The server stores the location and personal data received from the users in a database and creates an individual profile for each user, which involves inserting the newly received data into the appropriate tables in the database, for example adding new records to the user profile table and the location information table.

[1615] Input: Location and personal data received from the user

[1616] Output: User profile created in the database

[1617] Step 3: Collect event information from social media

[1618] The server periodically collects event information from social media and other online platforms. Specifically, it uses scraping tools and APIs to search for information related to users' interests and obtain the necessary data. The collected information includes the event title, location, date and time, and user reviews. The collected data is temporarily stored.

[1619] Input: Event information from social media and online platforms

[1620] Output: Temporarily saved event information data

[1621] Step 4: Summarizing and organizing information using generative AI

[1622] The server inputs the collected event information into a generative AI model. The generative AI model (e.g., GPT-3) summarizes and organizes the collected information and extracts the event information that best suits the user's interests. This summarized and organized data is extracted and organized based on each user's profile.

[1623] Input: Collected event information

[1624] Output: Summarized and organized event information data

[1625] Step 5: Calculate travel times and generate time schedules

[1626] The server calculates the travel time from the user's current location to the selected event. It uses a map service such as Google Maps API to calculate the appropriate route and travel time. An optimal time schedule is generated along with the calculated travel time. The time schedule includes the start time and travel time of each event.

[1627] Input: User's current location, summary and organized event information

[1628] Output: Generated time schedule

[1629] Step 6: Present the event information and timetable

[1630] The server sends the generated time schedule and event information to the user's device. The device displays the received information on a GUI so that the user can easily check it. The user can view the proposed event information and detailed time schedule.

[1631] Input: Generated time schedule and event information

[1632] Output: Detailed information displayed on the terminal

[1633] Step 7: Gather user feedback

[1634] The user provides feedback on the proposed events and actions from the device. The user inputs feedback such as ratings, comments, and usage history, and presses the send button. The device then sends this feedback information to the server.

[1635] Input: User feedback (ratings, comments, usage history)

[1636] Output: Feedback data sent to the server

[1637] Step 8: Improve your system

[1638] The server stores the received feedback data in a database and uses it to train the existing generative AI model, improving the algorithm and increasing the accuracy of future suggestions.

[1639] Input: Feedback data

[1640] Output: Improved generative AI models and algorithms

[1641] The above is a specific explanation of each processing step of the system, including how the input and output are processed and calculated at each step.

[1642] (Application example 1)

[1643] 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."

[1644] In today's world, there is a growing need for efficient and convenient shopping at brick-and-mortar stores. However, it is difficult for users to plan optimal shopping routes by collecting information on numerous stores, sales, new product arrivals, and other information all at once. Furthermore, finding stores that match one's interests and preferences from the collected information takes time and effort, and users are also required to calculate travel times and select the optimal means of transportation. Conventional systems have had difficulty consistently resolving these issues.

[1645] 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.

[1646] In this invention, the server includes means for acquiring user location information, means for acquiring user personal data, means for collecting physical store information from various online platforms using information collection means, means for summarizing and organizing the collected physical store information based on the user's personal data using a generative AI model, means for calculating optimal travel routes and travel times between physical stores using linkage means with map data to generate a shopping route, and means for presenting the generated shopping route to the user, thereby enabling the user to shop efficiently and have a pleasant shopping experience.

[1647] "User location information" is information that indicates the user's current geographic location.

[1648] "Personal data" is data that includes personal information such as a user's interests and preferences.

[1649] "Information collection means" refers to the means used to collect necessary information from various online platforms.

[1650] "Physical store information" refers to sales information, new product information, business information, etc. related to physical stores.

[1651] A "generative AI model" is a model that uses artificial intelligence to summarize and organize collected information.

[1652] "Map data" refers to data containing geographical information and is used for route calculation and navigation.

[1653] "Travel route" refers to the route a user takes from one point to another.

[1654] "Travel time" refers to the time required to travel from one point to another.

[1655] A "shopping route" refers to a route planned to efficiently visit multiple destinations.

[1656] "Feedback" refers to information such as opinions and ratings provided by users.

[1657] An "algorithm" refers to a procedure or computational method for solving a specific problem.

[1658] "Means for linking with map data" refers to means for calculating travel routes and travel times using geographical information.

[1659] An "online platform" refers to a service that provides information on the Internet, such as a website or social networking site.

[1660] The present invention is a system that uses a user's location information and personal data to provide optimal store information and generate an efficient shopping route. The system includes a means for collecting information from multiple online platforms, summarizing and organizing the information using a generative AI model, and providing the user with the optimal route.

[1661] In one embodiment of the present invention, the process starts when a user uses a smartphone to input their current location and product categories they are interested in. Based on this, the server performs the following process.

[1662] 1. User registration and data entry

[1663] Users access the application from their own devices and register. When registering, they enter their location information (e.g., "Shibuya-ku, Tokyo") and personal data (e.g., "fashion," "electronic devices").

[1664] 2. Data storage and initial settings

[1665] The server stores the location and personal data sent by the user in a database, which creates an individual profile for each user.

[1666] 3. Collection by information gathering means

[1667] The server periodically collects store information from various online platforms, such as social media and store websites. This information includes sales information, new product information, and customer reviews. This information is collected using scraping tools and APIs.

[1668] 4. Summarizing and Organizing Information Using Generative AI Models

[1669] The server uses a generative AI model to summarize and organize the collected store information. The generative AI model uses natural language processing technology to extract the most appropriate information based on the user's personal data and provide useful information to the user.

[1670] 5. Creating shopping routes in conjunction with map data

[1671] Next, the server uses a method to link with map data to calculate the travel time from the user's current location to each store, thereby generating the optimal shopping route. Map services such as Google Maps API can be used.

[1672] 6. Shopping route suggestions

[1673] The generated shopping route and store information is sent to the user's smartphone, where the user can check detailed store information and travel routes through the application and shop efficiently.

[1674] 7. Collecting user feedback and improving the system

[1675] Users can provide feedback about the stores they visit and the products they buy, which is sent to a server to help improve the system's data and algorithms.

[1676] As a concrete example, if a user is located in Shibuya Ward, Tokyo, and is interested in fashion and electronics, the server collects relevant sales and new product information and provides the following prompt sentence as input to the generative AI model: "Based on my current location in Shibuya Ward, Tokyo, please tell me nearby stores where I can purchase the fashion and electronics products I'm interested in. I'd especially like to know about sales and new product information."

[1677] In this way, users can efficiently find stores that suit their interests and plan the optimal shopping route in a short amount of time.

[1678] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1679] Step 1:

[1680] A user registers for the application using a device (e.g., a smartphone). Input includes location information (e.g., "Shibuya-ku, Tokyo") and personal data (e.g., "fashion" and "electronic devices"). The registration data is sent to a server and stored in a database. This creates an individual profile for the user.

[1681] Step 2:

[1682] The server periodically collects information about the physical store from social media and various online platforms (e.g., the store's website) using scraping tools and APIs. The collected information includes sales information, new product information, and reviews. The collected information is stored in the server's database.

[1683] Step 3:

[1684] The server provides the collected store information to a generative AI model, which summarizes and organizes it. The generative AI model uses natural language processing technology to extract the most appropriate information based on the user's personal data. For example, it prioritizes summarizing store information related to specific interests and preferences. The input is the collected store information, and the output is summarized and organized store information. This output is stored in the server's database.

[1685] Step 4:

[1686] The server uses a means of linking with map data to calculate the travel time from the current location to the store. It calculates the travel time and optimal travel route using the Google Maps API, etc. For example, it can give results such as a 10-minute walk to store A and a 15-minute walk to store B. The input is the user's current location and the store's location information, and the output is the travel time and travel route.

[1687] Step 5:

[1688] The server generates a shopping route based on travel time and the optimal travel route, and sends the generated shopping route to the user's terminal. The terminal application receives it and displays detailed store information and the travel route on the user's screen. The user can proceed with shopping along the recommended route. The input is the travel route and summarized store information, and the output is the optimal shopping route.

[1689] Step 6:

[1690] After the user has finished shopping, they provide feedback about the stores they visited and the products they purchased through their device, which is then sent to the server and stored in a database.

[1691] Step 7:

[1692] The server continues to train the generative AI model based on the collected feedback, improving the data and algorithms, which in turn improves the accuracy of future suggestions. The input is the feedback data, and the output is the improved data and algorithms.

[1693] 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.

[1694] This invention is a system that uses a user's location information, personal data, and emotional data to suggest events and schedules, and provides users with the most suitable event information by collecting information from social media, summarizing the data using generative AI, linking it with map data, and using an emotional engine. Below, we will explain the program processing and specific examples of this system in natural language.

[1695] Overall system flow

[1696] 1. User registration and data entry

[1697] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums) along with their account information. This information is sent to the server.

[1698] 2. Data storage and initial settings

[1699] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1700] 3. Collecting event information from social media

[1701] The server periodically collects event information from online platforms such as social media platforms. It uses scraping tools and APIs to collect data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[1702] 4. Summarizing and organizing information using generative AI

[1703] Next, the server uses a generation AI to summarize and organize the collected event information. The generation AI uses natural language processing technology to extract event information that matches the user's interests. This process creates an optimal event list for the user.

[1704] 5. Calculating travel time and generating time schedules

[1705] The server calculates travel time using map data based on the user's current location and selected event information. It uses Google Maps and other map APIs to calculate the optimal travel route between events and create a time schedule. The created schedule includes the start time and travel time for each event.

[1706] 6. Collecting Emotional Data

[1707] The user's device is equipped with an emotion engine to collect emotional data about the proposed event, and understands the user's current emotional state through facial expression recognition and voice analysis.

[1708] 7. Leveraging Emotional Engines

[1709] The server obtains a real-time evaluation of the proposed event based on the collected emotional data. For example, it analyzes whether the user is interested or indifferent to the proposed event information and uses this information to improve the accuracy of future event suggestions.

[1710] 8. Event information and timetable

[1711] The server sends the generated time schedule to the user's device, which displays detailed event information, transportation options, travel time, user reviews, and even feedback on the user's emotional state, allowing the user to easily select events that interest them.

[1712] 9. Collecting User Feedback

[1713] Users provide feedback on proposed events and actions, including ratings, comments, usage history, and even emotional data from the emotion engine. This information is sent to the server.

[1714] 10. System Improvements

[1715] The server improves its data and algorithms based on the feedback and sentiment data collected from users, which is then used to retrain the generative AI model to improve the accuracy of future suggestions.

[1716] Specific examples

[1717] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system will operate as follows:

[1718] 1. Registration and Data Entry

[1719] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[1720] 2. Data Collection

[1721] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[1722] 3. Generative AI Processing

[1723] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[1724] 4. Generate a time schedule

[1725] The server calculates the travel time from the user's current location to each event and creates a time schedule for a live music venue and art museum that are within a 10-minute walk, for example, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[1726] 5. Presentation of Information

[1727] The server sends this schedule to the user's device, where detailed information is displayed. At this time, the emotion engine analyzes the user's emotions in real time and uses them to provide feedback on events.

[1728] 6. User Feedback

[1729] Users participate in the proposed events and provide feedback about their experiences, and emotional data collected by the emotion engine is also sent to the server.

[1730] In this way, the system takes the user's emotional state into consideration and suggests optimal event information and time schedules, allowing users to easily obtain the event information that is best suited to them and spend their time in a fulfilling manner.

[1731] The processing flow will be explained below.

[1732] Step 1:

[1733] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums) along with their account information. This information is sent to the server.

[1734] Step 2:

[1735] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1736] Step 3:

[1737] The server periodically collects event information from social media sites. Using scraping tools and APIs, it collects data based on specific keywords (e.g., music events, museums). The collected information includes the event title, location, date and time, and user reviews.

[1738] Step 4:

[1739] The server stores the collected event information in a database and categorizes and organizes the information as needed.

[1740] Step 5:

[1741] The server uses a generation AI to summarize and organize the collected event information based on the user's personal data. The generation AI uses natural language processing technology to extract interesting event information and create a list containing only the important information.

[1742] Step 6:

[1743] The server creates an optimal event list for the user based on the event information summarized by the generative AI, including rankings and importance.

[1744] Step 7:

[1745] The server uses map data to calculate travel time between events based on the user's current location and the event list, and uses Google Maps and map APIs to determine the optimal route and mode of transportation (walking, cycling, driving, public transportation, etc.).

[1746] Step 8:

[1747] The server generates a detailed time schedule by taking into account the calculated travel time and the event start time, for example, "14:00 - Live Concert (Shibuya Ward)" → "15:30 - Travel (15 minutes on foot)" → "17:00 - Art Exhibition (Shibuya Ward)".

[1748] Step 9:

[1749] The user's device uses an emotion engine to analyze the user's emotions in real time. It uses facial expression recognition and voice analysis to understand how the user feels about the proposed event information. This emotion data is then sent to the server.

[1750] Step 10:

[1751] The server receives the emotion data and obtains real-time evaluations of the proposed events. The server classifies the events that the user is interested in and those that the user is not interested in, and reflects this in future event suggestions.

[1752] Step 11:

[1753] The server then sends the generated time schedule and event information based on the results of the emotion analysis to the user's device, which then displays detailed information about the event, transportation methods, travel time, user reviews, and the results of the emotion analysis on the device's display.

[1754] Step 12:

[1755] Users provide additional emotional feedback for the proposed events, including ratings and comments on the events they have actually attended, as well as real-time emotional data from the emotion engine, which is then sent to the server.

[1756] Step 13:

[1757] The server improves its data and algorithms based on the feedback and sentiment data collected from users, analyzing the feedback information and retraining the generative AI model to improve the accuracy of future suggestions.

[1758] Through these steps, the system takes the user's emotional state into consideration and suggests optimal event information and time schedules, allowing users to easily obtain the event information that best suits them and spend their time in a fulfilling manner.

[1759] Example 2

[1760] 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."

[1761] Conventional event suggestion systems have limited means of providing event information based on users' personal data, and it is difficult to make suggestions that take into account travel time and emotional state. Furthermore, there is a lack of mechanisms for improving the system using user feedback and emotional data, making it difficult to improve the accuracy of suggestions.

[1762] 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 acquiring user location information, means for acquiring user personal data, means for collecting event information from online platforms using information collection means, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for calculating travel time between events using map data and generating a time schedule, means for collecting emotion data, means for improving event suggestions based on the collected emotion data, means for presenting the generated time schedule to the user, means for collecting user feedback, and means for improving data and algorithms based on the collected feedback. This makes it possible to generate optimal event suggestions and time schedules taking into account the user's location information and emotion data, and to improve the system based on user feedback.

[1763] "Means for obtaining user location information" refers to a device or software that has the function of determining the user's location and transmitting that location data to the system.

[1764] "Means for obtaining user personal data" refers to devices or software that have the function of collecting specific information such as the user's interests, hobbies, and personal information, and providing it to the system.

[1765] "Means for collecting event information from online platforms using information collection means" refers to tools and technologies for obtaining data about events from social media and other online platforms via the Internet.

[1766] "Means for summarizing and organizing event information collected using generative AI based on user personal data" refers to a technology that uses a generative AI model to summarize and organize large amounts of event information based on user interests and specific information.

[1767] "Means of calculating travel times between events using map data and generating a time schedule" refers to a technology that uses a map service API to calculate travel times from the user's current location to each event location and creates an optimal time schedule based on that.

[1768] "Means for collecting emotional data" refers to a device or software that analyzes the user's emotional state from facial expressions, voice, etc., and collects that data.

[1769] "Means for improving event suggestions based on collected emotional data" refers to technology that analyzes collected emotional data and makes more attractive event suggestions to users.

[1770] "Means for presenting the generated time schedule to the user" refers to a technology for visually displaying the generated time schedule and related information and providing it to the user.

[1771] "Means for collecting user feedback" means any device or software that allows users to input and submit ratings and comments about proposed events.

[1772] "Means for improving data and algorithms based on collected feedback" refers to technology that analyzes feedback collected from users and optimizes and improves the system's database and algorithms based on that feedback.

[1773] The present invention is a system for suggesting events and schedules by utilizing a user's location information, personal data, and emotional data. The system mainly includes the following elements: a means for acquiring a user's location information, a means for acquiring a user's personal data, a means for collecting event information from online platforms using an information collection means, a means for summarizing and organizing the collected event information using a generative AI, a means for calculating travel times between events using map data and generating a time schedule, a means for collecting emotional data, a means for improving event suggestions based on the collected emotional data, a means for presenting the generated time schedule to the user, and a means for collecting user feedback to improve the data and algorithms.

[1774] The user accesses the new registration screen using their device and enters their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, art museums) along with their account information. This information is sent to the server. The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1775] The server periodically collects event information from social media and other online platforms. It uses scraping tools and APIs (e.g., Twitter API, Instagram Graph API) to extract data based on specific keywords (e.g., music events, museums). The collected information includes event titles, locations, dates, and reviews.

[1776] The server then uses a generative AI (e.g., OpenAI's GPT model) to summarize and organize the collected event information. The generative AI uses natural language processing technology to extract event information that matches the user's interests, and this process creates an optimal event list for the user.

[1777] The server then calculates travel time using a map API such as Google Maps based on the user's current location and the selected event information. This process generates the optimal travel route and time schedule between events. Detailed event information, transportation methods, travel time, and customer reviews are then displayed on the user's device.

[1778] The user's device is equipped with an emotion engine (e.g., Face API, voice analysis engine) that grasps the user's current emotional state through facial expression recognition and voice analysis. The server analyzes the user's emotional state based on the collected emotion data and obtains a real-time evaluation of the proposed event. This data is used to improve the accuracy of future event suggestions.

[1779] Users participate in the suggested events and provide ratings and comments about their experiences. Emotional data collected by the emotion engine is also sent to the server. The server uses this collected feedback and emotion data to improve the system's data and algorithms, thereby improving the accuracy of future suggestions.

[1780] Specific examples

[1781] For example, if a user lives in Shibuya, Tokyo, and is interested in music events and museums, the system works as follows:

[1782] 1. Registration and Data Entry

[1783] A user registers as a new user, entering their address as Shibuya-ku, Tokyo, and their interests as "music events" and "museums."

[1784] 2. Data Collection

[1785] The server collects information about "music events in Shibuya Ward" and "special exhibitions at art museums in Tokyo" from social media. For example, suppose there is a live concert at a live music venue in Shibuya Ward starting at 2:00 PM, and a special exhibition at an art museum in Shibuya Ward starting at 4:00 PM.

[1786] 3. Generative AI Processing

[1787] The server uses generative AI to extract events that match the user's interests from the collected event information, and selects live concerts and art exhibitions.

[1788] 4. Generate a time schedule

[1789] The server calculates the travel time from the user's current location to each event and creates a time schedule for live music venues and art museums that are within a 10-minute walk, with a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m.

[1790] 5. Presentation of Information

[1791] The server sends this schedule to the user's device, where detailed event information is displayed. At this time, the emotion engine analyzes the user's emotions in real time and obtains their feedback.

[1792] 6. User Feedback

[1793] Users participate in the proposed events and provide feedback about their experiences, and emotional data collected by the emotion engine is also sent to the server.

[1794] Prompt Sentence Examples

[1795] The prompt text to explain the system's behavior is:

[1796] "The user lives in Shibuya Ward and is interested in music events and art museums. Please generate the optimal time schedule for the user based on event information collected from social media. Please also provide detailed information about each event and travel times."

[1797] In this way, the present invention provides optimal event information and time schedules while taking into consideration the emotional state of the user, allowing the user to easily obtain event information that is optimal for them and spend a fulfilling time.

[1798] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1799] Step 1: User registration and data entry

[1800] Specific explanation

[1801] The user accesses the new registration screen using their device and enters their account information (such as name, email address, and password) along with their location information (e.g., Shibuya-ku, Tokyo) and personal data (e.g., interests: music events, museums). This information is sent to the server.

[1802] input

[1803] User account information, location information, and personal data

[1804] output

[1805] User data sent to the server

[1806] Specific actions

[1807] A user opens a web browser or mobile app and accesses the new registration screen.

[1808] Enter your name, email address, password, location, and interests.

[1809] Press the "Register" button and the device will send the input data to the server.

[1810] ---

[1811] Step 2: Save data and set up

[1812] Specific explanation

[1813] The server stores the location information and personal data sent by the user in a database and creates an individual profile for each user.

[1814] input

[1815] User location information, personal data

[1816] output

[1817] User profiles stored in a database

[1818] Specific actions

[1819] The server processes the data received from the terminal and stores it in a database.

[1820] A unique user ID is assigned to each user and initial settings are performed.

[1821] Generate a keyword list based on personal data.

[1822] ---

[1823] Step 3: Collect event information from social media

[1824] Specific explanation

[1825] The server periodically collects event information from social media and other online platforms, and uses scraping tools and APIs to extract data based on specific keywords.

[1826] input

[1827] Keyword List

[1828] output

[1829] Event information stored in the database

[1830] Specific actions

[1831] The server calls the SNS API based on the keyword list.

[1832] Get information about the event (title, location, date, time, reviews, etc.).

[1833] The acquired data is saved in the "Event Information" table of the database.

[1834] ---

[1835] Step 4: Summarizing and organizing information using generative AI

[1836] Specific explanation

[1837] The server summarizes and organizes the collected event information using a generation AI, which uses natural language processing technology to extract event information that matches the user's interests.

[1838] input

[1839] Event information collected from SNS

[1840] output

[1841] Abridged Event Listing

[1842] Specific actions

[1843] The server inputs the collected event data into a generative AI model.

[1844] A generative AI model extracts event information relevant to the user's interests.

[1845] The extracted information is organized to create an optimal event list for each user.

[1846] ---

[1847] Step 5: Calculate travel times and generate time schedules

[1848] Specific explanation

[1849] The server uses a map API to calculate travel time based on the user's current location and selected event information, generating the optimal travel route and time schedule between events.

[1850] input

[1851] User's current location, event information

[1852] output

[1853] Time Schedule

[1854] Specific actions

[1855] The server sends the user's current location and the event's location information to the map API.

[1856] Get travel route and travel time.

[1857] A time schedule is generated based on the start time and travel time of each event.

[1858] ---

[1859] Step 6: Collect emotion data

[1860] Specific explanation

[1861] The user's device is equipped with an emotion engine that grasps the user's emotional state through facial expression recognition and voice analysis.

[1862] input

[1863] User facial expression data, voice data

[1864] output

[1865] Emotional Data

[1866] Specific actions

[1867] The device uses the built-in camera and microphone to capture the user's facial expressions and voice.

[1868] The emotion engine analyzes the data and determines the emotional state.

[1869] The determined emotion data is transmitted to the server.

[1870] ---

[1871] Step 7: Leverage your emotional engine

[1872] Specific explanation

[1873] The server uses the collected emotional data to evaluate the user's level of interest in the proposed event and improves the accuracy of future suggestions.

[1874] input

[1875] Emotional Data

[1876] output

[1877] Proposed algorithm with improved accuracy

[1878] Specific actions

[1879] The server receives and analyzes the emotional data and evaluates the user's emotional state.

[1880] We will adjust the suggestion algorithm and reflect this in our next event suggestions.

[1881] ---

[1882] Step 8: Present the event information and timetable

[1883] Specific explanation

[1884] The server sends the generated time schedule and event information to the user's terminal.

[1885] input

[1886] Time schedule and event information

[1887] output

[1888] Event information and schedules displayed on your device

[1889] Specific actions

[1890] The server transmits the event list and time schedule generated for each user to the terminal.

[1891] The device organizes the received information and displays it on a user interface.

[1892] Information displayed includes event details, transportation options, and reviews.

[1893] ---

[1894] Step 9: Gather user feedback

[1895] Specific explanation

[1896] Users attend the suggested events and provide feedback about their experience, including emotional data collected by the emotion engine.

[1897] input

[1898] User feedback comments and sentiment data

[1899] output

[1900] Feedback data sent to the server

[1901] Specific actions

[1902] Users use their device to enter ratings and comments and press the send button.

[1903] The emotion data collected by the emotion engine is also sent to the server in parallel.

[1904] ---

[1905] Step 10: Improve your system

[1906] Specific explanation

[1907] The server uses feedback and sentiment data collected from users to improve the system's data and algorithms.

[1908] input

[1909] Feedback data, emotion data

[1910] output

[1911] Improved algorithms and databases

[1912] Specific actions

[1913] The server analyzes the collected feedback and emotion data.

[1914] Based on the analysis results, the generative AI model is retrained and the proposed algorithm is optimized.

[1915] The improved algorithm will be reflected in the system and used to suggest future events.

[1916] (Application example 2)

[1917] 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."

[1918] Conventional event suggestion systems primarily suggest events based on the user's location information and personal data, but because they do not take into account the user's emotional state, they may not provide completely satisfying suggestions. Furthermore, because individual suggestions are not integrated into a continuous action plan, users must independently secure transportation and routes, which is inconvenient. Furthermore, they lack convenience due to the lack of real-time optimization of event suggestions and efficient transportation management using autonomous vehicles.

[1919] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for acquiring user personal data, means for collecting event information from online platforms using information collection means, means for summarizing and organizing the collected event information based on the user's personal data using generation AI, means for calculating travel time between events and generating a time schedule using linkage means with map data, means for collecting and analyzing user emotion data, means for presenting the generated time schedule to an autonomous vehicle and presenting it to the user, means for optimizing event suggestions in real time based on the user emotion data, and means for selecting an optimal travel route and automatically adjusting the means of transportation. This makes it possible to optimize event suggestions and means of transportation taking emotion data into consideration.

[1920] "Means for obtaining user location information" refers to a device or system that obtains the user's current location using location information technologies such as GPS, Wi-Fi, or Bluetooth.

[1921] "Means for obtaining user personal data" refers to a device or system that collects personal data about a user, such as the user's categories of interest and past behavioral history.

[1922] "Information collection means" refers to tools and APIs for obtaining data such as event information from online platforms such as social media, blogs, and news sites.

[1923] "Generative AI" is an artificial intelligence technology that analyzes collected information and appropriately summarizes and organizes it based on the user's personal data.

[1924] "Means of linking with map data" refers to the use of map APIs and geographic information systems (GIS) to calculate travel times and routes based on the user's current location and destination.

[1925] The "means for generating a time schedule" is a system for creating an efficient schedule by taking into account the user's travel time and the start time of events.

[1926] "Means for collecting and analyzing user emotional data" refers to a system that uses devices such as cameras and microphones to analyze the user's facial expressions and tone of voice, and grasps the user's current emotional state.

[1927] The "means for presenting to the user" refers to an interface or display that displays the generated time schedule and event proposals on the user's device so that the user can view them.

[1928] The "means for optimizing event suggestions in real time" is a system for adjusting event suggestions in real time according to the user's current emotional state based on collected emotional data.

[1929] "Means for selecting optimal travel routes and automatically adjusting means of transportation" refers to a system that uses autonomous vehicles to optimize travel between events in which a user participates, and automatically selects and adjusts routes and means of transportation.

[1930] overview

[1931] This invention is a system that uses a user's location information, personal data, and emotion data to suggest optimal events and transportation methods. This system is particularly intended for efficient management of travel between events in autonomous vehicles and for providing optimal events to users in real time.

[1932] Required Hardware and Software

[1933] In order to implement this invention, the following hardware and software are required.

[1934] 1. Hardware

[1935] GPS module: To obtain the user's location information

[1936] Camera: To collect user facial expression data

[1937] Microphone: To collect user voice data

[1938] Smartphone or tablet: as the user interface

[1939] Autonomous vehicles: transportation

[1940] 2. Software

[1941] GPS tracking software: To obtain location information

[1942] Facial expression recognition software: To analyze the user's facial expressions and obtain emotional data

[1943] Voice analysis software: To analyze the user's voice and obtain emotional data

[1944] Social media scraping tools: To collect event information from online platforms

[1945] Generative AI model: To summarize the collected event information and extract the most suitable events for the user

[1946] Map APIs (e.g., Google Maps API): for travel time calculations and route optimization

[1947] Autonomous driving systems: as a means of transportation

[1948] Specific example of system operation

[1949] 1. Entering your location and personal data

[1950] Users log in to the system using a smartphone or tablet and enter their location information and personal data (such as categories of interest). This location information is acquired by a GPS module, and the personal data is stored in the system.

[1951] 2. Collecting event information

[1952] The server uses scraping tools to collect event information from social media and online platforms, retrieves event information based on specific keywords, and stores it on the server.

[1953] 3. Summarizing and organizing event information using generative AI

[1954] The server inputs the collected event information into a generative AI model, which then summarizes and organizes appropriate event information based on the user's personal data. As a concrete example, we use the following prompt sentence:

[1955] Summarize the following events and extract those that match the user's interest in music events or museums:

[1956] [Event information collected from social media]

[1957] 4. Generate travel routes and time schedules

[1958] The server uses a map API (such as Google Maps API) to calculate the travel time from the user's current location to each event venue, generates the optimal route, and creates an efficient time schedule taking into account the time slots of the proposed events.

[1959] 5. Emotional Data Collection and Analysis

[1960] Cameras and microphones inside the autonomous vehicle collect user emotional data, which is then analyzed using facial recognition and voice analysis software to understand the user's current emotional state.

[1961] 6. Real-time recommendation optimization

[1962] The server uses a generative AI model based on emotion data to optimize event suggestions in real time: for example, if a user has a positive reaction to a suggested event, the next event will be tailored to elicit a similarly positive reaction.

[1963] 7. Present the final schedule and execute the transfer

[1964] The optimized time schedule and travel route will be displayed on the autonomous vehicle's system and on the user's device, and the autonomous vehicle will then take the user to the next event venue according to the optimal route.

[1965] Through these processes, the present invention can provide users with optimal event information and efficient means of transportation, and improve the accuracy of suggestions in real time by taking into account the user's emotional state.

[1966] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1967] Step 1:

[1968] Users log in to the app using their smartphone or tablet and enter their location and personal data, including their current location (e.g., Shibuya-ku, Tokyo) obtained via a GPS module and categories of interest (e.g., music events, museums). The server receives this information, stores it in a database, and creates an individual profile for the user.

[1969] Step 2:

[1970] The server collects event information from social media and online platforms. It uses information collection tools (scraping tools and APIs) to obtain event information based on specific keywords (e.g., music events, art museums). The collected event information includes the event title, location, date and time, and user reviews. It performs a search based on the entered keyword information and stores the obtained event data in a database.

[1971] Step 3:

[1972] The server uses a generative AI model to summarize and organize the collected event information. A prompt is input to the generative AI model, which then summarizes the event based on specific keywords. For example, the following prompt is given to the generative AI model:

[1973] Summarize the following events and extract those that match the user's interest in music events or museums:

[1974] [Event information collected from social media]

[1975] The generative AI model extracts relevant events based on the prompt and outputs summarized information, which the server stores in a database.

[1976] Step 4:

[1977] The server uses a map API (e.g., Google Maps API) to calculate travel times and generate a time schedule. The user's current location information obtained from the database and summarized event information are input into the map API to calculate travel times and routes. The obtained travel time data is used to optimize the daily schedule. For example, a time schedule is generated that includes a live concert at 2:00 p.m. and an art exhibition at 3:30 p.m. The generated schedule is saved on the server.

[1978] Step 5:

[1979] Cameras and microphones installed inside the autonomous vehicle are used to collect user emotional data. Facial expression recognition software and voice analysis software are used to analyze the user's facial and voice data to determine their current emotional state (e.g., positive, negative). The obtained emotional data is sent to a server and added to the user's profile.

[1980] Step 6:

[1981] The server optimizes event suggestions in real time based on the collected emotional data. It then uses the generative AI model again to suggest the next event, taking into account the emotional data. This process re-extracts the events that are best suited to the user's emotional state (e.g., events that can be expected to provide a similarly positive experience if the user is in a positive state). The optimized event suggestions are then displayed on the user's device.

[1982] Step 7:

[1983] The final timetable and route are presented to the user's device and the autonomous vehicle's system. The autonomous vehicle then selects the optimal route based on this schedule and drives the user to their destination. Emotional data is continuously monitored during the journey, and suggestions are adjusted in real time as needed.

[1984] Through these processes, the system can provide users with the most appropriate event information and efficient transportation methods, and improve the accuracy of suggestions in real time by taking into account the user's emotional state.

[1985] 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.

[1986] 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 ...

Claims

1. A means for obtaining user location information; The means by which the personal data of the user is obtained; A means of collecting event information from SNS using information collection means; A means of summarizing and organizing the event information collected using generative AI based on the user's personal data; a means for calculating travel times between events using a means for linking with map data and generating a time schedule; The system includes a means for presenting the generated time schedule to a user.

2. a means of collecting user feedback; The system of claim 1 further comprising means for improving the data and algorithms based on the collected feedback.

3. The system of claim 1 , further comprising means for selecting an optimal means of transportation and calculating travel time based on the user's location information.

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