System

Abstract

A system is provided.SOLUTION: A means for arranging schedules of an event among a plurality of participants via a communication network, a AI (AI) means for collecting schedule information of the participants and proposing an optimal schedule, a means for automatically transmitting reminders to participants who have not responded, a means for proposing a place to hold the event via the communication network, a means for automatically making a reservation for a place selected from the proposed places, and a means for collecting accounting information of the event, A system comprising: means for automatically calculating a split bill between participants; and means for completing payment between the participants in cooperation with a settlement application based on the accounting information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The work of organizing a drinking party or event requires a lot of time and effort, including coordinating schedules for participants, selecting an appropriate venue, and even handling accounting. This increases the burden on the organizer, and can make it difficult to run the event smoothly. Manual management can be particularly cumbersome when there are many participants or when scheduling around a busy schedule. Furthermore, the procedures for accounting and splitting the bill are cumbersome, and there is a risk of financial troubles occurring. Existing methods are insufficient to solve these problems, and a new system that can handle them efficiently and accurately is needed. [Means for solving the problem]

[0005] The present invention includes a means for coordinating event schedules among multiple participants via a communications network, a generating artificial intelligence (AI) means for collecting participant schedule information and proposing optimal schedules, and a means for automatically sending reminder notifications to participants who have not yet responded. It also includes a means for proposing event locations and a means for automatically making reservations at locations selected from the proposed locations. The present invention also includes a means for collecting accounting information for the event and automatically splitting the bill among participants, and a means for completing payments among participants in cooperation with a payment application based on the accounting information. This reduces the workload of event organizers and enables efficient and smooth event management.

[0006] A "communications network" is an infrastructure for transmitting and receiving data between multiple terminals.

[0007] "Schedule adjustment" is the process of aggregating the schedules of multiple participants and selecting the optimal date.

[0008] "Generative AI" is a system that uses artificial intelligence technology to analyze data and generate results.

[0009] A "reminder notification" is an automatic notification sent to participants who have not yet responded to encourage them to respond.

[0010] The "means of suggestion" is a mechanism that provides optimal options based on input information.

[0011] The "means for making a reservation" is a mechanism that automatically performs the necessary reservation procedures for the selected location or facility.

[0012] "Accounting information" refers to information relating to the amount of payment incurred for services or products used.

[0013] "Bill splitting" is a calculation process in which the total amount incurred is divided fairly among the participants.

[0014] A "payment application" is software for processing payments electronically. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0023] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0036] The present invention relates to a drinking party organizer support system that uses a communication application. This system uses a generation AI to provide comprehensive support for scheduling, restaurant selection, and payment. Specific embodiments of the system are described below.

[0037] 1. Schedule adjustment function

[0038] The server has the function of sending a questionnaire for scheduling an event to LINE groups and other communication groups. Each participant answers the questionnaire to indicate their available dates. This response data is sent to the server via the terminal. The server collects this data and proposes the optimal schedule.

[0039] When User A enters and submits their free schedule, the device immediately transfers this information to the server. The server uses a generation AI to analyze the collected schedule information and sends the optimal schedule as a proposal to the LINE group. After that, the server automatically sends reminder notifications to users who have not yet responded.

[0040] 2. Store selection function

[0041] Users enter information such as the date, budget, food preferences, and location of the event on the LINE application. This information is sent to the server via the device. The server uses AI to generate a list of suitable restaurants based on this information and sends it to the LINE group.

[0042] For example, if User B enters "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server will search for Japanese restaurants in Shibuya based on this data and use generation AI to suggest "Restaurant A, Restaurant B, Restaurant C." If User B selects "Restaurant B" from the list, the server will automatically send an instruction to make a reservation at Restaurant B.

[0043] 3. Payment and splitting features

[0044] After the drinking party is over, the billing information from the bar is sent to the server. This information is stored in a database, and the server tallies the total amount and calculates the split between the participants. The calculation result is notified to the LINE group, and payment details are communicated to each user.

[0045] User C receives a notification on the LINE app and makes a payment using a payment application such as PayPay. This payment data is transferred by the device to the server, and the server confirms that the payment has been completed.

[0046] Specific examples

[0047] For example, the date of a drinking party is decided to be "April 1st," and the server uses a generation AI to suggest "Store X, Store Y, Store Z" from among Japanese restaurants in Shibuya. User D selects "Store Y" and the reservation is completed. After the drinking party, a total of 15,000 yen is registered on the server, and the bill is split among five people, at 3,000 yen each. The server sends a notification to the LINE group that "3,000 yen per person," and each user pays 3,000 yen with PayPay.

[0048] This allows event organizers to efficiently and smoothly manage a series of tasks, from scheduling to choosing restaurants and paying the bill. The introduction of this system significantly reduces the burden on event organizers and allows participants to enjoy the event comfortably.

[0049] The processing flow will be explained below.

[0050] 1. Schedule adjustment function

[0051] Step 1: Send the survey

[0052] Server: Create and send a schedule adjustment survey to all participants in the LINE group.

[0053] Device: The survey form is displayed to the user on the LINE app.

[0054] Step 2: Collect responses

[0055] User: Enter your available dates in the survey form and tap the submit button.

[0056] Terminal: Transfers user input to the server.

[0057] Server: Saves the collected response data of each user in a database.

[0058] Step 3: Propose the best schedule

[0059] Server: Based on the collected data, the optimal schedule is calculated using a generative AI.

[0060] Server: Sends the calculation results to the LINE group as a proposal.

[0061] Terminal: Notifies the user of the suggested optimal schedule.

[0062] Step 4: Send a reminder

[0063] Server: Lists participants who have not responded and automatically sends reminder messages.

[0064] Terminal: Display a prompt message to the user.

[0065] 2. Store selection function

[0066] Step 1: Enter your information

[0067] User: Enter necessary information such as dates, budget, food preferences, and location on the LINE app.

[0068] Terminal: Transfers the entered information to the server.

[0069] Step 2: Generate a list of stores

[0070] Server: Uses generative AI to create a list of appropriate stores based on the input information.

[0071] Server: Send the created list to the LINE group.

[0072] Terminal: Shows the user a list of stores.

[0073] Step 3: Confirm your reservation

[0074] User: Select the desired store from the list of suggested stores.

[0075] Terminal: Transfers the selection results to the server.

[0076] Server: Automatically executes the reservation procedure for the selected restaurant.

[0077] 3. Payment and splitting features

[0078] Step 1: Collect your billing information

[0079] Server: Receives billing information from the restaurant on the day of the drinking party.

[0080] Server: Stores the collected accounting information in a database.

[0081] Step 2: Split the bill

[0082] Server: Calculate the total amount divided by the number of people.

[0083] Server: Notify the LINE group of the calculation results.

[0084] Terminal: Display a notification of the split amount to the user.

[0085] Step 3: Checkout

[0086] User: Checks the notification and pays his / her share using the payment application.

[0087] Terminal: Transfers payment data to the server.

[0088] Server: Works with the payment application to verify payments from each user.

[0089] This allows the organizer to efficiently and smoothly carry out the entire process of the drinking party, from preparation to its end.

[0090] Example 1

[0091] 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."

[0092] With conventional event management systems, a series of tasks such as scheduling, selecting restaurants, splitting the bill, and settling the payment required a lot of time and effort, placing a heavy burden on the organizer. Furthermore, communication between participants was sometimes not smooth, which could lead to delays in planning and execution of the event.

[0093] 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.

[0094] In this invention, the server includes: means for coordinating event dates among multiple participants via a communications network; a generating artificial intelligence (AI) means for collecting schedule information from the participants and proposing the optimal schedule; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing event locations via the communications network; means for automatically making reservations at locations selected from the proposed locations; means for collecting accounting information for the event and automatically splitting the bill among participants; and means for completing payment among participants in cooperation with a payment application based on the accounting information. This automates the entire process from scheduling to restaurant selection, accounting, and payment, significantly reducing the burden on event organizers and enabling smoother event planning and execution.

[0095] A "communications network" refers to a network that allows computers and terminals to exchange information with each other. This includes the Internet and local area networks (LANs).

[0096] "Participant" means any person or group who intends to attend the Event and who is involved in scheduling and selecting the location of the Event.

[0097] "Generative artificial intelligence (AI)" refers to a technology that analyzes large amounts of data, finds patterns, and supports decision-making. In this invention, it plays a role in suggesting optimal dates and restaurant options.

[0098] A "reminder" is a warning message that alerts users to take a specific action, such as a notification to remind unanswered participants to reschedule.

[0099] "Event location" refers to the physical or virtual location where the event takes place, such as a restaurant, conference room, or online meeting platform.

[0100] "Financial Information" means detailed information about costs and expenses related to an Event, including data necessary to calculate totals and split bills at restaurants.

[0101] "Payment application" means software that enables users to make or receive payments online or through a mobile device. Examples include e-wallet apps and mobile banking apps.

[0102] This invention relates to a system for efficiently managing events over a communication network. Specific components of the system include a server, terminals, and users. The purpose of this invention is to provide a series of functions using generative AI models to facilitate smooth communication between participants and event implementation.

[0103] First, the server provides a means for multiple participants to coordinate event dates via a communication network. Specifically, the server sends a questionnaire for scheduling an event using a LINE group or other communication platform. Participants respond with their available dates using their devices, and this information is sent to the server.

[0104] Next, the server collects the participants' schedule information and uses a generation AI to suggest the best schedule. This generation AI analyzes a large amount of data to find the best schedule for all participants. Reminder notifications are also automatically sent to participants who have not yet responded. These notifications include a reminder message and encourage them to respond again.

[0105] Furthermore, the server has a means to suggest locations for events. Users input requirements such as event dates, budget, food preferences, and location through the LINE app. The input information is sent to the server via the device, and the server uses generation AI to generate a list of appropriate restaurants based on this information. This list is sent to the LINE group, allowing the user to select the restaurant of their choice.

[0106] When a user selects a store, the server automatically makes a reservation at the selected store. This eliminates the need for reservations and allows for smooth seating arrangements. After the event ends, the store sends accounting information to the server. This information is stored in a database, and the server tallies the total amount and calculates the split between participants.

[0107] Finally, the calculation result is notified to the LINE group, and payment details are sent to each user. Users receive a notification on the LINE app and make the payment using a payment app such as PayPay. The payment data is transferred by the device to the server, and the server confirms that the payment has been completed.

[0108] Examples:

[0109] For example, when User A enters his or her available dates of "October 5th, 8th, and 10th" in the LINE app and submits them, the server collects this information, analyzes it using the generation AI, and suggests "October 8th" as the optimal date. If User B then enters information such as "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server suggests "Restaurant A, Restaurant B, and Restaurant C," and User B selects "Restaurant B," completing the reservation. After the drinking party, the total amount of 15,000 yen is registered in the database, and the bill is split among the five people at 3,000 yen each, and this is notified to the LINE group. Each user pays 3,000 yen with PayPay, and the server sends a completion notification.

[0110] Example prompt sentence:

[0111] "I'd like to schedule a drinking party in October. Please choose any days that are free. For example, October 5th, 8th, and 10th."

[0112] "Please find a Japanese restaurant in Shibuya on March 15th that costs under 5,000 yen."

[0113] "The total cost of the drinking party is 15,000 yen. We will split it among five people, so please pay 3,000 yen per person with PayPay."

[0114] This allows the organizer to efficiently and smoothly manage a series of tasks, from scheduling to choosing a restaurant and paying the bill, allowing participants to enjoy the event comfortably.

[0115] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0116] Processing steps for the schedule adjustment function

[0117] Step 1:

[0118] The server sends a questionnaire for scheduling an event to a LINE group or other communication group via a communication network. The input includes a list of participants and the contents of the questionnaire. Based on this, the server generates a questionnaire message and sends it to the group. The output is the sent questionnaire message.

[0119] Step 2:

[0120] Users enter their free dates in a questionnaire format through the LINE app. For example, User A enters "October 5th, 8th, and 10th." This data is sent as input to the device, which then forwards the information to the server. The output is the schedule information sent to the server.

[0121] Step 3:

[0122] The server collects schedule data sent by all users. The input includes individual schedule information from participants. The server analyzes this data using a generative AI to calculate the optimal schedule. The output is the optimal schedule information.

[0123] Step 4:

[0124] The server sends the analysis results as a proposal to the LINE group and notifies participants. The input required is the optimal schedule information calculated by the generation AI. The server forms this as a proposal message and sends it to the group. The output is the proposal message for the optimal schedule that was sent.

[0125] Step 5:

[0126] The server automatically sends reminder notifications to participants who have not yet responded. The input includes a list of participants who have not yet responded. Based on this, the server generates and sends a reminder message. The output is the sent reminder message. Specifically, the message is sent using the reminder notification function.

[0127] Store selection function processing steps

[0128] Step 1:

[0129] Users input information such as the date, budget, food preferences, and location of an event through the LINE app. For example, User B inputs "March 15th, budget 5,000 yen, Japanese food, Shibuya." This data is sent to the server via the device. The input is the event information entered by the user, and the output is the event information sent to the server.

[0130] Step 2:

[0131] The server uses a generative AI to generate a list of suitable stores based on the collected event information. The input includes the event information and a generative AI model. The generative AI analyzes this information and creates a list of candidate stores. The output is the generated store list.

[0132] Step 3:

[0133] The server sends the generated store list to the LINE group, and the user selects the desired store from the proposed list. The input includes the generated store list. The server sends this list and waits for a reply from the user. The output is the user's selection information.

[0134] Step 4:

[0135] When the user selects a store, the server automatically makes a reservation at the selected store. The input includes the user's selection information and store information. The server processes the reservation based on this and completes the reservation. The output is a notification that the reservation is complete.

[0136] Payment and split payment processing steps

[0137] Step 1:

[0138] When the drinking party ends, the billing information from the bar is sent to the server. The input includes the billing information. The server stores it in a database. The output is the stored billing information.

[0139] Step 2:

[0140] The server calculates the total amount based on the accounting information and splits the bill among the participants. The input includes the saved accounting information and the list of participants. The server performs calculations based on this information and calculates the split amount. The output is the calculated split amount.

[0141] Step 3:

[0142] The server notifies the LINE group of the calculation result and conveys payment details to each user. The input includes the calculated split amount. The server generates this as a notification message and sends it to the group. The output is the payment notification sent.

[0143] Step 4:

[0144] The user receives a notification on the LINE app and makes a payment using a payment app such as PayPay. The input includes the notified payment details. The user proceeds with the payment process according to this, and the payment data is transferred to the server by the device. The output is the payment data sent to the server.

[0145] Step 5:

[0146] The server verifies the payment data and notifies each user that the payment has been completed. The input includes payment data. The server verifies this, generates a payment completion notification, and sends it. The output is the payment completion notification that was sent. Specifically, the confirmation operation is performed using the payment confirmation function.

[0147] In this way, detailed data processing and data calculations are performed at each processing step, making the management of a series of events more efficient for the entire system.

[0148] (Application example 1)

[0149] 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."

[0150] Conventional event management systems involve complicated processes such as coordinating schedules among participants, selecting restaurants, managing accounting information, and making payments, placing a heavy burden on event organizers in particular. Furthermore, sufficient measures are often not implemented to ensure the safe handling of participants' personal information and accounting information. This makes it difficult for all participants to enjoy the event with peace of mind. There is a need for a system that can solve these issues and provide efficient and safe event management.

[0151] 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.

[0152] In this invention, the server includes: means for coordinating event schedules among multiple participants via a communications network; a generating artificial intelligence (AI) means for collecting schedule information from the participants and proposing optimal schedules; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing event locations via the communications network; means for automatically making reservations at locations selected from the proposed locations; means for collecting accounting information for the event and automatically splitting the bill among participants; means for completing payments among participants in cooperation with a payment application based on the accounting information; and means for encrypting and storing participant data and using secure communications when accessing the data. This significantly reduces the burden on the organizer and allows all participants to enjoy the event with peace of mind.

[0153] A "communications network" is an infrastructure for exchanging data between multiple terminals, and includes the Internet and local area networks.

[0154] "Participants" refers to multiple users who participate in an event.

[0155] "Date scheduling" refers to the process of surveying and arranging participants' availability to determine the best date and time for an event.

[0156] "Generative artificial intelligence (AI)" is a technology that uses machine learning or data analysis techniques to derive optimal solutions based on large amounts of data.

[0157] A "reminder" is an automatic notification message sent to participants who have not yet responded to encourage them to respond.

[0158] "Venue" means the physical location or facilities used for the actual conduct of an Event.

[0159] A "reservation" is a procedure for reserving a specific location at a specific date and time.

[0160] "Accounting information" is data that records all expenses related to the event.

[0161] "Bill-splitting" is the process of dividing the total cost equally among the participants.

[0162] A "payment application" is software that enables online payments.

[0163] "Encryption" is a process that transforms data using a specific algorithm to prevent it from being deciphered by third parties.

[0164] "Secure communications" refers to communications protocols that use technology to prevent unauthorized access and tampering when sending and receiving data.

[0165] The present invention relates to a system for managing events efficiently and securely over a communications network. This system provides a series of functions, including scheduling, restaurant selection, and payment, and securely manages participant data.

[0166] Hardware and software used

[0167] Server: Collects, analyzes, suggests, and encrypts data.

[0168] Terminal: The device through which a user enters data (e.g., smartphone, tablet, PC).

[0169] Generative AI model: Used for scheduling and restaurant selection.

[0170] LINE API: Used as a communication application.

[0171] PayPay API: Provides payment functions.

[0172] Encryption technology: used to protect participant data (e.g., AES encryption).

[0173] Program processing overview

[0174] The server receives information entered by the user, such as dates, budget, preferences, and location, and encrypts and stores it in a database. Based on this data, a generative AI model is used to generate a list of optimal dates and restaurants, which are then proposed to participants. Reminders are also automatically sent to participants who have not yet responded using the LINE API. Event reservations are automatically made at the restaurant selected by the user from the proposed restaurant list.

[0175] After the drinking party ends, the server receives the bill from the bar and automatically splits the bill based on this information. The calculation results are notified to all participants using the LINE API, and payment is made safely and quickly via the PayPay API. All data access uses encryption technology and secure communication protocols to prevent unauthorized access and data leaks.

[0176] Specific examples

[0177] For example, if the event date is set for "2023-04-01," the server will suggest "Japanese restaurants X, Y, and Z in Shibuya" based on the participants' preferences. All of this information is encrypted and securely stored. Reservations at "restaurant Y" are automatically made based on the participants' selections. Furthermore, the total bill of 15,000 yen after the drinking party is split among five people, with payment notifications sent to each person via LINE. Each person can pay securely using PayPay.

[0178] Prompt Sentence Examples

[0179] The following data is input into the generative AI model to generate a list of optimal dates and restaurants:

[0180] {

[0181] "group_id": "sample_group_id",

[0182] "availability": {"userA": "2023-04-01", "userB": "2023-04-02"},

[0183] "preferences": {

[0184] "date": "2023-04-01",

[0185] "budget": 5000,

[0186] "cuisine": "Japanese food",

[0187] "location": "Shibuya"

[0188] }

[0189] }

[0190] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0191] Step 1:

[0192] The server receives the schedule information entered by the user through the LINE API. It collects each user's free schedule data and sends it to the server via a secure method. The input is the user's schedule information, and the server stores the information in a database based on this.

[0193] Step 2:

[0194] The server uses a generative AI model to analyze the optimal schedule based on the collected schedule information. This analysis results in a proposal for a schedule that allows the most participants to participate conveniently. The input is each user's schedule data, and the generative AI model analyzes the data and outputs the optimal schedule.

[0195] Step 3:

[0196] The server notifies all participants of the optimal schedule obtained as a result of the analysis using the LINE API. It also automatically sends reminder notifications to users who have not yet responded. The input is the optimal schedule output from the generative AI model, and this is notified using the LINE API.

[0197] Step 4:

[0198] Users enter information such as the date, budget, preferences, and location of the event on the LINE application. The device collects this data and sends it to the server using encryption technology. The input is the user's event details, and the output is encrypted data.

[0199] Step 5:

[0200] The server analyzes the encrypted data and uses a generative AI model to generate a list of suitable venues (e.g., restaurants), which it then recommends to the user. The input is the encrypted event details, and the server outputs a list of suggested venues based on the analysis by the generative AI model.

[0201] Step 6:

[0202] Participants select from the proposed locations, and the server automatically makes a reservation for the selected location. The input is the user's selection, and the output is a reservation completion notification.

[0203] Step 7:

[0204] After the drinking party, the bar sends the billing information to the server. The server collects this information and automatically splits the bill among the participants. The input is the billing information from the bar, and the output is the split amount for each participant.

[0205] Step 8:

[0206] The server notifies the participants of the split calculation results using the LINE API. Participants receive the notification on their own devices and make payments accordingly. The input is the split calculation result, and the output is the notification to each participant.

[0207] Step 9:

[0208] After receiving the notification, the participant makes the payment using the PayPay API. The payment data is sent from the terminal to the server, and the server confirms the completion of the payment. The input is the payment data from the participant, and the output is a payment completion notification.

[0209] Step 10:

[0210] The server stores all data using encryption technology and uses secure communication protocols such as SSH when accessing data, preventing unauthorized access and data leakage. The input is all processed data, and the output is encrypted data storage.

[0211] 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.

[0212] This invention is a system that uses communication applications to support the organizer of events, especially drinking parties, and utilizes generative AI and an emotion engine to arrange dates, select restaurants, and make payments. This system recognizes the emotions of participants and makes optimal suggestions based on them, thereby increasing user satisfaction.

[0213] 1. Schedule adjustment function

[0214] The server has the function of sending a questionnaire for scheduling an event to LINE groups and other communication groups. Each participant answers the questionnaire to indicate their available dates. This response data is sent to the server via their device. The server collects this data and proposes the optimal date. In addition, the server automatically sends reminder notifications to users who have not yet responded.

[0215] For example, when User A enters and submits their free schedule, the information is transferred to the server via their device. The server then uses the generation AI to analyze this information and propose optimal dates to the LINE group. At the same time, reminders are sent to users who have not yet responded, ensuring that everyone has responded.

[0216] 2. Store selection function

[0217] Users enter information such as the date, budget, food preferences, and location of the event on the LINE application. This information is sent to the server via the device. The server uses generative AI to generate a list of appropriate restaurants based on this information. It also uses an emotion engine to recognize the user's emotions from text messages and voice input, and customizes suggestions based on that emotional information.

[0218] For example, if User B enters "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server will use the generation AI to suggest "Restaurant A, Restaurant B, Restaurant C" based on this data. At the same time, if the emotion engine recognizes emotions such as "looking happy" or "delighted" from the user's past messages and voice input, it will prioritize suggesting particularly popular restaurants or restaurants with good reviews. If User B selects "Restaurant B," the server will automatically make a reservation at Restaurant B based on this information.

[0219] 3. Payment and splitting features

[0220] After the drinking party is over, the bill information from the bar is sent to the server. This bill information is saved in a database, and the server calculates the total amount divided by the number of people. The calculation result is notified to the LINE group, and payment details are communicated to each user.

[0221] User C receives a notification on the LINE app and makes a payment using a payment application such as PayPay. This payment data is transferred by the device to the server, which then confirms that the payment has been completed. The emotion engine can analyze the user's emotions after payment and collect feedback for improvement if satisfaction is low.

[0222] Specific examples

[0223] For example, if the date of a drinking party is decided to be "April 1st," the server uses a generation AI to suggest "Store X, Store Y, and Store Z" from among Japanese restaurants in Shibuya. The emotion engine recognizes that User D said in a past message that he "likes restaurants with a nice atmosphere," and prioritizes "Store Y," which has a particularly good atmosphere, on the list. User D selects "Store Y," and the reservation is completed. After the drinking party, a total of 15,000 yen is registered on the server, and the bill is split among five people, at 3,000 yen each. The server sends a notification to the LINE group that "3,000 yen per person," and each user pays 3,000 yen with PayPay. The emotion engine analyzes subsequent messages and determines whether the user is satisfied.

[0224] In this way, event organizers can utilize the emotion engine to efficiently manage events while increasing participant satisfaction.

[0225] The processing flow will be explained below.

[0226] 1. Schedule adjustment function

[0227] Step 1: Send the survey

[0228] Server: Create and send a schedule adjustment survey to all participants in the LINE group.

[0229] Device: The survey form is displayed to the user on the LINE app.

[0230] Step 2: Collect responses

[0231] User: Enter your available dates in the survey form and tap the submit button.

[0232] Terminal: Transfers user input to the server.

[0233] Server: Saves the collected response data of each user in a database.

[0234] Step 3: Propose the best schedule

[0235] Server: Based on the collected data, the optimal schedule is calculated using a generative AI.

[0236] Server: Sends the calculation results to the LINE group as a proposal.

[0237] Terminal: Notifies the user of the suggested optimal schedule.

[0238] Step 4: Send a reminder

[0239] Server: Lists participants who have not responded and automatically sends reminder messages.

[0240] Terminal: Display a prompt message to the user.

[0241] 2. Store selection function

[0242] Step 1: Enter your information

[0243] User: Enter necessary information such as dates, budget, food preferences, and location on the LINE app.

[0244] Terminal: Transfers the entered information to the server.

[0245] Step 2: Sentiment Analysis

[0246] Server: Uses an emotion engine to recognize the user's emotions from the input message and voice data.

[0247] Server: Adjusts the content of suggestions based on the recognized emotion data.

[0248] Step 3: Generate a list of stores

[0249] Server: Uses generative AI to create a list of relevant businesses based on input information and sentiment data.

[0250] Server: Send the created list to the LINE group.

[0251] Terminal: Shows the user a list of stores.

[0252] Step 4: Confirm your reservation

[0253] User: Select the desired store from the list of suggested stores.

[0254] Terminal: Transfers the selection results to the server.

[0255] Server: Automatically executes the reservation procedure for the selected restaurant.

[0256] 3. Payment and splitting features

[0257] Step 1: Collect your billing information

[0258] Server: Receives billing information from the restaurant on the day of the drinking party.

[0259] Server: Stores the collected accounting information in a database.

[0260] Step 2: Split the bill

[0261] Server: Calculate the total amount divided by the number of people.

[0262] Server: Notify the LINE group of the calculation results.

[0263] Terminal: Display a notification of the split amount to the user.

[0264] Step 3: Checkout

[0265] User: Checks the notification and pays his / her share using the payment application.

[0266] Terminal: Transfers payment data to the server.

[0267] Server: Works with the payment application to verify payments from each user.

[0268] Step 4: Feedback after sentiment analysis

[0269] Server: Analyzes the user's messages and behavior after payment using an emotion engine.

[0270] Server: If satisfaction is low, collect feedback to help improve the system.

[0271] For example, if User D previously messaged, "I like places with a good atmosphere," the emotion engine would recognize this, and the generation AI would prioritize those establishments in the list. Similarly, if User D messaged after a drinking party saying, "It was fun," the emotion engine would analyze this, and the server would evaluate the high level of satisfaction. In this way, the emotion engine can be used to increase participant satisfaction.

[0272] Example 2

[0273] 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."

[0274] Traditional event planning tasks require a great deal of time and effort, including coordinating schedules for multiple participants, choosing restaurants, and handling payments, placing a heavy burden on event organizers. Furthermore, because it is not possible to make optimal proposals that take into account the feelings of participants, user satisfaction often declines. In particular, the complicated process of following up with non-respondents and processing payments is problematic.

[0275] The specific processing by the specific 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 coordinating the event schedule among multiple participants via a communications network; a generative artificial intelligence (AI) means for collecting schedule information of the participants and proposing an optimal schedule; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing a venue for the event via the communications network; means for automatically making a reservation at a venue selected from the proposed venues; means for collecting accounting information for the event and automatically splitting the bill among participants; means for completing payment among participants in cooperation with a payment application based on the accounting information; and an emotion engine means for recognizing participants' emotions and customizing the proposal content based on the emotion information. This makes it possible to improve the efficiency of event organizer work and significantly improve participant satisfaction.

[0276] A "communications network" is an infrastructure for sending and receiving data between multiple devices and computers, such as the Internet or a mobile phone network.

[0277] "Participant" means any person who intends to participate in an Event.

[0278] "Date Information" is availability information provided by participants regarding the date and time of the event.

[0279] A "generative artificial intelligence (AI) means" is a system that uses artificial intelligence technology to generate optimal proposals based on data collected from participants.

[0280] A "reminder notification" is a notification that is automatically sent to participants who have not yet responded, encouraging them to respond.

[0281] "Location" means the geographic location or facility where the Event actually takes place.

[0282] "Reservation" is a procedure that participants take in advance to secure the venue of their choice.

[0283] "Accounting information" refers to information regarding all expenses incurred after the event has ended.

[0284] "Split the bill" is a process of calculating the amount each participant should pay based on accounting information.

[0285] "Payment Application" means software that enables Participants to complete payments electronically.

[0286] An "emotion engine" is a software technology that recognizes a user's emotions and optimizes the content of suggestions based on those emotions.

[0287] This invention is a system that automates the event planning process via a communications network. The system utilizes a generative AI model and an emotion engine to efficiently coordinate schedules, select restaurants, and make payments. An example implementation of this system is described in detail below.

[0288] Schedule adjustment function

[0289] server:

[0290] The server sends a schedule-setting questionnaire to multiple participants. This questionnaire is sent via a communication network (e.g., the Internet or a mobile phone network). Each participant responds with their availability, and this information is sent to the server via their device. The server uses a generative AI model based on the collected schedule information to propose the optimal schedule. It also automatically sends reminder notifications to participants who have not responded.

[0291] (Example)

[0292] If User A answers "March 15th," this date information is sent to the server via the device. The server collects all responses and calculates the optimal date using a generative AI model. For example, if "March 20th" is determined to be optimal, the server will suggest that date to the LINE group. A reminder notification will be automatically sent to users who have not yet responded.

[0293] Shop selection function

[0294] User:

[0295] Users input requirements such as event dates, budget, food preferences, and location via a communication application (e.g., LINE). The input information is sent to the server via the terminal.

[0296] server:

[0297] The server uses a generative AI model based on the requirements information it receives to generate a list of suitable restaurants. It then uses an emotion engine to recognize the user's emotions and customizes the suggestions based on those emotions. For example, if the user indicates emotions such as "fun" or "happy" from past messages or voice input, restaurants with particularly good reputations or high reviews will be ranked high on the suggestion list.

[0298] (Example)

[0299] When User B enters "budget 5,000 yen, Japanese food, Shibuya," this information is sent from the device to the server. The server uses a generative AI model to suggest "Store A, Store B, Store C." At the same time, the emotion engine analyzes the user's emotions, and if it recognizes that the restaurant "looks fun," it prioritizes suggestions of restaurants with particularly good reviews.

[0300] Payment and split payment function

[0301] server:

[0302] After the event is over, the restaurant sends the billing information to the server. This billing information is stored in a database, and the server calculates the total amount divided by the number of people. The server then notifies each participant of the split amount via a communication application.

[0303] User:

[0304] The user receives a notification and makes a payment through an electronic payment application (e.g., PayPay). The payment information is sent from the terminal to the server, and the server confirms that the payment has been completed. The emotion engine analyzes the user's emotions after payment and collects feedback if the user is not satisfied.

[0305] (Example)

[0306] After the drinking party ends, the total bill of 15,000 yen is registered on the server. Based on this, the server calculates the amount per person to be 3,000 yen when divided among five people and notifies each user. When User C pays 3,000 yen with PayPay, this information is sent to the server and the payment is completed. The server uses an emotion engine to analyze messages such as "It was fun" and "I was satisfied" and confirm the user's level of satisfaction.

[0307] Prompt Sentence Examples

[0308] "We are organizing an upcoming event. To make our work more efficient, we would like to develop a system that utilizes generative AI models and an emotion engine. This system has the following requirements:

[0309] Use a communication application to coordinate schedules.

[0310] Choose a restaurant based on your budget, food preferences, and location.

[0311] The system automatically calculates the split and notifies you.

[0312] Maximize user satisfaction using an emotion engine.

[0313] In this way, the invention improves the efficiency of organizing tasks and participant satisfaction.

[0314] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0315] System processing steps

[0316] Step 1:

[0317] Create and send a scheduling survey

[0318] server:

[0319] The server automatically generates a survey for scheduling an event using the LINE API and sends it to the LINE group. The survey includes options for dates that users can select.

[0320] input:

[0321] Possible date for the event

[0322] output:

[0323] A scheduling survey sent to users

[0324] Specific behavior:

[0325] The server generates a survey that asks users to "choose a convenient date between March and April" and sends it via the LINE API.

[0326] Step 2:

[0327] Collection of responses to schedule adjustment questionnaires and proposals

[0328] User:

[0329] Each participant answers the questionnaire they received, which includes the user's free days.

[0330] input:

[0331] User's available schedule

[0332] output:

[0333] Response data sent to the server

[0334] Specific behavior:

[0335] User A enters his free date as "March 15th" and presses the send button. The information is transferred from the device to the server.

[0336] server:

[0337] The system collects response data sent via devices and uses a generative AI model to suggest optimal dates, while also sending reminder notifications to users who have not yet responded.

[0338] input:

[0339] Response data for each participant

[0340] output:

[0341] Optimal schedule suggestions and reminder notifications

[0342] Specific behavior:

[0343] If the server determines that March 20th is the best date based on the response data collected, it will notify the LINE group of the result. Users who have not yet responded will receive a reminder to respond.

[0344] Step 3:

[0345] Enter information to select a restaurant

[0346] User:

[0347] Use the LINE application to enter and submit requirements such as the event date, budget, food preferences, and location.

[0348] input:

[0349] Requirements such as dates, budget, food preferences, location, etc.

[0350] output:

[0351] Requirement data sent to the server

[0352] Specific behavior:

[0353] User B enters "March 20th, budget 5000 yen, Japanese food, Shibuya" and presses the send button. This information is sent from the device to the server.

[0354] Step 4:

[0355] Restaurant list generation and suggestions

[0356] server:

[0357] Based on the submitted requirements, a generative AI model is used to generate an appropriate restaurant list, while an emotion engine is used to analyze the user's emotions and customize the recommendations.

[0358] input:

[0359] Requirement Data

[0360] output:

[0361] Suggested restaurant list

[0362] Specific behavior:

[0363] Based on the requirements of "budget 5,000 yen, Japanese food, Shibuya," the server generates a list of "Store A, Store B, Store C" and suggests them to the LINE group. At the same time, the emotion engine recognizes the user's emotion of "looks fun" and places particularly popular stores at the top of the list.

[0364] Step 5:

[0365] Restaurant selection and reservations

[0366] User:

[0367] Select the appropriate restaurant from the list of suggested restaurants.

[0368] input:

[0369] User Selection

[0370] output:

[0371] Selection data sent to the server

[0372] Specific behavior:

[0373] User B selects "Store B" and sends the information to the server.

[0374] server:

[0375] Based on the user's selection, reservations are automatically made at selected stores.

[0376] input:

[0377] Selected Data

[0378] output:

[0379] Reservation confirmation

[0380] Specific behavior:

[0381] The server connects to Store B's reservation system and automatically confirms the reservation.

[0382] Step 6:

[0383] Registering accounting information and splitting the bill

[0384] server:

[0385] After the event, the restaurant sends accounting information, which is then stored in a database and split according to the number of participants.

[0386] input:

[0387] Accounting Information

[0388] output:

[0389] Split amount

[0390] Specific behavior:

[0391] The restaurant sends billing information totaling 15,000 yen, and the server saves this data in a database. Dividing this by five people results in 3,000 yen per person, so the server notifies the LINE group of the result.

[0392] Step 7:

[0393] Payment and feedback collection

[0394] User:

[0395] Receive notification of the split amount and make payment using your electronic payment application.

[0396] input:

[0397] Split amount notification

[0398] output:

[0399] Payment completion notification

[0400] Specific behavior:

[0401] User C receives the LINE notification and pays 3,000 yen using an electronic payment application. This payment data is sent from the device to the server.

[0402] server:

[0403] It confirms that the payment has been completed and uses a sentiment engine to analyze the user's sentiment and collect feedback.

[0404] input:

[0405] Payment completion notification

[0406] output:

[0407] Sentiment analysis results, feedback data

[0408] Specific behavior:

[0409] The server checks the payment data, and then analyzes the user's messages of "enjoyment" and "satisfaction" using an emotion engine. If the satisfaction level is low, feedback is collected and used to improve the system.

[0410] (Application example 2)

[0411] 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."

[0412] This invention relates to a system that efficiently supports the organizer's work for events, especially drinking parties, and increases participant satisfaction. Conventional methods place a heavy burden on the organizer, as scheduling, restaurant selection, and accounting are time-consuming tasks. Furthermore, it is not possible to make proposals that take into account the feelings of participants, making it difficult to hold an event that satisfies everyone. Furthermore, collecting feedback after an event is done manually, which makes it difficult to improve the system for the next event.

[0413] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for coordinating event schedules among multiple participants via a communications network; a generative artificial intelligence (AI) means for collecting participant schedule information and proposing optimal schedules; a means for automatically sending reminder notifications to participants who have not yet responded; a means for proposing event locations via a communications network; a means for automatically making reservations at locations selected from among the proposed locations; an emotion engine means for recognizing participant emotions from text messages or voice input and customizing the proposal based on the emotion information; a means for automatically making reservations at locations selected by participants on a smartphone application; a means for collecting event accounting information and automatically splitting the bill among participants; a means for completing payment among participants in cooperation with a payment application based on the accounting information; and a feedback means for reanalyzing participant emotions after the event and reflecting them in the next proposal. This improves the efficiency of event organizer tasks and enables events that increase the satisfaction of all participants.

[0414] A "communications network" is an infrastructure for transmitting and receiving data, including the Internet and local area networks (LANs).

[0415] "Participant" refers to an individual who attends an event or drinking party.

[0416] "Scheduling" refers to the task of coordinating schedules among multiple participants.

[0417] "Date information" refers to a list of participants' available dates and times.

[0418] "Generative artificial intelligence (AI)" is a system that uses machine learning and natural language processing to analyze data and generate optimal suggestions.

[0419] "Reminder" means a reminder message that is automatically sent to participants who have not responded.

[0420] The "venue" refers to the specific location where the event or drinking party will be held.

[0421] "Automatic booking" refers to the process by which the system automatically makes a booking based on user input.

[0422] An "emotion engine" is a system that analyzes a user's emotions from text messages and voice input, and customizes suggestions based on that information.

[0423] A "smartphone application" is a software program that runs on a smartphone.

[0424] "Accounting information" refers to data on the total amount of an event or drinking party and the amount paid by each participant.

[0425] "Splitting the bill" is the process of calculating the amount each participant will pay based on accounting information.

[0426] A "payment application" is application software for electronically transferring money.

[0427] "Feedback" refers to evaluations and impressions collected from participants after the event.

[0428] This invention is a system for improving the efficiency of event organizer work and increasing participant satisfaction. This system coordinates event schedules, restaurant selection, and accounting among multiple participants via a communications network, and further customizes proposals using an emotion engine to achieve optimal event management that takes participants' emotions into consideration.

[0429] Schedule adjustment

[0430] The server coordinates event dates among participants through a communication application. Specifically, it sends a schedule coordination survey to LINE groups and other messaging groups. Each participant responds to the survey about their available dates, and the information is sent to the server via their device. The server collects the data and suggests optimal dates using generative artificial intelligence (AI) methods. It also automatically sends reminder notifications to participants who have not yet responded.

[0431] Choosing a restaurant

[0432] The server accepts input from participants to suggest locations for the event. Participants enter information such as the event date, budget, food preferences, and location on a communication application. This information is sent to the server via their terminal, and the server uses generative AI to generate a list of appropriate restaurants. Furthermore, it can use an emotion engine means to recognize participants' emotions from text messages and voice inputs and customize the suggestions based on that emotion information. The server also automatically makes reservations at locations selected by the user.

[0433] Accounting and settlement

[0434] After the drinking party is over, the bill information from the bar is sent to the server. This bill information is saved in a database, and the server automatically splits the bill among the participants based on the total amount. The calculation result is notified to the participants via a communication application, and each participant makes payment using a payment application (e.g., an electronic payment application). This payment data is also transferred to the server via the terminal, and the server confirms that the payment has been completed.

[0435] Sentiment Analysis and Feedback

[0436] After the event, the server reanalyzes the participants' emotions and provides feedback to reflect the results in proposals for the next event. Specifically, by using the emotion engine described above again and analyzing the participants' messages and feedback data, it is possible to identify areas for improvement for the next event.

[0437] Examples of concrete examples and prompts

[0438] Specific examples

[0439] 1. Scheduling:

[0440] Send a survey in a group chat asking, "Which of the following days are you free: March 15th, 22nd, or 29th?"

[0441] Send a reminder to those who haven't responded: "If you haven't responded yet, hurry up and respond!"

[0442] 2. Choosing a restaurant:

[0443] The participant enters "March 22nd, budget 5,000 yen, yakiniku, Shinjuku."

[0444] The server uses a generative AI to suggest "Store A, Store B, Store C," and "Store B" is given priority based on the results of sentiment analysis.

[0445] The user selects "Store B" and the reservation is made automatically.

[0446] 3. Accounting:

[0447] After the drinking party, the total amount of 20,000 yen will be divided among the four people, with each person receiving 5,000 yen.

[0448] Each participant pays 5,000 yen using an electronic payment application, and the server confirms that the payment has been completed.

[0449] Prompt Sentence Examples

[0450] Scheduling prompt:

[0451] "When would be a good date for a drinking party?" "March 15th," "March 22nd," "March 29th"

[0452] Shop selection prompt:

[0453] "What's your budget?" "What are your food preferences?" "Where is it?" "Japanese food," "Yakiniku," "Chinese food"

[0454] Payment prompt:

[0455] "Today's bill is 5,000 yen per person. Please pay using the electronic payment application."

[0456] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0457] Step 1:

[0458] (Send schedule adjustment survey)

[0459] The user initiates a schedule adjustment survey on a communication application. At this time, the user inputs candidate dates and sends the candidate date data to the server. The server receives this data and sends the survey message to LINE groups and other messaging groups.

[0460] Input: Candidate dates specified by the user (e.g. March 15th, 22nd, 29th)

[0461] Data processing: The server converts the candidate date data into a message format

[0462] Output: Survey message sent to each participant

[0463] Step 2:

[0464] (Collecting schedule information)

[0465] Each participant clicks on the link in the survey message to answer their free dates. The answer data is sent to the server via their device. The server aggregates this data and stores each participant's free dates in a database.

[0466] Input: Available dates for participants to answer (e.g. March 15th, 22nd)

[0467] Data processing: The server aggregates and integrates individual response data

[0468] Output: Free schedule information of participants stored in the database

[0469] Step 3:

[0470] (Optimal schedule suggestions)

[0471] The server analyzes the collected schedule information using artificial intelligence (AI) to propose the optimal schedule. This AI selects the date that the most participants can attend based on the available dates of all participants.

[0472] Input: Attendee schedule information stored in the database

[0473] Data Calculation: Generative AI for Optimal Schedule Analysis

[0474] Output: Optimal date suggestion (e.g. March 22nd)

[0475] Step 4:

[0476] (Send reminder notifications)

[0477] The server identifies participants who have not responded and automatically sends reminders via LINE groups or other messaging groups.

[0478] Input: Answer status (Answered / Not answered)

[0479] Data processing: Generate reminder notifications based on response status

[0480] Output: Reminder notification message

[0481] Step 5:

[0482] (Suggestions for choosing a restaurant)

[0483] Users input details of the event (budget, food preferences, location, etc.) into the communication application. This information is sent via the device to the server, which then uses generative AI to generate a list of suitable restaurants.

[0484] Input: Event details (e.g., budget 5,000 yen, Yakiniku, Shinjuku)

[0485] Data calculation: Generative AI generates appropriate store lists

[0486] Output: Suggested store list (e.g., Store A, Store B, Store C)

[0487] Step 6:

[0488] (Analysis of emotional information)

[0489] The server uses an emotion engine means to recognize emotion information from the participant's text messages and voice inputs and customizes the suggestions based on the emotion information, for example, analyzing emotions such as "happy" and "delighted."

[0490] Input: Text messages and voice input data

[0491] Data Computation: Emotion Analysis with Emotion Engine

[0492] Output: Customized suggestions

[0493] Step 7:

[0494] (Automatic reservation)

[0495] When the user confirms the restaurant they selected from the list of suggested restaurants, the server automatically makes a reservation for that restaurant. The reservation information is sent to the terminal and a confirmation message is displayed to the user.

[0496] Input: User selected store

[0497] Data processing: Automatic reservation information generation

[0498] Output: Reservation confirmation message

[0499] Step 8:

[0500] (Collection of accounting information)

[0501] After the drinking party is over, the billing information is sent from the bar to the server, which stores this information in a database.

[0502] Input: Accounting information sent from the store (e.g. total amount 20,000 yen)

[0503] Data processing: Saving accounting information

[0504] Output: Accounting information stored in a database

[0505] Step 9:

[0506] (Split the bill)

[0507] The server automatically splits the bill among the participants based on the received accounting information, and the results are communicated via a communication application.

[0508] Input: Accounting information stored in the database

[0509] Data calculation: Calculating the payment amount for each participant

[0510] Output: Notification of split amount (e.g. 5000 yen per person)

[0511] Step 10:

[0512] (Electronic Payment)

[0513] Each participant pays the notified split amount using the electronic payment application. Data indicating the completion of the payment is transferred to the server via the terminal, and the server confirms that the payment has been completed.

[0514] Input: Payment data by each participant

[0515] Data processing: Payment completion status update

[0516] Output: Payment confirmation message

[0517] Step 11:

[0518] (Feedback collection and analysis)

[0519] After the event, the server reanalyzes the participants' emotions and collects feedback to be reflected in proposals for the next event.The emotion engine is used to analyze the participants' messages and feedback data to extract satisfaction levels and areas for improvement.

[0520] Input: Feedback data from participants

[0521] Data Calculation: Reanalysis by Emotion Engine

[0522] Output: Feedback data to be reflected in the next proposal

[0523] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0524] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0525] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0526] [Second embodiment]

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

[0528] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0529] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0530] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0531] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0532] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0533] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0534] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0535] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0536] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0537] In the smart glasses 214, the 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.

[0538] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0539] The present invention relates to a drinking party organizer support system that uses a communication application. This system uses a generation AI to provide comprehensive support for scheduling, restaurant selection, and payment. Specific embodiments of the system are described below.

[0540] 1. Schedule adjustment function

[0541] The server has the function of sending a questionnaire for scheduling an event to LINE groups and other communication groups. Each participant answers the questionnaire to indicate their available dates. This response data is sent to the server via the terminal. The server collects this data and proposes the optimal schedule.

[0542] When User A enters and submits their free schedule, the device immediately transfers this information to the server. The server uses a generation AI to analyze the collected schedule information and sends the optimal schedule as a proposal to the LINE group. After that, the server automatically sends reminder notifications to users who have not yet responded.

[0543] 2. Store selection function

[0544] Users enter information such as the date, budget, food preferences, and location of the event on the LINE application. This information is sent to the server via the device. The server uses AI to generate a list of suitable restaurants based on this information and sends it to the LINE group.

[0545] For example, if User B enters "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server will search for Japanese restaurants in Shibuya based on this data and use generation AI to suggest "Restaurant A, Restaurant B, Restaurant C." If User B selects "Restaurant B" from the list, the server will automatically send an instruction to make a reservation at Restaurant B.

[0546] 3. Payment and splitting features

[0547] After the drinking party is over, the billing information from the bar is sent to the server. This information is stored in a database, and the server tallies the total amount and calculates the split between the participants. The calculation result is notified to the LINE group, and payment details are communicated to each user.

[0548] User C receives a notification on the LINE app and makes a payment using a payment application such as PayPay. This payment data is transferred by the device to the server, and the server confirms that the payment has been completed.

[0549] Specific examples

[0550] For example, the date of a drinking party is decided to be "April 1st," and the server uses a generation AI to suggest "Store X, Store Y, Store Z" from among Japanese restaurants in Shibuya. User D selects "Store Y" and the reservation is completed. After the drinking party, a total of 15,000 yen is registered on the server, and the bill is split among five people, at 3,000 yen each. The server sends a notification to the LINE group that "3,000 yen per person," and each user pays 3,000 yen with PayPay.

[0551] This allows event organizers to efficiently and smoothly manage a series of tasks, from scheduling to choosing restaurants and paying the bill. The introduction of this system significantly reduces the burden on event organizers and allows participants to enjoy the event comfortably.

[0552] The processing flow will be explained below.

[0553] 1. Schedule adjustment function

[0554] Step 1: Send the survey

[0555] Server: Create and send a schedule adjustment survey to all participants in the LINE group.

[0556] Device: The survey form is displayed to the user on the LINE app.

[0557] Step 2: Collect responses

[0558] User: Enter your available dates in the survey form and tap the submit button.

[0559] Terminal: Transfers user input to the server.

[0560] Server: Saves the collected response data of each user in a database.

[0561] Step 3: Propose the best schedule

[0562] Server: Based on the collected data, the optimal schedule is calculated using a generative AI.

[0563] Server: Sends the calculation results to the LINE group as a proposal.

[0564] Terminal: Notifies the user of the suggested optimal schedule.

[0565] Step 4: Send a reminder

[0566] Server: Lists participants who have not responded and automatically sends reminder messages.

[0567] Terminal: Display a prompt message to the user.

[0568] 2. Store selection function

[0569] Step 1: Enter your information

[0570] User: Enter necessary information such as dates, budget, food preferences, and location on the LINE app.

[0571] Terminal: Transfers the entered information to the server.

[0572] Step 2: Generate a list of stores

[0573] Server: Uses generative AI to create a list of appropriate stores based on the input information.

[0574] Server: Send the created list to the LINE group.

[0575] Terminal: Shows the user a list of stores.

[0576] Step 3: Confirm your reservation

[0577] User: Select the desired store from the list of suggested stores.

[0578] Terminal: Transfers the selection results to the server.

[0579] Server: Automatically executes the reservation procedure for the selected restaurant.

[0580] 3. Payment and splitting features

[0581] Step 1: Collect your billing information

[0582] Server: Receives billing information from the restaurant on the day of the drinking party.

[0583] Server: Stores the collected accounting information in a database.

[0584] Step 2: Split the bill

[0585] Server: Calculate the total amount divided by the number of people.

[0586] Server: Notify the LINE group of the calculation results.

[0587] Terminal: Display a notification of the split amount to the user.

[0588] Step 3: Checkout

[0589] User: Checks the notification and pays his / her share using the payment application.

[0590] Terminal: Transfers payment data to the server.

[0591] Server: Works with the payment application to verify payments from each user.

[0592] This allows the organizer to efficiently and smoothly carry out the entire process of the drinking party, from preparation to its end.

[0593] Example 1

[0594] 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."

[0595] With conventional event management systems, a series of tasks such as scheduling, selecting restaurants, splitting the bill, and settling the payment required a lot of time and effort, placing a heavy burden on the organizer. Furthermore, communication between participants was sometimes not smooth, which could lead to delays in planning and execution of the event.

[0596] 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.

[0597] In this invention, the server includes: means for coordinating event dates among multiple participants via a communications network; a generating artificial intelligence (AI) means for collecting schedule information from the participants and proposing the optimal schedule; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing event locations via the communications network; means for automatically making reservations at locations selected from the proposed locations; means for collecting accounting information for the event and automatically splitting the bill among participants; and means for completing payment among participants in cooperation with a payment application based on the accounting information. This automates the entire process from scheduling to restaurant selection, accounting, and payment, significantly reducing the burden on event organizers and enabling smoother event planning and execution.

[0598] A "communications network" refers to a network that allows computers and terminals to exchange information with each other. This includes the Internet and local area networks (LANs).

[0599] "Participant" means any person or group who intends to attend the Event and who is involved in scheduling and selecting the location of the Event.

[0600] "Generative artificial intelligence (AI)" refers to a technology that analyzes large amounts of data, finds patterns, and supports decision-making. In this invention, it plays a role in suggesting optimal dates and restaurant options.

[0601] A "reminder" is a warning message that alerts users to take a specific action, such as a notification to remind unanswered participants to reschedule.

[0602] "Event location" refers to the physical or virtual location where the event takes place, such as a restaurant, conference room, or online meeting platform.

[0603] "Financial Information" means detailed information about costs and expenses related to an Event, including data necessary to calculate totals and split bills at restaurants.

[0604] "Payment application" means software that enables users to make or receive payments online or through a mobile device. Examples include e-wallet apps and mobile banking apps.

[0605] This invention relates to a system for efficiently managing events over a communication network. Specific components of the system include a server, terminals, and users. The purpose of this invention is to provide a series of functions using generative AI models to facilitate smooth communication between participants and event implementation.

[0606] First, the server provides a means for multiple participants to coordinate event dates via a communication network. Specifically, the server sends a questionnaire for scheduling an event using a LINE group or other communication platform. Participants respond with their available dates using their devices, and this information is sent to the server.

[0607] Next, the server collects the participants' schedule information and uses a generation AI to suggest the best schedule. This generation AI analyzes a large amount of data to find the best schedule for all participants. Reminder notifications are also automatically sent to participants who have not yet responded. These notifications include a reminder message and encourage them to respond again.

[0608] Furthermore, the server has a means to suggest locations for events. Users input requirements such as event dates, budget, food preferences, and location through the LINE app. The input information is sent to the server via the device, and the server uses generation AI to generate a list of appropriate restaurants based on this information. This list is sent to the LINE group, allowing the user to select the restaurant of their choice.

[0609] When a user selects a store, the server automatically makes a reservation at the selected store. This eliminates the need for reservations and allows for smooth seating arrangements. After the event ends, the store sends accounting information to the server. This information is stored in a database, and the server tallies the total amount and calculates the split between participants.

[0610] Finally, the calculation result is notified to the LINE group, and payment details are sent to each user. Users receive a notification on the LINE app and make the payment using a payment app such as PayPay. The payment data is transferred by the device to the server, and the server confirms that the payment has been completed.

[0611] Examples:

[0612] For example, when User A enters his or her available dates of "October 5th, 8th, and 10th" in the LINE app and submits them, the server collects this information, analyzes it using the generation AI, and suggests "October 8th" as the optimal date. If User B then enters information such as "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server suggests "Restaurant A, Restaurant B, and Restaurant C," and User B selects "Restaurant B," completing the reservation. After the drinking party, the total amount of 15,000 yen is registered in the database, and the bill is split among the five people at 3,000 yen each, and this is notified to the LINE group. Each user pays 3,000 yen with PayPay, and the server sends a completion notification.

[0613] Example prompt sentence:

[0614] "I'd like to schedule a drinking party in October. Please choose any days that are free. For example, October 5th, 8th, and 10th."

[0615] "Please find a Japanese restaurant in Shibuya on March 15th that costs under 5,000 yen."

[0616] "The total cost of the drinking party is 15,000 yen. We will split it among five people, so please pay 3,000 yen per person with PayPay."

[0617] This allows the organizer to efficiently and smoothly manage a series of tasks, from scheduling to choosing a restaurant and paying the bill, allowing participants to enjoy the event comfortably.

[0618] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0619] Processing steps for the schedule adjustment function

[0620] Step 1:

[0621] The server sends a questionnaire for scheduling an event to a LINE group or other communication group via a communication network. The input includes a list of participants and the contents of the questionnaire. Based on this, the server generates a questionnaire message and sends it to the group. The output is the sent questionnaire message.

[0622] Step 2:

[0623] Users enter their free dates in a questionnaire format through the LINE app. For example, User A enters "October 5th, 8th, and 10th." This data is sent as input to the device, which then forwards the information to the server. The output is the schedule information sent to the server.

[0624] Step 3:

[0625] The server collects schedule data sent by all users. The input includes individual schedule information from participants. The server analyzes this data using a generative AI to calculate the optimal schedule. The output is the optimal schedule information.

[0626] Step 4:

[0627] The server sends the analysis results as a proposal to the LINE group and notifies participants. The input required is the optimal schedule information calculated by the generation AI. The server forms this as a proposal message and sends it to the group. The output is the proposal message for the optimal schedule that was sent.

[0628] Step 5:

[0629] The server automatically sends reminder notifications to participants who have not yet responded. The input includes a list of participants who have not yet responded. Based on this, the server generates and sends a reminder message. The output is the sent reminder message. Specifically, the message is sent using the reminder notification function.

[0630] Store selection function processing steps

[0631] Step 1:

[0632] Users input information such as the date, budget, food preferences, and location of an event through the LINE app. For example, User B inputs "March 15th, budget 5,000 yen, Japanese food, Shibuya." This data is sent to the server via the device. The input is the event information entered by the user, and the output is the event information sent to the server.

[0633] Step 2:

[0634] The server uses a generative AI to generate a list of suitable stores based on the collected event information. The input includes the event information and a generative AI model. The generative AI analyzes this information and creates a list of candidate stores. The output is the generated store list.

[0635] Step 3:

[0636] The server sends the generated store list to the LINE group, and the user selects the desired store from the proposed list. The input includes the generated store list. The server sends this list and waits for a reply from the user. The output is the user's selection information.

[0637] Step 4:

[0638] When the user selects a store, the server automatically makes a reservation at the selected store. The input includes the user's selection information and store information. The server processes the reservation based on this and completes the reservation. The output is a notification that the reservation is complete.

[0639] Payment and split payment processing steps

[0640] Step 1:

[0641] When the drinking party ends, the billing information from the bar is sent to the server. The input includes the billing information. The server stores it in a database. The output is the stored billing information.

[0642] Step 2:

[0643] The server calculates the total amount based on the accounting information and splits the bill among the participants. The input includes the saved accounting information and the list of participants. The server performs calculations based on this information and calculates the split amount. The output is the calculated split amount.

[0644] Step 3:

[0645] The server notifies the LINE group of the calculation result and conveys payment details to each user. The input includes the calculated split amount. The server generates this as a notification message and sends it to the group. The output is the payment notification sent.

[0646] Step 4:

[0647] The user receives a notification on the LINE app and makes a payment using a payment app such as PayPay. The input includes the notified payment details. The user proceeds with the payment process according to this, and the payment data is transferred to the server by the device. The output is the payment data sent to the server.

[0648] Step 5:

[0649] The server verifies the payment data and notifies each user that the payment has been completed. The input includes payment data. The server verifies this, generates a payment completion notification, and sends it. The output is the payment completion notification that was sent. Specifically, the confirmation operation is performed using the payment confirmation function.

[0650] In this way, detailed data processing and data calculations are performed at each processing step, making the management of a series of events more efficient for the entire system.

[0651] (Application example 1)

[0652] 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."

[0653] Conventional event management systems involve complicated processes such as coordinating schedules among participants, selecting restaurants, managing accounting information, and making payments, placing a heavy burden on event organizers in particular. Furthermore, sufficient measures are often not implemented to ensure the safe handling of participants' personal information and accounting information. This makes it difficult for all participants to enjoy the event with peace of mind. There is a need for a system that can solve these issues and provide efficient and safe event management.

[0654] 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.

[0655] In this invention, the server includes: means for coordinating event schedules among multiple participants via a communications network; a generating artificial intelligence (AI) means for collecting schedule information from the participants and proposing optimal schedules; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing event locations via the communications network; means for automatically making reservations at locations selected from the proposed locations; means for collecting accounting information for the event and automatically splitting the bill among participants; means for completing payments among participants in cooperation with a payment application based on the accounting information; and means for encrypting and storing participant data and using secure communications when accessing the data. This significantly reduces the burden on the organizer and allows all participants to enjoy the event with peace of mind.

[0656] A "communications network" is an infrastructure for exchanging data between multiple terminals, and includes the Internet and local area networks.

[0657] "Participants" refers to multiple users who participate in an event.

[0658] "Date scheduling" refers to the process of surveying and arranging participants' availability to determine the best date and time for an event.

[0659] "Generative artificial intelligence (AI)" is a technology that uses machine learning or data analysis techniques to derive optimal solutions based on large amounts of data.

[0660] A "reminder" is an automatic notification message sent to participants who have not yet responded to encourage them to respond.

[0661] "Venue" means the physical location or facilities used for the actual conduct of an Event.

[0662] A "reservation" is a procedure for reserving a specific location at a specific date and time.

[0663] "Accounting information" is data that records all expenses related to the event.

[0664] "Bill-splitting" is the process of dividing the total cost equally among the participants.

[0665] A "payment application" is software that enables online payments.

[0666] "Encryption" is a process that transforms data using a specific algorithm to prevent it from being deciphered by third parties.

[0667] "Secure communications" refers to communications protocols that use technology to prevent unauthorized access and tampering when sending and receiving data.

[0668] The present invention relates to a system for managing events efficiently and securely over a communications network. This system provides a series of functions, including scheduling, restaurant selection, and payment, and securely manages participant data.

[0669] Hardware and software used

[0670] Server: Collects, analyzes, suggests, and encrypts data.

[0671] Terminal: The device through which a user enters data (e.g., smartphone, tablet, PC).

[0672] Generative AI model: Used for scheduling and restaurant selection.

[0673] LINE API: Used as a communication application.

[0674] PayPay API: Provides payment functions.

[0675] Encryption technology: used to protect participant data (e.g., AES encryption).

[0676] Program processing overview

[0677] The server receives information entered by the user, such as dates, budget, preferences, and location, and encrypts and stores it in a database. Based on this data, a generative AI model is used to generate a list of optimal dates and restaurants, which are then proposed to participants. Reminders are also automatically sent to participants who have not yet responded using the LINE API. Event reservations are automatically made at the restaurant selected by the user from the proposed restaurant list.

[0678] After the drinking party ends, the server receives the bill from the bar and automatically splits the bill based on this information. The calculation results are notified to all participants using the LINE API, and payment is made safely and quickly via the PayPay API. All data access uses encryption technology and secure communication protocols to prevent unauthorized access and data leaks.

[0679] Specific examples

[0680] For example, if the event date is set for "2023-04-01," the server will suggest "Japanese restaurants X, Y, and Z in Shibuya" based on the participants' preferences. All of this information is encrypted and securely stored. Reservations at "restaurant Y" are automatically made based on the participants' selections. Furthermore, the total bill of 15,000 yen after the drinking party is split among five people, with payment notifications sent to each person via LINE. Each person can pay securely using PayPay.

[0681] Prompt Sentence Examples

[0682] The following data is input into the generative AI model to generate a list of optimal dates and restaurants:

[0683] {

[0684] "group_id": "sample_group_id",

[0685] "availability": {"userA": "2023-04-01", "userB": "2023-04-02"},

[0686] "preferences": {

[0687] "date": "2023-04-01",

[0688] "budget": 5000,

[0689] "cuisine": "Japanese food",

[0690] "location": "Shibuya"

[0691] }

[0692] }

[0693] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0694] Step 1:

[0695] The server receives the schedule information entered by the user through the LINE API. It collects each user's free schedule data and sends it to the server via a secure method. The input is the user's schedule information, and the server stores the information in a database based on this.

[0696] Step 2:

[0697] The server uses a generative AI model to analyze the optimal schedule based on the collected schedule information. This analysis results in a proposal for a schedule that allows the most participants to participate conveniently. The input is each user's schedule data, and the generative AI model analyzes the data and outputs the optimal schedule.

[0698] Step 3:

[0699] The server notifies all participants of the optimal schedule obtained as a result of the analysis using the LINE API. It also automatically sends reminder notifications to users who have not yet responded. The input is the optimal schedule output from the generative AI model, and this is notified using the LINE API.

[0700] Step 4:

[0701] Users enter information such as the date, budget, preferences, and location of the event on the LINE application. The device collects this data and sends it to the server using encryption technology. The input is the user's event details, and the output is encrypted data.

[0702] Step 5:

[0703] The server analyzes the encrypted data and uses a generative AI model to generate a list of suitable venues (e.g., restaurants), which it then recommends to the user. The input is the encrypted event details, and the server outputs a list of suggested venues based on the analysis by the generative AI model.

[0704] Step 6:

[0705] Participants select from the proposed locations, and the server automatically makes a reservation for the selected location. The input is the user's selection, and the output is a reservation completion notification.

[0706] Step 7:

[0707] After the drinking party, the bar sends the billing information to the server. The server collects this information and automatically splits the bill among the participants. The input is the billing information from the bar, and the output is the split amount for each participant.

[0708] Step 8:

[0709] The server notifies the participants of the split calculation results using the LINE API. Participants receive the notification on their own devices and make payments accordingly. The input is the split calculation result, and the output is the notification to each participant.

[0710] Step 9:

[0711] After receiving the notification, the participant makes the payment using the PayPay API. The payment data is sent from the terminal to the server, and the server confirms the completion of the payment. The input is the payment data from the participant, and the output is a payment completion notification.

[0712] Step 10:

[0713] The server stores all data using encryption technology and uses secure communication protocols such as SSH when accessing data, preventing unauthorized access and data leakage. The input is all processed data, and the output is encrypted data storage.

[0714] 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.

[0715] This invention is a system that uses communication applications to support the organizer of events, especially drinking parties, and utilizes generative AI and an emotion engine to arrange dates, select restaurants, and make payments. This system recognizes the emotions of participants and makes optimal suggestions based on them, thereby increasing user satisfaction.

[0716] 1. Schedule adjustment function

[0717] The server has the function of sending a questionnaire for scheduling an event to LINE groups and other communication groups. Each participant answers the questionnaire to indicate their available dates. This response data is sent to the server via their device. The server collects this data and proposes the optimal date. In addition, the server automatically sends reminder notifications to users who have not yet responded.

[0718] For example, when User A enters and submits their free schedule, the information is transferred to the server via their device. The server then uses the generation AI to analyze this information and propose optimal dates to the LINE group. At the same time, reminders are sent to users who have not yet responded, ensuring that everyone has responded.

[0719] 2. Store selection function

[0720] Users enter information such as the date, budget, food preferences, and location of the event on the LINE application. This information is sent to the server via the device. The server uses generative AI to generate a list of appropriate restaurants based on this information. It also uses an emotion engine to recognize the user's emotions from text messages and voice input, and customizes suggestions based on that emotional information.

[0721] For example, if User B enters "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server will use the generation AI to suggest "Restaurant A, Restaurant B, Restaurant C" based on this data. At the same time, if the emotion engine recognizes emotions such as "looking happy" or "delighted" from the user's past messages and voice input, it will prioritize suggesting particularly popular restaurants or restaurants with good reviews. If User B selects "Restaurant B," the server will automatically make a reservation at Restaurant B based on this information.

[0722] 3. Payment and splitting features

[0723] After the drinking party is over, the bill information from the bar is sent to the server. This bill information is saved in a database, and the server calculates the total amount divided by the number of people. The calculation result is notified to the LINE group, and payment details are communicated to each user.

[0724] User C receives a notification on the LINE app and makes a payment using a payment application such as PayPay. This payment data is transferred by the device to the server, which then confirms that the payment has been completed. The emotion engine can analyze the user's emotions after payment and collect feedback for improvement if satisfaction is low.

[0725] Specific examples

[0726] For example, if the date of a drinking party is decided to be "April 1st," the server uses a generation AI to suggest "Store X, Store Y, and Store Z" from among Japanese restaurants in Shibuya. The emotion engine recognizes that User D said in a past message that he "likes restaurants with a nice atmosphere," and prioritizes "Store Y," which has a particularly good atmosphere, on the list. User D selects "Store Y," and the reservation is completed. After the drinking party, a total of 15,000 yen is registered on the server, and the bill is split among five people, at 3,000 yen each. The server sends a notification to the LINE group that "3,000 yen per person," and each user pays 3,000 yen with PayPay. The emotion engine analyzes subsequent messages and determines whether the user is satisfied.

[0727] In this way, event organizers can utilize the emotion engine to efficiently manage events while increasing participant satisfaction.

[0728] The processing flow will be explained below.

[0729] 1. Schedule adjustment function

[0730] Step 1: Send the survey

[0731] Server: Create and send a schedule adjustment survey to all participants in the LINE group.

[0732] Device: The survey form is displayed to the user on the LINE app.

[0733] Step 2: Collect responses

[0734] User: Enter your available dates in the survey form and tap the submit button.

[0735] Terminal: Transfers user input to the server.

[0736] Server: Saves the collected response data of each user in a database.

[0737] Step 3: Propose the best schedule

[0738] Server: Based on the collected data, the optimal schedule is calculated using a generative AI.

[0739] Server: Sends the calculation results to the LINE group as a proposal.

[0740] Terminal: Notifies the user of the suggested optimal schedule.

[0741] Step 4: Send a reminder

[0742] Server: Lists participants who have not responded and automatically sends reminder messages.

[0743] Terminal: Display a prompt message to the user.

[0744] 2. Store selection function

[0745] Step 1: Enter your information

[0746] User: Enter necessary information such as dates, budget, food preferences, and location on the LINE app.

[0747] Terminal: Transfers the entered information to the server.

[0748] Step 2: Sentiment Analysis

[0749] Server: Uses an emotion engine to recognize the user's emotions from the input message and voice data.

[0750] Server: Adjusts the content of suggestions based on the recognized emotion data.

[0751] Step 3: Generate a list of stores

[0752] Server: Uses generative AI to create a list of relevant businesses based on input information and sentiment data.

[0753] Server: Send the created list to the LINE group.

[0754] Terminal: Shows the user a list of stores.

[0755] Step 4: Confirm your reservation

[0756] User: Select the desired store from the list of suggested stores.

[0757] Terminal: Transfers the selection results to the server.

[0758] Server: Automatically executes the reservation procedure for the selected restaurant.

[0759] 3. Payment and splitting features

[0760] Step 1: Collect your billing information

[0761] Server: Receives billing information from the restaurant on the day of the drinking party.

[0762] Server: Stores the collected accounting information in a database.

[0763] Step 2: Split the bill

[0764] Server: Calculate the total amount divided by the number of people.

[0765] Server: Notify the LINE group of the calculation results.

[0766] Terminal: Display a notification of the split amount to the user.

[0767] Step 3: Checkout

[0768] User: Checks the notification and pays his / her share using the payment application.

[0769] Terminal: Transfers payment data to the server.

[0770] Server: Works with the payment application to verify payments from each user.

[0771] Step 4: Feedback after sentiment analysis

[0772] Server: Analyzes the user's messages and behavior after payment using an emotion engine.

[0773] Server: If satisfaction is low, collect feedback to help improve the system.

[0774] For example, if User D previously messaged, "I like places with a good atmosphere," the emotion engine would recognize this, and the generation AI would prioritize those establishments in the list. Similarly, if User D messaged after a drinking party saying, "It was fun," the emotion engine would analyze this, and the server would evaluate the high level of satisfaction. In this way, the emotion engine can be used to increase participant satisfaction.

[0775] Example 2

[0776] 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."

[0777] Traditional event planning tasks require a great deal of time and effort, including coordinating schedules for multiple participants, choosing restaurants, and handling payments, placing a heavy burden on event organizers. Furthermore, because it is not possible to make optimal proposals that take into account the feelings of participants, user satisfaction often declines. In particular, the complicated process of following up with non-respondents and processing payments is problematic.

[0778] The specific processing by the specific 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 coordinating the event schedule among multiple participants via a communications network; a generative artificial intelligence (AI) means for collecting schedule information of the participants and proposing an optimal schedule; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing a venue for the event via the communications network; means for automatically making a reservation at a venue selected from the proposed venues; means for collecting accounting information for the event and automatically splitting the bill among participants; means for completing payment among participants in cooperation with a payment application based on the accounting information; and an emotion engine means for recognizing participants' emotions and customizing the proposal content based on the emotion information. This makes it possible to improve the efficiency of event organizer work and significantly improve participant satisfaction.

[0779] A "communications network" is an infrastructure for sending and receiving data between multiple devices and computers, such as the Internet or a mobile phone network.

[0780] "Participant" means any person who intends to participate in an Event.

[0781] "Date Information" is availability information provided by participants regarding the date and time of the event.

[0782] A "generative artificial intelligence (AI) means" is a system that uses artificial intelligence technology to generate optimal proposals based on data collected from participants.

[0783] A "reminder notification" is a notification that is automatically sent to participants who have not yet responded, encouraging them to respond.

[0784] "Location" means the geographic location or facility where the Event actually takes place.

[0785] "Reservation" is a procedure that participants take in advance to secure the venue of their choice.

[0786] "Accounting information" refers to information regarding all expenses incurred after the event has ended.

[0787] "Split the bill" is a process of calculating the amount each participant should pay based on accounting information.

[0788] "Payment Application" means software that enables Participants to complete payments electronically.

[0789] An "emotion engine" is a software technology that recognizes a user's emotions and optimizes the content of suggestions based on those emotions.

[0790] This invention is a system that automates the event planning process via a communications network. The system utilizes a generative AI model and an emotion engine to efficiently coordinate schedules, select restaurants, and make payments. An example implementation of this system is described in detail below.

[0791] Schedule adjustment function

[0792] server:

[0793] The server sends a schedule-setting questionnaire to multiple participants. This questionnaire is sent via a communication network (e.g., the Internet or a mobile phone network). Each participant responds with their availability, and this information is sent to the server via their device. The server uses a generative AI model based on the collected schedule information to propose the optimal schedule. It also automatically sends reminder notifications to participants who have not responded.

[0794] (Example)

[0795] If User A answers "March 15th," this date information is sent to the server via the device. The server collects all responses and calculates the optimal date using a generative AI model. For example, if "March 20th" is determined to be optimal, the server will suggest that date to the LINE group. A reminder notification will be automatically sent to users who have not yet responded.

[0796] Shop selection function

[0797] User:

[0798] Users input requirements such as event dates, budget, food preferences, and location via a communication application (e.g., LINE). The input information is sent to the server via the terminal.

[0799] server:

[0800] The server uses a generative AI model based on the requirements information it receives to generate a list of suitable restaurants. It then uses an emotion engine to recognize the user's emotions and customizes the suggestions based on those emotions. For example, if the user indicates emotions such as "fun" or "happy" from past messages or voice input, restaurants with particularly good reputations or high reviews will be ranked high on the suggestion list.

[0801] (Example)

[0802] When User B enters "budget 5,000 yen, Japanese food, Shibuya," this information is sent from the device to the server. The server uses a generative AI model to suggest "Store A, Store B, Store C." At the same time, the emotion engine analyzes the user's emotions, and if it recognizes that the restaurant "looks fun," it prioritizes suggestions of restaurants with particularly good reviews.

[0803] Payment and split payment function

[0804] server:

[0805] After the event is over, the restaurant sends the billing information to the server. This billing information is stored in a database, and the server calculates the total amount divided by the number of people. The server then notifies each participant of the split amount via a communication application.

[0806] User:

[0807] The user receives a notification and makes a payment through an electronic payment application (e.g., PayPay). The payment information is sent from the terminal to the server, and the server confirms that the payment has been completed. The emotion engine analyzes the user's emotions after payment and collects feedback if the user is not satisfied.

[0808] (Example)

[0809] After the drinking party ends, the total bill of 15,000 yen is registered on the server. Based on this, the server calculates the amount per person to be 3,000 yen when divided among five people and notifies each user. When User C pays 3,000 yen with PayPay, this information is sent to the server and the payment is completed. The server uses an emotion engine to analyze messages such as "It was fun" and "I was satisfied" and confirm the user's level of satisfaction.

[0810] Prompt Sentence Examples

[0811] "We are organizing an upcoming event. To make our work more efficient, we would like to develop a system that utilizes generative AI models and an emotion engine. This system has the following requirements:

[0812] Use a communication application to coordinate schedules.

[0813] Choose a restaurant based on your budget, food preferences, and location.

[0814] The system automatically calculates the split and notifies you.

[0815] Maximize user satisfaction using an emotion engine.

[0816] In this way, the invention improves the efficiency of organizing tasks and participant satisfaction.

[0817] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0818] System processing steps

[0819] Step 1:

[0820] Create and send a scheduling survey

[0821] server:

[0822] The server automatically generates a survey for scheduling an event using the LINE API and sends it to the LINE group. The survey includes options for dates that users can select.

[0823] input:

[0824] Possible date for the event

[0825] output:

[0826] A scheduling survey sent to users

[0827] Specific behavior:

[0828] The server generates a survey that asks users to "choose a convenient date between March and April" and sends it via the LINE API.

[0829] Step 2:

[0830] Collection of responses to schedule adjustment questionnaires and proposals

[0831] User:

[0832] Each participant answers the questionnaire they received, which includes the user's free days.

[0833] input:

[0834] User's available schedule

[0835] output:

[0836] Response data sent to the server

[0837] Specific behavior:

[0838] User A enters his free date as "March 15th" and presses the send button. The information is transferred from the device to the server.

[0839] server:

[0840] The system collects response data sent via devices and uses a generative AI model to suggest optimal dates, while also sending reminder notifications to users who have not yet responded.

[0841] input:

[0842] Response data for each participant

[0843] output:

[0844] Optimal schedule suggestions and reminder notifications

[0845] Specific behavior:

[0846] If the server determines that March 20th is the best date based on the response data collected, it will notify the LINE group of the result. Users who have not yet responded will receive a reminder to respond.

[0847] Step 3:

[0848] Enter information to select a restaurant

[0849] User:

[0850] Use the LINE application to enter and submit requirements such as the event date, budget, food preferences, and location.

[0851] input:

[0852] Requirements such as dates, budget, food preferences, location, etc.

[0853] output:

[0854] Requirement data sent to the server

[0855] Specific behavior:

[0856] User B enters "March 20th, budget 5000 yen, Japanese food, Shibuya" and presses the send button. This information is sent from the device to the server.

[0857] Step 4:

[0858] Restaurant list generation and suggestions

[0859] server:

[0860] Based on the submitted requirements, a generative AI model is used to generate an appropriate restaurant list, while an emotion engine is used to analyze the user's emotions and customize the recommendations.

[0861] input:

[0862] Requirement Data

[0863] output:

[0864] Suggested restaurant list

[0865] Specific behavior:

[0866] Based on the requirements of "budget 5,000 yen, Japanese food, Shibuya," the server generates a list of "Store A, Store B, Store C" and suggests them to the LINE group. At the same time, the emotion engine recognizes the user's emotion of "looks fun" and places particularly popular stores at the top of the list.

[0867] Step 5:

[0868] Restaurant selection and reservations

[0869] User:

[0870] Select the appropriate restaurant from the list of suggested restaurants.

[0871] input:

[0872] User Selection

[0873] output:

[0874] Selection data sent to the server

[0875] Specific behavior:

[0876] User B selects "Store B" and sends the information to the server.

[0877] server:

[0878] Based on the user's selection, reservations are automatically made at selected stores.

[0879] input:

[0880] Selected Data

[0881] output:

[0882] Reservation confirmation

[0883] Specific behavior:

[0884] The server connects to Store B's reservation system and automatically confirms the reservation.

[0885] Step 6:

[0886] Registering accounting information and splitting the bill

[0887] server:

[0888] After the event, the restaurant sends accounting information, which is then stored in a database and split according to the number of participants.

[0889] input:

[0890] Accounting Information

[0891] output:

[0892] Split amount

[0893] Specific behavior:

[0894] The restaurant sends billing information totaling 15,000 yen, and the server saves this data in a database. Dividing this by five people results in 3,000 yen per person, so the server notifies the LINE group of the result.

[0895] Step 7:

[0896] Payment and feedback collection

[0897] User:

[0898] Receive notification of the split amount and make payment using your electronic payment application.

[0899] input:

[0900] Split amount notification

[0901] output:

[0902] Payment completion notification

[0903] Specific behavior:

[0904] User C receives the LINE notification and pays 3,000 yen using an electronic payment application. This payment data is sent from the device to the server.

[0905] server:

[0906] It confirms that the payment has been completed and uses a sentiment engine to analyze the user's sentiment and collect feedback.

[0907] input:

[0908] Payment completion notification

[0909] output:

[0910] Sentiment analysis results, feedback data

[0911] Specific behavior:

[0912] The server checks the payment data, and then analyzes the user's messages of "enjoyment" and "satisfaction" using an emotion engine. If the satisfaction level is low, feedback is collected and used to improve the system.

[0913] (Application example 2)

[0914] 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."

[0915] This invention relates to a system that efficiently supports the organizer's work for events, especially drinking parties, and increases participant satisfaction. Conventional methods place a heavy burden on the organizer, as scheduling, restaurant selection, and accounting are time-consuming tasks. Furthermore, it is not possible to make proposals that take into account the feelings of participants, making it difficult to hold an event that satisfies everyone. Furthermore, collecting feedback after an event is done manually, which makes it difficult to improve the system for the next event.

[0916] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for coordinating event schedules among multiple participants via a communications network; a generative artificial intelligence (AI) means for collecting participant schedule information and proposing optimal schedules; a means for automatically sending reminder notifications to participants who have not yet responded; a means for proposing event locations via a communications network; a means for automatically making reservations at locations selected from among the proposed locations; an emotion engine means for recognizing participant emotions from text messages or voice input and customizing the proposal based on the emotion information; a means for automatically making reservations at locations selected by participants on a smartphone application; a means for collecting event accounting information and automatically splitting the bill among participants; a means for completing payment among participants in cooperation with a payment application based on the accounting information; and a feedback means for reanalyzing participant emotions after the event and reflecting them in the next proposal. This improves the efficiency of event organizer tasks and enables events that increase the satisfaction of all participants.

[0917] A "communications network" is an infrastructure for transmitting and receiving data, including the Internet and local area networks (LANs).

[0918] "Participant" refers to an individual who attends an event or drinking party.

[0919] "Scheduling" refers to the task of coordinating schedules among multiple participants.

[0920] "Date information" refers to a list of participants' available dates and times.

[0921] "Generative artificial intelligence (AI)" is a system that uses machine learning and natural language processing to analyze data and generate optimal suggestions.

[0922] "Reminder" means a reminder message that is automatically sent to participants who have not responded.

[0923] The "venue" refers to the specific location where the event or drinking party will be held.

[0924] "Automatic booking" refers to the process by which the system automatically makes a booking based on user input.

[0925] An "emotion engine" is a system that analyzes a user's emotions from text messages and voice input, and customizes suggestions based on that information.

[0926] A "smartphone application" is a software program that runs on a smartphone.

[0927] "Accounting information" refers to data on the total amount of an event or drinking party and the amount paid by each participant.

[0928] "Splitting the bill" is the process of calculating the amount each participant will pay based on accounting information.

[0929] A "payment application" is application software for electronically transferring money.

[0930] "Feedback" refers to evaluations and impressions collected from participants after the event.

[0931] This invention is a system for improving the efficiency of event organizer work and increasing participant satisfaction. This system coordinates event schedules, restaurant selection, and accounting among multiple participants via a communications network, and further customizes proposals using an emotion engine to achieve optimal event management that takes participants' emotions into consideration.

[0932] Schedule adjustment

[0933] The server coordinates event dates among participants through a communication application. Specifically, it sends a schedule coordination survey to LINE groups and other messaging groups. Each participant responds to the survey about their available dates, and the information is sent to the server via their device. The server collects the data and suggests optimal dates using generative artificial intelligence (AI) methods. It also automatically sends reminder notifications to participants who have not yet responded.

[0934] Choosing a restaurant

[0935] The server accepts input from participants to suggest locations for the event. Participants enter information such as the event date, budget, food preferences, and location on a communication application. This information is sent to the server via their terminal, and the server uses generative AI to generate a list of appropriate restaurants. Furthermore, it can use an emotion engine means to recognize participants' emotions from text messages and voice inputs and customize the suggestions based on that emotion information. The server also automatically makes reservations at locations selected by the user.

[0936] Accounting and settlement

[0937] After the drinking party is over, the bill information from the bar is sent to the server. This bill information is saved in a database, and the server automatically splits the bill among the participants based on the total amount. The calculation result is notified to the participants via a communication application, and each participant makes payment using a payment application (e.g., an electronic payment application). This payment data is also transferred to the server via the terminal, and the server confirms that the payment has been completed.

[0938] Sentiment Analysis and Feedback

[0939] After the event, the server reanalyzes the participants' emotions and provides feedback to reflect the results in proposals for the next event. Specifically, by using the emotion engine described above again and analyzing the participants' messages and feedback data, it is possible to identify areas for improvement for the next event.

[0940] Examples of concrete examples and prompts

[0941] Specific examples

[0942] 1. Scheduling:

[0943] Send a survey in a group chat asking, "Which of the following days are you free: March 15th, 22nd, or 29th?"

[0944] Send a reminder to those who haven't responded: "If you haven't responded yet, hurry up and respond!"

[0945] 2. Choosing a restaurant:

[0946] The participant enters "March 22nd, budget 5,000 yen, yakiniku, Shinjuku."

[0947] The server uses a generative AI to suggest "Store A, Store B, Store C," and "Store B" is given priority based on the results of sentiment analysis.

[0948] The user selects "Store B" and the reservation is made automatically.

[0949] 3. Accounting:

[0950] After the drinking party, the total amount of 20,000 yen will be divided among the four people, with each person receiving 5,000 yen.

[0951] Each participant pays 5,000 yen using an electronic payment application, and the server confirms that the payment has been completed.

[0952] Prompt Sentence Examples

[0953] Scheduling prompt:

[0954] "When would be a good date for a drinking party?" "March 15th," "March 22nd," "March 29th"

[0955] Shop selection prompt:

[0956] "What's your budget?" "What are your food preferences?" "Where is it?" "Japanese food," "Yakiniku," "Chinese food"

[0957] Payment prompt:

[0958] "Today's bill is 5,000 yen per person. Please pay using the electronic payment application."

[0959] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0960] Step 1:

[0961] (Send schedule adjustment survey)

[0962] The user initiates a schedule adjustment survey on a communication application. At this time, the user inputs candidate dates and sends the candidate date data to the server. The server receives this data and sends the survey message to LINE groups and other messaging groups.

[0963] Input: Candidate dates specified by the user (e.g. March 15th, 22nd, 29th)

[0964] Data processing: The server converts the candidate date data into a message format

[0965] Output: Survey message sent to each participant

[0966] Step 2:

[0967] (Collecting schedule information)

[0968] Each participant clicks on the link in the survey message to answer their free dates. The answer data is sent to the server via their device. The server aggregates this data and stores each participant's free dates in a database.

[0969] Input: Available dates for participants to answer (e.g. March 15th, 22nd)

[0970] Data processing: The server aggregates and integrates individual response data

[0971] Output: Free schedule information of participants stored in the database

[0972] Step 3:

[0973] (Optimal schedule suggestions)

[0974] The server analyzes the collected schedule information using artificial intelligence (AI) to propose the optimal schedule. This AI selects the date that the most participants can attend based on the available dates of all participants.

[0975] Input: Attendee schedule information stored in the database

[0976] Data Calculation: Generative AI for Optimal Schedule Analysis

[0977] Output: Optimal date suggestion (e.g. March 22nd)

[0978] Step 4:

[0979] (Send reminder notifications)

[0980] The server identifies participants who have not responded and automatically sends reminders via LINE groups or other messaging groups.

[0981] Input: Answer status (Answered / Not answered)

[0982] Data processing: Generate reminder notifications based on response status

[0983] Output: Reminder notification message

[0984] Step 5:

[0985] (Suggestions for choosing a restaurant)

[0986] Users input details of the event (budget, food preferences, location, etc.) into the communication application. This information is sent via the device to the server, which then uses generative AI to generate a list of suitable restaurants.

[0987] Input: Event details (e.g., budget 5,000 yen, Yakiniku, Shinjuku)

[0988] Data calculation: Generative AI generates appropriate store lists

[0989] Output: Suggested store list (e.g., Store A, Store B, Store C)

[0990] Step 6:

[0991] (Analysis of emotional information)

[0992] The server uses an emotion engine means to recognize emotion information from the participant's text messages and voice inputs and customizes the suggestions based on the emotion information, for example, analyzing emotions such as "happy" and "delighted."

[0993] Input: Text messages and voice input data

[0994] Data Computation: Emotion Analysis with Emotion Engine

[0995] Output: Customized suggestions

[0996] Step 7:

[0997] (Automatic reservation)

[0998] When the user confirms the restaurant they selected from the list of suggested restaurants, the server automatically makes a reservation for that restaurant. The reservation information is sent to the terminal and a confirmation message is displayed to the user.

[0999] Input: User selected store

[1000] Data processing: Automatic reservation information generation

[1001] Output: Reservation confirmation message

[1002] Step 8:

[1003] (Collection of accounting information)

[1004] After the drinking party is over, the billing information is sent from the bar to the server, which stores this information in a database.

[1005] Input: Accounting information sent from the store (e.g. total amount 20,000 yen)

[1006] Data processing: Saving accounting information

[1007] Output: Accounting information stored in a database

[1008] Step 9:

[1009] (Split the bill)

[1010] The server automatically splits the bill among the participants based on the received accounting information, and the results are communicated via a communication application.

[1011] Input: Accounting information stored in the database

[1012] Data calculation: Calculating the payment amount for each participant

[1013] Output: Notification of split amount (e.g. 5000 yen per person)

[1014] Step 10:

[1015] (Electronic Payment)

[1016] Each participant pays the notified split amount using the electronic payment application. Data indicating the completion of the payment is transferred to the server via the terminal, and the server confirms that the payment has been completed.

[1017] Input: Payment data by each participant

[1018] Data processing: Payment completion status update

[1019] Output: Payment confirmation message

[1020] Step 11:

[1021] (Feedback collection and analysis)

[1022] After the event, the server reanalyzes the participants' emotions and collects feedback to be reflected in proposals for the next event.The emotion engine is used to analyze the participants' messages and feedback data to extract satisfaction levels and areas for improvement.

[1023] Input: Feedback data from participants

[1024] Data Calculation: Reanalysis by Emotion Engine

[1025] Output: Feedback data to be reflected in the next proposal

[1026] 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.

[1027] 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.

[1028] 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.

[1029] [Third embodiment]

[1030] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1031] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1032] 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).

[1033] 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.

[1034] 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.

[1035] 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).

[1036] 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.

[1037] 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.

[1038] 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.

[1039] 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.

[1040] 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.

[1041] 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."

[1042] The present invention relates to a drinking party organizer support system that uses a communication application. This system uses a generation AI to provide comprehensive support for scheduling, restaurant selection, and payment. Specific embodiments of the system are described below.

[1043] 1. Schedule adjustment function

[1044] The server has the function of sending a questionnaire for scheduling an event to LINE groups and other communication groups. Each participant answers the questionnaire to indicate their available dates. This response data is sent to the server via the terminal. The server collects this data and proposes the optimal schedule.

[1045] When User A enters and submits their free schedule, the device immediately transfers this information to the server. The server uses a generation AI to analyze the collected schedule information and sends the optimal schedule as a proposal to the LINE group. After that, the server automatically sends reminder notifications to users who have not yet responded.

[1046] 2. Store selection function

[1047] Users enter information such as the date, budget, food preferences, and location of the event on the LINE application. This information is sent to the server via the device. The server uses AI to generate a list of suitable restaurants based on this information and sends it to the LINE group.

[1048] For example, if User B enters "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server will search for Japanese restaurants in Shibuya based on this data and use generation AI to suggest "Restaurant A, Restaurant B, Restaurant C." If User B selects "Restaurant B" from the list, the server will automatically send an instruction to make a reservation at Restaurant B.

[1049] 3. Payment and splitting features

[1050] After the drinking party is over, the billing information from the bar is sent to the server. This information is stored in a database, and the server tallies the total amount and calculates the split between the participants. The calculation result is notified to the LINE group, and payment details are communicated to each user.

[1051] User C receives a notification on the LINE app and makes a payment using a payment application such as PayPay. This payment data is transferred by the device to the server, and the server confirms that the payment has been completed.

[1052] Specific examples

[1053] For example, the date of a drinking party is decided to be "April 1st," and the server uses a generation AI to suggest "Store X, Store Y, Store Z" from among Japanese restaurants in Shibuya. User D selects "Store Y" and the reservation is completed. After the drinking party, a total of 15,000 yen is registered on the server, and the bill is split among five people, at 3,000 yen each. The server sends a notification to the LINE group that "3,000 yen per person," and each user pays 3,000 yen with PayPay.

[1054] This allows event organizers to efficiently and smoothly manage a series of tasks, from scheduling to choosing restaurants and paying the bill. The introduction of this system significantly reduces the burden on event organizers and allows participants to enjoy the event comfortably.

[1055] The processing flow will be explained below.

[1056] 1. Schedule adjustment function

[1057] Step 1: Send the survey

[1058] Server: Create and send a schedule adjustment survey to all participants in the LINE group.

[1059] Device: The survey form is displayed to the user on the LINE app.

[1060] Step 2: Collect responses

[1061] User: Enter your available dates in the survey form and tap the submit button.

[1062] Terminal: Transfers user input to the server.

[1063] Server: Saves the collected response data of each user in a database.

[1064] Step 3: Propose the best schedule

[1065] Server: Based on the collected data, the optimal schedule is calculated using a generative AI.

[1066] Server: Sends the calculation results to the LINE group as a proposal.

[1067] Terminal: Notifies the user of the suggested optimal schedule.

[1068] Step 4: Send a reminder

[1069] Server: Lists participants who have not responded and automatically sends reminder messages.

[1070] Terminal: Display a prompt message to the user.

[1071] 2. Store selection function

[1072] Step 1: Enter your information

[1073] User: Enter necessary information such as dates, budget, food preferences, and location on the LINE app.

[1074] Terminal: Transfers the entered information to the server.

[1075] Step 2: Generate a list of stores

[1076] Server: Uses generative AI to create a list of appropriate stores based on the input information.

[1077] Server: Send the created list to the LINE group.

[1078] Terminal: Shows the user a list of stores.

[1079] Step 3: Confirm your reservation

[1080] User: Select the desired store from the list of suggested stores.

[1081] Terminal: Transfers the selection results to the server.

[1082] Server: Automatically executes the reservation procedure for the selected restaurant.

[1083] 3. Payment and splitting features

[1084] Step 1: Collect your billing information

[1085] Server: Receives billing information from the restaurant on the day of the drinking party.

[1086] Server: Stores the collected accounting information in a database.

[1087] Step 2: Split the bill

[1088] Server: Calculate the total amount divided by the number of people.

[1089] Server: Notify the LINE group of the calculation results.

[1090] Terminal: Display a notification of the split amount to the user.

[1091] Step 3: Checkout

[1092] User: Checks the notification and pays his / her share using the payment application.

[1093] Terminal: Transfers payment data to the server.

[1094] Server: Works with the payment application to verify payments from each user.

[1095] This allows the organizer to efficiently and smoothly carry out the entire process of the drinking party, from preparation to its end.

[1096] Example 1

[1097] 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."

[1098] With conventional event management systems, a series of tasks such as scheduling, selecting restaurants, splitting the bill, and settling the payment required a lot of time and effort, placing a heavy burden on the organizer. Furthermore, communication between participants was sometimes not smooth, which could lead to delays in planning and execution of the event.

[1099] 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.

[1100] In this invention, the server includes: means for coordinating event dates among multiple participants via a communications network; a generating artificial intelligence (AI) means for collecting schedule information from the participants and proposing the optimal schedule; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing event locations via the communications network; means for automatically making reservations at locations selected from the proposed locations; means for collecting accounting information for the event and automatically splitting the bill among participants; and means for completing payment among participants in cooperation with a payment application based on the accounting information. This automates the entire process from scheduling to restaurant selection, accounting, and payment, significantly reducing the burden on event organizers and enabling smoother event planning and execution.

[1101] A "communications network" refers to a network that allows computers and terminals to exchange information with each other. This includes the Internet and local area networks (LANs).

[1102] "Participant" means any person or group who intends to attend the Event and who is involved in scheduling and selecting the location of the Event.

[1103] "Generative artificial intelligence (AI)" refers to a technology that analyzes large amounts of data, finds patterns, and supports decision-making. In this invention, it plays a role in suggesting optimal dates and restaurant options.

[1104] A "reminder" is a warning message that alerts users to take a specific action, such as a notification to remind unanswered participants to reschedule.

[1105] "Event location" refers to the physical or virtual location where the event takes place, such as a restaurant, conference room, or online meeting platform.

[1106] "Financial Information" means detailed information about costs and expenses related to an Event, including data necessary to calculate totals and split bills at restaurants.

[1107] "Payment application" means software that enables users to make or receive payments online or through a mobile device. Examples include e-wallet apps and mobile banking apps.

[1108] This invention relates to a system for efficiently managing events over a communication network. Specific components of the system include a server, terminals, and users. The purpose of this invention is to provide a series of functions using generative AI models to facilitate smooth communication between participants and event implementation.

[1109] First, the server provides a means for multiple participants to coordinate event dates via a communication network. Specifically, the server sends a questionnaire for scheduling an event using a LINE group or other communication platform. Participants respond with their available dates using their devices, and this information is sent to the server.

[1110] Next, the server collects the participants' schedule information and uses a generation AI to suggest the best schedule. This generation AI analyzes a large amount of data to find the best schedule for all participants. Reminder notifications are also automatically sent to participants who have not yet responded. These notifications include a reminder message and encourage them to respond again.

[1111] Furthermore, the server has a means to suggest locations for events. Users input requirements such as event dates, budget, food preferences, and location through the LINE app. The input information is sent to the server via the device, and the server uses generation AI to generate a list of appropriate restaurants based on this information. This list is sent to the LINE group, allowing the user to select the restaurant of their choice.

[1112] When a user selects a store, the server automatically makes a reservation at the selected store. This eliminates the need for reservations and allows for smooth seating arrangements. After the event ends, the store sends accounting information to the server. This information is stored in a database, and the server tallies the total amount and calculates the split between participants.

[1113] Finally, the calculation result is notified to the LINE group, and payment details are sent to each user. Users receive a notification on the LINE app and make the payment using a payment app such as PayPay. The payment data is transferred by the device to the server, and the server confirms that the payment has been completed.

[1114] Examples:

[1115] For example, when User A enters his or her available dates of "October 5th, 8th, and 10th" in the LINE app and submits them, the server collects this information, analyzes it using the generation AI, and suggests "October 8th" as the optimal date. If User B then enters information such as "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server suggests "Restaurant A, Restaurant B, and Restaurant C," and User B selects "Restaurant B," completing the reservation. After the drinking party, the total amount of 15,000 yen is registered in the database, and the bill is split among the five people at 3,000 yen each, and this is notified to the LINE group. Each user pays 3,000 yen with PayPay, and the server sends a completion notification.

[1116] Example prompt sentence:

[1117] "I'd like to schedule a drinking party in October. Please choose any days that are free. For example, October 5th, 8th, and 10th."

[1118] "Please find a Japanese restaurant in Shibuya on March 15th that costs under 5,000 yen."

[1119] "The total cost of the drinking party is 15,000 yen. We will split it among five people, so please pay 3,000 yen per person with PayPay."

[1120] This allows the organizer to efficiently and smoothly manage a series of tasks, from scheduling to choosing a restaurant and paying the bill, allowing participants to enjoy the event comfortably.

[1121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1122] Processing steps for the schedule adjustment function

[1123] Step 1:

[1124] The server sends a questionnaire for scheduling an event to a LINE group or other communication group via a communication network. The input includes a list of participants and the contents of the questionnaire. Based on this, the server generates a questionnaire message and sends it to the group. The output is the sent questionnaire message.

[1125] Step 2:

[1126] Users enter their free dates in a questionnaire format through the LINE app. For example, User A enters "October 5th, 8th, and 10th." This data is sent as input to the device, which then forwards the information to the server. The output is the schedule information sent to the server.

[1127] Step 3:

[1128] The server collects schedule data sent by all users. The input includes individual schedule information from participants. The server analyzes this data using a generative AI to calculate the optimal schedule. The output is the optimal schedule information.

[1129] Step 4:

[1130] The server sends the analysis results as a proposal to the LINE group and notifies participants. The input required is the optimal schedule information calculated by the generation AI. The server forms this as a proposal message and sends it to the group. The output is the proposal message for the optimal schedule that was sent.

[1131] Step 5:

[1132] The server automatically sends reminder notifications to participants who have not yet responded. The input includes a list of participants who have not yet responded. Based on this, the server generates and sends a reminder message. The output is the sent reminder message. Specifically, the message is sent using the reminder notification function.

[1133] Store selection function processing steps

[1134] Step 1:

[1135] Users input information such as the date, budget, food preferences, and location of an event through the LINE app. For example, User B inputs "March 15th, budget 5,000 yen, Japanese food, Shibuya." This data is sent to the server via the device. The input is the event information entered by the user, and the output is the event information sent to the server.

[1136] Step 2:

[1137] The server uses a generative AI to generate a list of suitable stores based on the collected event information. The input includes the event information and a generative AI model. The generative AI analyzes this information and creates a list of candidate stores. The output is the generated store list.

[1138] Step 3:

[1139] The server sends the generated store list to the LINE group, and the user selects the desired store from the proposed list. The input includes the generated store list. The server sends this list and waits for a reply from the user. The output is the user's selection information.

[1140] Step 4:

[1141] When the user selects a store, the server automatically makes a reservation at the selected store. The input includes the user's selection information and store information. The server processes the reservation based on this and completes the reservation. The output is a notification that the reservation is complete.

[1142] Payment and split payment processing steps

[1143] Step 1:

[1144] When the drinking party ends, the billing information from the bar is sent to the server. The input includes the billing information. The server stores it in a database. The output is the stored billing information.

[1145] Step 2:

[1146] The server calculates the total amount based on the accounting information and splits the bill among the participants. The input includes the saved accounting information and the list of participants. The server performs calculations based on this information and calculates the split amount. The output is the calculated split amount.

[1147] Step 3:

[1148] The server notifies the LINE group of the calculation result and conveys payment details to each user. The input includes the calculated split amount. The server generates this as a notification message and sends it to the group. The output is the payment notification sent.

[1149] Step 4:

[1150] The user receives a notification on the LINE app and makes a payment using a payment app such as PayPay. The input includes the notified payment details. The user proceeds with the payment process according to this, and the payment data is transferred to the server by the device. The output is the payment data sent to the server.

[1151] Step 5:

[1152] The server verifies the payment data and notifies each user that the payment has been completed. The input includes payment data. The server verifies this, generates a payment completion notification, and sends it. The output is the payment completion notification that was sent. Specifically, the confirmation operation is performed using the payment confirmation function.

[1153] In this way, detailed data processing and data calculations are performed at each processing step, making the management of a series of events more efficient for the entire system.

[1154] (Application example 1)

[1155] 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."

[1156] Conventional event management systems involve complicated processes such as coordinating schedules among participants, selecting restaurants, managing accounting information, and making payments, placing a heavy burden on event organizers in particular. Furthermore, sufficient measures are often not implemented to ensure the safe handling of participants' personal information and accounting information. This makes it difficult for all participants to enjoy the event with peace of mind. There is a need for a system that can solve these issues and provide efficient and safe event management.

[1157] 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.

[1158] In this invention, the server includes: means for coordinating event schedules among multiple participants via a communications network; a generating artificial intelligence (AI) means for collecting schedule information from the participants and proposing optimal schedules; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing event locations via the communications network; means for automatically making reservations at locations selected from the proposed locations; means for collecting accounting information for the event and automatically splitting the bill among participants; means for completing payments among participants in cooperation with a payment application based on the accounting information; and means for encrypting and storing participant data and using secure communications when accessing the data. This significantly reduces the burden on the organizer and allows all participants to enjoy the event with peace of mind.

[1159] A "communications network" is an infrastructure for exchanging data between multiple terminals, and includes the Internet and local area networks.

[1160] "Participants" refers to multiple users who participate in an event.

[1161] "Date scheduling" refers to the process of surveying and arranging participants' availability to determine the best date and time for an event.

[1162] "Generative artificial intelligence (AI)" is a technology that uses machine learning or data analysis techniques to derive optimal solutions based on large amounts of data.

[1163] A "reminder" is an automatic notification message sent to participants who have not yet responded to encourage them to respond.

[1164] "Venue" means the physical location or facilities used for the actual conduct of an Event.

[1165] A "reservation" is a procedure for reserving a specific location at a specific date and time.

[1166] "Accounting information" is data that records all expenses related to the event.

[1167] "Bill-splitting" is the process of dividing the total cost equally among the participants.

[1168] A "payment application" is software that enables online payments.

[1169] "Encryption" is a process that transforms data using a specific algorithm to prevent it from being deciphered by third parties.

[1170] "Secure communications" refers to communications protocols that use technology to prevent unauthorized access and tampering when sending and receiving data.

[1171] The present invention relates to a system for managing events efficiently and securely over a communications network. This system provides a series of functions, including scheduling, restaurant selection, and payment, and securely manages participant data.

[1172] Hardware and software used

[1173] Server: Collects, analyzes, suggests, and encrypts data.

[1174] Terminal: The device through which a user enters data (e.g., smartphone, tablet, PC).

[1175] Generative AI model: Used for scheduling and restaurant selection.

[1176] LINE API: Used as a communication application.

[1177] PayPay API: Provides payment functions.

[1178] Encryption technology: used to protect participant data (e.g., AES encryption).

[1179] Program processing overview

[1180] The server receives information entered by the user, such as dates, budget, preferences, and location, and encrypts and stores it in a database. Based on this data, a generative AI model is used to generate a list of optimal dates and restaurants, which are then proposed to participants. Reminders are also automatically sent to participants who have not yet responded using the LINE API. Event reservations are automatically made at the restaurant selected by the user from the proposed restaurant list.

[1181] After the drinking party ends, the server receives the bill from the bar and automatically splits the bill based on this information. The calculation results are notified to all participants using the LINE API, and payment is made safely and quickly via the PayPay API. All data access uses encryption technology and secure communication protocols to prevent unauthorized access and data leaks.

[1182] Specific examples

[1183] For example, if the event date is set for "2023-04-01," the server will suggest "Japanese restaurants X, Y, and Z in Shibuya" based on the participants' preferences. All of this information is encrypted and securely stored. Reservations at "restaurant Y" are automatically made based on the participants' selections. Furthermore, the total bill of 15,000 yen after the drinking party is split among five people, with payment notifications sent to each person via LINE. Each person can pay securely using PayPay.

[1184] Prompt Sentence Examples

[1185] The following data is input into the generative AI model to generate a list of optimal dates and restaurants:

[1186] {

[1187] "group_id": "sample_group_id",

[1188] "availability": {"userA": "2023-04-01", "userB": "2023-04-02"},

[1189] "preferences": {

[1190] "date": "2023-04-01",

[1191] "budget": 5000,

[1192] "cuisine": "Japanese food",

[1193] "location": "Shibuya"

[1194] }

[1195] }

[1196] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1197] Step 1:

[1198] The server receives the schedule information entered by the user through the LINE API. It collects each user's free schedule data and sends it to the server via a secure method. The input is the user's schedule information, and the server stores the information in a database based on this.

[1199] Step 2:

[1200] The server uses a generative AI model to analyze the optimal schedule based on the collected schedule information. This analysis results in a proposal for a schedule that allows the most participants to participate conveniently. The input is each user's schedule data, and the generative AI model analyzes the data and outputs the optimal schedule.

[1201] Step 3:

[1202] The server notifies all participants of the optimal schedule obtained as a result of the analysis using the LINE API. It also automatically sends reminder notifications to users who have not yet responded. The input is the optimal schedule output from the generative AI model, and this is notified using the LINE API.

[1203] Step 4:

[1204] Users enter information such as the date, budget, preferences, and location of the event on the LINE application. The device collects this data and sends it to the server using encryption technology. The input is the user's event details, and the output is encrypted data.

[1205] Step 5:

[1206] The server analyzes the encrypted data and uses a generative AI model to generate a list of suitable venues (e.g., restaurants), which it then recommends to the user. The input is the encrypted event details, and the server outputs a list of suggested venues based on the analysis by the generative AI model.

[1207] Step 6:

[1208] Participants select from the proposed locations, and the server automatically makes a reservation for the selected location. The input is the user's selection, and the output is a reservation completion notification.

[1209] Step 7:

[1210] After the drinking party, the bar sends the billing information to the server. The server collects this information and automatically splits the bill among the participants. The input is the billing information from the bar, and the output is the split amount for each participant.

[1211] Step 8:

[1212] The server notifies the participants of the split calculation results using the LINE API. Participants receive the notification on their own devices and make payments accordingly. The input is the split calculation result, and the output is the notification to each participant.

[1213] Step 9:

[1214] After receiving the notification, the participant makes the payment using the PayPay API. The payment data is sent from the terminal to the server, and the server confirms the completion of the payment. The input is the payment data from the participant, and the output is a payment completion notification.

[1215] Step 10:

[1216] The server stores all data using encryption technology and uses secure communication protocols such as SSH when accessing data, preventing unauthorized access and data leakage. The input is all processed data, and the output is encrypted data storage.

[1217] 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.

[1218] This invention is a system that uses communication applications to support the organizer of events, especially drinking parties, and utilizes generative AI and an emotion engine to arrange dates, select restaurants, and make payments. This system recognizes the emotions of participants and makes optimal suggestions based on them, thereby increasing user satisfaction.

[1219] 1. Schedule adjustment function

[1220] The server has the function of sending a questionnaire for scheduling an event to LINE groups and other communication groups. Each participant answers the questionnaire to indicate their available dates. This response data is sent to the server via their device. The server collects this data and proposes the optimal date. In addition, the server automatically sends reminder notifications to users who have not yet responded.

[1221] For example, when User A enters and submits their free schedule, the information is transferred to the server via their device. The server then uses the generation AI to analyze this information and propose optimal dates to the LINE group. At the same time, reminders are sent to users who have not yet responded, ensuring that everyone has responded.

[1222] 2. Store selection function

[1223] Users enter information such as the date, budget, food preferences, and location of the event on the LINE application. This information is sent to the server via the device. The server uses generative AI to generate a list of appropriate restaurants based on this information. It also uses an emotion engine to recognize the user's emotions from text messages and voice input, and customizes suggestions based on that emotional information.

[1224] For example, if User B enters "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server will use the generation AI to suggest "Restaurant A, Restaurant B, Restaurant C" based on this data. At the same time, if the emotion engine recognizes emotions such as "looking happy" or "delighted" from the user's past messages and voice input, it will prioritize suggesting particularly popular restaurants or restaurants with good reviews. If User B selects "Restaurant B," the server will automatically make a reservation at Restaurant B based on this information.

[1225] 3. Payment and splitting features

[1226] After the drinking party is over, the bill information from the bar is sent to the server. This bill information is saved in a database, and the server calculates the total amount divided by the number of people. The calculation result is notified to the LINE group, and payment details are communicated to each user.

[1227] User C receives a notification on the LINE app and makes a payment using a payment application such as PayPay. This payment data is transferred by the device to the server, which then confirms that the payment has been completed. The emotion engine can analyze the user's emotions after payment and collect feedback for improvement if satisfaction is low.

[1228] Specific examples

[1229] For example, if the date of a drinking party is decided to be "April 1st," the server uses a generation AI to suggest "Store X, Store Y, and Store Z" from among Japanese restaurants in Shibuya. The emotion engine recognizes that User D said in a past message that he "likes restaurants with a nice atmosphere," and prioritizes "Store Y," which has a particularly good atmosphere, on the list. User D selects "Store Y," and the reservation is completed. After the drinking party, a total of 15,000 yen is registered on the server, and the bill is split among five people, at 3,000 yen each. The server sends a notification to the LINE group that "3,000 yen per person," and each user pays 3,000 yen with PayPay. The emotion engine analyzes subsequent messages and determines whether the user is satisfied.

[1230] In this way, event organizers can utilize the emotion engine to efficiently manage events while increasing participant satisfaction.

[1231] The processing flow will be explained below.

[1232] 1. Schedule adjustment function

[1233] Step 1: Send the survey

[1234] Server: Create and send a schedule adjustment survey to all participants in the LINE group.

[1235] Device: The survey form is displayed to the user on the LINE app.

[1236] Step 2: Collect responses

[1237] User: Enter your available dates in the survey form and tap the submit button.

[1238] Terminal: Transfers user input to the server.

[1239] Server: Saves the collected response data of each user in a database.

[1240] Step 3: Propose the best schedule

[1241] Server: Based on the collected data, the optimal schedule is calculated using a generative AI.

[1242] Server: Sends the calculation results to the LINE group as a proposal.

[1243] Terminal: Notifies the user of the suggested optimal schedule.

[1244] Step 4: Send a reminder

[1245] Server: Lists participants who have not responded and automatically sends reminder messages.

[1246] Terminal: Display a prompt message to the user.

[1247] 2. Store selection function

[1248] Step 1: Enter your information

[1249] User: Enter necessary information such as dates, budget, food preferences, and location on the LINE app.

[1250] Terminal: Transfers the entered information to the server.

[1251] Step 2: Sentiment Analysis

[1252] Server: Uses an emotion engine to recognize the user's emotions from the input message and voice data.

[1253] Server: Adjusts the content of suggestions based on the recognized emotion data.

[1254] Step 3: Generate a list of stores

[1255] Server: Uses generative AI to create a list of relevant businesses based on input information and sentiment data.

[1256] Server: Send the created list to the LINE group.

[1257] Terminal: Shows the user a list of stores.

[1258] Step 4: Confirm your reservation

[1259] User: Select the desired store from the list of suggested stores.

[1260] Terminal: Transfers the selection results to the server.

[1261] Server: Automatically executes the reservation procedure for the selected restaurant.

[1262] 3. Payment and splitting features

[1263] Step 1: Collect your billing information

[1264] Server: Receives billing information from the restaurant on the day of the drinking party.

[1265] Server: Stores the collected accounting information in a database.

[1266] Step 2: Split the bill

[1267] Server: Calculate the total amount divided by the number of people.

[1268] Server: Notify the LINE group of the calculation results.

[1269] Terminal: Display a notification of the split amount to the user.

[1270] Step 3: Checkout

[1271] User: Checks the notification and pays his / her share using the payment application.

[1272] Terminal: Transfers payment data to the server.

[1273] Server: Works with the payment application to verify payments from each user.

[1274] Step 4: Feedback after sentiment analysis

[1275] Server: Analyzes the user's messages and behavior after payment using an emotion engine.

[1276] Server: If satisfaction is low, collect feedback to help improve the system.

[1277] For example, if User D previously messaged, "I like places with a good atmosphere," the emotion engine would recognize this, and the generation AI would prioritize those establishments in the list. Similarly, if User D messaged after a drinking party saying, "It was fun," the emotion engine would analyze this, and the server would evaluate the high level of satisfaction. In this way, the emotion engine can be used to increase participant satisfaction.

[1278] Example 2

[1279] 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."

[1280] Traditional event planning tasks require a great deal of time and effort, including coordinating schedules for multiple participants, choosing restaurants, and handling payments, placing a heavy burden on event organizers. Furthermore, because it is not possible to make optimal proposals that take into account the feelings of participants, user satisfaction often declines. In particular, the complicated process of following up with non-respondents and processing payments is problematic.

[1281] The specific processing by the specific 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 coordinating the event schedule among multiple participants via a communications network; a generative artificial intelligence (AI) means for collecting schedule information of the participants and proposing an optimal schedule; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing a venue for the event via the communications network; means for automatically making a reservation at a venue selected from the proposed venues; means for collecting accounting information for the event and automatically splitting the bill among participants; means for completing payment among participants in cooperation with a payment application based on the accounting information; and an emotion engine means for recognizing participants' emotions and customizing the proposal content based on the emotion information. This makes it possible to improve the efficiency of event organizer work and significantly improve participant satisfaction.

[1282] A "communications network" is an infrastructure for sending and receiving data between multiple devices and computers, such as the Internet or a mobile phone network.

[1283] "Participant" means any person who intends to participate in an Event.

[1284] "Date Information" is availability information provided by participants regarding the date and time of the event.

[1285] A "generative artificial intelligence (AI) means" is a system that uses artificial intelligence technology to generate optimal proposals based on data collected from participants.

[1286] A "reminder notification" is a notification that is automatically sent to participants who have not yet responded, encouraging them to respond.

[1287] "Location" means the geographic location or facility where the Event actually takes place.

[1288] "Reservation" is a procedure that participants take in advance to secure the venue of their choice.

[1289] "Accounting information" refers to information regarding all expenses incurred after the event has ended.

[1290] "Split the bill" is a process of calculating the amount each participant should pay based on accounting information.

[1291] "Payment Application" means software that enables Participants to complete payments electronically.

[1292] An "emotion engine" is a software technology that recognizes a user's emotions and optimizes the content of suggestions based on those emotions.

[1293] This invention is a system that automates the event planning process via a communications network. The system utilizes a generative AI model and an emotion engine to efficiently coordinate schedules, select restaurants, and make payments. An example implementation of this system is described in detail below.

[1294] Schedule adjustment function

[1295] server:

[1296] The server sends a schedule-setting questionnaire to multiple participants. This questionnaire is sent via a communication network (e.g., the Internet or a mobile phone network). Each participant responds with their availability, and this information is sent to the server via their device. The server uses a generative AI model based on the collected schedule information to propose the optimal schedule. It also automatically sends reminder notifications to participants who have not responded.

[1297] (Example)

[1298] If User A answers "March 15th," this date information is sent to the server via the device. The server collects all responses and calculates the optimal date using a generative AI model. For example, if "March 20th" is determined to be optimal, the server will suggest that date to the LINE group. A reminder notification will be automatically sent to users who have not yet responded.

[1299] Shop selection function

[1300] User:

[1301] Users input requirements such as event dates, budget, food preferences, and location via a communication application (e.g., LINE). The input information is sent to the server via the terminal.

[1302] server:

[1303] The server uses a generative AI model based on the requirements information it receives to generate a list of suitable restaurants. It then uses an emotion engine to recognize the user's emotions and customizes the suggestions based on those emotions. For example, if the user indicates emotions such as "fun" or "happy" from past messages or voice input, restaurants with particularly good reputations or high reviews will be ranked high on the suggestion list.

[1304] (Example)

[1305] When User B enters "budget 5,000 yen, Japanese food, Shibuya," this information is sent from the device to the server. The server uses a generative AI model to suggest "Store A, Store B, Store C." At the same time, the emotion engine analyzes the user's emotions, and if it recognizes that the restaurant "looks fun," it prioritizes suggestions of restaurants with particularly good reviews.

[1306] Payment and split payment function

[1307] server:

[1308] After the event is over, the restaurant sends the billing information to the server. This billing information is stored in a database, and the server calculates the total amount divided by the number of people. The server then notifies each participant of the split amount via a communication application.

[1309] User:

[1310] The user receives a notification and makes a payment through an electronic payment application (e.g., PayPay). The payment information is sent from the terminal to the server, and the server confirms that the payment has been completed. The emotion engine analyzes the user's emotions after payment and collects feedback if the user is not satisfied.

[1311] (Example)

[1312] After the drinking party ends, the total bill of 15,000 yen is registered on the server. Based on this, the server calculates the amount per person to be 3,000 yen when divided among five people and notifies each user. When User C pays 3,000 yen with PayPay, this information is sent to the server and the payment is completed. The server uses an emotion engine to analyze messages such as "It was fun" and "I was satisfied" and confirm the user's level of satisfaction.

[1313] Prompt Sentence Examples

[1314] "We are organizing an upcoming event. To make our work more efficient, we would like to develop a system that utilizes generative AI models and an emotion engine. This system has the following requirements:

[1315] Use a communication application to coordinate schedules.

[1316] Choose a restaurant based on your budget, food preferences, and location.

[1317] The system automatically calculates the split and notifies you.

[1318] Maximize user satisfaction using an emotion engine.

[1319] In this way, the invention improves the efficiency of organizing tasks and participant satisfaction.

[1320] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1321] System processing steps

[1322] Step 1:

[1323] Create and send a scheduling survey

[1324] server:

[1325] The server automatically generates a survey for scheduling an event using the LINE API and sends it to the LINE group. The survey includes options for dates that users can select.

[1326] input:

[1327] Possible date for the event

[1328] output:

[1329] A scheduling survey sent to users

[1330] Specific behavior:

[1331] The server generates a survey that asks users to "choose a convenient date between March and April" and sends it via the LINE API.

[1332] Step 2:

[1333] Collection of responses to schedule adjustment questionnaires and proposals

[1334] User:

[1335] Each participant answers the questionnaire they received, which includes the user's free days.

[1336] input:

[1337] User's available schedule

[1338] output:

[1339] Response data sent to the server

[1340] Specific behavior:

[1341] User A enters his free date as "March 15th" and presses the send button. The information is transferred from the device to the server.

[1342] server:

[1343] The system collects response data sent via devices and uses a generative AI model to suggest optimal dates, while also sending reminder notifications to users who have not yet responded.

[1344] input:

[1345] Response data for each participant

[1346] output:

[1347] Optimal schedule suggestions and reminder notifications

[1348] Specific behavior:

[1349] If the server determines that March 20th is the best date based on the response data collected, it will notify the LINE group of the result. Users who have not yet responded will receive a reminder to respond.

[1350] Step 3:

[1351] Enter information to select a restaurant

[1352] User:

[1353] Use the LINE application to enter and submit requirements such as the event date, budget, food preferences, and location.

[1354] input:

[1355] Requirements such as dates, budget, food preferences, location, etc.

[1356] output:

[1357] Requirement data sent to the server

[1358] Specific behavior:

[1359] User B enters "March 20th, budget 5000 yen, Japanese food, Shibuya" and presses the send button. This information is sent from the device to the server.

[1360] Step 4:

[1361] Restaurant list generation and suggestions

[1362] server:

[1363] Based on the submitted requirements, a generative AI model is used to generate an appropriate restaurant list, while an emotion engine is used to analyze the user's emotions and customize the recommendations.

[1364] input:

[1365] Requirement Data

[1366] output:

[1367] Suggested restaurant list

[1368] Specific behavior:

[1369] Based on the requirements of "budget 5,000 yen, Japanese food, Shibuya," the server generates a list of "Store A, Store B, Store C" and suggests them to the LINE group. At the same time, the emotion engine recognizes the user's emotion of "looks fun" and places particularly popular stores at the top of the list.

[1370] Step 5:

[1371] Restaurant selection and reservations

[1372] User:

[1373] Select the appropriate restaurant from the list of suggested restaurants.

[1374] input:

[1375] User Selection

[1376] output:

[1377] Selection data sent to the server

[1378] Specific behavior:

[1379] User B selects "Store B" and sends the information to the server.

[1380] server:

[1381] Based on the user's selection, reservations are automatically made at selected stores.

[1382] input:

[1383] Selected Data

[1384] output:

[1385] Reservation confirmation

[1386] Specific behavior:

[1387] The server connects to Store B's reservation system and automatically confirms the reservation.

[1388] Step 6:

[1389] Registering accounting information and splitting the bill

[1390] server:

[1391] After the event, the restaurant sends accounting information, which is then stored in a database and split according to the number of participants.

[1392] input:

[1393] Accounting Information

[1394] output:

[1395] Split amount

[1396] Specific behavior:

[1397] The restaurant sends billing information totaling 15,000 yen, and the server saves this data in a database. Dividing this by five people results in 3,000 yen per person, so the server notifies the LINE group of the result.

[1398] Step 7:

[1399] Payment and feedback collection

[1400] User:

[1401] Receive notification of the split amount and make payment using your electronic payment application.

[1402] input:

[1403] Split amount notification

[1404] output:

[1405] Payment completion notification

[1406] Specific behavior:

[1407] User C receives the LINE notification and pays 3,000 yen using an electronic payment application. This payment data is sent from the device to the server.

[1408] server:

[1409] It confirms that the payment has been completed and uses a sentiment engine to analyze the user's sentiment and collect feedback.

[1410] input:

[1411] Payment completion notification

[1412] output:

[1413] Sentiment analysis results, feedback data

[1414] Specific behavior:

[1415] The server checks the payment data, and then analyzes the user's messages of "enjoyment" and "satisfaction" using an emotion engine. If the satisfaction level is low, feedback is collected and used to improve the system.

[1416] (Application example 2)

[1417] 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."

[1418] This invention relates to a system that efficiently supports the organizer's work for events, especially drinking parties, and increases participant satisfaction. Conventional methods place a heavy burden on the organizer, as scheduling, restaurant selection, and accounting are time-consuming tasks. Furthermore, it is not possible to make proposals that take into account the feelings of participants, making it difficult to hold an event that satisfies everyone. Furthermore, collecting feedback after an event is done manually, which makes it difficult to improve the system for the next event.

[1419] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for coordinating event schedules among multiple participants via a communications network; a generative artificial intelligence (AI) means for collecting participant schedule information and proposing optimal schedules; a means for automatically sending reminder notifications to participants who have not yet responded; a means for proposing event locations via a communications network; a means for automatically making reservations at locations selected from among the proposed locations; an emotion engine means for recognizing participant emotions from text messages or voice input and customizing the proposal based on the emotion information; a means for automatically making reservations at locations selected by participants on a smartphone application; a means for collecting event accounting information and automatically splitting the bill among participants; a means for completing payment among participants in cooperation with a payment application based on the accounting information; and a feedback means for reanalyzing participant emotions after the event and reflecting them in the next proposal. This improves the efficiency of event organizer tasks and enables events that increase the satisfaction of all participants.

[1420] A "communications network" is an infrastructure for transmitting and receiving data, including the Internet and local area networks (LANs).

[1421] "Participant" refers to an individual who attends an event or drinking party.

[1422] "Scheduling" refers to the task of coordinating schedules among multiple participants.

[1423] "Date information" refers to a list of participants' available dates and times.

[1424] "Generative artificial intelligence (AI)" is a system that uses machine learning and natural language processing to analyze data and generate optimal suggestions.

[1425] "Reminder" means a reminder message that is automatically sent to participants who have not responded.

[1426] The "venue" refers to the specific location where the event or drinking party will be held.

[1427] "Automatic booking" refers to the process by which the system automatically makes a booking based on user input.

[1428] An "emotion engine" is a system that analyzes a user's emotions from text messages and voice input, and customizes suggestions based on that information.

[1429] A "smartphone application" is a software program that runs on a smartphone.

[1430] "Accounting information" refers to data on the total amount of an event or drinking party and the amount paid by each participant.

[1431] "Splitting the bill" is the process of calculating the amount each participant will pay based on accounting information.

[1432] A "payment application" is application software for electronically transferring money.

[1433] "Feedback" refers to evaluations and impressions collected from participants after the event.

[1434] This invention is a system for improving the efficiency of event organizer work and increasing participant satisfaction. This system coordinates event schedules, restaurant selection, and accounting among multiple participants via a communications network, and further customizes proposals using an emotion engine to achieve optimal event management that takes participants' emotions into consideration.

[1435] Schedule adjustment

[1436] The server coordinates event dates among participants through a communication application. Specifically, it sends a schedule coordination survey to LINE groups and other messaging groups. Each participant responds to the survey about their available dates, and the information is sent to the server via their device. The server collects the data and suggests optimal dates using generative artificial intelligence (AI) methods. It also automatically sends reminder notifications to participants who have not yet responded.

[1437] Choosing a restaurant

[1438] The server accepts input from participants to suggest locations for the event. Participants enter information such as the event date, budget, food preferences, and location on a communication application. This information is sent to the server via their terminal, and the server uses generative AI to generate a list of appropriate restaurants. Furthermore, it can use an emotion engine means to recognize participants' emotions from text messages and voice inputs and customize the suggestions based on that emotion information. The server also automatically makes reservations at locations selected by the user.

[1439] Accounting and settlement

[1440] After the drinking party is over, the bill information from the bar is sent to the server. This bill information is saved in a database, and the server automatically splits the bill among the participants based on the total amount. The calculation result is notified to the participants via a communication application, and each participant makes payment using a payment application (e.g., an electronic payment application). This payment data is also transferred to the server via the terminal, and the server confirms that the payment has been completed.

[1441] Sentiment Analysis and Feedback

[1442] After the event, the server reanalyzes the participants' emotions and provides feedback to reflect the results in proposals for the next event. Specifically, by using the emotion engine described above again and analyzing the participants' messages and feedback data, it is possible to identify areas for improvement for the next event.

[1443] Examples of concrete examples and prompts

[1444] Specific examples

[1445] 1. Scheduling:

[1446] Send a survey in a group chat asking, "Which of the following days are you free: March 15th, 22nd, or 29th?"

[1447] Send a reminder to those who haven't responded: "If you haven't responded yet, hurry up and respond!"

[1448] 2. Choosing a restaurant:

[1449] The participant enters "March 22nd, budget 5,000 yen, yakiniku, Shinjuku."

[1450] The server uses a generative AI to suggest "Store A, Store B, Store C," and "Store B" is given priority based on the results of sentiment analysis.

[1451] The user selects "Store B" and the reservation is made automatically.

[1452] 3. Accounting:

[1453] After the drinking party, the total amount of 20,000 yen will be divided among the four people, with each person receiving 5,000 yen.

[1454] Each participant pays 5,000 yen using an electronic payment application, and the server confirms that the payment has been completed.

[1455] Prompt Sentence Examples

[1456] Scheduling prompt:

[1457] "When would be a good date for a drinking party?" "March 15th," "March 22nd," "March 29th"

[1458] Shop selection prompt:

[1459] "What's your budget?" "What are your food preferences?" "Where is it?" "Japanese food," "Yakiniku," "Chinese food"

[1460] Payment prompt:

[1461] "Today's bill is 5,000 yen per person. Please pay using the electronic payment application."

[1462] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1463] Step 1:

[1464] (Send schedule adjustment survey)

[1465] The user initiates a schedule adjustment survey on a communication application. At this time, the user inputs candidate dates and sends the candidate date data to the server. The server receives this data and sends the survey message to LINE groups and other messaging groups.

[1466] Input: Candidate dates specified by the user (e.g. March 15th, 22nd, 29th)

[1467] Data processing: The server converts the candidate date data into a message format

[1468] Output: Survey message sent to each participant

[1469] Step 2:

[1470] (Collecting schedule information)

[1471] Each participant clicks on the link in the survey message to answer their free dates. The answer data is sent to the server via their device. The server aggregates this data and stores each participant's free dates in a database.

[1472] Input: Available dates for participants to answer (e.g. March 15th, 22nd)

[1473] Data processing: The server aggregates and integrates individual response data

[1474] Output: Free schedule information of participants stored in the database

[1475] Step 3:

[1476] (Optimal schedule suggestions)

[1477] The server analyzes the collected schedule information using artificial intelligence (AI) to propose the optimal schedule. This AI selects the date that the most participants can attend based on the available dates of all participants.

[1478] Input: Attendee schedule information stored in the database

[1479] Data Calculation: Generative AI for Optimal Schedule Analysis

[1480] Output: Optimal date suggestion (e.g. March 22nd)

[1481] Step 4:

[1482] (Send reminder notifications)

[1483] The server identifies participants who have not responded and automatically sends reminders via LINE groups or other messaging groups.

[1484] Input: Answer status (Answered / Not answered)

[1485] Data processing: Generate reminder notifications based on response status

[1486] Output: Reminder notification message

[1487] Step 5:

[1488] (Suggestions for choosing a restaurant)

[1489] Users input details of the event (budget, food preferences, location, etc.) into the communication application. This information is sent via the device to the server, which then uses generative AI to generate a list of suitable restaurants.

[1490] Input: Event details (e.g., budget 5,000 yen, Yakiniku, Shinjuku)

[1491] Data calculation: Generative AI generates appropriate store lists

[1492] Output: Suggested store list (e.g., Store A, Store B, Store C)

[1493] Step 6:

[1494] (Analysis of emotional information)

[1495] The server uses an emotion engine means to recognize emotion information from the participant's text messages and voice inputs and customizes the suggestions based on the emotion information, for example, analyzing emotions such as "happy" and "delighted."

[1496] Input: Text messages and voice input data

[1497] Data Computation: Emotion Analysis with Emotion Engine

[1498] Output: Customized suggestions

[1499] Step 7:

[1500] (Automatic reservation)

[1501] When the user confirms the restaurant they selected from the list of suggested restaurants, the server automatically makes a reservation for that restaurant. The reservation information is sent to the terminal and a confirmation message is displayed to the user.

[1502] Input: User selected store

[1503] Data processing: Automatic reservation information generation

[1504] Output: Reservation confirmation message

[1505] Step 8:

[1506] (Collection of accounting information)

[1507] After the drinking party is over, the billing information is sent from the bar to the server, which stores this information in a database.

[1508] Input: Accounting information sent from the store (e.g. total amount 20,000 yen)

[1509] Data processing: Saving accounting information

[1510] Output: Accounting information stored in a database

[1511] Step 9:

[1512] (Split the bill)

[1513] The server automatically splits the bill among the participants based on the received accounting information, and the results are communicated via a communication application.

[1514] Input: Accounting information stored in the database

[1515] Data calculation: Calculating the payment amount for each participant

[1516] Output: Notification of split amount (e.g. 5000 yen per person)

[1517] Step 10:

[1518] (Electronic Payment)

[1519] Each participant pays the notified split amount using the electronic payment application. Data indicating the completion of the payment is transferred to the server via the terminal, and the server confirms that the payment has been completed.

[1520] Input: Payment data by each participant

[1521] Data processing: Payment completion status update

[1522] Output: Payment confirmation message

[1523] Step 11:

[1524] (Feedback collection and analysis)

[1525] After the event, the server reanalyzes the participants' emotions and collects feedback to be reflected in proposals for the next event.The emotion engine is used to analyze the participants' messages and feedback data to extract satisfaction levels and areas for improvement.

[1526] Input: Feedback data from participants

[1527] Data Calculation: Reanalysis by Emotion Engine

[1528] Output: Feedback data to be reflected in the next proposal

[1529] 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.

[1530] 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.

[1531] 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.

[1532] [Fourth embodiment]

[1533] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1534] 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.

[1535] 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).

[1536] 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.

[1537] 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.

[1538] 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).

[1539] 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.

[1540] 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.

[1541] 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.

[1542] 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.

[1543] 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.

[1544] 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.

[1545] 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."

[1546] The present invention relates to a drinking party organizer support system that uses a communication application. This system uses a generation AI to provide comprehensive support for scheduling, restaurant selection, and payment. Specific embodiments of the system are described below.

[1547] 1. Schedule adjustment function

[1548] The server has the function of sending a questionnaire for scheduling an event to LINE groups and other communication groups. Each participant answers the questionnaire to indicate their available dates. This response data is sent to the server via the terminal. The server collects this data and proposes the optimal schedule.

[1549] When User A enters and submits their free schedule, the device immediately transfers this information to the server. The server uses a generation AI to analyze the collected schedule information and sends the optimal schedule as a proposal to the LINE group. After that, the server automatically sends reminder notifications to users who have not yet responded.

[1550] 2. Store selection function

[1551] Users enter information such as the date, budget, food preferences, and location of the event on the LINE application. This information is sent to the server via the device. The server uses AI to generate a list of suitable restaurants based on this information and sends it to the LINE group.

[1552] For example, if User B enters "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server will search for Japanese restaurants in Shibuya based on this data and use generation AI to suggest "Restaurant A, Restaurant B, Restaurant C." If User B selects "Restaurant B" from the list, the server will automatically send an instruction to make a reservation at Restaurant B.

[1553] 3. Payment and splitting features

[1554] After the drinking party is over, the billing information from the bar is sent to the server. This information is stored in a database, and the server tallies the total amount and calculates the split between the participants. The calculation result is notified to the LINE group, and payment details are communicated to each user.

[1555] User C receives a notification on the LINE app and makes a payment using a payment application such as PayPay. This payment data is transferred by the device to the server, and the server confirms that the payment has been completed.

[1556] Specific examples

[1557] For example, the date of a drinking party is decided to be "April 1st," and the server uses a generation AI to suggest "Store X, Store Y, Store Z" from among Japanese restaurants in Shibuya. User D selects "Store Y" and the reservation is completed. After the drinking party, a total of 15,000 yen is registered on the server, and the bill is split among five people, at 3,000 yen each. The server sends a notification to the LINE group that "3,000 yen per person," and each user pays 3,000 yen with PayPay.

[1558] This allows event organizers to efficiently and smoothly manage a series of tasks, from scheduling to choosing restaurants and paying the bill. The introduction of this system significantly reduces the burden on event organizers and allows participants to enjoy the event comfortably.

[1559] The processing flow will be explained below.

[1560] 1. Schedule adjustment function

[1561] Step 1: Send the survey

[1562] Server: Create and send a schedule adjustment survey to all participants in the LINE group.

[1563] Device: The survey form is displayed to the user on the LINE app.

[1564] Step 2: Collect responses

[1565] User: Enter your available dates in the survey form and tap the submit button.

[1566] Terminal: Transfers user input to the server.

[1567] Server: Saves the collected response data of each user in a database.

[1568] Step 3: Propose the best schedule

[1569] Server: Based on the collected data, the optimal schedule is calculated using a generative AI.

[1570] Server: Sends the calculation results to the LINE group as a proposal.

[1571] Terminal: Notifies the user of the suggested optimal schedule.

[1572] Step 4: Send a reminder

[1573] Server: Lists participants who have not responded and automatically sends reminder messages.

[1574] Terminal: Display a prompt message to the user.

[1575] 2. Store selection function

[1576] Step 1: Enter your information

[1577] User: Enter necessary information such as dates, budget, food preferences, and location on the LINE app.

[1578] Terminal: Transfers the entered information to the server.

[1579] Step 2: Generate a list of stores

[1580] Server: Uses generative AI to create a list of appropriate stores based on the input information.

[1581] Server: Send the created list to the LINE group.

[1582] Terminal: Shows the user a list of stores.

[1583] Step 3: Confirm your reservation

[1584] User: Select the desired store from the list of suggested stores.

[1585] Terminal: Transfers the selection results to the server.

[1586] Server: Automatically executes the reservation procedure for the selected restaurant.

[1587] 3. Payment and splitting features

[1588] Step 1: Collect your billing information

[1589] Server: Receives billing information from the restaurant on the day of the drinking party.

[1590] Server: Stores the collected accounting information in a database.

[1591] Step 2: Split the bill

[1592] Server: Calculate the total amount divided by the number of people.

[1593] Server: Notify the LINE group of the calculation results.

[1594] Terminal: Display a notification of the split amount to the user.

[1595] Step 3: Checkout

[1596] User: Checks the notification and pays his / her share using the payment application.

[1597] Terminal: Transfers payment data to the server.

[1598] Server: Works with the payment application to verify payments from each user.

[1599] This allows the organizer to efficiently and smoothly carry out the entire process of the drinking party, from preparation to its end.

[1600] Example 1

[1601] 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."

[1602] With conventional event management systems, a series of tasks such as scheduling, selecting restaurants, splitting the bill, and settling the payment required a lot of time and effort, placing a heavy burden on the organizer. Furthermore, communication between participants was sometimes not smooth, which could lead to delays in planning and execution of the event.

[1603] 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.

[1604] In this invention, the server includes: means for coordinating event dates among multiple participants via a communications network; a generating artificial intelligence (AI) means for collecting schedule information from the participants and proposing the optimal schedule; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing event locations via the communications network; means for automatically making reservations at locations selected from the proposed locations; means for collecting accounting information for the event and automatically splitting the bill among participants; and means for completing payment among participants in cooperation with a payment application based on the accounting information. This automates the entire process from scheduling to restaurant selection, accounting, and payment, significantly reducing the burden on event organizers and enabling smoother event planning and execution.

[1605] A "communications network" refers to a network that allows computers and terminals to exchange information with each other. This includes the Internet and local area networks (LANs).

[1606] "Participant" means any person or group who intends to attend the Event and who is involved in scheduling and selecting the location of the Event.

[1607] "Generative artificial intelligence (AI)" refers to a technology that analyzes large amounts of data, finds patterns, and supports decision-making. In this invention, it plays a role in suggesting optimal dates and restaurant options.

[1608] A "reminder" is a warning message that alerts users to take a specific action, such as a notification to remind unanswered participants to reschedule.

[1609] "Event location" refers to the physical or virtual location where the event takes place, such as a restaurant, conference room, or online meeting platform.

[1610] "Financial Information" means detailed information about costs and expenses related to an Event, including data necessary to calculate totals and split bills at restaurants.

[1611] "Payment application" means software that enables users to make or receive payments online or through a mobile device. Examples include e-wallet apps and mobile banking apps.

[1612] This invention relates to a system for efficiently managing events over a communication network. Specific components of the system include a server, terminals, and users. The purpose of this invention is to provide a series of functions using generative AI models to facilitate smooth communication between participants and event implementation.

[1613] First, the server provides a means for multiple participants to coordinate event dates via a communication network. Specifically, the server sends a questionnaire for scheduling an event using a LINE group or other communication platform. Participants respond with their available dates using their devices, and this information is sent to the server.

[1614] Next, the server collects the participants' schedule information and uses a generation AI to suggest the best schedule. This generation AI analyzes a large amount of data to find the best schedule for all participants. Reminder notifications are also automatically sent to participants who have not yet responded. These notifications include a reminder message and encourage them to respond again.

[1615] Furthermore, the server has a means to suggest locations for events. Users input requirements such as event dates, budget, food preferences, and location through the LINE app. The input information is sent to the server via the device, and the server uses generation AI to generate a list of appropriate restaurants based on this information. This list is sent to the LINE group, allowing the user to select the restaurant of their choice.

[1616] When a user selects a store, the server automatically makes a reservation at the selected store. This eliminates the need for reservations and allows for smooth seating arrangements. After the event ends, the store sends accounting information to the server. This information is stored in a database, and the server tallies the total amount and calculates the split between participants.

[1617] Finally, the calculation result is notified to the LINE group, and payment details are sent to each user. Users receive a notification on the LINE app and make the payment using a payment app such as PayPay. The payment data is transferred by the device to the server, and the server confirms that the payment has been completed.

[1618] Examples:

[1619] For example, when User A enters his or her available dates of "October 5th, 8th, and 10th" in the LINE app and submits them, the server collects this information, analyzes it using the generation AI, and suggests "October 8th" as the optimal date. If User B then enters information such as "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server suggests "Restaurant A, Restaurant B, and Restaurant C," and User B selects "Restaurant B," completing the reservation. After the drinking party, the total amount of 15,000 yen is registered in the database, and the bill is split among the five people at 3,000 yen each, and this is notified to the LINE group. Each user pays 3,000 yen with PayPay, and the server sends a completion notification.

[1620] Example prompt sentence:

[1621] "I'd like to schedule a drinking party in October. Please choose any days that are free. For example, October 5th, 8th, and 10th."

[1622] "Please find a Japanese restaurant in Shibuya on March 15th that costs under 5,000 yen."

[1623] "The total cost of the drinking party is 15,000 yen. We will split it among five people, so please pay 3,000 yen per person with PayPay."

[1624] This allows the organizer to efficiently and smoothly manage a series of tasks, from scheduling to choosing a restaurant and paying the bill, allowing participants to enjoy the event comfortably.

[1625] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1626] Processing steps for the schedule adjustment function

[1627] Step 1:

[1628] The server sends a questionnaire for scheduling an event to a LINE group or other communication group via a communication network. The input includes a list of participants and the contents of the questionnaire. Based on this, the server generates a questionnaire message and sends it to the group. The output is the sent questionnaire message.

[1629] Step 2:

[1630] Users enter their free dates in a questionnaire format through the LINE app. For example, User A enters "October 5th, 8th, and 10th." This data is sent as input to the device, which then forwards the information to the server. The output is the schedule information sent to the server.

[1631] Step 3:

[1632] The server collects schedule data sent by all users. The input includes individual schedule information from participants. The server analyzes this data using a generative AI to calculate the optimal schedule. The output is the optimal schedule information.

[1633] Step 4:

[1634] The server sends the analysis results as a proposal to the LINE group and notifies participants. The input required is the optimal schedule information calculated by the generation AI. The server forms this as a proposal message and sends it to the group. The output is the proposal message for the optimal schedule that was sent.

[1635] Step 5:

[1636] The server automatically sends reminder notifications to participants who have not yet responded. The input includes a list of participants who have not yet responded. Based on this, the server generates and sends a reminder message. The output is the sent reminder message. Specifically, the message is sent using the reminder notification function.

[1637] Store selection function processing steps

[1638] Step 1:

[1639] Users input information such as the date, budget, food preferences, and location of an event through the LINE app. For example, User B inputs "March 15th, budget 5,000 yen, Japanese food, Shibuya." This data is sent to the server via the device. The input is the event information entered by the user, and the output is the event information sent to the server.

[1640] Step 2:

[1641] The server uses a generative AI to generate a list of suitable stores based on the collected event information. The input includes the event information and a generative AI model. The generative AI analyzes this information and creates a list of candidate stores. The output is the generated store list.

[1642] Step 3:

[1643] The server sends the generated store list to the LINE group, and the user selects the desired store from the proposed list. The input includes the generated store list. The server sends this list and waits for a reply from the user. The output is the user's selection information.

[1644] Step 4:

[1645] When the user selects a store, the server automatically makes a reservation at the selected store. The input includes the user's selection information and store information. The server processes the reservation based on this and completes the reservation. The output is a notification that the reservation is complete.

[1646] Payment and split payment processing steps

[1647] Step 1:

[1648] When the drinking party ends, the billing information from the bar is sent to the server. The input includes the billing information. The server stores it in a database. The output is the stored billing information.

[1649] Step 2:

[1650] The server calculates the total amount based on the accounting information and splits the bill among the participants. The input includes the saved accounting information and the list of participants. The server performs calculations based on this information and calculates the split amount. The output is the calculated split amount.

[1651] Step 3:

[1652] The server notifies the LINE group of the calculation result and conveys payment details to each user. The input includes the calculated split amount. The server generates this as a notification message and sends it to the group. The output is the payment notification sent.

[1653] Step 4:

[1654] The user receives a notification on the LINE app and makes a payment using a payment app such as PayPay. The input includes the notified payment details. The user proceeds with the payment process according to this, and the payment data is transferred to the server by the device. The output is the payment data sent to the server.

[1655] Step 5:

[1656] The server verifies the payment data and notifies each user that the payment has been completed. The input includes payment data. The server verifies this, generates a payment completion notification, and sends it. The output is the payment completion notification that was sent. Specifically, the confirmation operation is performed using the payment confirmation function.

[1657] In this way, detailed data processing and data calculations are performed at each processing step, making the management of a series of events more efficient for the entire system.

[1658] (Application example 1)

[1659] 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."

[1660] Conventional event management systems involve complicated processes such as coordinating schedules among participants, selecting restaurants, managing accounting information, and making payments, placing a heavy burden on event organizers in particular. Furthermore, sufficient measures are often not implemented to ensure the safe handling of participants' personal information and accounting information. This makes it difficult for all participants to enjoy the event with peace of mind. There is a need for a system that can solve these issues and provide efficient and safe event management.

[1661] 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.

[1662] In this invention, the server includes: means for coordinating event schedules among multiple participants via a communications network; a generating artificial intelligence (AI) means for collecting schedule information from the participants and proposing optimal schedules; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing event locations via the communications network; means for automatically making reservations at locations selected from the proposed locations; means for collecting accounting information for the event and automatically splitting the bill among participants; means for completing payments among participants in cooperation with a payment application based on the accounting information; and means for encrypting and storing participant data and using secure communications when accessing the data. This significantly reduces the burden on the organizer and allows all participants to enjoy the event with peace of mind.

[1663] A "communications network" is an infrastructure for exchanging data between multiple terminals, and includes the Internet and local area networks.

[1664] "Participants" refers to multiple users who participate in an event.

[1665] "Date scheduling" refers to the process of surveying and arranging participants' availability to determine the best date and time for an event.

[1666] "Generative artificial intelligence (AI)" is a technology that uses machine learning or data analysis techniques to derive optimal solutions based on large amounts of data.

[1667] A "reminder" is an automatic notification message sent to participants who have not yet responded to encourage them to respond.

[1668] "Venue" means the physical location or facilities used for the actual conduct of an Event.

[1669] A "reservation" is a procedure for reserving a specific location at a specific date and time.

[1670] "Accounting information" is data that records all expenses related to the event.

[1671] "Bill-splitting" is the process of dividing the total cost equally among the participants.

[1672] A "payment application" is software that enables online payments.

[1673] "Encryption" is a process that transforms data using a specific algorithm to prevent it from being deciphered by third parties.

[1674] "Secure communications" refers to communications protocols that use technology to prevent unauthorized access and tampering when sending and receiving data.

[1675] The present invention relates to a system for managing events efficiently and securely over a communications network. This system provides a series of functions, including scheduling, restaurant selection, and payment, and securely manages participant data.

[1676] Hardware and software used

[1677] Server: Collects, analyzes, suggests, and encrypts data.

[1678] Terminal: The device through which a user enters data (e.g., smartphone, tablet, PC).

[1679] Generative AI model: Used for scheduling and restaurant selection.

[1680] LINE API: Used as a communication application.

[1681] PayPay API: Provides payment functions.

[1682] Encryption technology: used to protect participant data (e.g., AES encryption).

[1683] Program processing overview

[1684] The server receives information entered by the user, such as dates, budget, preferences, and location, and encrypts and stores it in a database. Based on this data, a generative AI model is used to generate a list of optimal dates and restaurants, which are then proposed to participants. Reminders are also automatically sent to participants who have not yet responded using the LINE API. Event reservations are automatically made at the restaurant selected by the user from the proposed restaurant list.

[1685] After the drinking party ends, the server receives the bill from the bar and automatically splits the bill based on this information. The calculation results are notified to all participants using the LINE API, and payment is made safely and quickly via the PayPay API. All data access uses encryption technology and secure communication protocols to prevent unauthorized access and data leaks.

[1686] Specific examples

[1687] For example, if the event date is set for "2023-04-01," the server will suggest "Japanese restaurants X, Y, and Z in Shibuya" based on the participants' preferences. All of this information is encrypted and securely stored. Reservations at "restaurant Y" are automatically made based on the participants' selections. Furthermore, the total bill of 15,000 yen after the drinking party is split among five people, with payment notifications sent to each person via LINE. Each person can pay securely using PayPay.

[1688] Prompt Sentence Examples

[1689] The following data is input into the generative AI model to generate a list of optimal dates and restaurants:

[1690] {

[1691] "group_id": "sample_group_id",

[1692] "availability": {"userA": "2023-04-01", "userB": "2023-04-02"},

[1693] "preferences": {

[1694] "date": "2023-04-01",

[1695] "budget": 5000,

[1696] "cuisine": "Japanese food",

[1697] "location": "Shibuya"

[1698] }

[1699] }

[1700] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1701] Step 1:

[1702] The server receives the schedule information entered by the user through the LINE API. It collects each user's free schedule data and sends it to the server via a secure method. The input is the user's schedule information, and the server stores the information in a database based on this.

[1703] Step 2:

[1704] The server uses a generative AI model to analyze the optimal schedule based on the collected schedule information. This analysis results in a proposal for a schedule that allows the most participants to participate conveniently. The input is each user's schedule data, and the generative AI model analyzes the data and outputs the optimal schedule.

[1705] Step 3:

[1706] The server notifies all participants of the optimal schedule obtained as a result of the analysis using the LINE API. It also automatically sends reminder notifications to users who have not yet responded. The input is the optimal schedule output from the generative AI model, and this is notified using the LINE API.

[1707] Step 4:

[1708] Users enter information such as the date, budget, preferences, and location of the event on the LINE application. The device collects this data and sends it to the server using encryption technology. The input is the user's event details, and the output is encrypted data.

[1709] Step 5:

[1710] The server analyzes the encrypted data and uses a generative AI model to generate a list of suitable venues (e.g., restaurants), which it then recommends to the user. The input is the encrypted event details, and the server outputs a list of suggested venues based on the analysis by the generative AI model.

[1711] Step 6:

[1712] Participants select from the proposed locations, and the server automatically makes a reservation for the selected location. The input is the user's selection, and the output is a reservation completion notification.

[1713] Step 7:

[1714] After the drinking party, the bar sends the billing information to the server. The server collects this information and automatically splits the bill among the participants. The input is the billing information from the bar, and the output is the split amount for each participant.

[1715] Step 8:

[1716] The server notifies the participants of the split calculation results using the LINE API. Participants receive the notification on their own devices and make payments accordingly. The input is the split calculation result, and the output is the notification to each participant.

[1717] Step 9:

[1718] After receiving the notification, the participant makes the payment using the PayPay API. The payment data is sent from the terminal to the server, and the server confirms the completion of the payment. The input is the payment data from the participant, and the output is a payment completion notification.

[1719] Step 10:

[1720] The server stores all data using encryption technology and uses secure communication protocols such as SSH when accessing data, preventing unauthorized access and data leakage. The input is all processed data, and the output is encrypted data storage.

[1721] 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.

[1722] This invention is a system that uses communication applications to support the organizer of events, especially drinking parties, and utilizes generative AI and an emotion engine to arrange dates, select restaurants, and make payments. This system recognizes the emotions of participants and makes optimal suggestions based on them, thereby increasing user satisfaction.

[1723] 1. Schedule adjustment function

[1724] The server has the function of sending a questionnaire for scheduling an event to LINE groups and other communication groups. Each participant answers the questionnaire to indicate their available dates. This response data is sent to the server via their device. The server collects this data and proposes the optimal date. In addition, the server automatically sends reminder notifications to users who have not yet responded.

[1725] For example, when User A enters and submits their free schedule, the information is transferred to the server via their device. The server then uses the generation AI to analyze this information and propose optimal dates to the LINE group. At the same time, reminders are sent to users who have not yet responded, ensuring that everyone has responded.

[1726] 2. Store selection function

[1727] Users enter information such as the date, budget, food preferences, and location of the event on the LINE application. This information is sent to the server via the device. The server uses generative AI to generate a list of appropriate restaurants based on this information. It also uses an emotion engine to recognize the user's emotions from text messages and voice input, and customizes suggestions based on that emotional information.

[1728] For example, if User B enters "March 15th, budget 5,000 yen, Japanese food, Shibuya," the server will use the generation AI to suggest "Restaurant A, Restaurant B, Restaurant C" based on this data. At the same time, if the emotion engine recognizes emotions such as "looking happy" or "delighted" from the user's past messages and voice input, it will prioritize suggesting particularly popular restaurants or restaurants with good reviews. If User B selects "Restaurant B," the server will automatically make a reservation at Restaurant B based on this information.

[1729] 3. Payment and splitting features

[1730] After the drinking party is over, the bill information from the bar is sent to the server. This bill information is saved in a database, and the server calculates the total amount divided by the number of people. The calculation result is notified to the LINE group, and payment details are communicated to each user.

[1731] User C receives a notification on the LINE app and makes a payment using a payment application such as PayPay. This payment data is transferred by the device to the server, which then confirms that the payment has been completed. The emotion engine can analyze the user's emotions after payment and collect feedback for improvement if satisfaction is low.

[1732] Specific examples

[1733] For example, if the date of a drinking party is decided to be "April 1st," the server uses a generation AI to suggest "Store X, Store Y, and Store Z" from among Japanese restaurants in Shibuya. The emotion engine recognizes that User D said in a past message that he "likes restaurants with a nice atmosphere," and prioritizes "Store Y," which has a particularly good atmosphere, on the list. User D selects "Store Y," and the reservation is completed. After the drinking party, a total of 15,000 yen is registered on the server, and the bill is split among five people, at 3,000 yen each. The server sends a notification to the LINE group that "3,000 yen per person," and each user pays 3,000 yen with PayPay. The emotion engine analyzes subsequent messages and determines whether the user is satisfied.

[1734] In this way, event organizers can utilize the emotion engine to efficiently manage events while increasing participant satisfaction.

[1735] The processing flow will be explained below.

[1736] 1. Schedule adjustment function

[1737] Step 1: Send the survey

[1738] Server: Create and send a schedule adjustment survey to all participants in the LINE group.

[1739] Device: The survey form is displayed to the user on the LINE app.

[1740] Step 2: Collect responses

[1741] User: Enter your available dates in the survey form and tap the submit button.

[1742] Terminal: Transfers user input to the server.

[1743] Server: Saves the collected response data of each user in a database.

[1744] Step 3: Propose the best schedule

[1745] Server: Based on the collected data, the optimal schedule is calculated using a generative AI.

[1746] Server: Sends the calculation results to the LINE group as a proposal.

[1747] Terminal: Notifies the user of the suggested optimal schedule.

[1748] Step 4: Send a reminder

[1749] Server: Lists participants who have not responded and automatically sends reminder messages.

[1750] Terminal: Display a prompt message to the user.

[1751] 2. Store selection function

[1752] Step 1: Enter your information

[1753] User: Enter necessary information such as dates, budget, food preferences, and location on the LINE app.

[1754] Terminal: Transfers the entered information to the server.

[1755] Step 2: Sentiment Analysis

[1756] Server: Uses an emotion engine to recognize the user's emotions from the input message and voice data.

[1757] Server: Adjusts the content of suggestions based on the recognized emotion data.

[1758] Step 3: Generate a list of stores

[1759] Server: Uses generative AI to create a list of relevant businesses based on input information and sentiment data.

[1760] Server: Send the created list to the LINE group.

[1761] Terminal: Shows the user a list of stores.

[1762] Step 4: Confirm your reservation

[1763] User: Select the desired store from the list of suggested stores.

[1764] Terminal: Transfers the selection results to the server.

[1765] Server: Automatically executes the reservation procedure for the selected restaurant.

[1766] 3. Payment and splitting features

[1767] Step 1: Collect your billing information

[1768] Server: Receives billing information from the restaurant on the day of the drinking party.

[1769] Server: Stores the collected accounting information in a database.

[1770] Step 2: Split the bill

[1771] Server: Calculate the total amount divided by the number of people.

[1772] Server: Notify the LINE group of the calculation results.

[1773] Terminal: Display a notification of the split amount to the user.

[1774] Step 3: Checkout

[1775] User: Checks the notification and pays his / her share using the payment application.

[1776] Terminal: Transfers payment data to the server.

[1777] Server: Works with the payment application to verify payments from each user.

[1778] Step 4: Feedback after sentiment analysis

[1779] Server: Analyzes the user's messages and behavior after payment using an emotion engine.

[1780] Server: If satisfaction is low, collect feedback to help improve the system.

[1781] For example, if User D previously messaged, "I like places with a good atmosphere," the emotion engine would recognize this, and the generation AI would prioritize those establishments in the list. Similarly, if User D messaged after a drinking party saying, "It was fun," the emotion engine would analyze this, and the server would evaluate the high level of satisfaction. In this way, the emotion engine can be used to increase participant satisfaction.

[1782] Example 2

[1783] 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."

[1784] Traditional event planning tasks require a great deal of time and effort, including coordinating schedules for multiple participants, choosing restaurants, and handling payments, placing a heavy burden on event organizers. Furthermore, because it is not possible to make optimal proposals that take into account the feelings of participants, user satisfaction often declines. In particular, the complicated process of following up with non-respondents and processing payments is problematic.

[1785] The specific processing by the specific 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 coordinating the event schedule among multiple participants via a communications network; a generative artificial intelligence (AI) means for collecting schedule information of the participants and proposing an optimal schedule; means for automatically sending reminder notifications to participants who have not yet responded; means for proposing a venue for the event via the communications network; means for automatically making a reservation at a venue selected from the proposed venues; means for collecting accounting information for the event and automatically splitting the bill among participants; means for completing payment among participants in cooperation with a payment application based on the accounting information; and an emotion engine means for recognizing participants' emotions and customizing the proposal content based on the emotion information. This makes it possible to improve the efficiency of event organizer work and significantly improve participant satisfaction.

[1786] A "communications network" is an infrastructure for sending and receiving data between multiple devices and computers, such as the Internet or a mobile phone network.

[1787] "Participant" means any person who intends to participate in an Event.

[1788] "Date Information" is availability information provided by participants regarding the date and time of the event.

[1789] A "generative artificial intelligence (AI) means" is a system that uses artificial intelligence technology to generate optimal proposals based on data collected from participants.

[1790] A "reminder notification" is a notification that is automatically sent to participants who have not yet responded, encouraging them to respond.

[1791] "Location" means the geographic location or facility where the Event actually takes place.

[1792] "Reservation" is a procedure that participants take in advance to secure the venue of their choice.

[1793] "Accounting information" refers to information regarding all expenses incurred after the event has ended.

[1794] "Split the bill" is a process of calculating the amount each participant should pay based on accounting information.

[1795] "Payment Application" means software that enables Participants to complete payments electronically.

[1796] An "emotion engine" is a software technology that recognizes a user's emotions and optimizes the content of suggestions based on those emotions.

[1797] This invention is a system that automates the event planning process via a communications network. The system utilizes a generative AI model and an emotion engine to efficiently coordinate schedules, select restaurants, and make payments. An example implementation of this system is described in detail below.

[1798] Schedule adjustment function

[1799] server:

[1800] The server sends a schedule-setting questionnaire to multiple participants. This questionnaire is sent via a communication network (e.g., the Internet or a mobile phone network). Each participant responds with their availability, and this information is sent to the server via their device. The server uses a generative AI model based on the collected schedule information to propose the optimal schedule. It also automatically sends reminder notifications to participants who have not responded.

[1801] (Example)

[1802] If User A answers "March 15th," this date information is sent to the server via the device. The server collects all responses and calculates the optimal date using a generative AI model. For example, if "March 20th" is determined to be optimal, the server will suggest that date to the LINE group. A reminder notification will be automatically sent to users who have not yet responded.

[1803] Shop selection function

[1804] User:

[1805] Users input requirements such as event dates, budget, food preferences, and location via a communication application (e.g., LINE). The input information is sent to the server via the terminal.

[1806] server:

[1807] The server uses a generative AI model based on the requirements information it receives to generate a list of suitable restaurants. It then uses an emotion engine to recognize the user's emotions and customizes the suggestions based on those emotions. For example, if the user indicates emotions such as "fun" or "happy" from past messages or voice input, restaurants with particularly good reputations or high reviews will be ranked high on the suggestion list.

[1808] (Example)

[1809] When User B enters "budget 5,000 yen, Japanese food, Shibuya," this information is sent from the device to the server. The server uses a generative AI model to suggest "Store A, Store B, Store C." At the same time, the emotion engine analyzes the user's emotions, and if it recognizes that the restaurant "looks fun," it prioritizes suggestions of restaurants with particularly good reviews.

[1810] Payment and split payment function

[1811] server:

[1812] After the event is over, the restaurant sends the billing information to the server. This billing information is stored in a database, and the server calculates the total amount divided by the number of people. The server then notifies each participant of the split amount via a communication application.

[1813] User:

[1814] The user receives a notification and makes a payment through an electronic payment application (e.g., PayPay). The payment information is sent from the terminal to the server, and the server confirms that the payment has been completed. The emotion engine analyzes the user's emotions after payment and collects feedback if the user is not satisfied.

[1815] (Example)

[1816] After the drinking party ends, the total bill of 15,000 yen is registered on the server. Based on this, the server calculates the amount per person to be 3,000 yen when divided among five people and notifies each user. When User C pays 3,000 yen with PayPay, this information is sent to the server and the payment is completed. The server uses an emotion engine to analyze messages such as "It was fun" and "I was satisfied" and confirm the user's level of satisfaction.

[1817] Prompt Sentence Examples

[1818] "We are organizing an upcoming event. To make our work more efficient, we would like to develop a system that utilizes generative AI models and an emotion engine. This system has the following requirements:

[1819] Use a communication application to coordinate schedules.

[1820] Choose a restaurant based on your budget, food preferences, and location.

[1821] The system automatically calculates the split and notifies you.

[1822] Maximize user satisfaction using an emotion engine.

[1823] In this way, the invention improves the efficiency of organizing tasks and participant satisfaction.

[1824] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1825] System processing steps

[1826] Step 1:

[1827] Create and send a scheduling survey

[1828] server:

[1829] The server automatically generates a survey for scheduling an event using the LINE API and sends it to the LINE group. The survey includes options for dates that users can select.

[1830] input:

[1831] Possible date for the event

[1832] output:

[1833] A scheduling survey sent to users

[1834] Specific behavior:

[1835] The server generates a survey that asks users to "choose a convenient date between March and April" and sends it via the LINE API.

[1836] Step 2:

[1837] Collection of responses to schedule adjustment questionnaires and proposals

[1838] User:

[1839] Each participant answers the questionnaire they received, which includes the user's free days.

[1840] input:

[1841] User's available schedule

[1842] output:

[1843] Response data sent to the server

[1844] Specific behavior:

[1845] User A enters his free date as "March 15th" and presses the send button. The information is transferred from the device to the server.

[1846] server:

[1847] The system collects response data sent via devices and uses a generative AI model to suggest optimal dates, while also sending reminder notifications to users who have not yet responded.

[1848] input:

[1849] Response data for each participant

[1850] output:

[1851] Optimal schedule suggestions and reminder notifications

[1852] Specific behavior:

[1853] If the server determines that March 20th is the best date based on the response data collected, it will notify the LINE group of the result. Users who have not yet responded will receive a reminder to respond.

[1854] Step 3:

[1855] Enter information to select a restaurant

[1856] User:

[1857] Use the LINE application to enter and submit requirements such as the event date, budget, food preferences, and location.

[1858] input:

[1859] Requirements such as dates, budget, food preferences, location, etc.

[1860] output:

[1861] Requirement data sent to the server

[1862] Specific behavior:

[1863] User B enters "March 20th, budget 5000 yen, Japanese food, Shibuya" and presses the send button. This information is sent from the device to the server.

[1864] Step 4:

[1865] Restaurant list generation and suggestions

[1866] server:

[1867] Based on the submitted requirements, a generative AI model is used to generate an appropriate restaurant list, while an emotion engine is used to analyze the user's emotions and customize the recommendations.

[1868] input:

[1869] Requirement Data

[1870] output:

[1871] Suggested restaurant list

[1872] Specific behavior:

[1873] Based on the requirements of "budget 5,000 yen, Japanese food, Shibuya," the server generates a list of "Store A, Store B, Store C" and suggests them to the LINE group. At the same time, the emotion engine recognizes the user's emotion of "looks fun" and places particularly popular stores at the top of the list.

[1874] Step 5:

[1875] Restaurant selection and reservations

[1876] User:

[1877] Select the appropriate restaurant from the list of suggested restaurants.

[1878] input:

[1879] User Selection

[1880] output:

[1881] Selection data sent to the server

[1882] Specific behavior:

[1883] User B selects "Store B" and sends the information to the server.

[1884] server:

[1885] Based on the user's selection, reservations are automatically made at selected stores.

[1886] input:

[1887] Selected Data

[1888] output:

[1889] Reservation confirmation

[1890] Specific behavior:

[1891] The server connects to Store B's reservation system and automatically confirms the reservation.

[1892] Step 6:

[1893] Registering accounting information and splitting the bill

[1894] server:

[1895] After the event, the restaurant sends accounting information, which is then stored in a database and split according to the number of participants.

[1896] input:

[1897] Accounting Information

[1898] output:

[1899] Split amount

[1900] Specific behavior:

[1901] The restaurant sends billing information totaling 15,000 yen, and the server saves this data in a database. Dividing this by five people results in 3,000 yen per person, so the server notifies the LINE group of the result.

[1902] Step 7:

[1903] Payment and feedback collection

[1904] User:

[1905] Receive notification of the split amount and make payment using your electronic payment application.

[1906] input:

[1907] Split amount notification

[1908] output:

[1909] Payment completion notification

[1910] Specific behavior:

[1911] User C receives the LINE notification and pays 3,000 yen using an electronic payment application. This payment data is sent from the device to the server.

[1912] server:

[1913] It confirms that the payment has been completed and uses a sentiment engine to analyze the user's sentiment and collect feedback.

[1914] input:

[1915] Payment completion notification

[1916] output:

[1917] Sentiment analysis results, feedback data

[1918] Specific behavior:

[1919] The server checks the payment data, and then analyzes the user's messages of "enjoyment" and "satisfaction" using an emotion engine. If the satisfaction level is low, feedback is collected and used to improve the system.

[1920] (Application example 2)

[1921] 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."

[1922] This invention relates to a system that efficiently supports the organizer's work for events, especially drinking parties, and increases participant satisfaction. Conventional methods place a heavy burden on the organizer, as scheduling, restaurant selection, and accounting are time-consuming tasks. Furthermore, it is not possible to make proposals that take into account the feelings of participants, making it difficult to hold an event that satisfies everyone. Furthermore, collecting feedback after an event is done manually, which makes it difficult to improve the system for the next event.

[1923] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for coordinating event schedules among multiple participants via a communications network; a generative artificial intelligence (AI) means for collecting participant schedule information and proposing optimal schedules; a means for automatically sending reminder notifications to participants who have not yet responded; a means for proposing event locations via a communications network; a means for automatically making reservations at locations selected from among the proposed locations; an emotion engine means for recognizing participant emotions from text messages or voice input and customizing the proposal based on the emotion information; a means for automatically making reservations at locations selected by participants on a smartphone application; a means for collecting event accounting information and automatically splitting the bill among participants; a means for completing payment among participants in cooperation with a payment application based on the accounting information; and a feedback means for reanalyzing participant emotions after the event and reflecting them in the next proposal. This improves the efficiency of event organizer tasks and enables events that increase the satisfaction of all participants.

[1924] A "communications network" is an infrastructure for transmitting and receiving data, including the Internet and local area networks (LANs).

[1925] "Participant" refers to an individual who attends an event or drinking party.

[1926] "Scheduling" refers to the task of coordinating schedules among multiple participants.

[1927] "Date information" refers to a list of participants' available dates and times.

[1928] "Generative artificial intelligence (AI)" is a system that uses machine learning and natural language processing to analyze data and generate optimal suggestions.

[1929] "Reminder" means a reminder message that is automatically sent to participants who have not responded.

[1930] The "venue" refers to the specific location where the event or drinking party will be held.

[1931] "Automatic booking" refers to the process by which the system automatically makes a booking based on user input.

[1932] An "emotion engine" is a system that analyzes a user's emotions from text messages and voice input, and customizes suggestions based on that information.

[1933] A "smartphone application" is a software program that runs on a smartphone.

[1934] "Accounting information" refers to data on the total amount of an event or drinking party and the amount paid by each participant.

[1935] "Splitting the bill" is the process of calculating the amount each participant will pay based on accounting information.

[1936] A "payment application" is application software for electronically transferring money.

[1937] "Feedback" refers to evaluations and impressions collected from participants after the event.

[1938] This invention is a system for improving the efficiency of event organizer work and increasing participant satisfaction. This system coordinates event schedules, restaurant selection, and accounting among multiple participants via a communications network, and further customizes proposals using an emotion engine to achieve optimal event management that takes participants' emotions into consideration.

[1939] Schedule adjustment

[1940] The server coordinates event dates among participants through a communication application. Specifically, it sends a schedule coordination survey to LINE groups and other messaging groups. Each participant responds to the survey about their available dates, and the information is sent to the server via their device. The server collects the data and suggests optimal dates using generative artificial intelligence (AI) methods. It also automatically sends reminder notifications to participants who have not yet responded.

[1941] Choosing a restaurant

[1942] The server accepts input from participants to suggest locations for the event. Participants enter information such as the event date, budget, food preferences, and location on a communication application. This information is sent to the server via their terminal, and the server uses generative AI to generate a list of appropriate restaurants. Furthermore, it can use an emotion engine means to recognize participants' emotions from text messages and voice inputs and customize the suggestions based on that emotion information. The server also automatically makes reservations at locations selected by the user.

[1943] Accounting and settlement

[1944] After the drinking party is over, the bill information from the bar is sent to the server. This bill information is saved in a database, and the server automatically splits the bill among the participants based on the total amount. The calculation result is notified to the participants via a communication application, and each participant makes payment using a payment application (e.g., an electronic payment application). This payment data is also transferred to the server via the terminal, and the server confirms that the payment has been completed.

[1945] Sentiment Analysis and Feedback

[1946] After the event, the server reanalyzes the participants' emotions and provides feedback to reflect the results in proposals for the next event. Specifically, by using the emotion engine described above again and analyzing the participants' messages and feedback data, it is possible to identify areas for improvement for the next event.

[1947] Examples of concrete examples and prompts

[1948] Specific examples

[1949] 1. Scheduling:

[1950] Send a survey in a group chat asking, "Which of the following days are you free: March 15th, 22nd, or 29th?"

[1951] Send a reminder to those who haven't responded: "If you haven't responded yet, hurry up and respond!"

[1952] 2. Choosing a restaurant:

[1953] The participant enters "March 22nd, budget 5,000 yen, yakiniku, Shinjuku."

[1954] The server uses a generative AI to suggest "Store A, Store B, Store C," and "Store B" is given priority based on the results of sentiment analysis.

[1955] The user selects "Store B" and the reservation is made automatically.

[1956] 3. Accounting:

[1957] After the drinking party, the total amount of 20,000 yen will be divided among the four people, with each person receiving 5,000 yen.

[1958] Each participant pays 5,000 yen using an electronic payment application, and the server confirms that the payment has been completed.

[1959] Prompt Sentence Examples

[1960] Scheduling prompt:

[1961] "When would be a good date for a drinking party?" "March 15th," "March 22nd," "March 29th"

[1962] Shop selection prompt:

[1963] "What's your budget?" "What are your food preferences?" "Where is it?" "Japanese food," "Yakiniku," "Chinese food"

[1964] Payment prompt:

[1965] "Today's bill is 5,000 yen per person. Please pay using the electronic payment application."

[1966] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1967] Step 1:

[1968] (Send schedule adjustment survey)

[1969] The user initiates a schedule adjustment survey on a communication application. At this time, the user inputs candidate dates and sends the candidate date data to the server. The server receives this data and sends the survey message to LINE groups and other messaging groups.

[1970] Input: Candidate dates specified by the user (e.g. March 15th, 22nd, 29th)

[1971] Data processing: The server converts the candidate date data into a message format

[1972] Output: Survey message sent to each participant

[1973] Step 2:

[1974] (Collecting schedule information)

[1975] Each participant clicks on the link in the survey message to answer their free dates. The answer data is sent to the server via their device. The server aggregates this data and stores each participant's free dates in a database.

[1976] Input: Available dates for participants to answer (e.g. March 15th, 22nd)

[1977] Data processing: The server aggregates and integrates individual response data

[1978] Output: Free schedule information of participants stored in the database

[1979] Step 3:

[1980] (Optimal schedule suggestions)

[1981] The server analyzes the collected schedule information using artificial intelligence (AI) to propose the optimal schedule. This AI selects the date that the most participants can attend based on the available dates of all participants.

[1982] Input: Attendee schedule information stored in the database

[1983] Data Calculation: Generative AI for Optimal Schedule Analysis

[1984] Output: Optimal date suggestion (e.g. March 22nd)

[1985] Step 4:

[1986] (Send reminder notifications)

[1987] The server identifies participants who have not responded and automatically sends reminders via LINE groups or other messaging groups.

[1988] Input: Answer status (Answered / Not answered)

[1989] Data processing: Generate reminder notifications based on response status

[1990] Output: Reminder notification message

[1991] Step 5:

[1992] (Suggestions for choosing a restaurant)

[1993] Users input details of the event (budget, food preferences, location, etc.) into the communication application. This information is sent via the device to the server, which then uses generative AI to generate a list of suitable restaurants.

[1994] Input: Event details (e.g., budget 5,000 yen, Yakiniku, Shinjuku)

[1995] Data calculation: Generative AI generates appropriate store lists

[1996] Output: Suggested store list (e.g., Store A, Store B, Store C)

[1997] Step 6:

[1998] (Analysis of emotional information)

[1999] The server uses an emotion engine means to recognize emotion information from the participant's text messages and voice inputs and customizes the suggestions based on the emotion information, for example, analyzing emotions such as "happy" and "delighted."

[2000] Input: Text messages and voice input data

[2001] Data Computation: Emotion Analysis with Emotion Engine

[2002] Output: Customized suggestions

[2003] Step 7:

[2004] (Automatic reservation)

[2005] When the user confirms the restaurant they selected from the list of suggested restaurants, the server automatically makes a reservation for that restaurant. The reservation information is sent to the terminal and a confirmation message is displayed to the user.

[2006] Input: User selected store

[2007] Data processing: Automatic reservation information generation

[2008] Output: Reservation confirmation message

[2009] Step 8:

[2010] (Collection of accounting information)

[2011] After the drinking party is over, the billing information is sent from the bar to the server, which stores this information in a database.

[2012] Input: Accounting information sent from the store (e.g. total amount 20,000 yen)

[2013] Data processing: Saving accounting information

[2014] Output: Accounting information stored in a database

[2015] Step 9:

[2016] (Split the bill)

[2017] The server automatically splits the bill among the participants based on the received accounting information, and the results are communicated via a communication application.

[2018] Input: Accounting information stored in the database

[2019] Data calculation: Calculating the payment amount for each participant

[2020] Output: Notification of split amount (e.g. 5000 yen per person)

[2021] Step 10:

[2022] (Electronic Payment)

[2023] Each participant pays the notified split amount using the electronic payment application. Data indicating the completion of the payment is transferred to the server via the terminal, and the server confirms that the payment has been completed.

[2024] Input: Payment data by each participant

[2025] Data processing: Payment completion status update

[2026] Output: Payment confirmation message

[2027] Step 11:

[2028] (Feedback collection and analysis)

[2029] After the event, the server reanalyzes the participants' emotions and collects feedback to be reflected in proposals for the next event.The emotion engine is used to analyze the participants' messages and feedback data to extract satisfaction levels and areas for improvement.

[2030] Input: Feedback data from participants

[2031] Data Calculation: Reanalysis by Emotion Engine

[2032] Output: Feedback data to be reflected in the next proposal

[2033] 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.

[2034] 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.

[2035] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2036] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2037] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2038] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2039] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2040] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2041] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2042] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2043] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2044] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2045] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2046] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2047] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2048] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2049] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2050] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2051] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2052] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of...

Claims

1. A means for coordinating event dates among a plurality of participants via a communications network; A generating artificial intelligence (AI) means for collecting schedule information of the participants and proposing an optimal schedule; A means to automatically send reminders to participants who have not responded, means for suggesting a location for an event via said communication network; means for automatically making a reservation at a location selected from the suggested locations; means for collecting accounting information for the event and automatically dividing the bill among participants; a means for completing payments between participants in cooperation with a payment application based on the accounting information; A system including:

2. A means of suggesting restaurant candidates using artificial intelligence (AI), A means for automatically making a reservation at a restaurant selected from the candidate restaurants is provided. The system of claim 1 .

3. the payment application is an electronic payment application; The system of claim 1 .

Images