System

Abstract

A system is provided.SOLUTION: A system includes a messenger application for receiving a request from a user, a generation system artificial intelligence for acquiring a schedule of each user and selecting an optimum candidate date, a means for retrieving reservation information from a reservation site, presenting the reservation information to the user, and deciding the reservation, and a means for collecting payment information, calculating a split bill amount, and performing payment processing between users.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] While the use of messenger applications has increased in recent years, there are issues with usability due to the complex operations required for users to access different services. Specifically, tasks such as scheduling, making reservations, and splitting bills are scattered across different applications and websites, forcing users to perform these tasks. As a result, user operations become cumbersome, leading some users to switch to external services. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides a system that integrates generative artificial intelligence into a messenger application, acquires each user's schedule after receiving a request from the user, and selects the optimal candidate date. This system allows users to arrange schedules within the messenger application. Furthermore, by including a system that acquires reservation information, presents it to the user, and automatically confirms the reservation, reservations can be made easily. Furthermore, by including a system that collects payment information, calculates the split amount, and processes payments between users, split payment settlement can be carried out seamlessly. In this way, by processing the tasks of schedule arrangement, reservation, and split payment settlement centrally within the messenger application, a system is provided that simplifies user operation and prevents users from switching to external services.

[0006] A "messenger application" is communication software that allows users to send and receive messages.

[0007] "Generative AI" is an AI technology that has the ability to generate optimal solutions based on user input information.

[0008] "Candidate dates" refer to dates presented by the generative artificial intelligence for the user to choose from multiple dates.

[0009] A "reservation site" is a website or application that provides online reservations for restaurants or establishments.

[0010] "Reservation Information" means detailed information for a User to use the Service at a pre-specified date, time and location.

[0011] "Payment information" is information required for a user to pay the service fee.

[0012] The "split amount" refers to the amount obtained by dividing the total payment amount equally among multiple users.

[0013] "User" refers to an individual or organization that uses the Messenger Application to send and receive messages and use various services.

[0014] "Schedule adjustment" refers to the task of checking and adjusting the schedules of multiple users and deciding on a date that everyone can attend.

[0015] "Suggesting candidate dates" refers to the operation in which the generative artificial intelligence proposes multiple dates that it thinks are best for the user.

[0016] "Reservation confirmation information" is information indicating that a reservation has been completed on the reservation site.

[0017] "Payment processing" refers to the procedures and operations required to facilitate the smooth exchange of money between users. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

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

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

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

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0033] 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.

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

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence within a messenger application. The system of the present invention operates as follows.

[0040] Schedule adjustment

[0041] Receiving a rescheduling request

[0042] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[0043] The terminal sends this request to the server.

[0044] Calendar integration

[0045] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[0046] The server analyzes the acquired calendar information and identifies commonly available time slots.

[0047] Proposal of dates

[0048] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[0049] A notification is sent to the device and the user can confirm the proposed dates via chat.

[0050] Confirmation of schedule

[0051] The user confirms and accepts the proposed dates and replies "OK" via chat.

[0052] The terminal transmits the user's consent to the server.

[0053] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[0054] reservation

[0055] Receiving a booking request

[0056] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0057] The terminal sends this request to the server.

[0058] Search for reservation candidates

[0059] The server uses generative artificial intelligence to access the API of the restaurant reservation site and obtain restaurant information that meets the criteria.

[0060] The server lists the restaurant candidates and presents them to the chat group.

[0061] Confirmation of reservation

[0062] The user selects one restaurant from the presented options and replies via chat.

[0063] The terminal transmits the selection result to the server.

[0064] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[0065] The server notifies everyone of the confirmed reservation information.

[0066] Split payment

[0067] Receiving a split bill request

[0068] After a meal, a user chats and asks to split the bill.

[0069] The terminal sends this request to the server.

[0070] Collecting payment information

[0071] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[0072] The user enters the payment amount in the chat.

[0073] The terminal transmits the payment information entered by the user to the server.

[0074] Calculating the split amount

[0075] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0076] Payment Processing

[0077] The server notifies each user of the total amount of payment and instructs them to make payment.

[0078] Users follow the instructions and make payments using the app's payment function.

[0079] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[0080] Specific Examples

[0081] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[0082] Schedule adjustment

[0083] 1. User A proposes a date for a meal via chat and sends a request.

[0084] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[0085] 3. The server presents the proposed dates in the group chat and gets everyone's approval.

[0086] reservation

[0087] 1. User B requests a reservation at a specific restaurant based on confirmed dates.

[0088] 2. The server presents reservation options and automatically makes a reservation at the restaurant selected by the user.

[0089] 3. The server notifies everyone of the confirmed reservation information.

[0090] Split payment

[0091] 1. User C requests splitting the bill and submits a request.

[0092] 2. The server collects the payment amount from each user and calculates and notifies the split amount.

[0093] 3. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[0094] This method allows all operations to be completed within the messenger application, resulting in a significant improvement in user convenience.

[0095] The processing flow will be explained below.

[0096] Schedule adjustment

[0097] Step 1:

[0098] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[0099] The terminal sends this request to the server.

[0100] Step 2:

[0101] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[0102] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[0103] The server analyzes the acquired calendar information and identifies commonly available time slots.

[0104] Step 3:

[0105] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[0106] A notification is sent to the device and the user can confirm the proposed dates via chat.

[0107] Step 4:

[0108] The user confirms and accepts the proposed dates and replies "OK" via chat.

[0109] The terminal transmits the user's consent to the server.

[0110] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[0111] reservation

[0112] Step 1:

[0113] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0114] The terminal sends this request to the server.

[0115] Step 2:

[0116] The server uses generative artificial intelligence to access the API of the restaurant reservation site and obtain restaurant information that meets the criteria.

[0117] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[0118] The server lists the restaurant candidates and presents them to the chat group.

[0119] Step 3:

[0120] The user selects one restaurant from the presented options and replies via chat.

[0121] The terminal transmits the selection result to the server.

[0122] Step 4:

[0123] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[0124] The server notifies everyone of the confirmed reservation information.

[0125] Split payment

[0126] Step 1:

[0127] After a meal, a user chats and asks to split the bill.

[0128] The terminal sends this request to the server.

[0129] Step 2:

[0130] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[0131] The user enters the payment amount in the chat.

[0132] The terminal transmits the payment information entered by the user to the server.

[0133] Step 3:

[0134] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0135] Step 4:

[0136] The server notifies each user of the total amount of payment and instructs them to make payment.

[0137] Users follow the instructions and make payments using the app's payment function.

[0138] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[0139] Example 1

[0140] 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."

[0141] Traditional messenger applications lacked the ability to centralize complex tasks such as scheduling, booking, and splitting bills. As a result, users had to perform these tasks individually in separate applications or manually, which required a great deal of time and effort. Furthermore, there was a high likelihood of mismatched or missing information between tasks, hindering smooth communication and efficient progress. This resulted in reduced user convenience and a poor quality experience.

[0142] 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.

[0143] In this invention, the server includes a communication application that accepts requests from users, a generative artificial intelligence means that acquires each user's schedule and selects the best candidate date, a device that acquires reservation information, presents it to the user, and confirms the reservation, a device that collects payment information, calculates the split amount, and processes payments between users, and a means for completing these operations within the messenger application. This allows users to efficiently and easily process schedule adjustments, reservations, and split payment settlements within a single messenger application.

[0144] A "communications application" is software that enables text messaging, voice, and video calls between users over the Internet.

[0145] "Generative AI" is an AI technology that learns from large amounts of data to perform prediction and generation tasks, rather than using traditional rule-based systems.

[0146] "Device" refers to hardware or software designed to perform a specific task, which in this invention includes obtaining, submitting, and confirming reservation information, collecting payment information, calculating split amounts, and processing payments.

[0147] "Means" refer to the methods, processes, or technical techniques required to achieve a particular function.

[0148] A "user" is a person or group of people who make requests such as scheduling, booking, splitting bills, etc. through a communication application.

[0149] "Candidate dates" refer to common available dates that are proposed taking into consideration the schedules of all users.

[0150] "Reservation information" refers to data necessary to guarantee the use of a specific service or place, and in the present invention, particularly refers to reservation data for restaurants and the like.

[0151] "Payment Information" means data related to a particular transaction, such as the amount and payment method.

[0152] "Split amount" refers to an amount calculated to divide multiple payments equally or in specific proportions.

[0153] "Complete within the messenger application" means that the user does not need to switch to an external application to complete a specific task, and all operations are completed within one application.

[0154] The present invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence within a messenger application. The system includes the following major hardware and software components:

[0155] Hardware and Software Components

[0156] 1. Server

[0157] Generative artificial intelligence: Using OpenAI's GPT-4 as an example.

[0158] API: Google Calendar API, restaurant reservation sites (e.g. Gurunavi API, Tabelog API)

[0159] Communication module: Data communication using HTTP / HTTPS protocol

[0160] 2. Terminal

[0161] Messenger applications: General communication applications (e.g., LINE, WhatsApp)

[0162] Data transmission / reception module: HTTP request sending and response receiving functions

[0163] 3. Users

[0164] Input devices: smartphones, tablets, PCs, etc.

[0165] Scheduling details

[0166] A user types "Let's all get together for dinner next Friday" in a chat group within a messenger application. The device sends this request to the server as an HTTP request. The server uses the received request as a trigger to launch a generative artificial intelligence (AI) and obtain schedule information from each user's Google Calendar API. The server analyzes this information, identifies common free time slots, and selects the most suitable candidate date. The selected candidate date (e.g., "Next Friday at 7pm") is notified within the chat group via the device. When the user accepts the candidate date, the final date is confirmed and everyone is notified.

[0167] Booking details

[0168] The user types "Make a reservation at a Japanese restaurant in Shinjuku" in a messenger application. The device sends this request to the server. The server uses generative artificial intelligence to access the APIs of multiple restaurant reservation sites and retrieve restaurant information that meets the criteria. The retrieved restaurant candidates are notified to the user via the device. When the user selects one restaurant from the candidates and replies, the server automatically makes a reservation at the selected restaurant and retrieves the reservation confirmation information. The server then notifies the chat group of the reservation confirmation information, and the device displays it to the user.

[0169] Split payment details

[0170] After the meal, a user requests in chat to "split the bill." The device sends this request to the server. The server then collects payment information by sending a message to each user asking them to enter their expected payment amount. Each user enters their payment amount in chat and sends that information to the server via their device. The server uses generative artificial intelligence to tally the entered payment amounts and calculates each user's share of the bill. Finally, the server notifies each user of the total share of the bill and instructs them to pay. Users follow the instructions and make the payment using the payment function within the app (e.g., PayPay, LINE Pay). The server confirms that each user has completed payment and sends a notification of settlement completion to everyone.

[0171] Examples and prompts

[0172] For example, if a user is planning a meal at a restaurant with a group of friends, they can enter the prompt text as follows:

[0173] "Let's all get together for dinner next Friday," I typed into the chat.

[0174] "Make a reservation at a Japanese restaurant in Shinjuku," he requested.

[0175] He asked to settle the bill, saying, "Let's split it."

[0176] This allows users to complete all operations within a single messenger application, enabling them to efficiently arrange schedules, make reservations, and split the bill.

[0177] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0178] Schedule adjustment

[0179] Step 1:

[0180] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[0181] Input: User's text message

[0182] Output: HTTP request from the terminal to the server

[0183] Step 2:

[0184] The terminal sends the received message to the server as an HTTP request.

[0185] Input: User's message

[0186] Output: The request data sent to the server

[0187] Step 3:

[0188] The server receives the request and launches a generative AI, which prepares access to the Google Calendar API for each user based on the model.

[0189] Input: HTTP request

[0190] Output: Prepare to access the calendar API

[0191] Step 4:

[0192] The server calls the Google Calendar API to obtain each user's calendar information.

[0193] Input: Calendar API request

[0194] Output: Calendar information for each user

[0195] Step 5:

[0196] The server analyzes the acquired calendar information and identifies commonly available time slots.

[0197] Input: Calendar information

[0198] Output: Candidate dates where everyone's schedules match

[0199] Step 6:

[0200] The server generates the best candidate date (e.g., "next Friday at 7pm") and notifies the chat group in the messenger application of this information.

[0201] Input: Data on the best candidate date

[0202] Output: Present candidate dates to the user

[0203] Step 7:

[0204] The terminal receives the candidate date notification from the server and displays it to the user.

[0205] Input: Candidate date notification

[0206] Output: Candidate dates displayed on the chat screen

[0207] Step 8:

[0208] The user checks the proposed dates and replies "OK" via chat.

[0209] Input: User consent message

[0210] Output: Acceptance request from device to server

[0211] Step 9:

[0212] The terminal sends the user's reply message to the server.

[0213] Input: Acceptance message

[0214] Output: Acceptance data sent to the server

[0215] Step 10:

[0216] The server waits until everyone agrees, and after confirming everyone's consent, it notifies the chat group of the confirmed date.

[0217] Input: consent data for all

[0218] Output: Notification of confirmed schedule

[0219] reservation

[0220] Step 1:

[0221] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0222] Input: User request message

[0223] Output: Request from terminal to server

[0224] Step 2:

[0225] The terminal sends this request to the server.

[0226] Input: Request message

[0227] Output: The request sent to the server

[0228] Step 3:

[0229] The server receives the request and uses generative artificial intelligence to access the APIs of multiple restaurant reservation sites.

[0230] Input: Request data

[0231] Output: API request to the booking site

[0232] Step 4:

[0233] The server retrieves restaurant information that meets the criteria and lists it.

[0234] Input: API response

[0235] Output: Restaurant candidate list

[0236] Step 5:

[0237] The server sends the generated restaurant candidates to a chat group in a messenger application.

[0238] Input: Restaurant candidate list

[0239] Output: Information presented to the user

[0240] Step 6:

[0241] The terminal receives the list of restaurant candidates from the server and displays it to the user.

[0242] Input: Restaurant candidate list

[0243] Output: Candidate list displayed on the chat screen

[0244] Step 7:

[0245] The user selects one restaurant from the presented options and replies via chat.

[0246] Input: User's selected message

[0247] Output: Selected data from the terminal to the server

[0248] Step 8:

[0249] The terminal transmits the selection result to the server.

[0250] Input:Selection data

[0251] Output: Notify the server of the selection results

[0252] Step 9:

[0253] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[0254] Input: Selected restaurant information

[0255] Output: Confirmed reservation information

[0256] Step 10:

[0257] The server notifies the chat group of the reservation confirmation information, and the terminal displays it to the user.

[0258] Input: Confirmed reservation information

[0259] Output: User notification

[0260] Split payment

[0261] Step 1:

[0262] After a meal, a user chats and asks to split the bill.

[0263] Input: User request message

[0264] Output: Request from terminal to server

[0265] Step 2:

[0266] The terminal sends this request to the server.

[0267] Input: Request message

[0268] Output: The request sent to the server

[0269] Step 3:

[0270] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[0271] Input: Request data

[0272] Output: Message requesting expected payment amount

[0273] Step 4:

[0274] The user enters the payment amount in the chat.

[0275] Input: Payment amount Message

[0276] Output: Input data from the terminal to the server

[0277] Step 5:

[0278] The terminal transmits the payment information entered by the user to the server.

[0279] Input: Payment amount data

[0280] Output: Payment information to the server

[0281] Step 6:

[0282] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0283] Input: Payment amount data

[0284] Output: Split amount data

[0285] Step 7:

[0286] The server notifies each user of the total split amount and instructs them to pay.

[0287] Input: Split amount data

[0288] Output: Payment instruction message

[0289] Step 8:

[0290] Users follow the instructions and make payments using the app's payment function.

[0291] Input: Payment Instruction Message

[0292] Output: Payment completion information

[0293] Step 9:

[0294] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[0295] Input: Payment completion information

[0296] Output: Payment completion notification

[0297] (Application example 1)

[0298] 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."

[0299] With traditional messaging applications, users often had to spend a lot of time coordinating schedules, making restaurant reservations, and splitting bills. These processes were also performed separately, resulting in poor overall convenience. Furthermore, insufficient information sharing and collaboration between different applications led to inconsistent user experiences.

[0300] 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.

[0301] In this invention, the server includes a message transfer application means for accepting requests from users, a generative model means for acquiring each user's schedule and selecting the optimal candidate date, a means for acquiring information from a reservation information site, presenting it to the user, and finalizing the reservation, a means for collecting payment information, calculating the split amount, and processing the payment between users, a calendar linking means for acquiring user schedule information, an information search means for searching for reservation candidates, and an electronic payment means for executing the payment process. This enables consistent operation within the messaging application, and allows each process of scheduling, making reservations, and splitting the bill to be carried out smoothly.

[0302] A "message transfer application that accepts requests from users" is an application that allows users to transmit various requests to the system by sending messages.

[0303] A "generative model" is an algorithm that uses artificial intelligence to analyze a user's schedule information and generate optimal candidate dates.

[0304] "Means for obtaining information from a reservation information site, presenting it to the user, and confirming the reservation" refers to a system for obtaining the necessary reservation information from an online reservation information service, presenting it to the user for selection, and confirming the reservation.

[0305] "Means for collecting payment information, calculating split amounts, and processing payments between users" refers to a system that collects payment amount information for each user, calculates split amounts based on that information, and ensures that appropriate payments are made between users.

[0306] The "calendar linking means for acquiring the user's schedule information" is a technology for linking with a calendar service used by the user and acquiring the schedule information.

[0307] The "information search means for searching for reservation candidates" is a technology for searching for suitable candidates from reservation information sites in response to a user request.

[0308] The "electronic payment means for executing payment processing" is a system for electronically settling payments between users based on the collected split amounts.

[0309] The present invention is a system that allows users to easily schedule, book, and split bill payments within a messaging application. The system includes the following components:

[0310] System Configuration

[0311] 1. A message transfer application that accepts requests from users

[0312] The server receives the dates and reservation requests that users propose in the chat, and these requests are sent to the server in an appropriate format.

[0313] 2. A generative model that obtains each user's schedule and selects the best candidate date

[0314] The server uses a generative AI model to retrieve and analyze each user's calendar information. For example, it uses the Google Calendar API to retrieve the user's schedule and select the best possible dates. This information is then analyzed based on prompts.

[0315] 3. A means of obtaining information from the reservation information site, presenting it to the user, and finalizing the reservation

[0316] The server searches for restaurant options from reservation information sites (e.g., OpenTable API) based on the specified date, time, and location, and presents them to the user in the chat. The server then automatically confirms the reservation based on the user's selection.

[0317] 4. A means of collecting payment information, dividing the bill, and processing payments between users.

[0318] The server collects payment information from the user, calculates the split amount using a generative AI model, notifies the user of the calculation result, and makes the payment using an electronic payment method (e.g., Stripe).

[0319] Hardware and software used

[0320] Hardware: Smartphones, smart glasses

[0321] Software: Python, Flask, Google Calendar API, OpenTable API, Stripe API

[0322] Overview of the process

[0323] 1. Scheduling:

[0324] If a user types into the chat, "Let's all get together for dinner next Friday," the server retrieves everyone's calendar information and presents the most suitable candidate dates.

[0325] 2. Reservations:

[0326] If a user types "Make a reservation at a Japanese restaurant in Shinjuku," the server will call the OpenTable API, retrieve and present restaurant information that matches the criteria, and confirm the reservation at the selected restaurant.

[0327] 3. Split the bill:

[0328] After the meal, if the user inputs "Let's split the bill," the server collects payment information, calculates the split amount using a generative AI model, and completes the payment using an electronic payment method.

[0329] Examples and prompts

[0330] For example, if a group of friends suggests in a chat, "Let's have a Japanese dinner in Shibuya next Friday," the server will check everyone's calendars and suggest "Friday at 7 PM." If a user then requests, "Make a reservation at a Japanese restaurant in Shinjuku," the server will use the OpenTable API to search for restaurants that meet the criteria and make a reservation at the recommended restaurant. After the meal, if the user requests, "Let's split the bill," the server will tally up the amounts paid by each user, calculate the split amount, and notify them.

[0331] Example prompt sentence:

[0332] I've suggested a Japanese dinner in Shibuya next Friday at 7pm. I've checked everyone's calendars and this date and time is most suitable. Please confirm and accept.

[0333] The restaurant search results are: 1. Shibuya Washokutei, 2. Ginza Washoku Teishoku, 3. Fine Japanese Restaurant. Please select the restaurant you want.

[0334] Your meal is complete. The total is 20,000 yen. We split the bill at 5,000 yen per person. Please complete the payment using the link below.

[0335] By using this system, all operations can be completed within the message forwarding app, greatly improving user convenience.

[0336] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0337] Step 1:

[0338] Input: A user inputs a scheduling request within a message forwarding application.

[0339] What happens: A user types in a chat group, "Let's all get together for dinner next Friday."

[0340] Server processing: The terminal receives this request and sends it to the server.

[0341] Output: The server receives the request and proceeds.

[0342] Step 2:

[0343] Input: The server retrieves all users' calendar information.

[0344] Specific operation: The server uses the Google Calendar API to obtain the schedule information of all participants.

[0345] Data processing: Analyze the acquired calendar information.

[0346] Server processing: Using a generative AI model, analyze each user's schedule and identify common free time slots.

[0347] Output: A list of optimal candidate dates is generated, ready to be presented to the user.

[0348] Step 3:

[0349] Input: The retrieved calendar information and a list of common free time slots.

[0350] Specific operation: The servers select "next Friday at 7pm" as a commonly available time slot.

[0351] Server processing: Format the selected candidate dates for presentation in the group chat.

[0352] Output: The server sends a notification to the device, allowing the user to check the proposed dates.

[0353] Step 4:

[0354] Input: Candidate dates provided by the server.

[0355] Specific behavior: The user confirms the proposed date in chat and replies "OK."

[0356] Terminal processing: The terminal sends the user's consent to the server.

[0357] Output: The server confirms everyone's acceptance and notifies everyone of the confirmed date.

[0358] Step 5:

[0359] Input: The user types a reservation request in the message.

[0360] Specific action: The user types, "Make a reservation at a Japanese restaurant in Shinjuku."

[0361] Terminal processing: The terminal sends this request to the server.

[0362] Output: The server receives the request and prepares to proceed.

[0363] Step 6:

[0364] Input: The server receives the reservation conditions (location, genre).

[0365] Specific operation: The server calls the OpenTable API and retrieves restaurant information using the conditions "Shinjuku" and "Japanese cuisine."

[0366] Data processing: Analyze and organize the list of restaurant candidates obtained.

[0367] Server processing: Generates a candidate list that can be presented to the user.

[0368] Output: Format the list of restaurant suggestions to present in the chat.

[0369] Step 7:

[0370] Input: A list of restaurant candidates.

[0371] Specific operation: The user selects one restaurant from the presented options and replies via chat.

[0372] Terminal processing: The terminal sends the selection results to the server.

[0373] Output: The server prepares to automatically make a reservation at the selected restaurant.

[0374] Step 8:

[0375] Input: User selection results, reservation candidate list.

[0376] Specific behavior: The server uses the OpenTable API to make a reservation at the selected restaurant.

[0377] Data processing: Obtain and format confirmed reservation information.

[0378] Server processing: Notify everyone of the confirmed reservation information.

[0379] Output: Send a notification to the device with the confirmed reservation information.

[0380] Step 9:

[0381] Input: The user enters a request for split payment in the message.

[0382] Specific action: The user types "Let's split the bill" in the chat.

[0383] Terminal processing: The terminal sends this request to the server.

[0384] Output: The server receives the request and prepares to proceed.

[0385] Step 10:

[0386] Input: Request to split the bill.

[0387] Specific operation: To collect payment information, the server sends a message to each user requesting them to enter the expected payment amount.

[0388] Data processing: Aggregate payment amounts from users.

[0389] Server processing: Using the generative AI model, the entered payment amounts are aggregated and the amount each user is responsible for is calculated.

[0390] Output: Notify each user of the split amount.

[0391] Step 11:

[0392] Input: Notification of split amount.

[0393] Specific behavior: The user makes a payment using the app's electronic payment function.

[0394] Data Processing: We process each user's payment using an electronic payment system (e.g., Stripe API).

[0395] Server processing: Confirm that each user has completed payment.

[0396] Output: Send a notification to everyone that payment is complete.

[0397] 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.

[0398] This invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence and an emotion engine within a messenger application. The system of the present invention operates as follows.

[0399] Schedule adjustment

[0400] Receiving a rescheduling request

[0401] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[0402] The terminal sends this request to the server.

[0403] Calendar integration

[0404] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[0405] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[0406] The server analyzes the acquired calendar information and identifies commonly available time slots.

[0407] Emotion recognition with emotion engine

[0408] The server activates an emotion engine to recognize each user's emotion before making scheduling suggestions.

[0409] The server analyzes the user's chat content and past responses to obtain emotional data.

[0410] The server then suggests the best possible date based on the recognized emotion data.

[0411] Proposal of dates

[0412] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[0413] A notification is sent to the device and the user can confirm the proposed dates via chat.

[0414] Confirmation of schedule

[0415] The user confirms and accepts the proposed dates and replies "OK" via chat.

[0416] The terminal transmits the user's consent to the server.

[0417] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[0418] reservation

[0419] Receiving a booking request

[0420] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0421] The terminal sends this request to the server.

[0422] Search for reservation candidates

[0423] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant reservation site and obtain restaurant information that meets the criteria.

[0424] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[0425] The emotion engine considers the user's emotional state and prioritizes appropriate restaurants to provide a better user experience.

[0426] The server lists the restaurant candidates and presents them to the chat group.

[0427] Confirmation of reservation

[0428] The user selects one restaurant from the presented options and replies via chat.

[0429] The terminal transmits the selection result to the server.

[0430] Notification of final information

[0431] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[0432] The server notifies everyone of the confirmed reservation information.

[0433] Split payment

[0434] Receiving a split bill request

[0435] After a meal, a user chats and asks to split the bill.

[0436] The terminal sends this request to the server.

[0437] Collecting payment information

[0438] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[0439] The user enters the payment amount in the chat.

[0440] The terminal transmits the payment information entered by the user to the server.

[0441] Emotion recognition with emotion engine

[0442] The server activates an emotion engine to recognize the emotion of each user during payment information collection and bill splitting calculation.

[0443] The server analyzes the user's chat content and reactions to obtain emotional data.

[0444] The server provides appropriate communication methods and feedback based on the recognized emotion data.

[0445] Calculating the split amount

[0446] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0447] Payment Processing

[0448] The server notifies each user of the total amount of payment and instructs them to make payment.

[0449] Users follow the instructions and make payments using the app's payment function.

[0450] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[0451] Specific Examples

[0452] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[0453] Schedule adjustment

[0454] 1. User A proposes a date for a meal in chat, types "next Friday," and sends the request.

[0455] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[0456] 3. The server uses the emotion engine to recognize each user's emotion data and check whether the candidate date matches the user's emotion.

[0457] 4. The server presents the proposed dates in the group chat and gets everyone's approval.

[0458] reservation

[0459] 1. User B requests a reservation at a specific restaurant based on confirmed dates.

[0460] 2. The server uses generative artificial intelligence and an emotion engine to present reservation options that meet the criteria, and the user can select one.

[0461] 3. The server will automatically make a reservation at the selected restaurant and notify everyone of the reservation confirmation.

[0462] Split payment

[0463] 1. User C requests splitting the bill and submits a request.

[0464] 2. The server collects the payment amount of each user and monitors the emotions of each user using an emotion engine.

[0465] 3. The server uses generative artificial intelligence to calculate the split amount and instructs payment.

[0466] 4. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[0467] This method not only allows all operations to be completed within the messenger application, greatly improving user convenience, but also further improves the user experience through processes that utilize the emotion engine.

[0468] The processing flow will be explained below.

[0469] Schedule adjustment

[0470] Step 1:

[0471] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[0472] The terminal sends this request to the server.

[0473] Step 2:

[0474] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[0475] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[0476] Step 3:

[0477] The server analyzes the acquired calendar information and identifies commonly available time slots.

[0478] Step 4:

[0479] The server activates an emotion engine to recognize each user's emotion before making suggestions.

[0480] The server analyzes the user's chat content and past responses to obtain emotional data.

[0481] Step 5:

[0482] The server selects the most suitable candidate date based on the recognized emotion data.

[0483] Step 6:

[0484] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[0485] A notification is sent to the device and the user can confirm the proposed dates via chat.

[0486] Step 7:

[0487] The user confirms and accepts the proposed dates and replies "OK" via chat.

[0488] The terminal transmits the user's consent to the server.

[0489] Step 8:

[0490] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[0491] reservation

[0492] Step 1:

[0493] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0494] The terminal sends this request to the server.

[0495] Step 2:

[0496] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant reservation site and obtain restaurant information that meets the criteria.

[0497] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[0498] Step 3:

[0499] The emotion engine considers the user's emotional state and prioritizes appropriate restaurants to provide a better user experience.

[0500] Step 4:

[0501] The server lists the restaurant candidates and presents them to the chat group.

[0502] Step 5:

[0503] The user selects one restaurant from the presented options and replies via chat.

[0504] The terminal transmits the selection result to the server.

[0505] Step 6:

[0506] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[0507] Step 7:

[0508] The server notifies everyone of the confirmed reservation information.

[0509] Split payment

[0510] Step 1:

[0511] After a meal, a user chats and asks to split the bill.

[0512] The terminal sends this request to the server.

[0513] Step 2:

[0514] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[0515] The user enters the payment amount in the chat.

[0516] The terminal transmits the payment information entered by the user to the server.

[0517] Step 3:

[0518] The server activates an emotion engine to recognize the emotion of each user during payment information collection and bill splitting calculation.

[0519] The server analyzes the user's chat content and reactions to obtain emotional data.

[0520] Step 4:

[0521] The server provides appropriate communication methods and feedback based on the recognized emotion data.

[0522] Step 5:

[0523] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0524] Step 6:

[0525] The server notifies each user of the total amount of payment and instructs them to make payment.

[0526] Step 7:

[0527] Users follow the instructions and make payments using the app's payment function.

[0528] Step 8:

[0529] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[0530] Specific Examples

[0531] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[0532] 1. User A proposes a date for a meal in chat, types "next Friday," and sends the request.

[0533] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[0534] 3. The server uses the emotion engine to recognize each user's emotion data and check whether the candidate date matches the user's emotion.

[0535] 4. The server presents the proposed dates in the group chat and gets everyone's approval.

[0536] 5. User B requests a reservation at a specific restaurant based on confirmed dates.

[0537] 6. The server uses generative artificial intelligence and an emotion engine to present reservation options that meet the criteria, and the user can select one.

[0538] 7. The server will automatically make a reservation at the selected restaurant and notify everyone of the reservation confirmation.

[0539] 8. User C requests splitting the bill and submits a request.

[0540] 9. The server collects the payment amount of each user and monitors the emotions of each user using the emotion engine.

[0541] 10. The server uses generative artificial intelligence to calculate the split amount and instructs payment.

[0542] 11. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[0543] This method not only allows all operations to be completed within the messenger application, greatly improving user convenience, but also further improves the user experience through processes that utilize the emotion engine.

[0544] Example 2

[0545] 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."

[0546] With conventional messenger applications, it was difficult to coordinate schedules, make reservations, and split payments all in one place, requiring users to use each application and service individually. Furthermore, due to a lack of smooth communication and understanding of emotions between users, it was difficult to select appropriate dates, make reservations, and process payments. This resulted in a poor user experience and required a lot of effort.

[0547] 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 a messenger application that accepts requests from users, a generative artificial intelligence means that acquires each user's schedule and selects the optimal candidate date, a means that recognizes user emotions using an emotion engine and optimizes schedule adjustment and reservation suggestions, a means that searches for reservation information from a reservation site and presents it to the user to confirm the reservation, a means that collects payment information and calculates the split amount and processes payments between users, a means that notifies all users of the approved schedule, and a means that notifies users of the confirmed reservation information after the reservation is confirmed. This allows users to centrally adjust schedules, make reservations, and split the bill within the messenger application, significantly improving user convenience and experience.

[0548] A "messenger application that accepts requests from users" is software that allows users to request operations and communicate through messages, and provides various services in cooperation with a server.

[0549] "Generative AI that obtains each user's schedule and selects the optimal candidate date" is an AI technology that analyzes the user's calendar data and suggests the optimal date and time taking into account the user's overall schedule.

[0550] "Means for searching reservation information from reservation sites, presenting it to the user, and finalizing the reservation" refers to a technology that accesses multiple reservation information providing sites to collect reservation information that meets the conditions, presents the candidates to the user, and executes the reservation based on the user's selection.

[0551] "Means for collecting payment information, calculating split amounts, and processing payments between users" refers to technology for collecting payment amount information from users, calculating fair split amounts, and smoothly processing payments.

[0552] "Means of using an emotion engine to recognize user emotions and optimize schedule adjustment and reservation suggestions" is a technology that analyzes a user's messages and past data to recognize their emotional state and suggests optimal dates and reservation details based on those emotions.

[0553] The "means for presenting candidate dates and receiving user's consent" is a technique for presenting optimal candidate dates to the user and receiving a response of approval or rejection from the user.

[0554] The "means for notifying all users of the approved schedule" is a technique for simultaneously notifying all users of the approved schedule.

[0555] "Means for notifying users of confirmed reservation information after a reservation is confirmed" refers to a technique for notifying all users of confirmed reservation information after the reservation procedure is completed.

[0556] This invention is a system that uses a messenger application to efficiently arrange schedules, make reservations, and split the bill. The devices used are the user's terminal (such as a smartphone or PC) and a server, which are linked via a communication network.

[0557] Overall structure

[0558] The system works by linking a messenger application, generative artificial intelligence, an emotion engine, and various APIs.

[0559] 1. Messenger Applications

[0560] Users request scheduling, reservations, and bill splits through a messenger application, which sends the requests to the server and receives responses from the server.

[0561] 2. Generative Artificial Intelligence

[0562] The server uses generative artificial intelligence to analyze each user's calendar information and propose optimal schedule adjustments. Calendar information is obtained through the APIs of Google Calendar and Outlook Calendar.

[0563] 3. Emotion Engine

[0564] The server uses an emotion engine to analyze the user's emotions. Based on the analysis results, it proposes optimal dates and reservations that match the user's emotions. Emotion data is obtained from the user's past message history and real-time reactions.

[0565] 4. Booking API

[0566] The server searches for reservation candidates that match the conditions via the API of various reservation sites, presents the acquired reservation information to the user, and confirms the reservation based on the user's selection.

[0567] 5. Payment Processing Functions

[0568] The server collects payment information from users, calculates split amounts using generative artificial intelligence, and processes payment instructions and payment confirmations.

[0569] Specific examples

[0570] Specific examples of schedule adjustments

[0571] User A sends a request to a chat group saying, "Let's all get together for dinner next Friday." The server uses the Google Calendar or Outlook Calendar API to obtain each user's calendar information and identify commonly available time slots. It then activates an emotion engine to analyze the user's emotional state. It then suggests the most suitable candidate date, for example, "next Friday at 7 p.m." The user replies "OK," and the server confirms everyone's acceptance before notifying them of the confirmed date.

[0572] Specific reservation examples

[0573] User B makes a request via a messenger application, saying, "Make a reservation at a Japanese restaurant in Shinjuku." The server searches for the criteria "Shinjuku," "Japanese food," and "next Friday night at 7pm" via the restaurant reservation site's API. Using an emotion engine, it prioritizes and selects the most suitable restaurant, taking into account the user's emotional state. The obtained restaurant candidates are then listed and presented to the chat group. The server then automatically makes a reservation at the restaurant selected by the user and notifies everyone of the confirmed reservation.

[0574] Specific examples of split payment

[0575] After the meal, User C sends a request via chat to "split the bill." The server sends each user a message prompting them to enter their expected payment amount. The user enters the payment amount via chat and sends it to the server. The emotion engine is activated to monitor the user's emotional state. Generative artificial intelligence is used to calculate the split amount based on the entered payment amount. The server notifies each user of the calculation result and instructs them to pay. The user pays using the payment function within the app, and after the server confirms that payment has been completed, it sends a notification to everyone that the settlement has been completed.

[0576] Example prompts

[0577] "Please arrange a date for us to all have dinner together next Friday at 7pm."

[0578] "Make a reservation at a Japanese restaurant in Shinjuku."

[0579] "Please split the bill."

[0580] Through this specific system configuration and operation procedure, the present invention can provide users with efficient and smooth schedule adjustment, reservation, and split payment functions.

[0581] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0582] Schedule adjustment

[0583] Step 1: Receiving a scheduling request

[0584] A user types, "Let's all get together for dinner next Friday" into a chat group on a messenger application.

[0585] The device sends this request to the server.

[0586] Input: User request message

[0587] Output: Request data to the server

[0588] Step 2: Calendar Integration

[0589] The server runs a generative artificial intelligence and calls the Google Calendar or Outlook Calendar API to retrieve each user's calendar information.

[0590] The server collects calendar information through an API with each user's permission.

[0591] Input: A request to get the user's calendar information

[0592] Data processing: Obtain calendar information through API and analyze it

[0593] Output: Parsed calendar information

[0594] Step 3: Emotion recognition by the emotion engine

[0595] The server launches an emotion engine and analyzes the user's chat content and past responses to obtain emotional data.

[0596] Input: User chat content, past reaction data

[0597] Data calculation: Recognize and acquire emotional data using the emotion engine

[0598] Output: User emotion data

[0599] Step 4: Present possible dates

[0600] The server will suggest the best possible dates based on the analyzed calendar information and emotional data.

[0601] For example, you could suggest "next Friday night at 7pm" in a group chat.

[0602] A notification will be sent to the device and the user can confirm the suggested dates.

[0603] Input: Analyzed calendar information, emotion data

[0604] Data calculation: Identifying the best candidate date

[0605] Output: Best candidate date notification

[0606] Step 5: Confirm the date

[0607] The user checks the proposed dates and replies with an "OK" message via chat to indicate their acceptance.

[0608] The device sends the user's consent to the server.

[0609] After the server confirms everyone's consent, it will notify everyone of the confirmed date.

[0610] Input: User consent message

[0611] Data calculation: Confirmation of consent from all users

[0612] Output: Notification of confirmed schedule

[0613] reservation

[0614] Step 1: Receiving a booking request

[0615] The user simply types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0616] The device sends this request to the server.

[0617] Input: User's reservation request message

[0618] Output: Reservation request data to the server

[0619] Step 2: Search for potential reservations

[0620] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant booking site.

[0621] The server retrieves restaurant information based on conditions such as "Shinjuku," "Japanese cuisine," and "next Friday night at 7 p.m."

[0622] Input: Reservation conditions (e.g., location, Shinjuku; genre, Japanese; time, next Friday at 7pm)

[0623] Data processing: Acquiring restaurant information through API

[0624] Output: A list of restaurant candidates obtained

[0625] Step 3: Optimizing with an Emotion Engine

[0626] The server uses an emotion engine to analyze the user's emotional state and prioritize appropriate restaurants.

[0627] Input: Obtained restaurant candidate list, user emotion data

[0628] Data calculations: Using sentiment engines to filter the best restaurants

[0629] Output: A list of the best restaurants

[0630] Step 4: Suggest candidates

[0631] The server will create a list of the best restaurant options and present them in the group chat.

[0632] The user selects one restaurant from the presented options and responds via chat.

[0633] The device sends the selection results to the server.

[0634] Input: Best Restaurant Shortlist

[0635] Output: Present candidate list to user, user selection message

[0636] Step 5: Confirm your booking

[0637] The server automatically makes a reservation at the selected restaurant and retrieves the reservation confirmation information.

[0638] The server will then notify everyone of the confirmed reservation information.

[0639] Input: User's selected message

[0640] Data calculation: Reservation processing through the booking site's API

[0641] Output: Notification of confirmed reservation information

[0642] Split payment

[0643] Step 1: Receiving a split request

[0644] After a meal, the user can chat and ask to split the bill.

[0645] The device sends this request to the server.

[0646] Input: User's bill split request message

[0647] Output: Split request data to the server

[0648] Step 2: Collect payment information

[0649] The server sends each user a message prompting them to enter their expected payment amount.

[0650] The user enters the payment amount in chat and sends it to the server.

[0651] Input: User payment amount input message

[0652] Output: Payment information from the user

[0653] Step 3: Emotion recognition by the emotion engine

[0654] The server runs an emotion engine to recognize each user's emotion during payment information collection and bill splitting.

[0655] Input: User's payment information, chat contents

[0656] Data calculation: Recognize and acquire emotional data using the emotion engine

[0657] Output: Emotion data

[0658] Step 4: Calculate the split amount

[0659] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0660] Input: User's payment information

[0661] Data calculation: aggregation and charge calculation

[0662] Output: Split amount

[0663] Step 5: Payment Processing

[0664] The server notifies each user of the total amount due and instructs them to pay.

[0665] Users follow the instructions and make payments using the in-app payment function.

[0666] The server confirms that each user has completed payment and sends a notification to everyone that the payment has been completed.

[0667] Input: Split amount, user payment information

[0668] Data calculation: Confirmation of payment processing

[0669] Output: Payment completion notification

[0670] Through the above processing steps, the present system can greatly improve user convenience and further enrich the user experience.

[0671] (Application example 2)

[0672] 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."

[0673] Conventional messenger applications can accept user requests and adjust schedules and make reservations, but they do not support work coordination and cost sharing for industrial robots, making it difficult to efficiently manage work and costs within factories.In addition, the sharing of usage fees for shared equipment and facilities is unclear, so there is a need for optimal schedule adjustment and an improved user experience.

[0674] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0675] In this invention, the server includes a communication means for accepting requests from users, a generative artificial intelligence device for acquiring each user's schedule and selecting the optimal candidate date, a reservation means for searching reservation information from a reservation site, presenting it to the user, and finalizing the reservation, a payment means for collecting payment information, calculating the split amount, and processing payments between users, a work coordination means for adjusting the work schedule of industrial robots, and a cost sharing means for sharing the usage fees for shared equipment and facilities among the responsible departments. This enables efficient work coordination and transparent cost management within the factory.

[0676] "Communication means for accepting requests from users" refers to technology or devices for receiving requests or instructions from users via a communication network.

[0677] The "generative artificial intelligence device that acquires each user's schedule and selects the optimal candidate date" is an artificial intelligence system that collects users' schedule information and automatically selects the optimal date based on that data.

[0678] "Reservation means for searching reservation information from a reservation site, presenting it to the user, and confirming the reservation" refers to technology or devices that search for the necessary reservation information from an online reservation platform, provide it to the user, and confirm the reservation.

[0679] A "payment method that collects payment information, splits the bill, and processes payments between users" refers to technology or a device that collects payment information from each user, splits the amount equally, and executes the payment process.

[0680] "Work adjustment means for adjusting the work schedule of industrial robots" refers to technology and devices for adjusting the work schedule of robots in factories and operating them efficiently.

[0681] "Cost sharing means for allocating the usage fees for shared equipment and facilities to the departments that bear the costs" refers to technology or devices that fairly distribute the usage fees for equipment and facilities that are jointly used by multiple departments to each department.

[0682] The present invention is a system for improving the efficiency of work coordination and cost management within a factory, and is specifically implemented as follows.

[0683] System Configuration

[0684] This system includes a communication means for accepting requests from users, a generative artificial intelligence device that obtains each user's schedule and selects the most suitable candidate date, a reservation means that searches for reservation information from a reservation site and presents it to the user to confirm the reservation, a payment means that collects payment information, calculates the split amount, and processes payments between users, a work coordination means that adjusts the work schedule of industrial robots, and a cost sharing means that allocates the usage fees for shared equipment and facilities to the departments that bear the costs.

[0685] Program processing and usage technology

[0686] The system uses the following hardware and software:

[0687] Communication method: Internet-enabled device (PC, smartphone, etc.)

[0688] Generative AI device: AI model using Python or JavaScript (e.g., TensorFlow, PyTorch)

[0689] Reservation method: Google Calendar API, Microsoft Outlook Calendar API

[0690] Payment method: Smartphone payment application (e.g., PayPal, Stripe)

[0691] Work coordination method: Work management software (e.g., JIRA, Trello)

[0692] Cost sharing method: Shared expense management system or spreadsheet software (e.g., Google Sheets, Microsoft Excel)

[0693] Data processing and calculation

[0694] The server processes and calculates data using the following means.

[0695] 1. Communication: Receives requests from users (e.g., scheduling or reservation requests) and analyzes their content. This communication requires an internet connection and uses messenger applications such as Slack or Microsoft Teams.

[0696] 2. Generative AI: Collects each user's calendar information via API, analyzes the data, and selects the best candidate dates. During this process, an AI model is used to adjust the schedule to avoid conflicts.

[0697] 3. Reservation method: Based on the obtained candidate dates, search for suitable reservation information from a reservation site (e.g., a restaurant reservation site) and present it to the user. The reservation is confirmed based on the user's selection.

[0698] 4. Payment Method: Payment information is collected after meals or tasks are completed, and the split amount is calculated. The necessary payment process is notified to each user and carried out through a smartphone payment application.

[0699] 5. Work Coordination: The server coordinates the work schedules of the industrial robots and schedules them efficiently. In this process, work management software is used to set up the work plan and allocate the necessary resources.

[0700] 6. Cost sharing measures: Calculate the appropriate cost sharing for shared equipment and facilities among each department. This information is entered into a shared expense management system or spreadsheet software for transparent cost management.

[0701] Specific examples

[0702] As a concrete example, consider the case where a user performs the following process:

[0703] 1. Scheduling: The factory maintenance team leader requests on Slack, "I'd like to perform maintenance on Robot A next Monday." The server receives this request, collects the schedules of each maintenance team member via the Google Calendar API, and suggests the optimal time slot.

[0704] 2. Reservation: The maintenance team reserves the necessary equipment and tools based on a specific date. The reservation information is retrieved by the server, presented to the team, and confirmed.

[0705] 3. Cost sharing: After maintenance, in response to a request to "calculate the cost sharing," the server aggregates the time and resources used by each department and calculates a fair cost sharing. The amount of the burden is notified to each department and recorded in the shared expense management system.

[0706] Prompt Sentence Examples

[0707] "I would like you to perform maintenance on Robot A next Monday."

[0708] "Please calculate the cost sharing after the maintenance is completed."

[0709] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0710] Step 1:

[0711] As a maintenance team leader at a factory, the user types into a messenger application, "I would like to perform maintenance on Robot A next Monday." The server receives this message. The input data is the user's request, and the server proceeds to the next step based on this.

[0712] Step 2:

[0713] The server starts the generative artificial intelligence device and obtains the calendar information of each maintenance member using the Google Calendar API. The input data is the calendar information of each maintenance member, and this data is analyzed to identify common free time slots. The output data is the optimal candidate date and time slot.

[0714] Step 3:

[0715] The server uses an emotion engine to analyze members' reactions and emotions and propose optimal candidate dates. Input data is the user's chat content and past reactions, and based on this, emotion data is obtained to confirm whether the proposed date and time are appropriate. The output data is a candidate date adjusted based on the emotions.

[0716] Step 4:

[0717] The server presents the adjusted candidate date to the group chat of the messenger application. The input data is the optimal candidate date, and by presenting it to the user, the process of obtaining the user's consent begins. The output data is the user's consent or a request for revision.

[0718] Step 5:

[0719] The user checks the proposed dates and replies "OK." The device sends this acceptance message to the server. The input data is the user's reply message, which the server receives and confirms everyone's acceptance. The output data is the confirmed schedule information.

[0720] Step 6:

[0721] The server notifies all maintenance members of the confirmed schedule information. The input data is the confirmed schedule information, and the schedule is finalized when the server sends it to all members. The output data is a notification to all members.

[0722] Step 7:

[0723] The user requests a specific reservation (for example, reserving a specific industrial robot or tool for maintenance). The server receives this request. The input data is the user's reservation request, and based on this, the next step is taken.

[0724] Step 8:

[0725] The server uses the reservation site's API to search for the necessary reservation information and present candidates. The input data is the user's reservation conditions (date, time, location, facilities), and reservation candidates are obtained based on this. The output data is a list of reservation candidates.

[0726] Step 9:

[0727] The user selects one of the reservation options presented and sends a request. The terminal sends this selection information to the server. The input data is the user's selection information, which the server receives and confirms the reservation. The output data is the confirmed reservation information.

[0728] Step 10:

[0729] The server notifies all maintenance members of the confirmed reservation information. The input data is the confirmed reservation information, and the reservation is confirmed when the server sends it to all members. The output data is a notification to all members.

[0730] Step 11:

[0731] After the maintenance is completed, the user requests "Please calculate the cost share." The server receives this request. The input data is the user's request, and the server proceeds to the next step based on this.

[0732] Step 12:

[0733] The server obtains the information necessary to collect the usage time and resources of each department. The input data is the usage information reported by each department, and the cost sharing is calculated based on this. The output data is the amount borne by each department.

[0734] Step 13:

[0735] The server notifies each department of the total burden amount. The input data is the burden amount of each department, and the server sends it to all departments, making the cost sharing clear. The output data is a notification of the cost sharing.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] [Second embodiment]

[0740] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0741] 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.

[0742] 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).

[0743] 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.

[0744] 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.

[0745] 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).

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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."

[0752] This invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence within a messenger application. The system of the present invention operates as follows.

[0753] Schedule adjustment

[0754] Receiving a rescheduling request

[0755] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[0756] The terminal sends this request to the server.

[0757] Calendar integration

[0758] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[0759] The server analyzes the acquired calendar information and identifies commonly available time slots.

[0760] Proposal of dates

[0761] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[0762] A notification is sent to the device and the user can confirm the proposed dates via chat.

[0763] Confirmation of schedule

[0764] The user confirms and accepts the proposed dates and replies "OK" via chat.

[0765] The terminal transmits the user's consent to the server.

[0766] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[0767] reservation

[0768] Receiving a booking request

[0769] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0770] The terminal sends this request to the server.

[0771] Search for reservation candidates

[0772] The server uses generative artificial intelligence to access the API of the restaurant reservation site and obtain restaurant information that meets the criteria.

[0773] The server lists the restaurant candidates and presents them to the chat group.

[0774] Confirmation of reservation

[0775] The user selects one restaurant from the presented options and replies via chat.

[0776] The terminal transmits the selection result to the server.

[0777] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[0778] The server notifies everyone of the confirmed reservation information.

[0779] Split payment

[0780] Receiving a split bill request

[0781] After a meal, a user chats and asks to split the bill.

[0782] The terminal sends this request to the server.

[0783] Collecting payment information

[0784] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[0785] The user enters the payment amount in the chat.

[0786] The terminal transmits the payment information entered by the user to the server.

[0787] Calculating the split amount

[0788] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0789] Payment Processing

[0790] The server notifies each user of the total amount of payment and instructs them to make payment.

[0791] Users follow the instructions and make payments using the app's payment function.

[0792] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[0793] Specific Examples

[0794] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[0795] Schedule adjustment

[0796] 1. User A proposes a date for a meal via chat and sends a request.

[0797] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[0798] 3. The server presents the proposed dates in the group chat and gets everyone's approval.

[0799] reservation

[0800] 1. User B requests a reservation at a specific restaurant based on confirmed dates.

[0801] 2. The server presents reservation options and automatically makes a reservation at the restaurant selected by the user.

[0802] 3. The server notifies everyone of the confirmed reservation information.

[0803] Split payment

[0804] 1. User C requests splitting the bill and submits a request.

[0805] 2. The server collects the payment amount from each user and calculates and notifies the split amount.

[0806] 3. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[0807] This method allows all operations to be completed within the messenger application, resulting in a significant improvement in user convenience.

[0808] The processing flow will be explained below.

[0809] Schedule adjustment

[0810] Step 1:

[0811] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[0812] The terminal sends this request to the server.

[0813] Step 2:

[0814] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[0815] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[0816] The server analyzes the acquired calendar information and identifies commonly available time slots.

[0817] Step 3:

[0818] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[0819] A notification is sent to the device and the user can confirm the proposed dates via chat.

[0820] Step 4:

[0821] The user confirms and accepts the proposed dates and replies "OK" via chat.

[0822] The terminal transmits the user's consent to the server.

[0823] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[0824] reservation

[0825] Step 1:

[0826] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0827] The terminal sends this request to the server.

[0828] Step 2:

[0829] The server uses generative artificial intelligence to access the API of the restaurant reservation site and obtain restaurant information that meets the criteria.

[0830] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[0831] The server lists the restaurant candidates and presents them to the chat group.

[0832] Step 3:

[0833] The user selects one restaurant from the presented options and replies via chat.

[0834] The terminal transmits the selection result to the server.

[0835] Step 4:

[0836] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[0837] The server notifies everyone of the confirmed reservation information.

[0838] Split payment

[0839] Step 1:

[0840] After a meal, a user chats and asks to split the bill.

[0841] The terminal sends this request to the server.

[0842] Step 2:

[0843] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[0844] The user enters the payment amount in the chat.

[0845] The terminal transmits the payment information entered by the user to the server.

[0846] Step 3:

[0847] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0848] Step 4:

[0849] The server notifies each user of the total amount of payment and instructs them to make payment.

[0850] Users follow the instructions and make payments using the app's payment function.

[0851] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[0852] Example 1

[0853] 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."

[0854] Traditional messenger applications lacked the ability to centralize complex tasks such as scheduling, booking, and splitting bills. As a result, users had to perform these tasks individually in separate applications or manually, which required a great deal of time and effort. Furthermore, there was a high likelihood of mismatched or missing information between tasks, hindering smooth communication and efficient progress. This resulted in reduced user convenience and a poor quality experience.

[0855] 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.

[0856] In this invention, the server includes a communication application that accepts requests from users, a generative artificial intelligence means that acquires each user's schedule and selects the best candidate date, a device that acquires reservation information, presents it to the user, and confirms the reservation, a device that collects payment information, calculates the split amount, and processes payments between users, and a means for completing these operations within the messenger application. This allows users to efficiently and easily process schedule adjustments, reservations, and split payment settlements within a single messenger application.

[0857] A "communications application" is software that enables text messaging, voice, and video calls between users over the Internet.

[0858] "Generative AI" is an AI technology that learns from large amounts of data to perform prediction and generation tasks, rather than using traditional rule-based systems.

[0859] "Device" refers to hardware or software designed to perform a specific task, which in this invention includes obtaining, submitting, and confirming reservation information, collecting payment information, calculating split amounts, and processing payments.

[0860] "Means" refer to the methods, processes, or technical techniques required to achieve a particular function.

[0861] A "user" is a person or group of people who make requests such as scheduling, booking, splitting bills, etc. through a communication application.

[0862] "Candidate dates" refer to common available dates that are proposed taking into consideration the schedules of all users.

[0863] "Reservation information" refers to data necessary to guarantee the use of a specific service or place, and in the present invention, particularly refers to reservation data for restaurants and the like.

[0864] "Payment Information" means data related to a particular transaction, such as the amount and payment method.

[0865] "Split amount" refers to an amount calculated to divide multiple payments equally or in specific proportions.

[0866] "Complete within the messenger application" means that the user does not need to switch to an external application to complete a specific task, and all operations are completed within one application.

[0867] The present invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence within a messenger application. The system includes the following major hardware and software components:

[0868] Hardware and Software Components

[0869] 1. Server

[0870] Generative artificial intelligence: Using OpenAI's GPT-4 as an example.

[0871] API: Google Calendar API, restaurant reservation sites (e.g. Gurunavi API, Tabelog API)

[0872] Communication module: Data communication using HTTP / HTTPS protocol

[0873] 2. Terminal

[0874] Messenger applications: General communication applications (e.g., LINE, WhatsApp)

[0875] Data transmission / reception module: HTTP request sending and response receiving functions

[0876] 3. Users

[0877] Input devices: smartphones, tablets, PCs, etc.

[0878] Scheduling details

[0879] A user types "Let's all get together for dinner next Friday" in a chat group within a messenger application. The device sends this request to the server as an HTTP request. The server uses the received request as a trigger to launch a generative artificial intelligence (AI) and obtain schedule information from each user's Google Calendar API. The server analyzes this information, identifies common free time slots, and selects the most suitable candidate date. The selected candidate date (e.g., "Next Friday at 7pm") is notified within the chat group via the device. When the user accepts the candidate date, the final date is confirmed and everyone is notified.

[0880] Booking details

[0881] The user types "Make a reservation at a Japanese restaurant in Shinjuku" in a messenger application. The device sends this request to the server. The server uses generative artificial intelligence to access the APIs of multiple restaurant reservation sites and retrieve restaurant information that meets the criteria. The retrieved restaurant candidates are notified to the user via the device. When the user selects one restaurant from the candidates and replies, the server automatically makes a reservation at the selected restaurant and retrieves the reservation confirmation information. The server then notifies the chat group of the reservation confirmation information, and the device displays it to the user.

[0882] Split payment details

[0883] After the meal, a user requests in chat to "split the bill." The device sends this request to the server. The server then collects payment information by sending a message to each user asking them to enter their expected payment amount. Each user enters their payment amount in chat and sends that information to the server via their device. The server uses generative artificial intelligence to tally the entered payment amounts and calculates each user's share of the bill. Finally, the server notifies each user of the total share of the bill and instructs them to pay. Users follow the instructions and make the payment using the payment function within the app (e.g., PayPay, LINE Pay). The server confirms that each user has completed payment and sends a notification of settlement completion to everyone.

[0884] Examples and prompts

[0885] For example, if a user is planning a meal at a restaurant with a group of friends, they can enter the prompt text as follows:

[0886] "Let's all get together for dinner next Friday," I typed into the chat.

[0887] "Make a reservation at a Japanese restaurant in Shinjuku," he requested.

[0888] He asked to settle the bill, saying, "Let's split it."

[0889] This allows users to complete all operations within a single messenger application, enabling them to efficiently arrange schedules, make reservations, and split the bill.

[0890] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0891] Schedule adjustment

[0892] Step 1:

[0893] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[0894] Input: User's text message

[0895] Output: HTTP request from the terminal to the server

[0896] Step 2:

[0897] The terminal sends the received message to the server as an HTTP request.

[0898] Input: User's message

[0899] Output: The request data sent to the server

[0900] Step 3:

[0901] The server receives the request and launches a generative AI, which prepares access to the Google Calendar API for each user based on the model.

[0902] Input: HTTP request

[0903] Output: Prepare to access the calendar API

[0904] Step 4:

[0905] The server calls the Google Calendar API to obtain each user's calendar information.

[0906] Input: Calendar API request

[0907] Output: Calendar information for each user

[0908] Step 5:

[0909] The server analyzes the acquired calendar information and identifies commonly available time slots.

[0910] Input: Calendar information

[0911] Output: Candidate dates where everyone's schedules match

[0912] Step 6:

[0913] The server generates the best candidate date (e.g., "next Friday at 7pm") and notifies the chat group in the messenger application of this information.

[0914] Input: Data on the best candidate date

[0915] Output: Present candidate dates to the user

[0916] Step 7:

[0917] The terminal receives the candidate date notification from the server and displays it to the user.

[0918] Input: Candidate date notification

[0919] Output: Candidate dates displayed on the chat screen

[0920] Step 8:

[0921] The user checks the proposed dates and replies "OK" via chat.

[0922] Input: User consent message

[0923] Output: Acceptance request from device to server

[0924] Step 9:

[0925] The terminal sends the user's reply message to the server.

[0926] Input: Acceptance message

[0927] Output: Acceptance data sent to the server

[0928] Step 10:

[0929] The server waits until everyone agrees, and after confirming everyone's consent, it notifies the chat group of the confirmed date.

[0930] Input: consent data for all

[0931] Output: Notification of confirmed schedule

[0932] reservation

[0933] Step 1:

[0934] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[0935] Input: User request message

[0936] Output: Request from terminal to server

[0937] Step 2:

[0938] The terminal sends this request to the server.

[0939] Input: Request message

[0940] Output: The request sent to the server

[0941] Step 3:

[0942] The server receives the request and uses generative artificial intelligence to access the APIs of multiple restaurant reservation sites.

[0943] Input: Request data

[0944] Output: API request to the booking site

[0945] Step 4:

[0946] The server retrieves restaurant information that meets the criteria and lists it.

[0947] Input: API response

[0948] Output: Restaurant candidate list

[0949] Step 5:

[0950] The server sends the generated restaurant candidates to a chat group in a messenger application.

[0951] Input: Restaurant candidate list

[0952] Output: Information presented to the user

[0953] Step 6:

[0954] The terminal receives the list of restaurant candidates from the server and displays it to the user.

[0955] Input: Restaurant candidate list

[0956] Output: Candidate list displayed on the chat screen

[0957] Step 7:

[0958] The user selects one restaurant from the presented options and replies via chat.

[0959] Input: User's selected message

[0960] Output: Selected data from the terminal to the server

[0961] Step 8:

[0962] The terminal transmits the selection result to the server.

[0963] Input:Selection data

[0964] Output: Notify the server of the selection results

[0965] Step 9:

[0966] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[0967] Input: Selected restaurant information

[0968] Output: Confirmed reservation information

[0969] Step 10:

[0970] The server notifies the chat group of the reservation confirmation information, and the terminal displays it to the user.

[0971] Input: Confirmed reservation information

[0972] Output: User notification

[0973] Split payment

[0974] Step 1:

[0975] After a meal, a user chats and asks to split the bill.

[0976] Input: User request message

[0977] Output: Request from terminal to server

[0978] Step 2:

[0979] The terminal sends this request to the server.

[0980] Input: Request message

[0981] Output: The request sent to the server

[0982] Step 3:

[0983] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[0984] Input: Request data

[0985] Output: Message requesting expected payment amount

[0986] Step 4:

[0987] The user enters the payment amount in the chat.

[0988] Input: Payment amount Message

[0989] Output: Input data from the terminal to the server

[0990] Step 5:

[0991] The terminal transmits the payment information entered by the user to the server.

[0992] Input: Payment amount data

[0993] Output: Payment information to the server

[0994] Step 6:

[0995] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[0996] Input: Payment amount data

[0997] Output: Split amount data

[0998] Step 7:

[0999] The server notifies each user of the total split amount and instructs them to pay.

[1000] Input: Split amount data

[1001] Output: Payment instruction message

[1002] Step 8:

[1003] Users follow the instructions and make payments using the app's payment function.

[1004] Input: Payment Instruction Message

[1005] Output: Payment completion information

[1006] Step 9:

[1007] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[1008] Input: Payment completion information

[1009] Output: Payment completion notification

[1010] (Application example 1)

[1011] 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."

[1012] With traditional messaging applications, users often had to spend a lot of time coordinating schedules, making restaurant reservations, and splitting bills. These processes were also performed separately, resulting in poor overall convenience. Furthermore, insufficient information sharing and collaboration between different applications led to inconsistent user experiences.

[1013] 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.

[1014] In this invention, the server includes a message transfer application means for accepting requests from users, a generative model means for acquiring each user's schedule and selecting the optimal candidate date, a means for acquiring information from a reservation information site, presenting it to the user, and finalizing the reservation, a means for collecting payment information, calculating the split amount, and processing the payment between users, a calendar linking means for acquiring user schedule information, an information search means for searching for reservation candidates, and an electronic payment means for executing the payment process. This enables consistent operation within the messaging application, and allows each process of scheduling, making reservations, and splitting the bill to be carried out smoothly.

[1015] A "message transfer application that accepts requests from users" is an application that allows users to transmit various requests to the system by sending messages.

[1016] A "generative model" is an algorithm that uses artificial intelligence to analyze a user's schedule information and generate optimal candidate dates.

[1017] "Means for obtaining information from a reservation information site, presenting it to the user, and confirming the reservation" refers to a system for obtaining the necessary reservation information from an online reservation information service, presenting it to the user for selection, and confirming the reservation.

[1018] "Means for collecting payment information, calculating split amounts, and processing payments between users" refers to a system that collects payment amount information for each user, calculates split amounts based on that information, and ensures that appropriate payments are made between users.

[1019] The "calendar linking means for acquiring the user's schedule information" is a technology for linking with a calendar service used by the user and acquiring the schedule information.

[1020] The "information search means for searching for reservation candidates" is a technology for searching for suitable candidates from reservation information sites in response to a user request.

[1021] The "electronic payment means for executing payment processing" is a system for electronically settling payments between users based on the collected split amounts.

[1022] The present invention is a system that allows users to easily schedule, book, and split bill payments within a messaging application. The system includes the following components:

[1023] System Configuration

[1024] 1. A message transfer application that accepts requests from users

[1025] The server receives the dates and reservation requests that users propose in the chat, and these requests are sent to the server in an appropriate format.

[1026] 2. A generative model that obtains each user's schedule and selects the best candidate date

[1027] The server uses a generative AI model to retrieve and analyze each user's calendar information. For example, it uses the Google Calendar API to retrieve the user's schedule and select the best possible dates. This information is then analyzed based on prompts.

[1028] 3. A means of obtaining information from the reservation information site, presenting it to the user, and finalizing the reservation

[1029] The server searches for restaurant options from reservation information sites (e.g., OpenTable API) based on the specified date, time, and location, and presents them to the user in the chat. The server then automatically confirms the reservation based on the user's selection.

[1030] 4. A means of collecting payment information, dividing the bill, and processing payments between users.

[1031] The server collects payment information from the user, calculates the split amount using a generative AI model, notifies the user of the calculation result, and makes the payment using an electronic payment method (e.g., Stripe).

[1032] Hardware and software used

[1033] Hardware: Smartphones, smart glasses

[1034] Software: Python, Flask, Google Calendar API, OpenTable API, Stripe API

[1035] Overview of the process

[1036] 1. Scheduling:

[1037] If a user types into the chat, "Let's all get together for dinner next Friday," the server retrieves everyone's calendar information and presents the most suitable candidate dates.

[1038] 2. Reservations:

[1039] If a user types "Make a reservation at a Japanese restaurant in Shinjuku," the server will call the OpenTable API, retrieve and present restaurant information that matches the criteria, and confirm the reservation at the selected restaurant.

[1040] 3. Split the bill:

[1041] After the meal, if the user inputs "Let's split the bill," the server collects payment information, calculates the split amount using a generative AI model, and completes the payment using an electronic payment method.

[1042] Examples and prompts

[1043] For example, if a group of friends suggests in a chat, "Let's have a Japanese dinner in Shibuya next Friday," the server will check everyone's calendars and suggest "Friday at 7 PM." If a user then requests, "Make a reservation at a Japanese restaurant in Shinjuku," the server will use the OpenTable API to search for restaurants that meet the criteria and make a reservation at the recommended restaurant. After the meal, if the user requests, "Let's split the bill," the server will tally up the amounts paid by each user, calculate the split amount, and notify them.

[1044] Example prompt sentence:

[1045] I've suggested a Japanese dinner in Shibuya next Friday at 7pm. I've checked everyone's calendars and this date and time is most suitable. Please confirm and accept.

[1046] The restaurant search results are: 1. Shibuya Washokutei, 2. Ginza Washoku Teishoku, 3. Fine Japanese Restaurant. Please select the restaurant you want.

[1047] Your meal is complete. The total is 20,000 yen. We split the bill at 5,000 yen per person. Please complete the payment using the link below.

[1048] By using this system, all operations can be completed within the message forwarding app, greatly improving user convenience.

[1049] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1050] Step 1:

[1051] Input: A user inputs a scheduling request within a message forwarding application.

[1052] What happens: A user types in a chat group, "Let's all get together for dinner next Friday."

[1053] Server processing: The terminal receives this request and sends it to the server.

[1054] Output: The server receives the request and proceeds.

[1055] Step 2:

[1056] Input: The server retrieves all users' calendar information.

[1057] Specific operation: The server uses the Google Calendar API to obtain the schedule information of all participants.

[1058] Data processing: Analyze the acquired calendar information.

[1059] Server processing: Using a generative AI model, analyze each user's schedule and identify common free time slots.

[1060] Output: A list of optimal candidate dates is generated, ready to be presented to the user.

[1061] Step 3:

[1062] Input: The retrieved calendar information and a list of common free time slots.

[1063] Specific operation: The servers select "next Friday at 7pm" as a commonly available time slot.

[1064] Server processing: Format the selected candidate dates for presentation in the group chat.

[1065] Output: The server sends a notification to the device, allowing the user to check the proposed dates.

[1066] Step 4:

[1067] Input: Candidate dates provided by the server.

[1068] Specific behavior: The user confirms the proposed date in chat and replies "OK."

[1069] Terminal processing: The terminal sends the user's consent to the server.

[1070] Output: The server confirms everyone's acceptance and notifies everyone of the confirmed date.

[1071] Step 5:

[1072] Input: The user types a reservation request in the message.

[1073] Specific action: The user types, "Make a reservation at a Japanese restaurant in Shinjuku."

[1074] Terminal processing: The terminal sends this request to the server.

[1075] Output: The server receives the request and prepares to proceed.

[1076] Step 6:

[1077] Input: The server receives the reservation conditions (location, genre).

[1078] Specific operation: The server calls the OpenTable API and retrieves restaurant information using the conditions "Shinjuku" and "Japanese cuisine."

[1079] Data processing: Analyze and organize the list of restaurant candidates obtained.

[1080] Server processing: Generates a candidate list that can be presented to the user.

[1081] Output: Format the list of restaurant suggestions to present in the chat.

[1082] Step 7:

[1083] Input: A list of restaurant candidates.

[1084] Specific operation: The user selects one restaurant from the presented options and replies via chat.

[1085] Terminal processing: The terminal sends the selection results to the server.

[1086] Output: The server prepares to automatically make a reservation at the selected restaurant.

[1087] Step 8:

[1088] Input: User selection results, reservation candidate list.

[1089] Specific behavior: The server uses the OpenTable API to make a reservation at the selected restaurant.

[1090] Data processing: Obtain and format confirmed reservation information.

[1091] Server processing: Notify everyone of the confirmed reservation information.

[1092] Output: Send a notification to the device with the confirmed reservation information.

[1093] Step 9:

[1094] Input: The user enters a request for split payment in the message.

[1095] Specific action: The user types "Let's split the bill" in the chat.

[1096] Terminal processing: The terminal sends this request to the server.

[1097] Output: The server receives the request and prepares to proceed.

[1098] Step 10:

[1099] Input: Request to split the bill.

[1100] Specific operation: To collect payment information, the server sends a message to each user requesting them to enter the expected payment amount.

[1101] Data processing: Aggregate payment amounts from users.

[1102] Server processing: Using the generative AI model, the entered payment amounts are aggregated and the amount each user is responsible for is calculated.

[1103] Output: Notify each user of the split amount.

[1104] Step 11:

[1105] Input: Notification of split amount.

[1106] Specific behavior: The user makes a payment using the app's electronic payment function.

[1107] Data Processing: We process each user's payment using an electronic payment system (e.g., Stripe API).

[1108] Server processing: Confirm that each user has completed payment.

[1109] Output: Send a notification to everyone that payment is complete.

[1110] 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.

[1111] This invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence and an emotion engine within a messenger application. The system of the present invention operates as follows.

[1112] Schedule adjustment

[1113] Receiving a rescheduling request

[1114] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[1115] The terminal sends this request to the server.

[1116] Calendar integration

[1117] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[1118] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[1119] The server analyzes the acquired calendar information and identifies commonly available time slots.

[1120] Emotion recognition with emotion engine

[1121] The server activates an emotion engine to recognize each user's emotion before making scheduling suggestions.

[1122] The server analyzes the user's chat content and past responses to obtain emotional data.

[1123] The server then suggests the best possible date based on the recognized emotion data.

[1124] Proposal of dates

[1125] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[1126] A notification is sent to the device and the user can confirm the proposed dates via chat.

[1127] Confirmation of schedule

[1128] The user confirms and accepts the proposed dates and replies "OK" via chat.

[1129] The terminal transmits the user's consent to the server.

[1130] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[1131] reservation

[1132] Receiving a booking request

[1133] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[1134] The terminal sends this request to the server.

[1135] Search for reservation candidates

[1136] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant reservation site and obtain restaurant information that meets the criteria.

[1137] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[1138] The emotion engine considers the user's emotional state and prioritizes appropriate restaurants to provide a better user experience.

[1139] The server lists the restaurant candidates and presents them to the chat group.

[1140] Confirmation of reservation

[1141] The user selects one restaurant from the presented options and replies via chat.

[1142] The terminal transmits the selection result to the server.

[1143] Notification of final information

[1144] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[1145] The server notifies everyone of the confirmed reservation information.

[1146] Split payment

[1147] Receiving a split bill request

[1148] After a meal, a user chats and asks to split the bill.

[1149] The terminal sends this request to the server.

[1150] Collecting payment information

[1151] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[1152] The user enters the payment amount in the chat.

[1153] The terminal transmits the payment information entered by the user to the server.

[1154] Emotion recognition with emotion engine

[1155] The server activates an emotion engine to recognize the emotion of each user during payment information collection and bill splitting calculation.

[1156] The server analyzes the user's chat content and reactions to obtain emotional data.

[1157] The server provides appropriate communication methods and feedback based on the recognized emotion data.

[1158] Calculating the split amount

[1159] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[1160] Payment Processing

[1161] The server notifies each user of the total amount of payment and instructs them to make payment.

[1162] Users follow the instructions and make payments using the app's payment function.

[1163] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[1164] Specific Examples

[1165] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[1166] Schedule adjustment

[1167] 1. User A proposes a date for a meal in chat, types "next Friday," and sends the request.

[1168] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[1169] 3. The server uses the emotion engine to recognize each user's emotion data and check whether the candidate date matches the user's emotion.

[1170] 4. The server presents the proposed dates in the group chat and gets everyone's approval.

[1171] reservation

[1172] 1. User B requests a reservation at a specific restaurant based on confirmed dates.

[1173] 2. The server uses generative artificial intelligence and an emotion engine to present reservation options that meet the criteria, and the user can select one.

[1174] 3. The server will automatically make a reservation at the selected restaurant and notify everyone of the reservation confirmation.

[1175] Split payment

[1176] 1. User C requests splitting the bill and submits a request.

[1177] 2. The server collects the payment amount of each user and monitors the emotions of each user using an emotion engine.

[1178] 3. The server uses generative artificial intelligence to calculate the split amount and instructs payment.

[1179] 4. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[1180] This method not only allows all operations to be completed within the messenger application, greatly improving user convenience, but also further improves the user experience through processes that utilize the emotion engine.

[1181] The processing flow will be explained below.

[1182] Schedule adjustment

[1183] Step 1:

[1184] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[1185] The terminal sends this request to the server.

[1186] Step 2:

[1187] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[1188] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[1189] Step 3:

[1190] The server analyzes the acquired calendar information and identifies commonly available time slots.

[1191] Step 4:

[1192] The server activates an emotion engine to recognize each user's emotion before making suggestions.

[1193] The server analyzes the user's chat content and past responses to obtain emotional data.

[1194] Step 5:

[1195] The server selects the most suitable candidate date based on the recognized emotion data.

[1196] Step 6:

[1197] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[1198] A notification is sent to the device and the user can confirm the proposed dates via chat.

[1199] Step 7:

[1200] The user confirms and accepts the proposed dates and replies "OK" via chat.

[1201] The terminal transmits the user's consent to the server.

[1202] Step 8:

[1203] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[1204] reservation

[1205] Step 1:

[1206] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[1207] The terminal sends this request to the server.

[1208] Step 2:

[1209] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant reservation site and obtain restaurant information that meets the criteria.

[1210] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[1211] Step 3:

[1212] The emotion engine considers the user's emotional state and prioritizes appropriate restaurants to provide a better user experience.

[1213] Step 4:

[1214] The server lists the restaurant candidates and presents them to the chat group.

[1215] Step 5:

[1216] The user selects one restaurant from the presented options and replies via chat.

[1217] The terminal transmits the selection result to the server.

[1218] Step 6:

[1219] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[1220] Step 7:

[1221] The server notifies everyone of the confirmed reservation information.

[1222] Split payment

[1223] Step 1:

[1224] After a meal, a user chats and asks to split the bill.

[1225] The terminal sends this request to the server.

[1226] Step 2:

[1227] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[1228] The user enters the payment amount in the chat.

[1229] The terminal transmits the payment information entered by the user to the server.

[1230] Step 3:

[1231] The server activates an emotion engine to recognize the emotion of each user during payment information collection and bill splitting calculation.

[1232] The server analyzes the user's chat content and reactions to obtain emotional data.

[1233] Step 4:

[1234] The server provides appropriate communication methods and feedback based on the recognized emotion data.

[1235] Step 5:

[1236] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[1237] Step 6:

[1238] The server notifies each user of the total amount of payment and instructs them to make payment.

[1239] Step 7:

[1240] Users follow the instructions and make payments using the app's payment function.

[1241] Step 8:

[1242] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[1243] Specific Examples

[1244] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[1245] 1. User A proposes a date for a meal in chat, types "next Friday," and sends the request.

[1246] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[1247] 3. The server uses the emotion engine to recognize each user's emotion data and check whether the candidate date matches the user's emotion.

[1248] 4. The server presents the proposed dates in the group chat and gets everyone's approval.

[1249] 5. User B requests a reservation at a specific restaurant based on confirmed dates.

[1250] 6. The server uses generative artificial intelligence and an emotion engine to present reservation options that meet the criteria, and the user can select one.

[1251] 7. The server will automatically make a reservation at the selected restaurant and notify everyone of the reservation confirmation.

[1252] 8. User C requests splitting the bill and submits a request.

[1253] 9. The server collects the payment amount of each user and monitors the emotions of each user using the emotion engine.

[1254] 10. The server uses generative artificial intelligence to calculate the split amount and instructs payment.

[1255] 11. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[1256] This method not only allows all operations to be completed within the messenger application, greatly improving user convenience, but also further improves the user experience through processes that utilize the emotion engine.

[1257] Example 2

[1258] 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."

[1259] With conventional messenger applications, it was difficult to coordinate schedules, make reservations, and split payments all in one place, requiring users to use each application and service individually. Furthermore, due to a lack of smooth communication and understanding of emotions between users, it was difficult to select appropriate dates, make reservations, and process payments. This resulted in a poor user experience and required a lot of effort.

[1260] 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 a messenger application that accepts requests from users, a generative artificial intelligence means that acquires each user's schedule and selects the optimal candidate date, a means that recognizes user emotions using an emotion engine and optimizes schedule adjustment and reservation suggestions, a means that searches for reservation information from a reservation site and presents it to the user to confirm the reservation, a means that collects payment information and calculates the split amount and processes payments between users, a means that notifies all users of the approved schedule, and a means that notifies users of the confirmed reservation information after the reservation is confirmed. This allows users to centrally adjust schedules, make reservations, and split the bill within the messenger application, significantly improving user convenience and experience.

[1261] A "messenger application that accepts requests from users" is software that allows users to request operations and communicate through messages, and provides various services in cooperation with a server.

[1262] "Generative AI that obtains each user's schedule and selects the optimal candidate date" is an AI technology that analyzes the user's calendar data and suggests the optimal date and time taking into account the user's overall schedule.

[1263] "Means for searching reservation information from reservation sites, presenting it to the user, and finalizing the reservation" refers to a technology that accesses multiple reservation information providing sites to collect reservation information that meets the conditions, presents the candidates to the user, and executes the reservation based on the user's selection.

[1264] "Means for collecting payment information, calculating split amounts, and processing payments between users" refers to technology for collecting payment amount information from users, calculating fair split amounts, and smoothly processing payments.

[1265] "Means of using an emotion engine to recognize user emotions and optimize schedule adjustment and reservation suggestions" is a technology that analyzes a user's messages and past data to recognize their emotional state and suggests optimal dates and reservation details based on those emotions.

[1266] The "means for presenting candidate dates and receiving user's consent" is a technique for presenting optimal candidate dates to the user and receiving a response of approval or rejection from the user.

[1267] The "means for notifying all users of the approved schedule" is a technique for simultaneously notifying all users of the approved schedule.

[1268] "Means for notifying users of confirmed reservation information after a reservation is confirmed" refers to a technique for notifying all users of confirmed reservation information after the reservation procedure is completed.

[1269] This invention is a system that uses a messenger application to efficiently arrange schedules, make reservations, and split the bill. The devices used are the user's terminal (such as a smartphone or PC) and a server, which are linked via a communication network.

[1270] Overall structure

[1271] The system works by linking a messenger application, generative artificial intelligence, an emotion engine, and various APIs.

[1272] 1. Messenger Applications

[1273] Users request scheduling, reservations, and bill splits through a messenger application, which sends the requests to the server and receives responses from the server.

[1274] 2. Generative Artificial Intelligence

[1275] The server uses generative artificial intelligence to analyze each user's calendar information and propose optimal schedule adjustments. Calendar information is obtained through the APIs of Google Calendar and Outlook Calendar.

[1276] 3. Emotion Engine

[1277] The server uses an emotion engine to analyze the user's emotions. Based on the analysis results, it proposes optimal dates and reservations that match the user's emotions. Emotion data is obtained from the user's past message history and real-time reactions.

[1278] 4. Booking API

[1279] The server searches for reservation candidates that match the conditions via the API of various reservation sites, presents the acquired reservation information to the user, and confirms the reservation based on the user's selection.

[1280] 5. Payment Processing Functions

[1281] The server collects payment information from users, calculates split amounts using generative artificial intelligence, and processes payment instructions and payment confirmations.

[1282] Specific examples

[1283] Specific examples of schedule adjustments

[1284] User A sends a request to a chat group saying, "Let's all get together for dinner next Friday." The server uses the Google Calendar or Outlook Calendar API to obtain each user's calendar information and identify commonly available time slots. It then activates an emotion engine to analyze the user's emotional state. It then suggests the most suitable candidate date, for example, "next Friday at 7 p.m." The user replies "OK," and the server confirms everyone's acceptance before notifying them of the confirmed date.

[1285] Specific reservation examples

[1286] User B makes a request via a messenger application, saying, "Make a reservation at a Japanese restaurant in Shinjuku." The server searches for the criteria "Shinjuku," "Japanese food," and "next Friday night at 7pm" via the restaurant reservation site's API. Using an emotion engine, it prioritizes and selects the most suitable restaurant, taking into account the user's emotional state. The obtained restaurant candidates are then listed and presented to the chat group. The server then automatically makes a reservation at the restaurant selected by the user and notifies everyone of the confirmed reservation.

[1287] Specific examples of split payment

[1288] After the meal, User C sends a request via chat to "split the bill." The server sends each user a message prompting them to enter their expected payment amount. The user enters the payment amount via chat and sends it to the server. The emotion engine is activated to monitor the user's emotional state. Generative artificial intelligence is used to calculate the split amount based on the entered payment amount. The server notifies each user of the calculation result and instructs them to pay. The user pays using the payment function within the app, and after the server confirms that payment has been completed, it sends a notification to everyone that the settlement has been completed.

[1289] Example prompts

[1290] "Please arrange a date for us to all have dinner together next Friday at 7pm."

[1291] "Make a reservation at a Japanese restaurant in Shinjuku."

[1292] "Please split the bill."

[1293] Through this specific system configuration and operation procedure, the present invention can provide users with efficient and smooth schedule adjustment, reservation, and split payment functions.

[1294] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1295] Schedule adjustment

[1296] Step 1: Receiving a scheduling request

[1297] A user types, "Let's all get together for dinner next Friday" into a chat group on a messenger application.

[1298] The device sends this request to the server.

[1299] Input: User request message

[1300] Output: Request data to the server

[1301] Step 2: Calendar Integration

[1302] The server runs a generative artificial intelligence and calls the Google Calendar or Outlook Calendar API to retrieve each user's calendar information.

[1303] The server collects calendar information through an API with each user's permission.

[1304] Input: A request to get the user's calendar information

[1305] Data processing: Obtain calendar information through API and analyze it

[1306] Output: Parsed calendar information

[1307] Step 3: Emotion recognition by the emotion engine

[1308] The server launches an emotion engine and analyzes the user's chat content and past responses to obtain emotional data.

[1309] Input: User chat content, past reaction data

[1310] Data calculation: Recognize and acquire emotional data using the emotion engine

[1311] Output: User emotion data

[1312] Step 4: Present possible dates

[1313] The server will suggest the best possible dates based on the analyzed calendar information and emotional data.

[1314] For example, you could suggest "next Friday night at 7pm" in a group chat.

[1315] A notification will be sent to the device and the user can confirm the suggested dates.

[1316] Input: Analyzed calendar information, emotion data

[1317] Data calculation: Identifying the best candidate date

[1318] Output: Best candidate date notification

[1319] Step 5: Confirm the date

[1320] The user checks the proposed dates and replies with an "OK" message via chat to indicate their acceptance.

[1321] The device sends the user's consent to the server.

[1322] After the server confirms everyone's consent, it will notify everyone of the confirmed date.

[1323] Input: User consent message

[1324] Data calculation: Confirmation of consent from all users

[1325] Output: Notification of confirmed schedule

[1326] reservation

[1327] Step 1: Receiving a booking request

[1328] The user simply types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[1329] The device sends this request to the server.

[1330] Input: User's reservation request message

[1331] Output: Reservation request data to the server

[1332] Step 2: Search for potential reservations

[1333] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant booking site.

[1334] The server retrieves restaurant information based on conditions such as "Shinjuku," "Japanese cuisine," and "next Friday night at 7 p.m."

[1335] Input: Reservation conditions (e.g., location, Shinjuku; genre, Japanese; time, next Friday at 7pm)

[1336] Data processing: Acquiring restaurant information through API

[1337] Output: A list of restaurant candidates obtained

[1338] Step 3: Optimizing with an Emotion Engine

[1339] The server uses an emotion engine to analyze the user's emotional state and prioritize appropriate restaurants.

[1340] Input: Obtained restaurant candidate list, user emotion data

[1341] Data calculations: Using sentiment engines to filter the best restaurants

[1342] Output: A list of the best restaurants

[1343] Step 4: Suggest candidates

[1344] The server will create a list of the best restaurant options and present them in the group chat.

[1345] The user selects one restaurant from the presented options and responds via chat.

[1346] The device sends the selection results to the server.

[1347] Input: Best Restaurant Shortlist

[1348] Output: Present candidate list to user, user selection message

[1349] Step 5: Confirm your booking

[1350] The server automatically makes a reservation at the selected restaurant and retrieves the reservation confirmation information.

[1351] The server will then notify everyone of the confirmed reservation information.

[1352] Input: User's selected message

[1353] Data calculation: Reservation processing through the booking site's API

[1354] Output: Notification of confirmed reservation information

[1355] Split payment

[1356] Step 1: Receiving a split request

[1357] After a meal, the user can chat and ask to split the bill.

[1358] The device sends this request to the server.

[1359] Input: User's bill split request message

[1360] Output: Split request data to the server

[1361] Step 2: Collect payment information

[1362] The server sends each user a message prompting them to enter their expected payment amount.

[1363] The user enters the payment amount in chat and sends it to the server.

[1364] Input: User payment amount input message

[1365] Output: Payment information from the user

[1366] Step 3: Emotion recognition by the emotion engine

[1367] The server runs an emotion engine to recognize each user's emotion during payment information collection and bill splitting.

[1368] Input: User's payment information, chat contents

[1369] Data calculation: Recognize and acquire emotional data using the emotion engine

[1370] Output: Emotion data

[1371] Step 4: Calculate the split amount

[1372] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[1373] Input: User's payment information

[1374] Data calculation: aggregation and charge calculation

[1375] Output: Split amount

[1376] Step 5: Payment Processing

[1377] The server notifies each user of the total amount due and instructs them to pay.

[1378] Users follow the instructions and make payments using the in-app payment function.

[1379] The server confirms that each user has completed payment and sends a notification to everyone that the payment has been completed.

[1380] Input: Split amount, user payment information

[1381] Data calculation: Confirmation of payment processing

[1382] Output: Payment completion notification

[1383] Through the above processing steps, the present system can greatly improve user convenience and further enrich the user experience.

[1384] (Application example 2)

[1385] 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."

[1386] Conventional messenger applications can accept user requests and adjust schedules and make reservations, but they do not support work coordination and cost sharing for industrial robots, making it difficult to efficiently manage work and costs within factories.In addition, the sharing of usage fees for shared equipment and facilities is unclear, so there is a need for optimal schedule adjustment and an improved user experience.

[1387] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1388] In this invention, the server includes a communication means for accepting requests from users, a generative artificial intelligence device for acquiring each user's schedule and selecting the optimal candidate date, a reservation means for searching reservation information from a reservation site, presenting it to the user, and finalizing the reservation, a payment means for collecting payment information, calculating the split amount, and processing payments between users, a work coordination means for adjusting the work schedule of industrial robots, and a cost sharing means for sharing the usage fees for shared equipment and facilities among the responsible departments. This enables efficient work coordination and transparent cost management within the factory.

[1389] "Communication means for accepting requests from users" refers to technology or devices for receiving requests or instructions from users via a communication network.

[1390] The "generative artificial intelligence device that acquires each user's schedule and selects the optimal candidate date" is an artificial intelligence system that collects users' schedule information and automatically selects the optimal date based on that data.

[1391] "Reservation means for searching reservation information from a reservation site, presenting it to the user, and confirming the reservation" refers to technology or devices that search for the necessary reservation information from an online reservation platform, provide it to the user, and confirm the reservation.

[1392] A "payment method that collects payment information, splits the bill, and processes payments between users" refers to technology or a device that collects payment information from each user, splits the amount equally, and executes the payment process.

[1393] "Work adjustment means for adjusting the work schedule of industrial robots" refers to technology and devices for adjusting the work schedule of robots in factories and operating them efficiently.

[1394] "Cost sharing means for allocating the usage fees for shared equipment and facilities to the departments that bear the costs" refers to technology or devices that fairly distribute the usage fees for equipment and facilities that are jointly used by multiple departments to each department.

[1395] The present invention is a system for improving the efficiency of work coordination and cost management within a factory, and is specifically implemented as follows.

[1396] System Configuration

[1397] This system includes a communication means for accepting requests from users, a generative artificial intelligence device that obtains each user's schedule and selects the most suitable candidate date, a reservation means that searches for reservation information from a reservation site and presents it to the user to confirm the reservation, a payment means that collects payment information, calculates the split amount, and processes payments between users, a work coordination means that adjusts the work schedule of industrial robots, and a cost sharing means that allocates the usage fees for shared equipment and facilities to the departments that bear the costs.

[1398] Program processing and usage technology

[1399] The system uses the following hardware and software:

[1400] Communication method: Internet-enabled device (PC, smartphone, etc.)

[1401] Generative AI device: AI model using Python or JavaScript (e.g., TensorFlow, PyTorch)

[1402] Reservation method: Google Calendar API, Microsoft Outlook Calendar API

[1403] Payment method: Smartphone payment application (e.g., PayPal, Stripe)

[1404] Work coordination method: Work management software (e.g., JIRA, Trello)

[1405] Cost sharing method: Shared expense management system or spreadsheet software (e.g., Google Sheets, Microsoft Excel)

[1406] Data processing and calculation

[1407] The server processes and calculates data using the following means.

[1408] 1. Communication: Receives requests from users (e.g., scheduling or reservation requests) and analyzes their content. This communication requires an internet connection and uses messenger applications such as Slack or Microsoft Teams.

[1409] 2. Generative AI: Collects each user's calendar information via API, analyzes the data, and selects the best candidate dates. During this process, an AI model is used to adjust the schedule to avoid conflicts.

[1410] 3. Reservation method: Based on the obtained candidate dates, search for suitable reservation information from a reservation site (e.g., a restaurant reservation site) and present it to the user. The reservation is confirmed based on the user's selection.

[1411] 4. Payment Method: Payment information is collected after meals or tasks are completed, and the split amount is calculated. The necessary payment process is notified to each user and carried out through a smartphone payment application.

[1412] 5. Work Coordination: The server coordinates the work schedules of the industrial robots and schedules them efficiently. In this process, work management software is used to set up the work plan and allocate the necessary resources.

[1413] 6. Cost sharing measures: Calculate the appropriate cost sharing for shared equipment and facilities among each department. This information is entered into a shared expense management system or spreadsheet software for transparent cost management.

[1414] Specific examples

[1415] As a concrete example, consider the case where a user performs the following process:

[1416] 1. Scheduling: The factory maintenance team leader requests on Slack, "I'd like to perform maintenance on Robot A next Monday." The server receives this request, collects the schedules of each maintenance team member via the Google Calendar API, and suggests the optimal time slot.

[1417] 2. Reservation: The maintenance team reserves the necessary equipment and tools based on a specific date. The reservation information is retrieved by the server, presented to the team, and confirmed.

[1418] 3. Cost sharing: After maintenance, in response to a request to "calculate the cost sharing," the server aggregates the time and resources used by each department and calculates a fair cost sharing. The amount of the burden is notified to each department and recorded in the shared expense management system.

[1419] Prompt Sentence Examples

[1420] "I would like you to perform maintenance on Robot A next Monday."

[1421] "Please calculate the cost sharing after the maintenance is completed."

[1422] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1423] Step 1:

[1424] As a maintenance team leader at a factory, the user types into a messenger application, "I would like to perform maintenance on Robot A next Monday." The server receives this message. The input data is the user's request, and the server proceeds to the next step based on this.

[1425] Step 2:

[1426] The server starts the generative artificial intelligence device and obtains the calendar information of each maintenance member using the Google Calendar API. The input data is the calendar information of each maintenance member, and this data is analyzed to identify common free time slots. The output data is the optimal candidate date and time slot.

[1427] Step 3:

[1428] The server uses an emotion engine to analyze members' reactions and emotions and propose optimal candidate dates. Input data is the user's chat content and past reactions, and based on this, emotion data is obtained to confirm whether the proposed date and time are appropriate. The output data is a candidate date adjusted based on the emotions.

[1429] Step 4:

[1430] The server presents the adjusted candidate date to the group chat of the messenger application. The input data is the optimal candidate date, and by presenting it to the user, the process of obtaining the user's consent begins. The output data is the user's consent or a request for revision.

[1431] Step 5:

[1432] The user checks the proposed dates and replies "OK." The device sends this acceptance message to the server. The input data is the user's reply message, which the server receives and confirms everyone's acceptance. The output data is the confirmed schedule information.

[1433] Step 6:

[1434] The server notifies all maintenance members of the confirmed schedule information. The input data is the confirmed schedule information, and the schedule is finalized when the server sends it to all members. The output data is a notification to all members.

[1435] Step 7:

[1436] The user requests a specific reservation (for example, reserving a specific industrial robot or tool for maintenance). The server receives this request. The input data is the user's reservation request, and based on this, the next step is taken.

[1437] Step 8:

[1438] The server uses the reservation site's API to search for the necessary reservation information and present candidates. The input data is the user's reservation conditions (date, time, location, facilities), and reservation candidates are obtained based on this. The output data is a list of reservation candidates.

[1439] Step 9:

[1440] The user selects one of the reservation options presented and sends a request. The terminal sends this selection information to the server. The input data is the user's selection information, which the server receives and confirms the reservation. The output data is the confirmed reservation information.

[1441] Step 10:

[1442] The server notifies all maintenance members of the confirmed reservation information. The input data is the confirmed reservation information, and the reservation is confirmed when the server sends it to all members. The output data is a notification to all members.

[1443] Step 11:

[1444] After the maintenance is completed, the user requests "Please calculate the cost share." The server receives this request. The input data is the user's request, and the server proceeds to the next step based on this.

[1445] Step 12:

[1446] The server obtains the information necessary to collect the usage time and resources of each department. The input data is the usage information reported by each department, and the cost sharing is calculated based on this. The output data is the amount borne by each department.

[1447] Step 13:

[1448] The server notifies each department of the total burden amount. The input data is the burden amount of each department, and the server sends it to all departments, making the cost sharing clear. The output data is a notification of the cost sharing.

[1449] 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.

[1450] 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.

[1451] 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.

[1452] [Third embodiment]

[1453] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1454] 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.

[1455] 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).

[1456] 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.

[1457] 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.

[1458] 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).

[1459] 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.

[1460] 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.

[1461] 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.

[1462] 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.

[1463] 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.

[1464] 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."

[1465] This invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence within a messenger application. The system of the present invention operates as follows.

[1466] Schedule adjustment

[1467] Receiving a rescheduling request

[1468] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[1469] The terminal sends this request to the server.

[1470] Calendar integration

[1471] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[1472] The server analyzes the acquired calendar information and identifies commonly available time slots.

[1473] Proposal of dates

[1474] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[1475] A notification is sent to the device and the user can confirm the proposed dates via chat.

[1476] Confirmation of schedule

[1477] The user confirms and accepts the proposed dates and replies "OK" via chat.

[1478] The terminal transmits the user's consent to the server.

[1479] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[1480] reservation

[1481] Receiving a booking request

[1482] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[1483] The terminal sends this request to the server.

[1484] Search for reservation candidates

[1485] The server uses generative artificial intelligence to access the API of the restaurant reservation site and obtain restaurant information that meets the criteria.

[1486] The server lists the restaurant candidates and presents them to the chat group.

[1487] Confirmation of reservation

[1488] The user selects one restaurant from the presented options and replies via chat.

[1489] The terminal transmits the selection result to the server.

[1490] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[1491] The server notifies everyone of the confirmed reservation information.

[1492] Split payment

[1493] Receiving a split bill request

[1494] After a meal, a user chats and asks to split the bill.

[1495] The terminal sends this request to the server.

[1496] Collecting payment information

[1497] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[1498] The user enters the payment amount in the chat.

[1499] The terminal transmits the payment information entered by the user to the server.

[1500] Calculating the split amount

[1501] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[1502] Payment Processing

[1503] The server notifies each user of the total amount of payment and instructs them to make payment.

[1504] Users follow the instructions and make payments using the app's payment function.

[1505] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[1506] Specific Examples

[1507] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[1508] Schedule adjustment

[1509] 1. User A proposes a date for a meal via chat and sends a request.

[1510] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[1511] 3. The server presents the proposed dates in the group chat and gets everyone's approval.

[1512] reservation

[1513] 1. User B requests a reservation at a specific restaurant based on confirmed dates.

[1514] 2. The server presents reservation options and automatically makes a reservation at the restaurant selected by the user.

[1515] 3. The server notifies everyone of the confirmed reservation information.

[1516] Split payment

[1517] 1. User C requests splitting the bill and submits a request.

[1518] 2. The server collects the payment amount from each user and calculates and notifies the split amount.

[1519] 3. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[1520] This method allows all operations to be completed within the messenger application, resulting in a significant improvement in user convenience.

[1521] The processing flow will be explained below.

[1522] Schedule adjustment

[1523] Step 1:

[1524] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[1525] The terminal sends this request to the server.

[1526] Step 2:

[1527] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[1528] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[1529] The server analyzes the acquired calendar information and identifies commonly available time slots.

[1530] Step 3:

[1531] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[1532] A notification is sent to the device and the user can confirm the proposed dates via chat.

[1533] Step 4:

[1534] The user confirms and accepts the proposed dates and replies "OK" via chat.

[1535] The terminal transmits the user's consent to the server.

[1536] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[1537] reservation

[1538] Step 1:

[1539] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[1540] The terminal sends this request to the server.

[1541] Step 2:

[1542] The server uses generative artificial intelligence to access the API of the restaurant reservation site and obtain restaurant information that meets the criteria.

[1543] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[1544] The server lists the restaurant candidates and presents them to the chat group.

[1545] Step 3:

[1546] The user selects one restaurant from the presented options and replies via chat.

[1547] The terminal transmits the selection result to the server.

[1548] Step 4:

[1549] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[1550] The server notifies everyone of the confirmed reservation information.

[1551] Split payment

[1552] Step 1:

[1553] After a meal, a user chats and asks to split the bill.

[1554] The terminal sends this request to the server.

[1555] Step 2:

[1556] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[1557] The user enters the payment amount in the chat.

[1558] The terminal transmits the payment information entered by the user to the server.

[1559] Step 3:

[1560] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[1561] Step 4:

[1562] The server notifies each user of the total amount of payment and instructs them to make payment.

[1563] Users follow the instructions and make payments using the app's payment function.

[1564] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[1565] Example 1

[1566] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1567] Traditional messenger applications lacked the ability to centralize complex tasks such as scheduling, booking, and splitting bills. As a result, users had to perform these tasks individually in separate applications or manually, which required a great deal of time and effort. Furthermore, there was a high likelihood of mismatched or missing information between tasks, hindering smooth communication and efficient progress. This resulted in reduced user convenience and a poor quality experience.

[1568] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1569] In this invention, the server includes a communication application that accepts requests from users, a generative artificial intelligence means that acquires each user's schedule and selects the best candidate date, a device that acquires reservation information, presents it to the user, and confirms the reservation, a device that collects payment information, calculates the split amount, and processes payments between users, and a means for completing these operations within the messenger application. This allows users to efficiently and easily process schedule adjustments, reservations, and split payment settlements within a single messenger application.

[1570] A "communications application" is software that enables text messaging, voice, and video calls between users over the Internet.

[1571] "Generative AI" is an AI technology that learns from large amounts of data to perform prediction and generation tasks, rather than using traditional rule-based systems.

[1572] "Device" refers to hardware or software designed to perform a specific task, which in this invention includes obtaining, submitting, and confirming reservation information, collecting payment information, calculating split amounts, and processing payments.

[1573] "Means" refer to the methods, processes, or technical techniques required to achieve a particular function.

[1574] A "user" is a person or group of people who make requests such as scheduling, booking, splitting bills, etc. through a communication application.

[1575] "Candidate dates" refer to common available dates that are proposed taking into consideration the schedules of all users.

[1576] "Reservation information" refers to data necessary to guarantee the use of a specific service or place, and in the present invention, particularly refers to reservation data for restaurants and the like.

[1577] "Payment Information" means data related to a particular transaction, such as the amount and payment method.

[1578] "Split amount" refers to an amount calculated to divide multiple payments equally or in specific proportions.

[1579] "Complete within the messenger application" means that the user does not need to switch to an external application to complete a specific task, and all operations are completed within one application.

[1580] The present invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence within a messenger application. The system includes the following major hardware and software components:

[1581] Hardware and Software Components

[1582] 1. Server

[1583] Generative artificial intelligence: Using OpenAI's GPT-4 as an example.

[1584] API: Google Calendar API, restaurant reservation sites (e.g. Gurunavi API, Tabelog API)

[1585] Communication module: Data communication using HTTP / HTTPS protocol

[1586] 2. Terminal

[1587] Messenger applications: General communication applications (e.g., LINE, WhatsApp)

[1588] Data transmission / reception module: HTTP request sending and response receiving functions

[1589] 3. Users

[1590] Input devices: smartphones, tablets, PCs, etc.

[1591] Scheduling details

[1592] A user types "Let's all get together for dinner next Friday" in a chat group within a messenger application. The device sends this request to the server as an HTTP request. The server uses the received request as a trigger to launch a generative artificial intelligence (AI) and obtain schedule information from each user's Google Calendar API. The server analyzes this information, identifies common free time slots, and selects the most suitable candidate date. The selected candidate date (e.g., "Next Friday at 7pm") is notified within the chat group via the device. When the user accepts the candidate date, the final date is confirmed and everyone is notified.

[1593] Booking details

[1594] The user types "Make a reservation at a Japanese restaurant in Shinjuku" in a messenger application. The device sends this request to the server. The server uses generative artificial intelligence to access the APIs of multiple restaurant reservation sites and retrieve restaurant information that meets the criteria. The retrieved restaurant candidates are notified to the user via the device. When the user selects one restaurant from the candidates and replies, the server automatically makes a reservation at the selected restaurant and retrieves the reservation confirmation information. The server then notifies the chat group of the reservation confirmation information, and the device displays it to the user.

[1595] Split payment details

[1596] After the meal, a user requests in chat to "split the bill." The device sends this request to the server. The server then collects payment information by sending a message to each user asking them to enter their expected payment amount. Each user enters their payment amount in chat and sends that information to the server via their device. The server uses generative artificial intelligence to tally the entered payment amounts and calculates each user's share of the bill. Finally, the server notifies each user of the total share of the bill and instructs them to pay. Users follow the instructions and make the payment using the payment function within the app (e.g., PayPay, LINE Pay). The server confirms that each user has completed payment and sends a notification of settlement completion to everyone.

[1597] Examples and prompts

[1598] For example, if a user is planning a meal at a restaurant with a group of friends, they can enter the prompt text as follows:

[1599] "Let's all get together for dinner next Friday," I typed into the chat.

[1600] "Make a reservation at a Japanese restaurant in Shinjuku," he requested.

[1601] He asked to settle the bill, saying, "Let's split it."

[1602] This allows users to complete all operations within a single messenger application, enabling them to efficiently arrange schedules, make reservations, and split the bill.

[1603] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1604] Schedule adjustment

[1605] Step 1:

[1606] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[1607] Input: User's text message

[1608] Output: HTTP request from the terminal to the server

[1609] Step 2:

[1610] The terminal sends the received message to the server as an HTTP request.

[1611] Input: User's message

[1612] Output: The request data sent to the server

[1613] Step 3:

[1614] The server receives the request and launches a generative AI, which prepares access to the Google Calendar API for each user based on the model.

[1615] Input: HTTP request

[1616] Output: Prepare to access the calendar API

[1617] Step 4:

[1618] The server calls the Google Calendar API to obtain each user's calendar information.

[1619] Input: Calendar API request

[1620] Output: Calendar information for each user

[1621] Step 5:

[1622] The server analyzes the acquired calendar information and identifies commonly available time slots.

[1623] Input: Calendar information

[1624] Output: Candidate dates where everyone's schedules match

[1625] Step 6:

[1626] The server generates the best candidate date (e.g., "next Friday at 7pm") and notifies the chat group in the messenger application of this information.

[1627] Input: Data on the best candidate date

[1628] Output: Present candidate dates to the user

[1629] Step 7:

[1630] The terminal receives the candidate date notification from the server and displays it to the user.

[1631] Input: Candidate date notification

[1632] Output: Candidate dates displayed on the chat screen

[1633] Step 8:

[1634] The user checks the proposed dates and replies "OK" via chat.

[1635] Input: User consent message

[1636] Output: Acceptance request from device to server

[1637] Step 9:

[1638] The terminal sends the user's reply message to the server.

[1639] Input: Acceptance message

[1640] Output: Acceptance data sent to the server

[1641] Step 10:

[1642] The server waits until everyone agrees, and after confirming everyone's consent, it notifies the chat group of the confirmed date.

[1643] Input: consent data for all

[1644] Output: Notification of confirmed schedule

[1645] reservation

[1646] Step 1:

[1647] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[1648] Input: User request message

[1649] Output: Request from terminal to server

[1650] Step 2:

[1651] The terminal sends this request to the server.

[1652] Input: Request message

[1653] Output: The request sent to the server

[1654] Step 3:

[1655] The server receives the request and uses generative artificial intelligence to access the APIs of multiple restaurant reservation sites.

[1656] Input: Request data

[1657] Output: API request to the booking site

[1658] Step 4:

[1659] The server retrieves restaurant information that meets the criteria and lists it.

[1660] Input: API response

[1661] Output: Restaurant candidate list

[1662] Step 5:

[1663] The server sends the generated restaurant candidates to a chat group in a messenger application.

[1664] Input: Restaurant candidate list

[1665] Output: Information presented to the user

[1666] Step 6:

[1667] The terminal receives the list of restaurant candidates from the server and displays it to the user.

[1668] Input: Restaurant candidate list

[1669] Output: Candidate list displayed on the chat screen

[1670] Step 7:

[1671] The user selects one restaurant from the presented options and replies via chat.

[1672] Input: User's selected message

[1673] Output: Selected data from the terminal to the server

[1674] Step 8:

[1675] The terminal transmits the selection result to the server.

[1676] Input:Selection data

[1677] Output: Notify the server of the selection results

[1678] Step 9:

[1679] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[1680] Input: Selected restaurant information

[1681] Output: Confirmed reservation information

[1682] Step 10:

[1683] The server notifies the chat group of the reservation confirmation information, and the terminal displays it to the user.

[1684] Input: Confirmed reservation information

[1685] Output: User notification

[1686] Split payment

[1687] Step 1:

[1688] After a meal, a user chats and asks to split the bill.

[1689] Input: User request message

[1690] Output: Request from terminal to server

[1691] Step 2:

[1692] The terminal sends this request to the server.

[1693] Input: Request message

[1694] Output: The request sent to the server

[1695] Step 3:

[1696] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[1697] Input: Request data

[1698] Output: Message requesting expected payment amount

[1699] Step 4:

[1700] The user enters the payment amount in the chat.

[1701] Input: Payment amount Message

[1702] Output: Input data from the terminal to the server

[1703] Step 5:

[1704] The terminal transmits the payment information entered by the user to the server.

[1705] Input: Payment amount data

[1706] Output: Payment information to the server

[1707] Step 6:

[1708] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[1709] Input: Payment amount data

[1710] Output: Split amount data

[1711] Step 7:

[1712] The server notifies each user of the total split amount and instructs them to pay.

[1713] Input: Split amount data

[1714] Output: Payment instruction message

[1715] Step 8:

[1716] Users follow the instructions and make payments using the app's payment function.

[1717] Input: Payment Instruction Message

[1718] Output: Payment completion information

[1719] Step 9:

[1720] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[1721] Input: Payment completion information

[1722] Output: Payment completion notification

[1723] (Application example 1)

[1724] 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."

[1725] With traditional messaging applications, users often had to spend a lot of time coordinating schedules, making restaurant reservations, and splitting bills. These processes were also performed separately, resulting in poor overall convenience. Furthermore, insufficient information sharing and collaboration between different applications led to inconsistent user experiences.

[1726] 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.

[1727] In this invention, the server includes a message transfer application means for accepting requests from users, a generative model means for acquiring each user's schedule and selecting the optimal candidate date, a means for acquiring information from a reservation information site, presenting it to the user, and finalizing the reservation, a means for collecting payment information, calculating the split amount, and processing the payment between users, a calendar linking means for acquiring user schedule information, an information search means for searching for reservation candidates, and an electronic payment means for executing the payment process. This enables consistent operation within the messaging application, and allows each process of scheduling, making reservations, and splitting the bill to be carried out smoothly.

[1728] A "message transfer application that accepts requests from users" is an application that allows users to transmit various requests to the system by sending messages.

[1729] A "generative model" is an algorithm that uses artificial intelligence to analyze a user's schedule information and generate optimal candidate dates.

[1730] "Means for obtaining information from a reservation information site, presenting it to the user, and confirming the reservation" refers to a system for obtaining the necessary reservation information from an online reservation information service, presenting it to the user for selection, and confirming the reservation.

[1731] "Means for collecting payment information, calculating split amounts, and processing payments between users" refers to a system that collects payment amount information for each user, calculates split amounts based on that information, and ensures that appropriate payments are made between users.

[1732] The "calendar linking means for acquiring the user's schedule information" is a technology for linking with a calendar service used by the user and acquiring the schedule information.

[1733] The "information search means for searching for reservation candidates" is a technology for searching for suitable candidates from reservation information sites in response to a user request.

[1734] The "electronic payment means for executing payment processing" is a system for electronically settling payments between users based on the collected split amounts.

[1735] The present invention is a system that allows users to easily schedule, book, and split bill payments within a messaging application. The system includes the following components:

[1736] System Configuration

[1737] 1. A message transfer application that accepts requests from users

[1738] The server receives the dates and reservation requests that users propose in the chat, and these requests are sent to the server in an appropriate format.

[1739] 2. A generative model that obtains each user's schedule and selects the best candidate date

[1740] The server uses a generative AI model to retrieve and analyze each user's calendar information. For example, it uses the Google Calendar API to retrieve the user's schedule and select the best possible dates. This information is then analyzed based on prompts.

[1741] 3. A means of obtaining information from the reservation information site, presenting it to the user, and finalizing the reservation

[1742] The server searches for restaurant options from reservation information sites (e.g., OpenTable API) based on the specified date, time, and location, and presents them to the user in the chat. The server then automatically confirms the reservation based on the user's selection.

[1743] 4. A means of collecting payment information, dividing the bill, and processing payments between users.

[1744] The server collects payment information from the user, calculates the split amount using a generative AI model, notifies the user of the calculation result, and makes the payment using an electronic payment method (e.g., Stripe).

[1745] Hardware and software used

[1746] Hardware: Smartphones, smart glasses

[1747] Software: Python, Flask, Google Calendar API, OpenTable API, Stripe API

[1748] Overview of the process

[1749] 1. Scheduling:

[1750] If a user types into the chat, "Let's all get together for dinner next Friday," the server retrieves everyone's calendar information and presents the most suitable candidate dates.

[1751] 2. Reservations:

[1752] If a user types "Make a reservation at a Japanese restaurant in Shinjuku," the server will call the OpenTable API, retrieve and present restaurant information that matches the criteria, and confirm the reservation at the selected restaurant.

[1753] 3. Split the bill:

[1754] After the meal, if the user inputs "Let's split the bill," the server collects payment information, calculates the split amount using a generative AI model, and completes the payment using an electronic payment method.

[1755] Examples and prompts

[1756] For example, if a group of friends suggests in a chat, "Let's have a Japanese dinner in Shibuya next Friday," the server will check everyone's calendars and suggest "Friday at 7 PM." If a user then requests, "Make a reservation at a Japanese restaurant in Shinjuku," the server will use the OpenTable API to search for restaurants that meet the criteria and make a reservation at the recommended restaurant. After the meal, if the user requests, "Let's split the bill," the server will tally up the amounts paid by each user, calculate the split amount, and notify them.

[1757] Example prompt sentence:

[1758] I've suggested a Japanese dinner in Shibuya next Friday at 7pm. I've checked everyone's calendars and this date and time is most suitable. Please confirm and accept.

[1759] The restaurant search results are: 1. Shibuya Washokutei, 2. Ginza Washoku Teishoku, 3. Fine Japanese Restaurant. Please select the restaurant you want.

[1760] Your meal is complete. The total is 20,000 yen. We split the bill at 5,000 yen per person. Please complete the payment using the link below.

[1761] By using this system, all operations can be completed within the message forwarding app, greatly improving user convenience.

[1762] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1763] Step 1:

[1764] Input: A user inputs a scheduling request within a message forwarding application.

[1765] What happens: A user types in a chat group, "Let's all get together for dinner next Friday."

[1766] Server processing: The terminal receives this request and sends it to the server.

[1767] Output: The server receives the request and proceeds.

[1768] Step 2:

[1769] Input: The server retrieves all users' calendar information.

[1770] Specific operation: The server uses the Google Calendar API to obtain the schedule information of all participants.

[1771] Data processing: Analyze the acquired calendar information.

[1772] Server processing: Using a generative AI model, analyze each user's schedule and identify common free time slots.

[1773] Output: A list of optimal candidate dates is generated, ready to be presented to the user.

[1774] Step 3:

[1775] Input: The retrieved calendar information and a list of common free time slots.

[1776] Specific operation: The servers select "next Friday at 7pm" as a commonly available time slot.

[1777] Server processing: Format the selected candidate dates for presentation in the group chat.

[1778] Output: The server sends a notification to the device, allowing the user to check the proposed dates.

[1779] Step 4:

[1780] Input: Candidate dates provided by the server.

[1781] Specific behavior: The user confirms the proposed date in chat and replies "OK."

[1782] Terminal processing: The terminal sends the user's consent to the server.

[1783] Output: The server confirms everyone's acceptance and notifies everyone of the confirmed date.

[1784] Step 5:

[1785] Input: The user types a reservation request in the message.

[1786] Specific action: The user types, "Make a reservation at a Japanese restaurant in Shinjuku."

[1787] Terminal processing: The terminal sends this request to the server.

[1788] Output: The server receives the request and prepares to proceed.

[1789] Step 6:

[1790] Input: The server receives the reservation conditions (location, genre).

[1791] Specific operation: The server calls the OpenTable API and retrieves restaurant information using the conditions "Shinjuku" and "Japanese cuisine."

[1792] Data processing: Analyze and organize the list of restaurant candidates obtained.

[1793] Server processing: Generates a candidate list that can be presented to the user.

[1794] Output: Format the list of restaurant suggestions to present in the chat.

[1795] Step 7:

[1796] Input: A list of restaurant candidates.

[1797] Specific operation: The user selects one restaurant from the presented options and replies via chat.

[1798] Terminal processing: The terminal sends the selection results to the server.

[1799] Output: The server prepares to automatically make a reservation at the selected restaurant.

[1800] Step 8:

[1801] Input: User selection results, reservation candidate list.

[1802] Specific behavior: The server uses the OpenTable API to make a reservation at the selected restaurant.

[1803] Data processing: Obtain and format confirmed reservation information.

[1804] Server processing: Notify everyone of the confirmed reservation information.

[1805] Output: Send a notification to the device with the confirmed reservation information.

[1806] Step 9:

[1807] Input: The user enters a request for split payment in the message.

[1808] Specific action: The user types "Let's split the bill" in the chat.

[1809] Terminal processing: The terminal sends this request to the server.

[1810] Output: The server receives the request and prepares to proceed.

[1811] Step 10:

[1812] Input: Request to split the bill.

[1813] Specific operation: To collect payment information, the server sends a message to each user requesting them to enter the expected payment amount.

[1814] Data processing: Aggregate payment amounts from users.

[1815] Server processing: Using the generative AI model, the entered payment amounts are aggregated and the amount each user is responsible for is calculated.

[1816] Output: Notify each user of the split amount.

[1817] Step 11:

[1818] Input: Notification of split amount.

[1819] Specific behavior: The user makes a payment using the app's electronic payment function.

[1820] Data Processing: We process each user's payment using an electronic payment system (e.g., Stripe API).

[1821] Server processing: Confirm that each user has completed payment.

[1822] Output: Send a notification to everyone that payment is complete.

[1823] 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.

[1824] This invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence and an emotion engine within a messenger application. The system of the present invention operates as follows.

[1825] Schedule adjustment

[1826] Receiving a rescheduling request

[1827] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[1828] The terminal sends this request to the server.

[1829] Calendar integration

[1830] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[1831] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[1832] The server analyzes the acquired calendar information and identifies commonly available time slots.

[1833] Emotion recognition with emotion engine

[1834] The server activates an emotion engine to recognize each user's emotion before making scheduling suggestions.

[1835] The server analyzes the user's chat content and past responses to obtain emotional data.

[1836] The server then suggests the best possible date based on the recognized emotion data.

[1837] Proposal of dates

[1838] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[1839] A notification is sent to the device and the user can confirm the proposed dates via chat.

[1840] Confirmation of schedule

[1841] The user confirms and accepts the proposed dates and replies "OK" via chat.

[1842] The terminal transmits the user's consent to the server.

[1843] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[1844] reservation

[1845] Receiving a booking request

[1846] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[1847] The terminal sends this request to the server.

[1848] Search for reservation candidates

[1849] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant reservation site and obtain restaurant information that meets the criteria.

[1850] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[1851] The emotion engine considers the user's emotional state and prioritizes appropriate restaurants to provide a better user experience.

[1852] The server lists the restaurant candidates and presents them to the chat group.

[1853] Confirmation of reservation

[1854] The user selects one restaurant from the presented options and replies via chat.

[1855] The terminal transmits the selection result to the server.

[1856] Notification of final information

[1857] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[1858] The server notifies everyone of the confirmed reservation information.

[1859] Split payment

[1860] Receiving a split bill request

[1861] After a meal, a user chats and asks to split the bill.

[1862] The terminal sends this request to the server.

[1863] Collecting payment information

[1864] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[1865] The user enters the payment amount in the chat.

[1866] The terminal transmits the payment information entered by the user to the server.

[1867] Emotion recognition with emotion engine

[1868] The server activates an emotion engine to recognize the emotion of each user during payment information collection and bill splitting calculation.

[1869] The server analyzes the user's chat content and reactions to obtain emotional data.

[1870] The server provides appropriate communication methods and feedback based on the recognized emotion data.

[1871] Calculating the split amount

[1872] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[1873] Payment Processing

[1874] The server notifies each user of the total amount of payment and instructs them to make payment.

[1875] Users follow the instructions and make payments using the app's payment function.

[1876] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[1877] Specific Examples

[1878] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[1879] Schedule adjustment

[1880] 1. User A proposes a date for a meal in chat, types "next Friday," and sends the request.

[1881] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[1882] 3. The server uses the emotion engine to recognize each user's emotion data and check whether the candidate date matches the user's emotion.

[1883] 4. The server presents the proposed dates in the group chat and gets everyone's approval.

[1884] reservation

[1885] 1. User B requests a reservation at a specific restaurant based on confirmed dates.

[1886] 2. The server uses generative artificial intelligence and an emotion engine to present reservation options that meet the criteria, and the user can select one.

[1887] 3. The server will automatically make a reservation at the selected restaurant and notify everyone of the reservation confirmation.

[1888] Split payment

[1889] 1. User C requests splitting the bill and submits a request.

[1890] 2. The server collects the payment amount of each user and monitors the emotions of each user using an emotion engine.

[1891] 3. The server uses generative artificial intelligence to calculate the split amount and instructs payment.

[1892] 4. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[1893] This method not only allows all operations to be completed within the messenger application, greatly improving user convenience, but also further improves the user experience through processes that utilize the emotion engine.

[1894] The processing flow will be explained below.

[1895] Schedule adjustment

[1896] Step 1:

[1897] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[1898] The terminal sends this request to the server.

[1899] Step 2:

[1900] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[1901] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[1902] Step 3:

[1903] The server analyzes the acquired calendar information and identifies commonly available time slots.

[1904] Step 4:

[1905] The server activates an emotion engine to recognize each user's emotion before making suggestions.

[1906] The server analyzes the user's chat content and past responses to obtain emotional data.

[1907] Step 5:

[1908] The server selects the most suitable candidate date based on the recognized emotion data.

[1909] Step 6:

[1910] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[1911] A notification is sent to the device and the user can confirm the proposed dates via chat.

[1912] Step 7:

[1913] The user confirms and accepts the proposed dates and replies "OK" via chat.

[1914] The terminal transmits the user's consent to the server.

[1915] Step 8:

[1916] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[1917] reservation

[1918] Step 1:

[1919] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[1920] The terminal sends this request to the server.

[1921] Step 2:

[1922] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant reservation site and obtain restaurant information that meets the criteria.

[1923] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[1924] Step 3:

[1925] The emotion engine considers the user's emotional state and prioritizes appropriate restaurants to provide a better user experience.

[1926] Step 4:

[1927] The server lists the restaurant candidates and presents them to the chat group.

[1928] Step 5:

[1929] The user selects one restaurant from the presented options and replies via chat.

[1930] The terminal transmits the selection result to the server.

[1931] Step 6:

[1932] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[1933] Step 7:

[1934] The server notifies everyone of the confirmed reservation information.

[1935] Split payment

[1936] Step 1:

[1937] After a meal, a user chats and asks to split the bill.

[1938] The terminal sends this request to the server.

[1939] Step 2:

[1940] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[1941] The user enters the payment amount in the chat.

[1942] The terminal transmits the payment information entered by the user to the server.

[1943] Step 3:

[1944] The server activates an emotion engine to recognize the emotion of each user during payment information collection and bill splitting calculation.

[1945] The server analyzes the user's chat content and reactions to obtain emotional data.

[1946] Step 4:

[1947] The server provides appropriate communication methods and feedback based on the recognized emotion data.

[1948] Step 5:

[1949] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[1950] Step 6:

[1951] The server notifies each user of the total amount of payment and instructs them to make payment.

[1952] Step 7:

[1953] Users follow the instructions and make payments using the app's payment function.

[1954] Step 8:

[1955] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[1956] Specific Examples

[1957] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[1958] 1. User A proposes a date for a meal in chat, types "next Friday," and sends the request.

[1959] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[1960] 3. The server uses the emotion engine to recognize each user's emotion data and check whether the candidate date matches the user's emotion.

[1961] 4. The server presents the proposed dates in the group chat and gets everyone's approval.

[1962] 5. User B requests a reservation at a specific restaurant based on confirmed dates.

[1963] 6. The server uses generative artificial intelligence and an emotion engine to present reservation options that meet the criteria, and the user can select one.

[1964] 7. The server will automatically make a reservation at the selected restaurant and notify everyone of the reservation confirmation.

[1965] 8. User C requests splitting the bill and submits a request.

[1966] 9. The server collects the payment amount of each user and monitors the emotions of each user using the emotion engine.

[1967] 10. The server uses generative artificial intelligence to calculate the split amount and instructs payment.

[1968] 11. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[1969] This method not only allows all operations to be completed within the messenger application, greatly improving user convenience, but also further improves the user experience through processes that utilize the emotion engine.

[1970] Example 2

[1971] 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."

[1972] With conventional messenger applications, it was difficult to coordinate schedules, make reservations, and split payments all in one place, requiring users to use each application and service individually. Furthermore, due to a lack of smooth communication and understanding of emotions between users, it was difficult to select appropriate dates, make reservations, and process payments. This resulted in a poor user experience and required a lot of effort.

[1973] 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 a messenger application that accepts requests from users, a generative artificial intelligence means that acquires each user's schedule and selects the optimal candidate date, a means that recognizes user emotions using an emotion engine and optimizes schedule adjustment and reservation suggestions, a means that searches for reservation information from a reservation site and presents it to the user to confirm the reservation, a means that collects payment information and calculates the split amount and processes payments between users, a means that notifies all users of the approved schedule, and a means that notifies users of the confirmed reservation information after the reservation is confirmed. This allows users to centrally adjust schedules, make reservations, and split the bill within the messenger application, significantly improving user convenience and experience.

[1974] A "messenger application that accepts requests from users" is software that allows users to request operations and communicate through messages, and provides various services in cooperation with a server.

[1975] "Generative AI that obtains each user's schedule and selects the optimal candidate date" is an AI technology that analyzes the user's calendar data and suggests the optimal date and time taking into account the user's overall schedule.

[1976] "Means for searching reservation information from reservation sites, presenting it to the user, and finalizing the reservation" refers to a technology that accesses multiple reservation information providing sites to collect reservation information that meets the conditions, presents the candidates to the user, and executes the reservation based on the user's selection.

[1977] "Means for collecting payment information, calculating split amounts, and processing payments between users" refers to technology for collecting payment amount information from users, calculating fair split amounts, and smoothly processing payments.

[1978] "Means of using an emotion engine to recognize user emotions and optimize schedule adjustment and reservation suggestions" is a technology that analyzes a user's messages and past data to recognize their emotional state and suggests optimal dates and reservation details based on those emotions.

[1979] The "means for presenting candidate dates and receiving user's consent" is a technique for presenting optimal candidate dates to the user and receiving a response of approval or rejection from the user.

[1980] The "means for notifying all users of the approved schedule" is a technique for simultaneously notifying all users of the approved schedule.

[1981] "Means for notifying users of confirmed reservation information after a reservation is confirmed" refers to a technique for notifying all users of confirmed reservation information after the reservation procedure is completed.

[1982] This invention is a system that uses a messenger application to efficiently arrange schedules, make reservations, and split the bill. The devices used are the user's terminal (such as a smartphone or PC) and a server, which are linked via a communication network.

[1983] Overall structure

[1984] The system works by linking a messenger application, generative artificial intelligence, an emotion engine, and various APIs.

[1985] 1. Messenger Applications

[1986] Users request scheduling, reservations, and bill splits through a messenger application, which sends the requests to the server and receives responses from the server.

[1987] 2. Generative Artificial Intelligence

[1988] The server uses generative artificial intelligence to analyze each user's calendar information and propose optimal schedule adjustments. Calendar information is obtained through the APIs of Google Calendar and Outlook Calendar.

[1989] 3. Emotion Engine

[1990] The server uses an emotion engine to analyze the user's emotions. Based on the analysis results, it proposes optimal dates and reservations that match the user's emotions. Emotion data is obtained from the user's past message history and real-time reactions.

[1991] 4. Booking API

[1992] The server searches for reservation candidates that match the conditions via the API of various reservation sites, presents the acquired reservation information to the user, and confirms the reservation based on the user's selection.

[1993] 5. Payment Processing Functions

[1994] The server collects payment information from users, calculates split amounts using generative artificial intelligence, and processes payment instructions and payment confirmations.

[1995] Specific examples

[1996] Specific examples of schedule adjustments

[1997] User A sends a request to a chat group saying, "Let's all get together for dinner next Friday." The server uses the Google Calendar or Outlook Calendar API to obtain each user's calendar information and identify commonly available time slots. It then activates an emotion engine to analyze the user's emotional state. It then suggests the most suitable candidate date, for example, "next Friday at 7 p.m." The user replies "OK," and the server confirms everyone's acceptance before notifying them of the confirmed date.

[1998] Specific reservation examples

[1999] User B makes a request via a messenger application, saying, "Make a reservation at a Japanese restaurant in Shinjuku." The server searches for the criteria "Shinjuku," "Japanese food," and "next Friday night at 7pm" via the restaurant reservation site's API. Using an emotion engine, it prioritizes and selects the most suitable restaurant, taking into account the user's emotional state. The obtained restaurant candidates are then listed and presented to the chat group. The server then automatically makes a reservation at the restaurant selected by the user and notifies everyone of the confirmed reservation.

[2000] Specific examples of split payment

[2001] After the meal, User C sends a request via chat to "split the bill." The server sends each user a message prompting them to enter their expected payment amount. The user enters the payment amount via chat and sends it to the server. The emotion engine is activated to monitor the user's emotional state. Generative artificial intelligence is used to calculate the split amount based on the entered payment amount. The server notifies each user of the calculation result and instructs them to pay. The user pays using the payment function within the app, and after the server confirms that payment has been completed, it sends a notification to everyone that the settlement has been completed.

[2002] Example prompts

[2003] "Please arrange a date for us to all have dinner together next Friday at 7pm."

[2004] "Make a reservation at a Japanese restaurant in Shinjuku."

[2005] "Please split the bill."

[2006] Through this specific system configuration and operation procedure, the present invention can provide users with efficient and smooth schedule adjustment, reservation, and split payment functions.

[2007] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2008] Schedule adjustment

[2009] Step 1: Receiving a scheduling request

[2010] A user types, "Let's all get together for dinner next Friday" into a chat group on a messenger application.

[2011] The device sends this request to the server.

[2012] Input: User request message

[2013] Output: Request data to the server

[2014] Step 2: Calendar Integration

[2015] The server runs a generative artificial intelligence and calls the Google Calendar or Outlook Calendar API to retrieve each user's calendar information.

[2016] The server collects calendar information through an API with each user's permission.

[2017] Input: A request to get the user's calendar information

[2018] Data processing: Obtain calendar information through API and analyze it

[2019] Output: Parsed calendar information

[2020] Step 3: Emotion recognition by the emotion engine

[2021] The server launches an emotion engine and analyzes the user's chat content and past responses to obtain emotional data.

[2022] Input: User chat content, past reaction data

[2023] Data calculation: Recognize and acquire emotional data using the emotion engine

[2024] Output: User emotion data

[2025] Step 4: Present possible dates

[2026] The server will suggest the best possible dates based on the analyzed calendar information and emotional data.

[2027] For example, you could suggest "next Friday night at 7pm" in a group chat.

[2028] A notification will be sent to the device and the user can confirm the suggested dates.

[2029] Input: Analyzed calendar information, emotion data

[2030] Data calculation: Identifying the best candidate date

[2031] Output: Best candidate date notification

[2032] Step 5: Confirm the date

[2033] The user checks the proposed dates and replies with an "OK" message via chat to indicate their acceptance.

[2034] The device sends the user's consent to the server.

[2035] After the server confirms everyone's consent, it will notify everyone of the confirmed date.

[2036] Input: User consent message

[2037] Data calculation: Confirmation of consent from all users

[2038] Output: Notification of confirmed schedule

[2039] reservation

[2040] Step 1: Receiving a booking request

[2041] The user simply types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[2042] The device sends this request to the server.

[2043] Input: User's reservation request message

[2044] Output: Reservation request data to the server

[2045] Step 2: Search for potential reservations

[2046] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant booking site.

[2047] The server retrieves restaurant information based on conditions such as "Shinjuku," "Japanese cuisine," and "next Friday night at 7 p.m."

[2048] Input: Reservation conditions (e.g., location, Shinjuku; genre, Japanese; time, next Friday at 7pm)

[2049] Data processing: Acquiring restaurant information through API

[2050] Output: A list of restaurant candidates obtained

[2051] Step 3: Optimizing with an Emotion Engine

[2052] The server uses an emotion engine to analyze the user's emotional state and prioritize appropriate restaurants.

[2053] Input: Obtained restaurant candidate list, user emotion data

[2054] Data calculations: Using sentiment engines to filter the best restaurants

[2055] Output: A list of the best restaurants

[2056] Step 4: Suggest candidates

[2057] The server will create a list of the best restaurant options and present them in the group chat.

[2058] The user selects one restaurant from the presented options and responds via chat.

[2059] The device sends the selection results to the server.

[2060] Input: Best Restaurant Shortlist

[2061] Output: Present candidate list to user, user selection message

[2062] Step 5: Confirm your booking

[2063] The server automatically makes a reservation at the selected restaurant and retrieves the reservation confirmation information.

[2064] The server will then notify everyone of the confirmed reservation information.

[2065] Input: User's selected message

[2066] Data calculation: Reservation processing through the booking site's API

[2067] Output: Notification of confirmed reservation information

[2068] Split payment

[2069] Step 1: Receiving a split request

[2070] After a meal, the user can chat and ask to split the bill.

[2071] The device sends this request to the server.

[2072] Input: User's bill split request message

[2073] Output: Split request data to the server

[2074] Step 2: Collect payment information

[2075] The server sends each user a message prompting them to enter their expected payment amount.

[2076] The user enters the payment amount in chat and sends it to the server.

[2077] Input: User payment amount input message

[2078] Output: Payment information from the user

[2079] Step 3: Emotion recognition by the emotion engine

[2080] The server runs an emotion engine to recognize each user's emotion during payment information collection and bill splitting.

[2081] Input: User's payment information, chat contents

[2082] Data calculation: Recognize and acquire emotional data using the emotion engine

[2083] Output: Emotion data

[2084] Step 4: Calculate the split amount

[2085] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[2086] Input: User's payment information

[2087] Data calculation: aggregation and charge calculation

[2088] Output: Split amount

[2089] Step 5: Payment Processing

[2090] The server notifies each user of the total amount due and instructs them to pay.

[2091] Users follow the instructions and make payments using the in-app payment function.

[2092] The server confirms that each user has completed payment and sends a notification to everyone that the payment has been completed.

[2093] Input: Split amount, user payment information

[2094] Data calculation: Confirmation of payment processing

[2095] Output: Payment completion notification

[2096] Through the above processing steps, the present system can greatly improve user convenience and further enrich the user experience.

[2097] (Application example 2)

[2098] 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."

[2099] Conventional messenger applications can accept user requests and adjust schedules and make reservations, but they do not support work coordination and cost sharing for industrial robots, making it difficult to efficiently manage work and costs within factories.In addition, the sharing of usage fees for shared equipment and facilities is unclear, so there is a need for optimal schedule adjustment and an improved user experience.

[2100] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2101] In this invention, the server includes a communication means for accepting requests from users, a generative artificial intelligence device for acquiring each user's schedule and selecting the optimal candidate date, a reservation means for searching reservation information from a reservation site, presenting it to the user, and finalizing the reservation, a payment means for collecting payment information, calculating the split amount, and processing payments between users, a work coordination means for adjusting the work schedule of industrial robots, and a cost sharing means for sharing the usage fees for shared equipment and facilities among the responsible departments. This enables efficient work coordination and transparent cost management within the factory.

[2102] "Communication means for accepting requests from users" refers to technology or devices for receiving requests or instructions from users via a communication network.

[2103] The "generative artificial intelligence device that acquires each user's schedule and selects the optimal candidate date" is an artificial intelligence system that collects users' schedule information and automatically selects the optimal date based on that data.

[2104] "Reservation means for searching reservation information from a reservation site, presenting it to the user, and confirming the reservation" refers to technology or devices that search for the necessary reservation information from an online reservation platform, provide it to the user, and confirm the reservation.

[2105] A "payment method that collects payment information, splits the bill, and processes payments between users" refers to technology or a device that collects payment information from each user, splits the amount equally, and executes the payment process.

[2106] "Work adjustment means for adjusting the work schedule of industrial robots" refers to technology and devices for adjusting the work schedule of robots in factories and operating them efficiently.

[2107] "Cost sharing means for allocating the usage fees for shared equipment and facilities to the departments that bear the costs" refers to technology or devices that fairly distribute the usage fees for equipment and facilities that are jointly used by multiple departments to each department.

[2108] The present invention is a system for improving the efficiency of work coordination and cost management within a factory, and is specifically implemented as follows.

[2109] System Configuration

[2110] This system includes a communication means for accepting requests from users, a generative artificial intelligence device that obtains each user's schedule and selects the most suitable candidate date, a reservation means that searches for reservation information from a reservation site and presents it to the user to confirm the reservation, a payment means that collects payment information, calculates the split amount, and processes payments between users, a work coordination means that adjusts the work schedule of industrial robots, and a cost sharing means that allocates the usage fees for shared equipment and facilities to the departments that bear the costs.

[2111] Program processing and usage technology

[2112] The system uses the following hardware and software:

[2113] Communication method: Internet-enabled device (PC, smartphone, etc.)

[2114] Generative AI device: AI model using Python or JavaScript (e.g., TensorFlow, PyTorch)

[2115] Reservation method: Google Calendar API, Microsoft Outlook Calendar API

[2116] Payment method: Smartphone payment application (e.g., PayPal, Stripe)

[2117] Work coordination method: Work management software (e.g., JIRA, Trello)

[2118] Cost sharing method: Shared expense management system or spreadsheet software (e.g., Google Sheets, Microsoft Excel)

[2119] Data processing and calculation

[2120] The server processes and calculates data using the following means.

[2121] 1. Communication: Receives requests from users (e.g., scheduling or reservation requests) and analyzes their content. This communication requires an internet connection and uses messenger applications such as Slack or Microsoft Teams.

[2122] 2. Generative AI: Collects each user's calendar information via API, analyzes the data, and selects the best candidate dates. During this process, an AI model is used to adjust the schedule to avoid conflicts.

[2123] 3. Reservation method: Based on the obtained candidate dates, search for suitable reservation information from a reservation site (e.g., a restaurant reservation site) and present it to the user. The reservation is confirmed based on the user's selection.

[2124] 4. Payment Method: Payment information is collected after meals or tasks are completed, and the split amount is calculated. The necessary payment process is notified to each user and carried out through a smartphone payment application.

[2125] 5. Work Coordination: The server coordinates the work schedules of the industrial robots and schedules them efficiently. In this process, work management software is used to set up the work plan and allocate the necessary resources.

[2126] 6. Cost sharing measures: Calculate the appropriate cost sharing for shared equipment and facilities among each department. This information is entered into a shared expense management system or spreadsheet software for transparent cost management.

[2127] Specific examples

[2128] As a concrete example, consider the case where a user performs the following process:

[2129] 1. Scheduling: The factory maintenance team leader requests on Slack, "I'd like to perform maintenance on Robot A next Monday." The server receives this request, collects the schedules of each maintenance team member via the Google Calendar API, and suggests the optimal time slot.

[2130] 2. Reservation: The maintenance team reserves the necessary equipment and tools based on a specific date. The reservation information is retrieved by the server, presented to the team, and confirmed.

[2131] 3. Cost sharing: After maintenance, in response to a request to "calculate the cost sharing," the server aggregates the time and resources used by each department and calculates a fair cost sharing. The amount of the burden is notified to each department and recorded in the shared expense management system.

[2132] Prompt Sentence Examples

[2133] "I would like you to perform maintenance on Robot A next Monday."

[2134] "Please calculate the cost sharing after the maintenance is completed."

[2135] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2136] Step 1:

[2137] As a maintenance team leader at a factory, the user types into a messenger application, "I would like to perform maintenance on Robot A next Monday." The server receives this message. The input data is the user's request, and the server proceeds to the next step based on this.

[2138] Step 2:

[2139] The server starts the generative artificial intelligence device and obtains the calendar information of each maintenance member using the Google Calendar API. The input data is the calendar information of each maintenance member, and this data is analyzed to identify common free time slots. The output data is the optimal candidate date and time slot.

[2140] Step 3:

[2141] The server uses an emotion engine to analyze members' reactions and emotions and propose optimal candidate dates. Input data is the user's chat content and past reactions, and based on this, emotion data is obtained to confirm whether the proposed date and time are appropriate. The output data is a candidate date adjusted based on the emotions.

[2142] Step 4:

[2143] The server presents the adjusted candidate date to the group chat of the messenger application. The input data is the optimal candidate date, and by presenting it to the user, the process of obtaining the user's consent begins. The output data is the user's consent or a request for revision.

[2144] Step 5:

[2145] The user checks the proposed dates and replies "OK." The device sends this acceptance message to the server. The input data is the user's reply message, which the server receives and confirms everyone's acceptance. The output data is the confirmed schedule information.

[2146] Step 6:

[2147] The server notifies all maintenance members of the confirmed schedule information. The input data is the confirmed schedule information, and the schedule is finalized when the server sends it to all members. The output data is a notification to all members.

[2148] Step 7:

[2149] The user requests a specific reservation (for example, reserving a specific industrial robot or tool for maintenance). The server receives this request. The input data is the user's reservation request, and based on this, the next step is taken.

[2150] Step 8:

[2151] The server uses the reservation site's API to search for the necessary reservation information and present candidates. The input data is the user's reservation conditions (date, time, location, facilities), and reservation candidates are obtained based on this. The output data is a list of reservation candidates.

[2152] Step 9:

[2153] The user selects one of the reservation options presented and sends a request. The terminal sends this selection information to the server. The input data is the user's selection information, which the server receives and confirms the reservation. The output data is the confirmed reservation information.

[2154] Step 10:

[2155] The server notifies all maintenance members of the confirmed reservation information. The input data is the confirmed reservation information, and the reservation is confirmed when the server sends it to all members. The output data is a notification to all members.

[2156] Step 11:

[2157] After the maintenance is completed, the user requests "Please calculate the cost share." The server receives this request. The input data is the user's request, and the server proceeds to the next step based on this.

[2158] Step 12:

[2159] The server obtains the information necessary to collect the usage time and resources of each department. The input data is the usage information reported by each department, and the cost sharing is calculated based on this. The output data is the amount borne by each department.

[2160] Step 13:

[2161] The server notifies each department of the total burden amount. The input data is the burden amount of each department, and the server sends it to all departments, making the cost sharing clear. The output data is a notification of the cost sharing.

[2162] 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.

[2163] 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.

[2164] 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.

[2165] [Fourth embodiment]

[2166] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2167] 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.

[2168] 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).

[2169] 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.

[2170] 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.

[2171] 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).

[2172] 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.

[2173] 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.

[2174] 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.

[2175] 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.

[2176] 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.

[2177] 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.

[2178] 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."

[2179] This invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence within a messenger application. The system of the present invention operates as follows.

[2180] Schedule adjustment

[2181] Receiving a rescheduling request

[2182] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[2183] The terminal sends this request to the server.

[2184] Calendar integration

[2185] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[2186] The server analyzes the acquired calendar information and identifies commonly available time slots.

[2187] Proposal of dates

[2188] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[2189] A notification is sent to the device and the user can confirm the proposed dates via chat.

[2190] Confirmation of schedule

[2191] The user confirms and accepts the proposed dates and replies "OK" via chat.

[2192] The terminal transmits the user's consent to the server.

[2193] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[2194] reservation

[2195] Receiving a booking request

[2196] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[2197] The terminal sends this request to the server.

[2198] Search for reservation candidates

[2199] The server uses generative artificial intelligence to access the API of the restaurant reservation site and obtain restaurant information that meets the criteria.

[2200] The server lists the restaurant candidates and presents them to the chat group.

[2201] Confirmation of reservation

[2202] The user selects one restaurant from the presented options and replies via chat.

[2203] The terminal transmits the selection result to the server.

[2204] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[2205] The server notifies everyone of the confirmed reservation information.

[2206] Split payment

[2207] Receiving a split bill request

[2208] After a meal, a user chats and asks to split the bill.

[2209] The terminal sends this request to the server.

[2210] Collecting payment information

[2211] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[2212] The user enters the payment amount in the chat.

[2213] The terminal transmits the payment information entered by the user to the server.

[2214] Calculating the split amount

[2215] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[2216] Payment Processing

[2217] The server notifies each user of the total amount of payment and instructs them to make payment.

[2218] Users follow the instructions and make payments using the app's payment function.

[2219] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[2220] Specific Examples

[2221] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[2222] Schedule adjustment

[2223] 1. User A proposes a date for a meal via chat and sends a request.

[2224] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[2225] 3. The server presents the proposed dates in the group chat and gets everyone's approval.

[2226] reservation

[2227] 1. User B requests a reservation at a specific restaurant based on confirmed dates.

[2228] 2. The server presents reservation options and automatically makes a reservation at the restaurant selected by the user.

[2229] 3. The server notifies everyone of the confirmed reservation information.

[2230] Split payment

[2231] 1. User C requests splitting the bill and submits a request.

[2232] 2. The server collects the payment amount from each user and calculates and notifies the split amount.

[2233] 3. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[2234] This method allows all operations to be completed within the messenger application, resulting in a significant improvement in user convenience.

[2235] The processing flow will be explained below.

[2236] Schedule adjustment

[2237] Step 1:

[2238] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[2239] The terminal sends this request to the server.

[2240] Step 2:

[2241] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[2242] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[2243] The server analyzes the acquired calendar information and identifies commonly available time slots.

[2244] Step 3:

[2245] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[2246] A notification is sent to the device and the user can confirm the proposed dates via chat.

[2247] Step 4:

[2248] The user confirms and accepts the proposed dates and replies "OK" via chat.

[2249] The terminal transmits the user's consent to the server.

[2250] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[2251] reservation

[2252] Step 1:

[2253] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[2254] The terminal sends this request to the server.

[2255] Step 2:

[2256] The server uses generative artificial intelligence to access the API of the restaurant reservation site and obtain restaurant information that meets the criteria.

[2257] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[2258] The server lists the restaurant candidates and presents them to the chat group.

[2259] Step 3:

[2260] The user selects one restaurant from the presented options and replies via chat.

[2261] The terminal transmits the selection result to the server.

[2262] Step 4:

[2263] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[2264] The server notifies everyone of the confirmed reservation information.

[2265] Split payment

[2266] Step 1:

[2267] After a meal, a user chats and asks to split the bill.

[2268] The terminal sends this request to the server.

[2269] Step 2:

[2270] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[2271] The user enters the payment amount in the chat.

[2272] The terminal transmits the payment information entered by the user to the server.

[2273] Step 3:

[2274] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[2275] Step 4:

[2276] The server notifies each user of the total amount of payment and instructs them to make payment.

[2277] Users follow the instructions and make payments using the app's payment function.

[2278] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[2279] Example 1

[2280] 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."

[2281] Traditional messenger applications lacked the ability to centralize complex tasks such as scheduling, booking, and splitting bills. As a result, users had to perform these tasks individually in separate applications or manually, which required a great deal of time and effort. Furthermore, there was a high likelihood of mismatched or missing information between tasks, hindering smooth communication and efficient progress. This resulted in reduced user convenience and a poor quality experience.

[2282] 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.

[2283] In this invention, the server includes a communication application that accepts requests from users, a generative artificial intelligence means that acquires each user's schedule and selects the best candidate date, a device that acquires reservation information, presents it to the user, and confirms the reservation, a device that collects payment information, calculates the split amount, and processes payments between users, and a means for completing these operations within the messenger application. This allows users to efficiently and easily process schedule adjustments, reservations, and split payment settlements within a single messenger application.

[2284] A "communications application" is software that enables text messaging, voice, and video calls between users over the Internet.

[2285] "Generative AI" is an AI technology that learns from large amounts of data to perform prediction and generation tasks, rather than using traditional rule-based systems.

[2286] "Device" refers to hardware or software designed to perform a specific task, which in this invention includes obtaining, submitting, and confirming reservation information, collecting payment information, calculating split amounts, and processing payments.

[2287] "Means" refer to the methods, processes, or technical techniques required to achieve a particular function.

[2288] A "user" is a person or group of people who make requests such as scheduling, booking, splitting bills, etc. through a communication application.

[2289] "Candidate dates" refer to common available dates that are proposed taking into consideration the schedules of all users.

[2290] "Reservation information" refers to data necessary to guarantee the use of a specific service or place, and in the present invention, particularly refers to reservation data for restaurants and the like.

[2291] "Payment Information" means data related to a particular transaction, such as the amount and payment method.

[2292] "Split amount" refers to an amount calculated to divide multiple payments equally or in specific proportions.

[2293] "Complete within the messenger application" means that the user does not need to switch to an external application to complete a specific task, and all operations are completed within one application.

[2294] The present invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence within a messenger application. The system includes the following major hardware and software components:

[2295] Hardware and Software Components

[2296] 1. Server

[2297] Generative artificial intelligence: Using OpenAI's GPT-4 as an example.

[2298] API: Google Calendar API, restaurant reservation sites (e.g. Gurunavi API, Tabelog API)

[2299] Communication module: Data communication using HTTP / HTTPS protocol

[2300] 2. Terminal

[2301] Messenger applications: General communication applications (e.g., LINE, WhatsApp)

[2302] Data transmission / reception module: HTTP request sending and response receiving functions

[2303] 3. Users

[2304] Input devices: smartphones, tablets, PCs, etc.

[2305] Scheduling details

[2306] A user types "Let's all get together for dinner next Friday" in a chat group within a messenger application. The device sends this request to the server as an HTTP request. The server uses the received request as a trigger to launch a generative artificial intelligence (AI) and obtain schedule information from each user's Google Calendar API. The server analyzes this information, identifies common free time slots, and selects the most suitable candidate date. The selected candidate date (e.g., "Next Friday at 7pm") is notified within the chat group via the device. When the user accepts the candidate date, the final date is confirmed and everyone is notified.

[2307] Booking details

[2308] The user types "Make a reservation at a Japanese restaurant in Shinjuku" in a messenger application. The device sends this request to the server. The server uses generative artificial intelligence to access the APIs of multiple restaurant reservation sites and retrieve restaurant information that meets the criteria. The retrieved restaurant candidates are notified to the user via the device. When the user selects one restaurant from the candidates and replies, the server automatically makes a reservation at the selected restaurant and retrieves the reservation confirmation information. The server then notifies the chat group of the reservation confirmation information, and the device displays it to the user.

[2309] Split payment details

[2310] After the meal, a user requests in chat to "split the bill." The device sends this request to the server. The server then collects payment information by sending a message to each user asking them to enter their expected payment amount. Each user enters their payment amount in chat and sends that information to the server via their device. The server uses generative artificial intelligence to tally the entered payment amounts and calculates each user's share of the bill. Finally, the server notifies each user of the total share of the bill and instructs them to pay. Users follow the instructions and make the payment using the payment function within the app (e.g., PayPay, LINE Pay). The server confirms that each user has completed payment and sends a notification of settlement completion to everyone.

[2311] Examples and prompts

[2312] For example, if a user is planning a meal at a restaurant with a group of friends, they can enter the prompt text as follows:

[2313] "Let's all get together for dinner next Friday," I typed into the chat.

[2314] "Make a reservation at a Japanese restaurant in Shinjuku," he requested.

[2315] He asked to settle the bill, saying, "Let's split it."

[2316] This allows users to complete all operations within a single messenger application, enabling them to efficiently arrange schedules, make reservations, and split the bill.

[2317] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2318] Schedule adjustment

[2319] Step 1:

[2320] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[2321] Input: User's text message

[2322] Output: HTTP request from the terminal to the server

[2323] Step 2:

[2324] The terminal sends the received message to the server as an HTTP request.

[2325] Input: User's message

[2326] Output: The request data sent to the server

[2327] Step 3:

[2328] The server receives the request and launches a generative AI, which prepares access to the Google Calendar API for each user based on the model.

[2329] Input: HTTP request

[2330] Output: Prepare to access the calendar API

[2331] Step 4:

[2332] The server calls the Google Calendar API to obtain each user's calendar information.

[2333] Input: Calendar API request

[2334] Output: Calendar information for each user

[2335] Step 5:

[2336] The server analyzes the acquired calendar information and identifies commonly available time slots.

[2337] Input: Calendar information

[2338] Output: Candidate dates where everyone's schedules match

[2339] Step 6:

[2340] The server generates the best candidate date (e.g., "next Friday at 7pm") and notifies the chat group in the messenger application of this information.

[2341] Input: Data on the best candidate date

[2342] Output: Present candidate dates to the user

[2343] Step 7:

[2344] The terminal receives the candidate date notification from the server and displays it to the user.

[2345] Input: Candidate date notification

[2346] Output: Candidate dates displayed on the chat screen

[2347] Step 8:

[2348] The user checks the proposed dates and replies "OK" via chat.

[2349] Input: User consent message

[2350] Output: Acceptance request from device to server

[2351] Step 9:

[2352] The terminal sends the user's reply message to the server.

[2353] Input: Acceptance message

[2354] Output: Acceptance data sent to the server

[2355] Step 10:

[2356] The server waits until everyone agrees, and after confirming everyone's consent, it notifies the chat group of the confirmed date.

[2357] Input: consent data for all

[2358] Output: Notification of confirmed schedule

[2359] reservation

[2360] Step 1:

[2361] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[2362] Input: User request message

[2363] Output: Request from terminal to server

[2364] Step 2:

[2365] The terminal sends this request to the server.

[2366] Input: Request message

[2367] Output: The request sent to the server

[2368] Step 3:

[2369] The server receives the request and uses generative artificial intelligence to access the APIs of multiple restaurant reservation sites.

[2370] Input: Request data

[2371] Output: API request to the booking site

[2372] Step 4:

[2373] The server retrieves restaurant information that meets the criteria and lists it.

[2374] Input: API response

[2375] Output: Restaurant candidate list

[2376] Step 5:

[2377] The server sends the generated restaurant candidates to a chat group in a messenger application.

[2378] Input: Restaurant candidate list

[2379] Output: Information presented to the user

[2380] Step 6:

[2381] The terminal receives the list of restaurant candidates from the server and displays it to the user.

[2382] Input: Restaurant candidate list

[2383] Output: Candidate list displayed on the chat screen

[2384] Step 7:

[2385] The user selects one restaurant from the presented options and replies via chat.

[2386] Input: User's selected message

[2387] Output: Selected data from the terminal to the server

[2388] Step 8:

[2389] The terminal transmits the selection result to the server.

[2390] Input:Selection data

[2391] Output: Notify the server of the selection results

[2392] Step 9:

[2393] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[2394] Input: Selected restaurant information

[2395] Output: Confirmed reservation information

[2396] Step 10:

[2397] The server notifies the chat group of the reservation confirmation information, and the terminal displays it to the user.

[2398] Input: Confirmed reservation information

[2399] Output: User notification

[2400] Split payment

[2401] Step 1:

[2402] After a meal, a user chats and asks to split the bill.

[2403] Input: User request message

[2404] Output: Request from terminal to server

[2405] Step 2:

[2406] The terminal sends this request to the server.

[2407] Input: Request message

[2408] Output: The request sent to the server

[2409] Step 3:

[2410] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[2411] Input: Request data

[2412] Output: Message requesting expected payment amount

[2413] Step 4:

[2414] The user enters the payment amount in the chat.

[2415] Input: Payment amount Message

[2416] Output: Input data from the terminal to the server

[2417] Step 5:

[2418] The terminal transmits the payment information entered by the user to the server.

[2419] Input: Payment amount data

[2420] Output: Payment information to the server

[2421] Step 6:

[2422] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[2423] Input: Payment amount data

[2424] Output: Split amount data

[2425] Step 7:

[2426] The server notifies each user of the total split amount and instructs them to pay.

[2427] Input: Split amount data

[2428] Output: Payment instruction message

[2429] Step 8:

[2430] Users follow the instructions and make payments using the app's payment function.

[2431] Input: Payment Instruction Message

[2432] Output: Payment completion information

[2433] Step 9:

[2434] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[2435] Input: Payment completion information

[2436] Output: Payment completion notification

[2437] (Application example 1)

[2438] 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."

[2439] With traditional messaging applications, users often had to spend a lot of time coordinating schedules, making restaurant reservations, and splitting bills. These processes were also performed separately, resulting in poor overall convenience. Furthermore, insufficient information sharing and collaboration between different applications led to inconsistent user experiences.

[2440] 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.

[2441] In this invention, the server includes a message transfer application means for accepting requests from users, a generative model means for acquiring each user's schedule and selecting the optimal candidate date, a means for acquiring information from a reservation information site, presenting it to the user, and finalizing the reservation, a means for collecting payment information, calculating the split amount, and processing the payment between users, a calendar linking means for acquiring user schedule information, an information search means for searching for reservation candidates, and an electronic payment means for executing the payment process. This enables consistent operation within the messaging application, and allows each process of scheduling, making reservations, and splitting the bill to be carried out smoothly.

[2442] A "message transfer application that accepts requests from users" is an application that allows users to transmit various requests to the system by sending messages.

[2443] A "generative model" is an algorithm that uses artificial intelligence to analyze a user's schedule information and generate optimal candidate dates.

[2444] "Means for obtaining information from a reservation information site, presenting it to the user, and confirming the reservation" refers to a system for obtaining the necessary reservation information from an online reservation information service, presenting it to the user for selection, and confirming the reservation.

[2445] "Means for collecting payment information, calculating split amounts, and processing payments between users" refers to a system that collects payment amount information for each user, calculates split amounts based on that information, and ensures that appropriate payments are made between users.

[2446] The "calendar linking means for acquiring the user's schedule information" is a technology for linking with a calendar service used by the user and acquiring the schedule information.

[2447] The "information search means for searching for reservation candidates" is a technology for searching for suitable candidates from reservation information sites in response to a user request.

[2448] The "electronic payment means for executing payment processing" is a system for electronically settling payments between users based on the collected split amounts.

[2449] The present invention is a system that allows users to easily schedule, book, and split bill payments within a messaging application. The system includes the following components:

[2450] System Configuration

[2451] 1. A message transfer application that accepts requests from users

[2452] The server receives the dates and reservation requests that users propose in the chat, and these requests are sent to the server in an appropriate format.

[2453] 2. A generative model that obtains each user's schedule and selects the best candidate date

[2454] The server uses a generative AI model to retrieve and analyze each user's calendar information. For example, it uses the Google Calendar API to retrieve the user's schedule and select the best possible dates. This information is then analyzed based on prompts.

[2455] 3. A means of obtaining information from the reservation information site, presenting it to the user, and finalizing the reservation

[2456] The server searches for restaurant options from reservation information sites (e.g., OpenTable API) based on the specified date, time, and location, and presents them to the user in the chat. The server then automatically confirms the reservation based on the user's selection.

[2457] 4. A means of collecting payment information, dividing the bill, and processing payments between users.

[2458] The server collects payment information from the user, calculates the split amount using a generative AI model, notifies the user of the calculation result, and makes the payment using an electronic payment method (e.g., Stripe).

[2459] Hardware and software used

[2460] Hardware: Smartphones, smart glasses

[2461] Software: Python, Flask, Google Calendar API, OpenTable API, Stripe API

[2462] Overview of the process

[2463] 1. Scheduling:

[2464] If a user types into the chat, "Let's all get together for dinner next Friday," the server retrieves everyone's calendar information and presents the most suitable candidate dates.

[2465] 2. Reservations:

[2466] If a user types "Make a reservation at a Japanese restaurant in Shinjuku," the server will call the OpenTable API, retrieve and present restaurant information that matches the criteria, and confirm the reservation at the selected restaurant.

[2467] 3. Split the bill:

[2468] After the meal, if the user inputs "Let's split the bill," the server collects payment information, calculates the split amount using a generative AI model, and completes the payment using an electronic payment method.

[2469] Examples and prompts

[2470] For example, if a group of friends suggests in a chat, "Let's have a Japanese dinner in Shibuya next Friday," the server will check everyone's calendars and suggest "Friday at 7 PM." If a user then requests, "Make a reservation at a Japanese restaurant in Shinjuku," the server will use the OpenTable API to search for restaurants that meet the criteria and make a reservation at the recommended restaurant. After the meal, if the user requests, "Let's split the bill," the server will tally up the amounts paid by each user, calculate the split amount, and notify them.

[2471] Example prompt sentence:

[2472] I've suggested a Japanese dinner in Shibuya next Friday at 7pm. I've checked everyone's calendars and this date and time is most suitable. Please confirm and accept.

[2473] The restaurant search results are: 1. Shibuya Washokutei, 2. Ginza Washoku Teishoku, 3. Fine Japanese Restaurant. Please select the restaurant you want.

[2474] Your meal is complete. The total is 20,000 yen. We split the bill at 5,000 yen per person. Please complete the payment using the link below.

[2475] By using this system, all operations can be completed within the message forwarding app, greatly improving user convenience.

[2476] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2477] Step 1:

[2478] Input: A user inputs a scheduling request within a message forwarding application.

[2479] What happens: A user types in a chat group, "Let's all get together for dinner next Friday."

[2480] Server processing: The terminal receives this request and sends it to the server.

[2481] Output: The server receives the request and proceeds.

[2482] Step 2:

[2483] Input: The server retrieves all users' calendar information.

[2484] Specific operation: The server uses the Google Calendar API to obtain the schedule information of all participants.

[2485] Data processing: Analyze the acquired calendar information.

[2486] Server processing: Using a generative AI model, analyze each user's schedule and identify common free time slots.

[2487] Output: A list of optimal candidate dates is generated, ready to be presented to the user.

[2488] Step 3:

[2489] Input: The retrieved calendar information and a list of common free time slots.

[2490] Specific operation: The servers select "next Friday at 7pm" as a commonly available time slot.

[2491] Server processing: Format the selected candidate dates for presentation in the group chat.

[2492] Output: The server sends a notification to the device, allowing the user to check the proposed dates.

[2493] Step 4:

[2494] Input: Candidate dates provided by the server.

[2495] Specific behavior: The user confirms the proposed date in chat and replies "OK."

[2496] Terminal processing: The terminal sends the user's consent to the server.

[2497] Output: The server confirms everyone's acceptance and notifies everyone of the confirmed date.

[2498] Step 5:

[2499] Input: The user types a reservation request in the message.

[2500] Specific action: The user types, "Make a reservation at a Japanese restaurant in Shinjuku."

[2501] Terminal processing: The terminal sends this request to the server.

[2502] Output: The server receives the request and prepares to proceed.

[2503] Step 6:

[2504] Input: The server receives the reservation conditions (location, genre).

[2505] Specific operation: The server calls the OpenTable API and retrieves restaurant information using the conditions "Shinjuku" and "Japanese cuisine."

[2506] Data processing: Analyze and organize the list of restaurant candidates obtained.

[2507] Server processing: Generates a candidate list that can be presented to the user.

[2508] Output: Format the list of restaurant suggestions to present in the chat.

[2509] Step 7:

[2510] Input: A list of restaurant candidates.

[2511] Specific operation: The user selects one restaurant from the presented options and replies via chat.

[2512] Terminal processing: The terminal sends the selection results to the server.

[2513] Output: The server prepares to automatically make a reservation at the selected restaurant.

[2514] Step 8:

[2515] Input: User selection results, reservation candidate list.

[2516] Specific behavior: The server uses the OpenTable API to make a reservation at the selected restaurant.

[2517] Data processing: Obtain and format confirmed reservation information.

[2518] Server processing: Notify everyone of the confirmed reservation information.

[2519] Output: Send a notification to the device with the confirmed reservation information.

[2520] Step 9:

[2521] Input: The user enters a request for split payment in the message.

[2522] Specific action: The user types "Let's split the bill" in the chat.

[2523] Terminal processing: The terminal sends this request to the server.

[2524] Output: The server receives the request and prepares to proceed.

[2525] Step 10:

[2526] Input: Request to split the bill.

[2527] Specific operation: To collect payment information, the server sends a message to each user requesting them to enter the expected payment amount.

[2528] Data processing: Aggregate payment amounts from users.

[2529] Server processing: Using the generative AI model, the entered payment amounts are aggregated and the amount each user is responsible for is calculated.

[2530] Output: Notify each user of the split amount.

[2531] Step 11:

[2532] Input: Notification of split amount.

[2533] Specific behavior: The user makes a payment using the app's electronic payment function.

[2534] Data Processing: We process each user's payment using an electronic payment system (e.g., Stripe API).

[2535] Server processing: Confirm that each user has completed payment.

[2536] Output: Send a notification to everyone that payment is complete.

[2537] 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.

[2538] This invention is a system for scheduling, booking, and splitting bills using generative artificial intelligence and an emotion engine within a messenger application. The system of the present invention operates as follows.

[2539] Schedule adjustment

[2540] Receiving a rescheduling request

[2541] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[2542] The terminal sends this request to the server.

[2543] Calendar integration

[2544] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[2545] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[2546] The server analyzes the acquired calendar information and identifies commonly available time slots.

[2547] Emotion recognition with emotion engine

[2548] The server activates an emotion engine to recognize each user's emotion before making scheduling suggestions.

[2549] The server analyzes the user's chat content and past responses to obtain emotional data.

[2550] The server then suggests the best possible date based on the recognized emotion data.

[2551] Proposal of dates

[2552] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[2553] A notification is sent to the device and the user can confirm the proposed dates via chat.

[2554] Confirmation of schedule

[2555] The user confirms and accepts the proposed dates and replies "OK" via chat.

[2556] The terminal transmits the user's consent to the server.

[2557] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[2558] reservation

[2559] Receiving a booking request

[2560] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[2561] The terminal sends this request to the server.

[2562] Search for reservation candidates

[2563] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant reservation site and obtain restaurant information that meets the criteria.

[2564] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[2565] The emotion engine considers the user's emotional state and prioritizes appropriate restaurants to provide a better user experience.

[2566] The server lists the restaurant candidates and presents them to the chat group.

[2567] Confirmation of reservation

[2568] The user selects one restaurant from the presented options and replies via chat.

[2569] The terminal transmits the selection result to the server.

[2570] Notification of final information

[2571] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[2572] The server notifies everyone of the confirmed reservation information.

[2573] Split payment

[2574] Receiving a split bill request

[2575] After a meal, a user chats and asks to split the bill.

[2576] The terminal sends this request to the server.

[2577] Collecting payment information

[2578] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[2579] The user enters the payment amount in the chat.

[2580] The terminal transmits the payment information entered by the user to the server.

[2581] Emotion recognition with emotion engine

[2582] The server activates an emotion engine to recognize the emotion of each user during payment information collection and bill splitting calculation.

[2583] The server analyzes the user's chat content and reactions to obtain emotional data.

[2584] The server provides appropriate communication methods and feedback based on the recognized emotion data.

[2585] Calculating the split amount

[2586] The server uses generative artificial intelligence to tally the entered payment amounts and calculate the amount each user will have to pay.

[2587] Payment Processing

[2588] The server notifies each user of the total amount of payment and instructs them to make payment.

[2589] Users follow the instructions and make payments using the app's payment function.

[2590] The server confirms that each user has completed payment and sends a notification of the completion of settlement to everyone.

[2591] Specific Examples

[2592] For example, if a user plans to dine at a restaurant with a group of friends, the system described above may be used as follows.

[2593] Schedule adjustment

[2594] 1. User A proposes a date for a meal in chat, types "next Friday," and sends the request.

[2595] 2. The server uses generative artificial intelligence to obtain each user's calendar information and select the optimal candidate date.

[2596] 3. The server uses the emotion engine to recognize each user's emotion data and check whether the candidate date matches the user's emotion.

[2597] 4. The server presents the proposed dates in the group chat and gets everyone's approval.

[2598] reservation

[2599] 1. User B requests a reservation at a specific restaurant based on confirmed dates.

[2600] 2. The server uses generative artificial intelligence and an emotion engine to present reservation options that meet the criteria, and the user can select one.

[2601] 3. The server will automatically make a reservation at the selected restaurant and notify everyone of the reservation confirmation.

[2602] Split payment

[2603] 1. User C requests splitting the bill and submits a request.

[2604] 2. The server collects the payment amount of each user and monitors the emotions of each user using an emotion engine.

[2605] 3. The server uses generative artificial intelligence to calculate the split amount and instructs payment.

[2606] 4. The user completes the payment using the in-app payment function, and the server sends a settlement completion notification to everyone.

[2607] This method not only allows all operations to be completed within the messenger application, greatly improving user convenience, but also further improves the user experience through processes that utilize the emotion engine.

[2608] The processing flow will be explained below.

[2609] Schedule adjustment

[2610] Step 1:

[2611] A user types "Let's all get together for dinner next Friday" in a chat group on a messenger application.

[2612] The terminal sends this request to the server.

[2613] Step 2:

[2614] The server launches a generative artificial intelligence and obtains each user's calendar information via an API.

[2615] The server obtains data from Google Calendar, Outlook Calendar, etc. with each user's permission.

[2616] Step 3:

[2617] The server analyzes the acquired calendar information and identifies commonly available time slots.

[2618] Step 4:

[2619] The server activates an emotion engine to recognize each user's emotion before making suggestions.

[2620] The server analyzes the user's chat content and past responses to obtain emotional data.

[2621] Step 5:

[2622] The server selects the most suitable candidate date based on the recognized emotion data.

[2623] Step 6:

[2624] The server selects the best candidate date (e.g., "next Friday at 7pm") and presents it in the group chat.

[2625] A notification is sent to the device and the user can confirm the proposed dates via chat.

[2626] Step 7:

[2627] The user confirms and accepts the proposed dates and replies "OK" via chat.

[2628] The terminal transmits the user's consent to the server.

[2629] Step 8:

[2630] After the server confirms everyone's consent, it notifies everyone of the confirmed schedule.

[2631] reservation

[2632] Step 1:

[2633] A user types "Make a reservation at a Japanese restaurant in Shinjuku" in the messenger app.

[2634] The terminal sends this request to the server.

[2635] Step 2:

[2636] The server uses generative artificial intelligence and an emotion engine to access the API of a restaurant reservation site and obtain restaurant information that meets the criteria.

[2637] For example, the server searches using the conditions "Shinjuku," "Japanese food," and "next Friday night at 7 p.m."

[2638] Step 3:

[2639] The emotion engine considers the user's emotional state and prioritizes appropriate restaurants to provide a better user experience.

[2640] Step 4:

[2641] The server lists the restaurant candidates and presents them to the chat group.

[2642] Step 5:

[2643] The user selects one restaurant from the presented options and replies via chat.

[2644] The terminal transmits the selection result to the server.

[2645] Step 6:

[2646] The server automatically makes a reservation at the selected restaurant and obtains the reservation confirmation information.

[2647] Step 7:

[2648] The server notifies everyone of the confirmed reservation information.

[2649] Split payment

[2650] Step 1:

[2651] After a meal, a user chats and asks to split the bill.

[2652] The terminal sends this request to the server.

[2653] Step 2:

[2654] To obtain payment information, the server sends a message to each user asking them to enter the amount they expect to pay.

[2655] The user enters the payment amount in the chat.

[2656] The terminal transmits the payment information entered by the user to the server.

[2657] Step 3:

[2658] The server activates an emotion engine to recognize the emotion of each user during payment information collection and bill splitting calculation.

[2659] The server analyzes...

Claims

1. a messenger application that accepts requests from users; A generative AI system that acquires each user's schedule and selects the best candidate date. A means for searching reservation information from a reservation site, presenting it to a user, and confirming the reservation; means for collecting payment information, splitting the payment amount, and processing the payment between users; A system including:

2. 10. The system of claim 1, further comprising means for presenting candidate dates and receiving user acceptance.

3. 2. The system according to claim 1, further comprising means for notifying the user of confirmed reservation information after the reservation is confirmed.

Images