system

Abstract

Provide a system. A means for a user to input predetermined date information; means for receiving input date information; A means for analyzing the received date information and referencing the rules of the corresponding service based on generative AI; means for calculating the earliest and latest dates based on the applicable rules; A means for verifying the consistency of the calculation results; A system including a means for presenting to a user the results of a calculation whose integrity has been confirmed.

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] Previously, when creating application forms for new non-telecommunications services, sales representatives had to manually check a large amount of information to create the application form in accordance with the date entry rules for each service, which was inefficient and posed a risk of human error. Furthermore, mistakes in selecting dates could lead to delays in service provision and a decrease in customer satisfaction. [Means for solving the problem]

[0005] This invention allows for efficient and accurate date suggestions using a system that includes a means for users to input specific date information, a means for receiving the input date information, a means for analyzing the received date information and referencing the rules of the corresponding service using generative AI, a means for calculating the earliest and latest dates based on the rules, a means for verifying the consistency of the calculation results, and a means for presenting the calculation results whose consistency has been confirmed to the user. As a result, it is possible to reduce the burden on sales representatives and human error in date selection.

[0006] "User" refers to the person or business that operates the system and inputs date information.

[0007] "Date information" refers to one or more of the application date, desired start date of use, desired start date of billing, activation date, and desired delivery date entered into the system.

[0008] "Means" refers to a device or method used to accomplish a particular function.

[0009] "Means for receiving" refers to a system component for obtaining and analyzing date information entered by a user.

[0010] "Analysis" refers to performing calculations and data processing according to specific rules based on the entered date information.

[0011] "Generative AI" refers to artificial intelligence that generates optimal output from input data based on specific rules.

[0012] "Applicable rules" refers to the criteria and conditions for selecting dates defined for each service.

[0013] "Earliest Date" means the earliest date possible under the rules.

[0014] "Latest Date" means the latest date possible under the rules.

[0015] "Calculation" refers to the process of deriving a date based on specific algorithms or rules.

[0016] "Integrity verification" refers to the process of checking whether a calculated date meets pre-defined conditions.

[0017] "Date suggestion" refers to presenting the earliest and latest dates derived by generative AI.

[0018] "System" refers to a comprehensive network and software platform consisting of multiple components, including the above-mentioned means and generative AI. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] This invention relates to a system that utilizes generative AI to propose optimal dates to streamline application forms for new non-telecommunications services. The system supports accurate and prompt application form creation by suggesting the earliest and latest dates when the user inputs specified date information.

[0041] System configuration

[0042] 1. User Interface (Terminal)

[0043] This includes a function that provides a form for the user to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, or desired delivery date).

[0044] 2. Data receiving module (server)

[0045] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[0046] 3. Analysis module (server)

[0047] The server includes a function to analyze the received date information and obtain the date rule set for the corresponding service.

[0048] 4. Generative AI module (server)

[0049] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[0050] 5. Integrity Verification Module (Server)

[0051] Includes a function to verify the consistency of the results output by generative AI.

[0052] 6. Result presentation module (terminal)

[0053] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[0054] Program processing flow

[0055] Input reception

[0056] Terminal: The user selects the desired service and enters date information through a specified interface. For example, the user enters "November 1, 2023" as the "desired delivery date."

[0057] Data reception and analysis

[0058] Terminal: Sends the entered information to the server.

[0059] Server: Analyzes the service identification information and date information based on the received data.

[0060] Calculating the earliest and latest dates

[0061] Server: Obtains a rule set corresponding to the service identification information based on generative AI.

[0062] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the applicable rules. For example, it calculates that the earliest delivery date is "November 3, 2023" and the latest delivery date is "November 15, 2023."

[0063] Consistency verification and presentation of results

[0064] Server: The calculation result is verified by the consistency verification module. For example, it checks whether the shortest delivery date falls on a holiday.

[0065] Terminal: Receives the results of the earliest and latest dates sent from the server and displays them on the user interface.

[0066] Specific examples

[0067] Suggested delivery date

[0068] User: Enters "November 1, 2023" as the "Desired delivery date" and clicks the send button on the device.

[0069] Server: Receives the information "November 1, 2023" and "desired delivery date" and instructs the generative AI to refer to the relevant rule based on the service identification.

[0070] Generative AI (on the server): Calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023."

[0071] Server: After verifying the integrity, it sends the calculation result to the terminal.

[0072] Terminal: Display "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" in the user interface.

[0073] The system of the present invention allows users to select dates efficiently and accurately, reducing the workload of sales representatives. Additionally, automated date suggestions reduce human error in application completion and minimize the risk of service delays.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] User: Select the desired service via the designated interface and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date). For example, enter "November 1, 2023" as the "desired delivery date."

[0077] Step 2:

[0078] Terminal: The service information and date information entered by the user are sent to the server via an HTTP POST request.

[0079] Step 3:

[0080] Server: Analyzes the received request and extracts the service ID and date information. For example, the service ID is "A", the date is "November 1, 2023", and the date type is "Desired delivery date".

[0081] Step 4:

[0082] Server: Based on the extracted service identification information, the server sends the corresponding date rule set to the generative AI, which then retrieves the corresponding rules from its internal database.

[0083] Step 5:

[0084] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the acquired rule set. For example, it calculates that the earliest delivery date is "November 3, 2023" and the latest delivery date is "November 15, 2023."

[0085] Step 6:

[0086] Server: Receives the calculation results of the earliest and latest dates returned by the generative AI and verifies the consistency of the results. For example, it checks whether the earliest date is the date on which the specified service can be provided.

[0087] Step 7:

[0088] Server: Converts the calculation results whose integrity has been confirmed into JSON format and sends them to the user's device.

[0089] Step 8:

[0090] Terminal: Receives and analyzes the JSON data sent from the server. As a result, the following is displayed on the user interface: "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0091] The above is a concrete processing flow of the entire system. The operations performed at each step from receiving input from the user to presenting the final date proposal have been explained in detail.

[0092] Example 1

[0093] 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."

[0094] Conventional application creation systems have the problem that it takes time and effort for users to select an appropriate date, making it difficult to select an accurate date. In addition, human error is likely to occur in selecting the date, which can lead to reduced efficiency and risk of delays in service provision.

[0095] 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.

[0096] In this invention, the server includes means for a user to input predetermined information, means for receiving the input information, means for analyzing the received information and referencing the rules of the relevant service based on generative artificial intelligence, means for calculating the earliest date and latest date based on the rules, means for verifying the consistency of the calculation results, and means for presenting the calculation results whose consistency has been confirmed to the user. This allows the user to select dates efficiently and accurately, speeding up the application form creation process, reducing human error, and minimizing the risk of delays in service provision.

[0097] "User" means any person or entity that uses the System to input information and receive results.

[0098] "Specified information" refers to specific data that the user must input into the system, including the application date, desired start date, activation date, desired date, etc.

[0099] "Means" refers to a method, device, or function by which a system realizes a specific function or role.

[0100] The "means for inputting information" refers to an interface or device that allows a user to input predetermined information into the system.

[0101] "Means for receiving information" refers to the method or function by which the system receives information input by the user.

[0102] "Means for analyzing received information" refers to the methods and algorithms that the system uses to understand the information it receives and process it appropriately.

[0103] "Service Rules" means the business rules and conditions associated with a particular Service.

[0104] "Generative AI" refers to artificial intelligence techniques used to perform specific tasks or calculations within a system.

[0105] "Means for referencing relevant rules" refers to the methods or functions that enable a generative artificial intelligence to obtain and use rules related to a specific service.

[0106] "Means for calculating the earliest and latest dates" refers to methods or functions that allow generative artificial intelligence to calculate optimal dates according to rules.

[0107] "Means for verifying the consistency of calculation results" refers to methods or functions that confirm whether the date results calculated by the generative artificial intelligence match the specified conditions.

[0108] The "means for presenting the calculation result whose consistency has been confirmed" is a method or function for displaying the optimal date result to the user after the validation has been performed.

[0109] The present invention relates to a system that utilizes generative AI to propose optimal dates to streamline the creation of application forms for new non-communication services. This system supports accurate and rapid creation of application forms by suggesting the earliest and latest dates based on the user's input of specified information. A specific embodiment of the present invention will be described below.

[0110] User Interface (Terminal)

[0111] The user uses the device's user interface to select a service and enter required information (such as date information). The user interface can take the form of, for example, a web form or a mobile app. Input fields include "application date," "desired start date," "desired billing start date," "activation date," and "desired delivery date."

[0112] Data receiving module (server)

[0113] The terminal sends the information entered by the user to the server. This data is sent to the server via a protocol such as an HTTP request. The server checks whether the received data is in the correct format and performs validation.

[0114] Analysis module (server)

[0115] The server analyzes the information received through the data reception module. Specifically, the server identifies the service based on the received data and determines the rules for the corresponding service. The analyzed data is passed to the generative AI module.

[0116] Generative AI module (server)

[0117] The generative AI module calculates the earliest and latest delivery dates based on the analyzed data and applicable service rules. This calculation uses an internal algorithm and rule set. For example, the "earliest delivery date" is calculated as "November 3, 2023" and the "latest delivery date" is calculated as "November 15, 2023."

[0118] Integrity verification module (server)

[0119] The results output by the generative AI module are passed to the consistency verification module, which checks whether the calculation results meet pre-set conditions, such as whether the calculated date falls on a holiday or is an unreasonable date.

[0120] Result presentation module (terminal)

[0121] Once the verification is complete, the server sends the results of the earliest and latest delivery dates to the terminal. The terminal displays the received data on the user interface and presents the results to the user. For example, it displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0122] Specific examples

[0123] For example, if a user enters "November 1, 2023" as the "desired delivery date" and clicks the send button on the device, the server receives the information "November 1, 2023" and the "desired delivery date." The server then references the rule set based on generative AI and calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023." Finally, if the calculation results pass consistency verification, the device displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0124] The system allows users to select dates efficiently and accurately, reducing the workload of sales representatives. Automated date suggestions also reduce human error in application completion, minimizing the risk of service delays.

[0125] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0126] Step 1:

[0127] The user inputs the specified information into the terminal. The user inputs the specified information, including the service selection and date information. For example, the user inputs "November 1, 2023" as the "desired delivery date." Once the input is complete, the user clicks the send button. The input data includes the application date, desired start date of use, desired start date of billing, activation date, desired delivery date, etc.

[0128] Step 2:

[0129] The terminal sends the entered information to the server. The information entered by the user is packaged in an appropriate format (for example, JSON format) and sent to the server via an HTTP request. The input data is sent in a format such as "Delivery request date: November 1, 2023".

[0130] Step 3:

[0131] The server receives and analyzes the input information. The server checks the received data and validates that it is in the appropriate format. If the received data is in the correct format, it analyzes the data and extracts the service identification and date information. For example, it analyzes the "desired delivery date" information and obtains the service identification information.

[0132] Step 4:

[0133] The server instructs the generative AI to retrieve the rule set. Based on the analyzed information, the server instructs the generative AI to refer to the rule set for the relevant service. For example, it retrieves the rule set related to delivery services. This rule set includes business rules and date calculation conditions.

[0134] Step 5:

[0135] The generative AI calculates the earliest and latest dates. The generative AI calculates the earliest and latest dates based on the received rule set and input information. For example, if the "desired delivery date" is "November 1, 2023," the earliest delivery date is calculated to be "November 3, 2023," and the latest delivery date is calculated to be "November 15, 2023." Calendar information and holiday information are taken into account in the calculation.

[0136] Step 6:

[0137] The server verifies the consistency of the calculation results. The server passes the date output by the generative AI to the consistency verification module. The consistency verification module checks whether the earliest and latest dates match the set conditions. For example, it checks whether the earliest date is a holiday or an unreasonable date.

[0138] Step 7:

[0139] The terminal receives and displays the results of the integrity check. The server sends the earliest and latest verification completion dates to the terminal. The terminal displays the results on the user interface. For example, "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" is displayed, visually presenting the results to the user.

[0140] (Application example 1)

[0141] 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."

[0142] In conventional application form creation systems for non-communication services, users manually select their desired date, which makes operation complicated and can lead to input errors and delays in application creation. Furthermore, particularly in food delivery, there are no systems that automatically calculate optimal departure and arrival times for the customer's desired delivery time, reducing delivery efficiency. The present invention aims to solve these problems and provide a system that efficiently and accurately selects dates and suggests delivery times.

[0143] 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.

[0144] In this invention, the server includes: a means for a user to input specified date information; a means for receiving the input date information; a means for analyzing the received date information and referencing the rules of the relevant service using a generative AI; a means for calculating the earliest date and latest date based on the rules; a means for adjusting and verifying the calculation result; a means for presenting the adjusted and confirmed calculation result to the user; and a means for a user to input a desired delivery time, calculate optimal departure and arrival times using the generative AI, and notify the restaurant operator and delivery person. This allows the user to efficiently and accurately select a date, and in the case of food delivery in particular, it is possible to automatically calculate optimal departure and arrival times for the customer's desired delivery time and promptly notify the restaurant operator and delivery person.

[0145] "Specified date information" is information including the specific date and time when the user wishes to use the service.

[0146] The "means for inputting" is a user interface that allows a user to input predetermined date information into the system.

[0147] The "receiving means" is a function that allows the server to receive date information entered by the user.

[0148] The "analysis means" is a function for analyzing received date information and extracting the rules for the corresponding service.

[0149] "Generative AI" is a technology that uses artificial intelligence to generate optimal dates and times based on specific rules.

[0150] The "earliest date" is the earliest date on which the service desired by the user can be provided.

[0151] The "latest date" is the latest date on which the service desired by the user can be provided.

[0152] "Means for calculating" means a function for calculating the earliest and latest dates based on applicable rules.

[0153] The "means for adjusting and verifying" is a function for checking whether the generated shortest date and latest date match the conditions set in advance.

[0154] The "means for presenting" is a function for notifying the user of the calculation results for which the adjustment has been confirmed.

[0155] "Desired delivery time" is information specifying the delivery date and time of a product or service that the user particularly desires.

[0156] "Departure time" is the time when the delivery person starts delivering the goods or services from the restaurant or warehouse.

[0157] "Arrival time" is the time when the product or service will arrive at the delivery destination specified by the user.

[0158] "Food service operators" refers to stores and companies that provide food delivery services.

[0159] A "delivery person" is a person or company responsible for delivering products or services to a customer on the date and time requested.

[0160] MODE FOR CARRYING OUT THE INVENTION

[0161] This invention relates to a food delivery system that automatically calculates optimal departure and arrival times based on the desired delivery time specified by the user. This system receives the desired delivery time entered by the user, uses generative AI to propose the optimal time, and notifies the restaurant operator and delivery staff, thereby achieving efficient delivery.

[0162] System configuration

[0163] User Interface (Terminal)

[0164] This is an interface that provides a form for the user to enter the desired delivery time. Taking a smartphone application as an example, the user specifies the desired delivery time as "December 1, 2023, 18:00."

[0165] Data receiving module (server)

[0166] This module receives the desired delivery time sent from the terminal. This module performs initial processing to analyze the user's input data on the server.

[0167] Analysis module (server)

[0168] It includes a function to analyze the requested delivery time received and obtain the rules for the corresponding service. Based on the results of this analysis, it prepares the data necessary for generative AI.

[0169] Generative AI module (server)

[0170] Based on the analyzed data, the module calculates the optimal departure and arrival times for the desired delivery time. This calculation is performed using AI models such as TENSORFLOW (registered trademark).

[0171] Adjustment verification module (server)

[0172] Validate that the calculated departure and arrival times meet predefined criteria, such as whether the optimal departure time is within the restaurant's opening hours and whether the arrival time matches the customer's preferred time slot.

[0173] Result presentation module (terminal)

[0174] The system notifies users, food service providers, and delivery personnel of the optimal departure and arrival times, providing accurate information to all parties via a smartphone app.

[0175] Hardware and software used

[0176] Hardware: Cloud servers such as Amazon EC2

[0177] Software: TensorFlow (generative AI model), custom validator (adjustment verification tool), smartphone application

[0178] Data calculation: Analyze received data and calculate optimal time using AI model, and verify adjustments

[0179] Specific usage scenarios and prompt examples

[0180] Usage scenarios

[0181] The user enters into the app a request for delivery at "December 1, 2023, 18:00." The server receives and analyzes the data. Generative AI is used to calculate the optimal departure and arrival times, and adjustments and verification are performed. As a result, the optimal departure time is calculated to be "December 1, 2023, 17:00" and the optimal arrival time is calculated to be "December 1, 2023, 18:00." These results are notified to the restaurant operator and delivery staff.

[0182] Prompt Sentence Examples

[0183] Desired delivery time: 2023-12-01 18:00

[0184] Generated departure time: 2023-12-01 17:00

[0185] Generated arrival time: 2023-12-01 18:00

[0186] The system will significantly improve the efficiency of food delivery and increase customer satisfaction by providing accurate delivery times.

[0187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0188] Step 1:

[0189] The user enters the desired delivery time

[0190] The user inputs the desired delivery time through the smartphone app interface. For example, they might input "December 1, 2023, 6:00 PM." This input information is sent to the system as the first data.

[0191] Step 2:

[0192] Receiving data

[0193] The server receives the requested delivery time entered from the terminal. The received data is temporarily stored on the server for use in the next analysis step. Specifically, the data entered by the user as "December 1, 2023, 18:00" is received.

[0194] Step 3:

[0195] Data analysis

[0196] The server analyzes the received desired delivery time. From this analysis, it extracts information about the user's desired delivery time and prepares to obtain the relevant delivery rules. For example, it analyzes "December 1, 2023, 18:00" and takes into account the restaurant's business hours and the delivery staff's working hours.

[0197] Step 4:

[0198] Calculating optimal time using generative AI

[0199] The generative AI model on the server calculates the optimal departure and arrival times based on the analyzed data. Specifically, using TensorFlow, for "December 1, 2023, 18:00," the optimal departure time is calculated as "December 1, 2023, 17:00" and the optimal arrival time is calculated as "December 1, 2023, 18:00."

[0200] Step 5:

[0201] Adjustment and verification of calculation results

[0202] The server verifies the calculation results using the adjustment verification module. For example, it checks whether the optimal departure time is within the restaurant's business hours, and whether the arrival time matches the time slot specified by the customer. Specifically, it checks whether "December 1, 2023, 5:00 PM" is within the restaurant's business hours, and whether "December 1, 2023, 6:00 PM" is within the time slot specified by the customer.

[0203] Step 6:

[0204] Presentation of results

[0205] The verified optimal departure and arrival times are sent to the terminal and notified to the user, the restaurant operator, and the delivery person. The information "Departure time: December 1, 2023, 5:00 PM, Arrival time: December 1, 2023, 6:00 PM" is displayed to all parties via the smartphone app interface.

[0206] 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.

[0207] This invention relates to a system that utilizes generative AI and an emotion engine to propose optimal dates and adjust the interface display and proposal content based on the user's emotions in order to streamline the creation of application forms for new non-telecommunications services. This system supports the accurate and speedy creation of application forms by allowing the user to input specific date information and proposing the earliest and latest dates, thereby improving user satisfaction.

[0208] System configuration

[0209] 1. User Interface (Terminal)

[0210] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[0211] It includes a function that uses an emotion engine to recognize the user's emotions and adjust the interface display and suggestions based on those emotions.

[0212] 2. Data receiving module (server)

[0213] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[0214] 3. Analysis module (server)

[0215] The server includes a function to analyze the received date information and obtain the date rule set for the corresponding service.

[0216] 4. Generative AI module (server)

[0217] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[0218] 5. Integrity Verification Module (Server)

[0219] Includes a function to verify the consistency of the results output by generative AI.

[0220] 6. Result presentation module (terminal)

[0221] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[0222] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine.

[0223] 7. Emotion engine module (terminal and server)

[0224] It includes the ability to analyze the user's emotions using voice recognition and facial expression recognition.

[0225] It includes a function to provide data that influences the analysis module and generative AI module based on the analysis results.

[0226] Program processing flow

[0227] Input acceptance and emotion recognition

[0228] Terminal: The user selects the desired service and enters date information via a specified interface. At the same time, the emotion engine analyzes voice or facial expression data to recognize the user's emotions. For example, while entering "November 1, 2023" as the "desired delivery date," the emotion engine recognizes from the user's tone of voice and facial expression that they are feeling stressed.

[0229] Data reception and analysis

[0230] Terminal: Sends input information and emotion data to the server.

[0231] Server: Based on the received data, analyzes the service ID and date information. Emotion data is also included in the analysis.

[0232] Calculating the earliest and latest dates

[0233] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[0234] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the relevant rules. For example, the earliest delivery date is calculated as "November 3, 2023" and the latest delivery date is calculated as "November 15, 2023." At the same time, if the user is stressed, the earlier delivery date will be prioritized.

[0235] Consistency verification and presentation of results

[0236] Server: The calculation result is verified by the consistency verification module. For example, it is verified whether the shortest date is within the date on which the specified service can be provided.

[0237] Device: Receives the results of the earliest and latest delivery dates sent from the server and adjusts the display content based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the device will suggest "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023," as well as play relaxing music and display encouraging messages.

[0238] Specific examples

[0239] Suggested delivery date

[0240] User: Enters "November 1, 2023" as the "Desired Delivery Date" and clicks the send button on the device. The emotion engine detects stress from the user's voice.

[0241] Server: Receives the information "November 1, 2023" and "desired delivery date" along with emotion data, and instructs the generative AI to refer to the relevant rules based on the service identification.

[0242] Generative AI (on the server): Calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023." At the same time, prioritizes and suggests shorter delivery dates based on emotional data to reduce stress.

[0243] Server: After verifying the integrity, it sends the calculation results and emotion-based adjustment results to the device.

[0244] Device: Display "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" on the user interface while playing relaxing music or displaying a light, encouraging message.

[0245] The system of the present invention allows users to select dates efficiently and accurately, reducing the workload of sales representatives, and further improves user satisfaction by adjusting the system based on the user's emotional state using the emotion engine.

[0246] The processing flow will be explained below.

[0247] Step 1:

[0248] User: Selects the desired service through a designated interface and enters date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date). For example, enter "November 1, 2023" as the "desired delivery date." At the same time, the emotion engine analyzes the user's facial expressions and voice to recognize their emotions.

[0249] Step 2:

[0250] The device sends the date information and emotion data entered by the user to the server. Specifically, it sends a request including the user's selected date (November 1, 2023) and desired delivery date, as well as emotion data.

[0251] Step 3:

[0252] Server: Analyzes the received request and extracts the service ID and date information. If emotion data is included, it is also included in the analysis. For example, the service ID is "A," the date information is "November 1, 2023," the date type is "Desired delivery date," and the emotion data is "Stress."

[0253] Step 4:

[0254] Server: Based on the extracted service identification information, the corresponding date rule set is sent to the generative AI. The generative AI retrieves the corresponding rules from its internal database. The application of the rules is also adjusted based on the emotion data.

[0255] Step 5:

[0256] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the acquired rule set. For example, the earliest delivery date is calculated as "November 3, 2023" and the latest delivery date is calculated as "November 15, 2023." At the same time, the earliest delivery date is given a higher priority based on emotion data.

[0257] Step 6:

[0258] Server: Receives the calculation results of the earliest and latest dates returned by the generative AI and verifies the consistency of the results. For example, it checks whether the earliest date is actually a date on which the service can be provided.

[0259] Step 7:

[0260] Server: The server sends the calculation results, whose integrity has been confirmed, in JSON format to the device, along with messages and influence factors based on the emotion data.

[0261] Step 8:

[0262] Terminal: Receives and analyzes the JSON data sent from the server. As a result of the analysis, the user interface displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023." Furthermore, if the user is feeling stressed, the device plays relaxing music and displays an encouraging message in a pop-up.

[0263] This is the specific processing flow of the entire system. By linking with the emotion engine, it can respond to the user's emotional state and provide a better user experience.

[0264] Example 2

[0265] 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."

[0266] Conventional application form creation systems make it difficult for users to accurately select date information and do not take the user's emotional state into consideration, which can sometimes compromise the user experience. As a result, the application process becomes cumbersome, resulting in problems of reduced user satisfaction. Furthermore, there are also problems with increased workloads for sales representatives and reduced work efficiency. To solve these issues, a system is needed that allows users to easily and quickly enter accurate date information and can adjust according to the user's emotional state.

[0267] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0268] In this invention, the server includes means for a user to input predetermined date information, means for receiving the input date information and user emotion information, means for analyzing the received date information and emotion information and referencing the rules of the relevant service, means for calculating the earliest date and latest date based on the relevant rules and emotion information, means for verifying the consistency of the calculation results, means for presenting the calculation results whose consistency has been confirmed to the user, and means for adjusting the display content of the interface in accordance with the user's emotional state. This allows the user to accurately and quickly select date information, and adjustments are made based on the user's emotional state, thereby improving user satisfaction and reducing the burden on sales representatives, thereby improving work efficiency.

[0269] "Date information" is information about specific dates such as the application date, desired start date of use, desired start date of billing, activation date, and desired delivery date that the user enters when filling out an application form for a service.

[0270] "Emotion information" is information about the user's emotional state that is analyzed by the emotion engine from the user's voice, facial expressions, and the like.

[0271] The "receiving means" refers to a hardware and software configuration for transmitting date information and emotion information input by the user to the server and receiving the information.

[0272] The "analysis means" refers to a hardware and software configuration for analyzing the received date information and emotion information and referencing the rules of the corresponding service based on the analysis.

[0273] "Generative AI" is an artificial intelligence model that calculates the earliest and latest dates based on received data according to specific rules.

[0274] A "means for calculating" is a hardware and software configuration for calculating the earliest and latest dates based on applicable rules and sentiment information.

[0275] The "means for verifying consistency" is a hardware and software configuration for checking whether the generated earliest and latest dates match pre-set conditions.

[0276] The "presentation means" refers to a hardware and software configuration for displaying the results of the earliest and latest dates for which consistency has been confirmed on a user interface and providing feedback to the user.

[0277] The "adjusting means" refers to a hardware and software configuration that adjusts the interface display content according to the user's emotional state, thereby improving user satisfaction.

[0278] This invention is a system that utilizes generative AI and an emotion engine to streamline the creation of application forms for new non-communication services and propose optimal dates based on the user's emotions. This system aims to not only support the accurate and speedy creation of application forms by allowing the user to input specific date information and proposing the earliest and latest dates, but also to improve user satisfaction.

[0279] System configuration

[0280] 1. User Interface (Terminal)

[0281] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[0282] It is equipped with an emotion engine that analyzes the user's voice and facial expression data to recognize the user's emotions.

[0283] 2. Data receiving module (server)

[0284] This module receives data entered by the user and includes a function to perform initial processing of the data. SSL is used to receive the data, ensuring its security.

[0285] 3. Analysis module (server)

[0286] The server analyzes the received date and emotion information and acquires the corresponding date rule set for the service. For example, the rule set for "Delivery Service" includes the conditions for "Shortest Shipping Date" and "Latest Shipping Date."

[0287] 4. Generative AI module (server)

[0288] Based on the analyzed data, the system calculates the earliest and latest dates based on the corresponding rules and sentiment information. For example, for a desired delivery date, "November 3, 2023" is calculated as the earliest date and "November 15, 2023" as the latest date.

[0289] 5. Integrity Verification Module (Server)

[0290] This includes a function to verify the consistency of the results output by the generative AI, checking whether the calculated earliest and latest dates match pre-set conditions.

[0291] 6. Result presentation module (terminal)

[0292] Includes a function to present the results of the earliest and latest dates for which consistency was confirmed to the user.

[0293] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine. For example, if the user is feeling stressed, it will display relaxing music or an encouraging message.

[0294] 7. Emotion engine module (terminal and server)

[0295] It includes the ability to analyze the user's emotions using voice recognition and facial expression recognition.

[0296] Based on the analysis results, data is provided that influences the analysis module and generative AI module.

[0297] Specific examples

[0298] Suggested delivery date

[0299] User: Enters "November 1, 2023" as the "Desired Delivery Date" and clicks the send button on the device. The emotion engine detects stress from the user's tone of voice and facial expression.

[0300] Device: Sends the entered "November 1, 2023" and emotion data to the server.

[0301] Server: Receives these data and retrieves the date rule set from the database. The emotion engine provides the analysis results and reflects the user's stress state.

[0302] Generative AI (server): Calculates "November 3, 2023" as the earliest date and "November 15, 2023" as the latest date, and at the same time, prioritizes "November 3, 2023" to reduce stress.

[0303] Server: Performs consistency verification and sends the results to the terminal via the result presentation module.

[0304] Device: Shows the suggested delivery date of November 3, 2023, and November 15, 2023, and plays relaxing music and displays an encouraging message.

[0305] Prompt Sentence Examples

[0306] "I'd like delivery on November 1, 2023, what are the earliest and latest dates? Can you please let me know if there is a preferred date to alleviate some of the stress?"

[0307] This system allows users to select date information efficiently and accurately, reducing the workload of sales representatives. The emotion engine adjusts according to the user's emotional state, further improving user satisfaction.

[0308] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0309] Step 1:

[0310] Terminal: The user selects the type of service and enters the required date information (e.g., application date, desired start date of use, desired start date of billing, desired delivery date) into the application form. The emotion engine simultaneously collects the user's voice and facial expressions and analyzes their emotional state. For example, if the user enters "November 1, 2023" as the "desired delivery date," the emotion engine simultaneously detects stress from the user's tone of voice and facial expression. This allows the input information (desired delivery date) and emotional data (stress level) to be collected.

[0311] Step 2:

[0312] Terminal: The input date information and emotion information are packaged and sent to the server via the data receiving module. The input data includes the user-entered "Desired delivery date of November 1, 2023" and the analyzed emotion data (e.g., stress level). The output is the sent data package.

[0313] Step 3:

[0314] Server: The data receiving module receives the date and emotion information and performs an initial analysis. This involves checking the data format and identifying any incomplete information. The received data includes the desired delivery date of November 1, 2023 and the stress level, and the data is output after being confirmed to be consistent.

[0315] Step 4:

[0316] Server: The analysis module retrieves the relevant date rule set from the database based on the service identification information. For example, a rule set for "Delivery Service" includes the conditions "Earliest Shipping Date" and "Latest Shipping Date." The input data are the consistency-checked date information and emotion data, and the output is a date rule set.

[0317] Step 5:

[0318] Server: The emotion engine provides the analysis results (e.g., the user's stress level) to the generative AI module, allowing it to make adjustments based on specific emotional states. For example, if the stress level is high, the generative AI can be configured to prioritize a faster delivery date. The input data is the emotion analysis results, and the output is the adjusted conditions.

[0319] Step 6:

[0320] Server: The generative AI module calculates the earliest and latest dates based on the date rule set and the sentiment analysis results. For example, the calculation results output "November 3, 2023" as the earliest date and "November 15, 2023" as the latest date. The input data are the rule set and the sentiment analysis results, and the output is the calculated earliest and latest dates.

[0321] Step 7:

[0322] Server: The consistency verification module receives the calculation results from the generative AI and checks whether the calculated date matches the pre-defined conditions. For example, it checks whether "November 3, 2023" and "November 15, 2023" are within the service availability period. The input data are the earliest and latest dates, and the output is the verified date.

[0323] Step 8:

[0324] Server: The result presentation module sends the results of the earliest and latest dates that have been verified to the user interface. The input data is the validated date, and the output is the date data for presentation.

[0325] Step 9:

[0326] Terminal: The user interface displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" and plays relaxing music and encouraging messages based on the analysis results of the emotion engine. The input data is the date data to be presented and the emotion analysis results, and the output is the displayed content.

[0327] In this way, the user can accurately and quickly select date information and receive feedback according to their emotional state.

[0328] (Application example 2)

[0329] 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."

[0330] Conventional systems can suggest optimal dates based on the date information entered by the user, but they often result in low user satisfaction because the suggestions do not take into account the user's emotional state. Furthermore, while there is a need for systems to make more appropriate suggestions to users by utilizing emotional information obtained from facial expressions and voice, there is currently a lack of a mechanism to achieve this.

[0331] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing predetermined date information and emotions of the user, means for receiving the input date information and emotion data, means for analyzing the received date information and emotion data and referencing the rules of the relevant service based on generative AI, means for calculating the earliest date and latest date based on the relevant rules and adjusting the proposal content based on the emotion, means for verifying the consistency of the calculation results, and means for presenting the calculation results whose consistency has been confirmed and the adjusted proposal content to the user. This enables optimal date suggestions and feedback according to the user's emotional state, thereby increasing user satisfaction.

[0332] The "means for analyzing the user's specified date information and emotions" refers to a device or software that analyzes the user's emotional state using voice recognition and facial expression recognition in addition to the date information entered by the user.

[0333] The "means for receiving input date information and emotion data" refers to a device or software for receiving date information and emotion data sent from the user and transferring them to the server.

[0334] "Means for analyzing received date information and emotion data and referencing the rules of the relevant service based on generative AI" refers to devices or software that analyzes the date information and user emotion data received by the server and uses generative AI to refer to the service rules based on that information.

[0335] "Means for calculating the earliest and latest dates based on the relevant rules and adjusting the content of the proposal based on emotions" refers to devices or software that allow the generative AI to adjust the content of the proposal based on the earliest and latest dates calculated in accordance with the service rules, taking into account the user's emotional state.

[0336] "Means for verifying the consistency of calculation results" refers to devices or software for verifying whether the earliest and latest dates calculated by generative AI match pre-set conditions and rules.

[0337] "Means for presenting to the user the calculation results whose consistency has been confirmed and the adjusted proposal content" refers to a device or software for visually or audibly presenting to the user the calculation results whose consistency has been confirmed and the proposal content that has been adjusted based on the user's emotional state.

[0338] "Means for analyzing emotions" refers to devices or software for analyzing a user's emotional state using technologies such as voice recognition and facial expression recognition.

[0339] "Date information" is information relating to a specific date entered by the user, such as the application date, desired start date of use, desired start date of billing, activation date, or desired delivery date.

[0340] The system for implementing the present invention provides a terminal for users to input specified date information and emotions, a server that analyzes the received data, calculates the earliest and latest dates using generative AI, and adjusts the suggestions based on the user's emotions, and a function that verifies the consistency of these calculation results before presenting them to the user.

[0341] System configuration

[0342] 1. User Interface (Terminal):

[0343] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[0344] It includes a function that uses an emotion engine to recognize the user's emotions and adjust the interface display and suggestions based on those emotions.

[0345] 2. Data receiving module (server):

[0346] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[0347] 3. Analysis module (server):

[0348] The server analyzes the received date information and emotion data, and includes a function to obtain the date rule set for the corresponding service.

[0349] 4. Generative AI module (server):

[0350] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[0351] 5. Integrity Verification Module (Server):

[0352] Includes a function to verify the consistency of the results output by generative AI.

[0353] 6. Result presentation module (terminal):

[0354] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[0355] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine.

[0356] Program processing

[0357] Input acceptance and emotion recognition

[0358] Terminal: The user selects the desired service and enters date information through a designated interface. At the same time, the emotion engine analyzes voice or facial expression data to recognize the user's emotions.

[0359] Data reception and analysis

[0360] Terminal: Sends input information and emotion data to the server.

[0361] Server: Analyzes the service ID and date information based on the received data. Emotion data is also included in the analysis.

[0362] Calculating the earliest and latest dates

[0363] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[0364] Generative AI: Calculates the earliest and latest dates based on applicable rules.

[0365] Consistency verification and presentation of results

[0366] Server: The calculation result is verified by the integrity verification module.

[0367] Device: Receives the results of the earliest and latest dates sent from the server and adjusts the display content based on the sentiment.

[0368] Hardware and software used

[0369] Smartphone: A device that installs applications and accepts user input.

[0370] Emotion Recognition Library:

[0371] Software that analyzes emotions using voice and facial recognition (e.g., Emotion Recognition Library).

[0372] Generative AI libraries:

[0373] Software that calculates dates based on service identifiers and date rules (e.g., AI Date Generator Library).

[0374] Flask: A framework used to implement server-side applications and provide APIs.

[0375] Specific examples

[0376] As a concrete example, in the case of an "e-commerce website date selection assistant app," if a user inputs "November 1, 2023" as the desired delivery date, the emotion engine recognizes from the voice that the user is feeling stressed. The server analyzes the received data, and the generative AI calculates the earliest and latest delivery dates based on the service rules. For example, the earliest delivery date is calculated as "November 3, 2023," and the latest delivery date as "November 15, 2023." At the same time, the system suggests prioritizing the faster delivery date based on the emotion data to reduce stress. The user interface also plays relaxing music and displays encouraging messages.

[0377] Prompt Sentence Examples

[0378] Specific examples of prompt sentences are shown below.

[0379] "SERVICE_TYPE: Delivery Service PREFERRED_DATE: 2023-11-01 USER_EMOTION: Stress level 80, Happiness level 20"

[0380] By feeding this prompt into a generative AI model, the results are tailored date suggestions based on emotional data.

[0381] The above is an embodiment of the present invention. The present invention makes it possible to provide optimal date suggestions and feedback according to the emotional state of the user, and is expected to have the effect of increasing user satisfaction.

[0382] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0383] Step 1:

[0384] Input reception

[0385] User: The user selects the desired service and enters date information via a specified interface. For example, the user enters "November 1, 2023" as the "desired delivery date."

[0386] Input data: Date information (e.g., "November 1, 2023"), user voice data, and user facial expression image data.

[0387] Output data: The date information entered by the user and the collected emotion data are saved on the device.

[0388] Step 2:

[0389] emotion recognition

[0390] Device: The emotion engine analyzes voice data and facial expression image data to recognize the user's emotions.

[0391] Input data: User's voice data, user's facial expression image data.

[0392] Specific operation: Using a voice recognition library and an facial expression recognition library, the system quantifies emotional states (e.g., stress level, happiness) from changes in voice tone and facial expressions.

[0393] Output data: Emotion data (e.g. stress level 80, happiness level 20) is generated.

[0394] Step 3:

[0395] Data reception

[0396] Terminal: Sends the entered date information and emotion data to the server.

[0397] Input data: User-entered date information and parsed emotion data.

[0398] Specific operation: Sends input data to a server via the Internet using an HTTP POST request.

[0399] Output data: The server receives the date information and emotion data.

[0400] Step 4:

[0401] Data analysis

[0402] Server: Based on the received data, analyzes the service ID and date information. Emotion data is also included in the analysis.

[0403] Input data: date information, emotion data.

[0404] Specific operation: The rule set for the relevant service is retrieved from the database, and the date information and emotion data are processed using the analysis engine.

[0405] Output data: Parsed service ID, analysis result date, and emotion data.

[0406] Step 5:

[0407] Date arithmetic

[0408] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[0409] Input data: service identification information, analysis result date information, emotion data.

[0410] What it does: Uses a generative AI model to calculate the earliest and latest delivery dates based on a set of rules. Optimizes recommendations based on sentiment data.

[0411] Output data: Calculated earliest and latest dates, adjusted proposal.

[0412] Step 6:

[0413] Integrity Verification

[0414] Server: The calculation result is verified by the integrity verification module, for example, to ensure that the calculated date is within the range of the service.

[0415] Input data: The calculated earliest and latest dates.

[0416] Specific behavior: Checks whether the calculated date is valid according to the service provision rules.

[0417] Output data: Calculation results with consistency checked.

[0418] Step 7:

[0419] Results presentation

[0420] Device: Receives the results of the earliest and latest dates sent from the server and adjusts the display content based on the user's emotions. For example, displaying relaxing music or encouraging messages to a user who is feeling stressed.

[0421] Input data: Consistent calculations and adjusted proposals.

[0422] Specific behavior: The calculation results are displayed in the user interface and feedback is provided according to the emotional data.

[0423] Output: The suggestions presented to the user visually or audibly.

[0424] The above are the specific processing steps for implementing the present invention. This enables optimal date suggestions and feedback based on the user's emotional state, which is expected to increase user satisfaction.

[0425] 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.

[0426] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0427] 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.

[0428] [Second embodiment]

[0429] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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).

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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."

[0441] This invention relates to a system that utilizes generative AI to propose optimal dates to streamline application forms for new non-telecommunications services. The system supports accurate and prompt application form creation by suggesting the earliest and latest dates when the user inputs specified date information.

[0442] System configuration

[0443] 1. User Interface (Terminal)

[0444] This includes a function that provides a form for the user to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, or desired delivery date).

[0445] 2. Data receiving module (server)

[0446] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[0447] 3. Analysis module (server)

[0448] The server includes a function to analyze the received date information and obtain the date rule set for the corresponding service.

[0449] 4. Generative AI module (server)

[0450] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[0451] 5. Integrity Verification Module (Server)

[0452] Includes a function to verify the consistency of the results output by generative AI.

[0453] 6. Result presentation module (terminal)

[0454] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[0455] Program processing flow

[0456] Input reception

[0457] Terminal: The user selects the desired service and enters date information through a specified interface. For example, the user enters "November 1, 2023" as the "desired delivery date."

[0458] Data reception and analysis

[0459] Terminal: Sends the entered information to the server.

[0460] Server: Analyzes the service identification information and date information based on the received data.

[0461] Calculating the earliest and latest dates

[0462] Server: Obtains a rule set corresponding to the service identification information based on generative AI.

[0463] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the applicable rules. For example, it calculates that the earliest delivery date is "November 3, 2023" and the latest delivery date is "November 15, 2023."

[0464] Consistency verification and presentation of results

[0465] Server: The calculation result is verified by the consistency verification module. For example, it checks whether the shortest delivery date falls on a holiday.

[0466] Terminal: Receives the results of the earliest and latest dates sent from the server and displays them on the user interface.

[0467] Specific examples

[0468] Suggested delivery date

[0469] User: Enters "November 1, 2023" as the "Desired delivery date" and clicks the send button on the device.

[0470] Server: Receives the information "November 1, 2023" and "desired delivery date" and instructs the generative AI to refer to the relevant rule based on the service identification.

[0471] Generative AI (on the server): Calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023."

[0472] Server: After verifying the integrity, it sends the calculation result to the terminal.

[0473] Terminal: Display "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" in the user interface.

[0474] The system of the present invention allows users to select dates efficiently and accurately, reducing the workload of sales representatives. Additionally, automated date suggestions reduce human error in application completion and minimize the risk of service delays.

[0475] The processing flow will be explained below.

[0476] Step 1:

[0477] User: Select the desired service via the designated interface and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date). For example, enter "November 1, 2023" as the "desired delivery date."

[0478] Step 2:

[0479] Terminal: The service information and date information entered by the user are sent to the server via an HTTP POST request.

[0480] Step 3:

[0481] Server: Analyzes the received request and extracts the service ID and date information. For example, the service ID is "A", the date is "November 1, 2023", and the date type is "Desired delivery date".

[0482] Step 4:

[0483] Server: Based on the extracted service identification information, the server sends the corresponding date rule set to the generative AI, which then retrieves the corresponding rules from its internal database.

[0484] Step 5:

[0485] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the acquired rule set. For example, it calculates that the earliest delivery date is "November 3, 2023" and the latest delivery date is "November 15, 2023."

[0486] Step 6:

[0487] Server: Receives the calculation results of the earliest and latest dates returned by the generative AI and verifies the consistency of the results. For example, it checks whether the earliest date is the date on which the specified service can be provided.

[0488] Step 7:

[0489] Server: Converts the calculation results whose integrity has been confirmed into JSON format and sends them to the user's device.

[0490] Step 8:

[0491] Terminal: Receives and analyzes the JSON data sent from the server. As a result, the following is displayed on the user interface: "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0492] The above is a concrete processing flow of the entire system. The operations performed at each step from receiving input from the user to presenting the final date proposal have been explained in detail.

[0493] Example 1

[0494] 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."

[0495] Conventional application creation systems have the problem that it takes time and effort for users to select an appropriate date, making it difficult to select an accurate date. In addition, human error is likely to occur in selecting the date, which can lead to reduced efficiency and risk of delays in service provision.

[0496] 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.

[0497] In this invention, the server includes means for a user to input predetermined information, means for receiving the input information, means for analyzing the received information and referencing the rules of the relevant service based on generative artificial intelligence, means for calculating the earliest date and latest date based on the rules, means for verifying the consistency of the calculation results, and means for presenting the calculation results whose consistency has been confirmed to the user. This allows the user to select dates efficiently and accurately, speeding up the application form creation process, reducing human error, and minimizing the risk of delays in service provision.

[0498] "User" means any person or entity that uses the System to input information and receive results.

[0499] "Specified information" refers to specific data that the user must input into the system, including the application date, desired start date, activation date, desired date, etc.

[0500] "Means" refers to a method, device, or function by which a system realizes a specific function or role.

[0501] The "means for inputting information" refers to an interface or device that allows a user to input predetermined information into the system.

[0502] "Means for receiving information" refers to the method or function by which the system receives information input by the user.

[0503] "Means for analyzing received information" refers to the methods and algorithms that the system uses to understand the information it receives and process it appropriately.

[0504] "Service Rules" means the business rules and conditions associated with a particular Service.

[0505] "Generative AI" refers to artificial intelligence techniques used to perform specific tasks or calculations within a system.

[0506] "Means for referencing relevant rules" refers to the methods or functions that enable a generative artificial intelligence to obtain and use rules related to a specific service.

[0507] "Means for calculating the earliest and latest dates" refers to methods or functions that allow generative artificial intelligence to calculate optimal dates according to rules.

[0508] "Means for verifying the consistency of calculation results" refers to methods or functions that confirm whether the date results calculated by the generative artificial intelligence match the specified conditions.

[0509] The "means for presenting the calculation result whose consistency has been confirmed" is a method or function for displaying the optimal date result to the user after the validation has been performed.

[0510] The present invention relates to a system that utilizes generative AI to propose optimal dates to streamline the creation of application forms for new non-communication services. This system supports accurate and rapid creation of application forms by suggesting the earliest and latest dates based on the user's input of specified information. A specific embodiment of the present invention will be described below.

[0511] User Interface (Terminal)

[0512] The user uses the device's user interface to select a service and enter required information (such as date information). The user interface can take the form of, for example, a web form or a mobile app. Input fields include "application date," "desired start date," "desired billing start date," "activation date," and "desired delivery date."

[0513] Data receiving module (server)

[0514] The terminal sends the information entered by the user to the server. This data is sent to the server via a protocol such as an HTTP request. The server checks whether the received data is in the correct format and performs validation.

[0515] Analysis module (server)

[0516] The server analyzes the information received through the data reception module. Specifically, the server identifies the service based on the received data and determines the rules for the corresponding service. The analyzed data is passed to the generative AI module.

[0517] Generative AI module (server)

[0518] The generative AI module calculates the earliest and latest delivery dates based on the analyzed data and applicable service rules. This calculation uses an internal algorithm and rule set. For example, the "earliest delivery date" is calculated as "November 3, 2023" and the "latest delivery date" is calculated as "November 15, 2023."

[0519] Integrity verification module (server)

[0520] The results output by the generative AI module are passed to the consistency verification module, which checks whether the calculation results meet pre-set conditions, such as whether the calculated date falls on a holiday or is an unreasonable date.

[0521] Result presentation module (terminal)

[0522] Once the verification is complete, the server sends the results of the earliest and latest delivery dates to the terminal. The terminal displays the received data on the user interface and presents the results to the user. For example, it displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0523] Specific examples

[0524] For example, if a user enters "November 1, 2023" as the "desired delivery date" and clicks the send button on the device, the server receives the information "November 1, 2023" and the "desired delivery date." The server then references the rule set based on generative AI and calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023." Finally, if the calculation results pass consistency verification, the device displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0525] The system allows users to select dates efficiently and accurately, reducing the workload of sales representatives. Automated date suggestions also reduce human error in application completion, minimizing the risk of service delays.

[0526] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0527] Step 1:

[0528] The user inputs the specified information into the terminal. The user inputs the specified information, including the service selection and date information. For example, the user inputs "November 1, 2023" as the "desired delivery date." Once the input is complete, the user clicks the send button. The input data includes the application date, desired start date of use, desired start date of billing, activation date, desired delivery date, etc.

[0529] Step 2:

[0530] The terminal sends the entered information to the server. The information entered by the user is packaged in an appropriate format (for example, JSON format) and sent to the server via an HTTP request. The input data is sent in a format such as "Delivery request date: November 1, 2023".

[0531] Step 3:

[0532] The server receives and analyzes the input information. The server checks the received data and validates that it is in the appropriate format. If the received data is in the correct format, it analyzes the data and extracts the service identification and date information. For example, it analyzes the "desired delivery date" information and obtains the service identification information.

[0533] Step 4:

[0534] The server instructs the generative AI to retrieve the rule set. Based on the analyzed information, the server instructs the generative AI to refer to the rule set for the relevant service. For example, it retrieves the rule set related to delivery services. This rule set includes business rules and date calculation conditions.

[0535] Step 5:

[0536] The generative AI calculates the earliest and latest dates. The generative AI calculates the earliest and latest dates based on the received rule set and input information. For example, if the "desired delivery date" is "November 1, 2023," the earliest delivery date is calculated to be "November 3, 2023," and the latest delivery date is calculated to be "November 15, 2023." Calendar information and holiday information are taken into account in the calculation.

[0537] Step 6:

[0538] The server verifies the consistency of the calculation results. The server passes the date output by the generative AI to the consistency verification module. The consistency verification module checks whether the earliest and latest dates match the set conditions. For example, it checks whether the earliest date is a holiday or an unreasonable date.

[0539] Step 7:

[0540] The terminal receives and displays the results of the integrity check. The server sends the earliest and latest verification completion dates to the terminal. The terminal displays the results on the user interface. For example, "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" is displayed, visually presenting the results to the user.

[0541] (Application example 1)

[0542] 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."

[0543] In conventional application form creation systems for non-communication services, users manually select their desired date, which makes operation complicated and can lead to input errors and delays in application creation. Furthermore, particularly in food delivery, there are no systems that automatically calculate optimal departure and arrival times for the customer's desired delivery time, reducing delivery efficiency. The present invention aims to solve these problems and provide a system that efficiently and accurately selects dates and suggests delivery times.

[0544] 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.

[0545] In this invention, the server includes: a means for a user to input specified date information; a means for receiving the input date information; a means for analyzing the received date information and referencing the rules of the relevant service using a generative AI; a means for calculating the earliest date and latest date based on the rules; a means for adjusting and verifying the calculation result; a means for presenting the adjusted and confirmed calculation result to the user; and a means for a user to input a desired delivery time, calculate optimal departure and arrival times using the generative AI, and notify the restaurant operator and delivery person. This allows the user to efficiently and accurately select a date, and in the case of food delivery in particular, it is possible to automatically calculate optimal departure and arrival times for the customer's desired delivery time and promptly notify the restaurant operator and delivery person.

[0546] "Specified date information" is information including the specific date and time when the user wishes to use the service.

[0547] The "means for inputting" is a user interface that allows a user to input predetermined date information into the system.

[0548] The "receiving means" is a function that allows the server to receive date information entered by the user.

[0549] The "analysis means" is a function for analyzing received date information and extracting the rules for the corresponding service.

[0550] "Generative AI" is a technology that uses artificial intelligence to generate optimal dates and times based on specific rules.

[0551] The "earliest date" is the earliest date on which the service desired by the user can be provided.

[0552] The "latest date" is the latest date on which the service desired by the user can be provided.

[0553] "Means for calculating" means a function for calculating the earliest and latest dates based on applicable rules.

[0554] The "means for adjusting and verifying" is a function for checking whether the generated shortest date and latest date match the conditions set in advance.

[0555] The "means for presenting" is a function for notifying the user of the calculation results for which the adjustment has been confirmed.

[0556] "Desired delivery time" is information specifying the delivery date and time of a product or service that the user particularly desires.

[0557] "Departure time" is the time when the delivery person starts delivering the goods or services from the restaurant or warehouse.

[0558] "Arrival time" is the time when the product or service will arrive at the delivery destination specified by the user.

[0559] "Food service operators" refers to stores and companies that provide food delivery services.

[0560] A "delivery person" is a person or company responsible for delivering products or services to a customer on the date and time requested.

[0561] MODE FOR CARRYING OUT THE INVENTION

[0562] This invention relates to a food delivery system that automatically calculates optimal departure and arrival times based on the desired delivery time specified by the user. This system receives the desired delivery time entered by the user, uses generative AI to propose the optimal time, and notifies the restaurant operator and delivery staff, thereby achieving efficient delivery.

[0563] System configuration

[0564] User Interface (Terminal)

[0565] This is an interface that provides a form for the user to enter the desired delivery time. Taking a smartphone application as an example, the user specifies the desired delivery time as "December 1, 2023, 18:00."

[0566] Data receiving module (server)

[0567] This module receives the desired delivery time sent from the terminal. This module performs initial processing to analyze the user's input data on the server.

[0568] Analysis module (server)

[0569] It includes a function to analyze the requested delivery time received and obtain the rules for the corresponding service. Based on the results of this analysis, it prepares the data necessary for generative AI.

[0570] Generative AI module (server)

[0571] Based on the analyzed data, the module calculates the optimal departure and arrival times for the desired delivery time. This calculation is performed using AI models such as TensorFlow.

[0572] Adjustment verification module (server)

[0573] Validate that the calculated departure and arrival times meet predefined criteria, such as whether the optimal departure time is within the restaurant's opening hours and whether the arrival time matches the customer's preferred time slot.

[0574] Result presentation module (terminal)

[0575] The system notifies users, food service providers, and delivery personnel of the optimal departure and arrival times, providing accurate information to all parties via a smartphone app.

[0576] Hardware and software used

[0577] Hardware: Cloud servers such as Amazon EC2

[0578] Software: TensorFlow (generative AI model), custom validator (adjustment verification tool), smartphone application

[0579] Data calculation: Analyze received data and calculate optimal time using AI model, and verify adjustments

[0580] Specific usage scenarios and prompt examples

[0581] Usage scenarios

[0582] The user enters into the app a request for delivery at "December 1, 2023, 18:00." The server receives and analyzes the data. Generative AI is used to calculate the optimal departure and arrival times, and adjustments and verification are performed. As a result, the optimal departure time is calculated to be "December 1, 2023, 17:00" and the optimal arrival time is calculated to be "December 1, 2023, 18:00." These results are notified to the restaurant operator and delivery staff.

[0583] Prompt Sentence Examples

[0584] Desired delivery time: 2023-12-01 18:00

[0585] Generated departure time: 2023-12-01 17:00

[0586] Generated arrival time: 2023-12-01 18:00

[0587] The system will significantly improve the efficiency of food delivery and increase customer satisfaction by providing accurate delivery times.

[0588] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0589] Step 1:

[0590] The user enters the desired delivery time

[0591] The user inputs the desired delivery time through the smartphone app interface. For example, they might input "December 1, 2023, 6:00 PM." This input information is sent to the system as the first data.

[0592] Step 2:

[0593] Receiving data

[0594] The server receives the requested delivery time entered from the terminal. The received data is temporarily stored on the server for use in the next analysis step. Specifically, the data entered by the user as "December 1, 2023, 18:00" is received.

[0595] Step 3:

[0596] Data analysis

[0597] The server analyzes the received desired delivery time. From this analysis, it extracts information about the user's desired delivery time and prepares to obtain the relevant delivery rules. For example, it analyzes "December 1, 2023, 18:00" and takes into account the restaurant's business hours and the delivery staff's working hours.

[0598] Step 4:

[0599] Calculating optimal time using generative AI

[0600] The generative AI model on the server calculates the optimal departure and arrival times based on the analyzed data. Specifically, using TensorFlow, for "December 1, 2023, 18:00," the optimal departure time is calculated as "December 1, 2023, 17:00" and the optimal arrival time is calculated as "December 1, 2023, 18:00."

[0601] Step 5:

[0602] Adjustment and verification of calculation results

[0603] The server verifies the calculation results using the adjustment verification module. For example, it checks whether the optimal departure time is within the restaurant's business hours, and whether the arrival time matches the time slot specified by the customer. Specifically, it checks whether "December 1, 2023, 5:00 PM" is within the restaurant's business hours, and whether "December 1, 2023, 6:00 PM" is within the time slot specified by the customer.

[0604] Step 6:

[0605] Presentation of results

[0606] The verified optimal departure and arrival times are sent to the terminal and notified to the user, the restaurant operator, and the delivery person. The information "Departure time: December 1, 2023, 5:00 PM, Arrival time: December 1, 2023, 6:00 PM" is displayed to all parties via the smartphone app interface.

[0607] 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.

[0608] This invention relates to a system that utilizes generative AI and an emotion engine to propose optimal dates and adjust the interface display and proposal content based on the user's emotions in order to streamline the creation of application forms for new non-telecommunications services. This system supports the accurate and speedy creation of application forms by allowing the user to input specific date information and proposing the earliest and latest dates, thereby improving user satisfaction.

[0609] System configuration

[0610] 1. User Interface (Terminal)

[0611] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[0612] It includes a function that uses an emotion engine to recognize the user's emotions and adjust the interface display and suggestions based on those emotions.

[0613] 2. Data receiving module (server)

[0614] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[0615] 3. Analysis module (server)

[0616] The server includes a function to analyze the received date information and obtain the date rule set for the corresponding service.

[0617] 4. Generative AI module (server)

[0618] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[0619] 5. Integrity Verification Module (Server)

[0620] Includes a function to verify the consistency of the results output by generative AI.

[0621] 6. Result presentation module (terminal)

[0622] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[0623] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine.

[0624] 7. Emotion engine module (terminal and server)

[0625] It includes the ability to analyze the user's emotions using voice recognition and facial expression recognition.

[0626] It includes a function to provide data that influences the analysis module and generative AI module based on the analysis results.

[0627] Program processing flow

[0628] Input acceptance and emotion recognition

[0629] Terminal: The user selects the desired service and enters date information via a specified interface. At the same time, the emotion engine analyzes voice or facial expression data to recognize the user's emotions. For example, while entering "November 1, 2023" as the "desired delivery date," the emotion engine recognizes from the user's tone of voice and facial expression that they are feeling stressed.

[0630] Data reception and analysis

[0631] Terminal: Sends input information and emotion data to the server.

[0632] Server: Based on the received data, analyzes the service ID and date information. Emotion data is also included in the analysis.

[0633] Calculating the earliest and latest dates

[0634] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[0635] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the relevant rules. For example, the earliest delivery date is calculated as "November 3, 2023" and the latest delivery date is calculated as "November 15, 2023." At the same time, if the user is stressed, the earlier delivery date will be prioritized.

[0636] Consistency verification and presentation of results

[0637] Server: The calculation result is verified by the consistency verification module. For example, it is verified whether the shortest date is within the date on which the specified service can be provided.

[0638] Device: Receives the results of the earliest and latest delivery dates sent from the server and adjusts the display content based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the device will suggest "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023," as well as play relaxing music and display encouraging messages.

[0639] Specific examples

[0640] Suggested delivery date

[0641] User: Enters "November 1, 2023" as the "Desired Delivery Date" and clicks the send button on the device. The emotion engine detects stress from the user's voice.

[0642] Server: Receives the information "November 1, 2023" and "desired delivery date" along with emotion data, and instructs the generative AI to refer to the relevant rules based on the service identification.

[0643] Generative AI (on the server): Calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023." At the same time, prioritizes and suggests shorter delivery dates based on emotional data to reduce stress.

[0644] Server: After verifying the integrity, it sends the calculation results and emotion-based adjustment results to the device.

[0645] Device: Display "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" on the user interface while playing relaxing music or displaying a light, encouraging message.

[0646] The system of the present invention allows users to select dates efficiently and accurately, reducing the workload of sales representatives, and further improves user satisfaction by adjusting the system based on the user's emotional state using the emotion engine.

[0647] The processing flow will be explained below.

[0648] Step 1:

[0649] User: Selects the desired service through a designated interface and enters date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date). For example, enter "November 1, 2023" as the "desired delivery date." At the same time, the emotion engine analyzes the user's facial expressions and voice to recognize their emotions.

[0650] Step 2:

[0651] The device sends the date information and emotion data entered by the user to the server. Specifically, it sends a request including the user's selected date (November 1, 2023) and desired delivery date, as well as emotion data.

[0652] Step 3:

[0653] Server: Analyzes the received request and extracts the service ID and date information. If emotion data is included, it is also included in the analysis. For example, the service ID is "A," the date information is "November 1, 2023," the date type is "Desired delivery date," and the emotion data is "Stress."

[0654] Step 4:

[0655] Server: Based on the extracted service identification information, the corresponding date rule set is sent to the generative AI. The generative AI retrieves the corresponding rules from its internal database. The application of the rules is also adjusted based on the emotion data.

[0656] Step 5:

[0657] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the acquired rule set. For example, the earliest delivery date is calculated as "November 3, 2023" and the latest delivery date is calculated as "November 15, 2023." At the same time, the earliest delivery date is given a higher priority based on emotion data.

[0658] Step 6:

[0659] Server: Receives the calculation results of the earliest and latest dates returned by the generative AI and verifies the consistency of the results. For example, it checks whether the earliest date is actually a date on which the service can be provided.

[0660] Step 7:

[0661] Server: The server sends the calculation results, whose integrity has been confirmed, in JSON format to the device, along with messages and influence factors based on the emotion data.

[0662] Step 8:

[0663] Terminal: Receives and analyzes the JSON data sent from the server. As a result of the analysis, the user interface displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023." Furthermore, if the user is feeling stressed, the device plays relaxing music and displays an encouraging message in a pop-up.

[0664] This is the specific processing flow of the entire system. By linking with the emotion engine, it can respond to the user's emotional state and provide a better user experience.

[0665] Example 2

[0666] 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."

[0667] Conventional application form creation systems make it difficult for users to accurately select date information and do not take the user's emotional state into consideration, which can sometimes compromise the user experience. As a result, the application process becomes cumbersome, resulting in problems of reduced user satisfaction. Furthermore, there are also problems with increased workloads for sales representatives and reduced work efficiency. To solve these issues, a system is needed that allows users to easily and quickly enter accurate date information and can adjust according to the user's emotional state.

[0668] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0669] In this invention, the server includes means for a user to input predetermined date information, means for receiving the input date information and user emotion information, means for analyzing the received date information and emotion information and referencing the rules of the relevant service, means for calculating the earliest date and latest date based on the relevant rules and emotion information, means for verifying the consistency of the calculation results, means for presenting the calculation results whose consistency has been confirmed to the user, and means for adjusting the display content of the interface in accordance with the user's emotional state. This allows the user to accurately and quickly select date information, and adjustments are made based on the user's emotional state, thereby improving user satisfaction and reducing the burden on sales representatives, thereby improving work efficiency.

[0670] "Date information" is information about specific dates such as the application date, desired start date of use, desired start date of billing, activation date, and desired delivery date that the user enters when filling out an application form for a service.

[0671] "Emotion information" is information about the user's emotional state that is analyzed by the emotion engine from the user's voice, facial expressions, and the like.

[0672] The "receiving means" refers to a hardware and software configuration for transmitting date information and emotion information input by the user to the server and receiving the information.

[0673] The "analysis means" refers to a hardware and software configuration for analyzing the received date information and emotion information and referencing the rules of the corresponding service based on the analysis.

[0674] "Generative AI" is an artificial intelligence model that calculates the earliest and latest dates based on received data according to specific rules.

[0675] A "means for calculating" is a hardware and software configuration for calculating the earliest and latest dates based on applicable rules and sentiment information.

[0676] The "means for verifying consistency" is a hardware and software configuration for checking whether the generated earliest and latest dates match pre-set conditions.

[0677] The "presentation means" refers to a hardware and software configuration for displaying the results of the earliest and latest dates for which consistency has been confirmed on a user interface and providing feedback to the user.

[0678] The "adjusting means" refers to a hardware and software configuration that adjusts the interface display content according to the user's emotional state, thereby improving user satisfaction.

[0679] This invention is a system that utilizes generative AI and an emotion engine to streamline the creation of application forms for new non-communication services and propose optimal dates based on the user's emotions. This system aims to not only support the accurate and speedy creation of application forms by allowing the user to input specific date information and proposing the earliest and latest dates, but also to improve user satisfaction.

[0680] System configuration

[0681] 1. User Interface (Terminal)

[0682] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[0683] It is equipped with an emotion engine that analyzes the user's voice and facial expression data to recognize the user's emotions.

[0684] 2. Data receiving module (server)

[0685] This module receives data entered by the user and includes a function to perform initial processing of the data. SSL is used to receive the data, ensuring its security.

[0686] 3. Analysis module (server)

[0687] The server analyzes the received date and emotion information and acquires the corresponding date rule set for the service. For example, the rule set for "Delivery Service" includes the conditions for "Shortest Shipping Date" and "Latest Shipping Date."

[0688] 4. Generative AI module (server)

[0689] Based on the analyzed data, the system calculates the earliest and latest dates based on the corresponding rules and sentiment information. For example, for a desired delivery date, "November 3, 2023" is calculated as the earliest date and "November 15, 2023" as the latest date.

[0690] 5. Integrity Verification Module (Server)

[0691] This includes a function to verify the consistency of the results output by the generative AI, checking whether the calculated earliest and latest dates match pre-set conditions.

[0692] 6. Result presentation module (terminal)

[0693] Includes a function to present the results of the earliest and latest dates for which consistency was confirmed to the user.

[0694] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine. For example, if the user is feeling stressed, it will display relaxing music or an encouraging message.

[0695] 7. Emotion engine module (terminal and server)

[0696] It includes the ability to analyze the user's emotions using voice recognition and facial expression recognition.

[0697] Based on the analysis results, data is provided that influences the analysis module and generative AI module.

[0698] Specific examples

[0699] Suggested delivery date

[0700] User: Enters "November 1, 2023" as the "Desired Delivery Date" and clicks the send button on the device. The emotion engine detects stress from the user's tone of voice and facial expression.

[0701] Device: Sends the entered "November 1, 2023" and emotion data to the server.

[0702] Server: Receives these data and retrieves the date rule set from the database. The emotion engine provides the analysis results and reflects the user's stress state.

[0703] Generative AI (server): Calculates "November 3, 2023" as the earliest date and "November 15, 2023" as the latest date, and at the same time, prioritizes "November 3, 2023" to reduce stress.

[0704] Server: Performs consistency verification and sends the results to the terminal via the result presentation module.

[0705] Device: Shows the suggested delivery date of November 3, 2023, and November 15, 2023, and plays relaxing music and displays an encouraging message.

[0706] Prompt Sentence Examples

[0707] "I'd like delivery on November 1, 2023, what are the earliest and latest dates? Can you please let me know if there is a preferred date to alleviate some of the stress?"

[0708] This system allows users to select date information efficiently and accurately, reducing the workload of sales representatives. The emotion engine adjusts according to the user's emotional state, further improving user satisfaction.

[0709] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0710] Step 1:

[0711] Terminal: The user selects the type of service and enters the required date information (e.g., application date, desired start date of use, desired start date of billing, desired delivery date) into the application form. The emotion engine simultaneously collects the user's voice and facial expressions and analyzes their emotional state. For example, if the user enters "November 1, 2023" as the "desired delivery date," the emotion engine simultaneously detects stress from the user's tone of voice and facial expression. This allows the input information (desired delivery date) and emotional data (stress level) to be collected.

[0712] Step 2:

[0713] Terminal: The input date information and emotion information are packaged and sent to the server via the data receiving module. The input data includes the user-entered "Desired delivery date of November 1, 2023" and the analyzed emotion data (e.g., stress level). The output is the sent data package.

[0714] Step 3:

[0715] Server: The data receiving module receives the date and emotion information and performs an initial analysis. This involves checking the data format and identifying any incomplete information. The received data includes the desired delivery date of November 1, 2023 and the stress level, and the data is output after being confirmed to be consistent.

[0716] Step 4:

[0717] Server: The analysis module retrieves the relevant date rule set from the database based on the service identification information. For example, a rule set for "Delivery Service" includes the conditions "Earliest Shipping Date" and "Latest Shipping Date." The input data are the consistency-checked date information and emotion data, and the output is a date rule set.

[0718] Step 5:

[0719] Server: The emotion engine provides the analysis results (e.g., the user's stress level) to the generative AI module, allowing it to make adjustments based on specific emotional states. For example, if the stress level is high, the generative AI can be configured to prioritize a faster delivery date. The input data is the emotion analysis results, and the output is the adjusted conditions.

[0720] Step 6:

[0721] Server: The generative AI module calculates the earliest and latest dates based on the date rule set and the sentiment analysis results. For example, the calculation results output "November 3, 2023" as the earliest date and "November 15, 2023" as the latest date. The input data are the rule set and the sentiment analysis results, and the output is the calculated earliest and latest dates.

[0722] Step 7:

[0723] Server: The consistency verification module receives the calculation results from the generative AI and checks whether the calculated date matches the pre-defined conditions. For example, it checks whether "November 3, 2023" and "November 15, 2023" are within the service availability period. The input data are the earliest and latest dates, and the output is the verified date.

[0724] Step 8:

[0725] Server: The result presentation module sends the results of the earliest and latest dates that have been verified to the user interface. The input data is the validated date, and the output is the date data for presentation.

[0726] Step 9:

[0727] Terminal: The user interface displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" and plays relaxing music and encouraging messages based on the analysis results of the emotion engine. The input data is the date data to be presented and the emotion analysis results, and the output is the displayed content.

[0728] In this way, the user can accurately and quickly select date information and receive feedback according to their emotional state.

[0729] (Application example 2)

[0730] 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."

[0731] Conventional systems can suggest optimal dates based on the date information entered by the user, but they often result in low user satisfaction because the suggestions do not take into account the user's emotional state. Furthermore, while there is a need for systems to make more appropriate suggestions to users by utilizing emotional information obtained from facial expressions and voice, there is currently a lack of a mechanism to achieve this.

[0732] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing predetermined date information and emotions of the user, means for receiving the input date information and emotion data, means for analyzing the received date information and emotion data and referencing the rules of the relevant service based on generative AI, means for calculating the earliest date and latest date based on the relevant rules and adjusting the proposal content based on the emotion, means for verifying the consistency of the calculation results, and means for presenting the calculation results whose consistency has been confirmed and the adjusted proposal content to the user. This enables optimal date suggestions and feedback according to the user's emotional state, thereby increasing user satisfaction.

[0733] The "means for analyzing the user's specified date information and emotions" refers to a device or software that analyzes the user's emotional state using voice recognition and facial expression recognition in addition to the date information entered by the user.

[0734] The "means for receiving input date information and emotion data" refers to a device or software for receiving date information and emotion data sent from the user and transferring them to the server.

[0735] "Means for analyzing received date information and emotion data and referencing the rules of the relevant service based on generative AI" refers to devices or software that analyzes the date information and user emotion data received by the server and uses generative AI to refer to the service rules based on that information.

[0736] "Means for calculating the earliest and latest dates based on the relevant rules and adjusting the content of the proposal based on emotions" refers to devices or software that allow the generative AI to adjust the content of the proposal based on the earliest and latest dates calculated in accordance with the service rules, taking into account the user's emotional state.

[0737] "Means for verifying the consistency of calculation results" refers to devices or software for verifying whether the earliest and latest dates calculated by generative AI match pre-set conditions and rules.

[0738] "Means for presenting to the user the calculation results whose consistency has been confirmed and the adjusted proposal content" refers to a device or software for visually or audibly presenting to the user the calculation results whose consistency has been confirmed and the proposal content that has been adjusted based on the user's emotional state.

[0739] "Means for analyzing emotions" refers to devices or software for analyzing a user's emotional state using technologies such as voice recognition and facial expression recognition.

[0740] "Date information" is information relating to a specific date entered by the user, such as the application date, desired start date of use, desired start date of billing, activation date, or desired delivery date.

[0741] The system for implementing the present invention provides a terminal for users to input specified date information and emotions, a server that analyzes the received data, calculates the earliest and latest dates using generative AI, and adjusts the suggestions based on the user's emotions, and a function that verifies the consistency of these calculation results before presenting them to the user.

[0742] System configuration

[0743] 1. User Interface (Terminal):

[0744] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[0745] It includes a function that uses an emotion engine to recognize the user's emotions and adjust the interface display and suggestions based on those emotions.

[0746] 2. Data receiving module (server):

[0747] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[0748] 3. Analysis module (server):

[0749] The server analyzes the received date information and emotion data, and includes a function to obtain the date rule set for the corresponding service.

[0750] 4. Generative AI module (server):

[0751] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[0752] 5. Integrity Verification Module (Server):

[0753] Includes a function to verify the consistency of the results output by generative AI.

[0754] 6. Result presentation module (terminal):

[0755] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[0756] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine.

[0757] Program processing

[0758] Input acceptance and emotion recognition

[0759] Terminal: The user selects the desired service and enters date information through a designated interface. At the same time, the emotion engine analyzes voice or facial expression data to recognize the user's emotions.

[0760] Data reception and analysis

[0761] Terminal: Sends input information and emotion data to the server.

[0762] Server: Analyzes the service ID and date information based on the received data. Emotion data is also included in the analysis.

[0763] Calculating the earliest and latest dates

[0764] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[0765] Generative AI: Calculates the earliest and latest dates based on applicable rules.

[0766] Consistency verification and presentation of results

[0767] Server: The calculation result is verified by the integrity verification module.

[0768] Device: Receives the results of the earliest and latest dates sent from the server and adjusts the display content based on the sentiment.

[0769] Hardware and software used

[0770] Smartphone: A device that installs applications and accepts user input.

[0771] Emotion Recognition Library:

[0772] Software that analyzes emotions using voice and facial recognition (e.g., Emotion Recognition Library).

[0773] Generative AI libraries:

[0774] Software that calculates dates based on service identifiers and date rules (e.g., AI Date Generator Library).

[0775] Flask: A framework used to implement server-side applications and provide APIs.

[0776] Specific examples

[0777] As a concrete example, in the case of an "e-commerce website date selection assistant app," if a user inputs "November 1, 2023" as the desired delivery date, the emotion engine recognizes from the voice that the user is feeling stressed. The server analyzes the received data, and the generative AI calculates the earliest and latest delivery dates based on the service rules. For example, the earliest delivery date is calculated as "November 3, 2023," and the latest delivery date as "November 15, 2023." At the same time, the system suggests prioritizing the faster delivery date based on the emotion data to reduce stress. The user interface also plays relaxing music and displays encouraging messages.

[0778] Prompt Sentence Examples

[0779] Specific examples of prompt sentences are shown below.

[0780] "SERVICE_TYPE: Delivery Service PREFERRED_DATE: 2023-11-01 USER_EMOTION: Stress level 80, Happiness level 20"

[0781] By feeding this prompt into a generative AI model, the results are tailored date suggestions based on emotional data.

[0782] The above is an embodiment of the present invention. The present invention makes it possible to provide optimal date suggestions and feedback according to the emotional state of the user, and is expected to have the effect of increasing user satisfaction.

[0783] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0784] Step 1:

[0785] Input reception

[0786] User: The user selects the desired service and enters date information via a specified interface. For example, the user enters "November 1, 2023" as the "desired delivery date."

[0787] Input data: Date information (e.g., "November 1, 2023"), user voice data, and user facial expression image data.

[0788] Output data: The date information entered by the user and the collected emotion data are saved on the device.

[0789] Step 2:

[0790] emotion recognition

[0791] Device: The emotion engine analyzes voice data and facial expression image data to recognize the user's emotions.

[0792] Input data: User's voice data, user's facial expression image data.

[0793] Specific operation: Using a voice recognition library and an facial expression recognition library, the system quantifies emotional states (e.g., stress level, happiness) from changes in voice tone and facial expressions.

[0794] Output data: Emotion data (e.g. stress level 80, happiness level 20) is generated.

[0795] Step 3:

[0796] Data reception

[0797] Terminal: Sends the entered date information and emotion data to the server.

[0798] Input data: User-entered date information and parsed emotion data.

[0799] Specific operation: Sends input data to a server via the Internet using an HTTP POST request.

[0800] Output data: The server receives the date information and emotion data.

[0801] Step 4:

[0802] Data analysis

[0803] Server: Based on the received data, analyzes the service ID and date information. Emotion data is also included in the analysis.

[0804] Input data: date information, emotion data.

[0805] Specific operation: The rule set for the relevant service is retrieved from the database, and the date information and emotion data are processed using the analysis engine.

[0806] Output data: Parsed service ID, analysis result date, and emotion data.

[0807] Step 5:

[0808] Date arithmetic

[0809] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[0810] Input data: service identification information, analysis result date information, emotion data.

[0811] What it does: Uses a generative AI model to calculate the earliest and latest delivery dates based on a set of rules. Optimizes recommendations based on sentiment data.

[0812] Output data: Calculated earliest and latest dates, adjusted proposal.

[0813] Step 6:

[0814] Integrity Verification

[0815] Server: The calculation result is verified by the integrity verification module, for example, to ensure that the calculated date is within the range of the service.

[0816] Input data: The calculated earliest and latest dates.

[0817] Specific behavior: Checks whether the calculated date is valid according to the service provision rules.

[0818] Output data: Calculation results with consistency checked.

[0819] Step 7:

[0820] Results presentation

[0821] Device: Receives the results of the earliest and latest dates sent from the server and adjusts the display content based on the user's emotions. For example, displaying relaxing music or encouraging messages to a user who is feeling stressed.

[0822] Input data: Consistent calculations and adjusted proposals.

[0823] Specific behavior: The calculation results are displayed in the user interface and feedback is provided according to the emotional data.

[0824] Output: The suggestions presented to the user visually or audibly.

[0825] The above are the specific processing steps for implementing the present invention. This enables optimal date suggestions and feedback based on the user's emotional state, which is expected to increase user satisfaction.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] [Third embodiment]

[0830] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0831] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0832] 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).

[0833] 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.

[0834] 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.

[0835] 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).

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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."

[0842] This invention relates to a system that utilizes generative AI to propose optimal dates to streamline application forms for new non-telecommunications services. The system supports accurate and prompt application form creation by suggesting the earliest and latest dates when the user inputs specified date information.

[0843] System configuration

[0844] 1. User Interface (Terminal)

[0845] This includes a function that provides a form for the user to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, or desired delivery date).

[0846] 2. Data receiving module (server)

[0847] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[0848] 3. Analysis module (server)

[0849] The server includes a function to analyze the received date information and obtain the date rule set for the corresponding service.

[0850] 4. Generative AI module (server)

[0851] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[0852] 5. Integrity Verification Module (Server)

[0853] Includes a function to verify the consistency of the results output by generative AI.

[0854] 6. Result presentation module (terminal)

[0855] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[0856] Program processing flow

[0857] Input reception

[0858] Terminal: The user selects the desired service and enters date information through a specified interface. For example, the user enters "November 1, 2023" as the "desired delivery date."

[0859] Data reception and analysis

[0860] Terminal: Sends the entered information to the server.

[0861] Server: Analyzes the service identification information and date information based on the received data.

[0862] Calculating the earliest and latest dates

[0863] Server: Obtains a rule set corresponding to the service identification information based on generative AI.

[0864] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the applicable rules. For example, it calculates that the earliest delivery date is "November 3, 2023" and the latest delivery date is "November 15, 2023."

[0865] Consistency verification and presentation of results

[0866] Server: The calculation result is verified by the consistency verification module. For example, it checks whether the shortest delivery date falls on a holiday.

[0867] Terminal: Receives the results of the earliest and latest dates sent from the server and displays them on the user interface.

[0868] Specific examples

[0869] Suggested delivery date

[0870] User: Enters "November 1, 2023" as the "Desired delivery date" and clicks the send button on the device.

[0871] Server: Receives the information "November 1, 2023" and "desired delivery date" and instructs the generative AI to refer to the relevant rule based on the service identification.

[0872] Generative AI (on the server): Calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023."

[0873] Server: After verifying the integrity, it sends the calculation result to the terminal.

[0874] Terminal: Display "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" in the user interface.

[0875] The system of the present invention allows users to select dates efficiently and accurately, reducing the workload of sales representatives. Additionally, automated date suggestions reduce human error in application completion and minimize the risk of service delays.

[0876] The processing flow will be explained below.

[0877] Step 1:

[0878] User: Select the desired service via the designated interface and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date). For example, enter "November 1, 2023" as the "desired delivery date."

[0879] Step 2:

[0880] Terminal: The service information and date information entered by the user are sent to the server via an HTTP POST request.

[0881] Step 3:

[0882] Server: Analyzes the received request and extracts the service ID and date information. For example, the service ID is "A", the date is "November 1, 2023", and the date type is "Desired delivery date".

[0883] Step 4:

[0884] Server: Based on the extracted service identification information, the server sends the corresponding date rule set to the generative AI, which then retrieves the corresponding rules from its internal database.

[0885] Step 5:

[0886] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the acquired rule set. For example, it calculates that the earliest delivery date is "November 3, 2023" and the latest delivery date is "November 15, 2023."

[0887] Step 6:

[0888] Server: Receives the calculation results of the earliest and latest dates returned by the generative AI and verifies the consistency of the results. For example, it checks whether the earliest date is the date on which the specified service can be provided.

[0889] Step 7:

[0890] Server: Converts the calculation results whose integrity has been confirmed into JSON format and sends them to the user's device.

[0891] Step 8:

[0892] Terminal: Receives and analyzes the JSON data sent from the server. As a result, the following is displayed on the user interface: "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0893] The above is a concrete processing flow of the entire system. The operations performed at each step from receiving input from the user to presenting the final date proposal have been explained in detail.

[0894] Example 1

[0895] 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."

[0896] Conventional application creation systems have the problem that it takes time and effort for users to select an appropriate date, making it difficult to select an accurate date. In addition, human error is likely to occur in selecting the date, which can lead to reduced efficiency and risk of delays in service provision.

[0897] 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.

[0898] In this invention, the server includes means for a user to input predetermined information, means for receiving the input information, means for analyzing the received information and referencing the rules of the relevant service based on generative artificial intelligence, means for calculating the earliest date and latest date based on the rules, means for verifying the consistency of the calculation results, and means for presenting the calculation results whose consistency has been confirmed to the user. This allows the user to select dates efficiently and accurately, speeding up the application form creation process, reducing human error, and minimizing the risk of delays in service provision.

[0899] "User" means any person or entity that uses the System to input information and receive results.

[0900] "Specified information" refers to specific data that the user must input into the system, including the application date, desired start date, activation date, desired date, etc.

[0901] "Means" refers to a method, device, or function by which a system realizes a specific function or role.

[0902] The "means for inputting information" refers to an interface or device that allows a user to input predetermined information into the system.

[0903] "Means for receiving information" refers to the method or function by which the system receives information input by the user.

[0904] "Means for analyzing received information" refers to the methods and algorithms that the system uses to understand the information it receives and process it appropriately.

[0905] "Service Rules" means the business rules and conditions associated with a particular Service.

[0906] "Generative AI" refers to artificial intelligence techniques used to perform specific tasks or calculations within a system.

[0907] "Means for referencing relevant rules" refers to the methods or functions that enable a generative artificial intelligence to obtain and use rules related to a specific service.

[0908] "Means for calculating the earliest and latest dates" refers to methods or functions that allow generative artificial intelligence to calculate optimal dates according to rules.

[0909] "Means for verifying the consistency of calculation results" refers to methods or functions that confirm whether the date results calculated by the generative artificial intelligence match the specified conditions.

[0910] The "means for presenting the calculation result whose consistency has been confirmed" is a method or function for displaying the optimal date result to the user after the validation has been performed.

[0911] The present invention relates to a system that utilizes generative AI to propose optimal dates to streamline the creation of application forms for new non-communication services. This system supports accurate and rapid creation of application forms by suggesting the earliest and latest dates based on the user's input of specified information. A specific embodiment of the present invention will be described below.

[0912] User Interface (Terminal)

[0913] The user uses the device's user interface to select a service and enter required information (such as date information). The user interface can take the form of, for example, a web form or a mobile app. Input fields include "application date," "desired start date," "desired billing start date," "activation date," and "desired delivery date."

[0914] Data receiving module (server)

[0915] The terminal sends the information entered by the user to the server. This data is sent to the server via a protocol such as an HTTP request. The server checks whether the received data is in the correct format and performs validation.

[0916] Analysis module (server)

[0917] The server analyzes the information received through the data reception module. Specifically, the server identifies the service based on the received data and determines the rules for the corresponding service. The analyzed data is passed to the generative AI module.

[0918] Generative AI module (server)

[0919] The generative AI module calculates the earliest and latest delivery dates based on the analyzed data and applicable service rules. This calculation uses an internal algorithm and rule set. For example, the "earliest delivery date" is calculated as "November 3, 2023" and the "latest delivery date" is calculated as "November 15, 2023."

[0920] Integrity verification module (server)

[0921] The results output by the generative AI module are passed to the consistency verification module, which checks whether the calculation results meet pre-set conditions, such as whether the calculated date falls on a holiday or is an unreasonable date.

[0922] Result presentation module (terminal)

[0923] Once the verification is complete, the server sends the results of the earliest and latest delivery dates to the terminal. The terminal displays the received data on the user interface and presents the results to the user. For example, it displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0924] Specific examples

[0925] For example, if a user enters "November 1, 2023" as the "desired delivery date" and clicks the send button on the device, the server receives the information "November 1, 2023" and the "desired delivery date." The server then references the rule set based on generative AI and calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023." Finally, if the calculation results pass consistency verification, the device displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[0926] The system allows users to select dates efficiently and accurately, reducing the workload of sales representatives. Automated date suggestions also reduce human error in application completion, minimizing the risk of service delays.

[0927] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0928] Step 1:

[0929] The user inputs the specified information into the terminal. The user inputs the specified information, including the service selection and date information. For example, the user inputs "November 1, 2023" as the "desired delivery date." Once the input is complete, the user clicks the send button. The input data includes the application date, desired start date of use, desired start date of billing, activation date, desired delivery date, etc.

[0930] Step 2:

[0931] The terminal sends the entered information to the server. The information entered by the user is packaged in an appropriate format (for example, JSON format) and sent to the server via an HTTP request. The input data is sent in a format such as "Delivery request date: November 1, 2023".

[0932] Step 3:

[0933] The server receives and analyzes the input information. The server checks the received data and validates that it is in the appropriate format. If the received data is in the correct format, it analyzes the data and extracts the service identification and date information. For example, it analyzes the "desired delivery date" information and obtains the service identification information.

[0934] Step 4:

[0935] The server instructs the generative AI to retrieve the rule set. Based on the analyzed information, the server instructs the generative AI to refer to the rule set for the relevant service. For example, it retrieves the rule set related to delivery services. This rule set includes business rules and date calculation conditions.

[0936] Step 5:

[0937] The generative AI calculates the earliest and latest dates. The generative AI calculates the earliest and latest dates based on the received rule set and input information. For example, if the "desired delivery date" is "November 1, 2023," the earliest delivery date is calculated to be "November 3, 2023," and the latest delivery date is calculated to be "November 15, 2023." Calendar information and holiday information are taken into account in the calculation.

[0938] Step 6:

[0939] The server verifies the consistency of the calculation results. The server passes the date output by the generative AI to the consistency verification module. The consistency verification module checks whether the earliest and latest dates match the set conditions. For example, it checks whether the earliest date is a holiday or an unreasonable date.

[0940] Step 7:

[0941] The terminal receives and displays the results of the integrity check. The server sends the earliest and latest verification completion dates to the terminal. The terminal displays the results on the user interface. For example, "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" is displayed, visually presenting the results to the user.

[0942] (Application example 1)

[0943] 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."

[0944] In conventional application form creation systems for non-communication services, users manually select their desired date, which makes operation complicated and can lead to input errors and delays in application creation. Furthermore, particularly in food delivery, there are no systems that automatically calculate optimal departure and arrival times for the customer's desired delivery time, reducing delivery efficiency. The present invention aims to solve these problems and provide a system that efficiently and accurately selects dates and suggests delivery times.

[0945] 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.

[0946] In this invention, the server includes: a means for a user to input specified date information; a means for receiving the input date information; a means for analyzing the received date information and referencing the rules of the relevant service using a generative AI; a means for calculating the earliest date and latest date based on the rules; a means for adjusting and verifying the calculation result; a means for presenting the adjusted and confirmed calculation result to the user; and a means for a user to input a desired delivery time, calculate optimal departure and arrival times using the generative AI, and notify the restaurant operator and delivery person. This allows the user to efficiently and accurately select a date, and in the case of food delivery in particular, it is possible to automatically calculate optimal departure and arrival times for the customer's desired delivery time and promptly notify the restaurant operator and delivery person.

[0947] "Specified date information" is information including the specific date and time when the user wishes to use the service.

[0948] The "means for inputting" is a user interface that allows a user to input predetermined date information into the system.

[0949] The "receiving means" is a function that allows the server to receive date information entered by the user.

[0950] The "analysis means" is a function for analyzing received date information and extracting the rules for the corresponding service.

[0951] "Generative AI" is a technology that uses artificial intelligence to generate optimal dates and times based on specific rules.

[0952] The "earliest date" is the earliest date on which the service desired by the user can be provided.

[0953] The "latest date" is the latest date on which the service desired by the user can be provided.

[0954] "Means for calculating" means a function for calculating the earliest and latest dates based on applicable rules.

[0955] The "means for adjusting and verifying" is a function for checking whether the generated shortest date and latest date match the conditions set in advance.

[0956] The "means for presenting" is a function for notifying the user of the calculation results for which the adjustment has been confirmed.

[0957] "Desired delivery time" is information specifying the delivery date and time of a product or service that the user particularly desires.

[0958] "Departure time" is the time when the delivery person starts delivering the goods or services from the restaurant or warehouse.

[0959] "Arrival time" is the time when the product or service will arrive at the delivery destination specified by the user.

[0960] "Food service operators" refers to stores and companies that provide food delivery services.

[0961] A "delivery person" is a person or company responsible for delivering products or services to a customer on the date and time requested.

[0962] MODE FOR CARRYING OUT THE INVENTION

[0963] This invention relates to a food delivery system that automatically calculates optimal departure and arrival times based on the desired delivery time specified by the user. This system receives the desired delivery time entered by the user, uses generative AI to propose the optimal time, and notifies the restaurant operator and delivery staff, thereby achieving efficient delivery.

[0964] System configuration

[0965] User Interface (Terminal)

[0966] This is an interface that provides a form for the user to enter the desired delivery time. Taking a smartphone application as an example, the user specifies the desired delivery time as "December 1, 2023, 18:00."

[0967] Data receiving module (server)

[0968] This module receives the desired delivery time sent from the terminal. This module performs initial processing to analyze the user's input data on the server.

[0969] Analysis module (server)

[0970] It includes a function to analyze the requested delivery time received and obtain the rules for the corresponding service. Based on the results of this analysis, it prepares the data necessary for generative AI.

[0971] Generative AI module (server)

[0972] Based on the analyzed data, the module calculates the optimal departure and arrival times for the desired delivery time. This calculation is performed using AI models such as TensorFlow.

[0973] Adjustment verification module (server)

[0974] Validate that the calculated departure and arrival times meet predefined criteria, such as whether the optimal departure time is within the restaurant's opening hours and whether the arrival time matches the customer's preferred time slot.

[0975] Result presentation module (terminal)

[0976] The system notifies users, food service providers, and delivery personnel of the optimal departure and arrival times, providing accurate information to all parties via a smartphone app.

[0977] Hardware and software used

[0978] Hardware: Cloud servers such as Amazon EC2

[0979] Software: TensorFlow (generative AI model), custom validator (adjustment verification tool), smartphone application

[0980] Data calculation: Analyze received data and calculate optimal time using AI model, and verify adjustments

[0981] Specific usage scenarios and prompt examples

[0982] Usage scenarios

[0983] The user enters into the app a request for delivery at "December 1, 2023, 18:00." The server receives and analyzes the data. Generative AI is used to calculate the optimal departure and arrival times, and adjustments and verification are performed. As a result, the optimal departure time is calculated to be "December 1, 2023, 17:00" and the optimal arrival time is calculated to be "December 1, 2023, 18:00." These results are notified to the restaurant operator and delivery staff.

[0984] Prompt Sentence Examples

[0985] Desired delivery time: 2023-12-01 18:00

[0986] Generated departure time: 2023-12-01 17:00

[0987] Generated arrival time: 2023-12-01 18:00

[0988] The system will significantly improve the efficiency of food delivery and increase customer satisfaction by providing accurate delivery times.

[0989] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0990] Step 1:

[0991] The user enters the desired delivery time

[0992] The user inputs the desired delivery time through the smartphone app interface. For example, they might input "December 1, 2023, 6:00 PM." This input information is sent to the system as the first data.

[0993] Step 2:

[0994] Receiving data

[0995] The server receives the requested delivery time entered from the terminal. The received data is temporarily stored on the server for use in the next analysis step. Specifically, the data entered by the user as "December 1, 2023, 18:00" is received.

[0996] Step 3:

[0997] Data analysis

[0998] The server analyzes the received desired delivery time. From this analysis, it extracts information about the user's desired delivery time and prepares to obtain the relevant delivery rules. For example, it analyzes "December 1, 2023, 18:00" and takes into account the restaurant's business hours and the delivery staff's working hours.

[0999] Step 4:

[1000] Calculating optimal time using generative AI

[1001] The generative AI model on the server calculates the optimal departure and arrival times based on the analyzed data. Specifically, using TensorFlow, for "December 1, 2023, 18:00," the optimal departure time is calculated as "December 1, 2023, 17:00" and the optimal arrival time is calculated as "December 1, 2023, 18:00."

[1002] Step 5:

[1003] Adjustment and verification of calculation results

[1004] The server verifies the calculation results using the adjustment verification module. For example, it checks whether the optimal departure time is within the restaurant's business hours, and whether the arrival time matches the time slot specified by the customer. Specifically, it checks whether "December 1, 2023, 5:00 PM" is within the restaurant's business hours, and whether "December 1, 2023, 6:00 PM" is within the time slot specified by the customer.

[1005] Step 6:

[1006] Presentation of results

[1007] The verified optimal departure and arrival times are sent to the terminal and notified to the user, the restaurant operator, and the delivery person. The information "Departure time: December 1, 2023, 5:00 PM, Arrival time: December 1, 2023, 6:00 PM" is displayed to all parties via the smartphone app interface.

[1008] 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.

[1009] This invention relates to a system that utilizes generative AI and an emotion engine to propose optimal dates and adjust the interface display and proposal content based on the user's emotions in order to streamline the creation of application forms for new non-telecommunications services. This system supports the accurate and speedy creation of application forms by allowing the user to input specific date information and proposing the earliest and latest dates, thereby improving user satisfaction.

[1010] System configuration

[1011] 1. User Interface (Terminal)

[1012] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[1013] It includes a function that uses an emotion engine to recognize the user's emotions and adjust the interface display and suggestions based on those emotions.

[1014] 2. Data receiving module (server)

[1015] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[1016] 3. Analysis module (server)

[1017] The server includes a function to analyze the received date information and obtain the date rule set for the corresponding service.

[1018] 4. Generative AI module (server)

[1019] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[1020] 5. Integrity Verification Module (Server)

[1021] Includes a function to verify the consistency of the results output by generative AI.

[1022] 6. Result presentation module (terminal)

[1023] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[1024] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine.

[1025] 7. Emotion engine module (terminal and server)

[1026] It includes the ability to analyze the user's emotions using voice recognition and facial expression recognition.

[1027] It includes a function to provide data that influences the analysis module and generative AI module based on the analysis results.

[1028] Program processing flow

[1029] Input acceptance and emotion recognition

[1030] Terminal: The user selects the desired service and enters date information via a specified interface. At the same time, the emotion engine analyzes voice or facial expression data to recognize the user's emotions. For example, while entering "November 1, 2023" as the "desired delivery date," the emotion engine recognizes from the user's tone of voice and facial expression that they are feeling stressed.

[1031] Data reception and analysis

[1032] Terminal: Sends input information and emotion data to the server.

[1033] Server: Based on the received data, analyzes the service ID and date information. Emotion data is also included in the analysis.

[1034] Calculating the earliest and latest dates

[1035] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[1036] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the relevant rules. For example, the earliest delivery date is calculated as "November 3, 2023" and the latest delivery date is calculated as "November 15, 2023." At the same time, if the user is stressed, the earlier delivery date will be prioritized.

[1037] Consistency verification and presentation of results

[1038] Server: The calculation result is verified by the consistency verification module. For example, it is verified whether the shortest date is within the date on which the specified service can be provided.

[1039] Device: Receives the results of the earliest and latest delivery dates sent from the server and adjusts the display content based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the device will suggest "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023," as well as play relaxing music and display encouraging messages.

[1040] Specific examples

[1041] Suggested delivery date

[1042] User: Enters "November 1, 2023" as the "Desired Delivery Date" and clicks the send button on the device. The emotion engine detects stress from the user's voice.

[1043] Server: Receives the information "November 1, 2023" and "desired delivery date" along with emotion data, and instructs the generative AI to refer to the relevant rules based on the service identification.

[1044] Generative AI (on the server): Calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023." At the same time, prioritizes and suggests shorter delivery dates based on emotional data to reduce stress.

[1045] Server: After verifying the integrity, it sends the calculation results and emotion-based adjustment results to the device.

[1046] Device: Display "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" on the user interface while playing relaxing music or displaying a light, encouraging message.

[1047] The system of the present invention allows users to select dates efficiently and accurately, reducing the workload of sales representatives, and further improves user satisfaction by adjusting the system based on the user's emotional state using the emotion engine.

[1048] The processing flow will be explained below.

[1049] Step 1:

[1050] User: Selects the desired service through a designated interface and enters date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date). For example, enter "November 1, 2023" as the "desired delivery date." At the same time, the emotion engine analyzes the user's facial expressions and voice to recognize their emotions.

[1051] Step 2:

[1052] The device sends the date information and emotion data entered by the user to the server. Specifically, it sends a request including the user's selected date (November 1, 2023) and desired delivery date, as well as emotion data.

[1053] Step 3:

[1054] Server: Analyzes the received request and extracts the service ID and date information. If emotion data is included, it is also included in the analysis. For example, the service ID is "A," the date information is "November 1, 2023," the date type is "Desired delivery date," and the emotion data is "Stress."

[1055] Step 4:

[1056] Server: Based on the extracted service identification information, the corresponding date rule set is sent to the generative AI. The generative AI retrieves the corresponding rules from its internal database. The application of the rules is also adjusted based on the emotion data.

[1057] Step 5:

[1058] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the acquired rule set. For example, the earliest delivery date is calculated as "November 3, 2023" and the latest delivery date is calculated as "November 15, 2023." At the same time, the earliest delivery date is given a higher priority based on emotion data.

[1059] Step 6:

[1060] Server: Receives the calculation results of the earliest and latest dates returned by the generative AI and verifies the consistency of the results. For example, it checks whether the earliest date is actually a date on which the service can be provided.

[1061] Step 7:

[1062] Server: The server sends the calculation results, whose integrity has been confirmed, in JSON format to the device, along with messages and influence factors based on the emotion data.

[1063] Step 8:

[1064] Terminal: Receives and analyzes the JSON data sent from the server. As a result of the analysis, the user interface displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023." Furthermore, if the user is feeling stressed, the device plays relaxing music and displays an encouraging message in a pop-up.

[1065] This is the specific processing flow of the entire system. By linking with the emotion engine, it can respond to the user's emotional state and provide a better user experience.

[1066] Example 2

[1067] 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."

[1068] Conventional application form creation systems make it difficult for users to accurately select date information and do not take the user's emotional state into consideration, which can sometimes compromise the user experience. As a result, the application process becomes cumbersome, resulting in problems of reduced user satisfaction. Furthermore, there are also problems with increased workloads for sales representatives and reduced work efficiency. To solve these issues, a system is needed that allows users to easily and quickly enter accurate date information and can adjust according to the user's emotional state.

[1069] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1070] In this invention, the server includes means for a user to input predetermined date information, means for receiving the input date information and user emotion information, means for analyzing the received date information and emotion information and referencing the rules of the relevant service, means for calculating the earliest date and latest date based on the relevant rules and emotion information, means for verifying the consistency of the calculation results, means for presenting the calculation results whose consistency has been confirmed to the user, and means for adjusting the display content of the interface in accordance with the user's emotional state. This allows the user to accurately and quickly select date information, and adjustments are made based on the user's emotional state, thereby improving user satisfaction and reducing the burden on sales representatives, thereby improving work efficiency.

[1071] "Date information" is information about specific dates such as the application date, desired start date of use, desired start date of billing, activation date, and desired delivery date that the user enters when filling out an application form for a service.

[1072] "Emotion information" is information about the user's emotional state that is analyzed by the emotion engine from the user's voice, facial expressions, and the like.

[1073] The "receiving means" refers to a hardware and software configuration for transmitting date information and emotion information input by the user to the server and receiving the information.

[1074] The "analysis means" refers to a hardware and software configuration for analyzing the received date information and emotion information and referencing the rules of the corresponding service based on the analysis.

[1075] "Generative AI" is an artificial intelligence model that calculates the earliest and latest dates based on received data according to specific rules.

[1076] A "means for calculating" is a hardware and software configuration for calculating the earliest and latest dates based on applicable rules and sentiment information.

[1077] The "means for verifying consistency" is a hardware and software configuration for checking whether the generated earliest and latest dates match pre-set conditions.

[1078] The "presentation means" refers to a hardware and software configuration for displaying the results of the earliest and latest dates for which consistency has been confirmed on a user interface and providing feedback to the user.

[1079] The "adjusting means" refers to a hardware and software configuration that adjusts the interface display content according to the user's emotional state, thereby improving user satisfaction.

[1080] This invention is a system that utilizes generative AI and an emotion engine to streamline the creation of application forms for new non-communication services and propose optimal dates based on the user's emotions. This system aims to not only support the accurate and speedy creation of application forms by allowing the user to input specific date information and proposing the earliest and latest dates, but also to improve user satisfaction.

[1081] System configuration

[1082] 1. User Interface (Terminal)

[1083] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[1084] It is equipped with an emotion engine that analyzes the user's voice and facial expression data to recognize the user's emotions.

[1085] 2. Data receiving module (server)

[1086] This module receives data entered by the user and includes a function to perform initial processing of the data. SSL is used to receive the data, ensuring its security.

[1087] 3. Analysis module (server)

[1088] The server analyzes the received date and emotion information and acquires the corresponding date rule set for the service. For example, the rule set for "Delivery Service" includes the conditions for "Shortest Shipping Date" and "Latest Shipping Date."

[1089] 4. Generative AI module (server)

[1090] Based on the analyzed data, the system calculates the earliest and latest dates based on the corresponding rules and sentiment information. For example, for a desired delivery date, "November 3, 2023" is calculated as the earliest date and "November 15, 2023" as the latest date.

[1091] 5. Integrity Verification Module (Server)

[1092] This includes a function to verify the consistency of the results output by the generative AI, checking whether the calculated earliest and latest dates match pre-set conditions.

[1093] 6. Result presentation module (terminal)

[1094] Includes a function to present the results of the earliest and latest dates for which consistency was confirmed to the user.

[1095] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine. For example, if the user is feeling stressed, it will display relaxing music or an encouraging message.

[1096] 7. Emotion engine module (terminal and server)

[1097] It includes the ability to analyze the user's emotions using voice recognition and facial expression recognition.

[1098] Based on the analysis results, data is provided that influences the analysis module and generative AI module.

[1099] Specific examples

[1100] Suggested delivery date

[1101] User: Enters "November 1, 2023" as the "Desired Delivery Date" and clicks the send button on the device. The emotion engine detects stress from the user's tone of voice and facial expression.

[1102] Device: Sends the entered "November 1, 2023" and emotion data to the server.

[1103] Server: Receives these data and retrieves the date rule set from the database. The emotion engine provides the analysis results and reflects the user's stress state.

[1104] Generative AI (server): Calculates "November 3, 2023" as the earliest date and "November 15, 2023" as the latest date, and at the same time, prioritizes "November 3, 2023" to reduce stress.

[1105] Server: Performs consistency verification and sends the results to the terminal via the result presentation module.

[1106] Device: Shows the suggested delivery date of November 3, 2023, and November 15, 2023, and plays relaxing music and displays an encouraging message.

[1107] Prompt Sentence Examples

[1108] "I'd like delivery on November 1, 2023, what are the earliest and latest dates? Can you please let me know if there is a preferred date to alleviate some of the stress?"

[1109] This system allows users to select date information efficiently and accurately, reducing the workload of sales representatives. The emotion engine adjusts according to the user's emotional state, further improving user satisfaction.

[1110] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1111] Step 1:

[1112] Terminal: The user selects the type of service and enters the required date information (e.g., application date, desired start date of use, desired start date of billing, desired delivery date) into the application form. The emotion engine simultaneously collects the user's voice and facial expressions and analyzes their emotional state. For example, if the user enters "November 1, 2023" as the "desired delivery date," the emotion engine simultaneously detects stress from the user's tone of voice and facial expression. This allows the input information (desired delivery date) and emotional data (stress level) to be collected.

[1113] Step 2:

[1114] Terminal: The input date information and emotion information are packaged and sent to the server via the data receiving module. The input data includes the user-entered "Desired delivery date of November 1, 2023" and the analyzed emotion data (e.g., stress level). The output is the sent data package.

[1115] Step 3:

[1116] Server: The data receiving module receives the date and emotion information and performs an initial analysis. This involves checking the data format and identifying any incomplete information. The received data includes the desired delivery date of November 1, 2023 and the stress level, and the data is output after being confirmed to be consistent.

[1117] Step 4:

[1118] Server: The analysis module retrieves the relevant date rule set from the database based on the service identification information. For example, a rule set for "Delivery Service" includes the conditions "Earliest Shipping Date" and "Latest Shipping Date." The input data are the consistency-checked date information and emotion data, and the output is a date rule set.

[1119] Step 5:

[1120] Server: The emotion engine provides the analysis results (e.g., the user's stress level) to the generative AI module, allowing it to make adjustments based on specific emotional states. For example, if the stress level is high, the generative AI can be configured to prioritize a faster delivery date. The input data is the emotion analysis results, and the output is the adjusted conditions.

[1121] Step 6:

[1122] Server: The generative AI module calculates the earliest and latest dates based on the date rule set and the sentiment analysis results. For example, the calculation results output "November 3, 2023" as the earliest date and "November 15, 2023" as the latest date. The input data are the rule set and the sentiment analysis results, and the output is the calculated earliest and latest dates.

[1123] Step 7:

[1124] Server: The consistency verification module receives the calculation results from the generative AI and checks whether the calculated date matches the pre-defined conditions. For example, it checks whether "November 3, 2023" and "November 15, 2023" are within the service availability period. The input data are the earliest and latest dates, and the output is the verified date.

[1125] Step 8:

[1126] Server: The result presentation module sends the results of the earliest and latest dates that have been verified to the user interface. The input data is the validated date, and the output is the date data for presentation.

[1127] Step 9:

[1128] Terminal: The user interface displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" and plays relaxing music and encouraging messages based on the analysis results of the emotion engine. The input data is the date data to be presented and the emotion analysis results, and the output is the displayed content.

[1129] In this way, the user can accurately and quickly select date information and receive feedback according to their emotional state.

[1130] (Application example 2)

[1131] 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."

[1132] Conventional systems can suggest optimal dates based on the date information entered by the user, but they often result in low user satisfaction because the suggestions do not take into account the user's emotional state. Furthermore, while there is a need for systems to make more appropriate suggestions to users by utilizing emotional information obtained from facial expressions and voice, there is currently a lack of a mechanism to achieve this.

[1133] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing predetermined date information and emotions of the user, means for receiving the input date information and emotion data, means for analyzing the received date information and emotion data and referencing the rules of the relevant service based on generative AI, means for calculating the earliest date and latest date based on the relevant rules and adjusting the proposal content based on the emotion, means for verifying the consistency of the calculation results, and means for presenting the calculation results whose consistency has been confirmed and the adjusted proposal content to the user. This enables optimal date suggestions and feedback according to the user's emotional state, thereby increasing user satisfaction.

[1134] The "means for analyzing the user's specified date information and emotions" refers to a device or software that analyzes the user's emotional state using voice recognition and facial expression recognition in addition to the date information entered by the user.

[1135] The "means for receiving input date information and emotion data" refers to a device or software for receiving date information and emotion data sent from the user and transferring them to the server.

[1136] "Means for analyzing received date information and emotion data and referencing the rules of the relevant service based on generative AI" refers to devices or software that analyzes the date information and user emotion data received by the server and uses generative AI to refer to the service rules based on that information.

[1137] "Means for calculating the earliest and latest dates based on the relevant rules and adjusting the content of the proposal based on emotions" refers to devices or software that allow the generative AI to adjust the content of the proposal based on the earliest and latest dates calculated in accordance with the service rules, taking into account the user's emotional state.

[1138] "Means for verifying the consistency of calculation results" refers to devices or software for verifying whether the earliest and latest dates calculated by generative AI match pre-set conditions and rules.

[1139] "Means for presenting to the user the calculation results whose consistency has been confirmed and the adjusted proposal content" refers to a device or software for visually or audibly presenting to the user the calculation results whose consistency has been confirmed and the proposal content that has been adjusted based on the user's emotional state.

[1140] "Means for analyzing emotions" refers to devices or software for analyzing a user's emotional state using technologies such as voice recognition and facial expression recognition.

[1141] "Date information" is information relating to a specific date entered by the user, such as the application date, desired start date of use, desired start date of billing, activation date, or desired delivery date.

[1142] The system for implementing the present invention provides a terminal for users to input specified date information and emotions, a server that analyzes the received data, calculates the earliest and latest dates using generative AI, and adjusts the suggestions based on the user's emotions, and a function that verifies the consistency of these calculation results before presenting them to the user.

[1143] System configuration

[1144] 1. User Interface (Terminal):

[1145] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[1146] It includes a function that uses an emotion engine to recognize the user's emotions and adjust the interface display and suggestions based on those emotions.

[1147] 2. Data receiving module (server):

[1148] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[1149] 3. Analysis module (server):

[1150] The server analyzes the received date information and emotion data, and includes a function to obtain the date rule set for the corresponding service.

[1151] 4. Generative AI module (server):

[1152] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[1153] 5. Integrity Verification Module (Server):

[1154] Includes a function to verify the consistency of the results output by generative AI.

[1155] 6. Result presentation module (terminal):

[1156] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[1157] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine.

[1158] Program processing

[1159] Input acceptance and emotion recognition

[1160] Terminal: The user selects the desired service and enters date information through a designated interface. At the same time, the emotion engine analyzes voice or facial expression data to recognize the user's emotions.

[1161] Data reception and analysis

[1162] Terminal: Sends input information and emotion data to the server.

[1163] Server: Analyzes the service ID and date information based on the received data. Emotion data is also included in the analysis.

[1164] Calculating the earliest and latest dates

[1165] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[1166] Generative AI: Calculates the earliest and latest dates based on applicable rules.

[1167] Consistency verification and presentation of results

[1168] Server: The calculation result is verified by the integrity verification module.

[1169] Device: Receives the results of the earliest and latest dates sent from the server and adjusts the display content based on the sentiment.

[1170] Hardware and software used

[1171] Smartphone: A device that installs applications and accepts user input.

[1172] Emotion Recognition Library:

[1173] Software that analyzes emotions using voice and facial recognition (e.g., Emotion Recognition Library).

[1174] Generative AI libraries:

[1175] Software that calculates dates based on service identifiers and date rules (e.g., AI Date Generator Library).

[1176] Flask: A framework used to implement server-side applications and provide APIs.

[1177] Specific examples

[1178] As a concrete example, in the case of an "e-commerce website date selection assistant app," if a user inputs "November 1, 2023" as the desired delivery date, the emotion engine recognizes from the voice that the user is feeling stressed. The server analyzes the received data, and the generative AI calculates the earliest and latest delivery dates based on the service rules. For example, the earliest delivery date is calculated as "November 3, 2023," and the latest delivery date as "November 15, 2023." At the same time, the system suggests prioritizing the faster delivery date based on the emotion data to reduce stress. The user interface also plays relaxing music and displays encouraging messages.

[1179] Prompt Sentence Examples

[1180] Specific examples of prompt sentences are shown below.

[1181] "SERVICE_TYPE: Delivery Service PREFERRED_DATE: 2023-11-01 USER_EMOTION: Stress level 80, Happiness level 20"

[1182] By feeding this prompt into a generative AI model, the results are tailored date suggestions based on emotional data.

[1183] The above is an embodiment of the present invention. The present invention makes it possible to provide optimal date suggestions and feedback according to the emotional state of the user, and is expected to have the effect of increasing user satisfaction.

[1184] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1185] Step 1:

[1186] Input reception

[1187] User: The user selects the desired service and enters date information via a specified interface. For example, the user enters "November 1, 2023" as the "desired delivery date."

[1188] Input data: Date information (e.g., "November 1, 2023"), user voice data, and user facial expression image data.

[1189] Output data: The date information entered by the user and the collected emotion data are saved on the device.

[1190] Step 2:

[1191] emotion recognition

[1192] Device: The emotion engine analyzes voice data and facial expression image data to recognize the user's emotions.

[1193] Input data: User's voice data, user's facial expression image data.

[1194] Specific operation: Using a voice recognition library and an facial expression recognition library, the system quantifies emotional states (e.g., stress level, happiness) from changes in voice tone and facial expressions.

[1195] Output data: Emotion data (e.g. stress level 80, happiness level 20) is generated.

[1196] Step 3:

[1197] Data reception

[1198] Terminal: Sends the entered date information and emotion data to the server.

[1199] Input data: User-entered date information and parsed emotion data.

[1200] Specific operation: Sends input data to a server via the Internet using an HTTP POST request.

[1201] Output data: The server receives the date information and emotion data.

[1202] Step 4:

[1203] Data analysis

[1204] Server: Based on the received data, analyzes the service ID and date information. Emotion data is also included in the analysis.

[1205] Input data: date information, emotion data.

[1206] Specific operation: The rule set for the relevant service is retrieved from the database, and the date information and emotion data are processed using the analysis engine.

[1207] Output data: Parsed service ID, analysis result date, and emotion data.

[1208] Step 5:

[1209] Date arithmetic

[1210] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[1211] Input data: service identification information, analysis result date information, emotion data.

[1212] What it does: Uses a generative AI model to calculate the earliest and latest delivery dates based on a set of rules. Optimizes recommendations based on sentiment data.

[1213] Output data: Calculated earliest and latest dates, adjusted proposal.

[1214] Step 6:

[1215] Integrity Verification

[1216] Server: The calculation result is verified by the integrity verification module, for example, to ensure that the calculated date is within the range of the service.

[1217] Input data: The calculated earliest and latest dates.

[1218] Specific behavior: Checks whether the calculated date is valid according to the service provision rules.

[1219] Output data: Calculation results with consistency checked.

[1220] Step 7:

[1221] Results presentation

[1222] Device: Receives the results of the earliest and latest dates sent from the server and adjusts the display content based on the user's emotions. For example, displaying relaxing music or encouraging messages to a user who is feeling stressed.

[1223] Input data: Consistent calculations and adjusted proposals.

[1224] Specific behavior: The calculation results are displayed in the user interface and feedback is provided according to the emotional data.

[1225] Output: The suggestions presented to the user visually or audibly.

[1226] The above are the specific processing steps for implementing the present invention. This enables optimal date suggestions and feedback based on the user's emotional state, which is expected to increase user satisfaction.

[1227] 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.

[1228] 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.

[1229] 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.

[1230] [Fourth embodiment]

[1231] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1232] 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.

[1233] 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).

[1234] 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.

[1235] 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.

[1236] 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).

[1237] 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.

[1238] 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.

[1239] 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.

[1240] 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.

[1241] 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.

[1242] 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.

[1243] 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."

[1244] This invention relates to a system that utilizes generative AI to propose optimal dates to streamline application forms for new non-telecommunications services. The system supports accurate and prompt application form creation by suggesting the earliest and latest dates when the user inputs specified date information.

[1245] System configuration

[1246] 1. User Interface (Terminal)

[1247] This includes a function that provides a form for the user to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, or desired delivery date).

[1248] 2. Data receiving module (server)

[1249] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[1250] 3. Analysis module (server)

[1251] The server includes a function to analyze the received date information and obtain the date rule set for the corresponding service.

[1252] 4. Generative AI module (server)

[1253] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[1254] 5. Integrity Verification Module (Server)

[1255] Includes a function to verify the consistency of the results output by generative AI.

[1256] 6. Result presentation module (terminal)

[1257] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[1258] Program processing flow

[1259] Input reception

[1260] Terminal: The user selects the desired service and enters date information through a specified interface. For example, the user enters "November 1, 2023" as the "desired delivery date."

[1261] Data reception and analysis

[1262] Terminal: Sends the entered information to the server.

[1263] Server: Analyzes the service identification information and date information based on the received data.

[1264] Calculating the earliest and latest dates

[1265] Server: Obtains a rule set corresponding to the service identification information based on generative AI.

[1266] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the applicable rules. For example, it calculates that the earliest delivery date is "November 3, 2023" and the latest delivery date is "November 15, 2023."

[1267] Consistency verification and presentation of results

[1268] Server: The calculation result is verified by the consistency verification module. For example, it checks whether the shortest delivery date falls on a holiday.

[1269] Terminal: Receives the results of the earliest and latest dates sent from the server and displays them on the user interface.

[1270] Specific examples

[1271] Suggested delivery date

[1272] User: Enters "November 1, 2023" as the "Desired delivery date" and clicks the send button on the device.

[1273] Server: Receives the information "November 1, 2023" and "desired delivery date" and instructs the generative AI to refer to the relevant rule based on the service identification.

[1274] Generative AI (on the server): Calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023."

[1275] Server: After verifying the integrity, it sends the calculation result to the terminal.

[1276] Terminal: Display "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" in the user interface.

[1277] The system of the present invention allows users to select dates efficiently and accurately, reducing the workload of sales representatives. Additionally, automated date suggestions reduce human error in application completion and minimize the risk of service delays.

[1278] The processing flow will be explained below.

[1279] Step 1:

[1280] User: Select the desired service via the designated interface and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date). For example, enter "November 1, 2023" as the "desired delivery date."

[1281] Step 2:

[1282] Terminal: The service information and date information entered by the user are sent to the server via an HTTP POST request.

[1283] Step 3:

[1284] Server: Analyzes the received request and extracts the service ID and date information. For example, the service ID is "A", the date is "November 1, 2023", and the date type is "Desired delivery date".

[1285] Step 4:

[1286] Server: Based on the extracted service identification information, the server sends the corresponding date rule set to the generative AI, which then retrieves the corresponding rules from its internal database.

[1287] Step 5:

[1288] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the acquired rule set. For example, it calculates that the earliest delivery date is "November 3, 2023" and the latest delivery date is "November 15, 2023."

[1289] Step 6:

[1290] Server: Receives the calculation results of the earliest and latest dates returned by the generative AI and verifies the consistency of the results. For example, it checks whether the earliest date is the date on which the specified service can be provided.

[1291] Step 7:

[1292] Server: Converts the calculation results whose integrity has been confirmed into JSON format and sends them to the user's device.

[1293] Step 8:

[1294] Terminal: Receives and analyzes the JSON data sent from the server. As a result, the following is displayed on the user interface: "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[1295] The above is a concrete processing flow of the entire system. The operations performed at each step from receiving input from the user to presenting the final date proposal have been explained in detail.

[1296] Example 1

[1297] 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."

[1298] Conventional application creation systems have the problem that it takes time and effort for users to select an appropriate date, making it difficult to select an accurate date. In addition, human error is likely to occur in selecting the date, which can lead to reduced efficiency and risk of delays in service provision.

[1299] 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.

[1300] In this invention, the server includes means for a user to input predetermined information, means for receiving the input information, means for analyzing the received information and referencing the rules of the relevant service based on generative artificial intelligence, means for calculating the earliest date and latest date based on the rules, means for verifying the consistency of the calculation results, and means for presenting the calculation results whose consistency has been confirmed to the user. This allows the user to select dates efficiently and accurately, speeding up the application form creation process, reducing human error, and minimizing the risk of delays in service provision.

[1301] "User" means any person or entity that uses the System to input information and receive results.

[1302] "Specified information" refers to specific data that the user must input into the system, including the application date, desired start date, activation date, desired date, etc.

[1303] "Means" refers to a method, device, or function by which a system realizes a specific function or role.

[1304] The "means for inputting information" refers to an interface or device that allows a user to input predetermined information into the system.

[1305] "Means for receiving information" refers to the method or function by which the system receives information input by the user.

[1306] "Means for analyzing received information" refers to the methods and algorithms that the system uses to understand the information it receives and process it appropriately.

[1307] "Service Rules" means the business rules and conditions associated with a particular Service.

[1308] "Generative AI" refers to artificial intelligence techniques used to perform specific tasks or calculations within a system.

[1309] "Means for referencing relevant rules" refers to the methods or functions that enable a generative artificial intelligence to obtain and use rules related to a specific service.

[1310] "Means for calculating the earliest and latest dates" refers to methods or functions that allow generative artificial intelligence to calculate optimal dates according to rules.

[1311] "Means for verifying the consistency of calculation results" refers to methods or functions that confirm whether the date results calculated by the generative artificial intelligence match the specified conditions.

[1312] The "means for presenting the calculation result whose consistency has been confirmed" is a method or function for displaying the optimal date result to the user after the validation has been performed.

[1313] The present invention relates to a system that utilizes generative AI to propose optimal dates to streamline the creation of application forms for new non-communication services. This system supports accurate and rapid creation of application forms by suggesting the earliest and latest dates based on the user's input of specified information. A specific embodiment of the present invention will be described below.

[1314] User Interface (Terminal)

[1315] The user uses the device's user interface to select a service and enter required information (such as date information). The user interface can take the form of, for example, a web form or a mobile app. Input fields include "application date," "desired start date," "desired billing start date," "activation date," and "desired delivery date."

[1316] Data receiving module (server)

[1317] The terminal sends the information entered by the user to the server. This data is sent to the server via a protocol such as an HTTP request. The server checks whether the received data is in the correct format and performs validation.

[1318] Analysis module (server)

[1319] The server analyzes the information received through the data reception module. Specifically, the server identifies the service based on the received data and determines the rules for the corresponding service. The analyzed data is passed to the generative AI module.

[1320] Generative AI module (server)

[1321] The generative AI module calculates the earliest and latest delivery dates based on the analyzed data and applicable service rules. This calculation uses an internal algorithm and rule set. For example, the "earliest delivery date" is calculated as "November 3, 2023" and the "latest delivery date" is calculated as "November 15, 2023."

[1322] Integrity verification module (server)

[1323] The results output by the generative AI module are passed to the consistency verification module, which checks whether the calculation results meet pre-set conditions, such as whether the calculated date falls on a holiday or is an unreasonable date.

[1324] Result presentation module (terminal)

[1325] Once the verification is complete, the server sends the results of the earliest and latest delivery dates to the terminal. The terminal displays the received data on the user interface and presents the results to the user. For example, it displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[1326] Specific examples

[1327] For example, if a user enters "November 1, 2023" as the "desired delivery date" and clicks the send button on the device, the server receives the information "November 1, 2023" and the "desired delivery date." The server then references the rule set based on generative AI and calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023." Finally, if the calculation results pass consistency verification, the device displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023."

[1328] The system allows users to select dates efficiently and accurately, reducing the workload of sales representatives. Automated date suggestions also reduce human error in application completion, minimizing the risk of service delays.

[1329] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1330] Step 1:

[1331] The user inputs the specified information into the terminal. The user inputs the specified information, including the service selection and date information. For example, the user inputs "November 1, 2023" as the "desired delivery date." Once the input is complete, the user clicks the send button. The input data includes the application date, desired start date of use, desired start date of billing, activation date, desired delivery date, etc.

[1332] Step 2:

[1333] The terminal sends the entered information to the server. The information entered by the user is packaged in an appropriate format (for example, JSON format) and sent to the server via an HTTP request. The input data is sent in a format such as "Delivery request date: November 1, 2023".

[1334] Step 3:

[1335] The server receives and analyzes the input information. The server checks the received data and validates that it is in the appropriate format. If the received data is in the correct format, it analyzes the data and extracts the service identification and date information. For example, it analyzes the "desired delivery date" information and obtains the service identification information.

[1336] Step 4:

[1337] The server instructs the generative AI to retrieve the rule set. Based on the analyzed information, the server instructs the generative AI to refer to the rule set for the relevant service. For example, it retrieves the rule set related to delivery services. This rule set includes business rules and date calculation conditions.

[1338] Step 5:

[1339] The generative AI calculates the earliest and latest dates. The generative AI calculates the earliest and latest dates based on the received rule set and input information. For example, if the "desired delivery date" is "November 1, 2023," the earliest delivery date is calculated to be "November 3, 2023," and the latest delivery date is calculated to be "November 15, 2023." Calendar information and holiday information are taken into account in the calculation.

[1340] Step 6:

[1341] The server verifies the consistency of the calculation results. The server passes the date output by the generative AI to the consistency verification module. The consistency verification module checks whether the earliest and latest dates match the set conditions. For example, it checks whether the earliest date is a holiday or an unreasonable date.

[1342] Step 7:

[1343] The terminal receives and displays the results of the integrity check. The server sends the earliest and latest verification completion dates to the terminal. The terminal displays the results on the user interface. For example, "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" is displayed, visually presenting the results to the user.

[1344] (Application example 1)

[1345] 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."

[1346] In conventional application form creation systems for non-communication services, users manually select their desired date, which makes operation complicated and can lead to input errors and delays in application creation. Furthermore, particularly in food delivery, there are no systems that automatically calculate optimal departure and arrival times for the customer's desired delivery time, reducing delivery efficiency. The present invention aims to solve these problems and provide a system that efficiently and accurately selects dates and suggests delivery times.

[1347] 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.

[1348] In this invention, the server includes: a means for a user to input specified date information; a means for receiving the input date information; a means for analyzing the received date information and referencing the rules of the relevant service using a generative AI; a means for calculating the earliest date and latest date based on the rules; a means for adjusting and verifying the calculation result; a means for presenting the adjusted and confirmed calculation result to the user; and a means for a user to input a desired delivery time, calculate optimal departure and arrival times using the generative AI, and notify the restaurant operator and delivery person. This allows the user to efficiently and accurately select a date, and in the case of food delivery in particular, it is possible to automatically calculate optimal departure and arrival times for the customer's desired delivery time and promptly notify the restaurant operator and delivery person.

[1349] "Specified date information" is information including the specific date and time when the user wishes to use the service.

[1350] The "means for inputting" is a user interface that allows a user to input predetermined date information into the system.

[1351] The "receiving means" is a function that allows the server to receive date information entered by the user.

[1352] The "analysis means" is a function for analyzing received date information and extracting the rules for the corresponding service.

[1353] "Generative AI" is a technology that uses artificial intelligence to generate optimal dates and times based on specific rules.

[1354] The "earliest date" is the earliest date on which the service desired by the user can be provided.

[1355] The "latest date" is the latest date on which the service desired by the user can be provided.

[1356] "Means for calculating" means a function for calculating the earliest and latest dates based on applicable rules.

[1357] The "means for adjusting and verifying" is a function for checking whether the generated shortest date and latest date match the conditions set in advance.

[1358] The "means for presenting" is a function for notifying the user of the calculation results for which the adjustment has been confirmed.

[1359] "Desired delivery time" is information specifying the delivery date and time of a product or service that the user particularly desires.

[1360] "Departure time" is the time when the delivery person starts delivering the goods or services from the restaurant or warehouse.

[1361] "Arrival time" is the time when the product or service will arrive at the delivery destination specified by the user.

[1362] "Food service operators" refers to stores and companies that provide food delivery services.

[1363] A "delivery person" is a person or company responsible for delivering products or services to a customer on the date and time requested.

[1364] MODE FOR CARRYING OUT THE INVENTION

[1365] This invention relates to a food delivery system that automatically calculates optimal departure and arrival times based on the desired delivery time specified by the user. This system receives the desired delivery time entered by the user, uses generative AI to propose the optimal time, and notifies the restaurant operator and delivery staff, thereby achieving efficient delivery.

[1366] System configuration

[1367] User Interface (Terminal)

[1368] This is an interface that provides a form for the user to enter the desired delivery time. Taking a smartphone application as an example, the user specifies the desired delivery time as "December 1, 2023, 18:00."

[1369] Data receiving module (server)

[1370] This module receives the desired delivery time sent from the terminal. This module performs initial processing to analyze the user's input data on the server.

[1371] Analysis module (server)

[1372] It includes a function to analyze the requested delivery time received and obtain the rules for the corresponding service. Based on the results of this analysis, it prepares the data necessary for generative AI.

[1373] Generative AI module (server)

[1374] Based on the analyzed data, the module calculates the optimal departure and arrival times for the desired delivery time. This calculation is performed using AI models such as TensorFlow.

[1375] Adjustment verification module (server)

[1376] Validate that the calculated departure and arrival times meet predefined criteria, such as whether the optimal departure time is within the restaurant's opening hours and whether the arrival time matches the customer's preferred time slot.

[1377] Result presentation module (terminal)

[1378] The system notifies users, food service providers, and delivery personnel of the optimal departure and arrival times, providing accurate information to all parties via a smartphone app.

[1379] Hardware and software used

[1380] Hardware: Cloud servers such as Amazon EC2

[1381] Software: TensorFlow (generative AI model), custom validator (adjustment verification tool), smartphone application

[1382] Data calculation: Analyze received data and calculate optimal time using AI model, and verify adjustments

[1383] Specific usage scenarios and prompt examples

[1384] Usage scenarios

[1385] The user enters into the app a request for delivery at "December 1, 2023, 18:00." The server receives and analyzes the data. Generative AI is used to calculate the optimal departure and arrival times, and adjustments and verification are performed. As a result, the optimal departure time is calculated to be "December 1, 2023, 17:00" and the optimal arrival time is calculated to be "December 1, 2023, 18:00." These results are notified to the restaurant operator and delivery staff.

[1386] Prompt Sentence Examples

[1387] Desired delivery time: 2023-12-01 18:00

[1388] Generated departure time: 2023-12-01 17:00

[1389] Generated arrival time: 2023-12-01 18:00

[1390] The system will significantly improve the efficiency of food delivery and increase customer satisfaction by providing accurate delivery times.

[1391] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1392] Step 1:

[1393] The user enters the desired delivery time

[1394] The user inputs the desired delivery time through the smartphone app interface. For example, they might input "December 1, 2023, 6:00 PM." This input information is sent to the system as the first data.

[1395] Step 2:

[1396] Receiving data

[1397] The server receives the requested delivery time entered from the terminal. The received data is temporarily stored on the server for use in the next analysis step. Specifically, the data entered by the user as "December 1, 2023, 18:00" is received.

[1398] Step 3:

[1399] Data analysis

[1400] The server analyzes the received desired delivery time. From this analysis, it extracts information about the user's desired delivery time and prepares to obtain the relevant delivery rules. For example, it analyzes "December 1, 2023, 18:00" and takes into account the restaurant's business hours and the delivery staff's working hours.

[1401] Step 4:

[1402] Calculating optimal time using generative AI

[1403] The generative AI model on the server calculates the optimal departure and arrival times based on the analyzed data. Specifically, using TensorFlow, for "December 1, 2023, 18:00," the optimal departure time is calculated as "December 1, 2023, 17:00" and the optimal arrival time is calculated as "December 1, 2023, 18:00."

[1404] Step 5:

[1405] Adjustment and verification of calculation results

[1406] The server verifies the calculation results using the adjustment verification module. For example, it checks whether the optimal departure time is within the restaurant's business hours, and whether the arrival time matches the time slot specified by the customer. Specifically, it checks whether "December 1, 2023, 5:00 PM" is within the restaurant's business hours, and whether "December 1, 2023, 6:00 PM" is within the time slot specified by the customer.

[1407] Step 6:

[1408] Presentation of results

[1409] The verified optimal departure and arrival times are sent to the terminal and notified to the user, the restaurant operator, and the delivery person. The information "Departure time: December 1, 2023, 5:00 PM, Arrival time: December 1, 2023, 6:00 PM" is displayed to all parties via the smartphone app interface.

[1410] 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.

[1411] This invention relates to a system that utilizes generative AI and an emotion engine to propose optimal dates and adjust the interface display and proposal content based on the user's emotions in order to streamline the creation of application forms for new non-telecommunications services. This system supports the accurate and speedy creation of application forms by allowing the user to input specific date information and proposing the earliest and latest dates, thereby improving user satisfaction.

[1412] System configuration

[1413] 1. User Interface (Terminal)

[1414] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[1415] It includes a function that uses an emotion engine to recognize the user's emotions and adjust the interface display and suggestions based on those emotions.

[1416] 2. Data receiving module (server)

[1417] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[1418] 3. Analysis module (server)

[1419] The server includes a function to analyze the received date information and obtain the date rule set for the corresponding service.

[1420] 4. Generative AI module (server)

[1421] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[1422] 5. Integrity Verification Module (Server)

[1423] Includes a function to verify the consistency of the results output by generative AI.

[1424] 6. Result presentation module (terminal)

[1425] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[1426] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine.

[1427] 7. Emotion engine module (terminal and server)

[1428] It includes the ability to analyze the user's emotions using voice recognition and facial expression recognition.

[1429] It includes a function to provide data that influences the analysis module and generative AI module based on the analysis results.

[1430] Program processing flow

[1431] Input acceptance and emotion recognition

[1432] Terminal: The user selects the desired service and enters date information via a specified interface. At the same time, the emotion engine analyzes voice or facial expression data to recognize the user's emotions. For example, while entering "November 1, 2023" as the "desired delivery date," the emotion engine recognizes from the user's tone of voice and facial expression that they are feeling stressed.

[1433] Data reception and analysis

[1434] Terminal: Sends input information and emotion data to the server.

[1435] Server: Based on the received data, analyzes the service ID and date information. Emotion data is also included in the analysis.

[1436] Calculating the earliest and latest dates

[1437] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[1438] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the relevant rules. For example, the earliest delivery date is calculated as "November 3, 2023" and the latest delivery date is calculated as "November 15, 2023." At the same time, if the user is stressed, the earlier delivery date will be prioritized.

[1439] Consistency verification and presentation of results

[1440] Server: The calculation result is verified by the consistency verification module. For example, it is verified whether the shortest date is within the date on which the specified service can be provided.

[1441] Device: Receives the results of the earliest and latest delivery dates sent from the server and adjusts the display content based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the device will suggest "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023," as well as play relaxing music and display encouraging messages.

[1442] Specific examples

[1443] Suggested delivery date

[1444] User: Enters "November 1, 2023" as the "Desired Delivery Date" and clicks the send button on the device. The emotion engine detects stress from the user's voice.

[1445] Server: Receives the information "November 1, 2023" and "desired delivery date" along with emotion data, and instructs the generative AI to refer to the relevant rules based on the service identification.

[1446] Generative AI (on the server): Calculates the earliest delivery date as "November 3, 2023" and the latest delivery date as "November 15, 2023." At the same time, prioritizes and suggests shorter delivery dates based on emotional data to reduce stress.

[1447] Server: After verifying the integrity, it sends the calculation results and emotion-based adjustment results to the device.

[1448] Device: Display "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" on the user interface while playing relaxing music or displaying a light, encouraging message.

[1449] The system of the present invention allows users to select dates efficiently and accurately, reducing the workload of sales representatives, and further improves user satisfaction by adjusting the system based on the user's emotional state using the emotion engine.

[1450] The processing flow will be explained below.

[1451] Step 1:

[1452] User: Selects the desired service through a designated interface and enters date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date). For example, enter "November 1, 2023" as the "desired delivery date." At the same time, the emotion engine analyzes the user's facial expressions and voice to recognize their emotions.

[1453] Step 2:

[1454] The device sends the date information and emotion data entered by the user to the server. Specifically, it sends a request including the user's selected date (November 1, 2023) and desired delivery date, as well as emotion data.

[1455] Step 3:

[1456] Server: Analyzes the received request and extracts the service ID and date information. If emotion data is included, it is also included in the analysis. For example, the service ID is "A," the date information is "November 1, 2023," the date type is "Desired delivery date," and the emotion data is "Stress."

[1457] Step 4:

[1458] Server: Based on the extracted service identification information, the corresponding date rule set is sent to the generative AI. The generative AI retrieves the corresponding rules from its internal database. The application of the rules is also adjusted based on the emotion data.

[1459] Step 5:

[1460] Generative AI (on the server): Calculates the earliest and latest delivery dates based on the acquired rule set. For example, the earliest delivery date is calculated as "November 3, 2023" and the latest delivery date is calculated as "November 15, 2023." At the same time, the earliest delivery date is given a higher priority based on emotion data.

[1461] Step 6:

[1462] Server: Receives the calculation results of the earliest and latest dates returned by the generative AI and verifies the consistency of the results. For example, it checks whether the earliest date is actually a date on which the service can be provided.

[1463] Step 7:

[1464] Server: The server sends the calculation results, whose integrity has been confirmed, in JSON format to the device, along with messages and influence factors based on the emotion data.

[1465] Step 8:

[1466] Terminal: Receives and analyzes the JSON data sent from the server. As a result of the analysis, the user interface displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023." Furthermore, if the user is feeling stressed, the device plays relaxing music and displays an encouraging message in a pop-up.

[1467] This is the specific processing flow of the entire system. By linking with the emotion engine, it can respond to the user's emotional state and provide a better user experience.

[1468] Example 2

[1469] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1470] Conventional application form creation systems make it difficult for users to accurately select date information and do not take the user's emotional state into consideration, which can sometimes compromise the user experience. As a result, the application process becomes cumbersome, resulting in problems of reduced user satisfaction. Furthermore, there are also problems with increased workloads for sales representatives and reduced work efficiency. To solve these issues, a system is needed that allows users to easily and quickly enter accurate date information and can adjust according to the user's emotional state.

[1471] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1472] In this invention, the server includes means for a user to input predetermined date information, means for receiving the input date information and user emotion information, means for analyzing the received date information and emotion information and referencing the rules of the relevant service, means for calculating the earliest date and latest date based on the relevant rules and emotion information, means for verifying the consistency of the calculation results, means for presenting the calculation results whose consistency has been confirmed to the user, and means for adjusting the display content of the interface in accordance with the user's emotional state. This allows the user to accurately and quickly select date information, and adjustments are made based on the user's emotional state, thereby improving user satisfaction and reducing the burden on sales representatives, thereby improving work efficiency.

[1473] "Date information" is information about specific dates such as the application date, desired start date of use, desired start date of billing, activation date, and desired delivery date that the user enters when filling out an application form for a service.

[1474] "Emotion information" is information about the user's emotional state that is analyzed by the emotion engine from the user's voice, facial expressions, and the like.

[1475] The "receiving means" refers to a hardware and software configuration for transmitting date information and emotion information input by the user to the server and receiving the information.

[1476] The "analysis means" refers to a hardware and software configuration for analyzing the received date information and emotion information and referencing the rules of the corresponding service based on the analysis.

[1477] "Generative AI" is an artificial intelligence model that calculates the earliest and latest dates based on received data according to specific rules.

[1478] A "means for calculating" is a hardware and software configuration for calculating the earliest and latest dates based on applicable rules and sentiment information.

[1479] The "means for verifying consistency" is a hardware and software configuration for checking whether the generated earliest and latest dates match pre-set conditions.

[1480] The "presentation means" refers to a hardware and software configuration for displaying the results of the earliest and latest dates for which consistency has been confirmed on a user interface and providing feedback to the user.

[1481] The "adjusting means" refers to a hardware and software configuration that adjusts the interface display content according to the user's emotional state, thereby improving user satisfaction.

[1482] This invention is a system that utilizes generative AI and an emotion engine to streamline the creation of application forms for new non-communication services and propose optimal dates based on the user's emotions. This system aims to not only support the accurate and speedy creation of application forms by allowing the user to input specific date information and proposing the earliest and latest dates, but also to improve user satisfaction.

[1483] System configuration

[1484] 1. User Interface (Terminal)

[1485] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[1486] It is equipped with an emotion engine that analyzes the user's voice and facial expression data to recognize the user's emotions.

[1487] 2. Data receiving module (server)

[1488] This module receives data entered by the user and includes a function to perform initial processing of the data. SSL is used to receive the data, ensuring its security.

[1489] 3. Analysis module (server)

[1490] The server analyzes the received date and emotion information and acquires the corresponding date rule set for the service. For example, the rule set for "Delivery Service" includes the conditions for "Shortest Shipping Date" and "Latest Shipping Date."

[1491] 4. Generative AI module (server)

[1492] Based on the analyzed data, the system calculates the earliest and latest dates based on the corresponding rules and sentiment information. For example, for a desired delivery date, "November 3, 2023" is calculated as the earliest date and "November 15, 2023" as the latest date.

[1493] 5. Integrity Verification Module (Server)

[1494] This includes a function to verify the consistency of the results output by the generative AI, checking whether the calculated earliest and latest dates match pre-set conditions.

[1495] 6. Result presentation module (terminal)

[1496] Includes a function to present the results of the earliest and latest dates for which consistency was confirmed to the user.

[1497] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine. For example, if the user is feeling stressed, it will display relaxing music or an encouraging message.

[1498] 7. Emotion engine module (terminal and server)

[1499] It includes the ability to analyze the user's emotions using voice recognition and facial expression recognition.

[1500] Based on the analysis results, data is provided that influences the analysis module and generative AI module.

[1501] Specific examples

[1502] Suggested delivery date

[1503] User: Enters "November 1, 2023" as the "Desired Delivery Date" and clicks the send button on the device. The emotion engine detects stress from the user's tone of voice and facial expression.

[1504] Device: Sends the entered "November 1, 2023" and emotion data to the server.

[1505] Server: Receives these data and retrieves the date rule set from the database. The emotion engine provides the analysis results and reflects the user's stress state.

[1506] Generative AI (server): Calculates "November 3, 2023" as the earliest date and "November 15, 2023" as the latest date, and at the same time, prioritizes "November 3, 2023" to reduce stress.

[1507] Server: Performs consistency verification and sends the results to the terminal via the result presentation module.

[1508] Device: Shows the suggested delivery date of November 3, 2023, and November 15, 2023, and plays relaxing music and displays an encouraging message.

[1509] Prompt Sentence Examples

[1510] "I'd like delivery on November 1, 2023, what are the earliest and latest dates? Can you please let me know if there is a preferred date to alleviate some of the stress?"

[1511] This system allows users to select date information efficiently and accurately, reducing the workload of sales representatives. The emotion engine adjusts according to the user's emotional state, further improving user satisfaction.

[1512] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1513] Step 1:

[1514] Terminal: The user selects the type of service and enters the required date information (e.g., application date, desired start date of use, desired start date of billing, desired delivery date) into the application form. The emotion engine simultaneously collects the user's voice and facial expressions and analyzes their emotional state. For example, if the user enters "November 1, 2023" as the "desired delivery date," the emotion engine simultaneously detects stress from the user's tone of voice and facial expression. This allows the input information (desired delivery date) and emotional data (stress level) to be collected.

[1515] Step 2:

[1516] Terminal: The input date information and emotion information are packaged and sent to the server via the data receiving module. The input data includes the user-entered "Desired delivery date of November 1, 2023" and the analyzed emotion data (e.g., stress level). The output is the sent data package.

[1517] Step 3:

[1518] Server: The data receiving module receives the date and emotion information and performs an initial analysis. This involves checking the data format and identifying any incomplete information. The received data includes the desired delivery date of November 1, 2023 and the stress level, and the data is output after being confirmed to be consistent.

[1519] Step 4:

[1520] Server: The analysis module retrieves the relevant date rule set from the database based on the service identification information. For example, a rule set for "Delivery Service" includes the conditions "Earliest Shipping Date" and "Latest Shipping Date." The input data are the consistency-checked date information and emotion data, and the output is a date rule set.

[1521] Step 5:

[1522] Server: The emotion engine provides the analysis results (e.g., the user's stress level) to the generative AI module, allowing it to make adjustments based on specific emotional states. For example, if the stress level is high, the generative AI can be configured to prioritize a faster delivery date. The input data is the emotion analysis results, and the output is the adjusted conditions.

[1523] Step 6:

[1524] Server: The generative AI module calculates the earliest and latest dates based on the date rule set and the sentiment analysis results. For example, the calculation results output "November 3, 2023" as the earliest date and "November 15, 2023" as the latest date. The input data are the rule set and the sentiment analysis results, and the output is the calculated earliest and latest dates.

[1525] Step 7:

[1526] Server: The consistency verification module receives the calculation results from the generative AI and checks whether the calculated date matches the pre-defined conditions. For example, it checks whether "November 3, 2023" and "November 15, 2023" are within the service availability period. The input data are the earliest and latest dates, and the output is the verified date.

[1527] Step 8:

[1528] Server: The result presentation module sends the results of the earliest and latest dates that have been verified to the user interface. The input data is the validated date, and the output is the date data for presentation.

[1529] Step 9:

[1530] Terminal: The user interface displays "Earliest delivery date: November 3, 2023, Latest delivery date: November 15, 2023" and plays relaxing music and encouraging messages based on the analysis results of the emotion engine. The input data is the date data to be presented and the emotion analysis results, and the output is the displayed content.

[1531] In this way, the user can accurately and quickly select date information and receive feedback according to their emotional state.

[1532] (Application example 2)

[1533] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1534] Conventional systems can suggest optimal dates based on the date information entered by the user, but they often result in low user satisfaction because the suggestions do not take into account the user's emotional state. Furthermore, while there is a need for systems to make more appropriate suggestions to users by utilizing emotional information obtained from facial expressions and voice, there is currently a lack of a mechanism to achieve this.

[1535] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing predetermined date information and emotions of the user, means for receiving the input date information and emotion data, means for analyzing the received date information and emotion data and referencing the rules of the relevant service based on generative AI, means for calculating the earliest date and latest date based on the relevant rules and adjusting the proposal content based on the emotion, means for verifying the consistency of the calculation results, and means for presenting the calculation results whose consistency has been confirmed and the adjusted proposal content to the user. This enables optimal date suggestions and feedback according to the user's emotional state, thereby increasing user satisfaction.

[1536] The "means for analyzing the user's specified date information and emotions" refers to a device or software that analyzes the user's emotional state using voice recognition and facial expression recognition in addition to the date information entered by the user.

[1537] The "means for receiving input date information and emotion data" refers to a device or software for receiving date information and emotion data sent from the user and transferring them to the server.

[1538] "Means for analyzing received date information and emotion data and referencing the rules of the relevant service based on generative AI" refers to devices or software that analyzes the date information and user emotion data received by the server and uses generative AI to refer to the service rules based on that information.

[1539] "Means for calculating the earliest and latest dates based on the relevant rules and adjusting the content of the proposal based on emotions" refers to devices or software that allow the generative AI to adjust the content of the proposal based on the earliest and latest dates calculated in accordance with the service rules, taking into account the user's emotional state.

[1540] "Means for verifying the consistency of calculation results" refers to devices or software for verifying whether the earliest and latest dates calculated by generative AI match pre-set conditions and rules.

[1541] "Means for presenting to the user the calculation results whose consistency has been confirmed and the adjusted proposal content" refers to a device or software for visually or audibly presenting to the user the calculation results whose consistency has been confirmed and the proposal content that has been adjusted based on the user's emotional state.

[1542] "Means for analyzing emotions" refers to devices or software for analyzing a user's emotional state using technologies such as voice recognition and facial expression recognition.

[1543] "Date information" is information relating to a specific date entered by the user, such as the application date, desired start date of use, desired start date of billing, activation date, or desired delivery date.

[1544] The system for implementing the present invention provides a terminal for users to input specified date information and emotions, a server that analyzes the received data, calculates the earliest and latest dates using generative AI, and adjusts the suggestions based on the user's emotions, and a function that verifies the consistency of these calculation results before presenting them to the user.

[1545] System configuration

[1546] 1. User Interface (Terminal):

[1547] This includes functionality to provide a form for users to select a service and enter date information (application date, desired start date of use, desired start date of billing, activation date, desired delivery date).

[1548] It includes a function that uses an emotion engine to recognize the user's emotions and adjust the interface display and suggestions based on those emotions.

[1549] 2. Data receiving module (server):

[1550] This module receives data entered by the user and includes an initial processing function for analyzing the data.

[1551] 3. Analysis module (server):

[1552] The server analyzes the received date information and emotion data, and includes a function to obtain the date rule set for the corresponding service.

[1553] 4. Generative AI module (server):

[1554] Includes functionality to calculate the earliest and latest dates based on the parsed data and according to applicable rules.

[1555] 5. Integrity Verification Module (Server):

[1556] Includes a function to verify the consistency of the results output by generative AI.

[1557] 6. Result presentation module (terminal):

[1558] Includes the ability to present the earliest and latest dates on which consistency was confirmed to the user.

[1559] It includes a function to adjust the content presented and provide feedback to the user based on the user's emotions analyzed by the emotion engine.

[1560] Program processing

[1561] Input acceptance and emotion recognition

[1562] Terminal: The user selects the desired service and enters date information through a designated interface. At the same time, the emotion engine analyzes voice or facial expression data to recognize the user's emotions.

[1563] Data reception and analysis

[1564] Terminal: Sends input information and emotion data to the server.

[1565] Server: Analyzes the service ID and date information based on the received data. Emotion data is also included in the analysis.

[1566] Calculating the earliest and latest dates

[1567] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[1568] Generative AI: Calculates the earliest and latest dates based on applicable rules.

[1569] Consistency verification and presentation of results

[1570] Server: The calculation result is verified by the integrity verification module.

[1571] Device: Receives the results of the earliest and latest dates sent from the server and adjusts the display content based on the sentiment.

[1572] Hardware and software used

[1573] Smartphone: A device that installs applications and accepts user input.

[1574] Emotion Recognition Library:

[1575] Software that analyzes emotions using voice and facial recognition (e.g., Emotion Recognition Library).

[1576] Generative AI libraries:

[1577] Software that calculates dates based on service identifiers and date rules (e.g., AI Date Generator Library).

[1578] Flask: A framework used to implement server-side applications and provide APIs.

[1579] Specific examples

[1580] As a concrete example, in the case of an "e-commerce website date selection assistant app," if a user inputs "November 1, 2023" as the desired delivery date, the emotion engine recognizes from the voice that the user is feeling stressed. The server analyzes the received data, and the generative AI calculates the earliest and latest delivery dates based on the service rules. For example, the earliest delivery date is calculated as "November 3, 2023," and the latest delivery date as "November 15, 2023." At the same time, the system suggests prioritizing the faster delivery date based on the emotion data to reduce stress. The user interface also plays relaxing music and displays encouraging messages.

[1581] Prompt Sentence Examples

[1582] Specific examples of prompt sentences are shown below.

[1583] "SERVICE_TYPE: Delivery Service PREFERRED_DATE: 2023-11-01 USER_EMOTION: Stress level 80, Happiness level 20"

[1584] By feeding this prompt into a generative AI model, the results are tailored date suggestions based on emotional data.

[1585] The above is an embodiment of the present invention. The present invention makes it possible to provide optimal date suggestions and feedback according to the emotional state of the user, and is expected to have the effect of increasing user satisfaction.

[1586] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1587] Step 1:

[1588] Input reception

[1589] User: The user selects the desired service and enters date information via a specified interface. For example, the user enters "November 1, 2023" as the "desired delivery date."

[1590] Input data: Date information (e.g., "November 1, 2023"), user voice data, and user facial expression image data.

[1591] Output data: The date information entered by the user and the collected emotion data are saved on the device.

[1592] Step 2:

[1593] emotion recognition

[1594] Device: The emotion engine analyzes voice data and facial expression image data to recognize the user's emotions.

[1595] Input data: User's voice data, user's facial expression image data.

[1596] Specific operation: Using a voice recognition library and an facial expression recognition library, the system quantifies emotional states (e.g., stress level, happiness) from changes in voice tone and facial expressions.

[1597] Output data: Emotion data (e.g. stress level 80, happiness level 20) is generated.

[1598] Step 3:

[1599] Data reception

[1600] Terminal: Sends the entered date information and emotion data to the server.

[1601] Input data: User-entered date information and parsed emotion data.

[1602] Specific operation: Sends input data to a server via the Internet using an HTTP POST request.

[1603] Output data: The server receives the date information and emotion data.

[1604] Step 4:

[1605] Data analysis

[1606] Server: Based on the received data, analyzes the service ID and date information. Emotion data is also included in the analysis.

[1607] Input data: date information, emotion data.

[1608] Specific operation: The rule set for the relevant service is retrieved from the database, and the date information and emotion data are processed using the analysis engine.

[1609] Output data: Parsed service ID, analysis result date, and emotion data.

[1610] Step 5:

[1611] Date arithmetic

[1612] Server: Based on the service identification information, the server sends the corresponding date rule set to the generative AI. The results of the emotion engine's analysis are also provided to the generative AI, which then adjusts the suggestions for specific emotional states (e.g., high stress).

[1613] Input data: service identification information, analysis result date information, emotion data.

[1614] What it does: Uses a generative AI model to calculate the earliest and latest delivery dates based on a set of rules. Optimizes recommendations based on sentiment data.

[1615] Output data: Calculated earliest and latest dates, adjusted proposal.

[1616] Step 6:

[1617] Integrity Verification

[1618] Server: The calculation result is verified by the integrity verification module, for example, to ensure that the calculated date is within the range of the service.

[1619] Input data: The calculated earliest and latest dates.

[1620] Specific behavior: Checks whether the calculated date is valid according to the service provision rules.

[1621] Output data: Calculation results with consistency checked.

[1622] Step 7:

[1623] Results presentation

[1624] Device: Receives the results of the earliest and latest dates sent from the server and adjusts the display content based on the user's emotions. For example, displaying relaxing music or encouraging messages to a user who is feeling stressed.

[1625] Input data: Consistent calculations and adjusted proposals.

[1626] Specific behavior: The calculation results are displayed in the user interface and feedback is provided according to the emotional data.

[1627] Output: The suggestions presented to the user visually or audibly.

[1628] The above are the specific processing steps for implementing the present invention. This enables optimal date suggestions and feedback based on the user's emotional state, which is expected to increase user satisfaction.

[1629] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1630] 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.

[1631] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1632] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1633] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1634] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1635] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1636] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1637] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1638] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1639] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1640] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1641] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1642] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1643] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1644] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1645] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1646] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1647] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1648] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1649] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1650] The following is further disclosed regarding the above embodiment.

[1651] (Claim 1)

[1652] A means for a user to input predetermined date information;

[1653] means for receiving input date information;

[1654] A means for analyzing the received date information and referencing the rules of the corresponding service based on generative AI;

[1655] means for calculating the earliest and latest dates based on the applicable rules;

[1656] A means for verifying the consistency of the calculation results;

[1657] A system including a means for presenting to a user the results of a calculation whose integrity has been confirmed.

[1658] (Claim 2)

[1659] 2. The system according to claim 1, wherein the date information includes at least one of an application date, a desired start date of use, a desired start date of billing, an activation date, and a desired delivery date.

[1660] (Claim 3)

[1661] The system according to claim 1, characterized in that as a means for verifying the consistency of the calculation results, it is confirmed whether the calculated shortest date and latest date match a preset condition.

[1662] "Example 1"

[1663] (Claim 1)

[1664] A means for a user to input predetermined information;

[1665] means for receiving input information;

[1666] A means for analyzing the received information and referencing the rules of the corresponding service based on generative artificial intelligence;

[1667] means for calculating the earliest and latest dates based on applicable rules;

[1668] A means for verifying the consistency of the calculation results;

[1669] A system including a means for presenting the calculation results whose consistency has been confirmed to a user.

[1670] (Claim 2)

[1671] 2. The system according to claim 1, wherein the information includes at least one of an application date, a desired start date, a desired start date, an activation date, and a desired date.

[1672] (Claim 3)

[1673] The system according to claim 1, characterized in that as a means for verifying the consistency of the calculation results, it is confirmed whether the calculated earliest date and latest date match a predetermined condition.

[1674] "Application Example 1"

[1675] (Claim 1)

[1676] A means for a user to input predetermined date information;

[1677] means for receiving input date information;

[1678] A means for analyzing the received date information and referencing the rules of the corresponding service based on generative AI;

[1679] means for calculating the earliest and latest dates based on applicable rules;

[1680] a means for adjusting and verifying the results of the calculations;

[1681] 1. A system including: a means for presenting the adjusted calculation results to a user,

[1682] The system includes a means for users to input their desired delivery time, use generative AI to calculate optimal departure and arrival times, and notify food service providers and delivery staff.

[1683] (Claim 2)

[1684] 2. The system according to claim 1, wherein the date information includes at least one of an application date, a desired start date of use, a desired start date of billing, an activation date, and a desired delivery date.

[1685] (Claim 3)

[1686] The system according to claim 1, characterized in that as a means for adjusting and verifying the calculation results, it is confirmed whether the calculated shortest date and latest date match a predetermined condition.

[1687] "Example 2: Combining Emotion Engines"

[1688] (Claim 1)

[1689] A means for a user to input predetermined date information;

[1690] means for receiving input date information and user emotion information;

[1691] A means for analyzing the received date information and emotion information and referencing the rules of the corresponding service;

[1692] means for calculating earliest and latest dates based on applicable rules and sentiment information;

[1693] A means for verifying the consistency of the calculation results;

[1694] a means for presenting the calculation results whose consistency has been confirmed to a user;

[1695] A system including means for adjusting the displayed content of an interface in response to the emotional state of a user.

[1696] (Claim 2)

[1697] 2. The system according to claim 1, wherein the date information includes at least one of an application date, a desired start date of use, a desired start date of billing, an activation date, and a desired delivery date.

[1698] (Claim 3)

[1699] The system according to claim 1, characterized in that as a means for verifying the consistency of the calculation results, it is confirmed whether the calculated shortest date and latest date match a preset condition.

[1700] "Application example 2 when combining emotion engines"

[1701] (Claim 1)

[1702] A means for a user to input predetermined date information and analyze emotions;

[1703] means for receiving input date information and emotion data;

[1704] A means for analyzing the received date information and emotion data and referencing the rules of the corresponding service based on generative AI;

[1705] a means for calculating the earliest and latest dates based on the applicable rules and adjusting the suggestions based on sentiment;

[1706] A means for verifying the consistency of the calculation results;

[1707] The system includes a means for presenting the consistency-checked calculation results and adjusted proposals to the user.

[1708] (Claim 2)

[1709] The system according to claim 1, characterized in that the date information includes at least one of the application date, desired start date of use, desired start date of billing, activation date, and desired delivery date, and that voice recognition and facial expression recognition are used for emotion analysis.

[1710] (Claim 3)

[1711] The system described in claim 1, characterized in that as a means of verifying the consistency of the calculation results, it checks whether the calculated earliest and latest dates match pre-set conditions and adjusts the presentation of the results based on the user's feelings. [Explanation of symbols]

[1712] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to input predetermined date information; means for receiving input date information; A means for analyzing the received date information and referencing the rules of the corresponding service based on generative AI; means for calculating the earliest and latest dates based on applicable rules; A means for verifying the consistency of the calculation results; A system including a means for presenting to a user the results of a calculation whose integrity has been confirmed.

2. 2. The system according to claim 1, wherein the date information includes at least one of an application date, a desired start date of use, a desired start date of billing, an activation date, and a desired delivery date.

3. 2. The system according to claim 1, wherein the means for verifying the consistency of the calculation result is to check whether the calculated shortest date and latest date match a preset condition.

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