System

Abstract

A system is provided.SOLUTION: A system comprising: means for allowing a user to input information about a current communication plan, call and data communication usage, and desired conditions; means for collecting and transmitting the input information from the user to a server; means for analyzing the information at the server and calculating an optimal communication plan using a generative artificial intelligence model; and means for displaying the calculated optimal communication plan to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The present invention aims to solve the problem of users finding a communication plan that is optimal for them. Because there are a wide variety of communication plan options, and each plan's offerings and pricing structures are complicated, choosing the appropriate plan takes time and effort. Furthermore, it is difficult for users to find a plan that suits their individual usage situation and desired conditions, and as a result, they may end up signing up for an inappropriate plan. This leads to a decrease in user satisfaction and an increase in cancellation rates for service providers. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the present invention provides the following means. First, a means is provided for allowing a user to input information regarding their current communication plan, voice and data communication usage, and desired conditions. Next, a means is provided for collecting the information input by the user and sending it to a server. Furthermore, a means is provided for the server to analyze this information and calculate the optimal communication plan using a generative AI model. Finally, a means is provided for displaying the calculated optimal plan to the user. This allows the user to easily find the plan that best suits their usage and desired conditions, thereby improving user satisfaction.

[0006] "User" means an individual or legal entity that uses a communication plan.

[0007] A "communication plan" is a contract type that provides a set of services such as voice calls, data communications, and messaging.

[0008] "Call" is a service that allows you to communicate with others through voice.

[0009] "Data communications" refers to the service of sending and receiving digital data via the Internet or applications.

[0010] "Server" means a central processing unit for receiving and analyzing information sent by users.

[0011] "Analysis" is the process of categorizing and evaluating data collected from users into meaningful information.

[0012] A "generative AI model" is an artificial intelligence algorithm that analyzes user input data and derives the optimal communication plan.

[0013] "Information" refers to data including the user's current communication plan, voice and data usage, and desired terms.

[0014] "Means" is a general term that refers to a method or apparatus for accomplishing a particular function or role.

[0015] The "optimal communication plan" is the communication plan that best suits the user's usage situation and desired conditions. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention is a system that utilizes a generative AI model to propose the optimal communication plan based on the user's smartphone usage status and desired conditions. This system is mainly composed of a user, a terminal, and a server, and is implemented in the following form.

[0038] First, the device displays a questionnaire to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required services, etc.). Once the user has completed the input, the device collects this information as a single data set and sends it to the server.

[0039] Next, the server receives the user's data sent from the device. The received data includes the user's current communication plan, call usage, data usage, desired service, desired rate range, etc. The server uses a generative AI model to analyze this data. The generative AI model calculates the optimal communication plan based on the user's data. This model includes an algorithm that derives the optimal plan by taking into account multiple factors related to the user's data usage, call duration, and budget, for example.

[0040] The server uses the generative AI model to calculate the optimal communication plan, and then sends the results to the device, including details of the communication plan it determines to be optimal (plan name, monthly fee, data volume, additional services, etc.).

[0041] Finally, the device displays the information on the optimal plan received from the server to the user, allowing the user to select the plan that best suits them.

[0042] Specific examples

[0043] A user is currently using "Plan A," which includes 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen.

[0044] (Device) collects the following information from you:

[0045] Current communication plan: Plan A

[0046] Call usage: 100 minutes per month

[0047] Data usage: 5GB per month

[0048] Desired service: Unlimited data plan

[0049] Desired price range: Up to 4,000 yen per month

[0050] This information is sent to a server, which then analyzes the data using a generative AI model. For example, the model considers the user's data volume, call duration, and budget to calculate the optimal plan, such as a "value plan" that includes unlimited data and international calls for 3,000 yen per month.

[0051] (Server) sends this "Special Offer" information to (Device), and the Device displays the following to the user:

[0052] Best plan: Value plan

[0053] Monthly fee: 3,000 yen

[0054] Data capacity: Unlimited

[0055] International calls: Yes

[0056] This allows users to easily find the best communication plan for them. Through this system, users can select the best plan while saving time and effort.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] (Device) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.).

[0060] Step 2:

[0061] The user follows the question form displayed on the terminal to input information about the communication plan currently in use, the amount of call usage, the amount of data usage, the desired service content, and the desired rate range.

[0062] Step 3:

[0063] (Terminal) collects the information entered by the user, compiles it into a single data set, and sends it to the server.

[0064] Step 4:

[0065] (Server) receives the user's dataset sent from the device and prepares it for analysis.

[0066] Step 5:

[0067] The server inputs the received user data into the generative AI model, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes multiple factors, such as the user's data volume, call duration, and rate band.

[0068] Step 6:

[0069] The server sends the optimal plan information obtained from the generative AI model to the device. The optimal plan information includes the plan name, monthly fee, data capacity, and additional service details.

[0070] Step 7:

[0071] The terminal displays the information about the optimal plan received from the server to the user.

[0072] Step 8:

[0073] The user checks the information about the optimal plan displayed on the device and selects the plan that best suits their usage situation and desired conditions.

[0074] Example 1

[0075] 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."

[0076] The problem with the traditional method of selecting a communication plan is that users have to manually search for the best plan based on their usage and desired conditions, which is a time-consuming and labor-intensive process. Furthermore, it is difficult to determine whether the selected plan is truly optimal for the user, and in some cases, users may end up choosing an inappropriate plan. This often leaves users unsure about communication costs and service satisfaction.

[0077] 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.

[0078] In this invention, the server includes means for prompting a user to input information regarding their current communication plan, their voice and data communication usage status, and their desired conditions, means for collecting the information input by the user and sending it to the server, means for the server to analyze the information and calculate an optimal communication plan using a generative artificial intelligence model, and means for displaying the calculated optimal communication plan to the user. This allows the user to automatically receive optimal communication plans and quickly and easily select the plan that best suits their usage status and desired conditions.

[0079] A "user" is an individual who uses the system to input their own communication plan, usage status, and desired conditions.

[0080] "Communication plan" refers to the specific plan details for the communication service to which the user has subscribed, including fees, data capacity, call time, etc.

[0081] "Usage status" refers to information that indicates how much a user actually uses a communication service, such as the amount of call time and data usage.

[0082] "Desired conditions" refer to the specific requirements and conditions that a user has for a communication plan, such as the price range they desire and the services they require.

[0083] "Terminal" refers to an electronic device that a user uses to input information and send it to a server. Examples include smartphones and personal computers.

[0084] The "server" is a central computer system that receives information sent from the terminal, analyzes it using a generative artificial intelligence model, and calculates the optimal communication plan.

[0085] A "generative artificial intelligence model" is a machine learning model equipped with an algorithm for deriving the optimal communication plan based on information entered by the user.

[0086] The "optimal communication plan" is the communication plan that the system determines to be the most suitable in terms of cost, service content, etc. based on the user's usage and desired conditions.

[0087] This invention is a system that uses a generative AI model to propose an optimal communication plan based on the user's usage status and desired conditions. This system is mainly composed of a user, a terminal, and a server, and is implemented in the following form.

[0088] First, the user accesses the inquiry form using their device. This inquiry form is created using HTML, CSS, and JavaScript, and provides an interface that allows users to intuitively enter information. Specifically, the user enters information such as their current communication plan, monthly call time, data communication usage, desired service, and desired price range. For example, "Communication plan name: Plan A," "Call time: 100 minutes," "Data communication amount: 5GB," "Desired service: Unlimited data," and "Desired price range: 4,000 yen or less."

[0089] As the user enters information, the device collects this data as a dataset and sends it to the server using an HTTP POST request. The device-side program is implemented in JavaScript, and this dataset contains all the entered information.

[0090] This data is then received by a server. Built using a web framework such as Node.js or Python's Flask, the server receives the data via HTTP requests. The server analyzes the received data and cleanses and normalizes it as necessary. It then uses a generative AI model (for example, a model using TensorFlow or PyTorch) to analyze the data. This generative AI model contains algorithms that derive the optimal communication plan based on the user's data usage, call duration, and desired conditions.

[0091] As a concrete example, the following prompt sentences can be input to a generative AI model:

[0092] "The user's current data plan is "Plan A," which allows for 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen. Please suggest the best data plan that meets these conditions."

[0093] Once the generative AI model calculates the optimal data plan, the result is converted into a data format such as JSON and sent to the device as an HTTP response, which includes the name of the optimal plan, the monthly fee, data volume, and details of additional services.

[0094] Finally, the device analyzes the data received from the server and displays it in an easy-to-read format for the user. This display is stylishly formatted using HTML and CSS. For example, information such as "Value Plan," "Monthly Fee: 3,000 yen," "Data Capacity: Unlimited," and "International Calls: Available" is displayed in list format. Using this information, users can select the communication plan that best suits them.

[0095] Through this system, users can easily find the communication plan that best suits their usage and desired conditions, while saving time and effort.

[0096] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0097] Step 1:

[0098] (User) enters information into a question form.

[0099] The user opens a browser on their device and accesses the inquiry form. The form has drop-down menus and radio buttons, and they input information in order, such as "Plan name: Plan A," "Call time: 100 minutes," "Data amount: 5GB," "Desired service: Unlimited data," and "Desired price range: 4,000 yen or less." The information entered by the user becomes the input data for the system.

[0100] Step 2:

[0101] (Device) collects input data and creates an HTTP POST request.

[0102] When the user clicks the "Submit" button, JavaScript is executed to combine the input data into a single data object. This data object contains all the information entered by the user. The device then sends this data object to the server as an HTTP POST request. It generates a JSON-formatted request body based on the input data, and the output is a request to the server.

[0103] Step 3:

[0104] (Server) receives the HTTP POST request and parses the data.

[0105] The server receives HTTP requests using a web framework such as Node.js or Python's Flask. It takes the received data and, if necessary, cleanses the input data (for example, by removing unnecessary whitespace or symbols) and normalizes it (for example, by standardizing the data format). In this process, the input data is parsed and converted into a format suitable for the AI ​​model. The output of the parsing process becomes the input data for the generative AI model.

[0106] Step 4:

[0107] (Server) analyzes the data using a generative AI model and calculates the optimal communication plan.

[0108] The server runs a generative AI model using AI frameworks such as TensorFlow and PyTorch. The analyzed data is input into the AI ​​model, which then calculates the optimal communication plan based on multiple factors (data volume, call duration, budget, etc.). The output of the generative AI model is detailed information about the optimal communication plan for the user (plan name, monthly fee, data volume, additional services, etc.).

[0109] Step 5:

[0110] (Server) sends details of the optimal communication plan to the device.

[0111] The server converts the detailed information obtained from the generative AI model into a data format such as JSON, and sends this to the device as an HTTP response. The output of the conversion process becomes the response data sent to the device.

[0112] Step 6:

[0113] (Device) receives the response from the server and displays it to the user.

[0114] The device uses JavaScript to analyze the data received from the server and reflects it in HTML. For example, information such as "Value Plan," "Monthly Fee: 3,000 yen," "Data Capacity: Unlimited," and "International Calls: Available" is displayed on the screen in list format. In this process, the response data is converted into a format that is easy for the user to understand and displayed on the screen. The output of the display process becomes the communication plan information presented to the user.

[0115] (Application example 1)

[0116] 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."

[0117] In recent years, the use of online shopping has increased dramatically, but many users spend a lot of time and effort trying to find the best purchase plan and discount information. To solve this problem, a system that automatically suggests the best purchase plan based on the user's shopping habits and desired conditions is needed. However, current systems do not effectively utilize the user's detailed shopping history or individual desired conditions, making it difficult to find the best plan.

[0118] 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.

[0119] In this invention, the server includes a means for prompting a user to input information about their current purchase plan, shopping habits, and desired conditions, a means for collecting the information input by the user and sending it to the server, a means for the server to analyze the information and calculate an optimal purchase plan using a generative artificial intelligence model, and a means for displaying details of the optimal purchase plan to the user, thereby enabling the user to easily find a purchase plan optimized to their shopping habits and desires, thereby saving time and effort.

[0120] A "user" is someone who uses this system to receive the optimal purchase plan.

[0121] "Purchase Plan" means a purchase option optimized for a User when purchasing an item online, including fees, discounts, subscription services, etc.

[0122] "Shopping habits" refers to the behavioral patterns of how a user typically purchases products, including purchase frequency and product category preferences.

[0123] "Desired conditions" are the specific requirements that a user has for a purchase plan, including price, type of product, and service content.

[0124] "Means for inputting information" refers to the interface that allows users to input information such as their current purchasing status and desired conditions into the system.

[0125] "Means for collecting information and transmitting it to the server" refers to the technical means by which the information entered by the user is compiled into a single data set and transmitted to the server.

[0126] "Means for analyzing the information on the server and calculating the optimal purchase plan using a generative AI model" refers to technology that enables a server to analyze information input by a user using a generative AI model and calculate the optimal purchase plan.

[0127] The "means for displaying the optimal purchase plan to the user" refers to an interface for visually presenting to the user the details of the optimal purchase plan calculated by the server.

[0128] "Generative AI model" refers to a machine learning algorithm used to analyze collected data and generate optimal suggestions for users.

[0129] To implement this invention, it is necessary to build a system that proposes optimal purchase plans based on the user's shopping habits and desired conditions. This system is mainly composed of a user terminal and a server.

[0130] First, the user terminal provides an interface that allows the user to input information about their current purchase plan, shopping habits, and desired conditions. This interface is realized by an application installed on a device such as a smartphone, smart glasses, a head-mounted display, or a personal robot.

[0131] Once the user has finished entering the information, the device collects this information as a single data set and sends it to the server. This communication must be secure and efficient, so for example, the HTTPS protocol is used.

[0132] The server uses a generative AI model to analyze the dataset received from the user. This generative AI model includes an algorithm that considers various factors (e.g., the user's shopping history, purchase frequency, desired conditions, etc.) to calculate the optimal purchase plan. Specifically, the server is built using the Node.js and Express.js frameworks and uses OpenAI's generative AI model.

[0133] For example, if a user provides the following information:

[0134] Current purchase plan: 10 items per month

[0135] Shopping habits: Often look for discounts in advance

[0136] Desired conditions: Monthly budget of 5,000 yen, purchase once a week

[0137] With this information, the server prompts the generative AI model with the following prompt:

[0138] Example prompt sentence:

[0139] Your current purchasing situation: 10 items purchased per month

[0140] Your shopping habits: I often look for discounts in advance

[0141] Your budget: Your monthly budget is 5,000 yen.

[0142] Your purchase frequency: Once a week

[0143] Please take the above into consideration and suggest the best purchase plan for you.

[0144] Based on these prompts, the generative AI model recommends the best purchasing plan for the user's needs, including the best subscription services, discount offers, and bulk buying options.

[0145] Finally, the information on the optimal purchase plan obtained from the server is sent to the user's device and visually displayed, allowing the user to easily find a purchase plan that is optimized for their shopping habits and preferences.

[0146] This system allows users to save time and effort while choosing the most suitable purchasing option.

[0147] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0148] Step 1:

[0149] The user inputs information about their current purchase plan, shopping habits, and desired conditions into the terminal, including their current purchase plan (e.g., buying 10 items per month), shopping habits (e.g., often looking for discounts in advance), and desired conditions (e.g., monthly budget of 5,000 yen, purchase frequency once a week).

[0150] Step 2:

[0151] The device collects the information entered by the user as a single data set and sends it to the server. This data set includes all of the user's input information. For example, the input data is configured in JSON format and sent securely to the server using the HTTPS protocol.

[0152] Step 3:

[0153] The server receives the data set sent from the device and analyzes this information with the generative AI model. At this time, the received data is converted into a prompt sentence and sent to the generative AI model. For example, the following prompt sentence is generated:

[0154] Your current purchasing situation: 10 items purchased per month

[0155] Your shopping habits: I often look for discounts in advance

[0156] Your budget: Your monthly budget is 5,000 yen.

[0157] Your purchase frequency: Once a week

[0158] Please take the above into consideration and suggest the best purchase plan for you.

[0159] The server sends this prompt to OpenAI's generative AI model and receives the AI ​​model's response.

[0160] Step 4:

[0161] The generative AI model generates the optimal purchase plan based on prompts sent by the server. The model analyzes factors such as the user's shopping habits, budget, and purchase frequency to calculate the optimal purchasing options (e.g., subscription services or discount offers). The output is returned to the server as a text response.

[0162] Step 5:

[0163] The server extracts and organizes the details of the most suitable purchase plan based on the response received from the generative AI model, and performs additional processing (e.g., converting the response format or filtering the information) as needed. Finally, it generates a dataset to display to the user.

[0164] Step 6:

[0165] The server sends the generated optimal purchase plan dataset to the terminal, which includes details of the purchase plan (e.g., subscription service type, discount rate, fee, etc.).

[0166] Step 7:

[0167] The terminal displays the information on the optimal purchase plan received from the server to the user. The user can check the plan details visually displayed on the terminal screen and select the optimal purchase option. This allows the user to efficiently make purchases based on the purchase plan optimized for their needs.

[0168] 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.

[0169] This invention combines a system that utilizes a generative AI model to propose the optimal communication plan based on the user's smartphone usage status and desired conditions with an emotion engine that recognizes the user's emotions. This system is composed of a user, a terminal, a server, and an emotion engine, and is implemented in the following form.

[0170] First, the (terminal) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.). The (user) enters this information according to the question form displayed on the terminal.

[0171] (Device) collects the information entered by the user, compiles it into a single data set, and sends it to the server. (Server) receives the user data sent from the device and prepares it for analysis.

[0172] The server inputs the received user data into a generative AI model and runs the model to calculate the optimal communication plan. This generative AI model includes an algorithm that analyzes multiple factors, such as the user's data volume, call duration, and rate band, to derive the optimal plan.

[0173] Furthermore, the present invention adds an emotion engine. The emotion engine analyzes the user's emotional state based on the user's input data and interactions. The analysis results are used to optimize communication plans using a generative AI model. For example, if the user is under stress, the emotion engine provides that information to the server, which can then make suggestions to help the user relax.

[0174] The server sends the optimal plan calculated based on information obtained from the generative AI model and emotion engine to the device. This optimal plan information includes the plan name, monthly fee, data capacity, additional service details, etc. The device displays the optimal plan information received from the server to the user.

[0175] Specific examples

[0176] A user is currently using "Plan A," which includes 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen.

[0177] First, (Device) collects the following information from the User:

[0178] Current communication plan: Plan A

[0179] Call usage: 100 minutes per month

[0180] Data usage: 5GB per month

[0181] Desired service: Unlimited data plan

[0182] Desired price range: Up to 4,000 yen per month

[0183] This information is sent to a server, which then analyzes the data using a generative AI model. For example, the model considers the user's data volume, call duration, and budget to calculate the optimal plan, such as a "value plan" that includes unlimited data and international calls for 3,000 yen per month.

[0184] Meanwhile, the Emotion Engine analyzes the data entered by the user and their reactions during operation to detect when the user is in a low-stress state. This information is also taken into account in the analysis results of the generative AI model to select a plan that best suits the user.

[0185] (Server) sends this "Special Offer" information to (Device), and the Device displays the following to the user:

[0186] Best plan: Value plan

[0187] Monthly fee: 3,000 yen

[0188] Data capacity: Unlimited

[0189] International calls: Yes

[0190] The user checks the information on the optimal plan displayed on the device and selects the plan that best suits them. Through this system, users can save time and effort while selecting the optimal plan that takes into account their emotional state.

[0191] The processing flow will be explained below.

[0192] Step 1:

[0193] (Device) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.).

[0194] Step 2:

[0195] The user follows the question form displayed on the terminal to input information about the current communication plan, call usage, data usage, desired service content, and desired rate range.

[0196] Step 3:

[0197] (Terminal) collects the information entered by the user, compiles it into a single data set, and sends it to the server.

[0198] Step 4:

[0199] (Server) receives the user's dataset sent from the device and prepares it for analysis.

[0200] Step 5:

[0201] The Emotion Engine analyzes the user's emotional state based on the user's input data and interactions. The analysis results are used to determine the user's emotional state in the current usage situation.

[0202] Step 6:

[0203] The server inputs the received user data into the generative AI model, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes multiple factors, such as the user's data volume, call duration, and rate band.

[0204] Step 7:

[0205] The server compares the optimal plan calculated based on the generative AI model with the emotion analysis results from the emotion engine, and further adjusts the plan according to the user's emotional state.

[0206] Step 8:

[0207] The server sends the generated optimal plan information to the terminal. This plan information includes the plan name, monthly fee, data capacity, additional services, etc.

[0208] Step 9:

[0209] The device receives the optimal plan from the server and displays it to the user. The displayed information takes into account the user's emotional state, allowing the user to make a more relaxed selection.

[0210] Step 10:

[0211] The user checks the information about the optimal plan displayed on the device and selects the plan that best suits their usage situation and desired conditions.

[0212] Example 2

[0213] 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."

[0214] While conventional communication plan proposal systems have methods for proposing optimal plans based on the user's usage status and desired conditions, they do not take into account the user's emotional state. As a result, they may propose plans that users find stressful or difficult to use, and they are unable to fully improve user satisfaction. In addition, many systems provide users with a large amount of information, which makes selection time-consuming and inefficient.

[0215] 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.

[0216] In this invention, the server includes: means for prompting a user to input information regarding their current communication plan, their voice and data communication usage status, and their desired conditions; means for collecting the information input by the user and sending it to the server; means for the server to analyze the information and calculate an optimal communication plan using a generative artificial intelligence model; means for displaying the calculated optimal communication plan to the user; emotion engine means for analyzing the emotional state of the user based on input data and interaction data; and means for optimizing the communication plan based on the analysis results of the emotion engine. This makes it possible to propose an optimal communication plan that takes into account not only the user's usage status and desired conditions, but also their emotional state, thereby improving user satisfaction.

[0217] "User" refers to any individual or entity that uses the System to optimize their communication plans.

[0218] "Terminal" refers to an electronic device used by a user to input information. Examples include smartphones and personal computers.

[0219] "Server" refers to a central processing unit that receives and analyzes information sent by users.

[0220] "Information" refers to data entered by the user, such as communication plans, voice and data usage, and desired conditions.

[0221] A "generative artificial intelligence model" refers to a model that uses machine learning algorithms to calculate the optimal communication plan from user data.

[0222] "Optimal communication plan" refers to the most suitable plan calculated based on the user's data usage, call time, fees, etc.

[0223] "Displaying means" refers to a method or device for presenting the calculated optimal communication plan to the user.

[0224] An "emotion engine" refers to software that analyzes user input and interaction data to assess the user's emotional state.

[0225] "Interaction data" refers to data about the actions and responses users take on the system.

[0226] "Optimization" refers to the process of calculating the outcome that best meets specific goals or conditions.

[0227] The present invention is a system for optimizing a user's communication plan, proposing the optimal communication plan based on the user's usage status, desired conditions, and emotional state. This system is composed of a user, a terminal, a server, and an emotion engine, and is implemented as follows.

[0228] First, the device displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required services, etc.). This question form is created using HTML and JavaScript. Specifically, it provides a user-friendly UI that allows users to easily enter information.

[0229] The user enters this information in the question form displayed on the device. For example, the user enters "Plan A" as their current communication plan, 100 minutes / month as their call usage, 5GB / month as their data usage, an unlimited data plan as their desired service, and a monthly fee of up to 4,000 yen.

[0230] The device collects the information entered by the user and compiles it into a single dataset. This dataset is sent to the server in a format such as JSON. For example, JavaScript can be used to convert the data into JSON and send it to an API endpoint using an HTTP POST request.

[0231] The server receives user data sent from the device and prepares it for analysis. At this stage, data is validated and normalized, and data is reshaped and missing values ​​are imputed using Python and data processing libraries (e.g., Pandas).

[0232] The server then inputs the preprocessed data into a generative AI model such as TensorFlow or PyTorch, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes the user's call duration, data usage, tariff band, etc.

[0233] Furthermore, the present invention uses an emotion engine. The emotion engine analyzes the user's input data and reactions during operation (e.g., input speed and contextual data) to evaluate the user's emotional state. Machine learning technology is used for this emotion analysis. The analysis results are fed back to the generative AI model, which then optimizes the communication plan taking the user's emotional state into account.

[0234] The server determines the optimal communication plan based on the information obtained from the generative AI model and emotion engine, and sends the final result to the device. The information sent includes the plan name, monthly fee, data capacity, and additional service details.

[0235] The device displays the information about the best plan received from the server to the user. For example, it uses HTML and JavaScript to display "Best plan: Value plan, Monthly fee: 3000 yen, Data capacity: Unlimited, International calls: Available."

[0236] Prompt Sentence Examples

[0237] For example, if a user enters the following information:

[0238] Current communication plan: Plan A

[0239] Call usage: 100 minutes per month

[0240] Data usage: 5GB per month

[0241] Desired service: Unlimited data plan

[0242] Desired price range: Up to 4,000 yen per month

[0243] This information is sent to a server, which uses a generative AI model to analyze the data and calculate the communication plan that best suits the user's requirements.

[0244] This not only enables users to quickly and easily find the best communication plan for them, but also allows them to receive more personalized suggestions that take their emotional state into account through an emotion engine.

[0245] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0246] Step 1:

[0247] The user enters information about their current communication plan, voice and data usage, and desired terms.

[0248] Input: Data entered by the user into the question form (e.g., current communication plan "Plan A," call usage of 100 minutes / month, data usage of 5GB / month, desired fee of 4,000 yen or less, etc.).

[0249] In concrete terms, the user enters answers into a form written in HTML and JavaScript.

[0250] Step 2:

[0251] The device collects the information the user enters and compiles it into a single data set.

[0252] Input: Data entered by the user.

[0253] Output: The dataset in JSON format.

[0254] Specifically, the device converts the data entered by the user into JSON format using JavaScript and sends it to the server using an HTTP POST request.

[0255] Step 3:

[0256] The server receives the user data sent from the device and prepares it for analysis.

[0257] Input: A dataset in JSON format received from the terminal.

[0258] Output: A normalized dataset.

[0259] Specifically, data processing libraries such as Python and Pandas are used to normalize data and fill in missing values.

[0260] Step 4:

[0261] The server inputs the preprocessed data into a generative AI model to calculate the optimal communication plan.

[0262] Input: The normalized dataset.

[0263] Output: Proposal of optimal communication plan.

[0264] Specifically, it uses TensorFlow and PyTorch to input data into a model and perform inference. The generative AI model takes into account factors such as the user's call duration, data usage, and price band.

[0265] Step 5:

[0266] The emotion engine analyzes the user's emotional state based on input data and interaction data.

[0267] Input: User input data and response data during operation.

[0268] Output: User's emotional state rating data.

[0269] Specifically, it uses machine learning models to analyze the user's typing speed and context to assess their emotional state.

[0270] Step 6:

[0271] The server integrates the results obtained from the generative AI model with the analysis results of the emotion engine and reevaluates the optimal communication plan.

[0272] Input: Inference results of the generative AI model, evaluation data of the emotion engine.

[0273] Output: The final optimal communication plan.

[0274] Specifically, the results of the generative AI model are added to the analysis results of the emotion engine, and the data is reprocessed to make optimal suggestions.

[0275] Step 7:

[0276] The server sends information about the optimal communication plan to the terminal.

[0277] Input: The final optimal communication plan.

[0278] Output: Plan information sent to the device.

[0279] Specifically, optimal plan information in JSON format is sent as an HTTP response.

[0280] Step 8:

[0281] The terminal displays the information on the optimum plan received from the server to the user.

[0282] Input: Information of the best plan received from the server.

[0283] Output: Details of the best plan displayed to the user.

[0284] Specifically, HTML and JavaScript are used to display the optimal plan to the user (e.g., "Optimal plan: Value plan, Monthly fee: 3,000 yen, Data capacity: Unlimited, International calls: Available").

[0285] The above are the specific processing steps of the program of this system.

[0286] (Application example 2)

[0287] 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."

[0288] Today's wide variety of electronic payment services makes it difficult for users to choose the plan that best suits them. As a result, users often cannot enjoy the most advantageous rewards and benefits, and they often feel stressed. Furthermore, there is no system that can propose the optimal plan taking into account the user's emotional state, making it impossible to provide an optimal experience for each individual user. There is a need to solve these problems.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0290] In this invention, the server includes: means for prompting a user to input information about their current electronic payment service, monthly expenditures and frequency of use, and desired benefits; means for collecting the information input by the user and sending it to the server; means for the server to analyze the information and calculate an optimal electronic payment plan using a generative AI model; means for analyzing the user's emotional state using an emotion engine and taking this into consideration when calculating the optimal plan; and means for displaying the calculated optimal electronic payment plan to the user. This provides an optimal electronic payment plan that takes into account the user's usage status and emotional state, allowing the user to make the most of their benefits and select the optimal plan without feeling stressed.

[0291] "User" refers to an individual or corporation that uses the system to select and use an electronic payment service plan.

[0292] "Electronic payment services" refer to services that enable online payments and transactions using the Internet or mobile devices.

[0293] "Monthly expenditure" refers to the total amount paid by a user using electronic payment services each month.

[0294] "Frequency of use" refers to the number of times or frequency with which a user uses an electronic payment service within a certain period of time.

[0295] "Desired benefits" are the added value of electronic payment services that users desire, including points rewards, no fees, and affiliated service benefits.

[0296] "Means for inputting information" refers to the user interface functions that allow the user to input the necessary information into the system.

[0297] "Means for collecting information and transmitting it to a server" refers to the function of collecting information entered by the user and transmitting it to a server via a communication network.

[0298] "Means for calculating optimal electronic payment plans using generative AI models" refers to algorithms that analyze and propose optimal plans based on user information collected using artificial intelligence technology.

[0299] An "emotion engine" refers to software or a system that analyzes a user's emotional state from their input data and reactions during operation.

[0300] "Means to consider when analyzing emotional state and calculating the optimal plan" refers to the function of reflecting emotional state information obtained from the emotion engine in the generative AI model and proposing the optimal plan to the user.

[0301] The "optimal electronic payment plan" refers to an electronic payment service plan that provides the greatest benefits by comprehensively considering the user's usage situation, desired conditions, and emotional state.

[0302] "Means for displaying the plan to the user" refers to a display or screen display function for visually presenting information about the calculated optimal plan to the user.

[0303] This invention describes a system that allows users to select the optimal electronic payment service. This system proposes the optimal electronic payment plan to the user by calculating the optimal plan using a generative AI model based on input user information and by analyzing and considering the user's emotional state using an emotion engine.

[0304] 1. System program for implementing this application example

[0305] A specific example of this system will be described below.

[0306] 1.1 Hardware and Software Used

[0307] Smartphone: Used by users to enter their information and view the best plan for them (e.g., iOS or Android device).

[0308] Server: Performs data analysis and processing of generative AI models and emotion engines (e.g., cloud-based servers).

[0309] software:

[0310] Mobile App: User frontend developed using React Native.

[0311] Server-side application: Built using Node.js.

[0312] Data Analysis: Python and its libraries (Pandas, Scikit-Learn).

[0313] Generative AI model: OpenAI's GPT-4.

[0314] Emotion engine: Emotion AI API.

[0315] 2. Explain the generated program's processing in natural language

[0316] The server specifically implements the present invention using the following means.

[0317] 2.1 User Information Collection

[0318] First, users enter their current electronic payment services, monthly spending and frequency of use, and desired rewards through a smartphone app. This information is collected via the user interface.

[0319] 2.2 Data Transmission

[0320] The app compiles the collected data into a single dataset and sends it to a server via HTTPS.

[0321] 2.3 Data analysis

[0322] The server inputs the received data into a generative AI model (e.g., OpenAI's GPT-4) to calculate the optimal electronic payment plan based on the user's spending patterns and desired conditions.

[0323] 2.4 Emotional State Analysis

[0324] The emotion engine analyzes the user's emotional state based on their input data and reactions during operation. The obtained emotional information is reflected in the analysis results of the generative AI model.

[0325] 2.5 Proposing the optimal plan

[0326] Based on the analysis results of the generative AI model and emotion engine, the server calculates an optimal plan, which is then displayed to the user via a smartphone app.

[0327] 3. Add examples to your description

[0328] Let's say a user currently uses "Service A" as their electronic payment service, and has entered that their monthly spending is 30,000 yen and that they use the service frequently. Furthermore, this user wishes to receive points back.

[0329] Prompt Sentence Examples

[0330] 1. Example prompts for collecting user information:

[0331] Please select the electronic payment service you are currently using.

[0332] Enter your monthly spending and frequency of use.

[0333] Please select the benefits you would like (e.g. points reward, no fees, partner service benefits).

[0334] 2. Example prompts to be input to the generative AI model when proposing the optimal plan:

[0335] The data provided by the user is as follows:

[0336] Current service: Service A

[0337] Monthly expenses: 30,000 yen

[0338] Frequency of use: High

[0339] Desired reward: Points redemption

[0340] Suggest the best e-payment plan for this user. Emotional state is low stress.

[0341] This allows users to easily find the most advantageous electronic payment plan for themselves and enjoy a comfortable service that takes their emotional state into consideration.

[0342] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0343] Step 1:

[0344] The terminal displays a form for the user to enter information about their electronic payment service usage (current services used, monthly expenditures, frequency of use, and desired benefits).

[0345] Input: Information about the user's electronic payment service

[0346] Output: User's input dataset

[0347] Step 2:

[0348] The device collects the information entered by the user and sends it to the server via HTTPS.

[0349] Input: User input dataset

[0350] Output: The dataset sent to the server

[0351] Step 3:

[0352] The server receives the received dataset and prepares it for input to the generative AI model by formatting the data and converting it into a format that the AI ​​model can understand.

[0353] Input: Dataset received by the server

[0354] Output: A formatted dataset

[0355] Step 4:

[0356] The server then inputs the formatted data set into a generative AI model (e.g., OpenAI GPT-4) to calculate the optimal electronic payment plan. The generative AI model performs data analysis and inference based on the user's spending patterns and preferences.

[0357] Input: Formatted dataset

[0358] Output: Proposal of optimal electronic payment plan

[0359] Step 5:

[0360] The server uses an emotion engine to analyze the user's emotional state, such as assessing stress levels and satisfaction levels based on input data and reactions during operation. This information is also added to the analysis results.

[0361] Input: Formatted dataset and user interaction data

[0362] Output: User's emotional state information

[0363] Step 6:

[0364] The server combines information obtained from the generative AI model and the emotion engine to determine the final optimal plan, taking into account the user's emotional state to select a plan that is most comfortable to use.

[0365] Input: Optimal e-payment plan recommendations and emotional state information

[0366] Output: The final optimal plan

[0367] Step 7:

[0368] The server then sends the final selected optimal plan to the device, again via HTTPS.

[0369] Input: The final optimal plan

[0370] Output: Plan data sent to device

[0371] Step 8:

[0372] The device will then display the received information about the optimal plan to the user, visually providing information such as the plan name, monthly cost, benefits, and details of affiliated services.

[0373] Input: Received plan data

[0374] Output: Information about the best plan displayed to the user

[0375] 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.

[0376] 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.

[0377] 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.

[0378] [Second embodiment]

[0379] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0380] 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.

[0381] 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).

[0382] 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.

[0383] 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.

[0384] 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).

[0385] 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.

[0386] 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.

[0387] 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.

[0388] 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.

[0389] 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.

[0390] 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."

[0391] This invention is a system that utilizes a generative AI model to propose the optimal communication plan based on the user's smartphone usage status and desired conditions. This system is mainly composed of a user, a terminal, and a server, and is implemented in the following form.

[0392] First, the device displays a questionnaire to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required services, etc.). Once the user has completed the input, the device collects this information as a single data set and sends it to the server.

[0393] Next, the server receives the user's data sent from the device. The received data includes the user's current communication plan, call usage, data usage, desired service, desired rate range, etc. The server uses a generative AI model to analyze this data. The generative AI model calculates the optimal communication plan based on the user's data. This model includes an algorithm that derives the optimal plan by taking into account multiple factors related to the user's data usage, call duration, and budget, for example.

[0394] The server uses the generative AI model to calculate the optimal communication plan, and then sends the results to the device, including details of the communication plan it determines to be optimal (plan name, monthly fee, data volume, additional services, etc.).

[0395] Finally, the device displays the information on the optimal plan received from the server to the user, allowing the user to select the plan that best suits them.

[0396] Specific examples

[0397] A user is currently using "Plan A," which includes 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen.

[0398] (Device) collects the following information from you:

[0399] Current communication plan: Plan A

[0400] Call usage: 100 minutes per month

[0401] Data usage: 5GB per month

[0402] Desired service: Unlimited data plan

[0403] Desired price range: Up to 4,000 yen per month

[0404] This information is sent to a server, which then analyzes the data using a generative AI model. For example, the model considers the user's data volume, call duration, and budget to calculate the optimal plan, such as a "value plan" that includes unlimited data and international calls for 3,000 yen per month.

[0405] (Server) sends this "Special Offer" information to (Device), and the Device displays the following to the user:

[0406] Best plan: Value plan

[0407] Monthly fee: 3,000 yen

[0408] Data capacity: Unlimited

[0409] International calls: Yes

[0410] This allows users to easily find the best communication plan for them. Through this system, users can select the best plan while saving time and effort.

[0411] The processing flow will be explained below.

[0412] Step 1:

[0413] (Device) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.).

[0414] Step 2:

[0415] The user follows the question form displayed on the terminal to input information about the communication plan currently in use, the amount of call usage, the amount of data usage, the desired service content, and the desired rate range.

[0416] Step 3:

[0417] (Terminal) collects the information entered by the user, compiles it into a single data set, and sends it to the server.

[0418] Step 4:

[0419] (Server) receives the user's dataset sent from the device and prepares it for analysis.

[0420] Step 5:

[0421] The server inputs the received user data into the generative AI model, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes multiple factors, such as the user's data volume, call duration, and rate band.

[0422] Step 6:

[0423] The server sends the optimal plan information obtained from the generative AI model to the device. The optimal plan information includes the plan name, monthly fee, data capacity, and additional service details.

[0424] Step 7:

[0425] The terminal displays the information about the optimal plan received from the server to the user.

[0426] Step 8:

[0427] The user checks the information about the optimal plan displayed on the device and selects the plan that best suits their usage situation and desired conditions.

[0428] Example 1

[0429] 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."

[0430] The problem with the traditional method of selecting a communication plan is that users have to manually search for the best plan based on their usage and desired conditions, which is a time-consuming and labor-intensive process. Furthermore, it is difficult to determine whether the selected plan is truly optimal for the user, and in some cases, users may end up choosing an inappropriate plan. This often leaves users unsure about communication costs and service satisfaction.

[0431] 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.

[0432] In this invention, the server includes means for prompting a user to input information regarding their current communication plan, their voice and data communication usage status, and their desired conditions, means for collecting the information input by the user and sending it to the server, means for the server to analyze the information and calculate an optimal communication plan using a generative artificial intelligence model, and means for displaying the calculated optimal communication plan to the user. This allows the user to automatically receive optimal communication plans and quickly and easily select the plan that best suits their usage status and desired conditions.

[0433] A "user" is an individual who uses the system to input their own communication plan, usage status, and desired conditions.

[0434] "Communication plan" refers to the specific plan details for the communication service to which the user has subscribed, including fees, data capacity, call time, etc.

[0435] "Usage status" refers to information that indicates how much a user actually uses a communication service, such as the amount of call time and data usage.

[0436] "Desired conditions" refer to the specific requirements and conditions that a user has for a communication plan, such as the price range they desire and the services they require.

[0437] "Terminal" refers to an electronic device that a user uses to input information and send it to a server. Examples include smartphones and personal computers.

[0438] The "server" is a central computer system that receives information sent from the terminal, analyzes it using a generative artificial intelligence model, and calculates the optimal communication plan.

[0439] A "generative artificial intelligence model" is a machine learning model equipped with an algorithm for deriving the optimal communication plan based on information entered by the user.

[0440] The "optimal communication plan" is the communication plan that the system determines to be the most suitable in terms of cost, service content, etc. based on the user's usage and desired conditions.

[0441] This invention is a system that uses a generative AI model to propose an optimal communication plan based on the user's usage status and desired conditions. This system is mainly composed of a user, a terminal, and a server, and is implemented in the following form.

[0442] First, the user accesses the inquiry form using their device. This inquiry form is created using HTML, CSS, and JavaScript, and provides an interface that allows users to intuitively enter information. Specifically, the user enters information such as their current communication plan, monthly call time, data communication usage, desired service, and desired price range. For example, "Communication plan name: Plan A," "Call time: 100 minutes," "Data communication amount: 5GB," "Desired service: Unlimited data," and "Desired price range: 4,000 yen or less."

[0443] As the user enters information, the device collects this data as a dataset and sends it to the server using an HTTP POST request. The device-side program is implemented in JavaScript, and this dataset contains all the entered information.

[0444] This data is then received by a server. Built using a web framework such as Node.js or Python's Flask, the server receives the data via HTTP requests. The server analyzes the received data and cleanses and normalizes it as necessary. It then uses a generative AI model (for example, a model using TensorFlow or PyTorch) to analyze the data. This generative AI model contains algorithms that derive the optimal communication plan based on the user's data usage, call duration, and desired conditions.

[0445] As a concrete example, the following prompt sentences can be input to a generative AI model:

[0446] "The user's current data plan is "Plan A," which allows for 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen. Please suggest the best data plan that meets these conditions."

[0447] Once the generative AI model calculates the optimal data plan, the result is converted into a data format such as JSON and sent to the device as an HTTP response, which includes the name of the optimal plan, the monthly fee, data volume, and details of additional services.

[0448] Finally, the device analyzes the data received from the server and displays it in an easy-to-read format for the user. This display is stylishly formatted using HTML and CSS. For example, information such as "Value Plan," "Monthly Fee: 3,000 yen," "Data Capacity: Unlimited," and "International Calls: Available" is displayed in list format. Using this information, users can select the communication plan that best suits them.

[0449] Through this system, users can easily find the communication plan that best suits their usage and desired conditions, while saving time and effort.

[0450] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0451] Step 1:

[0452] (User) enters information into a question form.

[0453] The user opens a browser on their device and accesses the inquiry form. The form has drop-down menus and radio buttons, and they input information in order, such as "Plan name: Plan A," "Call time: 100 minutes," "Data amount: 5GB," "Desired service: Unlimited data," and "Desired price range: 4,000 yen or less." The information entered by the user becomes the input data for the system.

[0454] Step 2:

[0455] (Device) collects input data and creates an HTTP POST request.

[0456] When the user clicks the "Submit" button, JavaScript is executed to combine the input data into a single data object. This data object contains all the information entered by the user. The device then sends this data object to the server as an HTTP POST request. It generates a JSON-formatted request body based on the input data, and the output is a request to the server.

[0457] Step 3:

[0458] (Server) receives the HTTP POST request and parses the data.

[0459] The server receives HTTP requests using a web framework such as Node.js or Python's Flask. It takes the received data and, if necessary, cleanses the input data (for example, by removing unnecessary whitespace or symbols) and normalizes it (for example, by standardizing the data format). In this process, the input data is parsed and converted into a format suitable for the AI ​​model. The output of the parsing process becomes the input data for the generative AI model.

[0460] Step 4:

[0461] (Server) analyzes the data using a generative AI model and calculates the optimal communication plan.

[0462] The server runs a generative AI model using AI frameworks such as TensorFlow and PyTorch. The analyzed data is input into the AI ​​model, which then calculates the optimal communication plan based on multiple factors (data volume, call duration, budget, etc.). The output of the generative AI model is detailed information about the optimal communication plan for the user (plan name, monthly fee, data volume, additional services, etc.).

[0463] Step 5:

[0464] (Server) sends details of the optimal communication plan to the device.

[0465] The server converts the detailed information obtained from the generative AI model into a data format such as JSON, and sends this to the device as an HTTP response. The output of the conversion process becomes the response data sent to the device.

[0466] Step 6:

[0467] (Device) receives the response from the server and displays it to the user.

[0468] The device uses JavaScript to analyze the data received from the server and reflects it in HTML. For example, information such as "Value Plan," "Monthly Fee: 3,000 yen," "Data Capacity: Unlimited," and "International Calls: Available" is displayed on the screen in list format. In this process, the response data is converted into a format that is easy for the user to understand and displayed on the screen. The output of the display process becomes the communication plan information presented to the user.

[0469] (Application example 1)

[0470] 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."

[0471] In recent years, the use of online shopping has increased dramatically, but many users spend a lot of time and effort trying to find the best purchase plan and discount information. To solve this problem, a system that automatically suggests the best purchase plan based on the user's shopping habits and desired conditions is needed. However, current systems do not effectively utilize the user's detailed shopping history or individual desired conditions, making it difficult to find the best plan.

[0472] 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.

[0473] In this invention, the server includes a means for prompting a user to input information about their current purchase plan, shopping habits, and desired conditions, a means for collecting the information input by the user and sending it to the server, a means for the server to analyze the information and calculate an optimal purchase plan using a generative artificial intelligence model, and a means for displaying details of the optimal purchase plan to the user, thereby enabling the user to easily find a purchase plan optimized to their shopping habits and desires, thereby saving time and effort.

[0474] A "user" is someone who uses this system to receive the optimal purchase plan.

[0475] "Purchase Plan" means a purchase option optimized for a User when purchasing an item online, including fees, discounts, subscription services, etc.

[0476] "Shopping habits" refers to the behavioral patterns of how a user typically purchases products, including purchase frequency and product category preferences.

[0477] "Desired conditions" are the specific requirements that a user has for a purchase plan, including price, type of product, and service content.

[0478] "Means for inputting information" refers to the interface that allows users to input information such as their current purchasing status and desired conditions into the system.

[0479] "Means for collecting information and transmitting it to the server" refers to the technical means by which the information entered by the user is compiled into a single data set and transmitted to the server.

[0480] "Means for analyzing the information on the server and calculating the optimal purchase plan using a generative AI model" refers to technology that enables a server to analyze information input by a user using a generative AI model and calculate the optimal purchase plan.

[0481] The "means for displaying the optimal purchase plan to the user" refers to an interface for visually presenting to the user the details of the optimal purchase plan calculated by the server.

[0482] "Generative AI model" refers to a machine learning algorithm used to analyze collected data and generate optimal suggestions for users.

[0483] To implement this invention, it is necessary to build a system that proposes optimal purchase plans based on the user's shopping habits and desired conditions. This system is mainly composed of a user terminal and a server.

[0484] First, the user terminal provides an interface that allows the user to input information about their current purchase plan, shopping habits, and desired conditions. This interface is realized by an application installed on a device such as a smartphone, smart glasses, a head-mounted display, or a personal robot.

[0485] Once the user has finished entering the information, the device collects this information as a single data set and sends it to the server. This communication must be secure and efficient, so for example, the HTTPS protocol is used.

[0486] The server uses a generative AI model to analyze the dataset received from the user. This generative AI model includes an algorithm that considers various factors (e.g., the user's shopping history, purchase frequency, desired conditions, etc.) to calculate the optimal purchase plan. Specifically, the server is built using the Node.js and Express.js frameworks and uses OpenAI's generative AI model.

[0487] For example, if a user provides the following information:

[0488] Current purchase plan: 10 items per month

[0489] Shopping habits: Often look for discounts in advance

[0490] Desired conditions: Monthly budget of 5,000 yen, purchase once a week

[0491] With this information, the server prompts the generative AI model with the following prompt:

[0492] Example prompt sentence:

[0493] Your current purchasing situation: 10 items purchased per month

[0494] Your shopping habits: I often look for discounts in advance

[0495] Your budget: Your monthly budget is 5,000 yen.

[0496] Your purchase frequency: Once a week

[0497] Please take the above into consideration and suggest the best purchase plan for you.

[0498] Based on these prompts, the generative AI model recommends the best purchasing plan for the user's needs, including the best subscription services, discount offers, and bulk buying options.

[0499] Finally, the information on the optimal purchase plan obtained from the server is sent to the user's device and visually displayed, allowing the user to easily find a purchase plan that is optimized for their shopping habits and preferences.

[0500] This system allows users to save time and effort while choosing the most suitable purchasing option.

[0501] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0502] Step 1:

[0503] The user inputs information about their current purchase plan, shopping habits, and desired conditions into the terminal, including their current purchase plan (e.g., buying 10 items per month), shopping habits (e.g., often looking for discounts in advance), and desired conditions (e.g., monthly budget of 5,000 yen, purchase frequency once a week).

[0504] Step 2:

[0505] The device collects the information entered by the user as a single data set and sends it to the server. This data set includes all of the user's input information. For example, the input data is configured in JSON format and sent securely to the server using the HTTPS protocol.

[0506] Step 3:

[0507] The server receives the data set sent from the device and analyzes this information with the generative AI model. At this time, the received data is converted into a prompt sentence and sent to the generative AI model. For example, the following prompt sentence is generated:

[0508] Your current purchasing situation: 10 items purchased per month

[0509] Your shopping habits: I often look for discounts in advance

[0510] Your budget: Your monthly budget is 5,000 yen.

[0511] Your purchase frequency: Once a week

[0512] Please take the above into consideration and suggest the best purchase plan for you.

[0513] The server sends this prompt to OpenAI's generative AI model and receives the AI ​​model's response.

[0514] Step 4:

[0515] The generative AI model generates the optimal purchase plan based on prompts sent by the server. The model analyzes factors such as the user's shopping habits, budget, and purchase frequency to calculate the optimal purchasing options (e.g., subscription services or discount offers). The output is returned to the server as a text response.

[0516] Step 5:

[0517] The server extracts and organizes the details of the most suitable purchase plan based on the response received from the generative AI model, and performs additional processing (e.g., converting the response format or filtering the information) as needed. Finally, it generates a dataset to display to the user.

[0518] Step 6:

[0519] The server sends the generated optimal purchase plan dataset to the terminal, which includes details of the purchase plan (e.g., subscription service type, discount rate, fee, etc.).

[0520] Step 7:

[0521] The terminal displays the information on the optimal purchase plan received from the server to the user. The user can check the plan details visually displayed on the terminal screen and select the optimal purchase option. This allows the user to efficiently make purchases based on the purchase plan optimized for their needs.

[0522] 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.

[0523] This invention combines a system that utilizes a generative AI model to propose the optimal communication plan based on the user's smartphone usage status and desired conditions with an emotion engine that recognizes the user's emotions. This system is composed of a user, a terminal, a server, and an emotion engine, and is implemented in the following form.

[0524] First, the (terminal) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.). The (user) enters this information according to the question form displayed on the terminal.

[0525] (Device) collects the information entered by the user, compiles it into a single data set, and sends it to the server. (Server) receives the user data sent from the device and prepares it for analysis.

[0526] The server inputs the received user data into a generative AI model and runs the model to calculate the optimal communication plan. This generative AI model includes an algorithm that analyzes multiple factors, such as the user's data volume, call duration, and rate band, to derive the optimal plan.

[0527] Furthermore, the present invention adds an emotion engine. The emotion engine analyzes the user's emotional state based on the user's input data and interactions. The analysis results are used to optimize communication plans using a generative AI model. For example, if the user is under stress, the emotion engine provides that information to the server, which can then make suggestions to help the user relax.

[0528] The server sends the optimal plan calculated based on information obtained from the generative AI model and emotion engine to the device. This optimal plan information includes the plan name, monthly fee, data capacity, additional service details, etc. The device displays the optimal plan information received from the server to the user.

[0529] Specific examples

[0530] A user is currently using "Plan A," which includes 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen.

[0531] First, (Device) collects the following information from the User:

[0532] Current communication plan: Plan A

[0533] Call usage: 100 minutes per month

[0534] Data usage: 5GB per month

[0535] Desired service: Unlimited data plan

[0536] Desired price range: Up to 4,000 yen per month

[0537] This information is sent to a server, which then analyzes the data using a generative AI model. For example, the model considers the user's data volume, call duration, and budget to calculate the optimal plan, such as a "value plan" that includes unlimited data and international calls for 3,000 yen per month.

[0538] Meanwhile, the Emotion Engine analyzes the data entered by the user and their reactions during operation to detect when the user is in a low-stress state. This information is also taken into account in the analysis results of the generative AI model to select a plan that best suits the user.

[0539] (Server) sends this "Special Offer" information to (Device), and the Device displays the following to the user:

[0540] Best plan: Value plan

[0541] Monthly fee: 3,000 yen

[0542] Data capacity: Unlimited

[0543] International calls: Yes

[0544] The user checks the information on the optimal plan displayed on the device and selects the plan that best suits them. Through this system, users can save time and effort while selecting the optimal plan that takes into account their emotional state.

[0545] The processing flow will be explained below.

[0546] Step 1:

[0547] (Device) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.).

[0548] Step 2:

[0549] The user follows the question form displayed on the terminal to input information about the current communication plan, call usage, data usage, desired service content, and desired rate range.

[0550] Step 3:

[0551] (Terminal) collects the information entered by the user, compiles it into a single data set, and sends it to the server.

[0552] Step 4:

[0553] (Server) receives the user's dataset sent from the device and prepares it for analysis.

[0554] Step 5:

[0555] The Emotion Engine analyzes the user's emotional state based on the user's input data and interactions. The analysis results are used to determine the user's emotional state in the current usage situation.

[0556] Step 6:

[0557] The server inputs the received user data into the generative AI model, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes multiple factors, such as the user's data volume, call duration, and rate band.

[0558] Step 7:

[0559] The server compares the optimal plan calculated based on the generative AI model with the emotion analysis results from the emotion engine, and further adjusts the plan according to the user's emotional state.

[0560] Step 8:

[0561] The server sends the generated optimal plan information to the terminal. This plan information includes the plan name, monthly fee, data capacity, additional services, etc.

[0562] Step 9:

[0563] The device receives the optimal plan from the server and displays it to the user. The displayed information takes into account the user's emotional state, allowing the user to make a more relaxed selection.

[0564] Step 10:

[0565] The user checks the information about the optimal plan displayed on the device and selects the plan that best suits their usage situation and desired conditions.

[0566] Example 2

[0567] 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."

[0568] While conventional communication plan proposal systems have methods for proposing optimal plans based on the user's usage status and desired conditions, they do not take into account the user's emotional state. As a result, they may propose plans that users find stressful or difficult to use, and they are unable to fully improve user satisfaction. In addition, many systems provide users with a large amount of information, which makes selection time-consuming and inefficient.

[0569] 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.

[0570] In this invention, the server includes: means for prompting a user to input information regarding their current communication plan, their voice and data communication usage status, and their desired conditions; means for collecting the information input by the user and sending it to the server; means for the server to analyze the information and calculate an optimal communication plan using a generative artificial intelligence model; means for displaying the calculated optimal communication plan to the user; emotion engine means for analyzing the emotional state of the user based on input data and interaction data; and means for optimizing the communication plan based on the analysis results of the emotion engine. This makes it possible to propose an optimal communication plan that takes into account not only the user's usage status and desired conditions, but also their emotional state, thereby improving user satisfaction.

[0571] "User" refers to any individual or entity that uses the System to optimize their communication plans.

[0572] "Terminal" refers to an electronic device used by a user to input information. Examples include smartphones and personal computers.

[0573] "Server" refers to a central processing unit that receives and analyzes information sent by users.

[0574] "Information" refers to data entered by the user, such as communication plans, voice and data usage, and desired conditions.

[0575] A "generative artificial intelligence model" refers to a model that uses machine learning algorithms to calculate the optimal communication plan from user data.

[0576] "Optimal communication plan" refers to the most suitable plan calculated based on the user's data usage, call time, fees, etc.

[0577] "Displaying means" refers to a method or device for presenting the calculated optimal communication plan to the user.

[0578] An "emotion engine" refers to software that analyzes user input and interaction data to assess the user's emotional state.

[0579] "Interaction data" refers to data about the actions and responses users take on the system.

[0580] "Optimization" refers to the process of calculating the outcome that best meets specific goals or conditions.

[0581] The present invention is a system for optimizing a user's communication plan, proposing the optimal communication plan based on the user's usage status, desired conditions, and emotional state. This system is composed of a user, a terminal, a server, and an emotion engine, and is implemented as follows.

[0582] First, the device displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required services, etc.). This question form is created using HTML and JavaScript. Specifically, it provides a user-friendly UI that allows users to easily enter information.

[0583] The user enters this information in the question form displayed on the device. For example, the user enters "Plan A" as their current communication plan, 100 minutes / month as their call usage, 5GB / month as their data usage, an unlimited data plan as their desired service, and a monthly fee of up to 4,000 yen.

[0584] The device collects the information entered by the user and compiles it into a single dataset. This dataset is sent to the server in a format such as JSON. For example, JavaScript can be used to convert the data into JSON and send it to an API endpoint using an HTTP POST request.

[0585] The server receives user data sent from the device and prepares it for analysis. At this stage, data is validated and normalized, and data is reshaped and missing values ​​are imputed using Python and data processing libraries (e.g., Pandas).

[0586] The server then inputs the preprocessed data into a generative AI model such as TensorFlow or PyTorch, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes the user's call duration, data usage, tariff band, etc.

[0587] Furthermore, the present invention uses an emotion engine. The emotion engine analyzes the user's input data and reactions during operation (e.g., input speed and contextual data) to evaluate the user's emotional state. Machine learning technology is used for this emotion analysis. The analysis results are fed back to the generative AI model, which then optimizes the communication plan taking the user's emotional state into account.

[0588] The server determines the optimal communication plan based on the information obtained from the generative AI model and emotion engine, and sends the final result to the device. The information sent includes the plan name, monthly fee, data capacity, and additional service details.

[0589] The device displays the information about the best plan received from the server to the user. For example, it uses HTML and JavaScript to display "Best plan: Value plan, Monthly fee: 3000 yen, Data capacity: Unlimited, International calls: Available."

[0590] Prompt Sentence Examples

[0591] For example, if a user enters the following information:

[0592] Current communication plan: Plan A

[0593] Call usage: 100 minutes per month

[0594] Data usage: 5GB per month

[0595] Desired service: Unlimited data plan

[0596] Desired price range: Up to 4,000 yen per month

[0597] This information is sent to a server, which uses a generative AI model to analyze the data and calculate the communication plan that best suits the user's requirements.

[0598] This not only enables users to quickly and easily find the best communication plan for them, but also allows them to receive more personalized suggestions that take their emotional state into account through an emotion engine.

[0599] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0600] Step 1:

[0601] The user enters information about their current communication plan, voice and data usage, and desired terms.

[0602] Input: Data entered by the user into the question form (e.g., current communication plan "Plan A," call usage of 100 minutes / month, data usage of 5GB / month, desired fee of 4,000 yen or less, etc.).

[0603] In concrete terms, the user enters answers into a form written in HTML and JavaScript.

[0604] Step 2:

[0605] The device collects the information the user enters and compiles it into a single data set.

[0606] Input: Data entered by the user.

[0607] Output: The dataset in JSON format.

[0608] Specifically, the device converts the data entered by the user into JSON format using JavaScript and sends it to the server using an HTTP POST request.

[0609] Step 3:

[0610] The server receives the user data sent from the device and prepares it for analysis.

[0611] Input: A dataset in JSON format received from the terminal.

[0612] Output: A normalized dataset.

[0613] Specifically, data processing libraries such as Python and Pandas are used to normalize data and fill in missing values.

[0614] Step 4:

[0615] The server inputs the preprocessed data into a generative AI model to calculate the optimal communication plan.

[0616] Input: The normalized dataset.

[0617] Output: Proposal of optimal communication plan.

[0618] Specifically, it uses TensorFlow and PyTorch to input data into a model and perform inference. The generative AI model takes into account factors such as the user's call duration, data usage, and price band.

[0619] Step 5:

[0620] The emotion engine analyzes the user's emotional state based on input data and interaction data.

[0621] Input: User input data and response data during operation.

[0622] Output: User's emotional state rating data.

[0623] Specifically, it uses machine learning models to analyze the user's typing speed and context to assess their emotional state.

[0624] Step 6:

[0625] The server integrates the results obtained from the generative AI model with the analysis results of the emotion engine and reevaluates the optimal communication plan.

[0626] Input: Inference results of the generative AI model, evaluation data of the emotion engine.

[0627] Output: The final optimal communication plan.

[0628] Specifically, the results of the generative AI model are added to the analysis results of the emotion engine, and the data is reprocessed to make optimal suggestions.

[0629] Step 7:

[0630] The server sends information about the optimal communication plan to the terminal.

[0631] Input: The final optimal communication plan.

[0632] Output: Plan information sent to the device.

[0633] Specifically, optimal plan information in JSON format is sent as an HTTP response.

[0634] Step 8:

[0635] The terminal displays the information on the optimum plan received from the server to the user.

[0636] Input: Information of the best plan received from the server.

[0637] Output: Details of the best plan displayed to the user.

[0638] Specifically, HTML and JavaScript are used to display the optimal plan to the user (e.g., "Optimal plan: Value plan, Monthly fee: 3,000 yen, Data capacity: Unlimited, International calls: Available").

[0639] The above are the specific processing steps of the program of this system.

[0640] (Application example 2)

[0641] 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."

[0642] Today's wide variety of electronic payment services makes it difficult for users to choose the plan that best suits them. As a result, users often cannot enjoy the most advantageous rewards and benefits, and they often feel stressed. Furthermore, there is no system that can propose the optimal plan taking into account the user's emotional state, making it impossible to provide an optimal experience for each individual user. There is a need to solve these problems.

[0643] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0644] In this invention, the server includes: means for prompting a user to input information about their current electronic payment service, monthly expenditures and frequency of use, and desired benefits; means for collecting the information input by the user and sending it to the server; means for the server to analyze the information and calculate an optimal electronic payment plan using a generative AI model; means for analyzing the user's emotional state using an emotion engine and taking this into consideration when calculating the optimal plan; and means for displaying the calculated optimal electronic payment plan to the user. This provides an optimal electronic payment plan that takes into account the user's usage status and emotional state, allowing the user to make the most of their benefits and select the optimal plan without feeling stressed.

[0645] "User" refers to an individual or corporation that uses the system to select and use an electronic payment service plan.

[0646] "Electronic payment services" refer to services that enable online payments and transactions using the Internet or mobile devices.

[0647] "Monthly expenditure" refers to the total amount paid by a user using electronic payment services each month.

[0648] "Frequency of use" refers to the number of times or frequency with which a user uses an electronic payment service within a certain period of time.

[0649] "Desired benefits" are the added value of electronic payment services that users desire, including points rewards, no fees, and affiliated service benefits.

[0650] "Means for inputting information" refers to the user interface functions that allow the user to input the necessary information into the system.

[0651] "Means for collecting information and transmitting it to a server" refers to the function of collecting information entered by the user and transmitting it to a server via a communication network.

[0652] "Means for calculating optimal electronic payment plans using generative AI models" refers to algorithms that analyze and propose optimal plans based on user information collected using artificial intelligence technology.

[0653] An "emotion engine" refers to software or a system that analyzes a user's emotional state from their input data and reactions during operation.

[0654] "Means to consider when analyzing emotional state and calculating the optimal plan" refers to the function of reflecting emotional state information obtained from the emotion engine in the generative AI model and proposing the optimal plan to the user.

[0655] The "optimal electronic payment plan" refers to an electronic payment service plan that provides the greatest benefits by comprehensively considering the user's usage situation, desired conditions, and emotional state.

[0656] "Means for displaying the plan to the user" refers to a display or screen display function for visually presenting information about the calculated optimal plan to the user.

[0657] This invention describes a system that allows users to select the optimal electronic payment service. This system proposes the optimal electronic payment plan to the user by calculating the optimal plan using a generative AI model based on input user information and by analyzing and considering the user's emotional state using an emotion engine.

[0658] 1. System program for implementing this application example

[0659] A specific example of this system will be described below.

[0660] 1.1 Hardware and Software Used

[0661] Smartphone: Used by users to enter their information and view the best plan for them (e.g., iOS or Android device).

[0662] Server: Performs data analysis and processing of generative AI models and emotion engines (e.g., cloud-based servers).

[0663] software:

[0664] Mobile App: User frontend developed using React Native.

[0665] Server-side application: Built using Node.js.

[0666] Data Analysis: Python and its libraries (Pandas, Scikit-Learn).

[0667] Generative AI model: OpenAI's GPT-4.

[0668] Emotion engine: Emotion AI API.

[0669] 2. Explain the generated program's processing in natural language

[0670] The server specifically implements the present invention using the following means.

[0671] 2.1 User Information Collection

[0672] First, users enter their current electronic payment services, monthly spending and frequency of use, and desired rewards through a smartphone app. This information is collected via the user interface.

[0673] 2.2 Data Transmission

[0674] The app compiles the collected data into a single dataset and sends it to a server via HTTPS.

[0675] 2.3 Data analysis

[0676] The server inputs the received data into a generative AI model (e.g., OpenAI's GPT-4) to calculate the optimal electronic payment plan based on the user's spending patterns and desired conditions.

[0677] 2.4 Emotional State Analysis

[0678] The emotion engine analyzes the user's emotional state based on their input data and reactions during operation. The obtained emotional information is reflected in the analysis results of the generative AI model.

[0679] 2.5 Proposing the optimal plan

[0680] Based on the analysis results of the generative AI model and emotion engine, the server calculates an optimal plan, which is then displayed to the user via a smartphone app.

[0681] 3. Add examples to your description

[0682] Let's say a user currently uses "Service A" as their electronic payment service, and has entered that their monthly spending is 30,000 yen and that they use the service frequently. Furthermore, this user wishes to receive points back.

[0683] Prompt Sentence Examples

[0684] 1. Example prompts for collecting user information:

[0685] Please select the electronic payment service you are currently using.

[0686] Enter your monthly spending and frequency of use.

[0687] Please select the benefits you would like (e.g. points reward, no fees, partner service benefits).

[0688] 2. Example prompts to be input to the generative AI model when proposing the optimal plan:

[0689] The data provided by the user is as follows:

[0690] Current service: Service A

[0691] Monthly expenses: 30,000 yen

[0692] Frequency of use: High

[0693] Desired reward: Points redemption

[0694] Suggest the best e-payment plan for this user. Emotional state is low stress.

[0695] This allows users to easily find the most advantageous electronic payment plan for themselves and enjoy a comfortable service that takes their emotional state into consideration.

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

[0697] Step 1:

[0698] The terminal displays a form for the user to enter information about their electronic payment service usage (current services used, monthly expenditures, frequency of use, and desired benefits).

[0699] Input: Information about the user's electronic payment service

[0700] Output: User's input dataset

[0701] Step 2:

[0702] The device collects the information entered by the user and sends it to the server via HTTPS.

[0703] Input: User input dataset

[0704] Output: The dataset sent to the server

[0705] Step 3:

[0706] The server receives the received dataset and prepares it for input to the generative AI model by formatting the data and converting it into a format that the AI ​​model can understand.

[0707] Input: Dataset received by the server

[0708] Output: A formatted dataset

[0709] Step 4:

[0710] The server then inputs the formatted data set into a generative AI model (e.g., OpenAI GPT-4) to calculate the optimal electronic payment plan. The generative AI model performs data analysis and inference based on the user's spending patterns and preferences.

[0711] Input: Formatted dataset

[0712] Output: Proposal of optimal electronic payment plan

[0713] Step 5:

[0714] The server uses an emotion engine to analyze the user's emotional state, such as assessing stress levels and satisfaction levels based on input data and reactions during operation. This information is also added to the analysis results.

[0715] Input: Formatted dataset and user interaction data

[0716] Output: User's emotional state information

[0717] Step 6:

[0718] The server combines information obtained from the generative AI model and the emotion engine to determine the final optimal plan, taking into account the user's emotional state to select a plan that is most comfortable to use.

[0719] Input: Optimal e-payment plan recommendations and emotional state information

[0720] Output: The final optimal plan

[0721] Step 7:

[0722] The server then sends the final selected optimal plan to the device, again via HTTPS.

[0723] Input: The final optimal plan

[0724] Output: Plan data sent to device

[0725] Step 8:

[0726] The device will then display the received information about the optimal plan to the user, visually providing information such as the plan name, monthly cost, benefits, and details of affiliated services.

[0727] Input: Received plan data

[0728] Output: Information about the best plan displayed to the user

[0729] 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.

[0730] 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.

[0731] 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.

[0732] [Third embodiment]

[0733] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0734] 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.

[0735] 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).

[0736] 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.

[0737] 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.

[0738] 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).

[0739] 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.

[0740] 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.

[0741] 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.

[0742] 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.

[0743] 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.

[0744] 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."

[0745] This invention is a system that utilizes a generative AI model to propose the optimal communication plan based on the user's smartphone usage status and desired conditions. This system is mainly composed of a user, a terminal, and a server, and is implemented in the following form.

[0746] First, the device displays a questionnaire to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required services, etc.). Once the user has completed the input, the device collects this information as a single data set and sends it to the server.

[0747] Next, the server receives the user's data sent from the device. The received data includes the user's current communication plan, call usage, data usage, desired service, desired rate range, etc. The server uses a generative AI model to analyze this data. The generative AI model calculates the optimal communication plan based on the user's data. This model includes an algorithm that derives the optimal plan by taking into account multiple factors related to the user's data usage, call duration, and budget, for example.

[0748] The server uses the generative AI model to calculate the optimal communication plan, and then sends the results to the device, including details of the communication plan it determines to be optimal (plan name, monthly fee, data volume, additional services, etc.).

[0749] Finally, the device displays the information on the optimal plan received from the server to the user, allowing the user to select the plan that best suits them.

[0750] Specific examples

[0751] A user is currently using "Plan A," which includes 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen.

[0752] (Device) collects the following information from you:

[0753] Current communication plan: Plan A

[0754] Call usage: 100 minutes per month

[0755] Data usage: 5GB per month

[0756] Desired service: Unlimited data plan

[0757] Desired price range: Up to 4,000 yen per month

[0758] This information is sent to a server, which then analyzes the data using a generative AI model. For example, the model considers the user's data volume, call duration, and budget to calculate the optimal plan, such as a "value plan" that includes unlimited data and international calls for 3,000 yen per month.

[0759] (Server) sends this "Special Offer" information to (Device), and the Device displays the following to the user:

[0760] Best plan: Value plan

[0761] Monthly fee: 3,000 yen

[0762] Data capacity: Unlimited

[0763] International calls: Yes

[0764] This allows users to easily find the best communication plan for them. Through this system, users can select the best plan while saving time and effort.

[0765] The processing flow will be explained below.

[0766] Step 1:

[0767] (Device) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.).

[0768] Step 2:

[0769] The user follows the question form displayed on the terminal to input information about the communication plan currently in use, the amount of call usage, the amount of data usage, the desired service content, and the desired rate range.

[0770] Step 3:

[0771] (Terminal) collects the information entered by the user, compiles it into a single data set, and sends it to the server.

[0772] Step 4:

[0773] (Server) receives the user's dataset sent from the device and prepares it for analysis.

[0774] Step 5:

[0775] The server inputs the received user data into the generative AI model, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes multiple factors, such as the user's data volume, call duration, and rate band.

[0776] Step 6:

[0777] The server sends the optimal plan information obtained from the generative AI model to the device. The optimal plan information includes the plan name, monthly fee, data capacity, and additional service details.

[0778] Step 7:

[0779] The terminal displays the information about the optimal plan received from the server to the user.

[0780] Step 8:

[0781] The user checks the information about the optimal plan displayed on the device and selects the plan that best suits their usage situation and desired conditions.

[0782] Example 1

[0783] 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."

[0784] The problem with the traditional method of selecting a communication plan is that users have to manually search for the best plan based on their usage and desired conditions, which is a time-consuming and labor-intensive process. Furthermore, it is difficult to determine whether the selected plan is truly optimal for the user, and in some cases, users may end up choosing an inappropriate plan. This often leaves users unsure about communication costs and service satisfaction.

[0785] 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.

[0786] In this invention, the server includes means for prompting a user to input information regarding their current communication plan, their voice and data communication usage status, and their desired conditions, means for collecting the information input by the user and sending it to the server, means for the server to analyze the information and calculate an optimal communication plan using a generative artificial intelligence model, and means for displaying the calculated optimal communication plan to the user. This allows the user to automatically receive optimal communication plans and quickly and easily select the plan that best suits their usage status and desired conditions.

[0787] A "user" is an individual who uses the system to input their own communication plan, usage status, and desired conditions.

[0788] "Communication plan" refers to the specific plan details for the communication service to which the user has subscribed, including fees, data capacity, call time, etc.

[0789] "Usage status" refers to information that indicates how much a user actually uses a communication service, such as the amount of call time and data usage.

[0790] "Desired conditions" refer to the specific requirements and conditions that a user has for a communication plan, such as the price range they desire and the services they require.

[0791] "Terminal" refers to an electronic device that a user uses to input information and send it to a server. Examples include smartphones and personal computers.

[0792] The "server" is a central computer system that receives information sent from the terminal, analyzes it using a generative artificial intelligence model, and calculates the optimal communication plan.

[0793] A "generative artificial intelligence model" is a machine learning model equipped with an algorithm for deriving the optimal communication plan based on information entered by the user.

[0794] The "optimal communication plan" is the communication plan that the system determines to be the most suitable in terms of cost, service content, etc. based on the user's usage and desired conditions.

[0795] This invention is a system that uses a generative AI model to propose an optimal communication plan based on the user's usage status and desired conditions. This system is mainly composed of a user, a terminal, and a server, and is implemented in the following form.

[0796] First, the user accesses the inquiry form using their device. This inquiry form is created using HTML, CSS, and JavaScript, and provides an interface that allows users to intuitively enter information. Specifically, the user enters information such as their current communication plan, monthly call time, data communication usage, desired service, and desired price range. For example, "Communication plan name: Plan A," "Call time: 100 minutes," "Data communication amount: 5GB," "Desired service: Unlimited data," and "Desired price range: 4,000 yen or less."

[0797] As the user enters information, the device collects this data as a dataset and sends it to the server using an HTTP POST request. The device-side program is implemented in JavaScript, and this dataset contains all the entered information.

[0798] This data is then received by a server. Built using a web framework such as Node.js or Python's Flask, the server receives the data via HTTP requests. The server analyzes the received data and cleanses and normalizes it as necessary. It then uses a generative AI model (for example, a model using TensorFlow or PyTorch) to analyze the data. This generative AI model contains algorithms that derive the optimal communication plan based on the user's data usage, call duration, and desired conditions.

[0799] As a concrete example, the following prompt sentences can be input to a generative AI model:

[0800] "The user's current data plan is "Plan A," which allows for 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen. Please suggest the best data plan that meets these conditions."

[0801] Once the generative AI model calculates the optimal data plan, the result is converted into a data format such as JSON and sent to the device as an HTTP response, which includes the name of the optimal plan, the monthly fee, data volume, and details of additional services.

[0802] Finally, the device analyzes the data received from the server and displays it in an easy-to-read format for the user. This display is stylishly formatted using HTML and CSS. For example, information such as "Value Plan," "Monthly Fee: 3,000 yen," "Data Capacity: Unlimited," and "International Calls: Available" is displayed in list format. Using this information, users can select the communication plan that best suits them.

[0803] Through this system, users can easily find the communication plan that best suits their usage and desired conditions, while saving time and effort.

[0804] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0805] Step 1:

[0806] (User) enters information into a question form.

[0807] The user opens a browser on their device and accesses the inquiry form. The form has drop-down menus and radio buttons, and they input information in order, such as "Plan name: Plan A," "Call time: 100 minutes," "Data amount: 5GB," "Desired service: Unlimited data," and "Desired price range: 4,000 yen or less." The information entered by the user becomes the input data for the system.

[0808] Step 2:

[0809] (Device) collects input data and creates an HTTP POST request.

[0810] When the user clicks the "Submit" button, JavaScript is executed to combine the input data into a single data object. This data object contains all the information entered by the user. The device then sends this data object to the server as an HTTP POST request. It generates a JSON-formatted request body based on the input data, and the output is a request to the server.

[0811] Step 3:

[0812] (Server) receives the HTTP POST request and parses the data.

[0813] The server receives HTTP requests using a web framework such as Node.js or Python's Flask. It takes the received data and, if necessary, cleanses the input data (for example, by removing unnecessary whitespace or symbols) and normalizes it (for example, by standardizing the data format). In this process, the input data is parsed and converted into a format suitable for the AI ​​model. The output of the parsing process becomes the input data for the generative AI model.

[0814] Step 4:

[0815] (Server) analyzes the data using a generative AI model and calculates the optimal communication plan.

[0816] The server runs a generative AI model using AI frameworks such as TensorFlow and PyTorch. The analyzed data is input into the AI ​​model, which then calculates the optimal communication plan based on multiple factors (data volume, call duration, budget, etc.). The output of the generative AI model is detailed information about the optimal communication plan for the user (plan name, monthly fee, data volume, additional services, etc.).

[0817] Step 5:

[0818] (Server) sends details of the optimal communication plan to the device.

[0819] The server converts the detailed information obtained from the generative AI model into a data format such as JSON, and sends this to the device as an HTTP response. The output of the conversion process becomes the response data sent to the device.

[0820] Step 6:

[0821] (Device) receives the response from the server and displays it to the user.

[0822] The device uses JavaScript to analyze the data received from the server and reflects it in HTML. For example, information such as "Value Plan," "Monthly Fee: 3,000 yen," "Data Capacity: Unlimited," and "International Calls: Available" is displayed on the screen in list format. In this process, the response data is converted into a format that is easy for the user to understand and displayed on the screen. The output of the display process becomes the communication plan information presented to the user.

[0823] (Application example 1)

[0824] 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."

[0825] In recent years, the use of online shopping has increased dramatically, but many users spend a lot of time and effort trying to find the best purchase plan and discount information. To solve this problem, a system that automatically suggests the best purchase plan based on the user's shopping habits and desired conditions is needed. However, current systems do not effectively utilize the user's detailed shopping history or individual desired conditions, making it difficult to find the best plan.

[0826] 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.

[0827] In this invention, the server includes a means for prompting a user to input information about their current purchase plan, shopping habits, and desired conditions, a means for collecting the information input by the user and sending it to the server, a means for the server to analyze the information and calculate an optimal purchase plan using a generative artificial intelligence model, and a means for displaying details of the optimal purchase plan to the user, thereby enabling the user to easily find a purchase plan optimized to their shopping habits and desires, thereby saving time and effort.

[0828] A "user" is someone who uses this system to receive the optimal purchase plan.

[0829] "Purchase Plan" means a purchase option optimized for a User when purchasing an item online, including fees, discounts, subscription services, etc.

[0830] "Shopping habits" refers to the behavioral patterns of how a user typically purchases products, including purchase frequency and product category preferences.

[0831] "Desired conditions" are the specific requirements that a user has for a purchase plan, including price, type of product, and service content.

[0832] "Means for inputting information" refers to the interface that allows users to input information such as their current purchasing status and desired conditions into the system.

[0833] "Means for collecting information and transmitting it to the server" refers to the technical means by which the information entered by the user is compiled into a single data set and transmitted to the server.

[0834] "Means for analyzing the information on the server and calculating the optimal purchase plan using a generative AI model" refers to technology that enables a server to analyze information input by a user using a generative AI model and calculate the optimal purchase plan.

[0835] The "means for displaying the optimal purchase plan to the user" refers to an interface for visually presenting to the user the details of the optimal purchase plan calculated by the server.

[0836] "Generative AI model" refers to a machine learning algorithm used to analyze collected data and generate optimal suggestions for users.

[0837] To implement this invention, it is necessary to build a system that proposes optimal purchase plans based on the user's shopping habits and desired conditions. This system is mainly composed of a user terminal and a server.

[0838] First, the user terminal provides an interface that allows the user to input information about their current purchase plan, shopping habits, and desired conditions. This interface is realized by an application installed on a device such as a smartphone, smart glasses, a head-mounted display, or a personal robot.

[0839] Once the user has finished entering the information, the device collects this information as a single data set and sends it to the server. This communication must be secure and efficient, so for example, the HTTPS protocol is used.

[0840] The server uses a generative AI model to analyze the dataset received from the user. This generative AI model includes an algorithm that considers various factors (e.g., the user's shopping history, purchase frequency, desired conditions, etc.) to calculate the optimal purchase plan. Specifically, the server is built using the Node.js and Express.js frameworks and uses OpenAI's generative AI model.

[0841] For example, if a user provides the following information:

[0842] Current purchase plan: 10 items per month

[0843] Shopping habits: Often look for discounts in advance

[0844] Desired conditions: Monthly budget of 5,000 yen, purchase once a week

[0845] With this information, the server prompts the generative AI model with the following prompt:

[0846] Example prompt sentence:

[0847] Your current purchasing situation: 10 items purchased per month

[0848] Your shopping habits: I often look for discounts in advance

[0849] Your budget: Your monthly budget is 5,000 yen.

[0850] Your purchase frequency: Once a week

[0851] Please take the above into consideration and suggest the best purchase plan for you.

[0852] Based on these prompts, the generative AI model recommends the best purchasing plan for the user's needs, including the best subscription services, discount offers, and bulk buying options.

[0853] Finally, the information on the optimal purchase plan obtained from the server is sent to the user's device and visually displayed, allowing the user to easily find a purchase plan that is optimized for their shopping habits and preferences.

[0854] This system allows users to save time and effort while choosing the most suitable purchasing option.

[0855] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0856] Step 1:

[0857] The user inputs information about their current purchase plan, shopping habits, and desired conditions into the terminal, including their current purchase plan (e.g., buying 10 items per month), shopping habits (e.g., often looking for discounts in advance), and desired conditions (e.g., monthly budget of 5,000 yen, purchase frequency once a week).

[0858] Step 2:

[0859] The device collects the information entered by the user as a single data set and sends it to the server. This data set includes all of the user's input information. For example, the input data is configured in JSON format and sent securely to the server using the HTTPS protocol.

[0860] Step 3:

[0861] The server receives the data set sent from the device and analyzes this information with the generative AI model. At this time, the received data is converted into a prompt sentence and sent to the generative AI model. For example, the following prompt sentence is generated:

[0862] Your current purchasing situation: 10 items purchased per month

[0863] Your shopping habits: I often look for discounts in advance

[0864] Your budget: Your monthly budget is 5,000 yen.

[0865] Your purchase frequency: Once a week

[0866] Please take the above into consideration and suggest the best purchase plan for you.

[0867] The server sends this prompt to OpenAI's generative AI model and receives the AI ​​model's response.

[0868] Step 4:

[0869] The generative AI model generates the optimal purchase plan based on prompts sent by the server. The model analyzes factors such as the user's shopping habits, budget, and purchase frequency to calculate the optimal purchasing options (e.g., subscription services or discount offers). The output is returned to the server as a text response.

[0870] Step 5:

[0871] The server extracts and organizes the details of the most suitable purchase plan based on the response received from the generative AI model, and performs additional processing (e.g., converting the response format or filtering the information) as needed. Finally, it generates a dataset to display to the user.

[0872] Step 6:

[0873] The server sends the generated optimal purchase plan dataset to the terminal, which includes details of the purchase plan (e.g., subscription service type, discount rate, fee, etc.).

[0874] Step 7:

[0875] The terminal displays the information on the optimal purchase plan received from the server to the user. The user can check the plan details visually displayed on the terminal screen and select the optimal purchase option. This allows the user to efficiently make purchases based on the purchase plan optimized for their needs.

[0876] 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.

[0877] This invention combines a system that utilizes a generative AI model to propose the optimal communication plan based on the user's smartphone usage status and desired conditions with an emotion engine that recognizes the user's emotions. This system is composed of a user, a terminal, a server, and an emotion engine, and is implemented in the following form.

[0878] First, the (terminal) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.). The (user) enters this information according to the question form displayed on the terminal.

[0879] (Device) collects the information entered by the user, compiles it into a single data set, and sends it to the server. (Server) receives the user data sent from the device and prepares it for analysis.

[0880] The server inputs the received user data into a generative AI model and runs the model to calculate the optimal communication plan. This generative AI model includes an algorithm that analyzes multiple factors, such as the user's data volume, call duration, and rate band, to derive the optimal plan.

[0881] Furthermore, the present invention adds an emotion engine. The emotion engine analyzes the user's emotional state based on the user's input data and interactions. The analysis results are used to optimize communication plans using a generative AI model. For example, if the user is under stress, the emotion engine provides that information to the server, which can then make suggestions to help the user relax.

[0882] The server sends the optimal plan calculated based on information obtained from the generative AI model and emotion engine to the device. This optimal plan information includes the plan name, monthly fee, data capacity, additional service details, etc. The device displays the optimal plan information received from the server to the user.

[0883] Specific examples

[0884] A user is currently using "Plan A," which includes 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen.

[0885] First, (Device) collects the following information from the User:

[0886] Current communication plan: Plan A

[0887] Call usage: 100 minutes per month

[0888] Data usage: 5GB per month

[0889] Desired service: Unlimited data plan

[0890] Desired price range: Up to 4,000 yen per month

[0891] This information is sent to a server, which then analyzes the data using a generative AI model. For example, the model considers the user's data volume, call duration, and budget to calculate the optimal plan, such as a "value plan" that includes unlimited data and international calls for 3,000 yen per month.

[0892] Meanwhile, the Emotion Engine analyzes the data entered by the user and their reactions during operation to detect when the user is in a low-stress state. This information is also taken into account in the analysis results of the generative AI model to select a plan that best suits the user.

[0893] (Server) sends this "Special Offer" information to (Device), and the Device displays the following to the user:

[0894] Best plan: Value plan

[0895] Monthly fee: 3,000 yen

[0896] Data capacity: Unlimited

[0897] International calls: Yes

[0898] The user checks the information on the optimal plan displayed on the device and selects the plan that best suits them. Through this system, users can save time and effort while selecting the optimal plan that takes into account their emotional state.

[0899] The processing flow will be explained below.

[0900] Step 1:

[0901] (Device) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.).

[0902] Step 2:

[0903] The user follows the question form displayed on the terminal to input information about the current communication plan, call usage, data usage, desired service content, and desired rate range.

[0904] Step 3:

[0905] (Terminal) collects the information entered by the user, compiles it into a single data set, and sends it to the server.

[0906] Step 4:

[0907] (Server) receives the user's dataset sent from the device and prepares it for analysis.

[0908] Step 5:

[0909] The Emotion Engine analyzes the user's emotional state based on the user's input data and interactions. The analysis results are used to determine the user's emotional state in the current usage situation.

[0910] Step 6:

[0911] The server inputs the received user data into the generative AI model, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes multiple factors, such as the user's data volume, call duration, and rate band.

[0912] Step 7:

[0913] The server compares the optimal plan calculated based on the generative AI model with the emotion analysis results from the emotion engine, and further adjusts the plan according to the user's emotional state.

[0914] Step 8:

[0915] The server sends the generated optimal plan information to the terminal. This plan information includes the plan name, monthly fee, data capacity, additional services, etc.

[0916] Step 9:

[0917] The device receives the optimal plan from the server and displays it to the user. The displayed information takes into account the user's emotional state, allowing the user to make a more relaxed selection.

[0918] Step 10:

[0919] The user checks the information about the optimal plan displayed on the device and selects the plan that best suits their usage situation and desired conditions.

[0920] Example 2

[0921] 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."

[0922] While conventional communication plan proposal systems have methods for proposing optimal plans based on the user's usage status and desired conditions, they do not take into account the user's emotional state. As a result, they may propose plans that users find stressful or difficult to use, and they are unable to fully improve user satisfaction. In addition, many systems provide users with a large amount of information, which makes selection time-consuming and inefficient.

[0923] 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.

[0924] In this invention, the server includes: means for prompting a user to input information regarding their current communication plan, their voice and data communication usage status, and their desired conditions; means for collecting the information input by the user and sending it to the server; means for the server to analyze the information and calculate an optimal communication plan using a generative artificial intelligence model; means for displaying the calculated optimal communication plan to the user; emotion engine means for analyzing the emotional state of the user based on input data and interaction data; and means for optimizing the communication plan based on the analysis results of the emotion engine. This makes it possible to propose an optimal communication plan that takes into account not only the user's usage status and desired conditions, but also their emotional state, thereby improving user satisfaction.

[0925] "User" refers to any individual or entity that uses the System to optimize their communication plans.

[0926] "Terminal" refers to an electronic device used by a user to input information. Examples include smartphones and personal computers.

[0927] "Server" refers to a central processing unit that receives and analyzes information sent by users.

[0928] "Information" refers to data entered by the user, such as communication plans, voice and data usage, and desired conditions.

[0929] A "generative artificial intelligence model" refers to a model that uses machine learning algorithms to calculate the optimal communication plan from user data.

[0930] "Optimal communication plan" refers to the most suitable plan calculated based on the user's data usage, call time, fees, etc.

[0931] "Displaying means" refers to a method or device for presenting the calculated optimal communication plan to the user.

[0932] An "emotion engine" refers to software that analyzes user input and interaction data to assess the user's emotional state.

[0933] "Interaction data" refers to data about the actions and responses users take on the system.

[0934] "Optimization" refers to the process of calculating the outcome that best meets specific goals or conditions.

[0935] The present invention is a system for optimizing a user's communication plan, proposing the optimal communication plan based on the user's usage status, desired conditions, and emotional state. This system is composed of a user, a terminal, a server, and an emotion engine, and is implemented as follows.

[0936] First, the device displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required services, etc.). This question form is created using HTML and JavaScript. Specifically, it provides a user-friendly UI that allows users to easily enter information.

[0937] The user enters this information in the question form displayed on the device. For example, the user enters "Plan A" as their current communication plan, 100 minutes / month as their call usage, 5GB / month as their data usage, an unlimited data plan as their desired service, and a monthly fee of up to 4,000 yen.

[0938] The device collects the information entered by the user and compiles it into a single dataset. This dataset is sent to the server in a format such as JSON. For example, JavaScript can be used to convert the data into JSON and send it to an API endpoint using an HTTP POST request.

[0939] The server receives user data sent from the device and prepares it for analysis. At this stage, data is validated and normalized, and data is reshaped and missing values ​​are imputed using Python and data processing libraries (e.g., Pandas).

[0940] The server then inputs the preprocessed data into a generative AI model such as TensorFlow or PyTorch, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes the user's call duration, data usage, tariff band, etc.

[0941] Furthermore, the present invention uses an emotion engine. The emotion engine analyzes the user's input data and reactions during operation (e.g., input speed and contextual data) to evaluate the user's emotional state. Machine learning technology is used for this emotion analysis. The analysis results are fed back to the generative AI model, which then optimizes the communication plan taking the user's emotional state into account.

[0942] The server determines the optimal communication plan based on the information obtained from the generative AI model and emotion engine, and sends the final result to the device. The information sent includes the plan name, monthly fee, data capacity, and additional service details.

[0943] The device displays the information about the best plan received from the server to the user. For example, it uses HTML and JavaScript to display "Best plan: Value plan, Monthly fee: 3000 yen, Data capacity: Unlimited, International calls: Available."

[0944] Prompt Sentence Examples

[0945] For example, if a user enters the following information:

[0946] Current communication plan: Plan A

[0947] Call usage: 100 minutes per month

[0948] Data usage: 5GB per month

[0949] Desired service: Unlimited data plan

[0950] Desired price range: Up to 4,000 yen per month

[0951] This information is sent to a server, which uses a generative AI model to analyze the data and calculate the communication plan that best suits the user's requirements.

[0952] This not only enables users to quickly and easily find the best communication plan for them, but also allows them to receive more personalized suggestions that take their emotional state into account through an emotion engine.

[0953] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0954] Step 1:

[0955] The user enters information about their current communication plan, voice and data usage, and desired terms.

[0956] Input: Data entered by the user into the question form (e.g., current communication plan "Plan A," call usage of 100 minutes / month, data usage of 5GB / month, desired fee of 4,000 yen or less, etc.).

[0957] In concrete terms, the user enters answers into a form written in HTML and JavaScript.

[0958] Step 2:

[0959] The device collects the information the user enters and compiles it into a single data set.

[0960] Input: Data entered by the user.

[0961] Output: The dataset in JSON format.

[0962] Specifically, the device converts the data entered by the user into JSON format using JavaScript and sends it to the server using an HTTP POST request.

[0963] Step 3:

[0964] The server receives the user data sent from the device and prepares it for analysis.

[0965] Input: A dataset in JSON format received from the terminal.

[0966] Output: A normalized dataset.

[0967] Specifically, data processing libraries such as Python and Pandas are used to normalize data and fill in missing values.

[0968] Step 4:

[0969] The server inputs the preprocessed data into a generative AI model to calculate the optimal communication plan.

[0970] Input: The normalized dataset.

[0971] Output: Proposal of optimal communication plan.

[0972] Specifically, it uses TensorFlow and PyTorch to input data into a model and perform inference. The generative AI model takes into account factors such as the user's call duration, data usage, and price band.

[0973] Step 5:

[0974] The emotion engine analyzes the user's emotional state based on input data and interaction data.

[0975] Input: User input data and response data during operation.

[0976] Output: User's emotional state rating data.

[0977] Specifically, it uses machine learning models to analyze the user's typing speed and context to assess their emotional state.

[0978] Step 6:

[0979] The server integrates the results obtained from the generative AI model with the analysis results of the emotion engine and reevaluates the optimal communication plan.

[0980] Input: Inference results of the generative AI model, evaluation data of the emotion engine.

[0981] Output: The final optimal communication plan.

[0982] Specifically, the results of the generative AI model are added to the analysis results of the emotion engine, and the data is reprocessed to make optimal suggestions.

[0983] Step 7:

[0984] The server sends information about the optimal communication plan to the terminal.

[0985] Input: The final optimal communication plan.

[0986] Output: Plan information sent to the device.

[0987] Specifically, optimal plan information in JSON format is sent as an HTTP response.

[0988] Step 8:

[0989] The terminal displays the information on the optimum plan received from the server to the user.

[0990] Input: Information of the best plan received from the server.

[0991] Output: Details of the best plan displayed to the user.

[0992] Specifically, HTML and JavaScript are used to display the optimal plan to the user (e.g., "Optimal plan: Value plan, Monthly fee: 3,000 yen, Data capacity: Unlimited, International calls: Available").

[0993] The above are the specific processing steps of the program of this system.

[0994] (Application example 2)

[0995] 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."

[0996] Today's wide variety of electronic payment services makes it difficult for users to choose the plan that best suits them. As a result, users often cannot enjoy the most advantageous rewards and benefits, and they often feel stressed. Furthermore, there is no system that can propose the optimal plan taking into account the user's emotional state, making it impossible to provide an optimal experience for each individual user. There is a need to solve these problems.

[0997] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0998] In this invention, the server includes: means for prompting a user to input information about their current electronic payment service, monthly expenditures and frequency of use, and desired benefits; means for collecting the information input by the user and sending it to the server; means for the server to analyze the information and calculate an optimal electronic payment plan using a generative AI model; means for analyzing the user's emotional state using an emotion engine and taking this into consideration when calculating the optimal plan; and means for displaying the calculated optimal electronic payment plan to the user. This provides an optimal electronic payment plan that takes into account the user's usage status and emotional state, allowing the user to make the most of their benefits and select the optimal plan without feeling stressed.

[0999] "User" refers to an individual or corporation that uses the system to select and use an electronic payment service plan.

[1000] "Electronic payment services" refer to services that enable online payments and transactions using the Internet or mobile devices.

[1001] "Monthly expenditure" refers to the total amount paid by a user using electronic payment services each month.

[1002] "Frequency of use" refers to the number of times or frequency with which a user uses an electronic payment service within a certain period of time.

[1003] "Desired benefits" are the added value of electronic payment services that users desire, including points rewards, no fees, and affiliated service benefits.

[1004] "Means for inputting information" refers to the user interface functions that allow the user to input the necessary information into the system.

[1005] "Means for collecting information and transmitting it to a server" refers to the function of collecting information entered by the user and transmitting it to a server via a communication network.

[1006] "Means for calculating optimal electronic payment plans using generative AI models" refers to algorithms that analyze and propose optimal plans based on user information collected using artificial intelligence technology.

[1007] An "emotion engine" refers to software or a system that analyzes a user's emotional state from their input data and reactions during operation.

[1008] "Means to consider when analyzing emotional state and calculating the optimal plan" refers to the function of reflecting emotional state information obtained from the emotion engine in the generative AI model and proposing the optimal plan to the user.

[1009] The "optimal electronic payment plan" refers to an electronic payment service plan that provides the greatest benefits by comprehensively considering the user's usage situation, desired conditions, and emotional state.

[1010] "Means for displaying the plan to the user" refers to a display or screen display function for visually presenting information about the calculated optimal plan to the user.

[1011] This invention describes a system that allows users to select the optimal electronic payment service. This system proposes the optimal electronic payment plan to the user by calculating the optimal plan using a generative AI model based on input user information and by analyzing and considering the user's emotional state using an emotion engine.

[1012] 1. System program for implementing this application example

[1013] A specific example of this system will be described below.

[1014] 1.1 Hardware and Software Used

[1015] Smartphone: Used by users to enter their information and view the best plan for them (e.g., iOS or Android device).

[1016] Server: Performs data analysis and processing of generative AI models and emotion engines (e.g., cloud-based servers).

[1017] software:

[1018] Mobile App: User frontend developed using React Native.

[1019] Server-side application: Built using Node.js.

[1020] Data Analysis: Python and its libraries (Pandas, Scikit-Learn).

[1021] Generative AI model: OpenAI's GPT-4.

[1022] Emotion engine: Emotion AI API.

[1023] 2. Explain the generated program's processing in natural language

[1024] The server specifically implements the present invention using the following means.

[1025] 2.1 User Information Collection

[1026] First, users enter their current electronic payment services, monthly spending and frequency of use, and desired rewards through a smartphone app. This information is collected via the user interface.

[1027] 2.2 Data Transmission

[1028] The app compiles the collected data into a single dataset and sends it to a server via HTTPS.

[1029] 2.3 Data analysis

[1030] The server inputs the received data into a generative AI model (e.g., OpenAI's GPT-4) to calculate the optimal electronic payment plan based on the user's spending patterns and desired conditions.

[1031] 2.4 Emotional State Analysis

[1032] The emotion engine analyzes the user's emotional state based on their input data and reactions during operation. The obtained emotional information is reflected in the analysis results of the generative AI model.

[1033] 2.5 Proposing the optimal plan

[1034] Based on the analysis results of the generative AI model and emotion engine, the server calculates an optimal plan, which is then displayed to the user via a smartphone app.

[1035] 3. Add examples to your description

[1036] Let's say a user currently uses "Service A" as their electronic payment service, and has entered that their monthly spending is 30,000 yen and that they use the service frequently. Furthermore, this user wishes to receive points back.

[1037] Prompt Sentence Examples

[1038] 1. Example prompts for collecting user information:

[1039] Please select the electronic payment service you are currently using.

[1040] Enter your monthly spending and frequency of use.

[1041] Please select the benefits you would like (e.g. points reward, no fees, partner service benefits).

[1042] 2. Example prompts to be input to the generative AI model when proposing the optimal plan:

[1043] The data provided by the user is as follows:

[1044] Current service: Service A

[1045] Monthly expenses: 30,000 yen

[1046] Frequency of use: High

[1047] Desired reward: Points redemption

[1048] Suggest the best e-payment plan for this user. Emotional state is low stress.

[1049] This allows users to easily find the most advantageous electronic payment plan for themselves and enjoy a comfortable service that takes their emotional state into consideration.

[1050] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1051] Step 1:

[1052] The terminal displays a form for the user to enter information about their electronic payment service usage (current services used, monthly expenditures, frequency of use, and desired benefits).

[1053] Input: Information about the user's electronic payment service

[1054] Output: User's input dataset

[1055] Step 2:

[1056] The device collects the information entered by the user and sends it to the server via HTTPS.

[1057] Input: User input dataset

[1058] Output: The dataset sent to the server

[1059] Step 3:

[1060] The server receives the received dataset and prepares it for input to the generative AI model by formatting the data and converting it into a format that the AI ​​model can understand.

[1061] Input: Dataset received by the server

[1062] Output: A formatted dataset

[1063] Step 4:

[1064] The server then inputs the formatted data set into a generative AI model (e.g., OpenAI GPT-4) to calculate the optimal electronic payment plan. The generative AI model performs data analysis and inference based on the user's spending patterns and preferences.

[1065] Input: Formatted dataset

[1066] Output: Proposal of optimal electronic payment plan

[1067] Step 5:

[1068] The server uses an emotion engine to analyze the user's emotional state, such as assessing stress levels and satisfaction levels based on input data and reactions during operation. This information is also added to the analysis results.

[1069] Input: Formatted dataset and user interaction data

[1070] Output: User's emotional state information

[1071] Step 6:

[1072] The server combines information obtained from the generative AI model and the emotion engine to determine the final optimal plan, taking into account the user's emotional state to select a plan that is most comfortable to use.

[1073] Input: Optimal e-payment plan recommendations and emotional state information

[1074] Output: The final optimal plan

[1075] Step 7:

[1076] The server then sends the final selected optimal plan to the device, again via HTTPS.

[1077] Input: The final optimal plan

[1078] Output: Plan data sent to device

[1079] Step 8:

[1080] The device will then display the received information about the optimal plan to the user, visually providing information such as the plan name, monthly cost, benefits, and details of affiliated services.

[1081] Input: Received plan data

[1082] Output: Information about the best plan displayed to the user

[1083] 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.

[1084] 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.

[1085] 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.

[1086] [Fourth embodiment]

[1087] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1088] 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.

[1089] 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).

[1090] 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.

[1091] 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.

[1092] 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).

[1093] 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.

[1094] 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.

[1095] 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.

[1096] 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.

[1097] 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.

[1098] 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.

[1099] 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."

[1100] This invention is a system that utilizes a generative AI model to propose the optimal communication plan based on the user's smartphone usage status and desired conditions. This system is mainly composed of a user, a terminal, and a server, and is implemented in the following form.

[1101] First, the device displays a questionnaire to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required services, etc.). Once the user has completed the input, the device collects this information as a single data set and sends it to the server.

[1102] Next, the server receives the user's data sent from the device. The received data includes the user's current communication plan, call usage, data usage, desired service, desired rate range, etc. The server uses a generative AI model to analyze this data. The generative AI model calculates the optimal communication plan based on the user's data. This model includes an algorithm that derives the optimal plan by taking into account multiple factors related to the user's data usage, call duration, and budget, for example.

[1103] The server uses the generative AI model to calculate the optimal communication plan, and then sends the results to the device, including details of the communication plan it determines to be optimal (plan name, monthly fee, data volume, additional services, etc.).

[1104] Finally, the device displays the information on the optimal plan received from the server to the user, allowing the user to select the plan that best suits them.

[1105] Specific examples

[1106] A user is currently using "Plan A," which includes 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen.

[1107] (Device) collects the following information from you:

[1108] Current communication plan: Plan A

[1109] Call usage: 100 minutes per month

[1110] Data usage: 5GB per month

[1111] Desired service: Unlimited data plan

[1112] Desired price range: Up to 4,000 yen per month

[1113] This information is sent to a server, which then analyzes the data using a generative AI model. For example, the model considers the user's data volume, call duration, and budget to calculate the optimal plan, such as a "value plan" that includes unlimited data and international calls for 3,000 yen per month.

[1114] (Server) sends this "Special Offer" information to (Device), and the Device displays the following to the user:

[1115] Best plan: Value plan

[1116] Monthly fee: 3,000 yen

[1117] Data capacity: Unlimited

[1118] International calls: Yes

[1119] This allows users to easily find the best communication plan for them. Through this system, users can select the best plan while saving time and effort.

[1120] The processing flow will be explained below.

[1121] Step 1:

[1122] (Device) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.).

[1123] Step 2:

[1124] The user follows the question form displayed on the terminal to input information about the communication plan currently in use, the amount of call usage, the amount of data usage, the desired service content, and the desired rate range.

[1125] Step 3:

[1126] (Terminal) collects the information entered by the user, compiles it into a single data set, and sends it to the server.

[1127] Step 4:

[1128] (Server) receives the user's dataset sent from the device and prepares it for analysis.

[1129] Step 5:

[1130] The server inputs the received user data into the generative AI model, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes multiple factors, such as the user's data volume, call duration, and rate band.

[1131] Step 6:

[1132] The server sends the optimal plan information obtained from the generative AI model to the device. The optimal plan information includes the plan name, monthly fee, data capacity, and additional service details.

[1133] Step 7:

[1134] The terminal displays the information about the optimal plan received from the server to the user.

[1135] Step 8:

[1136] The user checks the information about the optimal plan displayed on the device and selects the plan that best suits their usage situation and desired conditions.

[1137] Example 1

[1138] 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."

[1139] The problem with the traditional method of selecting a communication plan is that users have to manually search for the best plan based on their usage and desired conditions, which is a time-consuming and labor-intensive process. Furthermore, it is difficult to determine whether the selected plan is truly optimal for the user, and in some cases, users may end up choosing an inappropriate plan. This often leaves users unsure about communication costs and service satisfaction.

[1140] 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.

[1141] In this invention, the server includes means for prompting a user to input information regarding their current communication plan, their voice and data communication usage status, and their desired conditions, means for collecting the information input by the user and sending it to the server, means for the server to analyze the information and calculate an optimal communication plan using a generative artificial intelligence model, and means for displaying the calculated optimal communication plan to the user. This allows the user to automatically receive optimal communication plans and quickly and easily select the plan that best suits their usage status and desired conditions.

[1142] A "user" is an individual who uses the system to input their own communication plan, usage status, and desired conditions.

[1143] "Communication plan" refers to the specific plan details for the communication service to which the user has subscribed, including fees, data capacity, call time, etc.

[1144] "Usage status" refers to information that indicates how much a user actually uses a communication service, such as the amount of call time and data usage.

[1145] "Desired conditions" refer to the specific requirements and conditions that a user has for a communication plan, such as the price range they desire and the services they require.

[1146] "Terminal" refers to an electronic device that a user uses to input information and send it to a server. Examples include smartphones and personal computers.

[1147] The "server" is a central computer system that receives information sent from the terminal, analyzes it using a generative artificial intelligence model, and calculates the optimal communication plan.

[1148] A "generative artificial intelligence model" is a machine learning model equipped with an algorithm for deriving the optimal communication plan based on information entered by the user.

[1149] The "optimal communication plan" is the communication plan that the system determines to be the most suitable in terms of cost, service content, etc. based on the user's usage and desired conditions.

[1150] This invention is a system that uses a generative AI model to propose an optimal communication plan based on the user's usage status and desired conditions. This system is mainly composed of a user, a terminal, and a server, and is implemented in the following form.

[1151] First, the user accesses the inquiry form using their device. This inquiry form is created using HTML, CSS, and JavaScript, and provides an interface that allows users to intuitively enter information. Specifically, the user enters information such as their current communication plan, monthly call time, data communication usage, desired service, and desired price range. For example, "Communication plan name: Plan A," "Call time: 100 minutes," "Data communication amount: 5GB," "Desired service: Unlimited data," and "Desired price range: 4,000 yen or less."

[1152] As the user enters information, the device collects this data as a dataset and sends it to the server using an HTTP POST request. The device-side program is implemented in JavaScript, and this dataset contains all the entered information.

[1153] This data is then received by a server. Built using a web framework such as Node.js or Python's Flask, the server receives the data via HTTP requests. The server analyzes the received data and cleanses and normalizes it as necessary. It then uses a generative AI model (for example, a model using TensorFlow or PyTorch) to analyze the data. This generative AI model contains algorithms that derive the optimal communication plan based on the user's data usage, call duration, and desired conditions.

[1154] As a concrete example, the following prompt sentences can be input to a generative AI model:

[1155] "The user's current data plan is "Plan A," which allows for 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen. Please suggest the best data plan that meets these conditions."

[1156] Once the generative AI model calculates the optimal data plan, the result is converted into a data format such as JSON and sent to the device as an HTTP response, which includes the name of the optimal plan, the monthly fee, data volume, and details of additional services.

[1157] Finally, the device analyzes the data received from the server and displays it in an easy-to-read format for the user. This display is stylishly formatted using HTML and CSS. For example, information such as "Value Plan," "Monthly Fee: 3,000 yen," "Data Capacity: Unlimited," and "International Calls: Available" is displayed in list format. Using this information, users can select the communication plan that best suits them.

[1158] Through this system, users can easily find the communication plan that best suits their usage and desired conditions, while saving time and effort.

[1159] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1160] Step 1:

[1161] (User) enters information into a question form.

[1162] The user opens a browser on their device and accesses the inquiry form. The form has drop-down menus and radio buttons, and they input information in order, such as "Plan name: Plan A," "Call time: 100 minutes," "Data amount: 5GB," "Desired service: Unlimited data," and "Desired price range: 4,000 yen or less." The information entered by the user becomes the input data for the system.

[1163] Step 2:

[1164] (Device) collects input data and creates an HTTP POST request.

[1165] When the user clicks the "Submit" button, JavaScript is executed to combine the input data into a single data object. This data object contains all the information entered by the user. The device then sends this data object to the server as an HTTP POST request. It generates a JSON-formatted request body based on the input data, and the output is a request to the server.

[1166] Step 3:

[1167] (Server) receives the HTTP POST request and parses the data.

[1168] The server receives HTTP requests using a web framework such as Node.js or Python's Flask. It takes the received data and, if necessary, cleanses the input data (for example, by removing unnecessary whitespace or symbols) and normalizes it (for example, by standardizing the data format). In this process, the input data is parsed and converted into a format suitable for the AI ​​model. The output of the parsing process becomes the input data for the generative AI model.

[1169] Step 4:

[1170] (Server) analyzes the data using a generative AI model and calculates the optimal communication plan.

[1171] The server runs a generative AI model using AI frameworks such as TensorFlow and PyTorch. The analyzed data is input into the AI ​​model, which then calculates the optimal communication plan based on multiple factors (data volume, call duration, budget, etc.). The output of the generative AI model is detailed information about the optimal communication plan for the user (plan name, monthly fee, data volume, additional services, etc.).

[1172] Step 5:

[1173] (Server) sends details of the optimal communication plan to the device.

[1174] The server converts the detailed information obtained from the generative AI model into a data format such as JSON, and sends this to the device as an HTTP response. The output of the conversion process becomes the response data sent to the device.

[1175] Step 6:

[1176] (Device) receives the response from the server and displays it to the user.

[1177] The device uses JavaScript to analyze the data received from the server and reflects it in HTML. For example, information such as "Value Plan," "Monthly Fee: 3,000 yen," "Data Capacity: Unlimited," and "International Calls: Available" is displayed on the screen in list format. In this process, the response data is converted into a format that is easy for the user to understand and displayed on the screen. The output of the display process becomes the communication plan information presented to the user.

[1178] (Application example 1)

[1179] 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."

[1180] In recent years, the use of online shopping has increased dramatically, but many users spend a lot of time and effort trying to find the best purchase plan and discount information. To solve this problem, a system that automatically suggests the best purchase plan based on the user's shopping habits and desired conditions is needed. However, current systems do not effectively utilize the user's detailed shopping history or individual desired conditions, making it difficult to find the best plan.

[1181] 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.

[1182] In this invention, the server includes a means for prompting a user to input information about their current purchase plan, shopping habits, and desired conditions, a means for collecting the information input by the user and sending it to the server, a means for the server to analyze the information and calculate an optimal purchase plan using a generative artificial intelligence model, and a means for displaying details of the optimal purchase plan to the user, thereby enabling the user to easily find a purchase plan optimized to their shopping habits and desires, thereby saving time and effort.

[1183] A "user" is someone who uses this system to receive the optimal purchase plan.

[1184] "Purchase Plan" means a purchase option optimized for a User when purchasing an item online, including fees, discounts, subscription services, etc.

[1185] "Shopping habits" refers to the behavioral patterns of how a user typically purchases products, including purchase frequency and product category preferences.

[1186] "Desired conditions" are the specific requirements that a user has for a purchase plan, including price, type of product, and service content.

[1187] "Means for inputting information" refers to the interface that allows users to input information such as their current purchasing status and desired conditions into the system.

[1188] "Means for collecting information and transmitting it to the server" refers to the technical means by which the information entered by the user is compiled into a single data set and transmitted to the server.

[1189] "Means for analyzing the information on the server and calculating the optimal purchase plan using a generative AI model" refers to technology that enables a server to analyze information input by a user using a generative AI model and calculate the optimal purchase plan.

[1190] The "means for displaying the optimal purchase plan to the user" refers to an interface for visually presenting to the user the details of the optimal purchase plan calculated by the server.

[1191] "Generative AI model" refers to a machine learning algorithm used to analyze collected data and generate optimal suggestions for users.

[1192] To implement this invention, it is necessary to build a system that proposes optimal purchase plans based on the user's shopping habits and desired conditions. This system is mainly composed of a user terminal and a server.

[1193] First, the user terminal provides an interface that allows the user to input information about their current purchase plan, shopping habits, and desired conditions. This interface is realized by an application installed on a device such as a smartphone, smart glasses, a head-mounted display, or a personal robot.

[1194] Once the user has finished entering the information, the device collects this information as a single data set and sends it to the server. This communication must be secure and efficient, so for example, the HTTPS protocol is used.

[1195] The server uses a generative AI model to analyze the dataset received from the user. This generative AI model includes an algorithm that considers various factors (e.g., the user's shopping history, purchase frequency, desired conditions, etc.) to calculate the optimal purchase plan. Specifically, the server is built using the Node.js and Express.js frameworks and uses OpenAI's generative AI model.

[1196] For example, if a user provides the following information:

[1197] Current purchase plan: 10 items per month

[1198] Shopping habits: Often look for discounts in advance

[1199] Desired conditions: Monthly budget of 5,000 yen, purchase once a week

[1200] With this information, the server prompts the generative AI model with the following prompt:

[1201] Example prompt sentence:

[1202] Your current purchasing situation: 10 items purchased per month

[1203] Your shopping habits: I often look for discounts in advance

[1204] Your budget: Your monthly budget is 5,000 yen.

[1205] Your purchase frequency: Once a week

[1206] Please take the above into consideration and suggest the best purchase plan for you.

[1207] Based on these prompts, the generative AI model recommends the best purchasing plan for the user's needs, including the best subscription services, discount offers, and bulk buying options.

[1208] Finally, the information on the optimal purchase plan obtained from the server is sent to the user's device and visually displayed, allowing the user to easily find a purchase plan that is optimized for their shopping habits and preferences.

[1209] This system allows users to save time and effort while choosing the most suitable purchasing option.

[1210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1211] Step 1:

[1212] The user inputs information about their current purchase plan, shopping habits, and desired conditions into the terminal, including their current purchase plan (e.g., buying 10 items per month), shopping habits (e.g., often looking for discounts in advance), and desired conditions (e.g., monthly budget of 5,000 yen, purchase frequency once a week).

[1213] Step 2:

[1214] The device collects the information entered by the user as a single data set and sends it to the server. This data set includes all of the user's input information. For example, the input data is configured in JSON format and sent securely to the server using the HTTPS protocol.

[1215] Step 3:

[1216] The server receives the data set sent from the device and analyzes this information with the generative AI model. At this time, the received data is converted into a prompt sentence and sent to the generative AI model. For example, the following prompt sentence is generated:

[1217] Your current purchasing situation: 10 items purchased per month

[1218] Your shopping habits: I often look for discounts in advance

[1219] Your budget: Your monthly budget is 5,000 yen.

[1220] Your purchase frequency: Once a week

[1221] Please take the above into consideration and suggest the best purchase plan for you.

[1222] The server sends this prompt to OpenAI's generative AI model and receives the AI ​​model's response.

[1223] Step 4:

[1224] The generative AI model generates the optimal purchase plan based on prompts sent by the server. The model analyzes factors such as the user's shopping habits, budget, and purchase frequency to calculate the optimal purchasing options (e.g., subscription services or discount offers). The output is returned to the server as a text response.

[1225] Step 5:

[1226] The server extracts and organizes the details of the most suitable purchase plan based on the response received from the generative AI model, and performs additional processing (e.g., converting the response format or filtering the information) as needed. Finally, it generates a dataset to display to the user.

[1227] Step 6:

[1228] The server sends the generated optimal purchase plan dataset to the terminal, which includes details of the purchase plan (e.g., subscription service type, discount rate, fee, etc.).

[1229] Step 7:

[1230] The terminal displays the information on the optimal purchase plan received from the server to the user. The user can check the plan details visually displayed on the terminal screen and select the optimal purchase option. This allows the user to efficiently make purchases based on the purchase plan optimized for their needs.

[1231] 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.

[1232] This invention combines a system that utilizes a generative AI model to propose the optimal communication plan based on the user's smartphone usage status and desired conditions with an emotion engine that recognizes the user's emotions. This system is composed of a user, a terminal, a server, and an emotion engine, and is implemented in the following form.

[1233] First, the (terminal) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.). The (user) enters this information according to the question form displayed on the terminal.

[1234] (Device) collects the information entered by the user, compiles it into a single data set, and sends it to the server. (Server) receives the user data sent from the device and prepares it for analysis.

[1235] The server inputs the received user data into a generative AI model and runs the model to calculate the optimal communication plan. This generative AI model includes an algorithm that analyzes multiple factors, such as the user's data volume, call duration, and rate band, to derive the optimal plan.

[1236] Furthermore, the present invention adds an emotion engine. The emotion engine analyzes the user's emotional state based on the user's input data and interactions. The analysis results are used to optimize communication plans using a generative AI model. For example, if the user is under stress, the emotion engine provides that information to the server, which can then make suggestions to help the user relax.

[1237] The server sends the optimal plan calculated based on information obtained from the generative AI model and emotion engine to the device. This optimal plan information includes the plan name, monthly fee, data capacity, additional service details, etc. The device displays the optimal plan information received from the server to the user.

[1238] Specific examples

[1239] A user is currently using "Plan A," which includes 100 minutes of calls and 5GB of data per month. The user wants an unlimited data plan and is looking for a plan with a monthly fee of less than 4,000 yen.

[1240] First, (Device) collects the following information from the User:

[1241] Current communication plan: Plan A

[1242] Call usage: 100 minutes per month

[1243] Data usage: 5GB per month

[1244] Desired service: Unlimited data plan

[1245] Desired price range: Up to 4,000 yen per month

[1246] This information is sent to a server, which then analyzes the data using a generative AI model. For example, the model considers the user's data volume, call duration, and budget to calculate the optimal plan, such as a "value plan" that includes unlimited data and international calls for 3,000 yen per month.

[1247] Meanwhile, the Emotion Engine analyzes the data entered by the user and their reactions during operation to detect when the user is in a low-stress state. This information is also taken into account in the analysis results of the generative AI model to select a plan that best suits the user.

[1248] (Server) sends this "Special Offer" information to (Device), and the Device displays the following to the user:

[1249] Best plan: Value plan

[1250] Monthly fee: 3,000 yen

[1251] Data capacity: Unlimited

[1252] International calls: Yes

[1253] The user checks the information on the optimal plan displayed on the device and selects the plan that best suits them. Through this system, users can save time and effort while selecting the optimal plan that takes into account their emotional state.

[1254] The processing flow will be explained below.

[1255] Step 1:

[1256] (Device) displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required service content, etc.).

[1257] Step 2:

[1258] The user follows the question form displayed on the terminal to input information about the current communication plan, call usage, data usage, desired service content, and desired rate range.

[1259] Step 3:

[1260] (Terminal) collects the information entered by the user, compiles it into a single data set, and sends it to the server.

[1261] Step 4:

[1262] (Server) receives the user's dataset sent from the device and prepares it for analysis.

[1263] Step 5:

[1264] The Emotion Engine analyzes the user's emotional state based on the user's input data and interactions. The analysis results are used to determine the user's emotional state in the current usage situation.

[1265] Step 6:

[1266] The server inputs the received user data into the generative AI model, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes multiple factors, such as the user's data volume, call duration, and rate band.

[1267] Step 7:

[1268] The server compares the optimal plan calculated based on the generative AI model with the emotion analysis results from the emotion engine, and further adjusts the plan according to the user's emotional state.

[1269] Step 8:

[1270] The server sends the generated optimal plan information to the terminal. This plan information includes the plan name, monthly fee, data capacity, additional services, etc.

[1271] Step 9:

[1272] The device receives the optimal plan from the server and displays it to the user. The displayed information takes into account the user's emotional state, allowing the user to make a more relaxed selection.

[1273] Step 10:

[1274] The user checks the information about the optimal plan displayed on the device and selects the plan that best suits their usage situation and desired conditions.

[1275] Example 2

[1276] 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."

[1277] While conventional communication plan proposal systems have methods for proposing optimal plans based on the user's usage status and desired conditions, they do not take into account the user's emotional state. As a result, they may propose plans that users find stressful or difficult to use, and they are unable to fully improve user satisfaction. In addition, many systems provide users with a large amount of information, which makes selection time-consuming and inefficient.

[1278] 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.

[1279] In this invention, the server includes: means for prompting a user to input information regarding their current communication plan, their voice and data communication usage status, and their desired conditions; means for collecting the information input by the user and sending it to the server; means for the server to analyze the information and calculate an optimal communication plan using a generative artificial intelligence model; means for displaying the calculated optimal communication plan to the user; emotion engine means for analyzing the emotional state of the user based on input data and interaction data; and means for optimizing the communication plan based on the analysis results of the emotion engine. This makes it possible to propose an optimal communication plan that takes into account not only the user's usage status and desired conditions, but also their emotional state, thereby improving user satisfaction.

[1280] "User" refers to any individual or entity that uses the System to optimize their communication plans.

[1281] "Terminal" refers to an electronic device used by a user to input information. Examples include smartphones and personal computers.

[1282] "Server" refers to a central processing unit that receives and analyzes information sent by users.

[1283] "Information" refers to data entered by the user, such as communication plans, voice and data usage, and desired conditions.

[1284] A "generative artificial intelligence model" refers to a model that uses machine learning algorithms to calculate the optimal communication plan from user data.

[1285] "Optimal communication plan" refers to the most suitable plan calculated based on the user's data usage, call time, fees, etc.

[1286] "Displaying means" refers to a method or device for presenting the calculated optimal communication plan to the user.

[1287] An "emotion engine" refers to software that analyzes user input and interaction data to assess the user's emotional state.

[1288] "Interaction data" refers to data about the actions and responses users take on the system.

[1289] "Optimization" refers to the process of calculating the outcome that best meets specific goals or conditions.

[1290] The present invention is a system for optimizing a user's communication plan, proposing the optimal communication plan based on the user's usage status, desired conditions, and emotional state. This system is composed of a user, a terminal, a server, and an emotion engine, and is implemented as follows.

[1291] First, the device displays a question form to the user, prompting them to enter their current communication plan, voice and data usage, and desired conditions (fees, required services, etc.). This question form is created using HTML and JavaScript. Specifically, it provides a user-friendly UI that allows users to easily enter information.

[1292] The user enters this information in the question form displayed on the device. For example, the user enters "Plan A" as their current communication plan, 100 minutes / month as their call usage, 5GB / month as their data usage, an unlimited data plan as their desired service, and a monthly fee of up to 4,000 yen.

[1293] The device collects the information entered by the user and compiles it into a single dataset. This dataset is sent to the server in a format such as JSON. For example, JavaScript can be used to convert the data into JSON and send it to an API endpoint using an HTTP POST request.

[1294] The server receives user data sent from the device and prepares it for analysis. At this stage, data is validated and normalized, and data is reshaped and missing values ​​are imputed using Python and data processing libraries (e.g., Pandas).

[1295] The server then inputs the preprocessed data into a generative AI model such as TensorFlow or PyTorch, which then runs the model to calculate the optimal communication plan. The generative AI model analyzes the user's call duration, data usage, tariff band, etc.

[1296] Furthermore, the present invention uses an emotion engine. The emotion engine analyzes the user's input data and reactions during operation (e.g., input speed and contextual data) to evaluate the user's emotional state. Machine learning technology is used for this emotion analysis. The analysis results are fed back to the generative AI model, which then optimizes the communication plan taking the user's emotional state into account.

[1297] The server determines the optimal communication plan based on the information obtained from the generative AI model and emotion engine, and sends the final result to the device. The information sent includes the plan name, monthly fee, data capacity, and additional service details.

[1298] The device displays the information about the best plan received from the server to the user. For example, it uses HTML and JavaScript to display "Best plan: Value plan, Monthly fee: 3000 yen, Data capacity: Unlimited, International calls: Available."

[1299] Prompt Sentence Examples

[1300] For example, if a user enters the following information:

[1301] Current communication plan: Plan A

[1302] Call usage: 100 minutes per month

[1303] Data usage: 5GB per month

[1304] Desired service: Unlimited data plan

[1305] Desired price range: Up to 4,000 yen per month

[1306] This information is sent to a server, which uses a generative AI model to analyze the data and calculate the communication plan that best suits the user's requirements.

[1307] This not only enables users to quickly and easily find the best communication plan for them, but also allows them to receive more personalized suggestions that take their emotional state into account through an emotion engine.

[1308] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1309] Step 1:

[1310] The user enters information about their current communication plan, voice and data usage, and desired terms.

[1311] Input: Data entered by the user into the question form (e.g., current communication plan "Plan A," call usage of 100 minutes / month, data usage of 5GB / month, desired fee of 4,000 yen or less, etc.).

[1312] In concrete terms, the user enters answers into a form written in HTML and JavaScript.

[1313] Step 2:

[1314] The device collects the information the user enters and compiles it into a single data set.

[1315] Input: Data entered by the user.

[1316] Output: The dataset in JSON format.

[1317] Specifically, the device converts the data entered by the user into JSON format using JavaScript and sends it to the server using an HTTP POST request.

[1318] Step 3:

[1319] The server receives the user data sent from the device and prepares it for analysis.

[1320] Input: A dataset in JSON format received from the terminal.

[1321] Output: A normalized dataset.

[1322] Specifically, data processing libraries such as Python and Pandas are used to normalize data and fill in missing values.

[1323] Step 4:

[1324] The server inputs the preprocessed data into a generative AI model to calculate the optimal communication plan.

[1325] Input: The normalized dataset.

[1326] Output: Proposal of optimal communication plan.

[1327] Specifically, it uses TensorFlow and PyTorch to input data into a model and perform inference. The generative AI model takes into account factors such as the user's call duration, data usage, and price band.

[1328] Step 5:

[1329] The emotion engine analyzes the user's emotional state based on input data and interaction data.

[1330] Input: User input data and response data during operation.

[1331] Output: User's emotional state rating data.

[1332] Specifically, it uses machine learning models to analyze the user's typing speed and context to assess their emotional state.

[1333] Step 6:

[1334] The server integrates the results obtained from the generative AI model with the analysis results of the emotion engine and reevaluates the optimal communication plan.

[1335] Input: Inference results of the generative AI model, evaluation data of the emotion engine.

[1336] Output: The final optimal communication plan.

[1337] Specifically, the results of the generative AI model are added to the analysis results of the emotion engine, and the data is reprocessed to make optimal suggestions.

[1338] Step 7:

[1339] The server sends information about the optimal communication plan to the terminal.

[1340] Input: The final optimal communication plan.

[1341] Output: Plan information sent to the device.

[1342] Specifically, optimal plan information in JSON format is sent as an HTTP response.

[1343] Step 8:

[1344] The terminal displays the information on the optimum plan received from the server to the user.

[1345] Input: Information of the best plan received from the server.

[1346] Output: Details of the best plan displayed to the user.

[1347] Specifically, HTML and JavaScript are used to display the optimal plan to the user (e.g., "Optimal plan: Value plan, Monthly fee: 3,000 yen, Data capacity: Unlimited, International calls: Available").

[1348] The above are the specific processing steps of the program of this system.

[1349] (Application example 2)

[1350] 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."

[1351] Today's wide variety of electronic payment services makes it difficult for users to choose the plan that best suits them. As a result, users often cannot enjoy the most advantageous rewards and benefits, and they often feel stressed. Furthermore, there is no system that can propose the optimal plan taking into account the user's emotional state, making it impossible to provide an optimal experience for each individual user. There is a need to solve these problems.

[1352] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1353] In this invention, the server includes: means for prompting a user to input information about their current electronic payment service, monthly expenditures and frequency of use, and desired benefits; means for collecting the information input by the user and sending it to the server; means for the server to analyze the information and calculate an optimal electronic payment plan using a generative AI model; means for analyzing the user's emotional state using an emotion engine and taking this into consideration when calculating the optimal plan; and means for displaying the calculated optimal electronic payment plan to the user. This provides an optimal electronic payment plan that takes into account the user's usage status and emotional state, allowing the user to make the most of their benefits and select the optimal plan without feeling stressed.

[1354] "User" refers to an individual or corporation that uses the system to select and use an electronic payment service plan.

[1355] "Electronic payment services" refer to services that enable online payments and transactions using the Internet or mobile devices.

[1356] "Monthly expenditure" refers to the total amount paid by a user using electronic payment services each month.

[1357] "Frequency of use" refers to the number of times or frequency with which a user uses an electronic payment service within a certain period of time.

[1358] "Desired benefits" are the added value of electronic payment services that users desire, including points rewards, no fees, and affiliated service benefits.

[1359] "Means for inputting information" refers to the user interface functions that allow the user to input the necessary information into the system.

[1360] "Means for collecting information and transmitting it to a server" refers to the function of collecting information entered by the user and transmitting it to a server via a communication network.

[1361] "Means for calculating optimal electronic payment plans using generative AI models" refers to algorithms that analyze and propose optimal plans based on user information collected using artificial intelligence technology.

[1362] An "emotion engine" refers to software or a system that analyzes a user's emotional state from their input data and reactions during operation.

[1363] "Means to consider when analyzing emotional state and calculating the optimal plan" refers to the function of reflecting emotional state information obtained from the emotion engine in the generative AI model and proposing the optimal plan to the user.

[1364] The "optimal electronic payment plan" refers to an electronic payment service plan that provides the greatest benefits by comprehensively considering the user's usage situation, desired conditions, and emotional state.

[1365] "Means for displaying the plan to the user" refers to a display or screen display function for visually presenting information about the calculated optimal plan to the user.

[1366] This invention describes a system that allows users to select the optimal electronic payment service. This system proposes the optimal electronic payment plan to the user by calculating the optimal plan using a generative AI model based on input user information and by analyzing and considering the user's emotional state using an emotion engine.

[1367] 1. System program for implementing this application example

[1368] A specific example of this system will be described below.

[1369] 1.1 Hardware and Software Used

[1370] Smartphone: Used by users to enter their information and view the best plan for them (e.g., iOS or Android device).

[1371] Server: Performs data analysis and processing of generative AI models and emotion engines (e.g., cloud-based servers).

[1372] software:

[1373] Mobile App: User frontend developed using React Native.

[1374] Server-side application: Built using Node.js.

[1375] Data Analysis: Python and its libraries (Pandas, Scikit-Learn).

[1376] Generative AI model: OpenAI's GPT-4.

[1377] Emotion engine: Emotion AI API.

[1378] 2. Explain the generated program's processing in natural language

[1379] The server specifically implements the present invention using the following means.

[1380] 2.1 User Information Collection

[1381] First, users enter their current electronic payment services, monthly spending and frequency of use, and desired rewards through a smartphone app. This information is collected via the user interface.

[1382] 2.2 Data Transmission

[1383] The app compiles the collected data into a single dataset and sends it to a server via HTTPS.

[1384] 2.3 Data analysis

[1385] The server inputs the received data into a generative AI model (e.g., OpenAI's GPT-4) to calculate the optimal electronic payment plan based on the user's spending patterns and desired conditions.

[1386] 2.4 Emotional State Analysis

[1387] The emotion engine analyzes the user's emotional state based on their input data and reactions during operation. The obtained emotional information is reflected in the analysis results of the generative AI model.

[1388] 2.5 Proposing the optimal plan

[1389] Based on the analysis results of the generative AI model and emotion engine, the server calculates an optimal plan, which is then displayed to the user via a smartphone app.

[1390] 3. Add examples to your description

[1391] Let's say a user currently uses "Service A" as their electronic payment service, and has entered that their monthly spending is 30,000 yen and that they use the service frequently. Furthermore, this user wishes to receive points back.

[1392] Prompt Sentence Examples

[1393] 1. Example prompts for collecting user information:

[1394] Please select the electronic payment service you are currently using.

[1395] Enter your monthly spending and frequency of use.

[1396] Please select the benefits you would like (e.g. points reward, no fees, partner service benefits).

[1397] 2. Example prompts to be input to the generative AI model when proposing the optimal plan:

[1398] The data provided by the user is as follows:

[1399] Current service: Service A

[1400] Monthly expenses: 30,000 yen

[1401] Frequency of use: High

[1402] Desired reward: Points redemption

[1403] Suggest the best e-payment plan for this user. Emotional state is low stress.

[1404] This allows users to easily find the most advantageous electronic payment plan for themselves and enjoy a comfortable service that takes their emotional state into consideration.

[1405] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1406] Step 1:

[1407] The terminal displays a form for the user to enter information about their electronic payment service usage (current services used, monthly expenditures, frequency of use, and desired benefits).

[1408] Input: Information about the user's electronic payment service

[1409] Output: User's input dataset

[1410] Step 2:

[1411] The device collects the information entered by the user and sends it to the server via HTTPS.

[1412] Input: User input dataset

[1413] Output: The dataset sent to the server

[1414] Step 3:

[1415] The server receives the received dataset and prepares it for input to the generative AI model by formatting the data and converting it into a format that the AI ​​model can understand.

[1416] Input: Dataset received by the server

[1417] Output: A formatted dataset

[1418] Step 4:

[1419] The server then inputs the formatted data set into a generative AI model (e.g., OpenAI GPT-4) to calculate the optimal electronic payment plan. The generative AI model performs data analysis and inference based on the user's spending patterns and preferences.

[1420] Input: Formatted dataset

[1421] Output: Proposal of optimal electronic payment plan

[1422] Step 5:

[1423] The server uses an emotion engine to analyze the user's emotional state, such as assessing stress levels and satisfaction levels based on input data and reactions during operation. This information is also added to the analysis results.

[1424] Input: Formatted dataset and user interaction data

[1425] Output: User's emotional state information

[1426] Step 6:

[1427] The server combines information obtained from the generative AI model and the emotion engine to determine the final optimal plan, taking into account the user's emotional state to select a plan that is most comfortable to use.

[1428] Input: Optimal e-payment plan recommendations and emotional state information

[1429] Output: The final optimal plan

[1430] Step 7:

[1431] The server then sends the final selected optimal plan to the device, again via HTTPS.

[1432] Input: The final optimal plan

[1433] Output: Plan data sent to device

[1434] Step 8:

[1435] The device will then display the received information about the optimal plan to the user, visually providing information such as the plan name, monthly cost, benefits, and details of affiliated services.

[1436] Input: Received plan data

[1437] Output: Information about the best plan displayed to the user

[1438] 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.

[1439] 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.

[1440] 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.

[1441] 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.

[1442] 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.

[1443] 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.

[1444] 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).

[1445] 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.

[1446] 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."

[1447] 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.

[1448] 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).

[1449] 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.

[1450] 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.

[1451] 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.

[1452] 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.

[1453] 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.

[1454] 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.

[1455] 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.

[1456] 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.

[1457] 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.

[1458] 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.

[1459] The following is further disclosed regarding the above embodiment.

[1460] (Claim 1)

[1461] a means for allowing a user to input information about their current communication plan, voice and data usage, and desired terms;

[1462] means for collecting information input by the user and transmitting the information to a server;

[1463] A means for analyzing the information in a server and calculating an optimal communication plan using a generative artificial intelligence model;

[1464] means for displaying the calculated optimum communication plan to a user;

[1465] A system including:

[1466] (Claim 2)

[1467] 10. The system of claim 1,

[1468] The system has a means for the desired conditions input by the user to include fees and required service contents.

[1469] (Claim 3)

[1470] 10. The system of claim 1,

[1471] The generative artificial intelligence model is a system that has a means for calculating the optimal communication plan based on multiple factors such as the user's data communication volume, call time, and fees.

[1472] "Example 1"

[1473] (Claim 1)

[1474] a means for allowing a user to input information about their current communication plan, voice and data usage, and desired terms;

[1475] means for collecting information input by the user and transmitting the information to a server;

[1476] A means for analyzing the information in a server and calculating an optimal communication plan using a generative artificial intelligence model;

[1477] means for displaying the calculated optimum communication plan to a user;

[1478] A system including:

[1479] (Claim 2)

[1480] 2. The system according to claim 1, further comprising a means for inputting desired conditions by the user, the desired conditions including a fee and required service contents.

[1481] (Claim 3)

[1482] The system of claim 1, wherein the generative artificial intelligence model has a means for calculating an optimal communication plan based on multiple factors such as the user's data traffic, call duration, and fees.

[1483] "Application Example 1"

[1484] (Claim 1)

[1485] means for allowing a user to enter information about their current purchasing plan, shopping habits, and desired terms;

[1486] means for collecting information input by the user and transmitting the information to a server;

[1487] A means for analyzing the information in a server and calculating an optimal purchase plan using a generative artificial intelligence model;

[1488] means for displaying the calculated optimal purchase plan to a user;

[1489] A system including:

[1490] (Claim 2)

[1491] 2. The system according to claim 1, further comprising a means for including a fee and required service content in the desired conditions input by the user.

[1492] (Claim 3)

[1493] The system of claim 1, wherein the generative artificial intelligence model has a means for calculating an optimal purchase plan based on multiple factors such as a user's purchase history, shopping habits, and prices.

[1494] "Example 2: Combining Emotion Engines"

[1495] (Claim 1)

[1496] a means for allowing a user to input information about their current communication plan, voice and data usage, and desired terms;

[1497] means for collecting information input by the user and transmitting the information to a server;

[1498] A means for analyzing the information in a server and calculating an optimal communication plan using a generative artificial intelligence model;

[1499] means for displaying the calculated optimum communication plan to a user;

[1500] an emotion engine means for analyzing an emotional state based on user input data and interaction data;

[1501] means for optimizing a communication plan based on the analysis result of the emotion engine;

[1502] A system including:

[1503] (Claim 2)

[1504] 2. The system according to claim 1, further comprising a means for inputting desired conditions by the user, the desired conditions including a fee and required service contents.

[1505] (Claim 3)

[1506] The system of claim 1, wherein the generative artificial intelligence model has a means for calculating an optimal communication plan based on multiple factors such as the user's data traffic, call duration, and fees.

[1507] "Application example 2 when combining emotion engines"

[1508] (Claim 1)

[1509] means for allowing a user to input information regarding their current electronic payment service, monthly expenditures and frequency of use, and desired rewards;

[1510] means for collecting information input by the user and transmitting the information to a server;

[1511] A means for analyzing the information on a server and calculating an optimal electronic payment plan using a generative AI model;

[1512] Using an emotion engine to analyze the user's emotional state and take it into account when calculating the optimal plan;

[1513] means for displaying the calculated optimal electronic payment plan to a user;

[1514] A system including:

[1515] (Claim 2)

[1516] 2. The system according to claim 1, wherein the desired benefits input by the user include point redemption, no handling fee, and affiliated service benefits.

[1517] (Claim 3)

[1518] The system of claim 1, wherein the generative AI model calculates an optimal electronic payment plan based on multiple factors, such as a user's spending patterns, frequency of use, and budget. [Explanation of symbols]

[1519] 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 allowing a user to input information about their current communication plan, voice and data usage, and desired terms; means for collecting information input by the user and transmitting the information to a server; A means for analyzing the information in a server and calculating an optimal communication plan using a generative artificial intelligence model; means for displaying the calculated optimum communication plan to a user; A system including:

2. 10. The system of claim 1, The system has a means for the desired conditions input by the user to include fees and required service contents.

3. 10. The system of claim 1, The generative artificial intelligence model is a system that has a means for calculating the optimal communication plan based on multiple factors such as the user's data communication volume, call time, and fees.

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