system

Abstract

Provide a system. [Solution] a means for receiving income, expenses, number of dependents, and deductions data from a user; means for calculating taxable income and tax amount based on said data; means for displaying the tax amount calculated by the calculation means; A means for proposing tax saving methods based on the data; and a means for generating reminders of important procedures.

Description

[Technical Field]

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

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

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

[0004] In modern society, calculating taxes and choosing appropriate tax-saving methods are extremely complicated, causing many individuals to find them difficult. Calculating accurate tax amounts based on data such as income, expenses, number of dependents, and deductions, as well as proposing appropriate tax-saving strategies, require specialized knowledge, placing a significant burden on the average individual. Meeting deadlines for tax procedures is also important, but insufficient reminders could result in penalties. To solve these problems, a system is needed that automatically calculates taxes, suggests appropriate tax-saving methods, and provides reminders of important tax procedures that require attention. [Means for solving the problem]

[0005] The present invention provides a system including means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, and means for generating reminders for important procedures. Furthermore, by adding means for transmitting the data on income, expenses, number of dependents, and deductions in JSON format and means for the suggested tax-saving methods to include deductions for dependents and medical expenses, it is possible to realize user-friendly, accurate, and effective tax management.

[0006] A "user" is a person who utilizes the system to enter and submit data such as income, expenses, number of dependents, and deductions.

[0007] "Income" refers to the total amount of income earned by a user during a particular period, including salary, bonuses, investment income, etc.

[0008] "Expenses" refers to the total amount used or consumed by a User during a specific period, including living expenses, education expenses, medical expenses, etc.

[0009] "Number of dependents" refers to the number of family members and relatives supported by the user, and is the number of people who qualify as dependents under tax law.

[0010] "Deduction amount" refers to the amount that can be deducted under tax law, such as the amount that can be deducted from income through medical expenses deductions and donation deductions.

[0011] "Taxable income" refers to income remaining after expenses and deductions have been deducted from income, and is the amount on which tax is calculated by applying the tax rate.

[0012] "Tax amount" refers to the total amount of tax calculated by applying the tax rate to taxable income.

[0013] "Tax saving methods" refer to various means and methods that users can use to reduce their tax burden, including, for example, dependent deductions and medical expense deductions.

[0014] "Recommendations" refers to the optimal tax saving methods and other advice provided by the System to the User.

[0015] "Reminder" refers to a system function that notifies users of deadlines and deadlines for important tax procedures, and is a notification that helps users meet deadlines. [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 illustrating 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] The present invention is a system that receives data on income, expenses, number of dependents, and deductions from a user, automatically calculates tax amounts, suggests appropriate tax-saving methods, and also reminds users of important tax procedures.

[0038] System Configuration

[0039] This system is mainly composed of a server, a terminal, and a user. Specifically, the system operates as follows:

[0040] Entering and submitting user data

[0041] The user enters their income, expenses, number of dependents, and deductions into an input form on the device. The entered data is sent to the server in JSON format.

[0042] Receiving and storing user data

[0043] The server receives the user data sent from the terminal, parses the received data, and stores it in the server's database as a UserData object.

[0044] Tax calculation

[0045] The server calculates taxable income based on the saved user data. Taxable income is the amount obtained by subtracting expenses and deductions from income. Then, it applies a hypothetical tax rate to this taxable income to calculate the tax amount.

[0046] Displaying calculation results

[0047] The server sends the calculated tax amount to the terminal, and the terminal displays the calculation result to the user. For example, a specific tax amount such as "The user's tax amount is XX yen" is displayed.

[0048] Tax saving suggestions

[0049] The server proposes appropriate tax-saving methods based on user data. Specifically, if the user has one or more dependents, the server suggests "take advantage of the dependent deduction," and if the medical expense deduction is not yet sufficient, the server suggests "consider taking the medical expense deduction." This proposal is sent to the terminal in JSON format, and the terminal displays it to the user.

[0050] Procedural Reminders

[0051] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date. For example, a reminder such as "X days left until year-end tax adjustments" is generated. This reminder information is also sent to the device in JSON format, and the device displays it to the user.

[0052] Specific examples

[0053] For example, if a user inputs "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0054] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0055] Tax amount = 3.3 million yen 20% = 660,000 yen

[0056] Next, you'll see suggestions like "Please claim your dependent deductions" and reminders like "30 days left until your tax return."

[0057] As described above, the present invention allows users to easily and accurately calculate tax amounts, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures, thereby reducing the burden of tax processing and preventing penalties and fines.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] The user enters their income, expenses, number of dependents, and deductions into the input form on the terminal. The entered data is sent to the server by clicking the send button.

[0061] Step 2:

[0062] The device sends the entered user data in JSON format to the server, including income, expenses, number of dependents, and deductions.

[0063] Step 3:

[0064] The server receives the JSON formatted user data sent from the device and parses it as a UserData object. The parsed data is stored in the database.

[0065] Step 4:

[0066] The server retrieves the stored user data from the database and calculates taxable income based on income, expenses, and deductions. Specifically, taxable income is the amount obtained by subtracting expenses and deductions from income.

[0067] Step 5:

[0068] The server calculates the tax amount by applying a hypothetical tax rate to the calculated taxable income. For example, if the tax rate is assumed to be 20%, the tax amount is calculated by multiplying the taxable income by 0.2.

[0069] Step 6:

[0070] The server sends the calculated tax amount in JSON format to the terminal. The sent data includes the user name and tax amount.

[0071] Step 7:

[0072] The terminal displays the tax amount received from the server to the user. For example, a specific amount such as "The user's tax amount is XX yen" is displayed.

[0073] Step 8:

[0074] The server will suggest tax-saving methods based on user data. For example, if the user has one or more dependents, it will suggest "take advantage of the dependent deduction," and if the medical expense deduction is not applied, it will suggest "consider taking the medical expense deduction."

[0075] Step 9:

[0076] The server sends the proposed tax saving methods in JSON format to the terminal. The sent data includes the proposed methods.

[0077] Step 10:

[0078] The terminal displays the tax saving suggestions received from the server to the user. For example, "Please accept the dependent deduction" or "Please consider the medical expense deduction" may be displayed.

[0079] Step 11:

[0080] The server obtains the current date and calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments. For example, it generates reminders such as "X days left until year-end tax adjustments."

[0081] Step 12:

[0082] The server sends the generated reminder information in JSON format to the device. The sent data includes the reminder content.

[0083] Step 13:

[0084] The device displays the reminder information received from the server to the user. For example, it displays the specific number of days until the end of the year tax adjustment.

[0085] Example 1

[0086] 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."

[0087] Traditional tax processing is complex, requiring a great deal of effort and expertise to accurately calculate tax amounts and individually recommend appropriate tax-saving methods. There is also a risk of forgetting deadlines for important tax procedures. To address these issues, users need a method that allows them to easily and accurately calculate tax amounts, receive appropriate tax-saving suggestions, and remember to complete important tax procedures.

[0088] 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.

[0089] In this invention, the server includes means for receiving information on income, expenses, number of dependents, and deductions from a user, means for transmitting the information in JSON format, means for receiving and storing the information in JSON format, means for calculating taxable income and tax amount based on the information, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the information, means for generating reminders of important procedures, and means for displaying the reminders to the user, thereby enabling the user to easily and accurately calculate tax amount, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures.

[0090] "User" means an individual or corporation that uses the system to enter tax information and receives tax calculations, tax saving suggestions, and tax procedure reminders.

[0091] "Income" refers to the total amount of income earned by a user in a year, and is the amount used as the basis for calculating taxable income.

[0092] "Expenses" refers to necessary expenses and consumption expenditures incurred by the user during the year, and are amounts that can be deducted from taxable income.

[0093] "Number of dependents" refers to the number of spouses, children, and other dependents of the user who qualify for tax deductions.

[0094] "Deductions" are certain legally recognized costs and expenses that can be deducted from income when calculating taxable income.

[0095] "JSON format" is a lightweight data exchange format for structuring and transmitting data, and is an abbreviation for JavaScript (registered trademark) Object Notation.

[0096] "Server" is a central computer system that receives, stores, and processes data sent by users and sends calculation results, suggestions, and reminder information to users.

[0097] "Taxable income" is the amount remaining after deducting expenses and deductions from the user's income, and is the amount used to calculate tax.

[0098] "Tax amount" is the amount of tax paid calculated based on taxable income.

[0099] "Tax saving methods" are means or methods for users to legally reduce their tax burden, and include dependent deductions and medical expense deductions.

[0100] "Reminders" are messages or alerts that notify users of important tax procedures or deadlines.

[0101] "Display means" refers to a method for visually presenting calculation results, tax saving suggestions, reminder information, etc. to the user, and includes web pages and application screens.

[0102] This invention is a system that automatically calculates tax amounts, suggests appropriate tax-saving methods, and reminds users of important tax procedures by allowing them to input information on income, expenses, number of dependents, and deductions. This system is composed of multiple elements, including a server, a terminal, and a user.

[0103] System Configuration

[0104] 1. Entering and submitting user data

[0105] Users open a web form on their device and enter their income, expenses, number of dependents, and deductions.

[0106] The device converts the input data into JSON format and sends a POST request to the server, using a standard web browser and HTTP request.

[0107] 2. Receiving and storing user data

[0108] The server receives JSON data from the device using the Python Flask framework, and parses it using the request.get_json() method.

[0109] The parsed data is then converted into a UserData object and stored in a MySQL database using SQLAlchemy.

[0110] 3. Tax calculation

[0111] The server calculates taxable income and tax amount based on the saved user data. Taxable income is the amount obtained by subtracting expenses and deductions from the user's income. The server also calculates the tax amount by applying a hypothetical tax rate.

[0112] 4. Displaying the calculation results

[0113] The server sends the calculated tax amount to the terminal in JSON format. To do this, the jsonify function is used to construct the response.

[0114] The terminal parses the response data and displays the calculation result to the user, for example, "Your tax amount is 660,000 yen."

[0115] 5. Tax saving suggestions

[0116] The server proposes appropriate tax-saving methods based on user data, taking into account the number of dependents and deduction amounts, and determines which methods are effective.

[0117] The server sends the proposal in JSON format to the device, which then displays it to the user. For example, the proposal might be "Please accept dependent deductions" or "Please consider medical expense deductions."

[0118] 6. Procedural Reminders

[0119] The server calculates deadlines for important tax procedures based on the current date and generates reminders, such as "30 days left until tax return."

[0120] This reminder is also sent in JSON format to the device, which then displays the reminder to the user.

[0121] Specific examples

[0122] For example, if a user enters the following data: Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen, the server will perform the following calculations:

[0123] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0124] Tax amount = 3.3 million yen 20% = 660,000 yen

[0125] Next, you'll see suggestions like "Please claim your dependent deductions" and reminders like "30 days left until your tax return."

[0126] Example prompts for generative AI models

[0127] "Calculate your tax amount based on the following information and suggest ways to save on tax: Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen."

[0128] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0129] Step 1: Enter and submit user data

[0130] The user opens a web form on their device and enters their income, expenses, number of dependents, and deductions. For example, the user enters "Income: 5 million yen," "Expenses: 1.5 million yen," "Number of dependents: 1," and "Deductions: 200,000 yen."

[0131] The terminal converts the input data into JSON format, specifically generating the following JSON object: {"income": 5000000, "expenses": 1500000, "dependents": 1, "deductions": 200000}.

[0132] The terminal sends this to the server as a POST request. The input data is collected on a web form and sent to the server by clicking the submit button.

[0133] Step 2: Receiving and storing user data

[0134] The server uses the Flask framework to receive the JSON data sent from the device. Specifically, it parses the received data using the request.get_json() method.

[0135] The server converts the parsed data into a UserData object, which is instantiated by creating an instance of the UserData class.

[0136] The server saves this object to the MySQL database via SQLAlchemy by executing the db_session.add(user_data) and db_session.commit() methods, which receives the input data, converts it into an object, and saves it to the database.

[0137] Step 3: Calculate taxes

[0138] The server retrieves the stored user data from the database using user_data = db_session.query(UserData).where(UserData.id == user_id).first().

[0139] The server calculates taxable income by subtracting expenses and deductions from the user's income. The specific calculation is taxable_income = user_data.income - user_data.expenses - user_data.deductions.

[0140] The server calculates the tax amount by applying a hypothetical tax rate. For example, this tax rate is set to 20%, and the calculation is tax_amount = taxable_income 0.20. The server calculates taxable income based on the input data and then calculates the tax amount from the result.

[0141] Step 4: Displaying the calculation results

[0142] The server sends the calculated tax amount in JSON format to the terminal. Specifically, it generates response = {"tax_amount": tax_amount} and returns it with return jsonify(response).

[0143] The terminal receives this response data and displays the calculation result to the user. For example, it displays "Your tax amount is 660,000 yen." The calculation result is received in JSON format and is presented visually to the user.

[0144] Step 5: Proposal for tax saving methods

[0145] The server recommends appropriate tax-saving methods based on user data. Specifically, it executes logic such as if user_data.dependents > 0: recommendations.append("Please take dependent deductions")

[0146] The server sends the recommendations in JSON format to the device. Specifically, it generates response = {"recommendations": recommendations} and returns it with return jsonify(response).

[0147] The device will then display the suggestions to the user. For example, it might say, "Accept dependent deductions" or "Consider medical expense deductions." It will then identify tax-saving methods based on user data and notify the user.

[0148] Step 6: Procedural Reminders

[0149] The server calculates deadlines for important tax procedures based on the current date: days_until_deadline = (deadline_date - datetime.now()).days.

[0150] The server generates reminders based on the calculation results and sends them to the device in JSON format. Specifically, it generates response = {"reminders": reminders} and returns it with return jsonify(response).

[0151] The device will display the sent reminder to the user, for example, "30 days left until tax return." By generating and notifying reminders, the device helps users remember important deadlines.

[0152] The above is a description of the specific operation of this system divided into processing steps.

[0153] (Application example 1)

[0154] 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."

[0155] It is time-consuming for users to calculate tax amounts based on their own income and expenditure data and find appropriate tax-saving methods. There is also a risk that they may forget important tax procedures. Conventional systems lack sufficient integration with electronic payment services, making it cumbersome to collect income and expenditure data and calculate tax amounts.

[0156] 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.

[0157] In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, means for generating reminders for important procedures, means for linking with an electronic payment service, and means for automatically importing income and expenditure data and periodically notifying the user of tax amount and tax-saving methods. This allows users to easily check their tax amount, find optimal tax-saving methods, and avoid forgetting deadlines for important tax procedures while using the electronic payment service.

[0158] "Means for receiving data on income, expenses, number of dependents, and deductions from users" refers to a function that allows users to input financial data such as their income, expenses, number of dependents, and deductions, and the system retrieves this data.

[0159] The "means for calculating taxable income and tax amount based on the data" is a function for calculating taxable income based on the received financial data and calculating the tax amount based on that.

[0160] The "means for displaying the tax amount calculated by the calculation means" is a function for displaying the calculated tax amount in a form that can be viewed by the user.

[0161] The "means for proposing tax-saving methods based on the data" is a function for analyzing appropriate tax-saving methods based on the collected financial data and recommending them to the user.

[0162] The "means for generating reminders for important procedures" is a function for managing dates and deadlines for important tax-related procedures and notifying users of them.

[0163] "Means for linking with electronic payment services" refers to a function for synchronizing with the electronic payment application used by the user and collecting and using the payment information.

[0164] "Means for automatically collecting income and expenditure data and periodically notifying users of tax amounts and tax-saving methods" is a function for automatically collecting income and expenditure data from electronic payment services and periodically providing users with information on tax amounts and tax-saving methods.

[0165] The system receives input data on a user's income, expenses, number of dependents, and deductions, automatically calculates tax amounts based on the data, and suggests appropriate tax-saving methods. It also has the function of reminding users of important tax procedures and effectively managing income and expenditure data in conjunction with electronic payment services.

[0166] System Configuration

[0167] The system mainly consists of a server, a terminal, and a user. It is implemented as an application on a smartphone. The server receives, stores, and analyzes user data, while the terminal receives input from the user and displays the results.

[0168] Entering and submitting user data

[0169] Users enter their income, expenses, number of dependents, and deductions through a smartphone app. This data is sent to the server in JSON format. Specifically, the data entered on the mobile device is sent to the server via the Internet.

[0170] Receiving and storing user data

[0171] The server receives the user data sent from the terminal, parses the received data appropriately, and stores it in a database management system (such as an RDBMS).

[0172] Tax calculation

[0173] The server analyzes the stored user data and calculates taxable income. Specifically, it calculates taxable income by subtracting expenses and deductions from income, and then applies a certain tax rate to it to calculate the amount of tax.

[0174] Displaying calculation results

[0175] The calculated tax amount is sent from the server to the terminal and displayed to the user as a specific number, for example, "The user's tax amount is 660,000 yen."

[0176] Tax saving suggestions

[0177] The server then suggests appropriate tax-saving methods based on the analyzed user data. For example, if the user has one or more dependents, it may suggest "take out a dependent deduction." Furthermore, through detailed data analysis, it may also suggest other tax-saving methods, such as medical expense deductions.

[0178] Procedural Reminders

[0179] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and generates reminders. This reminder information is also sent to the device in JSON format and displayed to the user.

[0180] Collaboration with electronic payment services

[0181] The server automatically retrieves income and expenditure data from electronic payment services (for example, mobile payment apps). This ensures that users' income and expenditure information is always up to date, and this latest information is reflected in tax calculations and tax-saving suggestions.

[0182] Cyclic Notification System

[0183] The server periodically notifies users of information about tax amounts and tax-saving methods. The notifications are based on income and expenditure data obtained from the electronic payment service, so users can always keep up to date with the latest information.

[0184] Specific examples

[0185] For example, if a user enters the following data: income: 5 million yen, expenses: 1.5 million yen, number of dependents: 1, deductions: 200,000 yen, the server will operate as follows:

[0186] 1. Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0187] 2. Tax amount = 3.3 million yen 20% = 660,000 yen

[0188] 3. Suggestions and reminders are provided, such as "Receive your dependent deductions" and "30 days left until you file your tax return."

[0189] Prompt Sentence Examples

[0190] "If my income is 5 million yen, my expenses are 1.5 million yen, I have one dependent, and my deductions are 200,000 yen, please calculate my taxable income and tax amount and suggest appropriate tax-saving methods. Also, please display reminders for filing tax returns and year-end tax adjustments."

[0191] In this way, the present invention is designed to allow users to easily process taxes, and by providing tax calculation, tax saving method suggestions, and reminder functions, it significantly reduces the burden of tax processing.

[0192] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0193] Step 1: Enter and submit user data

[0194] The user enters income, expenses, number of dependents, and deductions through a smartphone app. This data is collected through an input form and converted into JSON format. After the input data is converted into JSON format, it is sent to the server. For example, if a user enters "income: 5 million yen, expenses: 1.5 million yen, number of dependents: 1, deductions: 200,000 yen," it will be sent as JSON format data.

[0195] Step 2: Receiving and storing user data

[0196] The server receives the JSON formatted user data sent from the terminal. After receiving it, the server parses this JSON data and stores it in a database together with the user identification information. The database system used here can be an RDBMS such as SQLite or MySQL.

[0197] Step 3: Calculate taxes

[0198] The server reads the user data stored in the database and calculates the tax amount. This calculation involves calculating taxable income by subtracting expenses and deductions from income. A hypothetical tax rate is then applied to calculate the tax amount. For example, if the taxable income is 3.3 million yen, a tax rate of 20% is applied, resulting in a tax amount of 660,000 yen.

[0199] Step 4: Displaying the calculation results

[0200] After the tax amount is calculated, the result is sent back to the terminal from the server. The terminal displays the received tax amount to the user. For example, a message such as "The tax amount is 660,000 yen" is displayed on the user's smartphone screen.

[0201] Step 5: Proposal for tax saving methods

[0202] The server proposes appropriate tax-saving methods based on user data. Specifically, if there is one or more dependents, a recommendation message is generated such as "Please claim the dependent deduction," or if there is a remaining medical expense deduction, "Please consider claiming the medical expense deduction." This suggestion is sent back to the terminal in JSON format and displayed to the user.

[0203] Step 6: Procedural Reminder

[0204] The server generates reminders for important tax procedures based on the current date. For example, it calculates the deadline for filing tax returns and year-end tax adjustments and generates a reminder such as "30 days left until tax returns are filed." This reminder information is also sent to the device in JSON format and notified to the user.

[0205] Step 7: Integrate with electronic payment services

[0206] The server automatically retrieves income and expenditure data from the electronic payment service and updates it periodically. This means that every time a user makes a purchase or makes a payment, that information is updated in real time in the system. This ensures that the latest data is always used for tax calculations and tax-saving suggestions.

[0207] Step 8: Periodic Notification System

[0208] The server periodically notifies users about their tax amount and tax saving methods based on the collected income and expenditure data. This is to ensure that users always have up-to-date information on important tax matters. For example, a notification may be sent to the user saying, "Your current tax amount is 660,000 yen. Please consider claiming medical expenses as a deduction."

[0209] 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.

[0210] The present invention combines a system that receives data on income, expenses, number of dependents, and deductions from users, automatically calculates tax amounts, suggests appropriate tax-saving methods, and reminds users of important tax procedures with an emotion engine that recognizes users' emotions, providing a more personalized service.

[0211] System Configuration

[0212] This system is mainly composed of a server, a terminal, a user, and an emotion engine. Specifically, the system operates in the following manner.

[0213] Entering and submitting user data

[0214] The user enters their income, expenses, number of dependents, and deductions into an input form on the device. The entered data is sent to the server in JSON format.

[0215] Receiving and storing user data

[0216] The server receives the user data sent from the device and parses it into a UserData object, which is then stored in a database.

[0217] Entering and sending emotional data

[0218] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes emotions from the user's voice, facial expressions, text, etc., and sends the data in JSON format to the server.

[0219] Receiving and analyzing emotion data

[0220] The server receives and analyzes the emotion data sent from the device, and is able to identify the emotion the user is currently feeling.

[0221] Tax calculation

[0222] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. Specifically, taxable income is calculated by subtracting expenses and deductions from income. A hypothetical tax rate is then applied to this taxable income to calculate the tax amount.

[0223] Displaying calculation results

[0224] The server sends the calculated tax amount in JSON format to the terminal, and the terminal displays the calculation result to the user. For example, a specific tax amount such as "The user's tax amount is XX yen" is displayed.

[0225] Tax saving suggestions

[0226] The server suggests appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will suggest easier and less time-consuming tax-saving methods. If the user is calm, it can suggest more detailed tax-saving methods. Specifically, if the user has one or more dependents, it will suggest "please claim the dependent deduction," and if the medical expense deduction is not applied, it will suggest "please consider claiming the medical expense deduction."

[0227] Procedural Reminders

[0228] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date. By taking emotional data into account, the system adjusts the reminder notification method. For example, if the user is nervous, the system will remind them in gentler terms. Also, if the user tends to forget, the system will remind them more frequently.

[0229] Specific examples

[0230] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0231] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0232] Tax amount = 3.3 million yen 20% = 660,000 yen

[0233] Next, if the emotion engine analyzes the user's emotion as "stress," it will suggest simple tax-saving measures such as "Please accept your dependent deductions." It will also gently remind the user, based on the emotion data, that "30 days left until your tax return."

[0234] As described above, the present invention enables users to easily and accurately calculate tax amounts, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures. Furthermore, by recognizing the user's emotions using an emotion engine, it is possible to provide more personalized services and reduce the burden of tax processing.

[0235] The processing flow will be explained below.

[0236] Step 1:

[0237] The user enters their income, expenses, number of dependents, and deductions into the input form on the terminal. The entered data is sent to the server by clicking the send button.

[0238] Step 2:

[0239] The device sends the entered user data in JSON format to the server, including income, expenses, number of dependents, and deductions.

[0240] Step 3:

[0241] The server receives the JSON formatted user data sent from the device and parses it as a UserData object. The parsed data is stored in the database.

[0242] Step 4:

[0243] An emotion engine that recognizes the user's emotions is connected to the device and analyzes emotions in real time from the user's voice, facial expressions, text, etc. The analyzed emotion data is sent to the server in JSON format.

[0244] Step 5:

[0245] The server receives the emotion data sent from the device and analyzes it to identify the user's current emotion, for example, identifying emotional states such as "stressed," "calm," or "elated."

[0246] Step 6:

[0247] The server retrieves the stored user data from the database and calculates taxable income based on income, expenses, and deductions. Specifically, taxable income is the amount obtained by subtracting expenses and deductions from income.

[0248] Step 7:

[0249] The server calculates the tax amount by applying a hypothetical tax rate to the calculated taxable income. For example, if the tax rate is assumed to be 20%, the tax amount is calculated by multiplying the taxable income by 0.2.

[0250] Step 8:

[0251] The server sends the calculated tax amount in JSON format to the terminal. The sent data includes the user name, taxable income, and tax amount.

[0252] Step 9:

[0253] The terminal displays the tax amount received from the server to the user. For example, a specific amount such as "The user's tax amount is XX yen" is displayed.

[0254] Step 10:

[0255] The server proposes appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will propose easier and less time-consuming tax-saving methods. If the user is calm, it will propose more detailed tax-saving methods.

[0256] Step 11:

[0257] The server sends the proposed tax saving methods in JSON format to the terminal. The sent data includes the specific tax saving methods and the reasons for them.

[0258] Step 12:

[0259] The terminal displays the tax saving suggestions received from the server to the user. For example, suggestions such as "Accept dependent deductions" or "Consider medical expense deductions" are displayed.

[0260] Step 13:

[0261] The server obtains the current date and calculates deadlines for important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments. By taking emotional data into account, the system adjusts the reminder notification method. For example, if the user is nervous, the system will remind them in calmer language.

[0262] Step 14:

[0263] The server sends the generated reminder information in JSON format to the device. The sent data includes the reminder content and notification method.

[0264] Step 15:

[0265] The device displays the reminder information received from the server to the user. For example, the specific number of days remaining until the end of the year tax adjustment is displayed in calm language.

[0266] Example 2

[0267] 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."

[0268] Conventional tax calculation systems calculate tax amounts based on data such as income, expenses, number of dependents, and deductions, and suggest ways to save on taxes. However, they were unable to provide personalized services that took into account the user's emotional state. As a result, users often felt stressed when completing tax procedures, making it difficult to process taxes efficiently.

[0269] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for converting the data into JSON format and transmitting it, means for receiving and analyzing user data transmitted from a terminal, means for recognizing the user's emotions and generating emotion data, means for analyzing emotions based on the emotion data, means for calculating taxable income and tax amount based on the data and the emotion data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data and the emotion data, and means for generating and notifying reminders of important procedures. This makes it possible to provide personalized tax services that take into account the user's emotional state.

[0270] "User Data" means data, including your tax information, such as your income, expenses, number of dependents, and deductions.

[0271] "JSON format" is an abbreviation for JavaScript Object Notation, and is a format for structuring data in text format.

[0272] A "terminal" is an electronic device that allows a user to input data and communicate with a server.

[0273] A "server" is a computer system that receives data sent from a terminal and performs various processes such as analysis, storage, and notification.

[0274] An "emotion engine" is software or hardware that analyzes emotions from a user's voice, facial expressions, text, etc., and generates emotion data.

[0275] "Emotion data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[0276] "Taxable income" is the amount of income remaining after deducting expenses and deductions, and is the basis for calculating tax.

[0277] "Tax amount" means the amount of tax payable calculated based on taxable income.

[0278] A "tax saving method" is a method for legally reducing the amount of tax you pay.

[0279] "Reminder" is a function that notifies users of deadlines and deadlines for important procedures.

[0280] "Personalized service" refers to the provision of customized services based on the user's specific data and emotional state.

[0281] A "notification" is a message or alert that conveys information to a user.

[0282] The present invention is a system that improves the convenience for users when calculating tax amounts and receiving suggestions for tax-saving methods, and specific embodiments are described below.

[0283] This system mainly consists of a server, a terminal, a user, and an emotion engine.

[0284] Entering and submitting user data

[0285] The user enters their income, expenses, number of dependents, and deductions into an input form on their device. The device receives this data and converts it into JSON format. After this conversion, the device sends the JSON data to the server. The device can be a regular computer, smartphone, or tablet.

[0286] Receiving and storing user data

[0287] The server has an API endpoint for receiving JSON-formatted data sent from the device. The server receives this data and parses it as a UserData object. The parsed data is stored in a database. For the database, a relational database management system such as MySQL or PostgreSQL is used.

[0288] Entering and sending emotional data

[0289] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes data such as the user's voice, facial expressions, and text, and converts the results into JSON format. Specific emotion engines that can be used include Affectiva's SDK and IBM Watson (registered trademark). This emotion data is also sent from the device to the server.

[0290] Receiving and analyzing emotion data

[0291] The server analyzes the emotion data sent from the device. This analysis identifies the emotion the user is currently feeling. The analysis results of the emotion engine are expressed as a state such as "stress" or "calm."

[0292] Tax calculation

[0293] The server calculates taxable income based on user data stored in the database. It subtracts expenses and deductions from income and then applies a hypothetical tax rate to calculate the tax amount. For example, if income is 5 million yen, expenses are 1.5 million yen, and deductions are 200,000 yen, taxable income is 3.3 million yen, and if a tax rate of 20% is applied, the tax amount is 660,000 yen.

[0294] Displaying calculation results

[0295] The server converts the calculated tax amount into JSON format and sends it to the terminal. The terminal then displays the received tax amount data to the user. A specific example of how it is displayed is a notification such as "Your tax amount is 660,000 yen."

[0296] Tax saving suggestions

[0297] The server suggests appropriate tax-saving methods based on user data and emotional data. If the user's emotion is analyzed as "stressed," the server will suggest simple tax-saving methods such as "take dependent deductions." On the other hand, if the user is calm, the server can also make more detailed suggestions such as "consider taking medical expense deductions."

[0298] Procedural Reminders

[0299] The server uses the current date to calculate deadlines for important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments. It also adjusts reminder notification methods based on emotional data. For example, if a user is nervous, it will send reminders in calming language, and if they tend to forget, it will send more frequent reminders.

[0300] Specific examples

[0301] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0302] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0303] Tax amount = 3.3 million yen 20% = 660,000 yen

[0304] If the emotion engine analyzes the emotion as "stress," it will suggest "Please accept your dependent deductions" and provide a gentle reminder that "30 days left until you file your tax return."

[0305] As described above, this invention provides a system that allows users to efficiently calculate tax amounts and receive suggestions for tax-saving methods without feeling stressed. By taking the user's emotions into consideration using an emotion engine, it is possible to realize more personalized services.

[0306] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0307] Step 1: Enter and submit user data

[0308] The user enters income, expenses, number of dependents, and deductions into an input form on the device. The device acquires this data and converts it into JSON format. The input data (input: "income: 5 million yen", "expense: 1.5 million yen", "number of dependents: 1", "deductions: 200,000 yen") is converted to JSON format (output: {"income": 5000000, "expense": 1500000, "dependents": 1, "deductions": 200000}). After conversion, the device sends this JSON data to the server. Specifically, the user enters the data using a web browser or a dedicated app, and JavaScript on the device converts it into JSON format and sends it via an HTTP POST request.

[0309] Step 2: Receiving and storing user data

[0310] The server receives JSON-formatted user data sent from the terminal via an HTTP POST request (input). The server parses the received data into a UserData object (data processing) and stores it in a database (output). Specifically, the server uses a web framework (e.g., Flask) to set up an endpoint to receive the POST request and reads the JSON-formatted data from the request body. Next, it connects to a database system (e.g., MySQL) and stores the parsed data.

[0311] Step 3: Enter and submit emotion data

[0312] The user's emotions are recognized by an emotion engine connected to the device (input). The emotion engine analyzes the user's voice, facial expressions, and text data (data calculation) and converts the results into JSON format (output). An example of the converted emotion data is {"emotion": "stress"}. In concrete terms, the user sends facial expressions and voice data to the emotion engine via the camera or microphone, and the emotion engine (for example, Affectiva's SDK) analyzes this and generates emotion data. The generated emotion data is then sent from the device to the server via an HTTP POST request.

[0313] Step 4: Receiving and analyzing emotion data

[0314] The server receives emotion data sent from the device via an HTTP POST request (input). The server analyzes the received emotion data (data calculation) and identifies the user's emotional state (output: identified as "stressed"). Specifically, the server uses a web framework (e.g., Flask) to set up an endpoint to receive emotion data and reads the JSON-formatted emotion data from the request body. It then performs specific processing based on the analysis results.

[0315] Step 5: Calculate taxes

[0316] The server calculates taxable income based on user data stored in the database (input). It subtracts expenses and deductions from income (data calculation) and calculates the tax amount by applying a hypothetical tax rate (output). As a specific calculation example, if income is 5 million yen, expenses are 1.5 million yen, and deductions are 200,000 yen, taxable income is 3.3 million yen. If a hypothetical tax rate of 20% is applied, the tax amount will be 660,000 yen. In concrete terms, the server retrieves user data from the database and calculates the tax amount using a function.

[0317] Step 6: Displaying the calculation results

[0318] The server converts the calculated tax amount into JSON format (output: {"tax_amount": 660000}) and sends it to the terminal (input). The terminal displays the received tax amount data to the user (output: "Your tax amount is 660,000 yen"). Specifically, the server converts the tax amount data into JSON format and returns it as an HTTP response to a request from the terminal. The terminal uses the received data to display it on the screen.

[0319] Step 7: Tax saving suggestions

[0320] The server proposes appropriate tax-saving methods based on user data and emotional data (input). If the user's emotional state is analyzed as "stressed," it proposes simple tax-saving methods such as "consider applying for dependent deductions" (output). Specifically, the server analyzes the user's emotional data and tax data, selects appropriate tax-saving methods, and notifies the user of the results.

[0321] Step 8: Procedural Reminders

[0322] The server uses the current date to remind users of important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments (input). The server adjusts the reminder notification method based on emotional data (output). Specifically, if the user is nervous, the server will notify them in calm language, and if they tend to forget, it will set up frequent reminders. The server adjusts the content of the reminder appropriately and notifies the user via their device.

[0323] (Application example 2)

[0324] 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."

[0325] In today's world, tax procedures and tax calculations are complicated, causing stress and burden to many users. Furthermore, there are few systems that provide personalized support and reminders to individual users, and the lack of emotional support is particularly problematic. When users are anxious or stressed, systems often fail to efficiently suggest or provide reminders for appropriate tax-saving methods.

[0326] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, means for generating reminders for important procedures, means for recognizing the user's emotional data using an emotion engine, and means for analyzing the emotional data and providing personalized services. This allows the user to easily and accurately calculate tax amounts, and by providing appropriate tax-saving method suggestions and reminders based on emotions, the burden of tax processing is reduced and more personalized services can be received.

[0327] "Income" refers to the total amount of money a user receives over a certain period of time, including salary, bonuses, business income, etc.

[0328] "Expenses" refers to the amount of money a user spends over a certain period of time, including living expenses, taxes, loan repayments, etc.

[0329] "Number of dependents" refers to the number of family members or relatives supported by the user.

[0330] "Deductions" are amounts that can be deducted from taxable income, including various statutory deductions.

[0331] "Taxable income" is income after deducting expenses and deductions, and is the base amount used to calculate taxes.

[0332] "Tax amount" is the amount of tax calculated based on taxable income.

[0333] A "tax saving method" is a method of legally reducing tax liability, including applying for deductions and making certain investments.

[0334] "Reminder" is a notification function that notifies users of important procedures and deadlines.

[0335] An "emotion engine" is a technology that analyzes a user's voice, facial expressions, text, etc. to recognize their current emotional state.

[0336] "Data submission" is the process of sending collected data to a server, often in JSON format.

[0337] The "JSON format" is a standard format for expressing data in text format and is widely used for data exchange.

[0338] A "personalized service" is a service that provides specific responses tailored based on a user's individual data and emotions.

[0339] System Configuration

[0340] The present invention is implemented by a system including a user, a server, a terminal, and an emotion engine. This system operates in the following manner.

[0341] Entering and submitting user data

[0342] The user launches the application on their device and enters their income, expenses, number of dependents, and deductions. The entered data is sent to the server in a standard format (JSON).

[0343] Receiving and storing user data

[0344] The server receives the user data sent from the terminal and parses it as a UserData object. The parsed data is stored in a database. This process uses a dedicated server as hardware and a database management system (DBMS) and parsing library as software.

[0345] Entering and sending emotional data

[0346] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes emotions from the user's voice, facial expressions, text, etc., and sends the data in a standard format (JSON) to the server. The software used is a voice and facial expression analysis library and a text analysis tool.

[0347] Receiving and analyzing emotion data

[0348] The server receives and analyzes the emotion data sent from the device to identify the emotion the user is currently feeling. Based on these results, personalized services are provided. As a specific example, EmotionEngine is used as a voice and facial expression analysis library, and an AI model is used as a text analysis tool.

[0349] Tax calculation

[0350] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. The server then calculates the amount of tax based on this taxable income. The software used is a dedicated tax calculation library.

[0351] Displaying calculation results

[0352] The calculated tax amount is sent to the terminal in a standard format (JSON format), and the terminal displays it to the user. An example of the display would be a specific amount such as "The user's tax amount is 660,000 yen."

[0353] Tax saving suggestions

[0354] The server proposes appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will propose simple tax-saving methods, and if the user is calm, it will propose detailed tax-saving methods. This is done using a tax-related database and a recommendation algorithm using an AI model.

[0355] Procedural Reminders

[0356] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and sends reminders to the user. It adjusts the notification method based on emotional data, providing reminders that correspond to the user's mental state.

[0357] Examples and prompts

[0358] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0359] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0360] Tax amount = 3.3 million yen 20% = 660,000 yen

[0361] Next, if the emotion engine analyzes the user's emotion as "stress," it suggests simple tax-saving methods such as "Please accept your dependent deductions" and gently reminds the user that "there are 30 days left until your tax return is due."

[0362] An example prompt is:

[0363] Simply enter the user's income (e.g., 5 million yen), expenses (e.g., 1.5 million yen), number of dependents (e.g., 1 person), and deductions (e.g., 200,000 yen). The app then analyzes the user's emotions from voice, facial expressions, and text, calculates the amount of tax, suggests appropriate tax-saving methods, and reminds users of the dates for required tax procedures.

[0364] In this way, the present invention provides a personalized tax support service based on the user's feelings, thereby reducing the burden on the user.

[0365] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0366] Step 1:

[0367] The user launches the application on their device and enters their income, expenses, number of dependents, and deductions. By filling in the data in the input form and pressing the data submission button, the collected data is sent to the server in a standard format (JSON format). Input: Income, expenses, number of dependents, deductions. Output: Collected data (JSON format).

[0368] Step 2:

[0369] The server receives user data sent from the device and parses it as a UserData object. Using a dedicated parsing library, it parses JSON format data and saves it in the database as structured data. Input: Collected data (JSON format). Output: Structured data (UserData object).

[0370] Step 3:

[0371] To collect user emotion data, an emotion engine connected to the device analyzes voice, facial expressions, text, etc. Using the device's camera and microphone, an emotion analysis library is used to recognize the user's emotions, and the data is sent to the server in a standard format (JSON format). Input: voice, facial expressions, text. Output: emotion data (JSON format).

[0372] Step 4:

[0373] The server receives and analyzes the emotion data sent from the device to identify the emotion the user is currently feeling. Using an analysis library called EmotionEngine, it extracts specific emotions (e.g., stress, calm, tension) from the emotion data. Input: Emotion data (JSON format). Output: Identified emotion information.

[0374] Step 5:

[0375] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. Using a dedicated tax calculation library, taxable income is calculated by subtracting expenses and deductions from income, and the tax amount is calculated based on that taxable income. Input: Structured data (UserData object). Output: Taxable income and tax amount.

[0376] Step 6:

[0377] The calculated tax amount is sent to the terminal in a standard format (JSON format), and the terminal displays it to the user. The specific tax amount (e.g., "The user's tax amount is 660,000 yen") is displayed on the screen. Input: Taxable income and tax amount. Output: Tax amount displayed (JSON format).

[0378] Step 7:

[0379] The server suggests appropriate tax-saving methods based on user data and emotional data. Taking emotional information into consideration, it suggests simple tax-saving methods if the user is stressed, and more detailed methods if the user is calm. It uses an AI model to make recommendations such as dependent deductions and medical expense deductions. Input: User data, emotional information. Output: Suggested tax-saving methods.

[0380] Step 8:

[0381] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and generates reminders. Taking into account emotional data, if the user is nervous, it will remind them in gentle words, and if they tend to forget, it will remind them more frequently. The reminder content is sent to the device in JSON format. Input: Current date, emotional information. Output: Reminder generation and sending (JSON format).

[0382] In this way, it is possible to provide the user with personalized tax support services throughout each processing step, thereby reducing the burden of tax processing on the user.

[0383] 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.

[0384] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0385] 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.

[0386] [Second embodiment]

[0387] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0388] 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.

[0389] 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).

[0390] 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.

[0391] 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.

[0392] 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).

[0393] 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.

[0394] 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.

[0395] 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.

[0396] 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.

[0397] 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.

[0398] 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."

[0399] The present invention is a system that receives data on income, expenses, number of dependents, and deductions from a user, automatically calculates tax amounts, suggests appropriate tax-saving methods, and also reminds users of important tax procedures.

[0400] System Configuration

[0401] This system is mainly composed of a server, a terminal, and a user. Specifically, the system operates as follows:

[0402] Entering and submitting user data

[0403] The user enters their income, expenses, number of dependents, and deductions into an input form on the device. The entered data is sent to the server in JSON format.

[0404] Receiving and storing user data

[0405] The server receives the user data sent from the terminal, parses the received data, and stores it in the server's database as a UserData object.

[0406] Tax calculation

[0407] The server calculates taxable income based on the saved user data. Taxable income is the amount obtained by subtracting expenses and deductions from income. Then, it applies a hypothetical tax rate to this taxable income to calculate the tax amount.

[0408] Displaying calculation results

[0409] The server sends the calculated tax amount to the terminal, and the terminal displays the calculation result to the user. For example, a specific tax amount such as "The user's tax amount is XX yen" is displayed.

[0410] Tax saving suggestions

[0411] The server proposes appropriate tax-saving methods based on user data. Specifically, if the user has one or more dependents, the server suggests "take advantage of the dependent deduction," and if the medical expense deduction is not yet sufficient, the server suggests "consider taking the medical expense deduction." This proposal is sent to the terminal in JSON format, and the terminal displays it to the user.

[0412] Procedural Reminders

[0413] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date. For example, a reminder such as "X days left until year-end tax adjustments" is generated. This reminder information is also sent to the device in JSON format, and the device displays it to the user.

[0414] Specific examples

[0415] For example, if a user inputs "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0416] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0417] Tax amount = 3.3 million yen 20% = 660,000 yen

[0418] Next, you'll see suggestions like "Please claim your dependent deductions" and reminders like "30 days left until your tax return."

[0419] As described above, the present invention allows users to easily and accurately calculate tax amounts, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures, thereby reducing the burden of tax processing and preventing penalties and fines.

[0420] The processing flow will be explained below.

[0421] Step 1:

[0422] The user enters their income, expenses, number of dependents, and deductions into the input form on the terminal. The entered data is sent to the server by clicking the send button.

[0423] Step 2:

[0424] The device sends the entered user data in JSON format to the server, including income, expenses, number of dependents, and deductions.

[0425] Step 3:

[0426] The server receives the JSON formatted user data sent from the device and parses it as a UserData object. The parsed data is stored in the database.

[0427] Step 4:

[0428] The server retrieves the stored user data from the database and calculates taxable income based on income, expenses, and deductions. Specifically, taxable income is the amount obtained by subtracting expenses and deductions from income.

[0429] Step 5:

[0430] The server calculates the tax amount by applying a hypothetical tax rate to the calculated taxable income. For example, if the tax rate is assumed to be 20%, the tax amount is calculated by multiplying the taxable income by 0.2.

[0431] Step 6:

[0432] The server sends the calculated tax amount in JSON format to the terminal. The sent data includes the user name and tax amount.

[0433] Step 7:

[0434] The terminal displays the tax amount received from the server to the user. For example, a specific amount such as "The user's tax amount is XX yen" is displayed.

[0435] Step 8:

[0436] The server will suggest tax-saving methods based on user data. For example, if the user has one or more dependents, it will suggest "take advantage of the dependent deduction," and if the medical expense deduction is not applied, it will suggest "consider taking the medical expense deduction."

[0437] Step 9:

[0438] The server sends the proposed tax saving methods in JSON format to the terminal. The sent data includes the proposed methods.

[0439] Step 10:

[0440] The terminal displays the tax saving suggestions received from the server to the user. For example, "Please accept the dependent deduction" or "Please consider the medical expense deduction" may be displayed.

[0441] Step 11:

[0442] The server obtains the current date and calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments. For example, it generates reminders such as "X days left until year-end tax adjustments."

[0443] Step 12:

[0444] The server sends the generated reminder information in JSON format to the device. The sent data includes the reminder content.

[0445] Step 13:

[0446] The device displays the reminder information received from the server to the user. For example, it displays the specific number of days until the end of the year tax adjustment.

[0447] Example 1

[0448] 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."

[0449] Traditional tax processing is complex, requiring a great deal of effort and expertise to accurately calculate tax amounts and individually recommend appropriate tax-saving methods. There is also a risk of forgetting deadlines for important tax procedures. To address these issues, users need a method that allows them to easily and accurately calculate tax amounts, receive appropriate tax-saving suggestions, and remember to complete important tax procedures.

[0450] 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.

[0451] In this invention, the server includes means for receiving information on income, expenses, number of dependents, and deductions from a user, means for transmitting the information in JSON format, means for receiving and storing the information in JSON format, means for calculating taxable income and tax amount based on the information, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the information, means for generating reminders of important procedures, and means for displaying the reminders to the user, thereby enabling the user to easily and accurately calculate tax amount, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures.

[0452] "User" means an individual or corporation that uses the system to enter tax information and receives tax calculations, tax saving suggestions, and tax procedure reminders.

[0453] "Income" refers to the total amount of income earned by a user in a year, and is the amount used as the basis for calculating taxable income.

[0454] "Expenses" refers to necessary expenses and consumption expenditures incurred by the user during the year, and are amounts that can be deducted from taxable income.

[0455] "Number of dependents" refers to the number of spouses, children, and other dependents of the user who qualify for tax deductions.

[0456] "Deductions" are certain legally recognized costs and expenses that can be deducted from income when calculating taxable income.

[0457] The "JSON format" is a lightweight data exchange format for structuring and sending and receiving data, and is an abbreviation for JavaScript Object Notation.

[0458] "Server" is a central computer system that receives, stores, and processes data sent by users and sends calculation results, suggestions, and reminder information to users.

[0459] "Taxable income" is the amount remaining after deducting expenses and deductions from the user's income, and is the amount used to calculate tax.

[0460] "Tax amount" is the amount of tax paid calculated based on taxable income.

[0461] "Tax saving methods" are means or methods for users to legally reduce their tax burden, and include dependent deductions and medical expense deductions.

[0462] "Reminders" are messages or alerts that notify users of important tax procedures or deadlines.

[0463] "Display means" refers to a method for visually presenting calculation results, tax saving suggestions, reminder information, etc. to the user, and includes web pages and application screens.

[0464] This invention is a system that automatically calculates tax amounts, suggests appropriate tax-saving methods, and reminds users of important tax procedures by allowing them to input information on income, expenses, number of dependents, and deductions. This system is composed of multiple elements, including a server, a terminal, and a user.

[0465] System Configuration

[0466] 1. Entering and submitting user data

[0467] Users open a web form on their device and enter their income, expenses, number of dependents, and deductions.

[0468] The device converts the input data into JSON format and sends a POST request to the server, using a standard web browser and HTTP request.

[0469] 2. Receiving and storing user data

[0470] The server receives JSON data from the device using the Python Flask framework, and parses it using the request.get_json() method.

[0471] The parsed data is then converted into a UserData object and saved to a MySQL database using SQLAlchemy.

[0472] 3. Tax calculation

[0473] The server calculates taxable income and tax amount based on the saved user data. Taxable income is the amount obtained by subtracting expenses and deductions from the user's income. The server also calculates the tax amount by applying a hypothetical tax rate.

[0474] 4. Displaying the calculation results

[0475] The server sends the calculated tax amount to the terminal in JSON format. To do this, the jsonify function is used to construct the response.

[0476] The terminal parses the response data and displays the calculation result to the user, for example, "Your tax amount is 660,000 yen."

[0477] 5. Tax saving suggestions

[0478] The server proposes appropriate tax-saving methods based on user data, taking into account the number of dependents and deduction amounts, and determines which methods are effective.

[0479] The server sends the proposal in JSON format to the device, which then displays it to the user. For example, the proposal might be "Please accept dependent deductions" or "Please consider medical expense deductions."

[0480] 6. Procedural Reminders

[0481] The server calculates deadlines for important tax procedures based on the current date and generates reminders, such as "30 days left until tax return."

[0482] This reminder is also sent in JSON format to the device, which then displays the reminder to the user.

[0483] Specific examples

[0484] For example, if a user enters the following data: Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen, the server will perform the following calculations:

[0485] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0486] Tax amount = 3.3 million yen 20% = 660,000 yen

[0487] Next, you'll see suggestions like "Please claim your dependent deductions" and reminders like "30 days left until your tax return."

[0488] Example prompts for generative AI models

[0489] "Calculate your tax amount based on the following information and suggest ways to save on tax: Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen."

[0490] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0491] Step 1: Enter and submit user data

[0492] The user opens a web form on their device and enters their income, expenses, number of dependents, and deductions. For example, the user enters "Income: 5 million yen," "Expenses: 1.5 million yen," "Number of dependents: 1," and "Deductions: 200,000 yen."

[0493] The terminal converts the input data into JSON format, specifically generating the following JSON object: {"income": 5000000, "expenses": 1500000, "dependents": 1, "deductions": 200000}.

[0494] The terminal sends this to the server as a POST request. The input data is collected on a web form and sent to the server by clicking the submit button.

[0495] Step 2: Receiving and storing user data

[0496] The server uses the Flask framework to receive the JSON data sent from the device. Specifically, it parses the received data using the request.get_json() method.

[0497] The server converts the parsed data into a UserData object, which is instantiated by creating an instance of the UserData class.

[0498] The server saves this object to the MySQL database via SQLAlchemy by executing the db_session.add(user_data) and db_session.commit() methods, which receives the input data, converts it into an object, and saves it to the database.

[0499] Step 3: Calculate taxes

[0500] The server retrieves the stored user data from the database using user_data = db_session.query(UserData).where(UserData.id == user_id).first().

[0501] The server calculates taxable income by subtracting expenses and deductions from the user's income. The specific calculation is taxable_income = user_data.income - user_data.expenses - user_data.deductions.

[0502] The server calculates the tax amount by applying a hypothetical tax rate. For example, this tax rate is set to 20%, and the calculation is tax_amount = taxable_income 0.20. The server calculates taxable income based on the input data and then calculates the tax amount from the result.

[0503] Step 4: Displaying the calculation results

[0504] The server sends the calculated tax amount in JSON format to the terminal. Specifically, it generates response = {"tax_amount": tax_amount} and returns it with return jsonify(response).

[0505] The terminal receives this response data and displays the calculation result to the user. For example, it displays "Your tax amount is 660,000 yen." The calculation result is received in JSON format and is presented visually to the user.

[0506] Step 5: Proposal for tax saving methods

[0507] The server recommends appropriate tax-saving methods based on user data. Specifically, it executes logic such as if user_data.dependents > 0: recommendations.append("Please take dependent deductions")

[0508] The server sends the recommendations in JSON format to the device. Specifically, it generates response = {"recommendations": recommendations} and returns it with return jsonify(response).

[0509] The device will then display the suggestions to the user. For example, it might say, "Accept dependent deductions" or "Consider medical expense deductions." It will then identify tax-saving methods based on user data and notify the user.

[0510] Step 6: Procedural Reminders

[0511] The server calculates deadlines for important tax procedures based on the current date: days_until_deadline = (deadline_date - datetime.now()).days.

[0512] The server generates reminders based on the calculation results and sends them to the device in JSON format. Specifically, it generates response = {"reminders": reminders} and returns it with return jsonify(response).

[0513] The device will display the sent reminder to the user, for example, "30 days left until tax return." By generating and notifying reminders, the device helps users remember important deadlines.

[0514] The above is a description of the specific operation of this system divided into processing steps.

[0515] (Application example 1)

[0516] 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."

[0517] It is time-consuming for users to calculate tax amounts based on their own income and expenditure data and find appropriate tax-saving methods. There is also a risk that they may forget important tax procedures. Conventional systems lack sufficient integration with electronic payment services, making it cumbersome to collect income and expenditure data and calculate tax amounts.

[0518] 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.

[0519] In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, means for generating reminders for important procedures, means for linking with an electronic payment service, and means for automatically importing income and expenditure data and periodically notifying the user of tax amount and tax-saving methods. This allows users to easily check their tax amount, find optimal tax-saving methods, and avoid forgetting deadlines for important tax procedures while using the electronic payment service.

[0520] "Means for receiving data on income, expenses, number of dependents, and deductions from users" refers to a function that allows users to input financial data such as their income, expenses, number of dependents, and deductions, and the system retrieves this data.

[0521] The "means for calculating taxable income and tax amount based on the data" is a function for calculating taxable income based on the received financial data and calculating the tax amount based on that.

[0522] The "means for displaying the tax amount calculated by the calculation means" is a function for displaying the calculated tax amount in a form that can be viewed by the user.

[0523] The "means for proposing tax-saving methods based on the data" is a function for analyzing appropriate tax-saving methods based on the collected financial data and recommending them to the user.

[0524] The "means for generating reminders for important procedures" is a function for managing dates and deadlines for important tax-related procedures and notifying users of them.

[0525] "Means for linking with electronic payment services" refers to a function for synchronizing with the electronic payment application used by the user and collecting and using the payment information.

[0526] "Means for automatically collecting income and expenditure data and periodically notifying users of tax amounts and tax-saving methods" is a function for automatically collecting income and expenditure data from electronic payment services and periodically providing users with information on tax amounts and tax-saving methods.

[0527] The system receives input data on a user's income, expenses, number of dependents, and deductions, automatically calculates tax amounts based on the data, and suggests appropriate tax-saving methods. It also has the function of reminding users of important tax procedures and effectively managing income and expenditure data in conjunction with electronic payment services.

[0528] System Configuration

[0529] The system mainly consists of a server, a terminal, and a user. It is implemented as an application on a smartphone. The server receives, stores, and analyzes user data, while the terminal receives input from the user and displays the results.

[0530] Entering and submitting user data

[0531] Users enter their income, expenses, number of dependents, and deductions through a smartphone app. This data is sent to the server in JSON format. Specifically, the data entered on the mobile device is sent to the server via the Internet.

[0532] Receiving and storing user data

[0533] The server receives the user data sent from the terminal, parses the received data appropriately, and stores it in a database management system (such as an RDBMS).

[0534] Tax calculation

[0535] The server analyzes the stored user data and calculates taxable income. Specifically, it calculates taxable income by subtracting expenses and deductions from income, and then applies a certain tax rate to it to calculate the amount of tax.

[0536] Displaying calculation results

[0537] The calculated tax amount is sent from the server to the terminal and displayed to the user as a specific number, for example, "The user's tax amount is 660,000 yen."

[0538] Tax saving suggestions

[0539] The server then suggests appropriate tax-saving methods based on the analyzed user data. For example, if the user has one or more dependents, it may suggest "take out a dependent deduction." Furthermore, through detailed data analysis, it may also suggest other tax-saving methods, such as medical expense deductions.

[0540] Procedural Reminders

[0541] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and generates reminders. This reminder information is also sent to the device in JSON format and displayed to the user.

[0542] Collaboration with electronic payment services

[0543] The server automatically retrieves income and expenditure data from electronic payment services (for example, mobile payment apps). This ensures that users' income and expenditure information is always up to date, and this latest information is reflected in tax calculations and tax-saving suggestions.

[0544] Cyclic Notification System

[0545] The server periodically notifies users of information about tax amounts and tax-saving methods. The notifications are based on income and expenditure data obtained from the electronic payment service, so users can always keep up to date with the latest information.

[0546] Specific examples

[0547] For example, if a user enters the following data: income: 5 million yen, expenses: 1.5 million yen, number of dependents: 1, deductions: 200,000 yen, the server will operate as follows:

[0548] 1. Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0549] 2. Tax amount = 3.3 million yen 20% = 660,000 yen

[0550] 3. Suggestions and reminders are provided, such as "Receive your dependent deductions" and "30 days left until you file your tax return."

[0551] Prompt Sentence Examples

[0552] "If my income is 5 million yen, my expenses are 1.5 million yen, I have one dependent, and my deductions are 200,000 yen, please calculate my taxable income and tax amount and suggest appropriate tax-saving methods. Also, please display reminders for filing tax returns and year-end tax adjustments."

[0553] In this way, the present invention is designed to allow users to easily process taxes, and by providing tax calculation, tax saving method suggestions, and reminder functions, it significantly reduces the burden of tax processing.

[0554] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0555] Step 1: Enter and submit user data

[0556] The user enters income, expenses, number of dependents, and deductions through a smartphone app. This data is collected through an input form and converted into JSON format. After the input data is converted into JSON format, it is sent to the server. For example, if a user enters "income: 5 million yen, expenses: 1.5 million yen, number of dependents: 1, deductions: 200,000 yen," it will be sent as JSON format data.

[0557] Step 2: Receiving and storing user data

[0558] The server receives the JSON formatted user data sent from the terminal. After receiving it, the server parses this JSON data and stores it in a database together with the user identification information. The database system used here can be an RDBMS such as SQLite or MySQL.

[0559] Step 3: Calculate taxes

[0560] The server reads the user data stored in the database and calculates the tax amount. This calculation involves calculating taxable income by subtracting expenses and deductions from income. A hypothetical tax rate is then applied to calculate the tax amount. For example, if the taxable income is 3.3 million yen, a tax rate of 20% is applied, resulting in a tax amount of 660,000 yen.

[0561] Step 4: Displaying the calculation results

[0562] After the tax amount is calculated, the result is sent back to the terminal from the server. The terminal displays the received tax amount to the user. For example, a message such as "The tax amount is 660,000 yen" is displayed on the user's smartphone screen.

[0563] Step 5: Proposal for tax saving methods

[0564] The server proposes appropriate tax-saving methods based on user data. Specifically, if there is one or more dependents, a recommendation message is generated such as "Please claim the dependent deduction," or if there is a remaining medical expense deduction, "Please consider claiming the medical expense deduction." This suggestion is sent back to the terminal in JSON format and displayed to the user.

[0565] Step 6: Procedural Reminder

[0566] The server generates reminders for important tax procedures based on the current date. For example, it calculates the deadline for filing tax returns and year-end tax adjustments and generates a reminder such as "30 days left until tax returns are filed." This reminder information is also sent to the device in JSON format and notified to the user.

[0567] Step 7: Integrate with electronic payment services

[0568] The server automatically retrieves income and expenditure data from the electronic payment service and updates it periodically. This means that every time a user makes a purchase or makes a payment, that information is updated in real time in the system. This ensures that the latest data is always used for tax calculations and tax-saving suggestions.

[0569] Step 8: Periodic Notification System

[0570] The server periodically notifies users about their tax amount and tax saving methods based on the collected income and expenditure data. This is to ensure that users always have up-to-date information on important tax matters. For example, a notification may be sent to the user saying, "Your current tax amount is 660,000 yen. Please consider claiming medical expenses as a deduction."

[0571] 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.

[0572] The present invention combines a system that receives data on income, expenses, number of dependents, and deductions from users, automatically calculates tax amounts, suggests appropriate tax-saving methods, and reminds users of important tax procedures with an emotion engine that recognizes users' emotions, providing a more personalized service.

[0573] System Configuration

[0574] This system is mainly composed of a server, a terminal, a user, and an emotion engine. Specifically, the system operates in the following manner.

[0575] Entering and submitting user data

[0576] The user enters their income, expenses, number of dependents, and deductions into an input form on the device. The entered data is sent to the server in JSON format.

[0577] Receiving and storing user data

[0578] The server receives the user data sent from the device and parses it into a UserData object, which is then stored in a database.

[0579] Entering and sending emotional data

[0580] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes emotions from the user's voice, facial expressions, text, etc., and sends the data in JSON format to the server.

[0581] Receiving and analyzing emotion data

[0582] The server receives and analyzes the emotion data sent from the device, and is able to identify the emotion the user is currently feeling.

[0583] Tax calculation

[0584] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. Specifically, taxable income is calculated by subtracting expenses and deductions from income. A hypothetical tax rate is then applied to this taxable income to calculate the tax amount.

[0585] Displaying calculation results

[0586] The server sends the calculated tax amount in JSON format to the terminal, and the terminal displays the calculation result to the user. For example, a specific tax amount such as "The user's tax amount is XX yen" is displayed.

[0587] Tax saving suggestions

[0588] The server suggests appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will suggest easier and less time-consuming tax-saving methods. If the user is calm, it can suggest more detailed tax-saving methods. Specifically, if the user has one or more dependents, it will suggest "please claim the dependent deduction," and if the medical expense deduction is not applied, it will suggest "please consider claiming the medical expense deduction."

[0589] Procedural Reminders

[0590] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date. By taking emotional data into account, the system adjusts the reminder notification method. For example, if the user is nervous, the system will remind them in gentler terms. Also, if the user tends to forget, the system will remind them more frequently.

[0591] Specific examples

[0592] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0593] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0594] Tax amount = 3.3 million yen 20% = 660,000 yen

[0595] Next, if the emotion engine analyzes the user's emotion as "stress," it will suggest simple tax-saving measures such as "Please accept your dependent deductions." It will also gently remind the user, based on the emotion data, that "30 days left until your tax return."

[0596] As described above, the present invention enables users to easily and accurately calculate tax amounts, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures. Furthermore, by recognizing the user's emotions using an emotion engine, it is possible to provide more personalized services and reduce the burden of tax processing.

[0597] The processing flow will be explained below.

[0598] Step 1:

[0599] The user enters their income, expenses, number of dependents, and deductions into the input form on the terminal. The entered data is sent to the server by clicking the send button.

[0600] Step 2:

[0601] The device sends the entered user data in JSON format to the server, including income, expenses, number of dependents, and deductions.

[0602] Step 3:

[0603] The server receives the JSON formatted user data sent from the device and parses it as a UserData object. The parsed data is stored in the database.

[0604] Step 4:

[0605] An emotion engine that recognizes the user's emotions is connected to the device and analyzes emotions in real time from the user's voice, facial expressions, text, etc. The analyzed emotion data is sent to the server in JSON format.

[0606] Step 5:

[0607] The server receives the emotion data sent from the device and analyzes it to identify the user's current emotion, for example, identifying emotional states such as "stressed," "calm," or "elated."

[0608] Step 6:

[0609] The server retrieves the stored user data from the database and calculates taxable income based on income, expenses, and deductions. Specifically, taxable income is the amount obtained by subtracting expenses and deductions from income.

[0610] Step 7:

[0611] The server calculates the tax amount by applying a hypothetical tax rate to the calculated taxable income. For example, if the tax rate is assumed to be 20%, the tax amount is calculated by multiplying the taxable income by 0.2.

[0612] Step 8:

[0613] The server sends the calculated tax amount in JSON format to the terminal. The sent data includes the user name, taxable income, and tax amount.

[0614] Step 9:

[0615] The terminal displays the tax amount received from the server to the user. For example, a specific amount such as "The user's tax amount is XX yen" is displayed.

[0616] Step 10:

[0617] The server proposes appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will propose easier and less time-consuming tax-saving methods. If the user is calm, it will propose more detailed tax-saving methods.

[0618] Step 11:

[0619] The server sends the proposed tax saving methods in JSON format to the terminal. The sent data includes the specific tax saving methods and the reasons for them.

[0620] Step 12:

[0621] The terminal displays the tax saving suggestions received from the server to the user. For example, suggestions such as "Accept dependent deductions" or "Consider medical expense deductions" are displayed.

[0622] Step 13:

[0623] The server obtains the current date and calculates deadlines for important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments. By taking emotional data into account, the system adjusts the reminder notification method. For example, if the user is nervous, the system will remind them in calmer language.

[0624] Step 14:

[0625] The server sends the generated reminder information in JSON format to the device. The sent data includes the reminder content and notification method.

[0626] Step 15:

[0627] The device displays the reminder information received from the server to the user. For example, the specific number of days remaining until the end of the year tax adjustment is displayed in calm language.

[0628] Example 2

[0629] 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."

[0630] Conventional tax calculation systems calculate tax amounts based on data such as income, expenses, number of dependents, and deductions, and suggest ways to save on taxes. However, they were unable to provide personalized services that took into account the user's emotional state. As a result, users often felt stressed when completing tax procedures, making it difficult to process taxes efficiently.

[0631] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for converting the data into JSON format and transmitting it, means for receiving and analyzing user data transmitted from a terminal, means for recognizing the user's emotions and generating emotion data, means for analyzing emotions based on the emotion data, means for calculating taxable income and tax amount based on the data and the emotion data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data and the emotion data, and means for generating and notifying reminders of important procedures. This makes it possible to provide personalized tax services that take into account the user's emotional state.

[0632] "User Data" means data, including your tax information, such as your income, expenses, number of dependents, and deductions.

[0633] "JSON format" is an abbreviation for JavaScript Object Notation, and is a format for structuring data in text format.

[0634] A "terminal" is an electronic device that allows a user to input data and communicate with a server.

[0635] A "server" is a computer system that receives data sent from a terminal and performs various processes such as analysis, storage, and notification.

[0636] An "emotion engine" is software or hardware that analyzes emotions from a user's voice, facial expressions, text, etc., and generates emotion data.

[0637] "Emotion data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[0638] "Taxable income" is the amount of income remaining after deducting expenses and deductions, and is the basis for calculating tax.

[0639] "Tax amount" means the amount of tax payable calculated based on taxable income.

[0640] A "tax saving method" is a method for legally reducing the amount of tax you pay.

[0641] "Reminder" is a function that notifies users of deadlines and deadlines for important procedures.

[0642] "Personalized service" refers to the provision of customized services based on the user's specific data and emotional state.

[0643] A "notification" is a message or alert that conveys information to a user.

[0644] The present invention is a system that improves the convenience for users when calculating tax amounts and receiving suggestions for tax-saving methods, and specific embodiments are described below.

[0645] This system mainly consists of a server, a terminal, a user, and an emotion engine.

[0646] Entering and submitting user data

[0647] The user enters their income, expenses, number of dependents, and deductions into an input form on their device. The device receives this data and converts it into JSON format. After this conversion, the device sends the JSON data to the server. The device can be a regular computer, smartphone, or tablet.

[0648] Receiving and storing user data

[0649] The server has an API endpoint for receiving JSON-formatted data sent from the device. The server receives this data and parses it as a UserData object. The parsed data is stored in a database. For the database, a relational database management system such as MySQL or PostgreSQL is used.

[0650] Entering and sending emotional data

[0651] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes data such as the user's voice, facial expressions, and text, and converts the results into JSON format. Specific emotion engines that can be used include Affectiva's SDK and IBM Watson. This emotion data is also sent from the device to the server.

[0652] Receiving and analyzing emotion data

[0653] The server analyzes the emotion data sent from the device. This analysis identifies the emotion the user is currently feeling. The analysis results of the emotion engine are expressed as a state such as "stress" or "calm."

[0654] Tax calculation

[0655] The server calculates taxable income based on user data stored in the database. It subtracts expenses and deductions from income and then applies a hypothetical tax rate to calculate the tax amount. For example, if income is 5 million yen, expenses are 1.5 million yen, and deductions are 200,000 yen, taxable income is 3.3 million yen, and if a tax rate of 20% is applied, the tax amount is 660,000 yen.

[0656] Displaying calculation results

[0657] The server converts the calculated tax amount into JSON format and sends it to the terminal. The terminal then displays the received tax amount data to the user. A specific example of how it is displayed is a notification such as "Your tax amount is 660,000 yen."

[0658] Tax saving suggestions

[0659] The server suggests appropriate tax-saving methods based on user data and emotional data. If the user's emotion is analyzed as "stressed," the server will suggest simple tax-saving methods such as "take dependent deductions." On the other hand, if the user is calm, the server can also make more detailed suggestions such as "consider taking medical expense deductions."

[0660] Procedural Reminders

[0661] The server uses the current date to calculate deadlines for important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments. It also adjusts reminder notification methods based on emotional data. For example, if a user is nervous, it will send reminders in calming language, and if they tend to forget, it will send more frequent reminders.

[0662] Specific examples

[0663] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0664] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0665] Tax amount = 3.3 million yen 20% = 660,000 yen

[0666] If the emotion engine analyzes the emotion as "stress," it will suggest "Please accept your dependent deductions" and provide a gentle reminder that "30 days left until you file your tax return."

[0667] As described above, this invention provides a system that allows users to efficiently calculate tax amounts and receive suggestions for tax-saving methods without feeling stressed. By taking the user's emotions into consideration using an emotion engine, it is possible to realize more personalized services.

[0668] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0669] Step 1: Enter and submit user data

[0670] The user enters income, expenses, number of dependents, and deductions into an input form on the device. The device acquires this data and converts it into JSON format. The input data (input: "income: 5 million yen", "expense: 1.5 million yen", "number of dependents: 1", "deductions: 200,000 yen") is converted to JSON format (output: {"income": 5000000, "expense": 1500000, "dependents": 1, "deductions": 200000}). After conversion, the device sends this JSON data to the server. Specifically, the user enters the data using a web browser or a dedicated app, and JavaScript on the device converts it into JSON format and sends it via an HTTP POST request.

[0671] Step 2: Receiving and storing user data

[0672] The server receives JSON-formatted user data sent from the terminal via an HTTP POST request (input). The server parses the received data into a UserData object (data processing) and stores it in a database (output). Specifically, the server uses a web framework (e.g., Flask) to set up an endpoint to receive the POST request and reads the JSON-formatted data from the request body. Next, it connects to a database system (e.g., MySQL) and stores the parsed data.

[0673] Step 3: Enter and submit emotion data

[0674] The user's emotions are recognized by an emotion engine connected to the device (input). The emotion engine analyzes the user's voice, facial expressions, and text data (data calculation) and converts the results into JSON format (output). An example of the converted emotion data is {"emotion": "stress"}. In concrete terms, the user sends facial expressions and voice data to the emotion engine via the camera or microphone, and the emotion engine (for example, Affectiva's SDK) analyzes this and generates emotion data. The generated emotion data is then sent from the device to the server via an HTTP POST request.

[0675] Step 4: Receiving and analyzing emotion data

[0676] The server receives emotion data sent from the device via an HTTP POST request (input). The server analyzes the received emotion data (data calculation) and identifies the user's emotional state (output: identified as "stressed"). Specifically, the server uses a web framework (e.g., Flask) to set up an endpoint to receive emotion data and reads the JSON-formatted emotion data from the request body. It then performs specific processing based on the analysis results.

[0677] Step 5: Calculate taxes

[0678] The server calculates taxable income based on user data stored in the database (input). It subtracts expenses and deductions from income (data calculation) and calculates the tax amount by applying a hypothetical tax rate (output). As a specific calculation example, if income is 5 million yen, expenses are 1.5 million yen, and deductions are 200,000 yen, taxable income is 3.3 million yen. If a hypothetical tax rate of 20% is applied, the tax amount will be 660,000 yen. In concrete terms, the server retrieves user data from the database and calculates the tax amount using a function.

[0679] Step 6: Displaying the calculation results

[0680] The server converts the calculated tax amount into JSON format (output: {"tax_amount": 660000}) and sends it to the terminal (input). The terminal displays the received tax amount data to the user (output: "Your tax amount is 660,000 yen"). Specifically, the server converts the tax amount data into JSON format and returns it as an HTTP response to a request from the terminal. The terminal uses the received data to display it on the screen.

[0681] Step 7: Tax saving suggestions

[0682] The server proposes appropriate tax-saving methods based on user data and emotional data (input). If the user's emotional state is analyzed as "stressed," it proposes simple tax-saving methods such as "consider applying for dependent deductions" (output). Specifically, the server analyzes the user's emotional data and tax data, selects appropriate tax-saving methods, and notifies the user of the results.

[0683] Step 8: Procedural Reminders

[0684] The server uses the current date to remind users of important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments (input). The server adjusts the reminder notification method based on emotional data (output). Specifically, if the user is nervous, the server will notify them in calm language, and if they tend to forget, it will set up frequent reminders. The server adjusts the content of the reminder appropriately and notifies the user via their device.

[0685] (Application example 2)

[0686] 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."

[0687] In today's world, tax procedures and tax calculations are complicated, causing stress and burden to many users. Furthermore, there are few systems that provide personalized support and reminders to individual users, and the lack of emotional support is particularly problematic. When users are anxious or stressed, systems often fail to efficiently suggest or provide reminders for appropriate tax-saving methods.

[0688] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, means for generating reminders for important procedures, means for recognizing the user's emotional data using an emotion engine, and means for analyzing the emotional data and providing personalized services. This allows the user to easily and accurately calculate tax amounts, and by providing appropriate tax-saving method suggestions and reminders based on emotions, the burden of tax processing is reduced and more personalized services can be received.

[0689] "Income" refers to the total amount of money a user receives over a certain period of time, including salary, bonuses, business income, etc.

[0690] "Expenses" refers to the amount of money a user spends over a certain period of time, including living expenses, taxes, loan repayments, etc.

[0691] "Number of dependents" refers to the number of family members or relatives supported by the user.

[0692] "Deductions" are amounts that can be deducted from taxable income, including various statutory deductions.

[0693] "Taxable income" is income after deducting expenses and deductions, and is the base amount used to calculate taxes.

[0694] "Tax amount" is the amount of tax calculated based on taxable income.

[0695] A "tax saving method" is a method of legally reducing tax liability, including applying for deductions and making certain investments.

[0696] "Reminder" is a notification function that notifies users of important procedures and deadlines.

[0697] An "emotion engine" is a technology that analyzes a user's voice, facial expressions, text, etc. to recognize their current emotional state.

[0698] "Data submission" is the process of sending collected data to a server, often in JSON format.

[0699] The "JSON format" is a standard format for expressing data in text format and is widely used for data exchange.

[0700] A "personalized service" is a service that provides specific responses tailored based on a user's individual data and emotions.

[0701] System Configuration

[0702] The present invention is implemented by a system including a user, a server, a terminal, and an emotion engine. This system operates in the following manner.

[0703] Entering and submitting user data

[0704] The user launches the application on their device and enters their income, expenses, number of dependents, and deductions. The entered data is sent to the server in a standard format (JSON).

[0705] Receiving and storing user data

[0706] The server receives the user data sent from the terminal and parses it as a UserData object. The parsed data is stored in a database. This process uses a dedicated server as hardware and a database management system (DBMS) and parsing library as software.

[0707] Entering and sending emotional data

[0708] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes emotions from the user's voice, facial expressions, text, etc., and sends the data in a standard format (JSON) to the server. The software used is a voice and facial expression analysis library and a text analysis tool.

[0709] Receiving and analyzing emotion data

[0710] The server receives and analyzes the emotion data sent from the device to identify the emotion the user is currently feeling. Based on these results, personalized services are provided. As a specific example, EmotionEngine is used as a voice and facial expression analysis library, and an AI model is used as a text analysis tool.

[0711] Tax calculation

[0712] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. The server then calculates the amount of tax based on this taxable income. The software used is a dedicated tax calculation library.

[0713] Displaying calculation results

[0714] The calculated tax amount is sent to the terminal in a standard format (JSON format), and the terminal displays it to the user. An example of the display would be a specific amount such as "The user's tax amount is 660,000 yen."

[0715] Tax saving suggestions

[0716] The server proposes appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will propose simple tax-saving methods, and if the user is calm, it will propose detailed tax-saving methods. This is done using a tax-related database and a recommendation algorithm using an AI model.

[0717] Procedural Reminders

[0718] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and sends reminders to the user. It adjusts the notification method based on emotional data, providing reminders that correspond to the user's mental state.

[0719] Examples and prompts

[0720] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0721] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0722] Tax amount = 3.3 million yen 20% = 660,000 yen

[0723] Next, if the emotion engine analyzes the user's emotion as "stress," it suggests simple tax-saving methods such as "Please accept your dependent deductions" and gently reminds the user that "there are 30 days left until your tax return is due."

[0724] An example prompt is:

[0725] Simply enter the user's income (e.g., 5 million yen), expenses (e.g., 1.5 million yen), number of dependents (e.g., 1 person), and deductions (e.g., 200,000 yen). The app then analyzes the user's emotions from voice, facial expressions, and text, calculates the amount of tax, suggests appropriate tax-saving methods, and reminds users of the dates for required tax procedures.

[0726] In this way, the present invention provides a personalized tax support service based on the user's feelings, thereby reducing the burden on the user.

[0727] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0728] Step 1:

[0729] The user launches the application on their device and enters their income, expenses, number of dependents, and deductions. By filling in the data in the input form and pressing the data submission button, the collected data is sent to the server in a standard format (JSON format). Input: Income, expenses, number of dependents, deductions. Output: Collected data (JSON format).

[0730] Step 2:

[0731] The server receives user data sent from the device and parses it as a UserData object. Using a dedicated parsing library, it parses JSON format data and saves it in the database as structured data. Input: Collected data (JSON format). Output: Structured data (UserData object).

[0732] Step 3:

[0733] To collect user emotion data, an emotion engine connected to the device analyzes voice, facial expressions, text, etc. Using the device's camera and microphone, an emotion analysis library is used to recognize the user's emotions, and the data is sent to the server in a standard format (JSON format). Input: voice, facial expressions, text. Output: emotion data (JSON format).

[0734] Step 4:

[0735] The server receives and analyzes the emotion data sent from the device to identify the emotion the user is currently feeling. Using an analysis library called EmotionEngine, it extracts specific emotions (e.g., stress, calm, tension) from the emotion data. Input: Emotion data (JSON format). Output: Identified emotion information.

[0736] Step 5:

[0737] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. Using a dedicated tax calculation library, taxable income is calculated by subtracting expenses and deductions from income, and the tax amount is calculated based on that taxable income. Input: Structured data (UserData object). Output: Taxable income and tax amount.

[0738] Step 6:

[0739] The calculated tax amount is sent to the terminal in a standard format (JSON format), and the terminal displays it to the user. The specific tax amount (e.g., "The user's tax amount is 660,000 yen") is displayed on the screen. Input: Taxable income and tax amount. Output: Tax amount displayed (JSON format).

[0740] Step 7:

[0741] The server suggests appropriate tax-saving methods based on user data and emotional data. Taking emotional information into consideration, it suggests simple tax-saving methods if the user is stressed, and more detailed methods if the user is calm. It uses an AI model to make recommendations such as dependent deductions and medical expense deductions. Input: User data, emotional information. Output: Suggested tax-saving methods.

[0742] Step 8:

[0743] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and generates reminders. Taking into account emotional data, if the user is nervous, it will remind them in gentle words, and if they tend to forget, it will remind them more frequently. The reminder content is sent to the device in JSON format. Input: Current date, emotional information. Output: Reminder generation and sending (JSON format).

[0744] In this way, it is possible to provide the user with personalized tax support services throughout each processing step, thereby reducing the burden of tax processing on the user.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] [Third embodiment]

[0749] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0750] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0751] 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).

[0752] 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.

[0753] 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.

[0754] 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).

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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."

[0761] The present invention is a system that receives data on income, expenses, number of dependents, and deductions from a user, automatically calculates tax amounts, suggests appropriate tax-saving methods, and also reminds users of important tax procedures.

[0762] System Configuration

[0763] This system is mainly composed of a server, a terminal, and a user. Specifically, the system operates as follows:

[0764] Entering and submitting user data

[0765] The user enters their income, expenses, number of dependents, and deductions into an input form on the device. The entered data is sent to the server in JSON format.

[0766] Receiving and storing user data

[0767] The server receives the user data sent from the terminal, parses the received data, and stores it in the server's database as a UserData object.

[0768] Tax calculation

[0769] The server calculates taxable income based on the saved user data. Taxable income is the amount obtained by subtracting expenses and deductions from income. Then, it applies a hypothetical tax rate to this taxable income to calculate the tax amount.

[0770] Displaying calculation results

[0771] The server sends the calculated tax amount to the terminal, and the terminal displays the calculation result to the user. For example, a specific tax amount such as "The user's tax amount is XX yen" is displayed.

[0772] Tax saving suggestions

[0773] The server proposes appropriate tax-saving methods based on user data. Specifically, if the user has one or more dependents, the server suggests "take advantage of the dependent deduction," and if the medical expense deduction is not yet sufficient, the server suggests "consider taking the medical expense deduction." This proposal is sent to the terminal in JSON format, and the terminal displays it to the user.

[0774] Procedural Reminders

[0775] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date. For example, a reminder such as "X days left until year-end tax adjustments" is generated. This reminder information is also sent to the device in JSON format, and the device displays it to the user.

[0776] Specific examples

[0777] For example, if a user inputs "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0778] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0779] Tax amount = 3.3 million yen 20% = 660,000 yen

[0780] Next, you'll see suggestions like "Please claim your dependent deductions" and reminders like "30 days left until your tax return."

[0781] As described above, the present invention allows users to easily and accurately calculate tax amounts, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures, thereby reducing the burden of tax processing and preventing penalties and fines.

[0782] The processing flow will be explained below.

[0783] Step 1:

[0784] The user enters their income, expenses, number of dependents, and deductions into the input form on the terminal. The entered data is sent to the server by clicking the send button.

[0785] Step 2:

[0786] The device sends the entered user data in JSON format to the server, including income, expenses, number of dependents, and deductions.

[0787] Step 3:

[0788] The server receives the JSON formatted user data sent from the device and parses it as a UserData object. The parsed data is stored in the database.

[0789] Step 4:

[0790] The server retrieves the stored user data from the database and calculates taxable income based on income, expenses, and deductions. Specifically, taxable income is the amount obtained by subtracting expenses and deductions from income.

[0791] Step 5:

[0792] The server calculates the tax amount by applying a hypothetical tax rate to the calculated taxable income. For example, if the tax rate is assumed to be 20%, the tax amount is calculated by multiplying the taxable income by 0.2.

[0793] Step 6:

[0794] The server sends the calculated tax amount in JSON format to the terminal. The sent data includes the user name and tax amount.

[0795] Step 7:

[0796] The terminal displays the tax amount received from the server to the user. For example, a specific amount such as "The user's tax amount is XX yen" is displayed.

[0797] Step 8:

[0798] The server will suggest tax-saving methods based on user data. For example, if the user has one or more dependents, it will suggest "take advantage of the dependent deduction," and if the medical expense deduction is not applied, it will suggest "consider taking the medical expense deduction."

[0799] Step 9:

[0800] The server sends the proposed tax saving methods in JSON format to the terminal. The sent data includes the proposed methods.

[0801] Step 10:

[0802] The terminal displays the tax saving suggestions received from the server to the user. For example, "Please accept the dependent deduction" or "Please consider the medical expense deduction" may be displayed.

[0803] Step 11:

[0804] The server obtains the current date and calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments. For example, it generates reminders such as "X days left until year-end tax adjustments."

[0805] Step 12:

[0806] The server sends the generated reminder information in JSON format to the device. The sent data includes the reminder content.

[0807] Step 13:

[0808] The device displays the reminder information received from the server to the user. For example, it displays the specific number of days until the end of the year tax adjustment.

[0809] Example 1

[0810] 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."

[0811] Traditional tax processing is complex, requiring a great deal of effort and expertise to accurately calculate tax amounts and individually recommend appropriate tax-saving methods. There is also a risk of forgetting deadlines for important tax procedures. To address these issues, users need a method that allows them to easily and accurately calculate tax amounts, receive appropriate tax-saving suggestions, and remember to complete important tax procedures.

[0812] 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.

[0813] In this invention, the server includes means for receiving information on income, expenses, number of dependents, and deductions from a user, means for transmitting the information in JSON format, means for receiving and storing the information in JSON format, means for calculating taxable income and tax amount based on the information, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the information, means for generating reminders of important procedures, and means for displaying the reminders to the user, thereby enabling the user to easily and accurately calculate tax amount, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures.

[0814] "User" means an individual or corporation that uses the system to enter tax information and receives tax calculations, tax saving suggestions, and tax procedure reminders.

[0815] "Income" refers to the total amount of income earned by a user in a year, and is the amount used as the basis for calculating taxable income.

[0816] "Expenses" refers to necessary expenses and consumption expenditures incurred by the user during the year, and are amounts that can be deducted from taxable income.

[0817] "Number of dependents" refers to the number of spouses, children, and other dependents of the user who qualify for tax deductions.

[0818] "Deductions" are certain legally recognized costs and expenses that can be deducted from income when calculating taxable income.

[0819] The "JSON format" is a lightweight data exchange format for structuring and sending and receiving data, and is an abbreviation for JavaScript Object Notation.

[0820] "Server" is a central computer system that receives, stores, and processes data sent by users and sends calculation results, suggestions, and reminder information to users.

[0821] "Taxable income" is the amount remaining after deducting expenses and deductions from the user's income, and is the amount used to calculate tax.

[0822] "Tax amount" is the amount of tax paid calculated based on taxable income.

[0823] "Tax saving methods" are means or methods for users to legally reduce their tax burden, and include dependent deductions and medical expense deductions.

[0824] "Reminders" are messages or alerts that notify users of important tax procedures or deadlines.

[0825] "Display means" refers to a method for visually presenting calculation results, tax saving suggestions, reminder information, etc. to the user, and includes web pages and application screens.

[0826] This invention is a system that automatically calculates tax amounts, suggests appropriate tax-saving methods, and reminds users of important tax procedures by allowing them to input information on income, expenses, number of dependents, and deductions. This system is composed of multiple elements, including a server, a terminal, and a user.

[0827] System Configuration

[0828] 1. Entering and submitting user data

[0829] Users open a web form on their device and enter their income, expenses, number of dependents, and deductions.

[0830] The device converts the input data into JSON format and sends a POST request to the server, using a standard web browser and HTTP request.

[0831] 2. Receiving and storing user data

[0832] The server receives JSON data from the device using the Python Flask framework, and parses it using the request.get_json() method.

[0833] The parsed data is then converted into a UserData object and saved to a MySQL database using SQLAlchemy.

[0834] 3. Tax calculation

[0835] The server calculates taxable income and tax amount based on the saved user data. Taxable income is the amount obtained by subtracting expenses and deductions from the user's income. The server also calculates the tax amount by applying a hypothetical tax rate.

[0836] 4. Displaying the calculation results

[0837] The server sends the calculated tax amount to the terminal in JSON format. To do this, the jsonify function is used to construct the response.

[0838] The terminal parses the response data and displays the calculation result to the user, for example, "Your tax amount is 660,000 yen."

[0839] 5. Tax saving suggestions

[0840] The server proposes appropriate tax-saving methods based on user data, taking into account the number of dependents and deduction amounts, and determines which methods are effective.

[0841] The server sends the proposal in JSON format to the device, which then displays it to the user. For example, the proposal might be "Please accept dependent deductions" or "Please consider medical expense deductions."

[0842] 6. Procedural Reminders

[0843] The server calculates deadlines for important tax procedures based on the current date and generates reminders, such as "30 days left until tax return."

[0844] This reminder is also sent in JSON format to the device, which then displays the reminder to the user.

[0845] Specific examples

[0846] For example, if a user enters the following data: Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen, the server will perform the following calculations:

[0847] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0848] Tax amount = 3.3 million yen 20% = 660,000 yen

[0849] Next, you'll see suggestions like "Please claim your dependent deductions" and reminders like "30 days left until your tax return."

[0850] Example prompts for generative AI models

[0851] "Calculate your tax amount based on the following information and suggest ways to save on tax: Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen."

[0852] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0853] Step 1: Enter and submit user data

[0854] The user opens a web form on their device and enters their income, expenses, number of dependents, and deductions. For example, the user enters "Income: 5 million yen," "Expenses: 1.5 million yen," "Number of dependents: 1," and "Deductions: 200,000 yen."

[0855] The terminal converts the input data into JSON format, specifically generating the following JSON object: {"income": 5000000, "expenses": 1500000, "dependents": 1, "deductions": 200000}.

[0856] The terminal sends this to the server as a POST request. The input data is collected on a web form and sent to the server by clicking the submit button.

[0857] Step 2: Receiving and storing user data

[0858] The server uses the Flask framework to receive the JSON data sent from the device. Specifically, it parses the received data using the request.get_json() method.

[0859] The server converts the parsed data into a UserData object, which is instantiated by creating an instance of the UserData class.

[0860] The server saves this object to the MySQL database via SQLAlchemy by executing the db_session.add(user_data) and db_session.commit() methods, which receives the input data, converts it into an object, and saves it to the database.

[0861] Step 3: Calculate taxes

[0862] The server retrieves the stored user data from the database using user_data = db_session.query(UserData).where(UserData.id == user_id).first().

[0863] The server calculates taxable income by subtracting expenses and deductions from the user's income. The specific calculation is taxable_income = user_data.income - user_data.expenses - user_data.deductions.

[0864] The server calculates the tax amount by applying a hypothetical tax rate. For example, this tax rate is set to 20%, and the calculation is tax_amount = taxable_income 0.20. The server calculates taxable income based on the input data and then calculates the tax amount from the result.

[0865] Step 4: Displaying the calculation results

[0866] The server sends the calculated tax amount in JSON format to the terminal. Specifically, it generates response = {"tax_amount": tax_amount} and returns it with return jsonify(response).

[0867] The terminal receives this response data and displays the calculation result to the user. For example, it displays "Your tax amount is 660,000 yen." The calculation result is received in JSON format and is presented visually to the user.

[0868] Step 5: Proposal for tax saving methods

[0869] The server recommends appropriate tax-saving methods based on user data. Specifically, it executes logic such as if user_data.dependents > 0: recommendations.append("Please take dependent deductions")

[0870] The server sends the recommendations in JSON format to the device. Specifically, it generates response = {"recommendations": recommendations} and returns it with return jsonify(response).

[0871] The device will then display the suggestions to the user. For example, it might say, "Accept dependent deductions" or "Consider medical expense deductions." It will then identify tax-saving methods based on user data and notify the user.

[0872] Step 6: Procedural Reminders

[0873] The server calculates deadlines for important tax procedures based on the current date: days_until_deadline = (deadline_date - datetime.now()).days.

[0874] The server generates reminders based on the calculation results and sends them to the device in JSON format. Specifically, it generates response = {"reminders": reminders} and returns it with return jsonify(response).

[0875] The device will display the sent reminder to the user, for example, "30 days left until tax return." By generating and notifying reminders, the device helps users remember important deadlines.

[0876] The above is a description of the specific operation of this system divided into processing steps.

[0877] (Application example 1)

[0878] 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."

[0879] It is time-consuming for users to calculate tax amounts based on their own income and expenditure data and find appropriate tax-saving methods. There is also a risk that they may forget important tax procedures. Conventional systems lack sufficient integration with electronic payment services, making it cumbersome to collect income and expenditure data and calculate tax amounts.

[0880] 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.

[0881] In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, means for generating reminders for important procedures, means for linking with an electronic payment service, and means for automatically importing income and expenditure data and periodically notifying the user of tax amount and tax-saving methods. This allows users to easily check their tax amount, find optimal tax-saving methods, and avoid forgetting deadlines for important tax procedures while using the electronic payment service.

[0882] "Means for receiving data on income, expenses, number of dependents, and deductions from users" refers to a function that allows users to input financial data such as their income, expenses, number of dependents, and deductions, and the system retrieves this data.

[0883] The "means for calculating taxable income and tax amount based on the data" is a function for calculating taxable income based on the received financial data and calculating the tax amount based on that.

[0884] The "means for displaying the tax amount calculated by the calculation means" is a function for displaying the calculated tax amount in a form that can be viewed by the user.

[0885] The "means for proposing tax-saving methods based on the data" is a function for analyzing appropriate tax-saving methods based on the collected financial data and recommending them to the user.

[0886] The "means for generating reminders for important procedures" is a function for managing dates and deadlines for important tax-related procedures and notifying users of them.

[0887] "Means for linking with electronic payment services" refers to a function for synchronizing with the electronic payment application used by the user and collecting and using the payment information.

[0888] "Means for automatically collecting income and expenditure data and periodically notifying users of tax amounts and tax-saving methods" is a function for automatically collecting income and expenditure data from electronic payment services and periodically providing users with information on tax amounts and tax-saving methods.

[0889] The system receives input data on a user's income, expenses, number of dependents, and deductions, automatically calculates tax amounts based on the data, and suggests appropriate tax-saving methods. It also has the function of reminding users of important tax procedures and effectively managing income and expenditure data in conjunction with electronic payment services.

[0890] System Configuration

[0891] The system mainly consists of a server, a terminal, and a user. It is implemented as an application on a smartphone. The server receives, stores, and analyzes user data, while the terminal receives input from the user and displays the results.

[0892] Entering and submitting user data

[0893] Users enter their income, expenses, number of dependents, and deductions through a smartphone app. This data is sent to the server in JSON format. Specifically, the data entered on the mobile device is sent to the server via the Internet.

[0894] Receiving and storing user data

[0895] The server receives the user data sent from the terminal, parses the received data appropriately, and stores it in a database management system (such as an RDBMS).

[0896] Tax calculation

[0897] The server analyzes the stored user data and calculates taxable income. Specifically, it calculates taxable income by subtracting expenses and deductions from income, and then applies a certain tax rate to it to calculate the amount of tax.

[0898] Displaying calculation results

[0899] The calculated tax amount is sent from the server to the terminal and displayed to the user as a specific number, for example, "The user's tax amount is 660,000 yen."

[0900] Tax saving suggestions

[0901] The server then suggests appropriate tax-saving methods based on the analyzed user data. For example, if the user has one or more dependents, it may suggest "take out a dependent deduction." Furthermore, through detailed data analysis, it may also suggest other tax-saving methods, such as medical expense deductions.

[0902] Procedural Reminders

[0903] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and generates reminders. This reminder information is also sent to the device in JSON format and displayed to the user.

[0904] Collaboration with electronic payment services

[0905] The server automatically retrieves income and expenditure data from electronic payment services (for example, mobile payment apps). This ensures that users' income and expenditure information is always up to date, and this latest information is reflected in tax calculations and tax-saving suggestions.

[0906] Cyclic Notification System

[0907] The server periodically notifies users of information about tax amounts and tax-saving methods. The notifications are based on income and expenditure data obtained from the electronic payment service, so users can always keep up to date with the latest information.

[0908] Specific examples

[0909] For example, if a user enters the following data: income: 5 million yen, expenses: 1.5 million yen, number of dependents: 1, deductions: 200,000 yen, the server will operate as follows:

[0910] 1. Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0911] 2. Tax amount = 3.3 million yen 20% = 660,000 yen

[0912] 3. Suggestions and reminders are provided, such as "Receive your dependent deductions" and "30 days left until you file your tax return."

[0913] Prompt Sentence Examples

[0914] "If my income is 5 million yen, my expenses are 1.5 million yen, I have one dependent, and my deductions are 200,000 yen, please calculate my taxable income and tax amount and suggest appropriate tax-saving methods. Also, please display reminders for filing tax returns and year-end tax adjustments."

[0915] In this way, the present invention is designed to allow users to easily process taxes, and by providing tax calculation, tax saving method suggestions, and reminder functions, it significantly reduces the burden of tax processing.

[0916] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0917] Step 1: Enter and submit user data

[0918] The user enters income, expenses, number of dependents, and deductions through a smartphone app. This data is collected through an input form and converted into JSON format. After the input data is converted into JSON format, it is sent to the server. For example, if a user enters "income: 5 million yen, expenses: 1.5 million yen, number of dependents: 1, deductions: 200,000 yen," it will be sent as JSON format data.

[0919] Step 2: Receiving and storing user data

[0920] The server receives the JSON formatted user data sent from the terminal. After receiving it, the server parses this JSON data and stores it in a database together with the user identification information. The database system used here can be an RDBMS such as SQLite or MySQL.

[0921] Step 3: Calculate taxes

[0922] The server reads the user data stored in the database and calculates the tax amount. This calculation involves calculating taxable income by subtracting expenses and deductions from income. A hypothetical tax rate is then applied to calculate the tax amount. For example, if the taxable income is 3.3 million yen, a tax rate of 20% is applied, resulting in a tax amount of 660,000 yen.

[0923] Step 4: Displaying the calculation results

[0924] After the tax amount is calculated, the result is sent back to the terminal from the server. The terminal displays the received tax amount to the user. For example, a message such as "The tax amount is 660,000 yen" is displayed on the user's smartphone screen.

[0925] Step 5: Proposal for tax saving methods

[0926] The server proposes appropriate tax-saving methods based on user data. Specifically, if there is one or more dependents, a recommendation message is generated such as "Please claim the dependent deduction," or if there is a remaining medical expense deduction, "Please consider claiming the medical expense deduction." This suggestion is sent back to the terminal in JSON format and displayed to the user.

[0927] Step 6: Procedural Reminder

[0928] The server generates reminders for important tax procedures based on the current date. For example, it calculates the deadline for filing tax returns and year-end tax adjustments and generates a reminder such as "30 days left until tax returns are filed." This reminder information is also sent to the device in JSON format and notified to the user.

[0929] Step 7: Integrate with electronic payment services

[0930] The server automatically retrieves income and expenditure data from the electronic payment service and updates it periodically. This means that every time a user makes a purchase or makes a payment, that information is updated in real time in the system. This ensures that the latest data is always used for tax calculations and tax-saving suggestions.

[0931] Step 8: Periodic Notification System

[0932] The server periodically notifies users about their tax amount and tax saving methods based on the collected income and expenditure data. This is to ensure that users always have up-to-date information on important tax matters. For example, a notification may be sent to the user saying, "Your current tax amount is 660,000 yen. Please consider claiming medical expenses as a deduction."

[0933] 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.

[0934] The present invention combines a system that receives data on income, expenses, number of dependents, and deductions from users, automatically calculates tax amounts, suggests appropriate tax-saving methods, and reminds users of important tax procedures with an emotion engine that recognizes users' emotions, providing a more personalized service.

[0935] System Configuration

[0936] This system is mainly composed of a server, a terminal, a user, and an emotion engine. Specifically, the system operates in the following manner.

[0937] Entering and submitting user data

[0938] The user enters their income, expenses, number of dependents, and deductions into an input form on the device. The entered data is sent to the server in JSON format.

[0939] Receiving and storing user data

[0940] The server receives the user data sent from the device and parses it into a UserData object, which is then stored in a database.

[0941] Entering and sending emotional data

[0942] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes emotions from the user's voice, facial expressions, text, etc., and sends the data in JSON format to the server.

[0943] Receiving and analyzing emotion data

[0944] The server receives and analyzes the emotion data sent from the device, and is able to identify the emotion the user is currently feeling.

[0945] Tax calculation

[0946] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. Specifically, taxable income is calculated by subtracting expenses and deductions from income. A hypothetical tax rate is then applied to this taxable income to calculate the tax amount.

[0947] Displaying calculation results

[0948] The server sends the calculated tax amount in JSON format to the terminal, and the terminal displays the calculation result to the user. For example, a specific tax amount such as "The user's tax amount is XX yen" is displayed.

[0949] Tax saving suggestions

[0950] The server suggests appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will suggest easier and less time-consuming tax-saving methods. If the user is calm, it can suggest more detailed tax-saving methods. Specifically, if the user has one or more dependents, it will suggest "please claim the dependent deduction," and if the medical expense deduction is not applied, it will suggest "please consider claiming the medical expense deduction."

[0951] Procedural Reminders

[0952] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date. By taking emotional data into account, the system adjusts the reminder notification method. For example, if the user is nervous, the system will remind them in gentler terms. Also, if the user tends to forget, the system will remind them more frequently.

[0953] Specific examples

[0954] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[0955] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[0956] Tax amount = 3.3 million yen 20% = 660,000 yen

[0957] Next, if the emotion engine analyzes the user's emotion as "stress," it will suggest simple tax-saving measures such as "Please accept your dependent deductions." It will also gently remind the user, based on the emotion data, that "30 days left until your tax return."

[0958] As described above, the present invention enables users to easily and accurately calculate tax amounts, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures. Furthermore, by recognizing the user's emotions using an emotion engine, it is possible to provide more personalized services and reduce the burden of tax processing.

[0959] The processing flow will be explained below.

[0960] Step 1:

[0961] The user enters their income, expenses, number of dependents, and deductions into the input form on the terminal. The entered data is sent to the server by clicking the send button.

[0962] Step 2:

[0963] The device sends the entered user data in JSON format to the server, including income, expenses, number of dependents, and deductions.

[0964] Step 3:

[0965] The server receives the JSON formatted user data sent from the device and parses it as a UserData object. The parsed data is stored in the database.

[0966] Step 4:

[0967] An emotion engine that recognizes the user's emotions is connected to the device and analyzes emotions in real time from the user's voice, facial expressions, text, etc. The analyzed emotion data is sent to the server in JSON format.

[0968] Step 5:

[0969] The server receives the emotion data sent from the device and analyzes it to identify the user's current emotion, for example, identifying emotional states such as "stressed," "calm," or "elated."

[0970] Step 6:

[0971] The server retrieves the stored user data from the database and calculates taxable income based on income, expenses, and deductions. Specifically, taxable income is the amount obtained by subtracting expenses and deductions from income.

[0972] Step 7:

[0973] The server calculates the tax amount by applying a hypothetical tax rate to the calculated taxable income. For example, if the tax rate is assumed to be 20%, the tax amount is calculated by multiplying the taxable income by 0.2.

[0974] Step 8:

[0975] The server sends the calculated tax amount in JSON format to the terminal. The sent data includes the user name, taxable income, and tax amount.

[0976] Step 9:

[0977] The terminal displays the tax amount received from the server to the user. For example, a specific amount such as "The user's tax amount is XX yen" is displayed.

[0978] Step 10:

[0979] The server proposes appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will propose easier and less time-consuming tax-saving methods. If the user is calm, it will propose more detailed tax-saving methods.

[0980] Step 11:

[0981] The server sends the proposed tax saving methods in JSON format to the terminal. The sent data includes the specific tax saving methods and the reasons for them.

[0982] Step 12:

[0983] The terminal displays the tax saving suggestions received from the server to the user. For example, suggestions such as "Accept dependent deductions" or "Consider medical expense deductions" are displayed.

[0984] Step 13:

[0985] The server obtains the current date and calculates deadlines for important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments. By taking emotional data into account, the system adjusts the reminder notification method. For example, if the user is nervous, the system will remind them in calmer language.

[0986] Step 14:

[0987] The server sends the generated reminder information in JSON format to the device. The sent data includes the reminder content and notification method.

[0988] Step 15:

[0989] The device displays the reminder information received from the server to the user. For example, the specific number of days remaining until the end of the year tax adjustment is displayed in calm language.

[0990] Example 2

[0991] 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."

[0992] Conventional tax calculation systems calculate tax amounts based on data such as income, expenses, number of dependents, and deductions, and suggest ways to save on taxes. However, they were unable to provide personalized services that took into account the user's emotional state. As a result, users often felt stressed when completing tax procedures, making it difficult to process taxes efficiently.

[0993] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for converting the data into JSON format and transmitting it, means for receiving and analyzing user data transmitted from a terminal, means for recognizing the user's emotions and generating emotion data, means for analyzing emotions based on the emotion data, means for calculating taxable income and tax amount based on the data and the emotion data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data and the emotion data, and means for generating and notifying reminders of important procedures. This makes it possible to provide personalized tax services that take into account the user's emotional state.

[0994] "User Data" means data, including your tax information, such as your income, expenses, number of dependents, and deductions.

[0995] "JSON format" is an abbreviation for JavaScript Object Notation, and is a format for structuring data in text format.

[0996] A "terminal" is an electronic device that allows a user to input data and communicate with a server.

[0997] A "server" is a computer system that receives data sent from a terminal and performs various processes such as analysis, storage, and notification.

[0998] An "emotion engine" is software or hardware that analyzes emotions from a user's voice, facial expressions, text, etc., and generates emotion data.

[0999] "Emotion data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[1000] "Taxable income" is the amount of income remaining after deducting expenses and deductions, and is the basis for calculating tax.

[1001] "Tax amount" means the amount of tax payable calculated based on taxable income.

[1002] A "tax saving method" is a method for legally reducing the amount of tax you pay.

[1003] "Reminder" is a function that notifies users of deadlines and deadlines for important procedures.

[1004] "Personalized service" refers to the provision of customized services based on the user's specific data and emotional state.

[1005] A "notification" is a message or alert that conveys information to a user.

[1006] The present invention is a system that improves the convenience for users when calculating tax amounts and receiving suggestions for tax-saving methods, and specific embodiments are described below.

[1007] This system mainly consists of a server, a terminal, a user, and an emotion engine.

[1008] Entering and submitting user data

[1009] The user enters their income, expenses, number of dependents, and deductions into an input form on their device. The device receives this data and converts it into JSON format. After this conversion, the device sends the JSON data to the server. The device can be a regular computer, smartphone, or tablet.

[1010] Receiving and storing user data

[1011] The server has an API endpoint for receiving JSON-formatted data sent from the device. The server receives this data and parses it as a UserData object. The parsed data is stored in a database. For the database, a relational database management system such as MySQL or PostgreSQL is used.

[1012] Entering and sending emotional data

[1013] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes data such as the user's voice, facial expressions, and text, and converts the results into JSON format. Specific emotion engines that can be used include Affectiva's SDK and IBM Watson. This emotion data is also sent from the device to the server.

[1014] Receiving and analyzing emotion data

[1015] The server analyzes the emotion data sent from the device. This analysis identifies the emotion the user is currently feeling. The analysis results of the emotion engine are expressed as a state such as "stress" or "calm."

[1016] Tax calculation

[1017] The server calculates taxable income based on user data stored in the database. It subtracts expenses and deductions from income and then applies a hypothetical tax rate to calculate the tax amount. For example, if income is 5 million yen, expenses are 1.5 million yen, and deductions are 200,000 yen, taxable income is 3.3 million yen, and if a tax rate of 20% is applied, the tax amount is 660,000 yen.

[1018] Displaying calculation results

[1019] The server converts the calculated tax amount into JSON format and sends it to the terminal. The terminal then displays the received tax amount data to the user. A specific example of how it is displayed is a notification such as "Your tax amount is 660,000 yen."

[1020] Tax saving suggestions

[1021] The server suggests appropriate tax-saving methods based on user data and emotional data. If the user's emotion is analyzed as "stressed," the server will suggest simple tax-saving methods such as "take dependent deductions." On the other hand, if the user is calm, the server can also make more detailed suggestions such as "consider taking medical expense deductions."

[1022] Procedural Reminders

[1023] The server uses the current date to calculate deadlines for important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments. It also adjusts reminder notification methods based on emotional data. For example, if a user is nervous, it will send reminders in calming language, and if they tend to forget, it will send more frequent reminders.

[1024] Specific examples

[1025] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[1026] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[1027] Tax amount = 3.3 million yen 20% = 660,000 yen

[1028] If the emotion engine analyzes the emotion as "stress," it will suggest "Please accept your dependent deductions" and provide a gentle reminder that "30 days left until you file your tax return."

[1029] As described above, this invention provides a system that allows users to efficiently calculate tax amounts and receive suggestions for tax-saving methods without feeling stressed. By taking the user's emotions into consideration using an emotion engine, it is possible to realize more personalized services.

[1030] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1031] Step 1: Enter and submit user data

[1032] The user enters income, expenses, number of dependents, and deductions into an input form on the device. The device acquires this data and converts it into JSON format. The input data (input: "income: 5 million yen", "expense: 1.5 million yen", "number of dependents: 1", "deductions: 200,000 yen") is converted to JSON format (output: {"income": 5000000, "expense": 1500000, "dependents": 1, "deductions": 200000}). After conversion, the device sends this JSON data to the server. Specifically, the user enters the data using a web browser or a dedicated app, and JavaScript on the device converts it into JSON format and sends it via an HTTP POST request.

[1033] Step 2: Receiving and storing user data

[1034] The server receives JSON-formatted user data sent from the terminal via an HTTP POST request (input). The server parses the received data into a UserData object (data processing) and stores it in a database (output). Specifically, the server uses a web framework (e.g., Flask) to set up an endpoint to receive the POST request and reads the JSON-formatted data from the request body. Next, it connects to a database system (e.g., MySQL) and stores the parsed data.

[1035] Step 3: Enter and submit emotion data

[1036] The user's emotions are recognized by an emotion engine connected to the device (input). The emotion engine analyzes the user's voice, facial expressions, and text data (data calculation) and converts the results into JSON format (output). An example of the converted emotion data is {"emotion": "stress"}. In concrete terms, the user sends facial expressions and voice data to the emotion engine via the camera or microphone, and the emotion engine (for example, Affectiva's SDK) analyzes this and generates emotion data. The generated emotion data is then sent from the device to the server via an HTTP POST request.

[1037] Step 4: Receiving and analyzing emotion data

[1038] The server receives emotion data sent from the device via an HTTP POST request (input). The server analyzes the received emotion data (data calculation) and identifies the user's emotional state (output: identified as "stressed"). Specifically, the server uses a web framework (e.g., Flask) to set up an endpoint to receive emotion data and reads the JSON-formatted emotion data from the request body. It then performs specific processing based on the analysis results.

[1039] Step 5: Calculate taxes

[1040] The server calculates taxable income based on user data stored in the database (input). It subtracts expenses and deductions from income (data calculation) and calculates the tax amount by applying a hypothetical tax rate (output). As a specific calculation example, if income is 5 million yen, expenses are 1.5 million yen, and deductions are 200,000 yen, taxable income is 3.3 million yen. If a hypothetical tax rate of 20% is applied, the tax amount will be 660,000 yen. In concrete terms, the server retrieves user data from the database and calculates the tax amount using a function.

[1041] Step 6: Displaying the calculation results

[1042] The server converts the calculated tax amount into JSON format (output: {"tax_amount": 660000}) and sends it to the terminal (input). The terminal displays the received tax amount data to the user (output: "Your tax amount is 660,000 yen"). Specifically, the server converts the tax amount data into JSON format and returns it as an HTTP response to a request from the terminal. The terminal uses the received data to display it on the screen.

[1043] Step 7: Tax saving suggestions

[1044] The server proposes appropriate tax-saving methods based on user data and emotional data (input). If the user's emotional state is analyzed as "stressed," it proposes simple tax-saving methods such as "consider applying for dependent deductions" (output). Specifically, the server analyzes the user's emotional data and tax data, selects appropriate tax-saving methods, and notifies the user of the results.

[1045] Step 8: Procedural Reminders

[1046] The server uses the current date to remind users of important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments (input). The server adjusts the reminder notification method based on emotional data (output). Specifically, if the user is nervous, the server will notify them in calm language, and if they tend to forget, it will set up frequent reminders. The server adjusts the content of the reminder appropriately and notifies the user via their device.

[1047] (Application example 2)

[1048] 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."

[1049] In today's world, tax procedures and tax calculations are complicated, causing stress and burden to many users. Furthermore, there are few systems that provide personalized support and reminders to individual users, and the lack of emotional support is particularly problematic. When users are anxious or stressed, systems often fail to efficiently suggest or provide reminders for appropriate tax-saving methods.

[1050] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, means for generating reminders for important procedures, means for recognizing the user's emotional data using an emotion engine, and means for analyzing the emotional data and providing personalized services. This allows the user to easily and accurately calculate tax amounts, and by providing appropriate tax-saving method suggestions and reminders based on emotions, the burden of tax processing is reduced and more personalized services can be received.

[1051] "Income" refers to the total amount of money a user receives over a certain period of time, including salary, bonuses, business income, etc.

[1052] "Expenses" refers to the amount of money a user spends over a certain period of time, including living expenses, taxes, loan repayments, etc.

[1053] "Number of dependents" refers to the number of family members or relatives supported by the user.

[1054] "Deductions" are amounts that can be deducted from taxable income, including various statutory deductions.

[1055] "Taxable income" is income after deducting expenses and deductions, and is the base amount used to calculate taxes.

[1056] "Tax amount" is the amount of tax calculated based on taxable income.

[1057] A "tax saving method" is a method of legally reducing tax liability, including applying for deductions and making certain investments.

[1058] "Reminder" is a notification function that notifies users of important procedures and deadlines.

[1059] An "emotion engine" is a technology that analyzes a user's voice, facial expressions, text, etc. to recognize their current emotional state.

[1060] "Data submission" is the process of sending collected data to a server, often in JSON format.

[1061] The "JSON format" is a standard format for expressing data in text format and is widely used for data exchange.

[1062] A "personalized service" is a service that provides specific responses tailored based on a user's individual data and emotions.

[1063] System Configuration

[1064] The present invention is implemented by a system including a user, a server, a terminal, and an emotion engine. This system operates in the following manner.

[1065] Entering and submitting user data

[1066] The user launches the application on their device and enters their income, expenses, number of dependents, and deductions. The entered data is sent to the server in a standard format (JSON).

[1067] Receiving and storing user data

[1068] The server receives the user data sent from the terminal and parses it as a UserData object. The parsed data is stored in a database. This process uses a dedicated server as hardware and a database management system (DBMS) and parsing library as software.

[1069] Entering and sending emotional data

[1070] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes emotions from the user's voice, facial expressions, text, etc., and sends the data in a standard format (JSON) to the server. The software used is a voice and facial expression analysis library and a text analysis tool.

[1071] Receiving and analyzing emotion data

[1072] The server receives and analyzes the emotion data sent from the device to identify the emotion the user is currently feeling. Based on these results, personalized services are provided. As a specific example, EmotionEngine is used as a voice and facial expression analysis library, and an AI model is used as a text analysis tool.

[1073] Tax calculation

[1074] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. The server then calculates the amount of tax based on this taxable income. The software used is a dedicated tax calculation library.

[1075] Displaying calculation results

[1076] The calculated tax amount is sent to the terminal in a standard format (JSON format), and the terminal displays it to the user. An example of the display would be a specific amount such as "The user's tax amount is 660,000 yen."

[1077] Tax saving suggestions

[1078] The server proposes appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will propose simple tax-saving methods, and if the user is calm, it will propose detailed tax-saving methods. This is done using a tax-related database and a recommendation algorithm using an AI model.

[1079] Procedural Reminders

[1080] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and sends reminders to the user. It adjusts the notification method based on emotional data, providing reminders that correspond to the user's mental state.

[1081] Examples and prompts

[1082] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[1083] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[1084] Tax amount = 3.3 million yen 20% = 660,000 yen

[1085] Next, if the emotion engine analyzes the user's emotion as "stress," it suggests simple tax-saving methods such as "Please accept your dependent deductions" and gently reminds the user that "there are 30 days left until your tax return is due."

[1086] An example prompt is:

[1087] Simply enter the user's income (e.g., 5 million yen), expenses (e.g., 1.5 million yen), number of dependents (e.g., 1 person), and deductions (e.g., 200,000 yen). The app then analyzes the user's emotions from voice, facial expressions, and text, calculates the amount of tax, suggests appropriate tax-saving methods, and reminds users of the dates for required tax procedures.

[1088] In this way, the present invention provides a personalized tax support service based on the user's feelings, thereby reducing the burden on the user.

[1089] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1090] Step 1:

[1091] The user launches the application on their device and enters their income, expenses, number of dependents, and deductions. By filling in the data in the input form and pressing the data submission button, the collected data is sent to the server in a standard format (JSON format). Input: Income, expenses, number of dependents, deductions. Output: Collected data (JSON format).

[1092] Step 2:

[1093] The server receives user data sent from the device and parses it as a UserData object. Using a dedicated parsing library, it parses JSON format data and saves it in the database as structured data. Input: Collected data (JSON format). Output: Structured data (UserData object).

[1094] Step 3:

[1095] To collect user emotion data, an emotion engine connected to the device analyzes voice, facial expressions, text, etc. Using the device's camera and microphone, an emotion analysis library is used to recognize the user's emotions, and the data is sent to the server in a standard format (JSON format). Input: voice, facial expressions, text. Output: emotion data (JSON format).

[1096] Step 4:

[1097] The server receives and analyzes the emotion data sent from the device to identify the emotion the user is currently feeling. Using an analysis library called EmotionEngine, it extracts specific emotions (e.g., stress, calm, tension) from the emotion data. Input: Emotion data (JSON format). Output: Identified emotion information.

[1098] Step 5:

[1099] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. Using a dedicated tax calculation library, taxable income is calculated by subtracting expenses and deductions from income, and the tax amount is calculated based on that taxable income. Input: Structured data (UserData object). Output: Taxable income and tax amount.

[1100] Step 6:

[1101] The calculated tax amount is sent to the terminal in a standard format (JSON format), and the terminal displays it to the user. The specific tax amount (e.g., "The user's tax amount is 660,000 yen") is displayed on the screen. Input: Taxable income and tax amount. Output: Tax amount displayed (JSON format).

[1102] Step 7:

[1103] The server suggests appropriate tax-saving methods based on user data and emotional data. Taking emotional information into consideration, it suggests simple tax-saving methods if the user is stressed, and more detailed methods if the user is calm. It uses an AI model to make recommendations such as dependent deductions and medical expense deductions. Input: User data, emotional information. Output: Suggested tax-saving methods.

[1104] Step 8:

[1105] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and generates reminders. Taking into account emotional data, if the user is nervous, it will remind them in gentle words, and if they tend to forget, it will remind them more frequently. The reminder content is sent to the device in JSON format. Input: Current date, emotional information. Output: Reminder generation and sending (JSON format).

[1106] In this way, it is possible to provide the user with personalized tax support services throughout each processing step, thereby reducing the burden of tax processing on the user.

[1107] 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.

[1108] 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.

[1109] 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.

[1110] [Fourth embodiment]

[1111] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1112] 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.

[1113] 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).

[1114] 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.

[1115] 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.

[1116] 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).

[1117] 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.

[1118] 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.

[1119] 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.

[1120] 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.

[1121] 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.

[1122] 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.

[1123] 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."

[1124] The present invention is a system that receives data on income, expenses, number of dependents, and deductions from a user, automatically calculates tax amounts, suggests appropriate tax-saving methods, and also reminds users of important tax procedures.

[1125] System Configuration

[1126] This system is mainly composed of a server, a terminal, and a user. Specifically, the system operates as follows:

[1127] Entering and submitting user data

[1128] The user enters their income, expenses, number of dependents, and deductions into an input form on the device. The entered data is sent to the server in JSON format.

[1129] Receiving and storing user data

[1130] The server receives the user data sent from the terminal, parses the received data, and stores it in the server's database as a UserData object.

[1131] Tax calculation

[1132] The server calculates taxable income based on the saved user data. Taxable income is the amount obtained by subtracting expenses and deductions from income. Then, it applies a hypothetical tax rate to this taxable income to calculate the tax amount.

[1133] Displaying calculation results

[1134] The server sends the calculated tax amount to the terminal, and the terminal displays the calculation result to the user. For example, a specific tax amount such as "The user's tax amount is XX yen" is displayed.

[1135] Tax saving suggestions

[1136] The server proposes appropriate tax-saving methods based on user data. Specifically, if the user has one or more dependents, the server suggests "take advantage of the dependent deduction," and if the medical expense deduction is not yet sufficient, the server suggests "consider taking the medical expense deduction." This proposal is sent to the terminal in JSON format, and the terminal displays it to the user.

[1137] Procedural Reminders

[1138] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date. For example, a reminder such as "X days left until year-end tax adjustments" is generated. This reminder information is also sent to the device in JSON format, and the device displays it to the user.

[1139] Specific examples

[1140] For example, if a user inputs "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[1141] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[1142] Tax amount = 3.3 million yen 20% = 660,000 yen

[1143] Next, you'll see suggestions like "Please claim your dependent deductions" and reminders like "30 days left until your tax return."

[1144] As described above, the present invention allows users to easily and accurately calculate tax amounts, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures, thereby reducing the burden of tax processing and preventing penalties and fines.

[1145] The processing flow will be explained below.

[1146] Step 1:

[1147] The user enters their income, expenses, number of dependents, and deductions into the input form on the terminal. The entered data is sent to the server by clicking the send button.

[1148] Step 2:

[1149] The device sends the entered user data in JSON format to the server, including income, expenses, number of dependents, and deductions.

[1150] Step 3:

[1151] The server receives the JSON formatted user data sent from the device and parses it as a UserData object. The parsed data is stored in the database.

[1152] Step 4:

[1153] The server retrieves the stored user data from the database and calculates taxable income based on income, expenses, and deductions. Specifically, taxable income is the amount obtained by subtracting expenses and deductions from income.

[1154] Step 5:

[1155] The server calculates the tax amount by applying a hypothetical tax rate to the calculated taxable income. For example, if the tax rate is assumed to be 20%, the tax amount is calculated by multiplying the taxable income by 0.2.

[1156] Step 6:

[1157] The server sends the calculated tax amount in JSON format to the terminal. The sent data includes the user name and tax amount.

[1158] Step 7:

[1159] The terminal displays the tax amount received from the server to the user. For example, a specific amount such as "The user's tax amount is XX yen" is displayed.

[1160] Step 8:

[1161] The server will suggest tax-saving methods based on user data. For example, if the user has one or more dependents, it will suggest "take advantage of the dependent deduction," and if the medical expense deduction is not applied, it will suggest "consider taking the medical expense deduction."

[1162] Step 9:

[1163] The server sends the proposed tax saving methods in JSON format to the terminal. The sent data includes the proposed methods.

[1164] Step 10:

[1165] The terminal displays the tax saving suggestions received from the server to the user. For example, "Please accept the dependent deduction" or "Please consider the medical expense deduction" may be displayed.

[1166] Step 11:

[1167] The server obtains the current date and calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments. For example, it generates reminders such as "X days left until year-end tax adjustments."

[1168] Step 12:

[1169] The server sends the generated reminder information in JSON format to the device. The sent data includes the reminder content.

[1170] Step 13:

[1171] The device displays the reminder information received from the server to the user. For example, it displays the specific number of days until the end of the year tax adjustment.

[1172] Example 1

[1173] 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."

[1174] Traditional tax processing is complex, requiring a great deal of effort and expertise to accurately calculate tax amounts and individually recommend appropriate tax-saving methods. There is also a risk of forgetting deadlines for important tax procedures. To address these issues, users need a method that allows them to easily and accurately calculate tax amounts, receive appropriate tax-saving suggestions, and remember to complete important tax procedures.

[1175] 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.

[1176] In this invention, the server includes means for receiving information on income, expenses, number of dependents, and deductions from a user, means for transmitting the information in JSON format, means for receiving and storing the information in JSON format, means for calculating taxable income and tax amount based on the information, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the information, means for generating reminders of important procedures, and means for displaying the reminders to the user, thereby enabling the user to easily and accurately calculate tax amount, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures.

[1177] "User" means an individual or corporation that uses the system to enter tax information and receives tax calculations, tax saving suggestions, and tax procedure reminders.

[1178] "Income" refers to the total amount of income earned by a user in a year, and is the amount used as the basis for calculating taxable income.

[1179] "Expenses" refers to necessary expenses and consumption expenditures incurred by the user during the year, and are amounts that can be deducted from taxable income.

[1180] "Number of dependents" refers to the number of spouses, children, and other dependents of the user who qualify for tax deductions.

[1181] "Deductions" are certain legally recognized costs and expenses that can be deducted from income when calculating taxable income.

[1182] The "JSON format" is a lightweight data exchange format for structuring and sending and receiving data, and is an abbreviation for JavaScript Object Notation.

[1183] "Server" is a central computer system that receives, stores, and processes data sent by users and sends calculation results, suggestions, and reminder information to users.

[1184] "Taxable income" is the amount remaining after deducting expenses and deductions from the user's income, and is the amount used to calculate tax.

[1185] "Tax amount" is the amount of tax paid calculated based on taxable income.

[1186] "Tax saving methods" are means or methods for users to legally reduce their tax burden, and include dependent deductions and medical expense deductions.

[1187] "Reminders" are messages or alerts that notify users of important tax procedures or deadlines.

[1188] "Display means" refers to a method for visually presenting calculation results, tax saving suggestions, reminder information, etc. to the user, and includes web pages and application screens.

[1189] This invention is a system that automatically calculates tax amounts, suggests appropriate tax-saving methods, and reminds users of important tax procedures by allowing them to input information on income, expenses, number of dependents, and deductions. This system is composed of multiple elements, including a server, a terminal, and a user.

[1190] System Configuration

[1191] 1. Entering and submitting user data

[1192] Users open a web form on their device and enter their income, expenses, number of dependents, and deductions.

[1193] The device converts the input data into JSON format and sends a POST request to the server, using a standard web browser and HTTP request.

[1194] 2. Receiving and storing user data

[1195] The server receives JSON data from the device using the Python Flask framework, and parses it using the request.get_json() method.

[1196] The parsed data is then converted into a UserData object and saved to a MySQL database using SQLAlchemy.

[1197] 3. Tax calculation

[1198] The server calculates taxable income and tax amount based on the saved user data. Taxable income is the amount obtained by subtracting expenses and deductions from the user's income. The server also calculates the tax amount by applying a hypothetical tax rate.

[1199] 4. Displaying the calculation results

[1200] The server sends the calculated tax amount to the terminal in JSON format. To do this, the jsonify function is used to construct the response.

[1201] The terminal parses the response data and displays the calculation result to the user, for example, "Your tax amount is 660,000 yen."

[1202] 5. Tax saving suggestions

[1203] The server proposes appropriate tax-saving methods based on user data, taking into account the number of dependents and deduction amounts, and determines which methods are effective.

[1204] The server sends the proposal in JSON format to the device, which then displays it to the user. For example, the proposal might be "Please accept dependent deductions" or "Please consider medical expense deductions."

[1205] 6. Procedural Reminders

[1206] The server calculates deadlines for important tax procedures based on the current date and generates reminders, such as "30 days left until tax return."

[1207] This reminder is also sent in JSON format to the device, which then displays the reminder to the user.

[1208] Specific examples

[1209] For example, if a user enters the following data: Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen, the server will perform the following calculations:

[1210] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[1211] Tax amount = 3.3 million yen 20% = 660,000 yen

[1212] Next, you'll see suggestions like "Please claim your dependent deductions" and reminders like "30 days left until your tax return."

[1213] Example prompts for generative AI models

[1214] "Calculate your tax amount based on the following information and suggest ways to save on tax: Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen."

[1215] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1216] Step 1: Enter and submit user data

[1217] The user opens a web form on their device and enters their income, expenses, number of dependents, and deductions. For example, the user enters "Income: 5 million yen," "Expenses: 1.5 million yen," "Number of dependents: 1," and "Deductions: 200,000 yen."

[1218] The terminal converts the input data into JSON format, specifically generating the following JSON object: {"income": 5000000, "expenses": 1500000, "dependents": 1, "deductions": 200000}.

[1219] The terminal sends this to the server as a POST request. The input data is collected on a web form and sent to the server by clicking the submit button.

[1220] Step 2: Receiving and storing user data

[1221] The server uses the Flask framework to receive the JSON data sent from the device. Specifically, it parses the received data using the request.get_json() method.

[1222] The server converts the parsed data into a UserData object, which is instantiated by creating an instance of the UserData class.

[1223] The server saves this object to the MySQL database via SQLAlchemy by executing the db_session.add(user_data) and db_session.commit() methods, which receives the input data, converts it into an object, and saves it to the database.

[1224] Step 3: Calculate taxes

[1225] The server retrieves the stored user data from the database using user_data = db_session.query(UserData).where(UserData.id == user_id).first().

[1226] The server calculates taxable income by subtracting expenses and deductions from the user's income. The specific calculation is taxable_income = user_data.income - user_data.expenses - user_data.deductions.

[1227] The server calculates the tax amount by applying a hypothetical tax rate. For example, this tax rate is set to 20%, and the calculation is tax_amount = taxable_income 0.20. The server calculates taxable income based on the input data and then calculates the tax amount from the result.

[1228] Step 4: Displaying the calculation results

[1229] The server sends the calculated tax amount in JSON format to the terminal. Specifically, it generates response = {"tax_amount": tax_amount} and returns it with return jsonify(response).

[1230] The terminal receives this response data and displays the calculation result to the user. For example, it displays "Your tax amount is 660,000 yen." The calculation result is received in JSON format and is presented visually to the user.

[1231] Step 5: Proposal for tax saving methods

[1232] The server recommends appropriate tax-saving methods based on user data. Specifically, it executes logic such as if user_data.dependents > 0: recommendations.append("Please take dependent deductions")

[1233] The server sends the recommendations in JSON format to the device. Specifically, it generates response = {"recommendations": recommendations} and returns it with return jsonify(response).

[1234] The device will then display the suggestions to the user. For example, it might say, "Accept dependent deductions" or "Consider medical expense deductions." It will then identify tax-saving methods based on user data and notify the user.

[1235] Step 6: Procedural Reminders

[1236] The server calculates deadlines for important tax procedures based on the current date: days_until_deadline = (deadline_date - datetime.now()).days.

[1237] The server generates reminders based on the calculation results and sends them to the device in JSON format. Specifically, it generates response = {"reminders": reminders} and returns it with return jsonify(response).

[1238] The device will display the sent reminder to the user, for example, "30 days left until tax return." By generating and notifying reminders, the device helps users remember important deadlines.

[1239] The above is a description of the specific operation of this system divided into processing steps.

[1240] (Application example 1)

[1241] 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."

[1242] It is time-consuming for users to calculate tax amounts based on their own income and expenditure data and find appropriate tax-saving methods. There is also a risk that they may forget important tax procedures. Conventional systems lack sufficient integration with electronic payment services, making it cumbersome to collect income and expenditure data and calculate tax amounts.

[1243] 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.

[1244] In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, means for generating reminders for important procedures, means for linking with an electronic payment service, and means for automatically importing income and expenditure data and periodically notifying the user of tax amount and tax-saving methods. This allows users to easily check their tax amount, find optimal tax-saving methods, and avoid forgetting deadlines for important tax procedures while using the electronic payment service.

[1245] "Means for receiving data on income, expenses, number of dependents, and deductions from users" refers to a function that allows users to input financial data such as their income, expenses, number of dependents, and deductions, and the system retrieves this data.

[1246] The "means for calculating taxable income and tax amount based on the data" is a function for calculating taxable income based on the received financial data and calculating the tax amount based on that.

[1247] The "means for displaying the tax amount calculated by the calculation means" is a function for displaying the calculated tax amount in a form that can be viewed by the user.

[1248] The "means for proposing tax-saving methods based on the data" is a function for analyzing appropriate tax-saving methods based on the collected financial data and recommending them to the user.

[1249] The "means for generating reminders for important procedures" is a function for managing dates and deadlines for important tax-related procedures and notifying users of them.

[1250] "Means for linking with electronic payment services" refers to a function for synchronizing with the electronic payment application used by the user and collecting and using the payment information.

[1251] "Means for automatically collecting income and expenditure data and periodically notifying users of tax amounts and tax-saving methods" is a function for automatically collecting income and expenditure data from electronic payment services and periodically providing users with information on tax amounts and tax-saving methods.

[1252] The system receives input data on a user's income, expenses, number of dependents, and deductions, automatically calculates tax amounts based on the data, and suggests appropriate tax-saving methods. It also has the function of reminding users of important tax procedures and effectively managing income and expenditure data in conjunction with electronic payment services.

[1253] System Configuration

[1254] The system mainly consists of a server, a terminal, and a user. It is implemented as an application on a smartphone. The server receives, stores, and analyzes user data, while the terminal receives input from the user and displays the results.

[1255] Entering and submitting user data

[1256] Users enter their income, expenses, number of dependents, and deductions through a smartphone app. This data is sent to the server in JSON format. Specifically, the data entered on the mobile device is sent to the server via the Internet.

[1257] Receiving and storing user data

[1258] The server receives the user data sent from the terminal, parses the received data appropriately, and stores it in a database management system (such as an RDBMS).

[1259] Tax calculation

[1260] The server analyzes the stored user data and calculates taxable income. Specifically, it calculates taxable income by subtracting expenses and deductions from income, and then applies a certain tax rate to it to calculate the amount of tax.

[1261] Displaying calculation results

[1262] The calculated tax amount is sent from the server to the terminal and displayed to the user as a specific number, for example, "The user's tax amount is 660,000 yen."

[1263] Tax saving suggestions

[1264] The server then suggests appropriate tax-saving methods based on the analyzed user data. For example, if the user has one or more dependents, it may suggest "take out a dependent deduction." Furthermore, through detailed data analysis, it may also suggest other tax-saving methods, such as medical expense deductions.

[1265] Procedural Reminders

[1266] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and generates reminders. This reminder information is also sent to the device in JSON format and displayed to the user.

[1267] Collaboration with electronic payment services

[1268] The server automatically retrieves income and expenditure data from electronic payment services (for example, mobile payment apps). This ensures that users' income and expenditure information is always up to date, and this latest information is reflected in tax calculations and tax-saving suggestions.

[1269] Cyclic Notification System

[1270] The server periodically notifies users of information about tax amounts and tax-saving methods. The notifications are based on income and expenditure data obtained from the electronic payment service, so users can always keep up to date with the latest information.

[1271] Specific examples

[1272] For example, if a user enters the following data: income: 5 million yen, expenses: 1.5 million yen, number of dependents: 1, deductions: 200,000 yen, the server will operate as follows:

[1273] 1. Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[1274] 2. Tax amount = 3.3 million yen 20% = 660,000 yen

[1275] 3. Suggestions and reminders are provided, such as "Receive your dependent deductions" and "30 days left until you file your tax return."

[1276] Prompt Sentence Examples

[1277] "If my income is 5 million yen, my expenses are 1.5 million yen, I have one dependent, and my deductions are 200,000 yen, please calculate my taxable income and tax amount and suggest appropriate tax-saving methods. Also, please display reminders for filing tax returns and year-end tax adjustments."

[1278] In this way, the present invention is designed to allow users to easily process taxes, and by providing tax calculation, tax saving method suggestions, and reminder functions, it significantly reduces the burden of tax processing.

[1279] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1280] Step 1: Enter and submit user data

[1281] The user enters income, expenses, number of dependents, and deductions through a smartphone app. This data is collected through an input form and converted into JSON format. After the input data is converted into JSON format, it is sent to the server. For example, if a user enters "income: 5 million yen, expenses: 1.5 million yen, number of dependents: 1, deductions: 200,000 yen," it will be sent as JSON format data.

[1282] Step 2: Receiving and storing user data

[1283] The server receives the JSON formatted user data sent from the terminal. After receiving it, the server parses this JSON data and stores it in a database together with the user identification information. The database system used here can be an RDBMS such as SQLite or MySQL.

[1284] Step 3: Calculate taxes

[1285] The server reads the user data stored in the database and calculates the tax amount. This calculation involves calculating taxable income by subtracting expenses and deductions from income. A hypothetical tax rate is then applied to calculate the tax amount. For example, if the taxable income is 3.3 million yen, a tax rate of 20% is applied, resulting in a tax amount of 660,000 yen.

[1286] Step 4: Displaying the calculation results

[1287] After the tax amount is calculated, the result is sent back to the terminal from the server. The terminal displays the received tax amount to the user. For example, a message such as "The tax amount is 660,000 yen" is displayed on the user's smartphone screen.

[1288] Step 5: Proposal for tax saving methods

[1289] The server proposes appropriate tax-saving methods based on user data. Specifically, if there is one or more dependents, a recommendation message is generated such as "Please claim the dependent deduction," or if there is a remaining medical expense deduction, "Please consider claiming the medical expense deduction." This suggestion is sent back to the terminal in JSON format and displayed to the user.

[1290] Step 6: Procedural Reminder

[1291] The server generates reminders for important tax procedures based on the current date. For example, it calculates the deadline for filing tax returns and year-end tax adjustments and generates a reminder such as "30 days left until tax returns are filed." This reminder information is also sent to the device in JSON format and notified to the user.

[1292] Step 7: Integrate with electronic payment services

[1293] The server automatically retrieves income and expenditure data from the electronic payment service and updates it periodically. This means that every time a user makes a purchase or makes a payment, that information is updated in real time in the system. This ensures that the latest data is always used for tax calculations and tax-saving suggestions.

[1294] Step 8: Periodic Notification System

[1295] The server periodically notifies users about their tax amount and tax saving methods based on the collected income and expenditure data. This is to ensure that users always have up-to-date information on important tax matters. For example, a notification may be sent to the user saying, "Your current tax amount is 660,000 yen. Please consider claiming medical expenses as a deduction."

[1296] 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.

[1297] The present invention combines a system that receives data on income, expenses, number of dependents, and deductions from users, automatically calculates tax amounts, suggests appropriate tax-saving methods, and reminds users of important tax procedures with an emotion engine that recognizes users' emotions, providing a more personalized service.

[1298] System Configuration

[1299] This system is mainly composed of a server, a terminal, a user, and an emotion engine. Specifically, the system operates in the following manner.

[1300] Entering and submitting user data

[1301] The user enters their income, expenses, number of dependents, and deductions into an input form on the device. The entered data is sent to the server in JSON format.

[1302] Receiving and storing user data

[1303] The server receives the user data sent from the device and parses it into a UserData object, which is then stored in a database.

[1304] Entering and sending emotional data

[1305] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes emotions from the user's voice, facial expressions, text, etc., and sends the data in JSON format to the server.

[1306] Receiving and analyzing emotion data

[1307] The server receives and analyzes the emotion data sent from the device, and is able to identify the emotion the user is currently feeling.

[1308] Tax calculation

[1309] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. Specifically, taxable income is calculated by subtracting expenses and deductions from income. A hypothetical tax rate is then applied to this taxable income to calculate the tax amount.

[1310] Displaying calculation results

[1311] The server sends the calculated tax amount in JSON format to the terminal, and the terminal displays the calculation result to the user. For example, a specific tax amount such as "The user's tax amount is XX yen" is displayed.

[1312] Tax saving suggestions

[1313] The server suggests appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will suggest easier and less time-consuming tax-saving methods. If the user is calm, it can suggest more detailed tax-saving methods. Specifically, if the user has one or more dependents, it will suggest "please claim the dependent deduction," and if the medical expense deduction is not applied, it will suggest "please consider claiming the medical expense deduction."

[1314] Procedural Reminders

[1315] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date. By taking emotional data into account, the system adjusts the reminder notification method. For example, if the user is nervous, the system will remind them in gentler terms. Also, if the user tends to forget, the system will remind them more frequently.

[1316] Specific examples

[1317] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[1318] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[1319] Tax amount = 3.3 million yen 20% = 660,000 yen

[1320] Next, if the emotion engine analyzes the user's emotion as "stress," it will suggest simple tax-saving measures such as "Please accept your dependent deductions." It will also gently remind the user, based on the emotion data, that "30 days left until your tax return."

[1321] As described above, the present invention enables users to easily and accurately calculate tax amounts, receive suggestions for appropriate tax-saving methods, and receive reminders of important tax procedures. Furthermore, by recognizing the user's emotions using an emotion engine, it is possible to provide more personalized services and reduce the burden of tax processing.

[1322] The processing flow will be explained below.

[1323] Step 1:

[1324] The user enters their income, expenses, number of dependents, and deductions into the input form on the terminal. The entered data is sent to the server by clicking the send button.

[1325] Step 2:

[1326] The device sends the entered user data in JSON format to the server, including income, expenses, number of dependents, and deductions.

[1327] Step 3:

[1328] The server receives the JSON formatted user data sent from the device and parses it as a UserData object. The parsed data is stored in the database.

[1329] Step 4:

[1330] An emotion engine that recognizes the user's emotions is connected to the device and analyzes emotions in real time from the user's voice, facial expressions, text, etc. The analyzed emotion data is sent to the server in JSON format.

[1331] Step 5:

[1332] The server receives the emotion data sent from the device and analyzes it to identify the user's current emotion, for example, identifying emotional states such as "stressed," "calm," or "elated."

[1333] Step 6:

[1334] The server retrieves the stored user data from the database and calculates taxable income based on income, expenses, and deductions. Specifically, taxable income is the amount obtained by subtracting expenses and deductions from income.

[1335] Step 7:

[1336] The server calculates the tax amount by applying a hypothetical tax rate to the calculated taxable income. For example, if the tax rate is assumed to be 20%, the tax amount is calculated by multiplying the taxable income by 0.2.

[1337] Step 8:

[1338] The server sends the calculated tax amount in JSON format to the terminal. The sent data includes the user name, taxable income, and tax amount.

[1339] Step 9:

[1340] The terminal displays the tax amount received from the server to the user. For example, a specific amount such as "The user's tax amount is XX yen" is displayed.

[1341] Step 10:

[1342] The server proposes appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will propose easier and less time-consuming tax-saving methods. If the user is calm, it will propose more detailed tax-saving methods.

[1343] Step 11:

[1344] The server sends the proposed tax saving methods in JSON format to the terminal. The sent data includes the specific tax saving methods and the reasons for them.

[1345] Step 12:

[1346] The terminal displays the tax saving suggestions received from the server to the user. For example, suggestions such as "Accept dependent deductions" or "Consider medical expense deductions" are displayed.

[1347] Step 13:

[1348] The server obtains the current date and calculates deadlines for important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments. By taking emotional data into account, the system adjusts the reminder notification method. For example, if the user is nervous, the system will remind them in calmer language.

[1349] Step 14:

[1350] The server sends the generated reminder information in JSON format to the device. The sent data includes the reminder content and notification method.

[1351] Step 15:

[1352] The device displays the reminder information received from the server to the user. For example, the specific number of days remaining until the end of the year tax adjustment is displayed in calm language.

[1353] Example 2

[1354] 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."

[1355] Conventional tax calculation systems calculate tax amounts based on data such as income, expenses, number of dependents, and deductions, and suggest ways to save on taxes. However, they were unable to provide personalized services that took into account the user's emotional state. As a result, users often felt stressed when completing tax procedures, making it difficult to process taxes efficiently.

[1356] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for converting the data into JSON format and transmitting it, means for receiving and analyzing user data transmitted from a terminal, means for recognizing the user's emotions and generating emotion data, means for analyzing emotions based on the emotion data, means for calculating taxable income and tax amount based on the data and the emotion data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data and the emotion data, and means for generating and notifying reminders of important procedures. This makes it possible to provide personalized tax services that take into account the user's emotional state.

[1357] "User Data" means data, including your tax information, such as your income, expenses, number of dependents, and deductions.

[1358] "JSON format" is an abbreviation for JavaScript Object Notation, and is a format for structuring data in text format.

[1359] A "terminal" is an electronic device that allows a user to input data and communicate with a server.

[1360] A "server" is a computer system that receives data sent from a terminal and performs various processes such as analysis, storage, and notification.

[1361] An "emotion engine" is software or hardware that analyzes emotions from a user's voice, facial expressions, text, etc., and generates emotion data.

[1362] "Emotion data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[1363] "Taxable income" is the amount of income remaining after deducting expenses and deductions, and is the basis for calculating tax.

[1364] "Tax amount" means the amount of tax payable calculated based on taxable income.

[1365] A "tax saving method" is a method for legally reducing the amount of tax you pay.

[1366] "Reminder" is a function that notifies users of deadlines and deadlines for important procedures.

[1367] "Personalized service" refers to the provision of customized services based on the user's specific data and emotional state.

[1368] A "notification" is a message or alert that conveys information to a user.

[1369] The present invention is a system that improves the convenience for users when calculating tax amounts and receiving suggestions for tax-saving methods, and specific embodiments are described below.

[1370] This system mainly consists of a server, a terminal, a user, and an emotion engine.

[1371] Entering and submitting user data

[1372] The user enters their income, expenses, number of dependents, and deductions into an input form on their device. The device receives this data and converts it into JSON format. After this conversion, the device sends the JSON data to the server. The device can be a regular computer, smartphone, or tablet.

[1373] Receiving and storing user data

[1374] The server has an API endpoint for receiving JSON-formatted data sent from the device. The server receives this data and parses it as a UserData object. The parsed data is stored in a database. For the database, a relational database management system such as MySQL or PostgreSQL is used.

[1375] Entering and sending emotional data

[1376] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes data such as the user's voice, facial expressions, and text, and converts the results into JSON format. Specific emotion engines that can be used include Affectiva's SDK and IBM Watson. This emotion data is also sent from the device to the server.

[1377] Receiving and analyzing emotion data

[1378] The server analyzes the emotion data sent from the device. This analysis identifies the emotion the user is currently feeling. The analysis results of the emotion engine are expressed as a state such as "stress" or "calm."

[1379] Tax calculation

[1380] The server calculates taxable income based on user data stored in the database. It subtracts expenses and deductions from income and then applies a hypothetical tax rate to calculate the tax amount. For example, if income is 5 million yen, expenses are 1.5 million yen, and deductions are 200,000 yen, taxable income is 3.3 million yen, and if a tax rate of 20% is applied, the tax amount is 660,000 yen.

[1381] Displaying calculation results

[1382] The server converts the calculated tax amount into JSON format and sends it to the terminal. The terminal then displays the received tax amount data to the user. A specific example of how it is displayed is a notification such as "Your tax amount is 660,000 yen."

[1383] Tax saving suggestions

[1384] The server suggests appropriate tax-saving methods based on user data and emotional data. If the user's emotion is analyzed as "stressed," the server will suggest simple tax-saving methods such as "take dependent deductions." On the other hand, if the user is calm, the server can also make more detailed suggestions such as "consider taking medical expense deductions."

[1385] Procedural Reminders

[1386] The server uses the current date to calculate deadlines for important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments. It also adjusts reminder notification methods based on emotional data. For example, if a user is nervous, it will send reminders in calming language, and if they tend to forget, it will send more frequent reminders.

[1387] Specific examples

[1388] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[1389] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[1390] Tax amount = 3.3 million yen 20% = 660,000 yen

[1391] If the emotion engine analyzes the emotion as "stress," it will suggest "Please accept your dependent deductions" and provide a gentle reminder that "30 days left until you file your tax return."

[1392] As described above, this invention provides a system that allows users to efficiently calculate tax amounts and receive suggestions for tax-saving methods without feeling stressed. By taking the user's emotions into consideration using an emotion engine, it is possible to realize more personalized services.

[1393] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1394] Step 1: Enter and submit user data

[1395] The user enters income, expenses, number of dependents, and deductions into an input form on the device. The device acquires this data and converts it into JSON format. The input data (input: "income: 5 million yen", "expense: 1.5 million yen", "number of dependents: 1", "deductions: 200,000 yen") is converted to JSON format (output: {"income": 5000000, "expense": 1500000, "dependents": 1, "deductions": 200000}). After conversion, the device sends this JSON data to the server. Specifically, the user enters the data using a web browser or a dedicated app, and JavaScript on the device converts it into JSON format and sends it via an HTTP POST request.

[1396] Step 2: Receiving and storing user data

[1397] The server receives JSON-formatted user data sent from the terminal via an HTTP POST request (input). The server parses the received data into a UserData object (data processing) and stores it in a database (output). Specifically, the server uses a web framework (e.g., Flask) to set up an endpoint to receive the POST request and reads the JSON-formatted data from the request body. Next, it connects to a database system (e.g., MySQL) and stores the parsed data.

[1398] Step 3: Enter and submit emotion data

[1399] The user's emotions are recognized by an emotion engine connected to the device (input). The emotion engine analyzes the user's voice, facial expressions, and text data (data calculation) and converts the results into JSON format (output). An example of the converted emotion data is {"emotion": "stress"}. In concrete terms, the user sends facial expressions and voice data to the emotion engine via the camera or microphone, and the emotion engine (for example, Affectiva's SDK) analyzes this and generates emotion data. The generated emotion data is then sent from the device to the server via an HTTP POST request.

[1400] Step 4: Receiving and analyzing emotion data

[1401] The server receives emotion data sent from the device via an HTTP POST request (input). The server analyzes the received emotion data (data calculation) and identifies the user's emotional state (output: identified as "stressed"). Specifically, the server uses a web framework (e.g., Flask) to set up an endpoint to receive emotion data and reads the JSON-formatted emotion data from the request body. It then performs specific processing based on the analysis results.

[1402] Step 5: Calculate taxes

[1403] The server calculates taxable income based on user data stored in the database (input). It subtracts expenses and deductions from income (data calculation) and calculates the tax amount by applying a hypothetical tax rate (output). As a specific calculation example, if income is 5 million yen, expenses are 1.5 million yen, and deductions are 200,000 yen, taxable income is 3.3 million yen. If a hypothetical tax rate of 20% is applied, the tax amount will be 660,000 yen. In concrete terms, the server retrieves user data from the database and calculates the tax amount using a function.

[1404] Step 6: Displaying the calculation results

[1405] The server converts the calculated tax amount into JSON format (output: {"tax_amount": 660000}) and sends it to the terminal (input). The terminal displays the received tax amount data to the user (output: "Your tax amount is 660,000 yen"). Specifically, the server converts the tax amount data into JSON format and returns it as an HTTP response to a request from the terminal. The terminal uses the received data to display it on the screen.

[1406] Step 7: Tax saving suggestions

[1407] The server proposes appropriate tax-saving methods based on user data and emotional data (input). If the user's emotional state is analyzed as "stressed," it proposes simple tax-saving methods such as "consider applying for dependent deductions" (output). Specifically, the server analyzes the user's emotional data and tax data, selects appropriate tax-saving methods, and notifies the user of the results.

[1408] Step 8: Procedural Reminders

[1409] The server uses the current date to remind users of important procedures such as filing tax returns, paying resident taxes, and year-end tax adjustments (input). The server adjusts the reminder notification method based on emotional data (output). Specifically, if the user is nervous, the server will notify them in calm language, and if they tend to forget, it will set up frequent reminders. The server adjusts the content of the reminder appropriately and notifies the user via their device.

[1410] (Application example 2)

[1411] 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."

[1412] In today's world, tax procedures and tax calculations are complicated, causing stress and burden to many users. Furthermore, there are few systems that provide personalized support and reminders to individual users, and the lack of emotional support is particularly problematic. When users are anxious or stressed, systems often fail to efficiently suggest or provide reminders for appropriate tax-saving methods.

[1413] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving data on income, expenses, number of dependents, and deductions from a user, means for calculating taxable income and tax amount based on the data, means for displaying the tax amount calculated by the calculation means, means for suggesting tax-saving methods based on the data, means for generating reminders for important procedures, means for recognizing the user's emotional data using an emotion engine, and means for analyzing the emotional data and providing personalized services. This allows the user to easily and accurately calculate tax amounts, and by providing appropriate tax-saving method suggestions and reminders based on emotions, the burden of tax processing is reduced and more personalized services can be received.

[1414] "Income" refers to the total amount of money a user receives over a certain period of time, including salary, bonuses, business income, etc.

[1415] "Expenses" refers to the amount of money a user spends over a certain period of time, including living expenses, taxes, loan repayments, etc.

[1416] "Number of dependents" refers to the number of family members or relatives supported by the user.

[1417] "Deductions" are amounts that can be deducted from taxable income, including various statutory deductions.

[1418] "Taxable income" is income after deducting expenses and deductions, and is the base amount used to calculate taxes.

[1419] "Tax amount" is the amount of tax calculated based on taxable income.

[1420] A "tax saving method" is a method of legally reducing tax liability, including applying for deductions and making certain investments.

[1421] "Reminder" is a notification function that notifies users of important procedures and deadlines.

[1422] An "emotion engine" is a technology that analyzes a user's voice, facial expressions, text, etc. to recognize their current emotional state.

[1423] "Data submission" is the process of sending collected data to a server, often in JSON format.

[1424] The "JSON format" is a standard format for expressing data in text format and is widely used for data exchange.

[1425] A "personalized service" is a service that provides specific responses tailored based on a user's individual data and emotions.

[1426] System Configuration

[1427] The present invention is implemented by a system including a user, a server, a terminal, and an emotion engine. This system operates in the following manner.

[1428] Entering and submitting user data

[1429] The user launches the application on their device and enters their income, expenses, number of dependents, and deductions. The entered data is sent to the server in a standard format (JSON).

[1430] Receiving and storing user data

[1431] The server receives the user data sent from the terminal and parses it as a UserData object. The parsed data is stored in a database. This process uses a dedicated server as hardware and a database management system (DBMS) and parsing library as software.

[1432] Entering and sending emotional data

[1433] The user's emotions are recognized by an emotion engine connected to the device. The emotion engine analyzes emotions from the user's voice, facial expressions, text, etc., and sends the data in a standard format (JSON) to the server. The software used is a voice and facial expression analysis library and a text analysis tool.

[1434] Receiving and analyzing emotion data

[1435] The server receives and analyzes the emotion data sent from the device to identify the emotion the user is currently feeling. Based on these results, personalized services are provided. As a specific example, EmotionEngine is used as a voice and facial expression analysis library, and an AI model is used as a text analysis tool.

[1436] Tax calculation

[1437] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. The server then calculates the amount of tax based on this taxable income. The software used is a dedicated tax calculation library.

[1438] Displaying calculation results

[1439] The calculated tax amount is sent to the terminal in a standard format (JSON format), and the terminal displays it to the user. An example of the display would be a specific amount such as "The user's tax amount is 660,000 yen."

[1440] Tax saving suggestions

[1441] The server proposes appropriate tax-saving methods based on user data and emotional data. For example, if the user is feeling stressed, it will propose simple tax-saving methods, and if the user is calm, it will propose detailed tax-saving methods. This is done using a tax-related database and a recommendation algorithm using an AI model.

[1442] Procedural Reminders

[1443] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and sends reminders to the user. It adjusts the notification method based on emotional data, providing reminders that correspond to the user's mental state.

[1444] Examples and prompts

[1445] For example, if a user enters "Income: 5 million yen, Expenses: 1.5 million yen, Number of dependents: 1, Deductions: 200,000 yen", the server will perform the following calculation:

[1446] Taxable income = 5 million yen - 1.5 million yen - 200,000 yen = 3.3 million yen

[1447] Tax amount = 3.3 million yen 20% = 660,000 yen

[1448] Next, if the emotion engine analyzes the user's emotion as "stress," it suggests simple tax-saving methods such as "Please accept your dependent deductions" and gently reminds the user that "there are 30 days left until your tax return is due."

[1449] An example prompt is:

[1450] Simply enter the user's income (e.g., 5 million yen), expenses (e.g., 1.5 million yen), number of dependents (e.g., 1 person), and deductions (e.g., 200,000 yen). The app then analyzes the user's emotions from voice, facial expressions, and text, calculates the amount of tax, suggests appropriate tax-saving methods, and reminds users of the dates for required tax procedures.

[1451] In this way, the present invention provides a personalized tax support service based on the user's feelings, thereby reducing the burden on the user.

[1452] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1453] Step 1:

[1454] The user launches the application on their device and enters their income, expenses, number of dependents, and deductions. By filling in the data in the input form and pressing the data submission button, the collected data is sent to the server in a standard format (JSON format). Input: Income, expenses, number of dependents, deductions. Output: Collected data (JSON format).

[1455] Step 2:

[1456] The server receives user data sent from the device and parses it as a UserData object. Using a dedicated parsing library, it parses JSON format data and saves it in the database as structured data. Input: Collected data (JSON format). Output: Structured data (UserData object).

[1457] Step 3:

[1458] To collect user emotion data, an emotion engine connected to the device analyzes voice, facial expressions, text, etc. Using the device's camera and microphone, an emotion analysis library is used to recognize the user's emotions, and the data is sent to the server in a standard format (JSON format). Input: voice, facial expressions, text. Output: emotion data (JSON format).

[1459] Step 4:

[1460] The server receives and analyzes the emotion data sent from the device to identify the emotion the user is currently feeling. Using an analysis library called EmotionEngine, it extracts specific emotions (e.g., stress, calm, tension) from the emotion data. Input: Emotion data (JSON format). Output: Identified emotion information.

[1461] Step 5:

[1462] The server calculates taxable income based on the saved user data, including income, expenses, and deductions. Using a dedicated tax calculation library, taxable income is calculated by subtracting expenses and deductions from income, and the tax amount is calculated based on that taxable income. Input: Structured data (UserData object). Output: Taxable income and tax amount.

[1463] Step 6:

[1464] The calculated tax amount is sent to the terminal in a standard format (JSON format), and the terminal displays it to the user. The specific tax amount (e.g., "The user's tax amount is 660,000 yen") is displayed on the screen. Input: Taxable income and tax amount. Output: Tax amount displayed (JSON format).

[1465] Step 7:

[1466] The server suggests appropriate tax-saving methods based on user data and emotional data. Taking emotional information into consideration, it suggests simple tax-saving methods if the user is stressed, and more detailed methods if the user is calm. It uses an AI model to make recommendations such as dependent deductions and medical expense deductions. Input: User data, emotional information. Output: Suggested tax-saving methods.

[1467] Step 8:

[1468] The server calculates deadlines for important procedures such as tax returns, resident tax payments, and year-end tax adjustments based on the current date, and generates reminders. Taking into account emotional data, if the user is nervous, it will remind them in gentle words, and if they tend to forget, it will remind them more frequently. The reminder content is sent to the device in JSON format. Input: Current date, emotional information. Output: Reminder generation and sending (JSON format).

[1469] In this way, it is possible to provide the user with personalized tax support services throughout each processing step, thereby reducing the burden of tax processing on the user.

[1470] 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.

[1471] 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.

[1472] 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.

[1473] 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.

[1474] 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.

[1475] 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.

[1476] 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).

[1477] 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.

[1478] 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."

[1479] 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.

[1480] 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).

[1481] 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.

[1482] 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.

[1483] 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.

[1484] 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.

[1485] 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.

[1486] 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.

[1487] 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.

[1488] 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.

[1489] 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.

[1490] 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.

[1491] The following is further disclosed regarding the above embodiment.

[1492] (Claim 1)

[1493] a means for receiving income, expenses, number of dependents, and deductions data from a user;

[1494] means for calculating taxable income and tax amount based on said data;

[1495] means for displaying the tax amount calculated by the calculation means;

[1496] A means for proposing tax saving methods based on the data;

[1497] A system that includes a means for generating reminders of important procedures.

[1498] (Claim 2)

[1499] The system according to claim 1, further comprising means for transmitting the data on income, expenses, number of dependents, and deductions in JSON format.

[1500] (Claim 3)

[1501] 2. The system of claim 1, wherein the suggested tax savings methods include dependent deductions and medical expense deductions.

[1502] "Example 1"

[1503] (Claim 1)

[1504] a means for receiving information on income, expenses, number of dependents, and deductions from a user;

[1505] means for transmitting said information in JSON format;

[1506] means for receiving and storing the JSON formatted information;

[1507] means for calculating taxable income and tax amount based on said information;

[1508] means for displaying the tax amount calculated by the calculation means;

[1509] A means for proposing tax saving methods based on the information;

[1510] A system that includes a means for generating reminders of important procedures.

[1511] (Claim 2)

[1512] The system of claim 1, wherein the tax saving methods include dependent deductions and medical expense deductions.

[1513] (Claim 3)

[1514] 10. The system of claim 1, further comprising: means for displaying the reminder to a user.

[1515] "Application Example 1"

[1516] (Claim 1)

[1517] a means for receiving income, expenses, number of dependents, and deductions data from a user;

[1518] means for calculating taxable income and tax amount based on said data;

[1519] means for displaying the tax amount calculated by the calculation means;

[1520] A means for proposing tax saving methods based on the data;

[1521] a means of generating reminders of important procedures;

[1522] A means of linking with electronic payment services;

[1523] A means to automatically import income and expenditure data and periodically notify tax amounts and tax-saving methods,

[1524] A system including:

[1525] (Claim 2)

[1526] The system according to claim 1, further comprising means for transmitting the data on income, expenses, number of dependents, and deductions in JSON format.

[1527] (Claim 3)

[1528] 2. The system of claim 1, wherein the suggested tax savings methods include dependent deductions and medical expense deductions.

[1529] "Example 2: Combining Emotion Engines"

[1530] (Claim 1)

[1531] a means for receiving income, expenses, number of dependents, and deductions data from a user;

[1532] means for converting the data into a JSON format and transmitting the converted data;

[1533] means for receiving and analyzing user data transmitted from the terminal;

[1534] means for recognizing a user's emotion and generating emotion data;

[1535] means for analyzing emotions based on the emotion data;

[1536] means for calculating taxable income and tax amount based on said data and said emotion data;

[1537] means for displaying the tax amount calculated by the calculation means;

[1538] means for proposing tax-saving methods based on the data and the emotion data;

[1539] A system that includes a means to generate and notify reminders of important procedures.

[1540] (Claim 2)

[1541] 10. The system of claim 1, wherein the emotion data is analyzed from a user's voice, facial expression, and text.

[1542] (Claim 3)

[1543] The system of claim 1 , wherein the suggested tax saving methods include different content depending on the user's emotional state.

[1544] "Application example 2 when combining emotion engines"

[1545] (Claim 1)

[1546] a means for receiving income, expenses, number of dependents, and deductions data from a user;

[1547] means for calculating taxable income and tax amount based on said data;

[1548] means for displaying the tax amount calculated by the calculation means;

[1549] A means for proposing tax saving methods based on the data;

[1550] a means of generating reminders of important procedures;

[1551] means for recognizing user emotion data by an emotion engine;

[1552] A system including means for analyzing emotion data and providing personalized services.

[1553] (Claim 2)

[1554] 2. The system according to claim 1, further comprising: means for transmitting the data on income, expenses, number of dependents, and deductions in JSON format; and means for transmitting the emotion data in JSON format.

[1555] (Claim 3)

[1556] The system according to claim 1, wherein the suggested tax saving methods include dependent deductions and medical expense deductions, and further comprising means for suggesting appropriate tax saving methods based on emotion data. [Explanation of symbols]

[1557] 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 receiving income, expenses, number of dependents, and deductions data from a user; means for calculating taxable income and tax amount based on said data; means for displaying the tax amount calculated by the calculation means; A means for proposing tax saving methods based on the data; and a means for generating reminders of important procedures.

2. The system according to claim 1 , further comprising means for transmitting the data on income, expenses, number of dependents, and deductions in JSON format.

3. The system of claim 1 , wherein the suggested tax savings methods include dependent deductions and medical expense deductions.

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