System

Abstract

A system is provided.SOLUTION: This system includes a means for acquiring income and expenditure data, a means for analyzing the acquired income and expenditure data, a means for generating an optimum tax saving plan on the basis of the analyzed income and expenditure data, a means for simulating the tax saving effect of the generated tax saving plan, and a means for supporting an application procedure necessary for the tax saving plan.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With the upcoming rise in prices and the cost of living, it is becoming increasingly important for individuals to find tax-saving strategies that suit them. However, finding the optimal tax-saving method based on income, expenditure, family structure, etc. requires specialized knowledge, and the application procedures are complicated. For this reason, it is difficult for ordinary individuals to implement effective and efficient tax-saving strategies, requiring a great deal of effort and time. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides a system including a means for acquiring income and expenditure data, a means for analyzing the acquired income and expenditure data, a means for generating an optimal tax saving plan based on the analyzed income and expenditure data, a means for simulating the tax saving effects of the generated tax saving plan, and a means for supporting the application procedures required for the tax saving plan. This system enables individuals to easily and accurately find a tax saving plan that suits them and efficiently complete the application procedures. The system also includes a learning means for reflecting the latest tax information and a means for periodically updating the profile and reevaluating the tax saving plan. Furthermore, by including a means for acquiring income and expenditure data using OCR technology, data acquisition can be performed more quickly and accurately.

[0006] "Income and Expenditure Data" means detailed information about the income and expenses of an individual or entity.

[0007] "Acquisition Means" refers to the technological methods or devices for collecting or receiving Income and Expenditure Data.

[0008] "Analytical tools" refers to processes or techniques for classifying, organizing, and evaluating income and expenditure data.

[0009] A "tax saving plan" is a plan that suggests optimal ways to save on taxes based on income and expenditure data.

[0010] "Generative means" refers to techniques and devices that create new information or plans based on relevant data.

[0011] "Simulation means" refers to technology that virtually calculates and evaluates the effectiveness of the generated tax saving plan.

[0012] "Application procedure support means" refers to technology or devices that assist in the preparation and submission of application documents required to apply for a tax-saving plan.

[0013] "Tax Information" means current information on tax laws, regulations, and procedures.

[0014] "Learning tools" refer to the technology that continuously incorporates the latest tax information and updates the system's knowledge base.

[0015] "Profile" refers to a data set containing basic information and historical financial data about an individual user.

[0016] "Reevaluation tools" refer to techniques that reevaluate the applicability of existing tax-saving plans based on updated income and expenditure data and tax information.

[0017] "OCR technology" refers to technology that uses optical character recognition technology to extract character data from scanned documents or images. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing data, means for generating tax-saving plans, means for simulation, and means for supporting application procedures. This system is designed to enable users to easily find and efficiently implement tax-saving strategies that are optimal for them.

[0040] System configuration

[0041] The system consists of a user's terminal, a server, and related databases. The user uses the terminal to input or scan income and expenditure data, which is then sent to the server. The server analyzes the income and expenditure data, generates and simulates tax-saving plans, and sends the information back to the terminal. It also generates the documents necessary for application procedures, helping the user to complete the procedures efficiently.

[0042] Acquisition of income and expenditure data

[0043] 1. Data Entry / Scanning:

[0044] Users manually enter income and expense information into the device or scan paper documents or electronic files, such as pay slips or household receipts.

[0045] The terminal uses OCR technology to convert the scanned data into text data, and obtains the income and expenditure data in digital format.

[0046] Sending and analyzing income and expenditure data

[0047] 2. Data transmission:

[0048] The terminal transmits the acquired balance data to the server using a secure communication protocol.

[0049] 3. Data Analysis:

[0050] The server analyzes the received income and expenditure data and categorizes it into categories such as income, expenditure, expenses, medical expenses, education expenses, etc. This allows the user's income and expenditure situation to be understood in detail.

[0051] Tax saving plan generation and simulation

[0052] 4. Generate tax saving plans:

[0053] The server generates an optimal tax-saving plan based on the user's income and expenditure data, taking into account the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, and mortgage deductions.

[0054] 5. Simulation:

[0055] The server simulates the tax savings effect of each tax saving plan and presents it to the user. The simulation results include predicted tax reductions and comparative information based on the plan selected by the user.

[0056] Support for application procedures

[0057] 6. Document generation and submission:

[0058] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal, where the user can download and print these documents and complete the necessary procedures.

[0059] Ongoing support

[0060] 7. Periodic Data Updates and Plan Reassessment:

[0061] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. By re-proposing the optimal tax saving plan based on new data and changes in the tax system, the user can always implement tax saving measures that are adapted to the latest tax system.

[0062] Specific examples

[0063] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0064] 1. The user enters or scans their pay stub and expense information into the terminal.

[0065] 2. The terminal sends the balance data to the server.

[0066] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0067] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0068] 5. The device will display the best tax saving plan for the user and its effects.

[0069] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the terminal.

[0070] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[0071] This system allows users to automatically and efficiently take the best possible tax-saving measures.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] The user collects income and expense data and manually enters it into the terminal or scans it.

[0075] Step 2:

[0076] The device uses OCR technology to convert scanned documents into text data, obtaining income and expenditure data in digital format.

[0077] Step 3:

[0078] The terminal transmits the collected data to the server using a secure communication protocol.

[0079] Step 4:

[0080] The server analyzes the received income and expenditure data and automatically classifies it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[0081] Step 5:

[0082] The server checks the data for inconsistencies and cleanses it as needed, including removing duplicate data and standardizing formats.

[0083] Step 6:

[0084] The server learns the latest tax information and generates the optimal tax-saving plan based on that information. For example, it suggests plans that include medical expense deductions and donation deductions.

[0085] Step 7:

[0086] The server simulates the tax savings effect of each tax saving plan and calculates the expected tax reduction.

[0087] Step 8:

[0088] The server sends the simulation results along with the optimal tax saving plan to the terminal.

[0089] Step 9:

[0090] The device graphically displays details of tax-saving plans and their effects to users, allowing them to intuitively understand the comparison of each plan.

[0091] Step 10:

[0092] The user selects the desired tax saving plan.

[0093] Step 11:

[0094] The server automatically generates the necessary application documents based on the selected tax saving plan, and also lists the necessary attachments.

[0095] Step 12:

[0096] The server sends the generated application documents to the terminal.

[0097] Step 13:

[0098] The terminal presents the application documents to the user and instructs them to download and print them.

[0099] Step 14:

[0100] The user downloads the generated documents and follows the instructions to complete the application process.

[0101] Step 15:

[0102] The server periodically updates income and expenditure data and incorporates new data to support ongoing tax-saving measures.

[0103] Step 16:

[0104] The server reevaluates the tax saving plan based on new income and expenditure data and changes in tax systems, and proposes a new plan to the user as necessary.

[0105] In this way, users can efficiently manage their income and expenditure data and easily take optimal tax-saving measures.

[0106] Example 1

[0107] 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."

[0108] The present invention relates to a system that supports individuals or corporations in efficiently implementing tax-saving measures. Conventional tax-saving measures are complex, requiring the management of numerous documents and an understanding of the tax system, making it difficult for individual users to find the optimal tax-saving plan. Furthermore, it is difficult to obtain a plan that constantly reflects the latest tax system information, resulting in ineffective tax savings. This has led to the problem that many users end up making wasteful expenditures and failing to implement appropriate tax-saving measures.

[0109] 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.

[0110] In this invention, the server includes means for acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting application procedures required for the tax saving plan, means for converting the income and expenditure data into text data using OCR technology, means for transmitting the income and expenditure data to the server using a secure communication protocol, means for learning the latest tax information using a generative AI model and generating a tax saving plan, means for periodically updating the income and expenditure data and reevaluating the tax saving plan, and means for presenting the simulation results to the user. This allows users to easily input income and expenditure data and efficiently obtain an optimal tax saving plan based on the latest tax information.

[0111] "Income and Expenditure Data" means information relating to income and expenditures that indicates the financial position of an individual or entity.

[0112] "Capture means" refers to the functionality of a device or software for inputting or scanning and collecting financial data from a user.

[0113] "Analysis means" refers to the function of a device or software that categorizes and performs statistical analysis based on the acquired income and expenditure data.

[0114] A "tax saving plan" refers to a specific plan that suggests ways and strategies to reduce tax based on the user's income and expenditure data.

[0115] "Simulation means" refers to the functionality of a device or software that predicts the effects of a generated tax saving plan and calculates the specific tax savings and benefits.

[0116] "Means to support application procedures" refers to auxiliary functions that allow users to prepare the necessary documents and carry out application procedures efficiently.

[0117] "OCR technology" refers to optical character recognition technology, which extracts text data from scanned images.

[0118] "Secure communication protocol" refers to a communication protocol that ensures security when sending and receiving data, and includes, for example, HTTPS.

[0119] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and operate for a specific purpose (in this case, learning tax information or generating tax-saving plans).

[0120] "Latest tax information" refers to the latest tax rules and information, including tax laws and deduction provisions in effect at the time.

[0121] "Database" refers to a collection of collected and stored data that allows the system to efficiently manage and use the information it needs.

[0122] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing data, means for generating tax-saving plans, means for simulation, and means for supporting application procedures. This system is designed to enable individuals or corporations to efficiently find and implement optimal tax-saving strategies. Each means will be specifically described below.

[0123] How to obtain income and expenditure data

[0124] Users enter or scan financial data using their device. For example, they can take a photo of a pay slip, receipt, or other financial document with their smartphone camera and import it into the app. The device then converts this data into text using OCR (optical character recognition) technology. Software such as Tesseract OCR can be used to extract text from the scanned image.

[0125] Data transmission method

[0126] The terminal transmits the acquired and converted balance data to the server via a secure communication protocol (e.g., HTTPS), which prevents data leakage and unauthorized access.

[0127] Data analysis methods

[0128] The server analyzes the received data, for example, by using the Python Pandas library to classify the data into different categories (income, expenditure, expenses, medical expenses, education expenses, etc.) to obtain a detailed understanding of the user's financial situation. The results of this analysis are then used to generate a tax saving plan.

[0129] Tax saving plan generation tool

[0130] The server uses the generative AI model to learn the latest tax information and update the database. This allows the server to generate optimal tax-saving plans based on the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, and mortgage deductions.

[0131] Simulation Method

[0132] The server simulates the tax savings effect of the generated tax saving plans. Using Python's NumPy library, it calculates the predicted tax reduction effect of each plan and presents it to the user. The simulation results include the effects and benefits of each plan.

[0133] Support for application procedures

[0134] The server automatically generates the application documents required for the tax-saving plan selected by the user and sends them to the terminal. The application documents are created in PDF format using the PyPDF2 library, etc. The user downloads and prints these documents and follows the instructions to complete the application process.

[0135] Ongoing support measures

[0136] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan based on the latest tax information, thereby always providing the optimal tax saving strategy.

[0137] Specific examples

[0138] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0139] 1. The user enters or scans their pay stub and expense information into the device, for example, by taking a photo of their pay stub using their smartphone camera and scanning it into the app.

[0140] 2. The device uses OCR technology to convert the scanned data into text data and sends that data to the server.

[0141] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0142] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0143] 5. The device will display the best tax saving plan for the user and its effects.

[0144] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the terminal.

[0145] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[0146] Prompt Sentence Examples

[0147] "Please enter or scan the data from your monthly pay slip and household ledger according to the following headings: income, expenditures, expenses, medical expenses, and education expenses."

[0148] This system allows users to automatically and efficiently take the best tax-saving measures.

[0149] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0150] Step 1:

[0151] Data Entry / Scanning

[0152] The user manually enters income and expense information into the device, or scans a paper document or electronic file. For example, they take a picture of a pay slip or receipt with their smartphone camera and scan it into the app. The input data includes income amount, expense amount, and expense category. The device then converts the scanned data into text data using OCR technology. For example, Tesseract OCR can be used to extract text from an image of a pay slip. This text data is then passed to the next processing step.

[0153] Step 2:

[0154] Data transmission

[0155] The terminal sends the acquired and converted balance data to the server using a secure communication protocol (e.g., HTTPS). The input data includes the text data obtained in step 1. Using a secure communication protocol prevents data leakage and unauthorized access. The balance data is securely passed to the server through this communication.

[0156] Step 3:

[0157] Data analysis

[0158] The server analyzes the received income and expenditure data. The input data includes the transmitted income and expenditure data (income, expenditure, expense items, etc.). Using Python's Pandas library, the data is classified into categories such as income, expenditure, expenses, medical expenses, and education expenses. For example, data such as "Salary: 300,000 yen," "Rent: 80,000 yen," and "Medical expenses: 10,000 yen" are classified into the appropriate categories. The classification results are passed to the next step.

[0159] Step 4:

[0160] Generate tax saving plans

[0161] The server uses the generative AI model to learn the latest tax information and update the database. The input data includes the analysis data obtained in step 3 and the latest tax information. Based on this, the optimal tax saving plan is generated. For example, the applicability of medical expense deductions, donation deductions, mortgage deductions, etc. is evaluated and each plan is generated. The generated results are passed to the next step.

[0162] Step 5:

[0163] simulation

[0164] The server simulates the tax savings effect of each tax saving plan generated. The input data includes each tax saving plan generated in step 4. Using Python's NumPy library, the tax reduction effect of each plan is calculated and presented to the user. For example, the simulation result obtained is "medical expense deductions can save 50,000 yen per year in taxes." This result is passed to the next step.

[0165] Step 6:

[0166] Support for application procedures

[0167] The server automatically generates the application documents required for the tax saving plan selected by the user and sends them to the terminal. The input data includes the simulation results from step 5 and the selected tax saving plan. The server uses the PyPDF2 library to create the application documents in PDF format. For example, it creates "Medical Expense Deduction Application Form.pdf" and sends it to the terminal. The user downloads this document, prints it, fills in the necessary information, and proceeds with the application procedure.

[0168] Step 7:

[0169] Ongoing support

[0170] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan based on new data and changes in the tax system. The input data includes the latest income and expenditure data and the latest tax system information. Based on this, a new tax saving plan is proposed. For example, new analysis results such as "new medical expense deductions are applicable" are provided.

[0171] (Application example 1)

[0172] 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."

[0173] Conventional tax saving systems require users to manually input income and expenditure data, select a tax saving plan, and complete the necessary application procedures, which is time-consuming and labor-intensive. Furthermore, there is no system that collects and analyzes electronic payment data in real time and proposes optimal tax saving plans. This makes it difficult for users to efficiently implement tax saving measures and find the appropriate plan.

[0174] 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.

[0175] In this invention, the server includes means for acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting the application procedures required for the tax saving plan, means for collecting and analyzing electronic payment data in real time, means for categorizing the collected data, means for notifying the user of the tax saving plan, and means for supporting the application procedures with a reminder function. This enables the user to automatically and efficiently find the optimal tax saving plan and smoothly complete the application procedures.

[0176] "Means for obtaining income and expenditure data" refers to means for collecting data on income and expenditure from users.

[0177] The "means for analyzing the acquired income and expenditure data" is a means for analyzing the collected income and expenditure data and classifying it by category.

[0178] The "means for generating an optimal tax saving plan" is a means for proposing the most effective tax saving measures for the user based on analyzed income and expenditure data.

[0179] The "means for simulating the tax saving effect of a tax saving plan" is a means for predicting the effect of the generated tax saving plan and presenting the results to the user.

[0180] "Means to support application procedures" refers to means to automatically generate the necessary application documents based on the tax saving plan selected by the user and to assist with the procedures.

[0181] "Means for collecting and analyzing electronic payment data in real time" refers to means for automatically obtaining data from a user's electronic payment service and analyzing it immediately.

[0182] The "means for categorizing collected data" is a means for classifying collected income and expenditure data into categories such as income, expenditure, medical expenses, and education expenses.

[0183] The "means for notifying the user of the tax saving plan" is a means for notifying the user of the generated tax saving plan and the results of its simulation.

[0184] "Means of supporting application procedures with a reminder function" refers to a means of notifying users of deadlines and important points to note when completing application procedures.

[0185] The present invention is a system that includes means for acquiring income and expenditure data, means for analysis, means for generating tax-saving plans, means for simulation, and means for supporting application procedures, thereby enabling users to easily find optimal tax-saving strategies and implement them efficiently.

[0186] System configuration

[0187] The system consists of a user's device, a server, and related databases. Users use their device to input or scan income and expenditure data, which is then sent to the server. The server analyzes the data, generates and simulates tax-saving plans, and sends the information back to the device. It also generates the documents necessary for the application process, helping users complete the process efficiently.

[0188] Acquisition of income and expenditure data

[0189] Users manually enter income and expense information into the terminal or scan paper documents or electronic files, such as pay slips or receipts. The terminal then uses OCR technology to convert the scanned data into text data, providing digital income and expenditure data. It also integrates with electronic payment services to collect transaction data in real time.

[0190] Data transmission and analysis

[0191] The device sends the acquired data to a server using a secure communication protocol. The server analyzes the data and categorizes it into categories such as income, expenses, medical expenses, and education expenses. This allows the user to understand their financial situation in detail.

[0192] Tax saving plan generation and simulation

[0193] The server generates an optimal tax-saving plan based on the user's income and expenditure data, using the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, mortgage deductions, etc. The server then simulates the tax savings effect of each generated tax-saving plan and presents it to the user. The simulation results include predicted tax reductions and comparative information based on the plan selected by the user.

[0194] Support for application procedures

[0195] The server automatically generates the application documents required for the selected tax-saving plan and sends them to the terminal. The user downloads and prints these documents and completes the necessary procedures. The application process is also supported by a reminder function, notifying the user of deadlines and important points to note.

[0196] Ongoing support

[0197] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. Based on new data and changes in the tax system, the server re-proposes the optimal tax saving plan, ensuring that the user can always take tax saving measures that are adapted to the latest tax system.

[0198] Specific processing examples

[0199] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0200] 1. The user enters or scans their pay stub and expense information into the terminal.

[0201] 2. The device sends the balance data to the server.

[0202] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0203] 4. The server generates multiple tax-saving plans based on the data and simulates the tax savings effect of each.

[0204] 5. The device will display the best tax saving plan for the user and its benefits.

[0205] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the device.

[0206] 7. The user downloads the application form and follows the instructions to complete the procedure.

[0207] Hardware and software used

[0208] The hardware used is mainly user devices such as smartphones and tablets, while the software used is OCR technology for acquiring income and expenditure data, algorithms for analyzing the collected data, a database for generating tax-saving plans, and a program for simulation.

[0209] Prompt Sentence Examples

[0210] Please provide a concrete example of an application that automatically collects and analyzes income and expenditure data, generates a tax-saving plan, and simulates its effectiveness. If user "example_user_id" uses an electronic payment service, please show data collection, classification, tax-saving plan proposal, and simulation results.

[0211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0212] Step 1:

[0213] The user inputs or scans income and expenditure data. The user manually inputs income and expenditure information, such as pay slips or receipts, into the device or scans documents. Input data includes income amounts, expense items, dates, etc. The output is the income and expenditure data in digital form.

[0214] Step 2:

[0215] The terminal uses OCR technology to convert the scanned data into text data. The terminal then performs OCR processing on the scanned image data and extracts the balance information as text data. The input is the scanned data, and the output is the balance data in text format.

[0216] Step 3:

[0217] The terminal transmits the acquired balance data to the server. The collected data (text-format balance data) is sent to the server using a secure communication protocol. The input is the text-format balance data, and the output is the data transmitted to the server.

[0218] Step 4:

[0219] The server analyzes the received data and runs an algorithm to classify it into categories such as income, expenses, medical expenses, and education expenses. The input is text-formatted data, and the output is the categorized data.

[0220] Step 5:

[0221] The server generates the optimal tax saving plan based on the latest tax system information. It references the tax system information stored in the database and identifies applicable tax saving measures based on the user's income and expenditure data. The input is categorized income and expenditure data and tax system information, and the output is candidate tax saving plans.

[0222] Step 6:

[0223] The server simulates the tax savings effect of each generated tax saving plan. It calculates the savings effect of each plan and performs a simulation to present it to the user. The input is the tax saving plan, and the output is the tax savings effect as a result of the simulation.

[0224] Step 7:

[0225] The terminal notifies the user of the optimal tax saving plan and the simulation results. The terminal interface shows the plans the user can choose from and their effects. The input is the simulation results, and the output is the information notified to the user.

[0226] Step 8:

[0227] Based on the plan selected by the user, the server automatically generates the necessary application documents. The generated application documents are sent to the terminal, where the user can download and print them. The input is the selected tax saving plan, and the output is the generated application documents.

[0228] Step 9:

[0229] The terminal supports the application procedure with a reminder function. It provides a reminder function that notifies the user of the deadline for submitting application documents and any additional information that is required. The input is the application schedule information, and the output is the reminder notified to the user.

[0230] Prompt Sentence Examples

[0231] Please provide a concrete example of an application that automatically collects and analyzes income and expenditure data, generates a tax-saving plan, and simulates its effectiveness. If user "example_user_id" uses an electronic payment service, please show data collection, classification, tax-saving plan proposal, and simulation results.

[0232] 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.

[0233] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing it, means for generating tax-saving plans, means for simulation, and means for supporting application procedures, as well as an emotion engine that recognizes the user's emotions. This system is designed to enable users to easily find and efficiently implement tax-saving strategies that are best suited to them. Furthermore, the emotion engine customizes the system's responses according to the user's emotional state, providing a more effective experience.

[0234] System configuration

[0235] The system consists of a user's device, a server, related databases, and an emotion engine that recognizes the user's emotions. The user uses the device to input or scan income and expenditure data and transmits the data to the server. The emotion engine simultaneously analyzes the user's emotions, and the server receives and analyzes this data, generating and simulating an optimal tax-saving plan. The system also generates the documents necessary for the application process, helping the user to complete the process efficiently.

[0236] Acquisition of income and expenditure data

[0237] 1. Data Entry / Scanning:

[0238] Users manually enter income and expense information into the device or scan paper documents or electronic files, such as pay slips or household receipts.

[0239] The terminal uses OCR technology to convert the scanned data into text data, and obtains the income and expenditure data in digital format.

[0240] Sending and analyzing income and expenditure data

[0241] 2. Data transmission:

[0242] The device transmits the acquired income and expenditure data and the user's emotional information to the server via a secure communication protocol.

[0243] 3. Data Analysis:

[0244] The server analyzes the received income and expenditure data and automatically categorizes it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[0245] The server simultaneously analyzes the user's emotional data to determine the user's current emotional state.

[0246] Tax saving plan generation and simulation

[0247] 4. Generate tax saving plans:

[0248] The server generates an optimal tax-saving plan based on the user's income and expenditure data, taking into account the latest tax information. For example, it suggests plans that include medical expense deductions, donation deductions, and mortgage deductions.

[0249] The emotion engine selects an appropriate plan presentation method based on the user's emotional state.

[0250] 5. Simulation:

[0251] The server simulates the tax savings effect of each generated tax saving plan and calculates the expected tax reduction.

[0252] Presentation of simulation results

[0253] 6. Presentation of results:

[0254] The device graphically displays details of the tax-saving plan and its benefits to the user, while the emotion engine adjusts the display and tone of the message depending on the user's emotions. For example, if the user is feeling stressed, the display will be more concise and reassuring.

[0255] Support for application procedures

[0256] 7. Document generation and submission:

[0257] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal, where the user can download and print these documents and complete the necessary procedures.

[0258] The emotion engine provides additional information and support to address any concerns or questions users may have during the process.

[0259] Ongoing support

[0260] 8. Periodic Data Updates and Plan Reassessment:

[0261] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. By re-proposing the optimal tax saving plan based on new data and changes in the tax system, the user can always implement tax saving measures that are adapted to the latest tax system.

[0262] Specific examples

[0263] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0264] 1. The user enters or scans their pay stub and expense information into the terminal.

[0265] 2. The device sends the income and expenditure data and the user's emotional information to the server.

[0266] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0267] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0268] 5. The device displays the optimal tax saving plan and its benefits to the user, with the emotion engine customizing the display based on the user's emotions.

[0269] 6. Once the user selects the desired tax saving plan, the server generates the necessary application documents and sends them to the terminal.

[0270] 7. The user downloads the application documents and follows the instructions to complete the procedure. Through this process, the user can automatically and effectively take optimal tax-saving measures.

[0271] The processing flow will be explained below.

[0272] Step 1:

[0273] The user collects income and expense data and manually enters it into the terminal or scans it.

[0274] Step 2:

[0275] The device uses OCR technology to convert scanned documents into text data, obtaining income and expenditure data in digital format.

[0276] Step 3:

[0277] The device transmits the collected data and the user's emotional information recognized by the emotion engine to the server using a secure communication protocol.

[0278] Step 4:

[0279] The server analyzes the received income and expenditure data and automatically classifies it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[0280] Step 5:

[0281] The server checks the data for inconsistencies and cleanses it as needed, including removing duplicate data and standardizing formats.

[0282] Step 6:

[0283] The server learns the latest tax information and generates the optimal tax-saving plan based on that information. For example, it suggests plans that include medical expense deductions, donation deductions, and mortgage deductions.

[0284] Step 7:

[0285] The server simulates the tax savings effect of each tax saving plan and calculates the expected tax reduction.

[0286] Step 8:

[0287] The server sends the simulation results along with the optimal tax saving plan to the terminal.

[0288] Step 9:

[0289] The device graphically displays details of the tax-saving plan and its benefits to the user, while an emotion engine adjusts the display and tone of the message based on the user's emotions. For example, if the user is feeling stressed, the display will be more concise and reassuring.

[0290] Step 10:

[0291] The user selects the desired tax saving plan.

[0292] Step 11:

[0293] The server automatically generates the necessary application documents based on the selected tax saving plan, and also lists the necessary attachments.

[0294] Step 12:

[0295] The server sends the generated application documents to the terminal.

[0296] Step 13:

[0297] The terminal presents the application documents to the user and instructs them to download and print them.

[0298] Step 14:

[0299] The user downloads the generated documents and follows the instructions to complete the application process.

[0300] Step 15:

[0301] The server periodically updates income and expenditure data and incorporates new data to support ongoing tax-saving measures.

[0302] Step 16:

[0303] The server reevaluates the tax saving plan based on new income and expenditure data and changes in tax systems, and proposes a new plan to the user as necessary.

[0304] In this way, users can efficiently manage their income and expenditure data and easily take optimal tax-saving measures. Furthermore, the emotion engine provides detailed support according to the user's emotions, improving the user experience.

[0305] Example 2

[0306] 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."

[0307] Previously, there were systems that proposed tax-saving plans based on income and expenditure data, but they lacked careful consideration for the user's emotional state. Furthermore, security considerations were insufficient, and a system that users could use with peace of mind was needed. In addition, there was a lack of support for addressing the anxieties and questions users had during the application process, making improving the user experience an urgent issue.

[0308] 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 acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting the application procedures required for the tax saving plan, emotion recognition means for recognizing the user's emotion and customizing the proposal content based on the emotion, means for transmitting data to the server using a secure communication protocol, and means for using the emotion recognition means to address any anxieties or questions the user may have during the procedure. This allows the user to use the system with peace of mind, find the optimal tax saving plan for themselves, and efficiently implement it.

[0309] "Income and expenditure data capture means" refers to a device or software that allows a user to input or scan information about income and expenses and capture it in digital form.

[0310] "Means for analyzing acquired income and expenditure data" refers to a device or software that performs a process of analyzing income and expenditure data and automatically classifying it into categories such as income, expenditure, and expenses.

[0311] The "means for generating an optimal tax saving plan" refers to a device or software that proposes an optimal tax saving plan to a user based on analyzed income and expenditure data and taking into account the latest tax system information.

[0312] "Means for simulating the tax saving effect of a tax saving plan" refers to a device or software that simulates the effect of a generated tax saving plan using numerical values, graphs, etc., and calculates the predicted tax reduction.

[0313] "Application procedure support means" refers to a device or software that automatically generates the application documents required for a tax-saving plan and provides assistance to users in downloading, printing, and properly completing the application documents.

[0314] "Emotion recognition means that recognizes a user's emotions and customizes the content of suggestions based on those emotions" refers to a device or software that analyzes a user's emotional state in real time and adjusts the content of suggestions and the display method based on the results.

[0315] "Means for transmitting data to a server using a secure communication protocol" refers to a device or software that uses a communication protocol (e.g., HTTPS) to encrypt data and transmit it securely to a server.

[0316] "Means for using emotion recognition means to address the anxiety and doubts that users may feel during a procedure" refers to devices or software that alleviate anxiety and doubts that users may feel during a procedure by providing necessary information and support based on the user's emotional state.

[0317] This invention is a system that inputs and acquires information on income and expenses, and then proposes optimal tax-saving plans based on that information. The system has multiple functions, including income and expenditure data acquisition, analysis, plan generation, simulation, application support, and emotion recognition, and is designed to enable users to efficiently implement tax-saving measures.

[0318] Hardware and Software

[0319] User device: PC, smartphone, tablet, etc. The device where the user enters or scans their financial data.

[0320] Server: A central processing unit that performs tasks such as data analysis, tax saving plan generation, and simulations.

[0321] Emotion Recognition Engine: An AI engine (e.g., emotion recognition API) that recognizes user emotions in real time and adjusts suggestions accordingly.

[0322] OCR technology: Technology that converts scanned documents into text data (e.g., OCR API).

[0323] System configuration

[0324] The user uses the device to input or scan income and expenditure data such as pay slips and receipts. The device then uses OCR technology to convert the scanned data into text data, obtaining digital income and expenditure data. This data is then sent to a server using a secure communication protocol (e.g., HTTPS), and the user's emotional information is also collected.

[0325] The server analyzes the received income and expenditure data and categorizes it into categories such as income, expenditure, and expenses. Furthermore, the server analyzes the user's emotional data provided by the emotion recognition engine to identify the user's current emotional state. Based on this information, the server generates an optimal tax saving plan by referring to the latest tax information.

[0326] For each tax saving plan, the server simulates its effects and calculates the projected tax savings. The results are displayed graphically, and an emotion recognition engine adjusts the content and tone of the message depending on the user's emotions.

[0327] Once the user selects the desired tax saving plan, the server automatically generates the necessary application documents and sends them to the terminal. The user can download and print these documents and follow the instructions to complete the formal procedures. During the application process, the emotion recognition engine provides appropriate information and support to address any concerns or questions the user may have about the process.

[0328] Specific examples

[0329] For example, if a user provides monthly pay stubs and expense data, the following occurs:

[0330] 1. The user enters or scans their pay stub and expense information into the terminal.

[0331] 2. The device sends the income and expenditure data and the user's emotional information to the server.

[0332] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0333] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0334] 5. The device displays the best tax-saving plan and its benefits to the user, with an emotion-recognition engine customizing the display based on the user's emotions.

[0335] 6. Once the user selects the desired tax saving plan, the server generates the necessary application documents and sends them to the terminal.

[0336] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[0337] Prompt Sentence Examples

[0338] "Tell me about an income / expense data analysis system that incorporates an emotion engine that recognizes the user's emotions. Please explain the overall process flow of the system that adjusts the display format and tone according to the user's emotional state and suggests the optimal tax saving plan."

[0339] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0340] Step 1:

[0341] Acquisition of income and expenditure data

[0342] The user enters or scans income and expenditure data, such as pay stubs or receipts, into the terminal.

[0343] Input: Paper or electronic files such as pay stubs or receipts.

[0344] Output: Digital balance data converted into text data using OCR technology.

[0345] How it works: The user takes a photo of their pay slip with their smartphone and uploads it. The device then uses the OCR API to convert the image into text data, and the income and expenditure data is obtained in digital form.

[0346] Step 2:

[0347] Sending financial data and emotional information

[0348] The terminal transmits the acquired income and expenditure data and the user's emotional information to the server.

[0349] Input: Digital balance data converted using OCR technology and sentiment information collected in real time.

[0350] Output: Encrypted financial data and emotional information are sent to the server.

[0351] How it works: The device encrypts financial data and emotional information and sends it to the server using the secure HTTPS protocol.

[0352] Step 3:

[0353] Analysis of income and expenditure data and emotional information

[0354] The server analyzes the received income and expenditure data, including emotional information.

[0355] Input: Submitted digital financial data and sentiment.

[0356] Output: Analysis results categorized into categories such as income, expenditure, and expenses, along with the user's emotional state.

[0357] How it works: The server analyzes the data and automatically categorizes the balance data, while the emotion recognition engine identifies the user's emotional state.

[0358] Step 4:

[0359] Generate optimal tax saving plans

[0360] The server generates the optimal tax saving plan based on the analyzed income and expenditure data, while referring to the latest tax information.

[0361] Input: Categorised financial data and information about the user's emotional state.

[0362] Output: A proposal with multiple tax saving plans.

[0363] Specific operation: The server references the tax database and generates multiple tax-saving plans based on the user's income and expenditure data. The emotion recognition engine selects the optimal presentation method.

[0364] Step 5:

[0365] Tax saving plan simulation

[0366] The server simulates the tax saving effect of the generated tax saving plan and calculates the expected tax reduction.

[0367] Input: Each generated tax saving plan.

[0368] Output: Projected tax savings as a result of the simulation.

[0369] Specific operation: The server simulates tax reduction for each plan and outputs the results in numerical and graphical form.

[0370] Step 6:

[0371] Presentation of simulation results

[0372] The terminal will then graphically display to the user the details of the tax saving plan and its effects.

[0373] Input: Simulated tax reduction results.

[0374] Output: A visual representation of the tax saving plan and its effects to the user.

[0375] Specific operation: The device displays the simulation results in graphs and charts, and the emotion recognition engine customizes the display according to the user's emotions.

[0376] Step 7:

[0377] Support for application procedures

[0378] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal.

[0379] Input: The tax saving plan selected by the user.

[0380] Output: Auto-generated application documents.

[0381] Specific operation: The server automatically generates the necessary application documents and sends them to the terminal. The user downloads these documents, prints them, and proceeds with the procedure.

[0382] Step 8:

[0383] Support during the process

[0384] The emotion recognition engine provides information to help users deal with any concerns or doubts they may have during the process.

[0385] Input: The user's emotional state and any concerns or doubts about the procedure.

[0386] Output: Additional information or support messages.

[0387] Specific operation: The emotion recognition engine monitors the user's emotional state and displays appropriate feedback and support messages in case of anxiety or doubt.

[0388] Step 9:

[0389] Continuous data updates and plan reevaluation

[0390] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan.

[0391] Input: Newly updated income and expenditure data.

[0392] Output: Reassessed optimal tax saving plan.

[0393] Specific operation: The server periodically updates the database and re-proposes new tax-saving plans based on the latest tax information and income and expenditure data.

[0394] (Application example 2)

[0395] 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."

[0396] Today's consumers spend a great deal of time and effort managing complex income and expenditures and implementing optimal tax-saving strategies. However, existing systems often fail to consider user emotions and are often stressful, resulting in a poor user experience. Furthermore, systems lack the digitalization and security of income and expenditure data, and are not up to date with the latest tax information, leaving users without an environment in place to quickly and efficiently implement optimal tax-saving strategies. Therefore, there is a need for the development of a new system that takes user emotions into consideration and provides comprehensive support, from acquiring income and expenditure data to secure data transmission and providing tax-saving plans based on the latest tax information.

[0397] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0398] In this invention, the server includes means for acquiring income and expenditure data, means including an emotion engine for recognizing user emotions, means for using OCR technology to acquire the income and expenditure data from the user and convert it into a digital format, means for simulating the tax savings effect of the generated tax saving plan, means for adjusting the display method and message tone according to the user's emotions when graphically displaying the tax savings effect of the tax saving plan, means for securely transmitting the income and expenditure data and the generated savings plan to the server, means for learning the latest tax information and updating the database, means for using a generative AI model to provide optimal advice to the user, and means for generating prompt sentences and making optimal suggestions to the user based on the generated prompt sentences. This enables the provision of a user-friendly interface that takes user emotions into consideration, while also enabling the digitization and secure management of income and expenditure data, and the prompt sentences to be quickly and efficiently proposed to the user as optimal tax saving plans based on the latest tax information.

[0399] definition statement

[0400] "Means for acquiring income and expenditure data" refers to a means by which a user inputs or scans income and expenditure information into a terminal, and includes technology for converting that data into digital form.

[0401] The "means for analyzing the acquired income and expenditure data" includes algorithms and software for categorizing the income and expenditure data and analyzing its contents.

[0402] The "means for generating an optimal tax saving plan" includes algorithms and systems that propose the most effective tax saving measures for users based on analyzed income and expenditure data and the latest tax system information.

[0403] "Means for simulating the tax savings effect of the generated tax savings plan" includes programs and systems for calculating and evaluating the expected tax savings effect based on the generated tax savings plan.

[0404] The "means for supporting the application procedures necessary for a tax saving plan" includes a system that automatically generates application documents prepared in accordance with an optimal tax saving plan and provides them to users.

[0405] The "emotion engine that recognizes the user's emotions" includes algorithms and systems that analyze the user's emotions from their facial expressions and tone of voice, and adjust the way they respond based on that information.

[0406] "Means using OCR technology" includes technology that reads text information from paper receipts or electronic files and converts it into digital data.

[0407] "Means for securely transmitting to the server" includes technology for securely transmitting income and expenditure data and savings plans to the server using security technology such as encryption.

[0408] "Means for providing optimal advice to users using a generative AI model" includes a system that uses a generative artificial intelligence model to provide appropriate advice based on the user's income and expenditure data and emotional data.

[0409] "Means for generating prompt sentences and making optimal suggestions to users based on the generated prompt sentences" includes a system in which a generative AI model generates appropriate prompt sentences for users based on input data and makes optimal suggestions based on the content of those sentences.

[0410] MODE FOR CARRYING OUT THE INVENTION

[0411] This invention provides a system that efficiently provides savings and purchasing advice to consumers on online shopping sites. The system utilizes a means of acquiring income and expenditure data, an emotion engine, OCR technology, a secure communication protocol, and a generative AI model.

[0412] System configuration

[0413] The system includes a terminal that collects the user's income and expenditure data and converts it into digital format, a server that securely analyzes and stores this data, and an emotion engine that recognizes the user's emotions and provides appropriate advice.

[0414] Hardware and Software

[0415] Hardware: Smartphones and tablets with a camera

[0416] Software: OCR technology (e.g., pytesseract), image processing library (PIL), HTTP request library (requests), generative AI models

[0417] Data processing and calculation

[0418] 1. The user takes a photo of the receipt for the purchased item with their smartphone camera, and the device uses OCR technology to convert the balance data into a digital format, which then recognizes the receipt image as text data.

[0419] 2. The acquired balance data is sent to a server using a secure communication protocol, and the server analyzes the data using a category classification algorithm for the balance data.

[0420] 3. The server generates the optimal tax saving plan from the analyzed income and expenditure data based on the latest tax information.

[0421] 4. The emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the tone and content of the suggested advice based on the user's current emotional state.

[0422] 5. Simulate the effects of the generated tax saving plan and display the results graphically.

[0423] 6. Using the generative AI model, provide optimal purchasing advice to the user and generate specific prompts, such as "Please suggest the best savings plan based on the user's purchase history and bank statements. Please also provide encouraging messages if the user is feeling stressed."

[0424] 7. If the user selects a tax-saving plan, the server automatically generates the documents required for the application procedure and provides a download link to the device.

[0425] Specific examples

[0426] After a user shops at the supermarket, they take a photo of the receipt with their smartphone. OCR technology extracts the product names and amounts from the receipt and captures them as income and expenditure data. The user's facial expressions are analyzed, and gentle advice is offered if they appear stressed. The server analyzes the income and expenditure data and displays specific advice, such as, "Your expenses have increased this month, so next time you shop, try replacing these items with cheaper alternatives."

[0427] Through this process, users can not only easily and effectively implement savings measures, but also enjoy a less stressful shopping experience.

[0428] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0429] Detailed explanation of the processing steps

[0430] Step 1:

[0431] The user takes a photo of the receipt with the smartphone camera. The input is the receipt image, and the output is image data. Specifically, the smartphone's camera app is launched, and the user takes a photo of the receipt.

[0432] Step 2:

[0433] The terminal uses OCR technology to extract text information from receipt images and convert it into balance data. The input is image data and the output is text data. Specifically, the image is read using the PIL library and the text information is extracted using pytesseract.

[0434] Step 3:

[0435] The terminal sends the balance data to the server using a secure communication protocol. The input is text data, and the output is the data sent to the server. Specifically, the data is sent as a POST request using the HTTP request library (requests).

[0436] Step 4:

[0437] The server analyzes the received income and expenditure data and categorizes it. The input is income and expenditure data, and the output is data categorized by category. Specifically, the server analyzes the data using an income and expenditure analysis algorithm and categorizes it into categories such as income and expenditure.

[0438] Step 5:

[0439] The server generates the optimal tax saving plan based on the latest tax information. The input is the analyzed income and expenditure data, and the output is the tax saving plan. Specifically, the server refers to the latest tax database and calculates the appropriate tax saving plan.

[0440] Step 6:

[0441] The emotion engine analyzes the user's facial expression and tone of voice to determine the user's current emotional state. The input is the user's facial expression or voice data, and the output is emotional state data. Specifically, it uses an emotion analysis algorithm to determine whether the user is feeling stressed.

[0442] Step 7:

[0443] The server simulates the tax savings effect of the tax saving plan and displays the results graphically. The input is the tax saving plan, and the output is the simulation result. Specifically, it uses a simulation algorithm to calculate the tax reduction effect and generates the data necessary to display it as a graph.

[0444] Step 8:

[0445] A generative AI model is used to provide optimal purchasing advice to users and generate specific prompts. The input is income and expenditure data and emotional state data, and the output is specific prompts. Specifically, the generative AI model analyzes the input data and generates prompts such as, "Please suggest the optimal savings plan based on the user's purchase history and bank statements. Please provide an encouraging message if the user is feeling stressed."

[0446] Step 9:

[0447] When a user selects a tax-saving plan, the server automatically generates the documents required for the application procedure and provides a download link to the terminal. The input is the selected tax-saving plan, and the output is a download link for the application documents. Specifically, the server uses a document generation algorithm to create the necessary application documents, generates a link for them, and sends it to the terminal.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] [Second embodiment]

[0452] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0453] 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.

[0454] 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).

[0455] 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.

[0456] 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.

[0457] 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).

[0458] 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.

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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.

[0463] 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."

[0464] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing data, means for generating tax-saving plans, means for simulation, and means for supporting application procedures. This system is designed to enable users to easily find and efficiently implement tax-saving strategies that are optimal for them.

[0465] System configuration

[0466] The system consists of a user's terminal, a server, and related databases. The user uses the terminal to input or scan income and expenditure data, which is then sent to the server. The server analyzes the income and expenditure data, generates and simulates tax-saving plans, and sends the information back to the terminal. It also generates the documents necessary for application procedures, helping the user to complete the procedures efficiently.

[0467] Acquisition of income and expenditure data

[0468] 1. Data Entry / Scanning:

[0469] Users manually enter income and expense information into the device or scan paper documents or electronic files, such as pay slips or household receipts.

[0470] The terminal uses OCR technology to convert the scanned data into text data, and obtains the income and expenditure data in digital format.

[0471] Sending and analyzing income and expenditure data

[0472] 2. Data transmission:

[0473] The terminal transmits the acquired balance data to the server using a secure communication protocol.

[0474] 3. Data Analysis:

[0475] The server analyzes the received income and expenditure data and categorizes it into categories such as income, expenditure, expenses, medical expenses, education expenses, etc. This allows the user's income and expenditure situation to be understood in detail.

[0476] Tax saving plan generation and simulation

[0477] 4. Generate tax saving plans:

[0478] The server generates an optimal tax-saving plan based on the user's income and expenditure data, taking into account the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, and mortgage deductions.

[0479] 5. Simulation:

[0480] The server simulates the tax savings effect of each tax saving plan and presents it to the user. The simulation results include predicted tax reductions and comparative information based on the plan selected by the user.

[0481] Support for application procedures

[0482] 6. Document generation and submission:

[0483] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal, where the user can download and print these documents and complete the necessary procedures.

[0484] Ongoing support

[0485] 7. Periodic Data Updates and Plan Reassessment:

[0486] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. By re-proposing the optimal tax saving plan based on new data and changes in the tax system, the user can always implement tax saving measures that are adapted to the latest tax system.

[0487] Specific examples

[0488] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0489] 1. The user enters or scans their pay stub and expense information into the terminal.

[0490] 2. The terminal sends the balance data to the server.

[0491] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0492] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0493] 5. The device will display the best tax saving plan for the user and its effects.

[0494] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the terminal.

[0495] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[0496] This system allows users to automatically and efficiently take the best possible tax-saving measures.

[0497] The processing flow will be explained below.

[0498] Step 1:

[0499] The user collects income and expense data and manually enters it into the terminal or scans it.

[0500] Step 2:

[0501] The device uses OCR technology to convert scanned documents into text data, obtaining income and expenditure data in digital format.

[0502] Step 3:

[0503] The terminal transmits the collected data to the server using a secure communication protocol.

[0504] Step 4:

[0505] The server analyzes the received income and expenditure data and automatically classifies it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[0506] Step 5:

[0507] The server checks the data for inconsistencies and cleanses it as needed, including removing duplicate data and standardizing formats.

[0508] Step 6:

[0509] The server learns the latest tax information and generates the optimal tax-saving plan based on that information. For example, it suggests plans that include medical expense deductions and donation deductions.

[0510] Step 7:

[0511] The server simulates the tax savings effect of each tax saving plan and calculates the expected tax reduction.

[0512] Step 8:

[0513] The server sends the simulation results along with the optimal tax saving plan to the terminal.

[0514] Step 9:

[0515] The device graphically displays details of tax-saving plans and their effects to users, allowing them to intuitively understand the comparison of each plan.

[0516] Step 10:

[0517] The user selects the desired tax saving plan.

[0518] Step 11:

[0519] The server automatically generates the necessary application documents based on the selected tax saving plan, and also lists the necessary attachments.

[0520] Step 12:

[0521] The server sends the generated application documents to the terminal.

[0522] Step 13:

[0523] The terminal presents the application documents to the user and instructs them to download and print them.

[0524] Step 14:

[0525] The user downloads the generated documents and follows the instructions to complete the application process.

[0526] Step 15:

[0527] The server periodically updates income and expenditure data and incorporates new data to support ongoing tax-saving measures.

[0528] Step 16:

[0529] The server reevaluates the tax saving plan based on new income and expenditure data and changes in tax systems, and proposes a new plan to the user as necessary.

[0530] In this way, users can efficiently manage their income and expenditure data and easily take optimal tax-saving measures.

[0531] Example 1

[0532] 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."

[0533] The present invention relates to a system that supports individuals or corporations in efficiently implementing tax-saving measures. Conventional tax-saving measures are complex, requiring the management of numerous documents and an understanding of the tax system, making it difficult for individual users to find the optimal tax-saving plan. Furthermore, it is difficult to obtain a plan that constantly reflects the latest tax system information, resulting in ineffective tax savings. This has led to the problem that many users end up making wasteful expenditures and failing to implement appropriate tax-saving measures.

[0534] 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.

[0535] In this invention, the server includes means for acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting application procedures required for the tax saving plan, means for converting the income and expenditure data into text data using OCR technology, means for transmitting the income and expenditure data to the server using a secure communication protocol, means for learning the latest tax information using a generative AI model and generating a tax saving plan, means for periodically updating the income and expenditure data and reevaluating the tax saving plan, and means for presenting the simulation results to the user. This allows users to easily input income and expenditure data and efficiently obtain an optimal tax saving plan based on the latest tax information.

[0536] "Income and Expenditure Data" means information relating to income and expenditures that indicates the financial position of an individual or entity.

[0537] "Capture means" refers to the functionality of a device or software for inputting or scanning and collecting financial data from a user.

[0538] "Analysis means" refers to the function of a device or software that categorizes and performs statistical analysis based on the acquired income and expenditure data.

[0539] A "tax saving plan" refers to a specific plan that suggests ways and strategies to reduce tax based on the user's income and expenditure data.

[0540] "Simulation means" refers to the functionality of a device or software that predicts the effects of a generated tax saving plan and calculates the specific tax savings and benefits.

[0541] "Means to support application procedures" refers to auxiliary functions that allow users to prepare the necessary documents and carry out application procedures efficiently.

[0542] "OCR technology" refers to optical character recognition technology, which extracts text data from scanned images.

[0543] "Secure communication protocol" refers to a communication protocol that ensures security when sending and receiving data, and includes, for example, HTTPS.

[0544] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and operate for a specific purpose (in this case, learning tax information or generating tax-saving plans).

[0545] "Latest tax information" refers to the latest tax rules and information, including tax laws and deduction provisions in effect at the time.

[0546] "Database" refers to a collection of collected and stored data that allows the system to efficiently manage and use the information it needs.

[0547] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing data, means for generating tax-saving plans, means for simulation, and means for supporting application procedures. This system is designed to enable individuals or corporations to efficiently find and implement optimal tax-saving strategies. Each means will be specifically described below.

[0548] How to obtain income and expenditure data

[0549] Users enter or scan financial data using their device. For example, they can take a photo of a pay slip, receipt, or other financial document with their smartphone camera and import it into the app. The device then converts this data into text using OCR (optical character recognition) technology. Software such as Tesseract OCR can be used to extract text from the scanned image.

[0550] Data transmission method

[0551] The terminal transmits the acquired and converted balance data to the server via a secure communication protocol (e.g., HTTPS), which prevents data leakage and unauthorized access.

[0552] Data analysis methods

[0553] The server analyzes the received data, for example, by using the Python Pandas library to classify the data into different categories (income, expenditure, expenses, medical expenses, education expenses, etc.) to obtain a detailed understanding of the user's financial situation. The results of this analysis are then used to generate a tax saving plan.

[0554] Tax saving plan generation tool

[0555] The server uses the generative AI model to learn the latest tax information and update the database. This allows the server to generate optimal tax-saving plans based on the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, and mortgage deductions.

[0556] Simulation Method

[0557] The server simulates the tax savings effect of the generated tax saving plans. Using Python's NumPy library, it calculates the predicted tax reduction effect of each plan and presents it to the user. The simulation results include the effects and benefits of each plan.

[0558] Support for application procedures

[0559] The server automatically generates the application documents required for the tax-saving plan selected by the user and sends them to the terminal. The application documents are created in PDF format using the PyPDF2 library, etc. The user downloads and prints these documents and follows the instructions to complete the application process.

[0560] Ongoing support measures

[0561] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan based on the latest tax information, thereby always providing the optimal tax saving strategy.

[0562] Specific examples

[0563] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0564] 1. The user enters or scans their pay stub and expense information into the device, for example, by taking a photo of their pay stub using their smartphone camera and scanning it into the app.

[0565] 2. The device uses OCR technology to convert the scanned data into text data and sends that data to the server.

[0566] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0567] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0568] 5. The device will display the best tax saving plan for the user and its effects.

[0569] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the terminal.

[0570] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[0571] Prompt Sentence Examples

[0572] "Please enter or scan the data from your monthly pay slip and household ledger according to the following headings: income, expenditures, expenses, medical expenses, and education expenses."

[0573] This system allows users to automatically and efficiently take the best tax-saving measures.

[0574] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0575] Step 1:

[0576] Data Entry / Scanning

[0577] The user manually enters income and expense information into the device, or scans a paper document or electronic file. For example, they take a picture of a pay slip or receipt with their smartphone camera and scan it into the app. The input data includes income amount, expense amount, and expense category. The device then converts the scanned data into text data using OCR technology. For example, Tesseract OCR can be used to extract text from an image of a pay slip. This text data is then passed to the next processing step.

[0578] Step 2:

[0579] Data transmission

[0580] The terminal sends the acquired and converted balance data to the server using a secure communication protocol (e.g., HTTPS). The input data includes the text data obtained in step 1. Using a secure communication protocol prevents data leakage and unauthorized access. The balance data is securely passed to the server through this communication.

[0581] Step 3:

[0582] Data analysis

[0583] The server analyzes the received income and expenditure data. The input data includes the transmitted income and expenditure data (income, expenditure, expense items, etc.). Using Python's Pandas library, the data is classified into categories such as income, expenditure, expenses, medical expenses, and education expenses. For example, data such as "Salary: 300,000 yen," "Rent: 80,000 yen," and "Medical expenses: 10,000 yen" are classified into the appropriate categories. The classification results are passed to the next step.

[0584] Step 4:

[0585] Generate tax saving plans

[0586] The server uses the generative AI model to learn the latest tax information and update the database. The input data includes the analysis data obtained in step 3 and the latest tax information. Based on this, the optimal tax saving plan is generated. For example, the applicability of medical expense deductions, donation deductions, mortgage deductions, etc. is evaluated and each plan is generated. The generated results are passed to the next step.

[0587] Step 5:

[0588] simulation

[0589] The server simulates the tax savings effect of each tax saving plan generated. The input data includes each tax saving plan generated in step 4. Using Python's NumPy library, the tax reduction effect of each plan is calculated and presented to the user. For example, the simulation result obtained is "medical expense deductions can save 50,000 yen per year in taxes." This result is passed to the next step.

[0590] Step 6:

[0591] Support for application procedures

[0592] The server automatically generates the application documents required for the tax saving plan selected by the user and sends them to the terminal. The input data includes the simulation results from step 5 and the selected tax saving plan. The server uses the PyPDF2 library to create the application documents in PDF format. For example, it creates "Medical Expense Deduction Application Form.pdf" and sends it to the terminal. The user downloads this document, prints it, fills in the necessary information, and proceeds with the application procedure.

[0593] Step 7:

[0594] Ongoing support

[0595] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan based on new data and changes in the tax system. The input data includes the latest income and expenditure data and the latest tax system information. Based on this, a new tax saving plan is proposed. For example, new analysis results such as "new medical expense deductions are applicable" are provided.

[0596] (Application example 1)

[0597] 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."

[0598] Conventional tax saving systems require users to manually input income and expenditure data, select a tax saving plan, and complete the necessary application procedures, which is time-consuming and labor-intensive. Furthermore, there is no system that collects and analyzes electronic payment data in real time and proposes optimal tax saving plans. This makes it difficult for users to efficiently implement tax saving measures and find the appropriate plan.

[0599] 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.

[0600] In this invention, the server includes means for acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting the application procedures required for the tax saving plan, means for collecting and analyzing electronic payment data in real time, means for categorizing the collected data, means for notifying the user of the tax saving plan, and means for supporting the application procedures with a reminder function. This enables the user to automatically and efficiently find the optimal tax saving plan and smoothly complete the application procedures.

[0601] "Means for obtaining income and expenditure data" refers to means for collecting data on income and expenditure from users.

[0602] The "means for analyzing the acquired income and expenditure data" is a means for analyzing the collected income and expenditure data and classifying it by category.

[0603] The "means for generating an optimal tax saving plan" is a means for proposing the most effective tax saving measures for the user based on analyzed income and expenditure data.

[0604] The "means for simulating the tax saving effect of a tax saving plan" is a means for predicting the effect of the generated tax saving plan and presenting the results to the user.

[0605] "Means to support application procedures" refers to means to automatically generate the necessary application documents based on the tax saving plan selected by the user and to assist with the procedures.

[0606] "Means for collecting and analyzing electronic payment data in real time" refers to means for automatically obtaining data from a user's electronic payment service and analyzing it immediately.

[0607] The "means for categorizing collected data" is a means for classifying collected income and expenditure data into categories such as income, expenditure, medical expenses, and education expenses.

[0608] The "means for notifying the user of the tax saving plan" is a means for notifying the user of the generated tax saving plan and the results of its simulation.

[0609] "Means of supporting application procedures with a reminder function" refers to a means of notifying users of deadlines and important points to note when completing application procedures.

[0610] The present invention is a system that includes means for acquiring income and expenditure data, means for analysis, means for generating tax-saving plans, means for simulation, and means for supporting application procedures, thereby enabling users to easily find optimal tax-saving strategies and implement them efficiently.

[0611] System configuration

[0612] The system consists of a user's device, a server, and related databases. Users use their device to input or scan income and expenditure data, which is then sent to the server. The server analyzes the data, generates and simulates tax-saving plans, and sends the information back to the device. It also generates the documents necessary for the application process, helping users complete the process efficiently.

[0613] Acquisition of income and expenditure data

[0614] Users manually enter income and expense information into the terminal or scan paper documents or electronic files, such as pay slips or receipts. The terminal then uses OCR technology to convert the scanned data into text data, providing digital income and expenditure data. It also integrates with electronic payment services to collect transaction data in real time.

[0615] Data transmission and analysis

[0616] The device sends the acquired data to a server using a secure communication protocol. The server analyzes the data and categorizes it into categories such as income, expenses, medical expenses, and education expenses. This allows the user to understand their financial situation in detail.

[0617] Tax saving plan generation and simulation

[0618] The server generates an optimal tax-saving plan based on the user's income and expenditure data, using the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, mortgage deductions, etc. The server then simulates the tax savings effect of each generated tax-saving plan and presents it to the user. The simulation results include predicted tax reductions and comparative information based on the plan selected by the user.

[0619] Support for application procedures

[0620] The server automatically generates the application documents required for the selected tax-saving plan and sends them to the terminal. The user downloads and prints these documents and completes the necessary procedures. The application process is also supported by a reminder function, notifying the user of deadlines and important points to note.

[0621] Ongoing support

[0622] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. Based on new data and changes in the tax system, the server re-proposes the optimal tax saving plan, ensuring that the user can always take tax saving measures that are adapted to the latest tax system.

[0623] Specific processing examples

[0624] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0625] 1. The user enters or scans their pay stub and expense information into the terminal.

[0626] 2. The device sends the balance data to the server.

[0627] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0628] 4. The server generates multiple tax-saving plans based on the data and simulates the tax savings effect of each.

[0629] 5. The device will display the best tax saving plan for the user and its benefits.

[0630] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the device.

[0631] 7. The user downloads the application form and follows the instructions to complete the procedure.

[0632] Hardware and software used

[0633] The hardware used is mainly user devices such as smartphones and tablets, while the software used is OCR technology for acquiring income and expenditure data, algorithms for analyzing the collected data, a database for generating tax-saving plans, and a program for simulation.

[0634] Prompt Sentence Examples

[0635] Please provide a concrete example of an application that automatically collects and analyzes income and expenditure data, generates a tax-saving plan, and simulates its effectiveness. If user "example_user_id" uses an electronic payment service, please show data collection, classification, tax-saving plan proposal, and simulation results.

[0636] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0637] Step 1:

[0638] The user inputs or scans income and expenditure data. The user manually inputs income and expenditure information, such as pay slips or receipts, into the device or scans documents. Input data includes income amounts, expense items, dates, etc. The output is the income and expenditure data in digital form.

[0639] Step 2:

[0640] The terminal uses OCR technology to convert the scanned data into text data. The terminal then performs OCR processing on the scanned image data and extracts the balance information as text data. The input is the scanned data, and the output is the balance data in text format.

[0641] Step 3:

[0642] The terminal transmits the acquired balance data to the server. The collected data (text-format balance data) is sent to the server using a secure communication protocol. The input is the text-format balance data, and the output is the data transmitted to the server.

[0643] Step 4:

[0644] The server analyzes the received data and runs an algorithm to classify it into categories such as income, expenses, medical expenses, and education expenses. The input is text-formatted data, and the output is the categorized data.

[0645] Step 5:

[0646] The server generates the optimal tax saving plan based on the latest tax system information. It references the tax system information stored in the database and identifies applicable tax saving measures based on the user's income and expenditure data. The input is categorized income and expenditure data and tax system information, and the output is candidate tax saving plans.

[0647] Step 6:

[0648] The server simulates the tax savings effect of each generated tax saving plan. It calculates the savings effect of each plan and performs a simulation to present it to the user. The input is the tax saving plan, and the output is the tax savings effect as a result of the simulation.

[0649] Step 7:

[0650] The terminal notifies the user of the optimal tax saving plan and the simulation results. The terminal interface shows the plans the user can choose from and their effects. The input is the simulation results, and the output is the information notified to the user.

[0651] Step 8:

[0652] Based on the plan selected by the user, the server automatically generates the necessary application documents. The generated application documents are sent to the terminal, where the user can download and print them. The input is the selected tax saving plan, and the output is the generated application documents.

[0653] Step 9:

[0654] The terminal supports the application procedure with a reminder function. It provides a reminder function that notifies the user of the deadline for submitting application documents and any additional information that is required. The input is the application schedule information, and the output is the reminder notified to the user.

[0655] Prompt Sentence Examples

[0656] Please provide a concrete example of an application that automatically collects and analyzes income and expenditure data, generates a tax-saving plan, and simulates its effectiveness. If user "example_user_id" uses an electronic payment service, please show data collection, classification, tax-saving plan proposal, and simulation results.

[0657] 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.

[0658] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing it, means for generating tax-saving plans, means for simulation, and means for supporting application procedures, as well as an emotion engine that recognizes the user's emotions. This system is designed to enable users to easily find and efficiently implement tax-saving strategies that are best suited to them. Furthermore, the emotion engine customizes the system's responses according to the user's emotional state, providing a more effective experience.

[0659] System configuration

[0660] The system consists of a user's device, a server, related databases, and an emotion engine that recognizes the user's emotions. The user uses the device to input or scan income and expenditure data and transmits the data to the server. The emotion engine simultaneously analyzes the user's emotions, and the server receives and analyzes this data, generating and simulating an optimal tax-saving plan. The system also generates the documents necessary for the application process, helping the user to complete the process efficiently.

[0661] Acquisition of income and expenditure data

[0662] 1. Data Entry / Scanning:

[0663] Users manually enter income and expense information into the device or scan paper documents or electronic files, such as pay slips or household receipts.

[0664] The terminal uses OCR technology to convert the scanned data into text data, and obtains the income and expenditure data in digital format.

[0665] Sending and analyzing income and expenditure data

[0666] 2. Data transmission:

[0667] The device transmits the acquired income and expenditure data and the user's emotional information to the server via a secure communication protocol.

[0668] 3. Data Analysis:

[0669] The server analyzes the received income and expenditure data and automatically categorizes it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[0670] The server simultaneously analyzes the user's emotional data to determine the user's current emotional state.

[0671] Tax saving plan generation and simulation

[0672] 4. Generate tax saving plans:

[0673] The server generates an optimal tax-saving plan based on the user's income and expenditure data, taking into account the latest tax information. For example, it suggests plans that include medical expense deductions, donation deductions, and mortgage deductions.

[0674] The emotion engine selects an appropriate plan presentation method based on the user's emotional state.

[0675] 5. Simulation:

[0676] The server simulates the tax savings effect of each generated tax saving plan and calculates the expected tax reduction.

[0677] Presentation of simulation results

[0678] 6. Presentation of results:

[0679] The device graphically displays details of the tax-saving plan and its benefits to the user, while the emotion engine adjusts the display and tone of the message depending on the user's emotions. For example, if the user is feeling stressed, the display will be more concise and reassuring.

[0680] Support for application procedures

[0681] 7. Document generation and submission:

[0682] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal, where the user can download and print these documents and complete the necessary procedures.

[0683] The emotion engine provides additional information and support to address any concerns or questions users may have during the process.

[0684] Ongoing support

[0685] 8. Periodic Data Updates and Plan Reassessment:

[0686] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. By re-proposing the optimal tax saving plan based on new data and changes in the tax system, the user can always implement tax saving measures that are adapted to the latest tax system.

[0687] Specific examples

[0688] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0689] 1. The user enters or scans their pay stub and expense information into the terminal.

[0690] 2. The device sends the income and expenditure data and the user's emotional information to the server.

[0691] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0692] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0693] 5. The device displays the optimal tax saving plan and its benefits to the user, with the emotion engine customizing the display based on the user's emotions.

[0694] 6. Once the user selects the desired tax saving plan, the server generates the necessary application documents and sends them to the terminal.

[0695] 7. The user downloads the application documents and follows the instructions to complete the procedure. Through this process, the user can automatically and effectively take optimal tax-saving measures.

[0696] The processing flow will be explained below.

[0697] Step 1:

[0698] The user collects income and expense data and manually enters it into the terminal or scans it.

[0699] Step 2:

[0700] The device uses OCR technology to convert scanned documents into text data, obtaining income and expenditure data in digital format.

[0701] Step 3:

[0702] The device transmits the collected data and the user's emotional information recognized by the emotion engine to the server using a secure communication protocol.

[0703] Step 4:

[0704] The server analyzes the received income and expenditure data and automatically classifies it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[0705] Step 5:

[0706] The server checks the data for inconsistencies and cleanses it as needed, including removing duplicate data and standardizing formats.

[0707] Step 6:

[0708] The server learns the latest tax information and generates the optimal tax-saving plan based on that information. For example, it suggests plans that include medical expense deductions, donation deductions, and mortgage deductions.

[0709] Step 7:

[0710] The server simulates the tax savings effect of each tax saving plan and calculates the expected tax reduction.

[0711] Step 8:

[0712] The server sends the simulation results along with the optimal tax saving plan to the terminal.

[0713] Step 9:

[0714] The device graphically displays details of the tax-saving plan and its benefits to the user, while an emotion engine adjusts the display and tone of the message based on the user's emotions. For example, if the user is feeling stressed, the display will be more concise and reassuring.

[0715] Step 10:

[0716] The user selects the desired tax saving plan.

[0717] Step 11:

[0718] The server automatically generates the necessary application documents based on the selected tax saving plan, and also lists the necessary attachments.

[0719] Step 12:

[0720] The server sends the generated application documents to the terminal.

[0721] Step 13:

[0722] The terminal presents the application documents to the user and instructs them to download and print them.

[0723] Step 14:

[0724] The user downloads the generated documents and follows the instructions to complete the application process.

[0725] Step 15:

[0726] The server periodically updates income and expenditure data and incorporates new data to support ongoing tax-saving measures.

[0727] Step 16:

[0728] The server reevaluates the tax saving plan based on new income and expenditure data and changes in tax systems, and proposes a new plan to the user as necessary.

[0729] In this way, users can efficiently manage their income and expenditure data and easily take optimal tax-saving measures. Furthermore, the emotion engine provides detailed support according to the user's emotions, improving the user experience.

[0730] Example 2

[0731] 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."

[0732] Previously, there were systems that proposed tax-saving plans based on income and expenditure data, but they lacked careful consideration for the user's emotional state. Furthermore, security considerations were insufficient, and a system that users could use with peace of mind was needed. In addition, there was a lack of support for addressing the anxieties and questions users had during the application process, making improving the user experience an urgent issue.

[0733] 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 acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting the application procedures required for the tax saving plan, emotion recognition means for recognizing the user's emotion and customizing the proposal content based on the emotion, means for transmitting data to the server using a secure communication protocol, and means for using the emotion recognition means to address any anxieties or questions the user may have during the procedure. This allows the user to use the system with peace of mind, find the optimal tax saving plan for themselves, and efficiently implement it.

[0734] "Income and expenditure data capture means" refers to a device or software that allows a user to input or scan information about income and expenses and capture it in digital form.

[0735] "Means for analyzing acquired income and expenditure data" refers to a device or software that performs a process of analyzing income and expenditure data and automatically classifying it into categories such as income, expenditure, and expenses.

[0736] The "means for generating an optimal tax saving plan" refers to a device or software that proposes an optimal tax saving plan to a user based on analyzed income and expenditure data and taking into account the latest tax system information.

[0737] "Means for simulating the tax saving effect of a tax saving plan" refers to a device or software that simulates the effect of a generated tax saving plan using numerical values, graphs, etc., and calculates the predicted tax reduction.

[0738] "Application procedure support means" refers to a device or software that automatically generates the application documents required for a tax-saving plan and provides assistance to users in downloading, printing, and properly completing the application documents.

[0739] "Emotion recognition means that recognizes a user's emotions and customizes the content of suggestions based on those emotions" refers to a device or software that analyzes a user's emotional state in real time and adjusts the content of suggestions and the display method based on the results.

[0740] "Means for transmitting data to a server using a secure communication protocol" refers to a device or software that uses a communication protocol (e.g., HTTPS) to encrypt data and transmit it securely to a server.

[0741] "Means for using emotion recognition means to address the anxiety and doubts that users may feel during a procedure" refers to devices or software that alleviate anxiety and doubts that users may feel during a procedure by providing necessary information and support based on the user's emotional state.

[0742] This invention is a system that inputs and acquires information on income and expenses, and then proposes optimal tax-saving plans based on that information. The system has multiple functions, including income and expenditure data acquisition, analysis, plan generation, simulation, application support, and emotion recognition, and is designed to enable users to efficiently implement tax-saving measures.

[0743] Hardware and Software

[0744] User device: PC, smartphone, tablet, etc. The device where the user enters or scans their financial data.

[0745] Server: A central processing unit that performs tasks such as data analysis, tax saving plan generation, and simulations.

[0746] Emotion Recognition Engine: An AI engine (e.g., emotion recognition API) that recognizes user emotions in real time and adjusts suggestions accordingly.

[0747] OCR technology: Technology that converts scanned documents into text data (e.g., OCR API).

[0748] System configuration

[0749] The user uses the device to input or scan income and expenditure data such as pay slips and receipts. The device then uses OCR technology to convert the scanned data into text data, obtaining digital income and expenditure data. This data is then sent to a server using a secure communication protocol (e.g., HTTPS), and the user's emotional information is also collected.

[0750] The server analyzes the received income and expenditure data and categorizes it into categories such as income, expenditure, and expenses. Furthermore, the server analyzes the user's emotional data provided by the emotion recognition engine to identify the user's current emotional state. Based on this information, the server generates an optimal tax saving plan by referring to the latest tax information.

[0751] For each tax saving plan, the server simulates its effects and calculates the projected tax savings. The results are displayed graphically, and an emotion recognition engine adjusts the content and tone of the message depending on the user's emotions.

[0752] Once the user selects the desired tax saving plan, the server automatically generates the necessary application documents and sends them to the terminal. The user can download and print these documents and follow the instructions to complete the formal procedures. During the application process, the emotion recognition engine provides appropriate information and support to address any concerns or questions the user may have about the process.

[0753] Specific examples

[0754] For example, if a user provides monthly pay stubs and expense data, the following occurs:

[0755] 1. The user enters or scans their pay stub and expense information into the terminal.

[0756] 2. The device sends the income and expenditure data and the user's emotional information to the server.

[0757] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0758] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0759] 5. The device displays the best tax-saving plan and its benefits to the user, with an emotion-recognition engine customizing the display based on the user's emotions.

[0760] 6. Once the user selects the desired tax saving plan, the server generates the necessary application documents and sends them to the terminal.

[0761] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[0762] Prompt Sentence Examples

[0763] "Tell me about an income / expense data analysis system that incorporates an emotion engine that recognizes the user's emotions. Please explain the overall process flow of the system that adjusts the display format and tone according to the user's emotional state and suggests the optimal tax saving plan."

[0764] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0765] Step 1:

[0766] Acquisition of income and expenditure data

[0767] The user enters or scans income and expenditure data, such as pay stubs or receipts, into the terminal.

[0768] Input: Paper or electronic files such as pay stubs or receipts.

[0769] Output: Digital balance data converted into text data using OCR technology.

[0770] How it works: The user takes a photo of their pay slip with their smartphone and uploads it. The device then uses the OCR API to convert the image into text data, and the income and expenditure data is obtained in digital form.

[0771] Step 2:

[0772] Sending financial data and emotional information

[0773] The terminal transmits the acquired income and expenditure data and the user's emotional information to the server.

[0774] Input: Digital balance data converted using OCR technology and sentiment information collected in real time.

[0775] Output: Encrypted financial data and emotional information are sent to the server.

[0776] How it works: The device encrypts financial data and emotional information and sends it to the server using the secure HTTPS protocol.

[0777] Step 3:

[0778] Analysis of income and expenditure data and emotional information

[0779] The server analyzes the received income and expenditure data, including emotional information.

[0780] Input: Submitted digital financial data and sentiment.

[0781] Output: Analysis results categorized into categories such as income, expenditure, and expenses, along with the user's emotional state.

[0782] How it works: The server analyzes the data and automatically categorizes the balance data, while the emotion recognition engine identifies the user's emotional state.

[0783] Step 4:

[0784] Generate optimal tax saving plans

[0785] The server generates the optimal tax saving plan based on the analyzed income and expenditure data, while referring to the latest tax information.

[0786] Input: Categorised financial data and information about the user's emotional state.

[0787] Output: A proposal with multiple tax saving plans.

[0788] Specific operation: The server references the tax database and generates multiple tax-saving plans based on the user's income and expenditure data. The emotion recognition engine selects the optimal presentation method.

[0789] Step 5:

[0790] Tax saving plan simulation

[0791] The server simulates the tax saving effect of the generated tax saving plan and calculates the expected tax reduction.

[0792] Input: Each generated tax saving plan.

[0793] Output: Projected tax savings as a result of the simulation.

[0794] Specific operation: The server simulates tax reduction for each plan and outputs the results in numerical and graphical form.

[0795] Step 6:

[0796] Presentation of simulation results

[0797] The terminal will then graphically display to the user the details of the tax saving plan and its effects.

[0798] Input: Simulated tax reduction results.

[0799] Output: A visual representation of the tax saving plan and its effects to the user.

[0800] Specific operation: The device displays the simulation results in graphs and charts, and the emotion recognition engine customizes the display according to the user's emotions.

[0801] Step 7:

[0802] Support for application procedures

[0803] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal.

[0804] Input: The tax saving plan selected by the user.

[0805] Output: Auto-generated application documents.

[0806] Specific operation: The server automatically generates the necessary application documents and sends them to the terminal. The user downloads these documents, prints them, and proceeds with the procedure.

[0807] Step 8:

[0808] Support during the process

[0809] The emotion recognition engine provides information to help users deal with any concerns or doubts they may have during the process.

[0810] Input: The user's emotional state and any concerns or doubts about the procedure.

[0811] Output: Additional information or support messages.

[0812] Specific operation: The emotion recognition engine monitors the user's emotional state and displays appropriate feedback and support messages in case of anxiety or doubt.

[0813] Step 9:

[0814] Continuous data updates and plan reevaluation

[0815] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan.

[0816] Input: Newly updated income and expenditure data.

[0817] Output: Reassessed optimal tax saving plan.

[0818] Specific operation: The server periodically updates the database and re-proposes new tax-saving plans based on the latest tax information and income and expenditure data.

[0819] (Application example 2)

[0820] 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."

[0821] Today's consumers spend a great deal of time and effort managing complex income and expenditures and implementing optimal tax-saving strategies. However, existing systems often fail to consider user emotions and are often stressful, resulting in a poor user experience. Furthermore, systems lack the digitalization and security of income and expenditure data, and are not up to date with the latest tax information, leaving users without an environment in place to quickly and efficiently implement optimal tax-saving strategies. Therefore, there is a need for the development of a new system that takes user emotions into consideration and provides comprehensive support, from acquiring income and expenditure data to secure data transmission and providing tax-saving plans based on the latest tax information.

[0822] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0823] In this invention, the server includes means for acquiring income and expenditure data, means including an emotion engine for recognizing user emotions, means for using OCR technology to acquire the income and expenditure data from the user and convert it into a digital format, means for simulating the tax savings effect of the generated tax saving plan, means for adjusting the display method and message tone according to the user's emotions when graphically displaying the tax savings effect of the tax saving plan, means for securely transmitting the income and expenditure data and the generated savings plan to the server, means for learning the latest tax information and updating the database, means for using a generative AI model to provide optimal advice to the user, and means for generating prompt sentences and making optimal suggestions to the user based on the generated prompt sentences. This enables the provision of a user-friendly interface that takes user emotions into consideration, while also enabling the digitization and secure management of income and expenditure data, and the prompt sentences to be quickly and efficiently proposed to the user as optimal tax saving plans based on the latest tax information.

[0824] definition statement

[0825] "Means for acquiring income and expenditure data" refers to a means by which a user inputs or scans income and expenditure information into a terminal, and includes technology for converting that data into digital form.

[0826] The "means for analyzing the acquired income and expenditure data" includes algorithms and software for categorizing the income and expenditure data and analyzing its contents.

[0827] The "means for generating an optimal tax saving plan" includes algorithms and systems that propose the most effective tax saving measures for users based on analyzed income and expenditure data and the latest tax system information.

[0828] "Means for simulating the tax savings effect of the generated tax savings plan" includes programs and systems for calculating and evaluating the expected tax savings effect based on the generated tax savings plan.

[0829] The "means for supporting the application procedures necessary for a tax saving plan" includes a system that automatically generates application documents prepared in accordance with an optimal tax saving plan and provides them to users.

[0830] The "emotion engine that recognizes the user's emotions" includes algorithms and systems that analyze the user's emotions from their facial expressions and tone of voice, and adjust the way they respond based on that information.

[0831] "Means using OCR technology" includes technology that reads text information from paper receipts or electronic files and converts it into digital data.

[0832] "Means for securely transmitting to the server" includes technology for securely transmitting income and expenditure data and savings plans to the server using security technology such as encryption.

[0833] "Means for providing optimal advice to users using a generative AI model" includes a system that uses a generative artificial intelligence model to provide appropriate advice based on the user's income and expenditure data and emotional data.

[0834] "Means for generating prompt sentences and making optimal suggestions to users based on the generated prompt sentences" includes a system in which a generative AI model generates appropriate prompt sentences for users based on input data and makes optimal suggestions based on the content of those sentences.

[0835] MODE FOR CARRYING OUT THE INVENTION

[0836] This invention provides a system that efficiently provides savings and purchasing advice to consumers on online shopping sites. The system utilizes a means of acquiring income and expenditure data, an emotion engine, OCR technology, a secure communication protocol, and a generative AI model.

[0837] System configuration

[0838] The system includes a terminal that collects the user's income and expenditure data and converts it into digital format, a server that securely analyzes and stores this data, and an emotion engine that recognizes the user's emotions and provides appropriate advice.

[0839] Hardware and Software

[0840] Hardware: Smartphones and tablets with a camera

[0841] Software: OCR technology (e.g., pytesseract), image processing library (PIL), HTTP request library (requests), generative AI models

[0842] Data processing and calculation

[0843] 1. The user takes a photo of the receipt for the purchased item with their smartphone camera, and the device uses OCR technology to convert the balance data into a digital format, which then recognizes the receipt image as text data.

[0844] 2. The acquired balance data is sent to a server using a secure communication protocol, and the server analyzes the data using a category classification algorithm for the balance data.

[0845] 3. The server generates the optimal tax saving plan from the analyzed income and expenditure data based on the latest tax information.

[0846] 4. The emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the tone and content of the suggested advice based on the user's current emotional state.

[0847] 5. Simulate the effects of the generated tax saving plan and display the results graphically.

[0848] 6. Using the generative AI model, provide optimal purchasing advice to the user and generate specific prompts, such as "Please suggest the best savings plan based on the user's purchase history and bank statements. Please also provide encouraging messages if the user is feeling stressed."

[0849] 7. If the user selects a tax-saving plan, the server automatically generates the documents required for the application procedure and provides a download link to the device.

[0850] Specific examples

[0851] After a user shops at the supermarket, they take a photo of the receipt with their smartphone. OCR technology extracts the product names and amounts from the receipt and captures them as income and expenditure data. The user's facial expressions are analyzed, and gentle advice is offered if they appear stressed. The server analyzes the income and expenditure data and displays specific advice, such as, "Your expenses have increased this month, so next time you shop, try replacing these items with cheaper alternatives."

[0852] Through this process, users can not only easily and effectively implement savings measures, but also enjoy a less stressful shopping experience.

[0853] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0854] Detailed explanation of the processing steps

[0855] Step 1:

[0856] The user takes a photo of the receipt with the smartphone camera. The input is the receipt image, and the output is image data. Specifically, the smartphone's camera app is launched, and the user takes a photo of the receipt.

[0857] Step 2:

[0858] The terminal uses OCR technology to extract text information from receipt images and convert it into balance data. The input is image data and the output is text data. Specifically, the image is read using the PIL library and the text information is extracted using pytesseract.

[0859] Step 3:

[0860] The terminal sends the balance data to the server using a secure communication protocol. The input is text data, and the output is the data sent to the server. Specifically, the data is sent as a POST request using the HTTP request library (requests).

[0861] Step 4:

[0862] The server analyzes the received income and expenditure data and categorizes it. The input is income and expenditure data, and the output is data categorized by category. Specifically, the server analyzes the data using an income and expenditure analysis algorithm and categorizes it into categories such as income and expenditure.

[0863] Step 5:

[0864] The server generates the optimal tax saving plan based on the latest tax information. The input is the analyzed income and expenditure data, and the output is the tax saving plan. Specifically, the server refers to the latest tax database and calculates the appropriate tax saving plan.

[0865] Step 6:

[0866] The emotion engine analyzes the user's facial expression and tone of voice to determine the user's current emotional state. The input is the user's facial expression or voice data, and the output is emotional state data. Specifically, it uses an emotion analysis algorithm to determine whether the user is feeling stressed.

[0867] Step 7:

[0868] The server simulates the tax savings effect of the tax saving plan and displays the results graphically. The input is the tax saving plan, and the output is the simulation result. Specifically, it uses a simulation algorithm to calculate the tax reduction effect and generates the data necessary to display it as a graph.

[0869] Step 8:

[0870] A generative AI model is used to provide optimal purchasing advice to users and generate specific prompts. The input is income and expenditure data and emotional state data, and the output is specific prompts. Specifically, the generative AI model analyzes the input data and generates prompts such as, "Please suggest the optimal savings plan based on the user's purchase history and bank statements. Please provide an encouraging message if the user is feeling stressed."

[0871] Step 9:

[0872] When a user selects a tax-saving plan, the server automatically generates the documents required for the application procedure and provides a download link to the terminal. The input is the selected tax-saving plan, and the output is a download link for the application documents. Specifically, the server uses a document generation algorithm to create the necessary application documents, generates a link for them, and sends it to the terminal.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] [Third embodiment]

[0877] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0878] 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.

[0879] 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).

[0880] 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.

[0881] 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.

[0882] 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).

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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."

[0889] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing data, means for generating tax-saving plans, means for simulation, and means for supporting application procedures. This system is designed to enable users to easily find and efficiently implement tax-saving strategies that are optimal for them.

[0890] System configuration

[0891] The system consists of a user's terminal, a server, and related databases. The user uses the terminal to input or scan income and expenditure data, which is then sent to the server. The server analyzes the income and expenditure data, generates and simulates tax-saving plans, and sends the information back to the terminal. It also generates the documents necessary for application procedures, helping the user to complete the procedures efficiently.

[0892] Acquisition of income and expenditure data

[0893] 1. Data Entry / Scanning:

[0894] Users manually enter income and expense information into the device or scan paper documents or electronic files, such as pay slips or household receipts.

[0895] The terminal uses OCR technology to convert the scanned data into text data, and obtains the income and expenditure data in digital format.

[0896] Sending and analyzing income and expenditure data

[0897] 2. Data transmission:

[0898] The terminal transmits the acquired balance data to the server using a secure communication protocol.

[0899] 3. Data Analysis:

[0900] The server analyzes the received income and expenditure data and categorizes it into categories such as income, expenditure, expenses, medical expenses, education expenses, etc. This allows the user's income and expenditure situation to be understood in detail.

[0901] Tax saving plan generation and simulation

[0902] 4. Generate tax saving plans:

[0903] The server generates an optimal tax-saving plan based on the user's income and expenditure data, taking into account the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, and mortgage deductions.

[0904] 5. Simulation:

[0905] The server simulates the tax savings effect of each tax saving plan and presents it to the user. The simulation results include predicted tax reductions and comparative information based on the plan selected by the user.

[0906] Support for application procedures

[0907] 6. Document generation and submission:

[0908] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal, where the user can download and print these documents and complete the necessary procedures.

[0909] Ongoing support

[0910] 7. Periodic Data Updates and Plan Reassessment:

[0911] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. By re-proposing the optimal tax saving plan based on new data and changes in the tax system, the user can always implement tax saving measures that are adapted to the latest tax system.

[0912] Specific examples

[0913] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0914] 1. The user enters or scans their pay stub and expense information into the terminal.

[0915] 2. The terminal sends the balance data to the server.

[0916] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0917] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0918] 5. The device will display the best tax saving plan for the user and its effects.

[0919] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the terminal.

[0920] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[0921] This system allows users to automatically and efficiently take the best possible tax-saving measures.

[0922] The processing flow will be explained below.

[0923] Step 1:

[0924] The user collects income and expense data and manually enters it into the terminal or scans it.

[0925] Step 2:

[0926] The device uses OCR technology to convert scanned documents into text data, obtaining income and expenditure data in digital format.

[0927] Step 3:

[0928] The terminal transmits the collected data to the server using a secure communication protocol.

[0929] Step 4:

[0930] The server analyzes the received income and expenditure data and automatically classifies it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[0931] Step 5:

[0932] The server checks the data for inconsistencies and cleanses it as needed, including removing duplicate data and standardizing formats.

[0933] Step 6:

[0934] The server learns the latest tax information and generates the optimal tax-saving plan based on that information. For example, it suggests plans that include medical expense deductions and donation deductions.

[0935] Step 7:

[0936] The server simulates the tax savings effect of each tax saving plan and calculates the expected tax reduction.

[0937] Step 8:

[0938] The server sends the simulation results along with the optimal tax saving plan to the terminal.

[0939] Step 9:

[0940] The device graphically displays details of tax-saving plans and their effects to users, allowing them to intuitively understand the comparison of each plan.

[0941] Step 10:

[0942] The user selects the desired tax saving plan.

[0943] Step 11:

[0944] The server automatically generates the necessary application documents based on the selected tax saving plan, and also lists the necessary attachments.

[0945] Step 12:

[0946] The server sends the generated application documents to the terminal.

[0947] Step 13:

[0948] The terminal presents the application documents to the user and instructs them to download and print them.

[0949] Step 14:

[0950] The user downloads the generated documents and follows the instructions to complete the application process.

[0951] Step 15:

[0952] The server periodically updates income and expenditure data and incorporates new data to support ongoing tax-saving measures.

[0953] Step 16:

[0954] The server reevaluates the tax saving plan based on new income and expenditure data and changes in tax systems, and proposes a new plan to the user as necessary.

[0955] In this way, users can efficiently manage their income and expenditure data and easily take optimal tax-saving measures.

[0956] Example 1

[0957] 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."

[0958] The present invention relates to a system that supports individuals or corporations in efficiently implementing tax-saving measures. Conventional tax-saving measures are complex, requiring the management of numerous documents and an understanding of the tax system, making it difficult for individual users to find the optimal tax-saving plan. Furthermore, it is difficult to obtain a plan that constantly reflects the latest tax system information, resulting in ineffective tax savings. This has led to the problem that many users end up making wasteful expenditures and failing to implement appropriate tax-saving measures.

[0959] 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.

[0960] In this invention, the server includes means for acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting application procedures required for the tax saving plan, means for converting the income and expenditure data into text data using OCR technology, means for transmitting the income and expenditure data to the server using a secure communication protocol, means for learning the latest tax information using a generative AI model and generating a tax saving plan, means for periodically updating the income and expenditure data and reevaluating the tax saving plan, and means for presenting the simulation results to the user. This allows users to easily input income and expenditure data and efficiently obtain an optimal tax saving plan based on the latest tax information.

[0961] "Income and Expenditure Data" means information relating to income and expenditures that indicates the financial position of an individual or entity.

[0962] "Capture means" refers to the functionality of a device or software for inputting or scanning and collecting financial data from a user.

[0963] "Analysis means" refers to the function of a device or software that categorizes and performs statistical analysis based on the acquired income and expenditure data.

[0964] A "tax saving plan" refers to a specific plan that suggests ways and strategies to reduce tax based on the user's income and expenditure data.

[0965] "Simulation means" refers to the functionality of a device or software that predicts the effects of a generated tax saving plan and calculates the specific tax savings and benefits.

[0966] "Means to support application procedures" refers to auxiliary functions that allow users to prepare the necessary documents and carry out application procedures efficiently.

[0967] "OCR technology" refers to optical character recognition technology, which extracts text data from scanned images.

[0968] "Secure communication protocol" refers to a communication protocol that ensures security when sending and receiving data, and includes, for example, HTTPS.

[0969] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and operate for a specific purpose (in this case, learning tax information or generating tax-saving plans).

[0970] "Latest tax information" refers to the latest tax rules and information, including tax laws and deduction provisions in effect at the time.

[0971] "Database" refers to a collection of collected and stored data that allows the system to efficiently manage and use the information it needs.

[0972] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing data, means for generating tax-saving plans, means for simulation, and means for supporting application procedures. This system is designed to enable individuals or corporations to efficiently find and implement optimal tax-saving strategies. Each means will be specifically described below.

[0973] How to obtain income and expenditure data

[0974] Users enter or scan financial data using their device. For example, they can take a photo of a pay slip, receipt, or other financial document with their smartphone camera and import it into the app. The device then converts this data into text using OCR (optical character recognition) technology. Software such as Tesseract OCR can be used to extract text from the scanned image.

[0975] Data transmission method

[0976] The terminal transmits the acquired and converted balance data to the server via a secure communication protocol (e.g., HTTPS), which prevents data leakage and unauthorized access.

[0977] Data analysis methods

[0978] The server analyzes the received data, for example, by using the Python Pandas library to classify the data into different categories (income, expenditure, expenses, medical expenses, education expenses, etc.) to obtain a detailed understanding of the user's financial situation. The results of this analysis are then used to generate a tax saving plan.

[0979] Tax saving plan generation tool

[0980] The server uses the generative AI model to learn the latest tax information and update the database. This allows the server to generate optimal tax-saving plans based on the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, and mortgage deductions.

[0981] Simulation Method

[0982] The server simulates the tax savings effect of the generated tax saving plans. Using Python's NumPy library, it calculates the predicted tax reduction effect of each plan and presents it to the user. The simulation results include the effects and benefits of each plan.

[0983] Support for application procedures

[0984] The server automatically generates the application documents required for the tax-saving plan selected by the user and sends them to the terminal. The application documents are created in PDF format using the PyPDF2 library, etc. The user downloads and prints these documents and follows the instructions to complete the application process.

[0985] Ongoing support measures

[0986] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan based on the latest tax information, thereby always providing the optimal tax saving strategy.

[0987] Specific examples

[0988] For example, after a user provides their monthly pay stub and expense data, the following happens:

[0989] 1. The user enters or scans their pay stub and expense information into the device, for example, by taking a photo of their pay stub using their smartphone camera and scanning it into the app.

[0990] 2. The device uses OCR technology to convert the scanned data into text data and sends that data to the server.

[0991] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[0992] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[0993] 5. The device will display the best tax saving plan for the user and its effects.

[0994] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the terminal.

[0995] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[0996] Prompt Sentence Examples

[0997] "Please enter or scan the data from your monthly pay slip and household ledger according to the following headings: income, expenditures, expenses, medical expenses, and education expenses."

[0998] This system allows users to automatically and efficiently take the best tax-saving measures.

[0999] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1000] Step 1:

[1001] Data Entry / Scanning

[1002] The user manually enters income and expense information into the device, or scans a paper document or electronic file. For example, they take a picture of a pay slip or receipt with their smartphone camera and scan it into the app. The input data includes income amount, expense amount, and expense category. The device then converts the scanned data into text data using OCR technology. For example, Tesseract OCR can be used to extract text from an image of a pay slip. This text data is then passed to the next processing step.

[1003] Step 2:

[1004] Data transmission

[1005] The terminal sends the acquired and converted balance data to the server using a secure communication protocol (e.g., HTTPS). The input data includes the text data obtained in step 1. Using a secure communication protocol prevents data leakage and unauthorized access. The balance data is securely passed to the server through this communication.

[1006] Step 3:

[1007] Data analysis

[1008] The server analyzes the received income and expenditure data. The input data includes the transmitted income and expenditure data (income, expenditure, expense items, etc.). Using Python's Pandas library, the data is classified into categories such as income, expenditure, expenses, medical expenses, and education expenses. For example, data such as "Salary: 300,000 yen," "Rent: 80,000 yen," and "Medical expenses: 10,000 yen" are classified into the appropriate categories. The classification results are passed to the next step.

[1009] Step 4:

[1010] Generate tax saving plans

[1011] The server uses the generative AI model to learn the latest tax information and update the database. The input data includes the analysis data obtained in step 3 and the latest tax information. Based on this, the optimal tax saving plan is generated. For example, the applicability of medical expense deductions, donation deductions, mortgage deductions, etc. is evaluated and each plan is generated. The generated results are passed to the next step.

[1012] Step 5:

[1013] simulation

[1014] The server simulates the tax savings effect of each tax saving plan generated. The input data includes each tax saving plan generated in step 4. Using Python's NumPy library, the tax reduction effect of each plan is calculated and presented to the user. For example, the simulation result obtained is "medical expense deductions can save 50,000 yen per year in taxes." This result is passed to the next step.

[1015] Step 6:

[1016] Support for application procedures

[1017] The server automatically generates the application documents required for the tax saving plan selected by the user and sends them to the terminal. The input data includes the simulation results from step 5 and the selected tax saving plan. The server uses the PyPDF2 library to create the application documents in PDF format. For example, it creates "Medical Expense Deduction Application Form.pdf" and sends it to the terminal. The user downloads this document, prints it, fills in the necessary information, and proceeds with the application procedure.

[1018] Step 7:

[1019] Ongoing support

[1020] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan based on new data and changes in the tax system. The input data includes the latest income and expenditure data and the latest tax system information. Based on this, a new tax saving plan is proposed. For example, new analysis results such as "new medical expense deductions are applicable" are provided.

[1021] (Application example 1)

[1022] 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."

[1023] Conventional tax saving systems require users to manually input income and expenditure data, select a tax saving plan, and complete the necessary application procedures, which is time-consuming and labor-intensive. Furthermore, there is no system that collects and analyzes electronic payment data in real time and proposes optimal tax saving plans. This makes it difficult for users to efficiently implement tax saving measures and find the appropriate plan.

[1024] 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.

[1025] In this invention, the server includes means for acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting the application procedures required for the tax saving plan, means for collecting and analyzing electronic payment data in real time, means for categorizing the collected data, means for notifying the user of the tax saving plan, and means for supporting the application procedures with a reminder function. This enables the user to automatically and efficiently find the optimal tax saving plan and smoothly complete the application procedures.

[1026] "Means for obtaining income and expenditure data" refers to means for collecting data on income and expenditure from users.

[1027] The "means for analyzing the acquired income and expenditure data" is a means for analyzing the collected income and expenditure data and classifying it by category.

[1028] The "means for generating an optimal tax saving plan" is a means for proposing the most effective tax saving measures for the user based on analyzed income and expenditure data.

[1029] The "means for simulating the tax saving effect of a tax saving plan" is a means for predicting the effect of the generated tax saving plan and presenting the results to the user.

[1030] "Means to support application procedures" refers to means to automatically generate the necessary application documents based on the tax saving plan selected by the user and to assist with the procedures.

[1031] "Means for collecting and analyzing electronic payment data in real time" refers to means for automatically obtaining data from a user's electronic payment service and analyzing it immediately.

[1032] The "means for categorizing collected data" is a means for classifying collected income and expenditure data into categories such as income, expenditure, medical expenses, and education expenses.

[1033] The "means for notifying the user of the tax saving plan" is a means for notifying the user of the generated tax saving plan and the results of its simulation.

[1034] "Means of supporting application procedures with a reminder function" refers to a means of notifying users of deadlines and important points to note when completing application procedures.

[1035] The present invention is a system that includes means for acquiring income and expenditure data, means for analysis, means for generating tax-saving plans, means for simulation, and means for supporting application procedures, thereby enabling users to easily find optimal tax-saving strategies and implement them efficiently.

[1036] System configuration

[1037] The system consists of a user's device, a server, and related databases. Users use their device to input or scan income and expenditure data, which is then sent to the server. The server analyzes the data, generates and simulates tax-saving plans, and sends the information back to the device. It also generates the documents necessary for the application process, helping users complete the process efficiently.

[1038] Acquisition of income and expenditure data

[1039] Users manually enter income and expense information into the terminal or scan paper documents or electronic files, such as pay slips or receipts. The terminal then uses OCR technology to convert the scanned data into text data, providing digital income and expenditure data. It also integrates with electronic payment services to collect transaction data in real time.

[1040] Data transmission and analysis

[1041] The device sends the acquired data to a server using a secure communication protocol. The server analyzes the data and categorizes it into categories such as income, expenses, medical expenses, and education expenses. This allows the user to understand their financial situation in detail.

[1042] Tax saving plan generation and simulation

[1043] The server generates an optimal tax-saving plan based on the user's income and expenditure data, using the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, mortgage deductions, etc. The server then simulates the tax savings effect of each generated tax-saving plan and presents it to the user. The simulation results include predicted tax reductions and comparative information based on the plan selected by the user.

[1044] Support for application procedures

[1045] The server automatically generates the application documents required for the selected tax-saving plan and sends them to the terminal. The user downloads and prints these documents and completes the necessary procedures. The application process is also supported by a reminder function, notifying the user of deadlines and important points to note.

[1046] Ongoing support

[1047] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. Based on new data and changes in the tax system, the server re-proposes the optimal tax saving plan, ensuring that the user can always take tax saving measures that are adapted to the latest tax system.

[1048] Specific processing examples

[1049] For example, after a user provides their monthly pay stub and expense data, the following happens:

[1050] 1. The user enters or scans their pay stub and expense information into the terminal.

[1051] 2. The device sends the balance data to the server.

[1052] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[1053] 4. The server generates multiple tax-saving plans based on the data and simulates the tax savings effect of each.

[1054] 5. The device will display the best tax saving plan for the user and its benefits.

[1055] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the device.

[1056] 7. The user downloads the application form and follows the instructions to complete the procedure.

[1057] Hardware and software used

[1058] The hardware used is mainly user devices such as smartphones and tablets, while the software used is OCR technology for acquiring income and expenditure data, algorithms for analyzing the collected data, a database for generating tax-saving plans, and a program for simulation.

[1059] Prompt Sentence Examples

[1060] Please provide a concrete example of an application that automatically collects and analyzes income and expenditure data, generates a tax-saving plan, and simulates its effectiveness. If user "example_user_id" uses an electronic payment service, please show data collection, classification, tax-saving plan proposal, and simulation results.

[1061] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1062] Step 1:

[1063] The user inputs or scans income and expenditure data. The user manually inputs income and expenditure information, such as pay slips or receipts, into the device or scans documents. Input data includes income amounts, expense items, dates, etc. The output is the income and expenditure data in digital form.

[1064] Step 2:

[1065] The terminal uses OCR technology to convert the scanned data into text data. The terminal then performs OCR processing on the scanned image data and extracts the balance information as text data. The input is the scanned data, and the output is the balance data in text format.

[1066] Step 3:

[1067] The terminal transmits the acquired balance data to the server. The collected data (text-format balance data) is sent to the server using a secure communication protocol. The input is the text-format balance data, and the output is the data transmitted to the server.

[1068] Step 4:

[1069] The server analyzes the received data and runs an algorithm to classify it into categories such as income, expenses, medical expenses, and education expenses. The input is text-formatted data, and the output is the categorized data.

[1070] Step 5:

[1071] The server generates the optimal tax saving plan based on the latest tax system information. It references the tax system information stored in the database and identifies applicable tax saving measures based on the user's income and expenditure data. The input is categorized income and expenditure data and tax system information, and the output is candidate tax saving plans.

[1072] Step 6:

[1073] The server simulates the tax savings effect of each generated tax saving plan. It calculates the savings effect of each plan and performs a simulation to present it to the user. The input is the tax saving plan, and the output is the tax savings effect as a result of the simulation.

[1074] Step 7:

[1075] The terminal notifies the user of the optimal tax saving plan and the simulation results. The terminal interface shows the plans the user can choose from and their effects. The input is the simulation results, and the output is the information notified to the user.

[1076] Step 8:

[1077] Based on the plan selected by the user, the server automatically generates the necessary application documents. The generated application documents are sent to the terminal, where the user can download and print them. The input is the selected tax saving plan, and the output is the generated application documents.

[1078] Step 9:

[1079] The terminal supports the application procedure with a reminder function. It provides a reminder function that notifies the user of the deadline for submitting application documents and any additional information that is required. The input is the application schedule information, and the output is the reminder notified to the user.

[1080] Prompt Sentence Examples

[1081] Please provide a concrete example of an application that automatically collects and analyzes income and expenditure data, generates a tax-saving plan, and simulates its effectiveness. If user "example_user_id" uses an electronic payment service, please show data collection, classification, tax-saving plan proposal, and simulation results.

[1082] 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.

[1083] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing it, means for generating tax-saving plans, means for simulation, and means for supporting application procedures, as well as an emotion engine that recognizes the user's emotions. This system is designed to enable users to easily find and efficiently implement tax-saving strategies that are best suited to them. Furthermore, the emotion engine customizes the system's responses according to the user's emotional state, providing a more effective experience.

[1084] System configuration

[1085] The system consists of a user's device, a server, related databases, and an emotion engine that recognizes the user's emotions. The user uses the device to input or scan income and expenditure data and transmits the data to the server. The emotion engine simultaneously analyzes the user's emotions, and the server receives and analyzes this data, generating and simulating an optimal tax-saving plan. The system also generates the documents necessary for the application process, helping the user to complete the process efficiently.

[1086] Acquisition of income and expenditure data

[1087] 1. Data Entry / Scanning:

[1088] Users manually enter income and expense information into the device or scan paper documents or electronic files, such as pay slips or household receipts.

[1089] The terminal uses OCR technology to convert the scanned data into text data, and obtains the income and expenditure data in digital format.

[1090] Sending and analyzing income and expenditure data

[1091] 2. Data transmission:

[1092] The device transmits the acquired income and expenditure data and the user's emotional information to the server via a secure communication protocol.

[1093] 3. Data Analysis:

[1094] The server analyzes the received income and expenditure data and automatically categorizes it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[1095] The server simultaneously analyzes the user's emotional data to determine the user's current emotional state.

[1096] Tax saving plan generation and simulation

[1097] 4. Generate tax saving plans:

[1098] The server generates an optimal tax-saving plan based on the user's income and expenditure data, taking into account the latest tax information. For example, it suggests plans that include medical expense deductions, donation deductions, and mortgage deductions.

[1099] The emotion engine selects an appropriate plan presentation method based on the user's emotional state.

[1100] 5. Simulation:

[1101] The server simulates the tax savings effect of each generated tax saving plan and calculates the expected tax reduction.

[1102] Presentation of simulation results

[1103] 6. Presentation of results:

[1104] The device graphically displays details of the tax-saving plan and its benefits to the user, while the emotion engine adjusts the display and tone of the message depending on the user's emotions. For example, if the user is feeling stressed, the display will be more concise and reassuring.

[1105] Support for application procedures

[1106] 7. Document generation and submission:

[1107] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal, where the user can download and print these documents and complete the necessary procedures.

[1108] The emotion engine provides additional information and support to address any concerns or questions users may have during the process.

[1109] Ongoing support

[1110] 8. Periodic Data Updates and Plan Reassessment:

[1111] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. By re-proposing the optimal tax saving plan based on new data and changes in the tax system, the user can always implement tax saving measures that are adapted to the latest tax system.

[1112] Specific examples

[1113] For example, after a user provides their monthly pay stub and expense data, the following happens:

[1114] 1. The user enters or scans their pay stub and expense information into the terminal.

[1115] 2. The device sends the income and expenditure data and the user's emotional information to the server.

[1116] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[1117] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[1118] 5. The device displays the optimal tax saving plan and its benefits to the user, with the emotion engine customizing the display based on the user's emotions.

[1119] 6. Once the user selects the desired tax saving plan, the server generates the necessary application documents and sends them to the terminal.

[1120] 7. The user downloads the application documents and follows the instructions to complete the procedure. Through this process, the user can automatically and effectively take optimal tax-saving measures.

[1121] The processing flow will be explained below.

[1122] Step 1:

[1123] The user collects income and expense data and manually enters it into the terminal or scans it.

[1124] Step 2:

[1125] The device uses OCR technology to convert scanned documents into text data, obtaining income and expenditure data in digital format.

[1126] Step 3:

[1127] The device transmits the collected data and the user's emotional information recognized by the emotion engine to the server using a secure communication protocol.

[1128] Step 4:

[1129] The server analyzes the received income and expenditure data and automatically classifies it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[1130] Step 5:

[1131] The server checks the data for inconsistencies and cleanses it as needed, including removing duplicate data and standardizing formats.

[1132] Step 6:

[1133] The server learns the latest tax information and generates the optimal tax-saving plan based on that information. For example, it suggests plans that include medical expense deductions, donation deductions, and mortgage deductions.

[1134] Step 7:

[1135] The server simulates the tax savings effect of each tax saving plan and calculates the expected tax reduction.

[1136] Step 8:

[1137] The server sends the simulation results along with the optimal tax saving plan to the terminal.

[1138] Step 9:

[1139] The device graphically displays details of the tax-saving plan and its benefits to the user, while an emotion engine adjusts the display and tone of the message based on the user's emotions. For example, if the user is feeling stressed, the display will be more concise and reassuring.

[1140] Step 10:

[1141] The user selects the desired tax saving plan.

[1142] Step 11:

[1143] The server automatically generates the necessary application documents based on the selected tax saving plan, and also lists the necessary attachments.

[1144] Step 12:

[1145] The server sends the generated application documents to the terminal.

[1146] Step 13:

[1147] The terminal presents the application documents to the user and instructs them to download and print them.

[1148] Step 14:

[1149] The user downloads the generated documents and follows the instructions to complete the application process.

[1150] Step 15:

[1151] The server periodically updates income and expenditure data and incorporates new data to support ongoing tax-saving measures.

[1152] Step 16:

[1153] The server reevaluates the tax saving plan based on new income and expenditure data and changes in tax systems, and proposes a new plan to the user as necessary.

[1154] In this way, users can efficiently manage their income and expenditure data and easily take optimal tax-saving measures. Furthermore, the emotion engine provides detailed support according to the user's emotions, improving the user experience.

[1155] Example 2

[1156] 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."

[1157] Previously, there were systems that proposed tax-saving plans based on income and expenditure data, but they lacked careful consideration for the user's emotional state. Furthermore, security considerations were insufficient, and a system that users could use with peace of mind was needed. In addition, there was a lack of support for addressing the anxieties and questions users had during the application process, making improving the user experience an urgent issue.

[1158] 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 acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting the application procedures required for the tax saving plan, emotion recognition means for recognizing the user's emotion and customizing the proposal content based on the emotion, means for transmitting data to the server using a secure communication protocol, and means for using the emotion recognition means to address any anxieties or questions the user may have during the procedure. This allows the user to use the system with peace of mind, find the optimal tax saving plan for themselves, and efficiently implement it.

[1159] "Income and expenditure data capture means" refers to a device or software that allows a user to input or scan information about income and expenses and capture it in digital form.

[1160] "Means for analyzing acquired income and expenditure data" refers to a device or software that performs a process of analyzing income and expenditure data and automatically classifying it into categories such as income, expenditure, and expenses.

[1161] The "means for generating an optimal tax saving plan" refers to a device or software that proposes an optimal tax saving plan to a user based on analyzed income and expenditure data and taking into account the latest tax system information.

[1162] "Means for simulating the tax saving effect of a tax saving plan" refers to a device or software that simulates the effect of a generated tax saving plan using numerical values, graphs, etc., and calculates the predicted tax reduction.

[1163] "Application procedure support means" refers to a device or software that automatically generates the application documents required for a tax-saving plan and provides assistance to users in downloading, printing, and properly completing the application documents.

[1164] "Emotion recognition means that recognizes a user's emotions and customizes the content of suggestions based on those emotions" refers to a device or software that analyzes a user's emotional state in real time and adjusts the content of suggestions and the display method based on the results.

[1165] "Means for transmitting data to a server using a secure communication protocol" refers to a device or software that uses a communication protocol (e.g., HTTPS) to encrypt data and transmit it securely to a server.

[1166] "Means for using emotion recognition means to address the anxiety and doubts that users may feel during a procedure" refers to devices or software that alleviate anxiety and doubts that users may feel during a procedure by providing necessary information and support based on the user's emotional state.

[1167] This invention is a system that inputs and acquires information on income and expenses, and then proposes optimal tax-saving plans based on that information. The system has multiple functions, including income and expenditure data acquisition, analysis, plan generation, simulation, application support, and emotion recognition, and is designed to enable users to efficiently implement tax-saving measures.

[1168] Hardware and Software

[1169] User device: PC, smartphone, tablet, etc. The device where the user enters or scans their financial data.

[1170] Server: A central processing unit that performs tasks such as data analysis, tax saving plan generation, and simulations.

[1171] Emotion Recognition Engine: An AI engine (e.g., emotion recognition API) that recognizes user emotions in real time and adjusts suggestions accordingly.

[1172] OCR technology: Technology that converts scanned documents into text data (e.g., OCR API).

[1173] System configuration

[1174] The user uses the device to input or scan income and expenditure data such as pay slips and receipts. The device then uses OCR technology to convert the scanned data into text data, obtaining digital income and expenditure data. This data is then sent to a server using a secure communication protocol (e.g., HTTPS), and the user's emotional information is also collected.

[1175] The server analyzes the received income and expenditure data and categorizes it into categories such as income, expenditure, and expenses. Furthermore, the server analyzes the user's emotional data provided by the emotion recognition engine to identify the user's current emotional state. Based on this information, the server generates an optimal tax saving plan by referring to the latest tax information.

[1176] For each tax saving plan, the server simulates its effects and calculates the projected tax savings. The results are displayed graphically, and an emotion recognition engine adjusts the content and tone of the message depending on the user's emotions.

[1177] Once the user selects the desired tax saving plan, the server automatically generates the necessary application documents and sends them to the terminal. The user can download and print these documents and follow the instructions to complete the formal procedures. During the application process, the emotion recognition engine provides appropriate information and support to address any concerns or questions the user may have about the process.

[1178] Specific examples

[1179] For example, if a user provides monthly pay stubs and expense data, the following occurs:

[1180] 1. The user enters or scans their pay stub and expense information into the terminal.

[1181] 2. The device sends the income and expenditure data and the user's emotional information to the server.

[1182] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[1183] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[1184] 5. The device displays the best tax-saving plan and its benefits to the user, with an emotion-recognition engine customizing the display based on the user's emotions.

[1185] 6. Once the user selects the desired tax saving plan, the server generates the necessary application documents and sends them to the terminal.

[1186] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[1187] Prompt Sentence Examples

[1188] "Tell me about an income / expense data analysis system that incorporates an emotion engine that recognizes the user's emotions. Please explain the overall process flow of the system that adjusts the display format and tone according to the user's emotional state and suggests the optimal tax saving plan."

[1189] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1190] Step 1:

[1191] Acquisition of income and expenditure data

[1192] The user enters or scans income and expenditure data, such as pay stubs or receipts, into the terminal.

[1193] Input: Paper or electronic files such as pay stubs or receipts.

[1194] Output: Digital balance data converted into text data using OCR technology.

[1195] How it works: The user takes a photo of their pay slip with their smartphone and uploads it. The device then uses the OCR API to convert the image into text data, and the income and expenditure data is obtained in digital form.

[1196] Step 2:

[1197] Sending financial data and emotional information

[1198] The terminal transmits the acquired income and expenditure data and the user's emotional information to the server.

[1199] Input: Digital balance data converted using OCR technology and sentiment information collected in real time.

[1200] Output: Encrypted financial data and emotional information are sent to the server.

[1201] How it works: The device encrypts financial data and emotional information and sends it to the server using the secure HTTPS protocol.

[1202] Step 3:

[1203] Analysis of income and expenditure data and emotional information

[1204] The server analyzes the received income and expenditure data, including emotional information.

[1205] Input: Submitted digital financial data and sentiment.

[1206] Output: Analysis results categorized into categories such as income, expenditure, and expenses, along with the user's emotional state.

[1207] How it works: The server analyzes the data and automatically categorizes the balance data, while the emotion recognition engine identifies the user's emotional state.

[1208] Step 4:

[1209] Generate optimal tax saving plans

[1210] The server generates the optimal tax saving plan based on the analyzed income and expenditure data, while referring to the latest tax information.

[1211] Input: Categorised financial data and information about the user's emotional state.

[1212] Output: A proposal with multiple tax saving plans.

[1213] Specific operation: The server references the tax database and generates multiple tax-saving plans based on the user's income and expenditure data. The emotion recognition engine selects the optimal presentation method.

[1214] Step 5:

[1215] Tax saving plan simulation

[1216] The server simulates the tax saving effect of the generated tax saving plan and calculates the expected tax reduction.

[1217] Input: Each generated tax saving plan.

[1218] Output: Projected tax savings as a result of the simulation.

[1219] Specific operation: The server simulates tax reduction for each plan and outputs the results in numerical and graphical form.

[1220] Step 6:

[1221] Presentation of simulation results

[1222] The terminal will then graphically display to the user the details of the tax saving plan and its effects.

[1223] Input: Simulated tax reduction results.

[1224] Output: A visual representation of the tax saving plan and its effects to the user.

[1225] Specific operation: The device displays the simulation results in graphs and charts, and the emotion recognition engine customizes the display according to the user's emotions.

[1226] Step 7:

[1227] Support for application procedures

[1228] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal.

[1229] Input: The tax saving plan selected by the user.

[1230] Output: Auto-generated application documents.

[1231] Specific operation: The server automatically generates the necessary application documents and sends them to the terminal. The user downloads these documents, prints them, and proceeds with the procedure.

[1232] Step 8:

[1233] Support during the process

[1234] The emotion recognition engine provides information to help users deal with any concerns or doubts they may have during the process.

[1235] Input: The user's emotional state and any concerns or doubts about the procedure.

[1236] Output: Additional information or support messages.

[1237] Specific operation: The emotion recognition engine monitors the user's emotional state and displays appropriate feedback and support messages in case of anxiety or doubt.

[1238] Step 9:

[1239] Continuous data updates and plan reevaluation

[1240] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan.

[1241] Input: Newly updated income and expenditure data.

[1242] Output: Reassessed optimal tax saving plan.

[1243] Specific operation: The server periodically updates the database and re-proposes new tax-saving plans based on the latest tax information and income and expenditure data.

[1244] (Application example 2)

[1245] 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."

[1246] Today's consumers spend a great deal of time and effort managing complex income and expenditures and implementing optimal tax-saving strategies. However, existing systems often fail to consider user emotions and are often stressful, resulting in a poor user experience. Furthermore, systems lack the digitalization and security of income and expenditure data, and are not up to date with the latest tax information, leaving users without an environment in place to quickly and efficiently implement optimal tax-saving strategies. Therefore, there is a need for the development of a new system that takes user emotions into consideration and provides comprehensive support, from acquiring income and expenditure data to secure data transmission and providing tax-saving plans based on the latest tax information.

[1247] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1248] In this invention, the server includes means for acquiring income and expenditure data, means including an emotion engine for recognizing user emotions, means for using OCR technology to acquire the income and expenditure data from the user and convert it into a digital format, means for simulating the tax savings effect of the generated tax saving plan, means for adjusting the display method and message tone according to the user's emotions when graphically displaying the tax savings effect of the tax saving plan, means for securely transmitting the income and expenditure data and the generated savings plan to the server, means for learning the latest tax information and updating the database, means for using a generative AI model to provide optimal advice to the user, and means for generating prompt sentences and making optimal suggestions to the user based on the generated prompt sentences. This enables the provision of a user-friendly interface that takes user emotions into consideration, while also enabling the digitization and secure management of income and expenditure data, and the prompt sentences to be quickly and efficiently proposed to the user as optimal tax saving plans based on the latest tax information.

[1249] definition statement

[1250] "Means for acquiring income and expenditure data" refers to a means by which a user inputs or scans income and expenditure information into a terminal, and includes technology for converting that data into digital form.

[1251] The "means for analyzing the acquired income and expenditure data" includes algorithms and software for categorizing the income and expenditure data and analyzing its contents.

[1252] The "means for generating an optimal tax saving plan" includes algorithms and systems that propose the most effective tax saving measures for users based on analyzed income and expenditure data and the latest tax system information.

[1253] "Means for simulating the tax savings effect of the generated tax savings plan" includes programs and systems for calculating and evaluating the expected tax savings effect based on the generated tax savings plan.

[1254] The "means for supporting the application procedures necessary for a tax saving plan" includes a system that automatically generates application documents prepared in accordance with an optimal tax saving plan and provides them to users.

[1255] The "emotion engine that recognizes the user's emotions" includes algorithms and systems that analyze the user's emotions from their facial expressions and tone of voice, and adjust the way they respond based on that information.

[1256] "Means using OCR technology" includes technology that reads text information from paper receipts or electronic files and converts it into digital data.

[1257] "Means for securely transmitting to the server" includes technology for securely transmitting income and expenditure data and savings plans to the server using security technology such as encryption.

[1258] "Means for providing optimal advice to users using a generative AI model" includes a system that uses a generative artificial intelligence model to provide appropriate advice based on the user's income and expenditure data and emotional data.

[1259] "Means for generating prompt sentences and making optimal suggestions to users based on the generated prompt sentences" includes a system in which a generative AI model generates appropriate prompt sentences for users based on input data and makes optimal suggestions based on the content of those sentences.

[1260] MODE FOR CARRYING OUT THE INVENTION

[1261] This invention provides a system that efficiently provides savings and purchasing advice to consumers on online shopping sites. The system utilizes a means of acquiring income and expenditure data, an emotion engine, OCR technology, a secure communication protocol, and a generative AI model.

[1262] System configuration

[1263] The system includes a terminal that collects the user's income and expenditure data and converts it into digital format, a server that securely analyzes and stores this data, and an emotion engine that recognizes the user's emotions and provides appropriate advice.

[1264] Hardware and Software

[1265] Hardware: Smartphones and tablets with a camera

[1266] Software: OCR technology (e.g., pytesseract), image processing library (PIL), HTTP request library (requests), generative AI models

[1267] Data processing and calculation

[1268] 1. The user takes a photo of the receipt for the purchased item with their smartphone camera, and the device uses OCR technology to convert the balance data into a digital format, which then recognizes the receipt image as text data.

[1269] 2. The acquired balance data is sent to a server using a secure communication protocol, and the server analyzes the data using a category classification algorithm for the balance data.

[1270] 3. The server generates the optimal tax saving plan from the analyzed income and expenditure data based on the latest tax information.

[1271] 4. The emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the tone and content of the suggested advice based on the user's current emotional state.

[1272] 5. Simulate the effects of the generated tax saving plan and display the results graphically.

[1273] 6. Using the generative AI model, provide optimal purchasing advice to the user and generate specific prompts, such as "Please suggest the best savings plan based on the user's purchase history and bank statements. Please also provide encouraging messages if the user is feeling stressed."

[1274] 7. If the user selects a tax-saving plan, the server automatically generates the documents required for the application procedure and provides a download link to the device.

[1275] Specific examples

[1276] After a user shops at the supermarket, they take a photo of the receipt with their smartphone. OCR technology extracts the product names and amounts from the receipt and captures them as income and expenditure data. The user's facial expressions are analyzed, and gentle advice is offered if they appear stressed. The server analyzes the income and expenditure data and displays specific advice, such as, "Your expenses have increased this month, so next time you shop, try replacing these items with cheaper alternatives."

[1277] Through this process, users can not only easily and effectively implement savings measures, but also enjoy a less stressful shopping experience.

[1278] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1279] Detailed explanation of the processing steps

[1280] Step 1:

[1281] The user takes a photo of the receipt with the smartphone camera. The input is the receipt image, and the output is image data. Specifically, the smartphone's camera app is launched, and the user takes a photo of the receipt.

[1282] Step 2:

[1283] The terminal uses OCR technology to extract text information from receipt images and convert it into balance data. The input is image data and the output is text data. Specifically, the image is read using the PIL library and the text information is extracted using pytesseract.

[1284] Step 3:

[1285] The terminal sends the balance data to the server using a secure communication protocol. The input is text data, and the output is the data sent to the server. Specifically, the data is sent as a POST request using the HTTP request library (requests).

[1286] Step 4:

[1287] The server analyzes the received income and expenditure data and categorizes it. The input is income and expenditure data, and the output is data categorized by category. Specifically, the server analyzes the data using an income and expenditure analysis algorithm and categorizes it into categories such as income and expenditure.

[1288] Step 5:

[1289] The server generates the optimal tax saving plan based on the latest tax information. The input is analyzed income and expenditure data, and the output is a tax saving plan. Specifically, the server refers to the latest tax database and calculates the appropriate tax saving plan.

[1290] Step 6:

[1291] The emotion engine analyzes the user's facial expression and tone of voice to determine the user's current emotional state. The input is the user's facial expression or voice data, and the output is emotional state data. Specifically, it uses an emotion analysis algorithm to determine whether the user is feeling stressed.

[1292] Step 7:

[1293] The server simulates the tax savings effect of the tax saving plan and displays the results graphically. The input is the tax saving plan, and the output is the simulation result. Specifically, it uses a simulation algorithm to calculate the tax reduction effect and generates the data necessary to display it as a graph.

[1294] Step 8:

[1295] A generative AI model is used to provide optimal purchasing advice to users and generate specific prompts. The input is income and expenditure data and emotional state data, and the output is specific prompts. Specifically, the generative AI model analyzes the input data and generates prompts such as, "Please suggest the optimal savings plan based on the user's purchase history and bank statements. Please provide an encouraging message if the user is feeling stressed."

[1296] Step 9:

[1297] When a user selects a tax-saving plan, the server automatically generates the documents required for the application procedure and provides a download link to the terminal. The input is the selected tax-saving plan, and the output is a download link for the application documents. Specifically, the server uses a document generation algorithm to create the necessary application documents, generates a link for them, and sends it to the terminal.

[1298] 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.

[1299] 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.

[1300] 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.

[1301] [Fourth embodiment]

[1302] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1303] 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.

[1304] 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).

[1305] 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.

[1306] 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.

[1307] 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).

[1308] 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.

[1309] 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.

[1310] 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.

[1311] 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.

[1312] 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.

[1313] 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.

[1314] 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."

[1315] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing data, means for generating tax-saving plans, means for simulation, and means for supporting application procedures. This system is designed to enable users to easily find and efficiently implement tax-saving strategies that are optimal for them.

[1316] System configuration

[1317] The system consists of a user's terminal, a server, and related databases. The user uses the terminal to input or scan income and expenditure data, which is then sent to the server. The server analyzes the income and expenditure data, generates and simulates tax-saving plans, and sends the information back to the terminal. It also generates the documents necessary for application procedures, helping the user to complete the procedures efficiently.

[1318] Acquisition of income and expenditure data

[1319] 1. Data Entry / Scanning:

[1320] Users manually enter income and expense information into the device or scan paper documents or electronic files, such as pay slips or household receipts.

[1321] The terminal uses OCR technology to convert the scanned data into text data, and obtains the income and expenditure data in digital format.

[1322] Sending and analyzing income and expenditure data

[1323] 2. Data transmission:

[1324] The terminal transmits the acquired balance data to the server using a secure communication protocol.

[1325] 3. Data Analysis:

[1326] The server analyzes the received income and expenditure data and categorizes it into categories such as income, expenditure, expenses, medical expenses, education expenses, etc. This allows the user's income and expenditure situation to be understood in detail.

[1327] Tax saving plan generation and simulation

[1328] 4. Generate tax saving plans:

[1329] The server generates an optimal tax-saving plan based on the user's income and expenditure data, taking into account the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, and mortgage deductions.

[1330] 5. Simulation:

[1331] The server simulates the tax savings effect of each tax saving plan and presents it to the user. The simulation results include predicted tax reductions and comparative information based on the plan selected by the user.

[1332] Support for application procedures

[1333] 6. Document generation and submission:

[1334] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal, where the user can download and print these documents and complete the necessary procedures.

[1335] Ongoing support

[1336] 7. Periodic Data Updates and Plan Reassessment:

[1337] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. By re-proposing the optimal tax saving plan based on new data and changes in the tax system, the user can always implement tax saving measures that are adapted to the latest tax system.

[1338] Specific examples

[1339] For example, after a user provides their monthly pay stub and expense data, the following happens:

[1340] 1. The user enters or scans their pay stub and expense information into the terminal.

[1341] 2. The terminal sends the balance data to the server.

[1342] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[1343] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[1344] 5. The device will display the best tax saving plan for the user and its effects.

[1345] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the terminal.

[1346] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[1347] This system allows users to automatically and efficiently take the best possible tax-saving measures.

[1348] The processing flow will be explained below.

[1349] Step 1:

[1350] The user collects income and expense data and manually enters it into the terminal or scans it.

[1351] Step 2:

[1352] The device uses OCR technology to convert scanned documents into text data, obtaining income and expenditure data in digital format.

[1353] Step 3:

[1354] The terminal transmits the collected data to the server using a secure communication protocol.

[1355] Step 4:

[1356] The server analyzes the received income and expenditure data and automatically classifies it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[1357] Step 5:

[1358] The server checks the data for inconsistencies and cleanses it as needed, including removing duplicate data and standardizing formats.

[1359] Step 6:

[1360] The server learns the latest tax information and generates the optimal tax-saving plan based on that information. For example, it suggests plans that include medical expense deductions and donation deductions.

[1361] Step 7:

[1362] The server simulates the tax savings effect of each tax saving plan and calculates the expected tax reduction.

[1363] Step 8:

[1364] The server sends the simulation results along with the optimal tax saving plan to the terminal.

[1365] Step 9:

[1366] The device graphically displays details of tax-saving plans and their effects to users, allowing them to intuitively understand the comparison of each plan.

[1367] Step 10:

[1368] The user selects the desired tax saving plan.

[1369] Step 11:

[1370] The server automatically generates the necessary application documents based on the selected tax saving plan, and also lists the necessary attachments.

[1371] Step 12:

[1372] The server sends the generated application documents to the terminal.

[1373] Step 13:

[1374] The terminal presents the application documents to the user and instructs them to download and print them.

[1375] Step 14:

[1376] The user downloads the generated documents and follows the instructions to complete the application process.

[1377] Step 15:

[1378] The server periodically updates income and expenditure data and incorporates new data to support ongoing tax-saving measures.

[1379] Step 16:

[1380] The server reevaluates the tax saving plan based on new income and expenditure data and changes in tax systems, and proposes a new plan to the user as necessary.

[1381] In this way, users can efficiently manage their income and expenditure data and easily take optimal tax-saving measures.

[1382] Example 1

[1383] 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."

[1384] The present invention relates to a system that supports individuals or corporations in efficiently implementing tax-saving measures. Conventional tax-saving measures are complex, requiring the management of numerous documents and an understanding of the tax system, making it difficult for individual users to find the optimal tax-saving plan. Furthermore, it is difficult to obtain a plan that constantly reflects the latest tax system information, resulting in ineffective tax savings. This has led to the problem that many users end up making wasteful expenditures and failing to implement appropriate tax-saving measures.

[1385] 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.

[1386] In this invention, the server includes means for acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting application procedures required for the tax saving plan, means for converting the income and expenditure data into text data using OCR technology, means for transmitting the income and expenditure data to the server using a secure communication protocol, means for learning the latest tax information using a generative AI model and generating a tax saving plan, means for periodically updating the income and expenditure data and reevaluating the tax saving plan, and means for presenting the simulation results to the user. This allows users to easily input income and expenditure data and efficiently obtain an optimal tax saving plan based on the latest tax information.

[1387] "Income and Expenditure Data" means information relating to income and expenditures that indicates the financial position of an individual or entity.

[1388] "Capture means" refers to the functionality of a device or software for inputting or scanning and collecting financial data from a user.

[1389] "Analysis means" refers to the function of a device or software that categorizes and performs statistical analysis based on the acquired income and expenditure data.

[1390] A "tax saving plan" refers to a specific plan that suggests ways and strategies to reduce tax based on the user's income and expenditure data.

[1391] "Simulation means" refers to the functionality of a device or software that predicts the effects of a generated tax saving plan and calculates the specific tax savings and benefits.

[1392] "Means to support application procedures" refers to auxiliary functions that allow users to prepare the necessary documents and carry out application procedures efficiently.

[1393] "OCR technology" refers to optical character recognition technology, which extracts text data from scanned images.

[1394] "Secure communication protocol" refers to a communication protocol that ensures security when sending and receiving data, and includes, for example, HTTPS.

[1395] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and operate for a specific purpose (in this case, learning tax information or generating tax-saving plans).

[1396] "Latest tax information" refers to the latest tax rules and information, including tax laws and deduction provisions in effect at the time.

[1397] "Database" refers to a collection of collected and stored data that allows the system to efficiently manage and use the information it needs.

[1398] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing data, means for generating tax-saving plans, means for simulation, and means for supporting application procedures. This system is designed to enable individuals or corporations to efficiently find and implement optimal tax-saving strategies. Each means will be specifically described below.

[1399] How to obtain income and expenditure data

[1400] Users enter or scan financial data using their device. For example, they can take a photo of a pay slip, receipt, or other financial document with their smartphone camera and import it into the app. The device then converts this data into text using OCR (optical character recognition) technology. Software such as Tesseract OCR can be used to extract text from the scanned image.

[1401] Data transmission method

[1402] The terminal transmits the acquired and converted balance data to the server via a secure communication protocol (e.g., HTTPS), which prevents data leakage and unauthorized access.

[1403] Data analysis methods

[1404] The server analyzes the received data, for example, by using the Python Pandas library to classify the data into different categories (income, expenditure, expenses, medical expenses, education expenses, etc.) to obtain a detailed understanding of the user's financial situation. The results of this analysis are then used to generate a tax saving plan.

[1405] Tax saving plan generation tool

[1406] The server uses the generative AI model to learn the latest tax information and update the database. This allows the server to generate optimal tax-saving plans based on the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, and mortgage deductions.

[1407] Simulation Method

[1408] The server simulates the tax savings effect of the generated tax saving plans. Using Python's NumPy library, it calculates the predicted tax reduction effect of each plan and presents it to the user. The simulation results include the effects and benefits of each plan.

[1409] Support for application procedures

[1410] The server automatically generates the application documents required for the tax-saving plan selected by the user and sends them to the terminal. The application documents are created in PDF format using the PyPDF2 library, etc. The user downloads and prints these documents and follows the instructions to complete the application process.

[1411] Ongoing support measures

[1412] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan based on the latest tax information, thereby always providing the optimal tax saving strategy.

[1413] Specific examples

[1414] For example, after a user provides their monthly pay stub and expense data, the following happens:

[1415] 1. The user enters or scans their pay stub and expense information into the device, for example, by taking a photo of their pay stub using their smartphone camera and scanning it into the app.

[1416] 2. The device uses OCR technology to convert the scanned data into text data and sends that data to the server.

[1417] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[1418] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[1419] 5. The device will display the best tax saving plan for the user and its effects.

[1420] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the terminal.

[1421] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[1422] Prompt Sentence Examples

[1423] "Please enter or scan the data from your monthly pay slip and household ledger according to the following headings: income, expenditures, expenses, medical expenses, and education expenses."

[1424] This system allows users to automatically and efficiently take the best tax-saving measures.

[1425] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1426] Step 1:

[1427] Data Entry / Scanning

[1428] The user manually enters income and expense information into the device, or scans a paper document or electronic file. For example, they take a picture of a pay slip or receipt with their smartphone camera and scan it into the app. The input data includes income amount, expense amount, and expense category. The device then converts the scanned data into text data using OCR technology. For example, Tesseract OCR can be used to extract text from an image of a pay slip. This text data is then passed to the next processing step.

[1429] Step 2:

[1430] Data transmission

[1431] The terminal sends the acquired and converted balance data to the server using a secure communication protocol (e.g., HTTPS). The input data includes the text data obtained in step 1. Using a secure communication protocol prevents data leakage and unauthorized access. The balance data is securely passed to the server through this communication.

[1432] Step 3:

[1433] Data analysis

[1434] The server analyzes the received income and expenditure data. The input data includes the transmitted income and expenditure data (income, expenditure, expense items, etc.). Using Python's Pandas library, the data is classified into categories such as income, expenditure, expenses, medical expenses, and education expenses. For example, data such as "Salary: 300,000 yen," "Rent: 80,000 yen," and "Medical expenses: 10,000 yen" are classified into the appropriate categories. The classification results are passed to the next step.

[1435] Step 4:

[1436] Generate tax saving plans

[1437] The server uses the generative AI model to learn the latest tax information and update the database. The input data includes the analysis data obtained in step 3 and the latest tax information. Based on this, the optimal tax saving plan is generated. For example, the applicability of medical expense deductions, donation deductions, mortgage deductions, etc. is evaluated and each plan is generated. The generated results are passed to the next step.

[1438] Step 5:

[1439] simulation

[1440] The server simulates the tax savings effect of each tax saving plan generated. The input data includes each tax saving plan generated in step 4. Using Python's NumPy library, the tax reduction effect of each plan is calculated and presented to the user. For example, the simulation result obtained is "medical expense deductions can save 50,000 yen per year in taxes." This result is passed to the next step.

[1441] Step 6:

[1442] Support for application procedures

[1443] The server automatically generates the application documents required for the tax saving plan selected by the user and sends them to the terminal. The input data includes the simulation results from step 5 and the selected tax saving plan. The server uses the PyPDF2 library to create the application documents in PDF format. For example, it creates "Medical Expense Deduction Application Form.pdf" and sends it to the terminal. The user downloads this document, prints it, fills in the necessary information, and proceeds with the application procedure.

[1444] Step 7:

[1445] Ongoing support

[1446] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan based on new data and changes in the tax system. The input data includes the latest income and expenditure data and the latest tax system information. Based on this, a new tax saving plan is proposed. For example, new analysis results such as "new medical expense deductions are applicable" are provided.

[1447] (Application example 1)

[1448] 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."

[1449] Conventional tax saving systems require users to manually input income and expenditure data, select a tax saving plan, and complete the necessary application procedures, which is time-consuming and labor-intensive. Furthermore, there is no system that collects and analyzes electronic payment data in real time and proposes optimal tax saving plans. This makes it difficult for users to efficiently implement tax saving measures and find the appropriate plan.

[1450] 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.

[1451] In this invention, the server includes means for acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting the application procedures required for the tax saving plan, means for collecting and analyzing electronic payment data in real time, means for categorizing the collected data, means for notifying the user of the tax saving plan, and means for supporting the application procedures with a reminder function. This enables the user to automatically and efficiently find the optimal tax saving plan and smoothly complete the application procedures.

[1452] "Means for obtaining income and expenditure data" refers to means for collecting data on income and expenditure from users.

[1453] The "means for analyzing the acquired income and expenditure data" is a means for analyzing the collected income and expenditure data and classifying it by category.

[1454] The "means for generating an optimal tax saving plan" is a means for proposing the most effective tax saving measures for the user based on analyzed income and expenditure data.

[1455] The "means for simulating the tax saving effect of a tax saving plan" is a means for predicting the effect of the generated tax saving plan and presenting the results to the user.

[1456] "Means to support application procedures" refers to means to automatically generate the necessary application documents based on the tax saving plan selected by the user and to assist with the procedures.

[1457] "Means for collecting and analyzing electronic payment data in real time" refers to means for automatically obtaining data from a user's electronic payment service and analyzing it immediately.

[1458] The "means for categorizing collected data" is a means for classifying collected income and expenditure data into categories such as income, expenditure, medical expenses, and education expenses.

[1459] The "means for notifying the user of the tax saving plan" is a means for notifying the user of the generated tax saving plan and the results of its simulation.

[1460] "Means of supporting application procedures with a reminder function" refers to a means of notifying users of deadlines and important points to note when completing application procedures.

[1461] The present invention is a system that includes means for acquiring income and expenditure data, means for analysis, means for generating tax-saving plans, means for simulation, and means for supporting application procedures, thereby enabling users to easily find optimal tax-saving strategies and implement them efficiently.

[1462] System configuration

[1463] The system consists of a user's device, a server, and related databases. Users use their device to input or scan income and expenditure data, which is then sent to the server. The server analyzes the data, generates and simulates tax-saving plans, and sends the information back to the device. It also generates the documents necessary for the application process, helping users complete the process efficiently.

[1464] Acquisition of income and expenditure data

[1465] Users manually enter income and expense information into the terminal or scan paper documents or electronic files, such as pay slips or receipts. The terminal then uses OCR technology to convert the scanned data into text data, providing digital income and expenditure data. It also integrates with electronic payment services to collect transaction data in real time.

[1466] Data transmission and analysis

[1467] The device sends the acquired data to a server using a secure communication protocol. The server analyzes the data and categorizes it into categories such as income, expenses, medical expenses, and education expenses. This allows the user to understand their financial situation in detail.

[1468] Tax saving plan generation and simulation

[1469] The server generates an optimal tax-saving plan based on the user's income and expenditure data, using the latest tax information. For example, it evaluates the applicability of medical expense deductions, donation deductions, mortgage deductions, etc. The server then simulates the tax savings effect of each generated tax-saving plan and presents it to the user. The simulation results include predicted tax reductions and comparative information based on the plan selected by the user.

[1470] Support for application procedures

[1471] The server automatically generates the application documents required for the selected tax-saving plan and sends them to the terminal. The user downloads and prints these documents and completes the necessary procedures. The application process is also supported by a reminder function, notifying the user of deadlines and important points to note.

[1472] Ongoing support

[1473] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. Based on new data and changes in the tax system, the server re-proposes the optimal tax saving plan, ensuring that the user can always take tax saving measures that are adapted to the latest tax system.

[1474] Specific processing examples

[1475] For example, after a user provides their monthly pay stub and expense data, the following happens:

[1476] 1. The user enters or scans their pay stub and expense information into the terminal.

[1477] 2. The device sends the balance data to the server.

[1478] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[1479] 4. The server generates multiple tax-saving plans based on the data and simulates the tax savings effect of each.

[1480] 5. The device will display the best tax saving plan for the user and its benefits.

[1481] 6. Based on the plan selected by the user, the server generates the necessary application documents and sends them to the device.

[1482] 7. The user downloads the application form and follows the instructions to complete the procedure.

[1483] Hardware and software used

[1484] The hardware used is mainly user devices such as smartphones and tablets, while the software used is OCR technology for acquiring income and expenditure data, algorithms for analyzing the collected data, a database for generating tax-saving plans, and a program for simulation.

[1485] Prompt Sentence Examples

[1486] Please provide a concrete example of an application that automatically collects and analyzes income and expenditure data, generates a tax-saving plan, and simulates its effectiveness. If user "example_user_id" uses an electronic payment service, please show data collection, classification, tax-saving plan proposal, and simulation results.

[1487] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1488] Step 1:

[1489] The user inputs or scans income and expenditure data. The user manually inputs income and expenditure information, such as pay slips or receipts, into the device or scans documents. Input data includes income amounts, expense items, dates, etc. The output is the income and expenditure data in digital form.

[1490] Step 2:

[1491] The terminal uses OCR technology to convert the scanned data into text data. The terminal then performs OCR processing on the scanned image data and extracts the balance information as text data. The input is the scanned data, and the output is the balance data in text format.

[1492] Step 3:

[1493] The terminal transmits the acquired balance data to the server. The collected data (text-format balance data) is sent to the server using a secure communication protocol. The input is the text-format balance data, and the output is the data transmitted to the server.

[1494] Step 4:

[1495] The server analyzes the received data and runs an algorithm to classify it into categories such as income, expenses, medical expenses, and education expenses. The input is text-formatted data, and the output is the categorized data.

[1496] Step 5:

[1497] The server generates the optimal tax saving plan based on the latest tax system information. It references the tax system information stored in the database and identifies applicable tax saving measures based on the user's income and expenditure data. The input is categorized income and expenditure data and tax system information, and the output is candidate tax saving plans.

[1498] Step 6:

[1499] The server simulates the tax savings effect of each generated tax saving plan. It calculates the savings effect of each plan and performs a simulation to present it to the user. The input is the tax saving plan, and the output is the tax savings effect as a result of the simulation.

[1500] Step 7:

[1501] The terminal notifies the user of the optimal tax saving plan and the simulation results. The terminal interface shows the plans the user can choose from and their effects. The input is the simulation results, and the output is the information notified to the user.

[1502] Step 8:

[1503] Based on the plan selected by the user, the server automatically generates the necessary application documents. The generated application documents are sent to the terminal, where the user can download and print them. The input is the selected tax saving plan, and the output is the generated application documents.

[1504] Step 9:

[1505] The terminal supports the application procedure with a reminder function. It provides a reminder function that notifies the user of the deadline for submitting application documents and any additional information that is required. The input is the application schedule information, and the output is the reminder notified to the user.

[1506] Prompt Sentence Examples

[1507] Please provide a concrete example of an application that automatically collects and analyzes income and expenditure data, generates a tax-saving plan, and simulates its effectiveness. If user "example_user_id" uses an electronic payment service, please show data collection, classification, tax-saving plan proposal, and simulation results.

[1508] 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.

[1509] The present invention is a system that includes means for acquiring income and expenditure data, means for analyzing it, means for generating tax-saving plans, means for simulation, and means for supporting application procedures, as well as an emotion engine that recognizes the user's emotions. This system is designed to enable users to easily find and efficiently implement tax-saving strategies that are best suited to them. Furthermore, the emotion engine customizes the system's responses according to the user's emotional state, providing a more effective experience.

[1510] System configuration

[1511] The system consists of a user's device, a server, related databases, and an emotion engine that recognizes the user's emotions. The user uses the device to input or scan income and expenditure data and transmits the data to the server. The emotion engine simultaneously analyzes the user's emotions, and the server receives and analyzes this data, generating and simulating an optimal tax-saving plan. The system also generates the documents necessary for the application process, helping the user to complete the process efficiently.

[1512] Acquisition of income and expenditure data

[1513] 1. Data Entry / Scanning:

[1514] Users manually enter income and expense information into the device or scan paper documents or electronic files, such as pay slips or household receipts.

[1515] The terminal uses OCR technology to convert the scanned data into text data, and obtains the income and expenditure data in digital format.

[1516] Sending and analyzing income and expenditure data

[1517] 2. Data transmission:

[1518] The device transmits the acquired income and expenditure data and the user's emotional information to the server via a secure communication protocol.

[1519] 3. Data Analysis:

[1520] The server analyzes the received income and expenditure data and automatically categorizes it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[1521] The server simultaneously analyzes the user's emotional data to determine the user's current emotional state.

[1522] Tax saving plan generation and simulation

[1523] 4. Generate tax saving plans:

[1524] The server generates an optimal tax-saving plan based on the user's income and expenditure data, taking into account the latest tax information. For example, it suggests plans that include medical expense deductions, donation deductions, and mortgage deductions.

[1525] The emotion engine selects an appropriate plan presentation method based on the user's emotional state.

[1526] 5. Simulation:

[1527] The server simulates the tax savings effect of each generated tax saving plan and calculates the expected tax reduction.

[1528] Presentation of simulation results

[1529] 6. Presentation of results:

[1530] The device graphically displays details of the tax-saving plan and its benefits to the user, while the emotion engine adjusts the display and tone of the message depending on the user's emotions. For example, if the user is feeling stressed, the display will be more concise and reassuring.

[1531] Support for application procedures

[1532] 7. Document generation and submission:

[1533] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal, where the user can download and print these documents and complete the necessary procedures.

[1534] The emotion engine provides additional information and support to address any concerns or questions users may have during the process.

[1535] Ongoing support

[1536] 8. Periodic Data Updates and Plan Reassessment:

[1537] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan. By re-proposing the optimal tax saving plan based on new data and changes in the tax system, the user can always implement tax saving measures that are adapted to the latest tax system.

[1538] Specific examples

[1539] For example, after a user provides their monthly pay stub and expense data, the following happens:

[1540] 1. The user enters or scans their pay stub and expense information into the terminal.

[1541] 2. The device sends the income and expenditure data and the user's emotional information to the server.

[1542] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[1543] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[1544] 5. The device displays the optimal tax saving plan and its benefits to the user, with the emotion engine customizing the display based on the user's emotions.

[1545] 6. Once the user selects the desired tax saving plan, the server generates the necessary application documents and sends them to the terminal.

[1546] 7. The user downloads the application documents and follows the instructions to complete the procedure. Through this process, the user can automatically and effectively take optimal tax-saving measures.

[1547] The processing flow will be explained below.

[1548] Step 1:

[1549] The user collects income and expense data and manually enters it into the terminal or scans it.

[1550] Step 2:

[1551] The device uses OCR technology to convert scanned documents into text data, obtaining income and expenditure data in digital format.

[1552] Step 3:

[1553] The device transmits the collected data and the user's emotional information recognized by the emotion engine to the server using a secure communication protocol.

[1554] Step 4:

[1555] The server analyzes the received income and expenditure data and automatically classifies it into categories such as income, expenditure, expenses, medical expenses, and education expenses.

[1556] Step 5:

[1557] The server checks the data for inconsistencies and cleanses it as needed, including removing duplicate data and standardizing formats.

[1558] Step 6:

[1559] The server learns the latest tax information and generates the optimal tax-saving plan based on that information. For example, it suggests plans that include medical expense deductions, donation deductions, and mortgage deductions.

[1560] Step 7:

[1561] The server simulates the tax savings effect of each tax saving plan and calculates the expected tax reduction.

[1562] Step 8:

[1563] The server sends the simulation results along with the optimal tax saving plan to the terminal.

[1564] Step 9:

[1565] The device graphically displays details of the tax-saving plan and its benefits to the user, while an emotion engine adjusts the display and tone of the message based on the user's emotions. For example, if the user is feeling stressed, the display will be more concise and reassuring.

[1566] Step 10:

[1567] The user selects the desired tax saving plan.

[1568] Step 11:

[1569] The server automatically generates the necessary application documents based on the selected tax saving plan, and also lists the necessary attachments.

[1570] Step 12:

[1571] The server sends the generated application documents to the terminal.

[1572] Step 13:

[1573] The terminal presents the application documents to the user and instructs them to download and print them.

[1574] Step 14:

[1575] The user downloads the generated documents and follows the instructions to complete the application process.

[1576] Step 15:

[1577] The server periodically updates income and expenditure data and incorporates new data to support ongoing tax-saving measures.

[1578] Step 16:

[1579] The server reevaluates the tax saving plan based on new income and expenditure data and changes in tax systems, and proposes a new plan to the user as necessary.

[1580] In this way, users can efficiently manage their income and expenditure data and easily take optimal tax-saving measures. Furthermore, the emotion engine provides detailed support according to the user's emotions, improving the user experience.

[1581] Example 2

[1582] 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."

[1583] Previously, there were systems that proposed tax-saving plans based on income and expenditure data, but they lacked careful consideration for the user's emotional state. Furthermore, security considerations were insufficient, and a system that users could use with peace of mind was needed. In addition, there was a lack of support for addressing the anxieties and questions users had during the application process, making improving the user experience an urgent issue.

[1584] 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 acquiring income and expenditure data, means for analyzing the acquired income and expenditure data, means for generating an optimal tax saving plan based on the analyzed income and expenditure data, means for simulating the tax saving effect of the generated tax saving plan, means for supporting the application procedures required for the tax saving plan, emotion recognition means for recognizing the user's emotion and customizing the proposal content based on the emotion, means for transmitting data to the server using a secure communication protocol, and means for using the emotion recognition means to address any anxieties or questions the user may have during the procedure. This allows the user to use the system with peace of mind, find the optimal tax saving plan for themselves, and efficiently implement it.

[1585] "Income and expenditure data capture means" refers to a device or software that allows a user to input or scan information about income and expenses and capture it in digital form.

[1586] "Means for analyzing acquired income and expenditure data" refers to a device or software that performs a process of analyzing income and expenditure data and automatically classifying it into categories such as income, expenditure, and expenses.

[1587] The "means for generating an optimal tax saving plan" refers to a device or software that proposes an optimal tax saving plan to a user based on analyzed income and expenditure data and taking into account the latest tax system information.

[1588] "Means for simulating the tax saving effect of a tax saving plan" refers to a device or software that simulates the effect of a generated tax saving plan using numerical values, graphs, etc., and calculates the predicted tax reduction.

[1589] "Application procedure support means" refers to a device or software that automatically generates the application documents required for a tax-saving plan and provides assistance to users in downloading, printing, and properly completing the application documents.

[1590] "Emotion recognition means that recognizes a user's emotions and customizes the content of suggestions based on those emotions" refers to a device or software that analyzes a user's emotional state in real time and adjusts the content of suggestions and the display method based on the results.

[1591] "Means for transmitting data to a server using a secure communication protocol" refers to a device or software that uses a communication protocol (e.g., HTTPS) to encrypt data and transmit it securely to a server.

[1592] "Means for using emotion recognition means to address the anxiety and doubts that users may feel during a procedure" refers to devices or software that alleviate anxiety and doubts that users may feel during a procedure by providing necessary information and support based on the user's emotional state.

[1593] This invention is a system that inputs and acquires information on income and expenses, and then proposes optimal tax-saving plans based on that information. The system has multiple functions, including income and expenditure data acquisition, analysis, plan generation, simulation, application support, and emotion recognition, and is designed to enable users to efficiently implement tax-saving measures.

[1594] Hardware and Software

[1595] User device: PC, smartphone, tablet, etc. The device where the user enters or scans their financial data.

[1596] Server: A central processing unit that performs tasks such as data analysis, tax saving plan generation, and simulations.

[1597] Emotion Recognition Engine: An AI engine (e.g., emotion recognition API) that recognizes user emotions in real time and adjusts suggestions accordingly.

[1598] OCR technology: Technology that converts scanned documents into text data (e.g., OCR API).

[1599] System configuration

[1600] The user uses the device to input or scan income and expenditure data such as pay slips and receipts. The device then uses OCR technology to convert the scanned data into text data, obtaining digital income and expenditure data. This data is then sent to a server using a secure communication protocol (e.g., HTTPS), and the user's emotional information is also collected.

[1601] The server analyzes the received income and expenditure data and categorizes it into categories such as income, expenditure, and expenses. Furthermore, the server analyzes the user's emotional data provided by the emotion recognition engine to identify the user's current emotional state. Based on this information, the server generates an optimal tax saving plan by referring to the latest tax information.

[1602] For each tax saving plan, the server simulates its effects and calculates the projected tax savings. The results are displayed graphically, and an emotion recognition engine adjusts the content and tone of the message depending on the user's emotions.

[1603] Once the user selects the desired tax saving plan, the server automatically generates the necessary application documents and sends them to the terminal. The user can download and print these documents and follow the instructions to complete the formal procedures. During the application process, the emotion recognition engine provides appropriate information and support to address any concerns or questions the user may have about the process.

[1604] Specific examples

[1605] For example, if a user provides monthly pay stubs and expense data, the following occurs:

[1606] 1. The user enters or scans their pay stub and expense information into the terminal.

[1607] 2. The device sends the income and expenditure data and the user's emotional information to the server.

[1608] 3. The server analyzes the data to determine total income, largest expenditure items, deductible expenses, etc.

[1609] 4. The server generates multiple tax saving plans based on the data and simulates the tax saving effect of each.

[1610] 5. The device displays the best tax-saving plan and its benefits to the user, with an emotion-recognition engine customizing the display based on the user's emotions.

[1611] 6. Once the user selects the desired tax saving plan, the server generates the necessary application documents and sends them to the terminal.

[1612] 7. The user downloads the application documents and follows the instructions to complete the procedure.

[1613] Prompt Sentence Examples

[1614] "Tell me about an income / expense data analysis system that incorporates an emotion engine that recognizes the user's emotions. Please explain the overall process flow of the system that adjusts the display format and tone according to the user's emotional state and suggests the optimal tax saving plan."

[1615] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1616] Step 1:

[1617] Acquisition of income and expenditure data

[1618] The user enters or scans income and expenditure data, such as pay stubs or receipts, into the terminal.

[1619] Input: Paper or electronic files such as pay stubs or receipts.

[1620] Output: Digital balance data converted into text data using OCR technology.

[1621] How it works: The user takes a photo of their pay slip with their smartphone and uploads it. The device then uses the OCR API to convert the image into text data, and the income and expenditure data is obtained in digital form.

[1622] Step 2:

[1623] Sending financial data and emotional information

[1624] The terminal transmits the acquired income and expenditure data and the user's emotional information to the server.

[1625] Input: Digital balance data converted using OCR technology and sentiment information collected in real time.

[1626] Output: Encrypted financial data and emotional information are sent to the server.

[1627] How it works: The device encrypts financial data and emotional information and sends it to the server using the secure HTTPS protocol.

[1628] Step 3:

[1629] Analysis of income and expenditure data and emotional information

[1630] The server analyzes the received income and expenditure data, including emotional information.

[1631] Input: Submitted digital financial data and sentiment.

[1632] Output: Analysis results categorized into categories such as income, expenditure, and expenses, along with the user's emotional state.

[1633] How it works: The server analyzes the data and automatically categorizes the balance data, while the emotion recognition engine identifies the user's emotional state.

[1634] Step 4:

[1635] Generate optimal tax saving plans

[1636] The server generates the optimal tax saving plan based on the analyzed income and expenditure data, while referring to the latest tax information.

[1637] Input: Categorised financial data and information about the user's emotional state.

[1638] Output: A proposal with multiple tax saving plans.

[1639] Specific operation: The server references the tax database and generates multiple tax-saving plans based on the user's income and expenditure data. The emotion recognition engine selects the optimal presentation method.

[1640] Step 5:

[1641] Tax saving plan simulation

[1642] The server simulates the tax saving effect of the generated tax saving plan and calculates the expected tax reduction.

[1643] Input: Each generated tax saving plan.

[1644] Output: Projected tax savings as a result of the simulation.

[1645] Specific operation: The server simulates tax reduction for each plan and outputs the results in numerical and graphical form.

[1646] Step 6:

[1647] Presentation of simulation results

[1648] The terminal will then graphically display to the user the details of the tax saving plan and its effects.

[1649] Input: Simulated tax reduction results.

[1650] Output: A visual representation of the tax saving plan and its effects to the user.

[1651] Specific operation: The device displays the simulation results in graphs and charts, and the emotion recognition engine customizes the display according to the user's emotions.

[1652] Step 7:

[1653] Support for application procedures

[1654] The server automatically generates the application documents required for the selected tax saving plan and sends them to the terminal.

[1655] Input: The tax saving plan selected by the user.

[1656] Output: Auto-generated application documents.

[1657] Specific operation: The server automatically generates the necessary application documents and sends them to the terminal. The user downloads these documents, prints them, and proceeds with the procedure.

[1658] Step 8:

[1659] Support during the process

[1660] The emotion recognition engine provides information to help users deal with any concerns or doubts they may have during the process.

[1661] Input: The user's emotional state and any concerns or doubts about the procedure.

[1662] Output: Additional information or support messages.

[1663] Specific operation: The emotion recognition engine monitors the user's emotional state and displays appropriate feedback and support messages in case of anxiety or doubt.

[1664] Step 9:

[1665] Continuous data updates and plan reevaluation

[1666] The server periodically updates the user's income and expenditure data and reevaluates the tax saving plan.

[1667] Input: Newly updated income and expenditure data.

[1668] Output: Reassessed optimal tax saving plan.

[1669] Specific operation: The server periodically updates the database and re-proposes new tax-saving plans based on the latest tax information and income and expenditure data.

[1670] (Application example 2)

[1671] 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."

[1672] Today's consumers spend a great deal of time and effort managing complex income and expenditures and implementing optimal tax-saving strategies. However, existing systems often fail to consider user emotions and are often stressful, resulting in a poor user experience. Furthermore, systems lack the digitalization and security of income and expenditure data, and are not up to date with the latest tax information, leaving users without an environment in place to quickly and efficiently implement optimal tax-saving strategies. Therefore, there is a need for the development of a new system that takes user emotions into consideration and provides comprehensive support, from acquiring income and expenditure data to secure data transmission and providing tax-saving plans based on the latest tax information.

[1673] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1674] In this invention, the server includes means for acquiring income and expenditure data, means including an emotion engine for recognizing user emotions, means for using OCR technology to acquire the income and expenditure data from the user and convert it into a digital format, means for simulating the tax savings effect of the generated tax saving plan, means for adjusting the display method and message tone according to the user's emotions when graphically displaying the tax savings effect of the tax saving plan, means for securely transmitting the income and expenditure data and the generated savings plan to the server, means for learning the latest tax information and updating the database, means for using a generative AI model to provide optimal advice to the user, and means for generating prompt sentences and making optimal suggestions to the user based on the generated prompt sentences. This enables the provision of a user-friendly interface that takes user emotions into consideration, while also enabling the digitization and secure management of income and expenditure data, and the prompt sentences to be quickly and efficiently proposed to the user as optimal tax saving plans based on the latest tax information.

[1675] definition statement

[1676] "Means for acquiring income and expenditure data" refers to a means by which a user inputs or scans income and expenditure information into a terminal, and includes technology for converting that data into digital form.

[1677] The "means for analyzing the acquired income and expenditure data" includes algorithms and software for categorizing the income and expenditure data and analyzing its contents.

[1678] The "means for generating an optimal tax saving plan" includes algorithms and systems that propose the most effective tax saving measures for users based on analyzed income and expenditure data and the latest tax system information.

[1679] "Means for simulating the tax savings effect of the generated tax savings plan" includes programs and systems for calculating and evaluating the expected tax savings effect based on the generated tax savings plan.

[1680] The "means for supporting the application procedures necessary for a tax saving plan" includes a system that automatically generates application documents prepared in accordance with an optimal tax saving plan and provides them to users.

[1681] The "emotion engine that recognizes the user's emotions" includes algorithms and systems that analyze the user's emotions from their facial expressions and tone of voice, and adjust the way they respond based on that information.

[1682] "Means using OCR technology" includes technology that reads text information from paper receipts or electronic files and converts it into digital data.

[1683] "Means for securely transmitting to the server" includes technology for securely transmitting income and expenditure data and savings plans to the server using security technology such as encryption.

[1684] "Means for providing optimal advice to users using a generative AI model" includes a system that uses a generative artificial intelligence model to provide appropriate advice based on the user's income and expenditure data and emotional data.

[1685] "Means for generating prompt sentences and making optimal suggestions to users based on the generated prompt sentences" includes a system in which a generative AI model generates appropriate prompt sentences for users based on input data and makes optimal suggestions based on the content of those sentences.

[1686] MODE FOR CARRYING OUT THE INVENTION

[1687] This invention provides a system that efficiently provides savings and purchasing advice to consumers on online shopping sites. The system utilizes a means of acquiring income and expenditure data, an emotion engine, OCR technology, a secure communication protocol, and a generative AI model.

[1688] System configuration

[1689] The system includes a terminal that collects the user's income and expenditure data and converts it into digital format, a server that securely analyzes and stores this data, and an emotion engine that recognizes the user's emotions and provides appropriate advice.

[1690] Hardware and Software

[1691] Hardware: Smartphones and tablets with a camera

[1692] Software: OCR technology (e.g., pytesseract), image processing library (PIL), HTTP request library (requests), generative AI models

[1693] Data processing and calculation

[1694] 1. The user takes a photo of the receipt for the purchased item with their smartphone camera, and the device uses OCR technology to convert the balance data into a digital format, which then recognizes the receipt image as text data.

[1695] 2. The acquired balance data is sent to a server using a secure communication protocol, and the server analyzes the data using a category classification algorithm for the balance data.

[1696] 3. The server generates the optimal tax saving plan from the analyzed income and expenditure data based on the latest tax information.

[1697] 4. The emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the tone and content of the suggested advice based on the user's current emotional state.

[1698] 5. Simulate the effects of the generated tax saving plan and display the results graphically.

[1699] 6. Using the generative AI model, provide optimal purchasing advice to the user and generate specific prompts, such as "Please suggest the best savings plan based on the user's purchase history and bank statements. Please also provide encouraging messages if the user is feeling stressed."

[1700] 7. If the user selects a tax-saving plan, the server automatically generates the documents required for the application procedure and provides a download link to the device.

[1701] Specific examples

[1702] After a user shops at the supermarket, they take a photo of the receipt with their smartphone. OCR technology extracts the product names and amounts from the receipt and captures them as income and expenditure data. The user's facial expressions are analyzed, and gentle advice is offered if they appear stressed. The server analyzes the income and expenditure data and displays specific advice, such as, "Your expenses have increased this month, so next time you shop, try replacing these items with cheaper alternatives."

[1703] Through this process, users can not only easily and effectively implement savings measures, but also enjoy a less stressful shopping experience.

[1704] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1705] Detailed explanation of the processing steps

[1706] Step 1:

[1707] The user takes a photo of the receipt with the smartphone camera. The input is the receipt image, and the output is image data. Specifically, the smartphone's camera app is launched, and the user takes a photo of the receipt.

[1708] Step 2:

[1709] The terminal uses OCR technology to extract text information from receipt images and convert it into balance data. The input is image data and the output is text data. Specifically, the image is read using the PIL library and the text information is extracted using pytesseract.

[1710] Step 3:

[1711] The terminal sends the balance data to the server using a secure communication protocol. The input is text data, and the output is the data sent to the server. Specifically, the data is sent as a POST request using the HTTP request library (requests).

[1712] Step 4:

[1713] The server analyzes the received income and expenditure data and categorizes it. The input is income and expenditure data, and the output is data categorized by category. Specifically, the server analyzes the data using an income and expenditure analysis algorithm and categorizes it into categories such as income and expenditure.

[1714] Step 5:

[1715] The server generates the optimal tax saving plan based on the latest tax information. The input is the analyzed income and expenditure data, and the output is the tax saving plan. Specifically, the server refers to the latest tax database and calculates the appropriate tax saving plan.

[1716] Step 6:

[1717] The emotion engine analyzes the user's facial expression and tone of voice to determine the user's current emotional state. The input is the user's facial expression or voice data, and the output is emotional state data. Specifically, it uses an emotion analysis algorithm to determine whether the user is feeling stressed.

[1718] Step 7:

[1719] The server simulates the tax savings effect of the tax saving plan and displays the results graphically. The input is the tax saving plan, and the output is the simulation result. Specifically, it uses a simulation algorithm to calculate the tax reduction effect and generates the data necessary to display it as a graph.

[1720] Step 8:

[1721] A generative AI model is used to provide optimal purchasing advice to users and generate specific prompts. The input is income and expenditure data and emotional state data, and the output is specific prompts. Specifically, the generative AI model analyzes the input data and generates prompts such as, "Please suggest the optimal savings plan based on the user's purchase history and bank statements. Please provide an encouraging message if the user is feeling stressed."

[1722] Step 9:

[1723] When a user selects a tax-saving plan, the server automatically generates the documents required for the application procedure and provides a download link to the terminal. The input is the selected tax-saving plan, and the output is a download link for the application documents. Specifically, the server uses a document generation algorithm to create the necessary application documents, generates a link for them, and sends it to the terminal.

[1724] 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.

[1725] 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.

[1726] 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.

[1727] 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.

[1728] 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.

[1729] 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.

[1730] 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).

[1731] 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.

[1732] 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."

[1733] 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.

[1734] 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).

[1735] 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.

[1736] 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.

[1737] 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.

[1738] 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.

[1739] 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.

[1740] 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.

[1741] 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.

[1742] 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.

[1743] 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.

[1744] 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.

[1745] The following is further disclosed regarding the above embodiment.

[1746] (Claim 1)

[1747] A means of obtaining income and expenditure data;

[1748] A means for analyzing the acquired income and expenditure data;

[1749] A means for generating an optimal tax saving plan based on the analyzed income and expenditure data;

[1750] A means for simulating the tax saving effect of the generated tax saving plan;

[1751] A system that includes means to support the application procedures required for tax-saving plans.

[1752] (Claim 2)

[1753] A means to learn the latest tax information and update the database;

[1754] 10. The system of claim 1, further comprising means for periodical...

Claims

1. A means of obtaining income and expenditure data; A means for analyzing the acquired income and expenditure data; A means for generating an optimal tax saving plan based on the analyzed income and expenditure data; A means for simulating the tax saving effect of the generated tax saving plan; A system that includes means to support the application procedures required for tax-saving plans.

2. A means to learn the latest tax information and update the database; 10. The system of claim 1, further comprising means for periodically updating the income and expenditure data and reevaluating the tax saving plan.

3. 10. The system of claim 1, further comprising means for obtaining the balance data using OCR technology.

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