system

Abstract

An object of the system according to the embodiment is to efficiently automate a working state of an employee, salary calculation, a social insurance procedure, and financial planning.SOLUTION: A system includes a working state collection part, a salary calculation part, a social insurance procedure part, a financial planning part, and a fund strategy proposal part. A working state collection part automatically collects the working state and PC operation of the employee. The salary calculation part automatically calculates the salary of the employee based on the data collected by the working state collection part. A social insurance procedure part automates procedures of social insurance and tax on the basis of the salary data calculated by the salary calculation part. A financial planning part simulates financial planning in the financial aspect of the employee on the basis of the salary data. A fund strategy proposing part proposes an effective fund strategy on the basis of the result simulated by the financial planning part.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] Conventional technologies do not adequately automate employee work status, payroll calculations, social insurance procedures, and financial planning efficiently, leaving room for improvement.

[0005] The system according to the embodiment aims to efficiently automate employee working status, payroll calculations, social insurance procedures, and financial planning. [Means for solving the problem]

[0006] The system according to the embodiment comprises a work status collection unit, a payroll calculation unit, a social insurance procedure unit, a financial planning unit, and a financial strategy proposal unit. The work status collection unit automatically collects employees' work status and PC operations. The payroll calculation unit automatically calculates employees' salaries based on the data collected by the work status collection unit. The social insurance procedure unit automates social insurance and tax procedures based on the payroll data calculated by the payroll calculation unit. The financial planning unit simulates financial planning for employees based on the payroll data. The financial strategy proposal unit proposes effective financial strategies based on the results of the simulation by the financial planning unit. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently automate employee work status, payroll calculations, social insurance procedures, and financial planning. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The automation service according to an embodiment of the present invention is a system that automatically collects employee work status and PC operation data, automates payroll calculations, social insurance and tax procedures using a generation AI, and also simulates financial planning and proposes funding strategies. As a result, the automation service can improve the efficiency and accuracy of payroll calculations and personnel processing.

[0029] The automated service according to the embodiment includes a work status collection unit, a payroll calculation unit, a social insurance procedure unit, a financial planning unit, and a financial strategy proposal unit. The work status collection unit automatically collects employee work status and PC operation data. For example, it records employee arrival and departure times, break times, and PC usage. The work status collection unit also monitors employee PC operation and collects the applications used, keystrokes, and mouse movements. The work status collection unit also collects employee biometric information (e.g., heart rate and body temperature) and uses it for detailed analysis of work status. For example, it monitors heart rate in real time to evaluate stress levels and concentration levels. The payroll calculation unit automatically calculates employee salaries based on the collected work status and PC operation data. For example, it calculates accurate salary amounts by taking into account base salary, overtime pay, transportation expenses, etc. The payroll calculation unit also calculates salaries taking into account employee skill levels and performance evaluations. For example, it sets base salary according to professional qualifications and technical skill levels. The Social Insurance Procedures Department automates social insurance and tax procedures based on payroll calculation results. For example, it automatically calculates social insurance premiums such as health insurance, employee pension insurance, and employment insurance, as well as taxes such as income tax and resident tax, and performs the necessary procedures. The Social Insurance Procedures Department also optimizes social insurance plans based on employees' family structures and life stages. For example, it adjusts insurance premiums based on the number of dependents. The Financial Planning Department simulates financial planning based on employees' salary information. For example, it proposes future savings plans, investment strategies, and loan repayment plans. The Financial Planning Department also proposes financial plans that take into account employees' life events (marriage, childbirth, home purchase, etc.). The Financial Strategy Proposal Department proposes effective financial strategies to employees based on the results of financial planning simulations. For example, it provides specific advice on how to increase savings, the timing of investments, and how to repay loans. The Financial Strategy Proposal Department also proposes financial strategies based on employees' short-, medium-, and long-term goals. For example, it recommends short-term savings goals and securing emergency funds. As a result, the automation service according to the embodiment can improve the efficiency and accuracy of payroll calculations and personnel processing.For example, you can accurately track employee working hours and pay them appropriately. Also, by automating social insurance and tax procedures, you can prevent procedural errors and save time. Furthermore, by supporting employees' financial planning, you can improve their quality of life.

[0030] The work status collection unit collects employees' heart rates and body temperatures, which can be used for detailed analysis of their work status. For example, the work status collection unit monitors employees' heart rates in real time to evaluate their stress levels and concentration levels. For example, it analyzes heart rate fluctuations to identify times when their concentration is low. The work status collection unit also periodically measures employees' body temperatures to understand their health status. For example, it detects abnormal fluctuations in body temperature to detect early signs of poor health. The work status collection unit also performs detailed analysis of employees' work patterns based on biometric information. For example, it combines heart rate and body temperature data to suggest optimal break times. This makes it possible to understand employees' health status and perform detailed analysis of their work status.

[0031] The work status collection unit can analyze the work content of employees in real time and evaluate their work efficiency and concentration level. For example, the work status collection unit analyzes employees' keystrokes and mouse movements to evaluate their work efficiency. For example, it measures efficiency based on input speed and number of clicks within a certain period of time. The work status collection unit also monitors application usage during work and evaluates the level of concentration. For example, if an employee frequently switches between applications, it determines that their level of concentration is low. The work status collection unit also analyzes work content in real time and suggests efficient work methods. For example, if there are frequent interruptions in work, it suggests re-prioritizing tasks. This allows the work efficiency and concentration level of employees to be evaluated in real time.

[0032] The work status collection unit also collects data from employees' smartphones and wearable devices, enabling a comprehensive understanding of their work status. For example, the work status collection unit collects location information from employees' smartphones to determine their work locations. For example, it analyzes their movement history inside and outside the office to accurately record their work hours. The work status collection unit also collects heart rate and step count data from wearable devices to monitor their health status. For example, it detects lack of exercise based on step count data and supports health management. The work status collection unit also integrates data from smartphones and wearable devices to comprehensively evaluate their work status. For example, it combines location information and heart rate data to evaluate their activity level during work. This allows data from smartphones and wearable devices to be collected and a comprehensive understanding of their work status.

[0033] The work status collection unit can introduce data collection methods customized for different business processes and departments. For example, for the sales department, the work status collection unit introduces a data collection method that records activities while out and about. For example, it automatically records visited locations using GPS data from smartphones. For the development department, the work status collection unit introduces a data collection method that records code edit history and build time. For example, it monitors IDE usage and evaluates work efficiency. For the customer support department, the work status collection unit introduces a data collection method that records call duration and number of cases handled. For example, it automatically collects call data by linking with a call center system. This makes it possible to introduce data collection methods customized for different business processes and departments.

[0034] The payroll calculation department can calculate salaries taking into account an employee's skill level and performance evaluation. For example, the payroll calculation department evaluates an employee's skill level and adjusts salaries based on that. For example, it sets a base salary according to the level of professional qualifications and technical skills. The payroll calculation department also calculates bonuses and incentives based on performance evaluation data. For example, it determines compensation according to the success rate of a project or the degree to which sales targets are achieved. The payroll calculation department also combines skill level and performance evaluation to perform comprehensive salary calculations. For example, it provides special allowances to employees with high skills and high performance. This makes it possible to calculate salaries taking into account an employee's skill level and performance evaluation.

[0035] The payroll calculation department can analyze employees' work patterns and propose optimal work schedules. For example, the payroll calculation department can analyze employees' work patterns and propose efficient work schedules. For example, it can assign important tasks to times when employees are most focused. The payroll calculation department can also propose the introduction of a flextime system based on the results of the work pattern analysis. For example, it can set flexible work hours that suit employees' lifestyles. The payroll calculation department can also analyze work patterns to detect early signs of overwork or stress. For example, it can recommend taking vacation if long working hours continue. This allows the department to analyze employees' work patterns and propose optimal work schedules.

[0036] The payroll calculation department can perform multilingual and multi-currency payroll calculations that correspond to the payroll systems of different countries and regions. For example, the payroll calculation department builds a multilingual and multi-currency payroll calculation system to correspond to the payroll systems of different countries and regions. For example, it supports multiple languages ​​such as English, French, and Chinese. The payroll calculation department also performs accurate payroll calculations based on the laws, regulations, and tax systems of each country. For example, it calculates salaries taking into account each country's minimum wage and tax rate. The payroll calculation department also introduces a multi-currency payroll calculation system to perform consistent payroll calculations even at international companies. For example, it automatically updates exchange rates and calculates accurate salary amounts. This makes it possible to perform multilingual and multi-currency payroll calculations that correspond to the payroll systems of different countries and regions.

[0037] The payroll calculation unit can perform payroll calculations that accommodate different employment types, such as freelancers and contract employees. For example, the payroll calculation unit calculates pay taking into account the working hours and project-based compensation of freelancers and contract employees. For example, compensation may be paid according to the degree of project completion. The payroll calculation unit also builds a flexible payroll calculation system to accommodate different employment types. For example, it performs hourly and performance-based payroll calculations. The payroll calculation unit also performs accurate payroll calculations based on the contract terms of freelancers and contract employees. For example, it calculates compensation according to the contract period and job content. This makes it possible to perform payroll calculations that accommodate different employment types, such as freelancers and contract employees.

[0038] The Social Insurance Procedures Department can optimize social insurance according to an employee's family structure and life stage. For example, the Social Insurance Procedures Department will consider an employee's family structure and propose the optimal social insurance plan. For example, it will adjust insurance premiums according to the number of dependents. The Social Insurance Procedures Department also optimizes social insurance according to an employee's life stage (marriage, childbirth, retirement, etc.). For example, it will automate the application for childcare leave benefits at the time of childbirth. The Social Insurance Procedures Department will also periodically review social insurance according to changes in family structure and life stage. For example, it will update the insurance plan as the child grows. This makes it possible to optimize social insurance according to an employee's family structure and life stage.

[0039] The Social Insurance Procedures Department can automatically suggest tax deductions and tax-saving measures. For example, the Social Insurance Procedures Department will suggest optimal tax deductions based on employee income and expenditure data. For example, it will automatically determine whether medical expense deductions or mortgage deductions apply. The Social Insurance Procedures Department will also build a system that automatically suggests tax-saving measures. For example, it will recommend the use of hometown tax donations and iDeCo (individual-type defined contribution pension plans). The Social Insurance Procedures Department will also customize its suggestions for tax deductions and tax-saving measures according to the employee's life stage and family structure. For example, it will suggest deductions for children's education expenses. This makes it possible to automatically suggest tax deductions and tax-saving measures.

[0040] The Social Insurance Procedure Department can carry out procedures that correspond to the social insurance systems and tax systems of different countries and regions. For example, the Social Insurance Procedure Department builds a multilingual procedure system to correspond to the social insurance systems and tax systems of each country. For example, it supports multiple languages ​​such as English, French, and Chinese. The Social Insurance Procedure Department also carries out accurate procedures based on the laws, regulations, and tax systems of each country. For example, it automates procedures taking into account the social insurance premiums and tax rates of each country. The Social Insurance Procedure Department also introduces a procedure system that corresponds to the social insurance systems and tax systems of different countries and regions for multinational corporations. For example, it automates the procedures required based on the laws, regulations, and regulations of each country. This makes it possible to carry out procedures that correspond to the social insurance systems and tax systems of different countries and regions.

[0041] The Social Insurance Procedures Department can handle social insurance and tax procedures for different employment types, such as freelancers and contract employees. The Social Insurance Procedures Department automates social insurance and tax procedures based on the contract terms of freelancers and contract employees. For example, it handles procedures based on the contract period and job content. The Social Insurance Procedures Department also builds a flexible procedure system to handle different employment types. For example, it automatically calculates social insurance premiums and taxes for freelancers and contract employees. The Social Insurance Procedures Department also handles accurate social insurance and tax procedures based on the work data of freelancers and contract employees. For example, it automates procedures based on project-based compensation. This makes it possible to handle social insurance and tax procedures for different employment types, such as freelancers and contract employees.

[0042] The financial planning department can propose financial plans that take into account employees' life events. The financial planning department proposes optimal financial plans, taking into account, for example, life events such as employees' marriage and childbirth. For example, it provides savings plans for wedding funds and education expenses. The financial planning department also proposes financial plans that take into account home purchases. For example, it provides mortgage repayment plans and savings plans for down payments. The financial planning department also customizes financial plans according to life events. For example, it provides savings plans for living expenses after retirement and medical expenses. In this way, it is possible to propose financial plans that take into account employees' life events.

[0043] The financial planning department can simulate investment strategies according to employees' risk tolerance. For example, the financial planning department evaluates employees' risk tolerance and proposes investment strategies based on that. For example, it recommends safe investment products to employees with low risk. The financial planning department also performs investment simulations according to risk tolerance and proposes optimal investment portfolios. For example, it recommends high-return investment products to employees with high risk. The financial planning department also customizes investment strategies based on risk tolerance. For example, it provides a balanced investment portfolio to employees with medium risk. This makes it possible to simulate investment strategies according to employees' risk tolerance.

[0044] The financial planning department can propose financial plans that correspond to financial products and investment opportunities in different countries and regions. For example, the financial planning department builds a multilingual financial planning system to accommodate financial products and investment opportunities in each country. For example, it supports multiple languages ​​such as English, French, and Chinese. The financial planning department also proposes optimal financial plans based on the laws and regulations and market trends of each country. For example, it customizes financial plans taking into account the financial products and investment opportunities of each country. The financial planning department also introduces financial planning systems that correspond to financial products and investment opportunities in different countries and regions for multinational corporations. For example, it proposes optimal investment strategies based on the market trends of each country. This enables it to propose financial plans that correspond to financial products and investment opportunities in different countries and regions.

[0045] The financial planning department can propose financial plans that accommodate different employment types, such as freelancers and contract employees. For example, the financial planning department proposes optimal financial plans based on income and expenditure data of freelancers and contract employees. For example, it provides savings plans that accommodate project-based income. The financial planning department also builds flexible financial planning systems to accommodate different employment types. For example, it proposes investment strategies for freelancers and contract employees. The financial planning department also customizes financial plans that accommodate the lifestyles of freelancers and contract employees. For example, it provides risk management plans that accommodate irregular income. This makes it possible to propose financial plans that accommodate different employment types, such as freelancers and contract employees.

[0046] The Financial Strategy Proposal Department can propose financial strategies according to employees' short-term, medium-term, and long-term goals. For example, the Financial Strategy Proposal Department proposes financial strategies according to employees' short-term goals (within one year). For example, it recommends short-term savings goals and the establishment of emergency funds. The Financial Strategy Proposal Department also proposes financial strategies according to employees' medium-term goals (1 to 5 years). For example, it provides savings plans for purchasing a home or for education expenses. The Financial Strategy Proposal Department also proposes financial strategies according to employees' long-term goals (5 years or more). For example, it provides savings plans for living expenses after retirement and medical expenses in old age. This makes it possible to propose financial strategies according to employees' short-term, medium-term, and long-term goals.

[0047] The Financial Strategy Proposal Department can propose a financial strategy based on the employee's risk profile. For example, the Financial Strategy Proposal Department evaluates the employee's risk profile and proposes a financial strategy based on it. For example, it recommends safe investment products to employees with low risk. The Financial Strategy Proposal Department also performs investment simulations according to the risk profile and proposes an optimal investment portfolio. For example, it recommends high-return investment products to employees with high risk. The Financial Strategy Proposal Department also customizes the financial strategy based on the risk profile. For example, it provides a balanced investment portfolio to employees with medium risk. This makes it possible to propose a financial strategy based on the employee's risk profile.

[0048] The Financial Strategy Proposal Department can propose financial strategies that correspond to the financial markets of different countries and regions. For example, the Financial Strategy Proposal Department builds a multilingual financial strategy system to correspond to the financial markets of each country. For example, it supports multiple languages ​​such as English, French, and Chinese. The Financial Strategy Proposal Department also proposes the optimal financial strategy based on the laws and regulations and market trends of each country. For example, it customizes the financial strategy taking into account the financial products and investment opportunities of each country. The Financial Strategy Proposal Department also introduces a financial strategy system that corresponds to the financial markets of different countries and regions for multinational corporations. For example, it proposes the optimal investment strategy based on the market trends of each country. This makes it possible to propose financial strategies that correspond to the financial markets of different countries and regions.

[0049] The financial strategy proposal department can propose financial strategies that accommodate different employment types, such as freelancers and contract employees. The financial strategy proposal department proposes optimal financial strategies, for example, based on income and expenditure data of freelancers and contract employees. For example, it provides savings plans that accommodate project-based income. The financial strategy proposal department also builds flexible financial strategy systems to accommodate different employment types. For example, it proposes investment strategies for freelancers and contract employees. The financial strategy proposal department also customizes financial strategies that accommodate the lifestyles of freelancers and contract employees. For example, it provides risk management plans that accommodate irregular income. This makes it possible to propose financial strategies that accommodate different employment types, such as freelancers and contract employees.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The work status collection unit collects data on the environment around employees' desks to improve work efficiency. For example, it monitors the brightness, temperature, and humidity of desk lighting and suggests the optimal environment. The work status collection unit also uses a camera to check the tidiness of desks and provides advice on maintaining an efficient work environment. Furthermore, the work status collection unit measures the noise level around the desk and recommends the use of noise-canceling headphones to improve concentration. This allows for the optimization of employees' desk environments and improves work efficiency.

[0052] The work status collection unit can collect and analyze regular health checkup data to understand employees' health status. For example, it can monitor health indicators such as blood pressure, blood sugar levels, and cholesterol levels to detect health risks early. The work status collection unit also records employees' dietary and exercise habits to encourage healthy lifestyles. Furthermore, the work status collection unit can collect employees' sleep data and provide advice on improving sleep quality. This allows for a comprehensive understanding of employees' health status and reduces health risks.

[0053] The work status collection unit analyzes employee communication patterns and can strengthen team cooperation. For example, it analyzes email and chat exchanges to evaluate the frequency and content of communication. The work status collection unit also records the content and number of comments made in meetings, in order to stimulate the exchange of opinions within the team. Furthermore, the work status collection unit visualizes the cooperative relationships between employees and suggests effective team-building methods. This makes it possible to analyze employee communication patterns and strengthen team cooperation.

[0054] The work status collection unit also collects data from employees' smartphones and wearable devices, enabling a comprehensive understanding of their work status. For example, it collects location information from employees' smartphones to determine their work locations. For example, it analyzes their movement history both inside and outside the office to accurately record their work hours. The work status collection unit also collects heart rate and step count data from wearable devices to monitor their health status. For example, it can detect lack of exercise based on step count data and support health management. The work status collection unit also integrates data from smartphones and wearable devices to comprehensively evaluate their work status. For example, it can combine location information and heart rate data to evaluate their activity level during work. This allows data from smartphones and wearable devices to be collected and a comprehensive understanding of their work status.

[0055] The Work Status Collection Department can implement data collection methods customized for different business processes and departments. For example, for the sales department, a data collection method can be implemented that records activities while out and about. For example, GPS data from smartphones can be used to automatically record visited locations. For the development department, the Work Status Collection Department can implement a data collection method that records code edit history and build times. For example, IDE usage can be monitored to evaluate work efficiency. For the customer support department, the Work Status Collection Department can implement a data collection method that records call duration and number of cases handled. For example, call data can be automatically collected by linking with a call center system. This makes it possible to implement data collection methods customized for different business processes and departments.

[0056] The payroll calculation department can calculate salaries taking into account an employee's skill level and performance evaluation. For example, it can evaluate an employee's skill level and adjust their salary based on that. For example, it can set a base salary according to the level of professional qualifications and technical skills. The payroll calculation department also calculates bonuses and incentives based on performance evaluation data. For example, it can determine compensation based on the success rate of a project or the degree to which sales targets are achieved. The payroll calculation department can also combine skill level and performance evaluation to perform comprehensive salary calculations. For example, it can provide special allowances to highly skilled and high-performing employees. This makes it possible to calculate salaries taking into account an employee's skill level and performance evaluation.

[0057] The payroll department can analyze employees' work patterns and propose optimal work schedules. For example, it can analyze employees' work patterns and propose efficient work schedules. For example, it can assign important tasks to times when employees are most focused. The payroll department can also propose the introduction of a flextime system based on the results of the work pattern analysis. For example, it can set flexible working hours to suit employees' lifestyles. The payroll department can also analyze work patterns to detect early signs of overwork or stress. For example, it can recommend taking vacation if long working hours continue. This allows the department to analyze employees' work patterns and propose optimal work schedules.

[0058] The processing flow of the first embodiment will be briefly explained below.

[0059] Step 1: The work status collection unit automatically collects employee work status and PC operation information. For example, it records the time employees arrive and leave work, break times, and PC usage. The work status collection unit also monitors employees' PC operation, collecting the applications used, keystrokes, and mouse movements. The work status collection unit also collects employees' biometric information (heart rate, body temperature, etc.) and uses this information for detailed analysis of their work status. For example, it monitors heart rate in real time to evaluate stress levels and concentration levels. Step 2: The payroll calculation department automatically calculates employee salaries based on the collected data on working conditions and PC operation. For example, it calculates the exact salary amount by taking into account basic salary, overtime pay, transportation expenses, etc. The payroll calculation department also calculates salaries taking into account the employee's skill level and performance evaluation. For example, it sets basic salary according to the level of professional qualifications and technical skills. Step 3: The Social Insurance Procedures Department automates social insurance and tax procedures based on the results of payroll calculations. For example, it automatically calculates social insurance premiums such as health insurance, employee pension insurance, and employment insurance, as well as taxes such as income tax and resident tax, and carries out the necessary procedures. The Social Insurance Procedures Department also optimizes social insurance according to employees' family structures and life stages. For example, it adjusts insurance premiums according to the number of dependents. Step 4: The Financial Planning Department simulates financial planning based on employee salary information. For example, they propose future savings plans, investment strategies, loan repayment plans, etc. The Financial Planning Department also proposes financial plans that take into account employee life events (marriage, childbirth, home purchase, etc.). Step 5: The Financial Strategy Proposal Department proposes effective financial strategies to employees based on the results of the financial planning simulation. For example, they provide specific advice on how to increase savings, when to invest, and how to repay loans. The Financial Strategy Proposal Department also proposes financial strategies based on employees' short-, medium-, and long-term goals. For example, they recommend short-term savings goals and securing emergency funds.

[0060] (Example 2) The automation service according to an embodiment of the present invention is a system that automatically collects employee work status and PC operation data, automates payroll calculations, social insurance and tax procedures using a generation AI, and also simulates financial planning and proposes funding strategies. As a result, the automation service can improve the efficiency and accuracy of payroll calculations and personnel processing.

[0061] The automated service according to the embodiment includes a work status collection unit, a payroll calculation unit, a social insurance procedure unit, a financial planning unit, and a financial strategy proposal unit. The work status collection unit automatically collects employee work status and PC operation data. For example, it records employee arrival and departure times, break times, and PC usage. The work status collection unit also monitors employee PC operation and collects the applications used, keystrokes, and mouse movements. The work status collection unit also collects employee biometric information (e.g., heart rate and body temperature) and uses it for detailed analysis of work status. For example, it monitors heart rate in real time to evaluate stress levels and concentration levels. The payroll calculation unit automatically calculates employee salaries based on the collected work status and PC operation data. For example, it calculates accurate salary amounts by taking into account base salary, overtime pay, transportation expenses, etc. The payroll calculation unit also calculates salaries taking into account employee skill levels and performance evaluations. For example, it sets base salary according to professional qualifications and technical skill levels. The Social Insurance Procedures Department automates social insurance and tax procedures based on payroll calculation results. For example, it automatically calculates social insurance premiums such as health insurance, employee pension insurance, and employment insurance, as well as taxes such as income tax and resident tax, and performs the necessary procedures. The Social Insurance Procedures Department also optimizes social insurance plans based on employees' family structures and life stages. For example, it adjusts insurance premiums based on the number of dependents. The Financial Planning Department simulates financial planning based on employees' salary information. For example, it proposes future savings plans, investment strategies, and loan repayment plans. The Financial Planning Department also proposes financial plans that take into account employees' life events (marriage, childbirth, home purchase, etc.). The Financial Strategy Proposal Department proposes effective financial strategies to employees based on the results of financial planning simulations. For example, it provides specific advice on how to increase savings, the timing of investments, and how to repay loans. The Financial Strategy Proposal Department also proposes financial strategies based on employees' short-, medium-, and long-term goals. For example, it recommends short-term savings goals and securing emergency funds. As a result, the automation service according to the embodiment can improve the efficiency and accuracy of payroll calculations and personnel processing.For example, you can accurately track employee working hours and pay them appropriately. Also, by automating social insurance and tax procedures, you can prevent procedural errors and save time. Furthermore, by supporting employees' financial planning, you can improve their quality of life.

[0062] The work status collection unit collects employees' heart rates and body temperatures, which can be used for detailed analysis of their work status. For example, the work status collection unit monitors employees' heart rates in real time to evaluate their stress levels and concentration levels. For example, it analyzes heart rate fluctuations to identify times when their concentration is low. The work status collection unit also periodically measures employees' body temperatures to understand their health status. For example, it detects abnormal fluctuations in body temperature to detect early signs of poor health. The work status collection unit also performs detailed analysis of employees' work patterns based on biometric information. For example, it combines heart rate and body temperature data to suggest optimal break times. This makes it possible to understand employees' health status and perform detailed analysis of their work status.

[0063] The work status collection unit can analyze the work content of employees in real time and evaluate their work efficiency and concentration level. For example, the work status collection unit analyzes employees' keystrokes and mouse movements to evaluate their work efficiency. For example, it measures efficiency based on input speed and number of clicks within a certain period of time. The work status collection unit also monitors application usage during work and evaluates the level of concentration. For example, if an employee frequently switches between applications, it determines that their level of concentration is low. The work status collection unit also analyzes work content in real time and suggests efficient work methods. For example, if there are frequent interruptions in work, it suggests re-prioritizing tasks. This allows the work efficiency and concentration level of employees to be evaluated in real time.

[0064] The work status collection unit can use the emotion estimation function to grasp the emotional state of employees and evaluate their stress levels and motivation. The work status collection unit, for example, analyzes the facial expressions of employees to grasp their emotional state in real time. For example, it uses a camera to detect changes in facial expression and evaluates their stress level. The work status collection unit also uses voice analysis technology to estimate the emotional state from the tone of voice and speaking style of the employee. For example, if the tone of voice is low, it is determined that stress is high. The work status collection unit also evaluates the motivation of employees based on the emotion estimation data. For example, if there are many positive emotions, it is determined that motivation is high. This makes it possible to grasp the emotional state of employees and evaluate their stress levels and motivation.

[0065] The work status collection unit also collects data from employees' smartphones and wearable devices, enabling a comprehensive understanding of their work status. For example, the work status collection unit collects location information from employees' smartphones to determine their work locations. For example, it analyzes their movement history inside and outside the office to accurately record their work hours. The work status collection unit also collects heart rate and step count data from wearable devices to monitor their health status. For example, it detects lack of exercise based on step count data and supports health management. The work status collection unit also integrates data from smartphones and wearable devices to comprehensively evaluate their work status. For example, it combines location information and heart rate data to evaluate their activity level during work. This allows data from smartphones and wearable devices to be collected and a comprehensive understanding of their work status.

[0066] The work status collection unit can introduce data collection methods customized for different business processes and departments. For example, for the sales department, the work status collection unit introduces a data collection method that records activities while out and about. For example, it automatically records visited locations using GPS data from smartphones. For the development department, the work status collection unit introduces a data collection method that records code edit history and build time. For example, it monitors IDE usage and evaluates work efficiency. For the customer support department, the work status collection unit introduces a data collection method that records call duration and number of cases handled. For example, it automatically collects call data by linking with a call center system. This makes it possible to introduce data collection methods customized for different business processes and departments.

[0067] The work status collection unit can use the emotion estimation function to suggest optimization of the work environment according to the emotional state of the employee. For example, based on the emotion estimation data, the work status collection unit suggests a relaxing environment when an employee's stress level is high. For example, it recommends increasing break time or using a relaxation space. The work status collection unit also sends encouraging messages based on the emotion estimation data when an employee's motivation is low. For example, it shares positive feedback and success stories. The work status collection unit also suggests adjustments to the work schedule according to the employee's emotional state based on the emotion estimation data. For example, it assigns important tasks to times when employees are most likely to concentrate. This makes it possible to suggest optimization of the work environment according to the employee's emotional state.

[0068] The payroll calculation department can calculate salaries taking into account an employee's skill level and performance evaluation. For example, the payroll calculation department evaluates an employee's skill level and adjusts salaries based on that. For example, it sets a base salary according to the level of professional qualifications and technical skills. The payroll calculation department also calculates bonuses and incentives based on performance evaluation data. For example, it determines compensation according to the success rate of a project or the degree to which sales targets are achieved. The payroll calculation department also combines skill level and performance evaluation to perform comprehensive salary calculations. For example, it provides special allowances to employees with high skills and high performance. This makes it possible to calculate salaries taking into account an employee's skill level and performance evaluation.

[0069] The payroll calculation department can analyze employees' work patterns and propose optimal work schedules. For example, the payroll calculation department can analyze employees' work patterns and propose efficient work schedules. For example, it can assign important tasks to times when employees are most focused. The payroll calculation department can also propose the introduction of a flextime system based on the results of the work pattern analysis. For example, it can set flexible work hours that suit employees' lifestyles. The payroll calculation department can also analyze work patterns to detect early signs of overwork or stress. For example, it can recommend taking vacation if long working hours continue. This allows the department to analyze employees' work patterns and propose optimal work schedules.

[0070] The payroll calculation department can use the emotion estimation function to introduce an incentive system based on the emotional state of employees. For example, the payroll calculation department provides incentives to employees who have a lot of positive emotions based on the emotion estimation data. For example, it provides special bonuses to highly motivated employees. The payroll calculation department also provides relaxation programs to employees who are highly stressed based on the emotion estimation data. For example, it grants special holidays to reduce stress. The payroll calculation department also designs incentive systems according to the emotional state of employees based on the emotion estimation data. For example, it provides career advancement opportunities to employees with high emotion scores. This makes it possible to introduce incentive systems based on the emotional state of employees.

[0071] The payroll calculation department can perform multilingual and multi-currency payroll calculations that correspond to the payroll systems of different countries and regions. For example, the payroll calculation department builds a multilingual and multi-currency payroll calculation system to correspond to the payroll systems of different countries and regions. For example, it supports multiple languages ​​such as English, French, and Chinese. The payroll calculation department also performs accurate payroll calculations based on the laws, regulations, and tax systems of each country. For example, it calculates salaries taking into account each country's minimum wage and tax rate. The payroll calculation department also introduces a multi-currency payroll calculation system to perform consistent payroll calculations even at international companies. For example, it automatically updates exchange rates and calculates accurate salary amounts. This makes it possible to perform multilingual and multi-currency payroll calculations that correspond to the payroll systems of different countries and regions.

[0072] The payroll calculation unit can perform payroll calculations that accommodate different employment types, such as freelancers and contract employees. For example, the payroll calculation unit calculates pay taking into account the working hours and project-based compensation of freelancers and contract employees. For example, compensation may be paid according to the degree of project completion. The payroll calculation unit also builds a flexible payroll calculation system to accommodate different employment types. For example, it performs hourly and performance-based payroll calculations. The payroll calculation unit also performs accurate payroll calculations based on the contract terms of freelancers and contract employees. For example, it calculates compensation according to the contract period and job content. This makes it possible to perform payroll calculations that accommodate different employment types, such as freelancers and contract employees.

[0073] The payroll calculation unit can use the emotion estimation function to propose a flexible pay system that corresponds to the emotional state of employees. The payroll calculation unit proposes a flexible pay system that corresponds to the emotional state of employees, for example, based on the emotion estimation data. For example, it increases performance-based rewards for highly motivated employees. The payroll calculation unit also provides special allowances to employees with high stress levels based on the emotion estimation data. For example, it provides relaxation allowances to reduce stress. The payroll calculation unit also designs a pay system that corresponds to the emotional state of employees, based on the emotion estimation data. For example, it provides career advancement opportunities to employees with high emotion scores. This makes it possible to propose a flexible pay system that corresponds to the emotional state of employees.

[0074] The Social Insurance Procedures Department can optimize social insurance according to an employee's family structure and life stage. For example, the Social Insurance Procedures Department will consider an employee's family structure and propose the optimal social insurance plan. For example, it will adjust insurance premiums according to the number of dependents. The Social Insurance Procedures Department also optimizes social insurance according to an employee's life stage (marriage, childbirth, retirement, etc.). For example, it will automate the application for childcare leave benefits at the time of childbirth. The Social Insurance Procedures Department will also periodically review social insurance according to changes in family structure and life stage. For example, it will update the insurance plan as the child grows. This makes it possible to optimize social insurance according to an employee's family structure and life stage.

[0075] The Social Insurance Procedures Department can automatically suggest tax deductions and tax-saving measures. For example, the Social Insurance Procedures Department will suggest optimal tax deductions based on employee income and expenditure data. For example, it will automatically determine whether medical expense deductions or mortgage deductions apply. The Social Insurance Procedures Department will also build a system that automatically suggests tax-saving measures. For example, it will recommend the use of hometown tax donations and iDeCo (individual-type defined contribution pension plans). The Social Insurance Procedures Department will also customize its suggestions for tax deductions and tax-saving measures according to the employee's life stage and family structure. For example, it will suggest deductions for children's education expenses. This makes it possible to automatically suggest tax deductions and tax-saving measures.

[0076] The social insurance procedure department can use the emotion estimation function to propose employee benefits based on the emotional state of employees. For example, based on the emotion estimation data, the social insurance procedure department can propose a relaxation program if an employee's stress level is high. For example, it can recommend massage or yoga classes. Furthermore, based on the emotion estimation data, the social insurance procedure department can provide career advancement opportunities if an employee's motivation is low. For example, it can propose skill development training or support for obtaining qualifications. Furthermore, based on the emotion estimation data, the social insurance procedure department can design employee benefit plans according to the employee's emotional state. For example, it can provide special leave to employees with high emotion scores. This makes it possible to propose employee benefits based on the employee's emotional state.

[0077] The Social Insurance Procedure Department can carry out procedures that correspond to the social insurance systems and tax systems of different countries and regions. For example, the Social Insurance Procedure Department builds a multilingual procedure system to correspond to the social insurance systems and tax systems of each country. For example, it supports multiple languages ​​such as English, French, and Chinese. The Social Insurance Procedure Department also carries out accurate procedures based on the laws, regulations, and tax systems of each country. For example, it automates procedures taking into account the social insurance premiums and tax rates of each country. The Social Insurance Procedure Department also introduces a procedure system that corresponds to the social insurance systems and tax systems of different countries and regions for multinational corporations. For example, it automates the procedures required based on the laws, regulations, and regulations of each country. This makes it possible to carry out procedures that correspond to the social insurance systems and tax systems of different countries and regions.

[0078] The Social Insurance Procedures Department can handle social insurance and tax procedures for different employment types, such as freelancers and contract employees. The Social Insurance Procedures Department automates social insurance and tax procedures based on the contract terms of freelancers and contract employees. For example, it handles procedures based on the contract period and job content. The Social Insurance Procedures Department also builds a flexible procedure system to handle different employment types. For example, it automatically calculates social insurance premiums and taxes for freelancers and contract employees. The Social Insurance Procedures Department also handles accurate social insurance and tax procedures based on the work data of freelancers and contract employees. For example, it automates procedures based on project-based compensation. This makes it possible to handle social insurance and tax procedures for different employment types, such as freelancers and contract employees.

[0079] The social insurance procedure department can use the emotion estimation function to propose optimization of social insurance and taxes according to the emotional state of an employee. For example, the social insurance procedure department proposes a social insurance plan according to the emotional state of an employee based on the emotion estimation data. For example, it provides a relaxation program to employees with high stress levels. The social insurance procedure department also proposes tax deductions according to the emotional state of an employee based on the emotion estimation data. For example, it applies special deductions to employees with high emotion scores. The social insurance procedure department also optimizes social insurance and taxes according to the emotional state of an employee based on the emotion estimation data. For example, it provides special allowances to employees with high emotion scores. This makes it possible to propose optimization of social insurance and taxes according to the emotional state of an employee.

[0080] The financial planning department can propose financial plans that take into account employees' life events. The financial planning department proposes optimal financial plans, taking into account, for example, life events such as employees' marriage and childbirth. For example, it provides savings plans for wedding funds and education expenses. The financial planning department also proposes financial plans that take into account home purchases. For example, it provides mortgage repayment plans and savings plans for down payments. The financial planning department also customizes financial plans according to life events. For example, it provides savings plans for living expenses after retirement and medical expenses. In this way, it is possible to propose financial plans that take into account employees' life events.

[0081] The financial planning department can simulate investment strategies according to employees' risk tolerance. For example, the financial planning department evaluates employees' risk tolerance and proposes investment strategies based on that. For example, it recommends safe investment products to employees with low risk. The financial planning department also performs investment simulations according to risk tolerance and proposes optimal investment portfolios. For example, it recommends high-return investment products to employees with high risk. The financial planning department also customizes investment strategies based on risk tolerance. For example, it provides a balanced investment portfolio to employees with medium risk. This makes it possible to simulate investment strategies according to employees' risk tolerance.

[0082] The financial planning department can use the emotion estimation function to propose a financial plan based on the emotional state of the employee. For example, the financial planning department proposes a financial plan according to the emotional state of the employee based on the emotion estimation data. For example, it recommends low-risk investment products to employees with high stress levels. The financial planning department also proposes a savings plan according to the emotional state of the employee based on the emotion estimation data. For example, it provides an aggressive savings plan to employees with high emotion scores. The financial planning department also customizes a financial plan according to the emotional state of the employee based on the emotion estimation data. For example, it provides a low-risk financial plan to employees with low emotion scores. This makes it possible to propose a financial plan based on the emotional state of the employee.

[0083] The financial planning department can propose financial plans that correspond to financial products and investment opportunities in different countries and regions. For example, the financial planning department builds a multilingual financial planning system to accommodate financial products and investment opportunities in each country. For example, it supports multiple languages ​​such as English, French, and Chinese. The financial planning department also proposes optimal financial plans based on the laws and regulations and market trends of each country. For example, it customizes financial plans taking into account the financial products and investment opportunities of each country. The financial planning department also introduces financial planning systems that correspond to financial products and investment opportunities in different countries and regions for multinational corporations. For example, it proposes optimal investment strategies based on the market trends of each country. This enables it to propose financial plans that correspond to financial products and investment opportunities in different countries and regions.

[0084] The financial planning department can propose financial plans that accommodate different employment types, such as freelancers and contract employees. For example, the financial planning department proposes optimal financial plans based on income and expenditure data of freelancers and contract employees. For example, it provides savings plans that accommodate project-based income. The financial planning department also builds flexible financial planning systems to accommodate different employment types. For example, it proposes investment strategies for freelancers and contract employees. The financial planning department also customizes financial plans that accommodate the lifestyles of freelancers and contract employees. For example, it provides risk management plans that accommodate irregular income. This makes it possible to propose financial plans that accommodate different employment types, such as freelancers and contract employees.

[0085] The financial planning department can use the emotion estimation function to propose a financial plan that corresponds to the emotional state of the employee. For example, the financial planning department proposes a financial plan that corresponds to the emotional state of the employee based on the emotion estimation data. For example, it recommends low-risk investment products to employees with high stress levels. The financial planning department also proposes a savings plan that corresponds to the emotional state of the employee based on the emotion estimation data. For example, it provides an aggressive savings plan to employees with high emotion scores. The financial planning department also customizes a financial plan that corresponds to the emotional state of the employee based on the emotion estimation data. For example, it provides a low-risk financial plan to employees with low emotion scores. This makes it possible to propose a financial plan that corresponds to the emotional state of the employee.

[0086] The Financial Strategy Proposal Department can propose financial strategies according to employees' short-term, medium-term, and long-term goals. For example, the Financial Strategy Proposal Department proposes financial strategies according to employees' short-term goals (within one year). For example, it recommends short-term savings goals and the establishment of emergency funds. The Financial Strategy Proposal Department also proposes financial strategies according to employees' medium-term goals (1 to 5 years). For example, it provides savings plans for purchasing a home or for education expenses. The Financial Strategy Proposal Department also proposes financial strategies according to employees' long-term goals (5 years or more). For example, it provides savings plans for living expenses after retirement and medical expenses in old age. This makes it possible to propose financial strategies according to employees' short-term, medium-term, and long-term goals.

[0087] The Financial Strategy Proposal Department can propose a financial strategy based on the employee's risk profile. For example, the Financial Strategy Proposal Department evaluates the employee's risk profile and proposes a financial strategy based on it. For example, it recommends safe investment products to employees with low risk. The Financial Strategy Proposal Department also performs investment simulations according to the risk profile and proposes an optimal investment portfolio. For example, it recommends high-return investment products to employees with high risk. The Financial Strategy Proposal Department also customizes the financial strategy based on the risk profile. For example, it provides a balanced investment portfolio to employees with medium risk. This makes it possible to propose a financial strategy based on the employee's risk profile.

[0088] The financial strategy proposal unit can use the emotion estimation function to propose a financial strategy based on the emotional state of the employee. The financial strategy proposal unit, for example, proposes a financial strategy according to the emotional state of the employee based on the emotion estimation data. For example, it recommends low-risk investment products to employees with high stress levels. The financial strategy proposal unit also proposes a savings plan according to the emotional state of the employee based on the emotion estimation data. For example, it provides an aggressive savings plan to employees with high emotion scores. The financial strategy proposal unit also customizes a financial strategy according to the emotional state of the employee based on the emotion estimation data. For example, it provides a low-risk financial strategy to employees with low emotion scores. This makes it possible to propose a financial strategy based on the emotional state of the employee.

[0089] The Financial Strategy Proposal Department can propose financial strategies that correspond to the financial markets of different countries and regions. For example, the Financial Strategy Proposal Department builds a multilingual financial strategy system to correspond to the financial markets of each country. For example, it supports multiple languages ​​such as English, French, and Chinese. The Financial Strategy Proposal Department also proposes the optimal financial strategy based on the laws and regulations and market trends of each country. For example, it customizes the financial strategy taking into account the financial products and investment opportunities of each country. The Financial Strategy Proposal Department also introduces a financial strategy system that corresponds to the financial markets of different countries and regions for multinational corporations. For example, it proposes the optimal investment strategy based on the market trends of each country. This makes it possible to propose financial strategies that correspond to the financial markets of different countries and regions.

[0090] The financial strategy proposal department can propose financial strategies that accommodate different employment types, such as freelancers and contract employees. The financial strategy proposal department proposes optimal financial strategies, for example, based on income and expenditure data of freelancers and contract employees. For example, it provides savings plans that accommodate project-based income. The financial strategy proposal department also builds flexible financial strategy systems to accommodate different employment types. For example, it proposes investment strategies for freelancers and contract employees. The financial strategy proposal department also customizes financial strategies that accommodate the lifestyles of freelancers and contract employees. For example, it provides risk management plans that accommodate irregular income. This makes it possible to propose financial strategies that accommodate different employment types, such as freelancers and contract employees.

[0091] The financial strategy proposal unit can use the emotion estimation function to propose a financial strategy based on the emotional state of the employee. The financial strategy proposal unit, for example, proposes a financial strategy according to the emotional state of the employee based on the emotion estimation data. For example, it recommends low-risk investment products to employees with high stress levels. The financial strategy proposal unit also proposes a savings plan according to the emotional state of the employee based on the emotion estimation data. For example, it provides an aggressive savings plan to employees with high emotion scores. The financial strategy proposal unit also customizes a financial strategy according to the emotional state of the employee based on the emotion estimation data. For example, it provides a low-risk financial strategy to employees with low emotion scores. This makes it possible to propose a financial strategy based on the emotional state of the employee.

[0092] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0093] The work status collection unit collects data on the environment around employees' desks to improve work efficiency. For example, it monitors the brightness, temperature, and humidity of desk lighting and suggests the optimal environment. The work status collection unit also uses a camera to check the tidiness of desks and provides advice on maintaining an efficient work environment. Furthermore, the work status collection unit measures the noise level around the desk and recommends the use of noise-canceling headphones to improve concentration. This allows for the optimization of employees' desk environments and improves work efficiency.

[0094] The work status collection unit can collect and analyze regular health checkup data to understand employees' health status. For example, it can monitor health indicators such as blood pressure, blood sugar levels, and cholesterol levels to detect health risks early. The work status collection unit also records employees' dietary and exercise habits to encourage healthy lifestyles. Furthermore, the work status collection unit can collect employees' sleep data and provide advice on improving sleep quality. This allows for a comprehensive understanding of employees' health status and reduces health risks.

[0095] The work status collection unit analyzes employee communication patterns and can strengthen team cooperation. For example, it analyzes email and chat exchanges to evaluate the frequency and content of communication. The work status collection unit also records the content and number of comments made in meetings, in order to stimulate the exchange of opinions within the team. Furthermore, the work status collection unit visualizes the cooperative relationships between employees and suggests effective team-building methods. This makes it possible to analyze employee communication patterns and strengthen team cooperation.

[0096] The work status collection unit can use the emotion estimation function to provide feedback based on the employee's emotional state. For example, based on the emotion estimation data, it can suggest relaxing activities when an employee's stress level is high. For example, it can recommend a short break or stretching time. The work status collection unit can also use the emotion estimation data to send encouraging messages when an employee's motivation is low. For example, it can share positive feedback or success stories. Furthermore, the work status collection unit can provide personalized feedback based on the employee's emotional state based on the emotion estimation data. This makes it possible to provide feedback based on the employee's emotional state and manage stress levels and motivation.

[0097] The work status collection unit also collects data from employees' smartphones and wearable devices, enabling a comprehensive understanding of their work status. For example, it collects location information from employees' smartphones to determine their work locations. For example, it analyzes their movement history both inside and outside the office to accurately record their work hours. The work status collection unit also collects heart rate and step count data from wearable devices to monitor their health status. For example, it can detect lack of exercise based on step count data and support health management. The work status collection unit also integrates data from smartphones and wearable devices to comprehensively evaluate their work status. For example, it can combine location information and heart rate data to evaluate their activity level during work. This allows data from smartphones and wearable devices to be collected and a comprehensive understanding of their work status.

[0098] The Work Status Collection Department can implement data collection methods customized for different business processes and departments. For example, for the sales department, a data collection method can be implemented that records activities while out and about. For example, GPS data from smartphones can be used to automatically record visited locations. For the development department, the Work Status Collection Department can implement a data collection method that records code edit history and build times. For example, IDE usage can be monitored to evaluate work efficiency. For the customer support department, the Work Status Collection Department can implement a data collection method that records call duration and number of cases handled. For example, call data can be automatically collected by linking with a call center system. This makes it possible to implement data collection methods customized for different business processes and departments.

[0099] The work status collection unit can use the emotion estimation function to suggest ways to optimize the work environment according to the employee's emotional state. For example, based on the emotion estimation data, it can suggest a relaxing environment when an employee's stress level is high. For example, it can recommend increasing break time or using a relaxation space. The work status collection unit can also use the emotion estimation data to send encouraging messages when an employee's motivation is low. For example, it can share positive feedback or success stories. The work status collection unit can also use the emotion estimation data to suggest ways to adjust the work schedule according to the employee's emotional state. For example, it can assign important tasks to times when employees are most likely to concentrate. This makes it possible to suggest ways to optimize the work environment according to the employee's emotional state.

[0100] The payroll calculation department can calculate salaries taking into account an employee's skill level and performance evaluation. For example, it can evaluate an employee's skill level and adjust their salary based on that. For example, it can set a base salary according to the level of professional qualifications and technical skills. The payroll calculation department also calculates bonuses and incentives based on performance evaluation data. For example, it can determine compensation based on the success rate of a project or the degree to which sales targets are achieved. The payroll calculation department can also combine skill level and performance evaluation to perform comprehensive salary calculations. For example, it can provide special allowances to highly skilled and high-performing employees. This makes it possible to calculate salaries taking into account an employee's skill level and performance evaluation.

[0101] The payroll department can analyze employees' work patterns and propose optimal work schedules. For example, it can analyze employees' work patterns and propose efficient work schedules. For example, it can assign important tasks to times when employees are most focused. The payroll department can also propose the introduction of a flextime system based on the results of the work pattern analysis. For example, it can set flexible working hours to suit employees' lifestyles. The payroll department can also analyze work patterns to detect early signs of overwork or stress. For example, it can recommend taking vacation if long working hours continue. This allows the department to analyze employees' work patterns and propose optimal work schedules.

[0102] The payroll calculation department can use the emotion estimation function to introduce an incentive system based on the emotional state of employees. For example, based on the emotion estimation data, incentives can be provided to employees with a high level of positive emotions. For example, a special bonus can be provided to highly motivated employees. The payroll calculation department can also provide a relaxation program to highly stressed employees based on the emotion estimation data. For example, special leave can be granted to reduce stress. The payroll calculation department can also design an incentive system based on the emotional state of employees based on the emotion estimation data. For example, opportunities for career advancement can be provided to employees with high emotion scores. This makes it possible to introduce an incentive system based on the emotional state of employees.

[0103] The processing flow of the second embodiment will be briefly explained below.

[0104] Step 1: The work status collection unit automatically collects employee work status and PC operation information. For example, it records the time employees arrive and leave work, break times, and PC usage. The work status collection unit also monitors employees' PC operation, collecting the applications used, keystrokes, and mouse movements. The work status collection unit also collects employees' biometric information (heart rate, body temperature, etc.) and uses this information for detailed analysis of their work status. For example, it monitors heart rate in real time to evaluate stress levels and concentration levels. Step 2: The payroll calculation department automatically calculates employee salaries based on the collected data on working conditions and PC operation. For example, it calculates the exact salary amount by taking into account basic salary, overtime pay, transportation expenses, etc. The payroll calculation department also calculates salaries taking into account the employee's skill level and performance evaluation. For example, it sets basic salary according to the level of professional qualifications and technical skills. Step 3: The Social Insurance Procedures Department automates social insurance and tax procedures based on the results of payroll calculations. For example, it automatically calculates social insurance premiums such as health insurance, employee pension insurance, and employment insurance, as well as taxes such as income tax and resident tax, and carries out the necessary procedures. The Social Insurance Procedures Department also optimizes social insurance according to employees' family structures and life stages. For example, it adjusts insurance premiums according to the number of dependents. Step 4: The Financial Planning Department simulates financial planning based on employee salary information. For example, they propose future savings plans, investment strategies, loan repayment plans, etc. The Financial Planning Department also proposes financial plans that take into account employee life events (marriage, childbirth, home purchase, etc.). Step 5: The Financial Strategy Proposal Department proposes effective financial strategies to employees based on the results of the financial planning simulation. For example, they provide specific advice on how to increase savings, when to invest, and how to repay loans. The Financial Strategy Proposal Department also proposes financial strategies based on employees' short-, medium-, and long-term goals. For example, they recommend short-term savings goals and securing emergency funds.

[0105] 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.

[0106] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0107] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0108] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0109] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0110] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0111] 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.

[0112] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0113] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0118] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0119] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0120] 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.

[0121] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0122] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0123] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0124] 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.

[0125] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0126] 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.

[0127] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0128] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0133] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0134] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0135] 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.

[0136] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0137] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0138] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0139] 7, the 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.

[0140] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0141] 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.

[0142] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0143] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0144] 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.

[0145] The control object 443 includes a display device, LEDs in the eyes, and motors that drive 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.

[0146] 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.

[0147] 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.

[0148] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0149] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0150] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0151] 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.

[0152] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0153] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0154] 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.

[0155] FIG. 9 illustrates 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 behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions 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.

[0156] 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.

[0157] 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).

[0158] 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 expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, 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 expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0159] 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."

[0160] 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.

[0161] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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. A processor also includes 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.

[0166] The hardware resource that executes the specific process 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 process may be a single processor.

[0167] 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.

[0168] 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.

[0169] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0170] 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.

[0171] 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. [Explanation of symbols]

[0172] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A work status collection unit that automatically collects employee work status and PC operations, a payroll calculation unit that automatically calculates employee pay based on the data collected by the work status collection unit; a social insurance procedure unit that automates social insurance and tax procedures based on the payroll data calculated by the payroll calculation unit; a financial planning department that simulates financial planning for employees based on the salary data; a financial strategy proposal unit that proposes an effective financial strategy based on the results of the simulation performed by the financial planning unit. A system characterized by:

2. The work status collection unit Collecting employee heart rate and body temperature data for detailed analysis of the work status 2. The system of claim 1.

3. The work status collection unit Analyze employee work in real time to evaluate work efficiency and concentration 2. The system of claim 1.

4. The work status collection unit Understand the employee's emotional state and assess their stress levels and motivation 2. The system of claim 1.

5. The work status collection unit Data from the employee's smartphone and wearable devices will also be collected to provide a comprehensive understanding of the employee's working conditions.

2. The system of claim 1.

6. The work status collection unit Implementing customized data collection methods for different business processes and departments 2. The system of claim 1.

7. The work status collection unit Propose optimization of the working environment according to the emotional state of the employee 2. The system of claim 1.

8. The payroll calculation unit Calculate payroll taking into account the employee's skill level and performance evaluation 2. The system of claim 1.

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