system

Abstract

Provide a system. 【Solution means】 Means for acquiring user information, Means for extracting and analyzing tasks based on the acquired user information, Means for optimizing the schedule based on the analysis results, Means for automating tasks and assisting in information creation and layout setting, Means for automatically arranging transportation means and accommodation, Means for analyzing electronic documents and generating a finalized reply, Means for reading the user's transaction records and analyzing the business history, Means for dynamically generating and optimizing a trading plan using a generated AI model, A system including the above.

Description

Technical Field

[0005] ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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] [[ID=,22]]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern enterprises, although ordinary employees are required to improve work efficiency, they spend a lot of time on routine tasks such as schedule management, meeting preparation, business trip arrangements, and email responses, and it is difficult to concentrate on their original work. In addition, the usually provided secretarial services are limited to management positions and officers, and have not reduced the burden on ordinary employees. As a result, there are problems such as inefficiency in work and no improvement in employee productivity.

Means for Solving the Problems

[0005] This invention provides a system that includes a program for acquiring user information and extracting and analyzing tasks based on that information. Furthermore, it optimizes schedules based on the analysis results and supports document creation and meeting scheduling through task automation. For business trips, it automatically arranges transportation and accommodation, and streamlines email correspondence through email analysis and response generation. The aim is to reduce the burden of daily tasks for general employees and support them in focusing on their core responsibilities.

[0006] "User information" refers to data displayed by the system regarding individual users, such as their attributes, history, and work details.

[0007] A "task" refers to an individual task or activity that a user is required to perform as part of their work.

[0008] "Analysis" refers to the process of examining and evaluating information based on acquired data, in accordance with the purpose.

[0009] A "schedule" is a time-based plan outlining the tasks and work that a user needs to complete.

[0010] "Optimization" refers to the process by which a system considers various input conditions to find the most efficient means or arrangement.

[0011] "Document creation" refers to the activity of a system organizing and generating documents and information necessary for meetings and business operations.

[0012] "Meeting scheduling" refers to the act of determining the necessary conditions for holding a meeting, such as the date, time, location, and participants.

[0013] "Transportation" refers to the means of getting around used for business trips, etc., and includes airplanes, trains, buses, etc.

[0014] "Accommodation facilities" refer to facilities used for lodging during travel or business trips, such as hotels and inns.

[0015] "Email" refers to message data transmitted and received using electronic communication.

[0016] "Analysis" refers to the operation of decomposing data and information to find its meaning and relevance.

[0017] "Reply proposal" refers to a proposal of the content of an appropriate reply to the received email.

Brief Description of Drawings

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

Mode for Carrying Out the Invention

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

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

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

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

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

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

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

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

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

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

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0035] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

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

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

[0039] This invention is a system designed to streamline users' work, and aims for the server, terminal, and user to work together in coordination. The roles of each component are described below.

[0040] User authentication and information retrieval:

[0041] When a user accesses the system through their device, the server authenticates the user and retrieves their profile data from the database. This data includes past work history and schedule information, serving as the foundation for providing personalized support based on the user's attributes.

[0042] Task automation:

[0043] The server analyzes the acquired user data and automatically extracts and lists the daily tasks required by the user. For example, for a sales representative, it automatically picks out a list of contracts scheduled to be concluded this week and important customer visit dates. It also dynamically adjusts the priority of these tasks using a generative AI model.

[0044] Schedule management and optimization:

[0045] The server analyzes the user's work schedule and optimizes the placement of each task. It adjusts the schedule to enable efficient work execution for the user and notifies the terminal accordingly. For example, it might adjust lunch breaks to coincide with sales travel time to ensure efficient work even on tight schedules.

[0046] Meeting preparation:

[0047] The server automatically collects and organizes the necessary materials for meetings the user is scheduled to attend from the user's past work data, and edits them according to a document template. These materials are then presented to the user on their terminal for review and adjustment.

[0048] Business trip arrangements:

[0049] When a user enters their business trip schedule, the server collects information on the most suitable transportation and accommodation options based on that schedule and completes the arrangements. Booking confirmations are automatically sent to the user's device, allowing them to prepare for their trip smoothly. Specifically, the server also provides weather and access information for the destination, supporting decision-making during the trip.

[0050] Email correspondence:

[0051] The server analyzes received emails, summarizes their content, and generates a draft reply. This reply is relevant to the business context and is sent after user confirmation. This allows users to efficiently process important emails from a large volume of messages.

[0052] In this way, this system provides a series of processes in which the server effectively utilizes the user's business data and reduces the user's workload via the terminal. Ultimately, it supports improved user productivity and enables innovation in business operations.

[0053] The following describes the processing flow.

[0054] Step 1:

[0055] When a user attempts to log in from a terminal, the server verifies the authentication information, and if successful, retrieves the user's profile data from the database. This prepares the server to understand the user's role in the workplace and their habits.

[0056] Step 2:

[0057] The server utilizes an AI model generated based on the acquired profile data to extract and list tasks that the user is scheduled to perform. These tasks include scheduled meetings and projects that require progress.

[0058] Step 3:

[0059] Based on analytical data, the server optimizes the user's daily schedule and efficiently allocates tasks. For example, it makes adjustments such as inserting preparation time between important meetings to prevent them from being scheduled consecutively.

[0060] Step 4:

[0061] The server schedules meetings based on the user's work schedule and automatically creates necessary documents from the user's data and system information. This reduces the time users spend creating documents. The created documents are notified to the terminal, allowing the user to review them.

[0062] Step 5:

[0063] When the server receives a travel request from a user, it matches the user's schedule with destination information and arranges the most suitable transportation and accommodation. Once the booking is complete, the travel plan is notified on the user's device, allowing them to confidently incorporate it into their schedule.

[0064] Step 6:

[0065] The server analyzes received emails, determines their importance, and prioritizes them. Furthermore, it understands the content of the emails and automatically generates draft replies. These draft replies are presented to the user via their device, allowing them to make minor adjustments before sending.

[0066] This series of steps will free users from tedious daily tasks, allowing them to focus on their core responsibilities.

[0067] (Example 1)

[0068] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0069] In today's workplace, improving work efficiency and productivity are crucial challenges. However, manual task management, scheduling, meeting preparation, and travel arrangements consume a great deal of time and effort, placing a significant burden on users. Furthermore, users are required to efficiently process the vast amount of information received via email. In this situation, users find it difficult to concentrate on their own work, and there is a need for support to perform tasks efficiently and smoothly.

[0070] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0071] In this invention, the server includes means for acquiring user information, means for extracting and analyzing work activities based on the acquired user information, and means for optimizing the timetable based on the analysis results. This enables users to efficiently manage their work and make effective use of their time. Furthermore, by automating work planning and scheduling, it is possible to reduce the burden on users and improve work productivity.

[0072] "User information" refers to identification data and profile information related to users registered in the system.

[0073] "Business activities" refer to the collection of all tasks and administrative processes related to the job that users perform on a daily basis.

[0074] "Analysis" is the act of finding patterns and trends based on acquired data and deepening one's understanding of it.

[0075] A "timetable" is a plan of time allocation to efficiently schedule the work activities of users.

[0076] "Automation" refers to making tasks that were previously performed manually possible through the control of machines or computers.

[0077] "Information organization" is the act of collecting necessary materials and data according to a purpose and arranging them in a format that is easy to use.

[0078] "Arranging" refers to the act of making the necessary preparations and procedures and moving things forward towards a goal.

[0079] "Electronic communication" refers to a means of exchanging messages that send and receive information in digital format, such as email.

[0080] A "draft reply" is the content of a proposed response to be sent in response to an received electronic communication.

[0081] "Generative AI technology" is a technology that uses artificial intelligence to generate new information and data.

[0082] A "work plan" is a strategic plan that systematically organizes and executes job activities aimed at achieving specific goals.

[0083] "Travel information" refers to all necessary data related to travel and accommodation, including departure point, destination, mode of transport, etc.

[0084] This invention is a system designed to streamline user operations and improve productivity, and it operates in a manner in which a server, terminal, and user interact with each other. A specific example of this system is shown below.

[0085] The server authenticates user information when a user accesses the system through a terminal. This process can utilize, for example, cloud-based authentication services or authentication algorithms. Once the user is successfully authenticated, the server retrieves user information from the database. This information includes work history, schedules, and profile data.

[0086] Next, the server analyzes business activities based on user information. Using Python's Pandas library and natural language processing tools, it analyzes the data and lists daily tasks. A generative AI model is used in this data analysis process to dynamically determine the priority of each task.

[0087] For example, a sales representative might list their customer visit dates and contract signing dates for the week and prioritize them. This allows the user to intuitively understand which tasks should be prioritized.

[0088] Schedule optimization involves the server rearranging the user's work schedule and making adjustments to ensure efficient work execution. Optimization tools are used to generate a personalized schedule. The terminal receives this optimized schedule and notifies the user.

[0089] Furthermore, the server automatically collects the necessary materials for meeting preparation and presents them to the terminal in an organized format according to a template. Natural language processing technology is used to analyze the materials, making them easily adjustable for the user.

[0090] In the business trip arrangement process, when a user enters their travel information, the server searches for and arranges the most suitable transportation and accommodation based on that information. Various APIs are used to provide users with the latest information, supporting efficient business trip preparation. This allows for quick decision-making during the business trip.

[0091] Finally, the server analyzes the email and generates a draft reply using a generative AI model. This draft reply is relevant to the business context and can be modified by the user as needed before being sent via their device.

[0092] For example, if a sales representative wants to check their priority tasks for the week, they would enter the following:

[0093] "What are this week's top priorities?"

[0094] Examples of prompt statements include the following:

[0095] "Please list your top priority tasks for this week as a sales representative. Include the estimated time and priority for each task."

[0096] In this way, the system utilizes servers, terminals, and generative AI technology to enable users to efficiently manage their work.

[0097] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0098] Step 1:

[0099] When a user accesses the system through a terminal, the terminal sends the user's authentication information to the server. The server initiates the authentication process using the user ID and password. This involves secure communication and the execution of an authentication service. If authentication is successful, the server accesses the database and retrieves user information. The input is the user's login information, and the output is the user profile and work history.

[0100] Step 2:

[0101] The server analyzes the user's work activities based on the acquired user information. This generates a task list for the user. The input is the user's past work history, and the output is a list of tasks the user must complete. Specifically, it uses Python's Pandas library for data analysis and a generated AI model to determine task priorities. The user can view the generated task list on their terminal.

[0102] Step 3:

[0103] The server optimizes the user's schedule based on the task list. The input is the task list, and the output is the optimized schedule. The server uses optimization tools and a generative AI model to create an efficient work plan. This schedule is notified to the terminal, allowing the user to view and adjust the schedule on their terminal.

[0104] Step 4:

[0105] The server collects and organizes the necessary data to prepare meeting materials for meetings that users are scheduled to attend. The input is historical business data, and the output is meeting materials based on a template. Natural language processing tools are used to analyze the data, and the materials are presented to the user's terminal for review and modification.

[0106] Step 5:

[0107] When a user enters their business trip information into a terminal, the server receives it and arranges the most suitable transportation and accommodation. The server uses an API to collect travel information and find the best options. The input is the user's business trip schedule, and the output is a booking confirmation notification. This allows users to efficiently prepare for their business trips.

[0108] Step 6:

[0109] The server analyzes received emails and generates suggested replies. The input is the received email, and the output is the generated suggested reply. It utilizes a generative AI model and natural language processing technology to summarize the email content and suggest appropriate replies. Users can review these on their devices, modify them as needed, and send them.

[0110] (Application Example 1)

[0111] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0112] In today's business environment, users need to efficiently handle a wide variety of tasks while making critical decisions within limited timeframes. However, the sheer volume of information, the time and effort required to manage transaction records and work schedules, and the difficulty in prioritizing and optimizing plans all hinder user productivity. This is particularly true in electronic payment operations, where rapid and accurate transaction planning and customer communication are essential, necessitating systems that address these challenges.

[0113] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0114] In this invention, the server includes means for acquiring user information, means for extracting and analyzing tasks based on the acquired user information, means for optimizing the schedule based on the analysis results, means for automating tasks and supporting information creation and placement settings, means for automatically arranging transportation and accommodation, means for analyzing electronic documents and generating response plans, means for reading user transaction records and analyzing business history, and means for dynamically generating and optimizing transaction plans using a generation AI model. This makes it possible to efficiently manage diverse business tasks and improve user productivity.

[0115] "Means for acquiring user information" refers to a function that collects user-related information, such as user profiles and past work data, and makes it available within the system.

[0116] "Means for extracting and analyzing tasks" refers to a function that identifies necessary business tasks from acquired user information and evaluates and analyzes them.

[0117] "Methods for optimizing schedules" refer to functions that efficiently allocate and manage users' work tasks, optimizing the use of time and resources.

[0118] "Means of automating tasks and supporting information creation and placement settings" refers to functions that automate parts of business tasks and support the preparation of meeting materials, visit arrangements, and other similar tasks.

[0119] "Methods for automatically arranging transportation and accommodation" refers to functions that automatically make reservations for available transportation and accommodation based on business trips and travel plans.

[0120] "Means for analyzing electronic documents and generating response drafts" refers to a function that analyzes received emails and other documents and automatically suggests response content.

[0121] "A means of reading user transaction records and analyzing business history" refers to a function that acquires a user's past transaction data and analyzes patterns and trends related to their business based on that data.

[0122] "A means of dynamically generating and optimizing trading plans using a generative AI model" refers to a function that utilizes artificial intelligence technology to formulate and improve the optimal trading plan for the current situation in real time.

[0123] The system that implements this application example is centered around a server program built on the Python Flask framework, using PostgreSQL as its database. On smartphones, the user interface is built using React Native.

[0124] The server first retrieves user information when a user accesses it through their terminal. This includes user profile data and past work history. Based on the retrieved information, it uses a generative AI model to extract and analyze work tasks relevant to the user. Once the necessary tasks are identified, the server optimizes the schedule based on them.

[0125] By analyzing users' transaction records and using a generative AI model, we dynamically generate and optimize transaction plans. This process makes it possible to propose the best transaction strategy tailored to the current business situation.

[0126] Furthermore, the server organizes the user's work tasks, analyzes electronic documents, and generates necessary materials and draft replies. This allows users to carry out their work efficiently and effectively. It also automatically arranges transportation and accommodation, supporting users in preparing for business trips.

[0127] For example, when a user plans their next campaign, the system predicts the necessary product inventory based on past data and automatically generates a related transaction plan. This allows them to schedule negotiations with suppliers at the appropriate time and maximize profits.

[0128] An example of a prompt for the generating AI model is: "Analyze the transaction data from the past three months and generate the optimal transaction schedule and inventory forecast for the next quarter."

[0129] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0130] Step 1:

[0131] The server authenticates users accessing through the terminal. The input includes a username and password, which the server compares against the registered information in the database to verify the user's legitimacy. During this process, user profile data is retrieved from the database and prepared for use in the next processing step. The output indicates whether authentication was successful or unsuccessful.

[0132] Step 2:

[0133] The server extracts relevant business tasks based on the acquired user profile data. The input is the user's profile data, and the output is a list of tasks relevant to the user's future work. Using a generative AI model, high-priority tasks are identified by dynamically determining task priorities based on the user's past work history.

[0134] Step 3:

[0135] The server optimizes the schedule based on the task list. The input is a prioritized task list, and the output is an optimized schedule. The generative AI model maximizes the efficiency of time and resource utilization and implements optimal scheduling. For example, it efficiently schedules sales visits and minimizes travel time.

[0136] Step 4:

[0137] The server analyzes emails and other necessary documents and automatically generates draft replies and supporting materials. The input is the received electronic documents, and the output is AI-generated draft replies and supporting material templates. Using a generation AI model, the content of the documents is analyzed to create contextually appropriate replies. During this process, emails are also organized according to their priority.

[0138] Step 5:

[0139] This system analyzes the user's transaction history and dynamically generates and optimizes transaction plans. The input is the user's past transaction data, and the output is an optimized transaction plan. The generating AI model analyzes past transaction patterns and presents the optimal transaction strategy in real time. Based on this, the user can then schedule their next business opportunity.

[0140] Step 6:

[0141] The server automatically arranges transportation and accommodation based on the business trip schedule. The input is business trip information provided by the user, and the output is booking confirmation information. The system uses external APIs to collect transportation and accommodation options and suggests the best choices to the user. After reviewing the suggestions, the user can easily prepare for their business trip.

[0142] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0143] This invention is a system that utilizes user emotion recognition to improve work efficiency and provide an appropriate work environment. This system consists of a server, a terminal, and an emotion engine, which are designed to work together to reduce the user's workload.

[0144] User recognition and data acquisition:

[0145] When a user accesses the system through their device, the server first authenticates the user and collects their profile data. This data includes the user's job information, past work history, schedule, etc., and forms the basis for providing personalized support.

[0146] Emotion recognition:

[0147] The server uses an emotion engine installed in the terminal to monitor the user's emotional state in real time. The emotion engine analyzes the user's input data, vital signs from the wearable device, voice, and facial expressions to identify the user's current emotion.

[0148] Task management and optimization:

[0149] The server adjusts task priorities using a generative AI model, taking into account the user's emotional state. For example, if the server determines that the user is stressed, it will either postpone low-priority tasks or prioritize assigning easier tasks.

[0150] Schedule adjustment:

[0151] Based on emotional data, the server optimizes the work schedule. For example, if a user is feeling fatigued, a short break is added to the schedule. Furthermore, to enhance concentration when working on specific tasks, it recommends music and suggests environmental settings that match the user's emotions.

[0152] Meeting preparation:

[0153] The server uses feedback from the emotion engine to prepare for the meeting. If the user is feeling anxious, it suggests relaxation techniques and provides materials to help them prepare for the meeting.

[0154] Business trip arrangements:

[0155] When a user plans a business trip, the server uses emotion recognition results to suggest comfortable modes of transportation and accommodations. Even when long-distance travel is involved, arrangements are made with the user's comfort as a top priority.

[0156] Email correspondence:

[0157] When users process emails, the server advises them to avoid difficult replies depending on their emotions, or, if it determines they are in a calm state, encourages them to prioritize replying to higher-priority emails.

[0158] In this way, this system, which incorporates an emotion engine, aims to improve the quality of work by taking into account the user's emotional state. As a result, improvements in employee satisfaction and productivity are expected.

[0159] The following describes the processing flow.

[0160] Step 1:

[0161] When a user logs into a terminal, the server verifies the user's authentication information and retrieves profile data from the database based on the results. This profile contains various data related to the user's work.

[0162] Step 2:

[0163] The server activates the emotion engine from the terminal and collects user emotion data in real time. The emotion engine identifies the user's emotional state by analyzing facial recognition, voice tone, and user input speed.

[0164] Step 3:

[0165] Based on the acquired emotional data, the server re-evaluates the prioritization of the user's daily tasks. Specifically, if data indicating stress is detected, the server prioritizes simpler tasks or adjusts the work plan to reduce stress.

[0166] Step 4:

[0167] The system notifies the user of an optimized schedule via the device. For example, if emotional data indicates fatigue, the server suggests a set amount of rest time and presents that schedule to the user.

[0168] Step 5:

[0169] The server uses emotional data to support meeting preparation. If a user is feeling nervous, it automatically generates materials and relaxation techniques to alleviate the tension and delivers them to the user via their device.

[0170] Step 6:

[0171] When preparing for a business trip, the user enters their travel information into their device. Based on emotional data, the server automatically arranges transportation and accommodations that prioritize comfort, and notifies the user of the details.

[0172] Step 7:

[0173] In analyzing incoming emails, the server utilizes an emotion engine to understand the user's emotional state and adjust the priority of suggested replies accordingly. For example, if the user is relaxed, the email might include a message urging them to respond quickly to important emails.

[0174] Through this series of processes, a system that incorporates emotion recognition capabilities takes into account the user's emotional state and provides support aimed at improving work efficiency and reducing mental burden.

[0175] (Example 2)

[0176] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0177] In today's work environment, there is a growing need for work support systems that take employees' emotional states into consideration. Traditional systems do not take emotions into account, resulting in insufficient task management and reduced mental burden. Solving this problem is essential.

[0178] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0179] In this invention, the server includes means for acquiring user identification information, means for adjusting task priorities according to the user's emotional state using a generative AI model, and means for supporting document creation and meeting preparation according to the user's emotional state. This enables efficient task management and stress reduction that takes into account the user's emotional state.

[0180] "User identification information" refers to attribute information necessary to identify a user. This information includes user ID, authentication information, job data, etc.

[0181] A "generative AI model" refers to an artificial intelligence program that uses machine learning techniques to analyze data patterns and make predictions and suggestions. This model plays a role in adjusting task priorities based on the user's work status.

[0182] "Emotional state" refers to data that indicates the user's mental or emotional condition. This data is obtained by analyzing voice, facial expressions, vital signs, etc.

[0183] "Adjusting task priorities" refers to the process of rearranging the order and importance of a user's work tasks based on their emotional state. This adjustment is done to improve the user's efficiency.

[0184] "Supporting document creation and meeting preparation" refers to providing support to help users prepare necessary documents and arrange meetings to ensure their work proceeds smoothly.

[0185] This system is an advanced business support system designed to improve work efficiency based on the user's emotional state. It primarily operates by combining a server, terminals, and an emotion engine.

[0186] First, when a user accesses the system via a terminal, the server obtains the user's identification information. The terminal has a built-in emotion engine that analyzes the user's emotional state using speech recognition software and image processing technology. Information obtained from voice data and facial expressions is important for determining the user's real-time mental state.

[0187] Next, the server uses a generative AI model to adjust task priorities based on the user's emotional state. The generative AI model suggests the most appropriate task assignments based on the user's past work data and current emotional state. This model enables more accurate task prioritization by explicitly indicating what decisions are needed from the AI ​​through prompt statements. For example, the instruction "Suggest the best task assignment for a user who is stressed" plays a crucial role here.

[0188] Within this system, the server also optimizes the schedule based on the user's emotional state. To this end, the server may add short breaks to the schedule or recommend music to enhance concentration while working.

[0189] Furthermore, if a user has a meeting or business trip scheduled, the server automatically suggests and prepares necessary materials, optimal transportation, and accommodation based on sentiment analysis. This reduces the burden on users in preparing for work and arranging business trips.

[0190] Ultimately, in email processing, the server considers the user's emotional state to generate the most appropriate reply and suggests email responses based on their importance. This entire process can reduce employee stress and improve work efficiency.

[0191] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0192] Step 1:

[0193] When a user logs into the system via a terminal, the server receives the user's identification information as input data. This authenticates the user. If authentication is successful, the server retrieves the user's job information, work history, and schedule data from the database as output.

[0194] Step 2:

[0195] An emotion engine built into the device monitors the user's emotional state in real time. Input data includes the user's voice, facial expressions, and biometric information from wearable devices. Based on this data, the device applies an emotion analysis algorithm to identify the user's current emotion. This identified emotional state is then sent to the server as output.

[0196] Step 3:

[0197] The server inputs the user's identification information and emotional state received from the emotion engine into a generative AI model. The generative AI model learns from past data and uses the prompt "Suggestion for optimal task placement for a user in a stressed state" to output the optimal task priority for the user. Based on this output, the server optimizes the task schedule.

[0198] Step 4:

[0199] The server adjusts the work schedule based on the user's emotional state. Input data includes information about the user's fatigue level and concentration level. The server provides output such as suggesting short breaks or recommending relaxing music. The terminal receives this information and notifies the user.

[0200] Step 5:

[0201] When users plan meetings or business trips, the server uses the entered schedule information and sentiment data to suggest suitable modes of transportation and accommodations. This suggestion also assists with booking procedures, ensuring users enjoy a convenient and hassle-free experience.

[0202] Step 6:

[0203] In processing emails, the server receives emails opened by users as input data. After analyzing the email content along with the emotional state, it outputs suggested replies. High-priority emails prompt for a quick response, while emails requiring a more complex reply receive warnings tailored to the emotional state of the user.

[0204] (Application Example 2)

[0205] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0206] In modern homes and workplaces, individual users face diverse emotional states and workloads, requiring efficient support tailored to their individual needs. Ideally, within the home, the living environment and conversation content should be adjusted to the user's emotions, but a suitable system for this is lacking. In this context, technology that recognizes emotions and supports work and daily life is essential.

[0207] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0208] In this invention, the server includes means for acquiring user information, means for extracting and analyzing tasks based on the acquired user information, and means for optimizing the schedule based on the analysis results. This makes it possible to optimize the user's work and home activities according to their emotional state.

[0209] "User information" is a general term for the data that a system collects to identify a user and understand their work history and emotional state.

[0210] "Emotional state" refers to the user's psychological state at that moment, analyzed based on their facial expressions, tone of voice, and other vital signs.

[0211] A "task" refers to an individual task or activity that a user must perform in their daily life or work.

[0212] "Optimizing the schedule" refers to efficiently rearranging the day's activities based on the user's emotional state and work priorities.

[0213] "Automation" refers to a process in which existing procedures are performed automatically rather than manually, through the intervention of a system.

[0214] "Adjusting the home environment" refers to robots and devices appropriately controlling lighting, music, conversations, and other elements within the home according to the user's emotional state.

[0215] "Recognizing emotions" refers to the technical process by which a system analyzes psychological characteristics derived from user input information to identify the user's current emotions.

[0216] This invention is a system that recognizes a user's emotional state in real time and provides support tailored to their individual circumstances. This system primarily consists of a server, a terminal, and an emotion recognition engine.

[0217] The server first acquires user information, and then extracts and analyzes tasks based on that information. This is achieved using hardware (such as sensors like cameras and microphones) that collects the user's work history and emotional state data. The emotion recognition engine processes the data acquired by these sensors and identifies the emotional state from facial expressions and tone of voice.

[0218] Furthermore, the device automatically prioritizes tasks and optimizes the schedule based on emotion recognition. By utilizing a generative AI model, it can suggest simple tasks if the user is feeling stressed. In addition, a smart home appliance control system is used to adjust the environment within the home. For example, if it determines that relaxation is needed, the music playback device will play calming music and the lighting will be adjusted to a softer tone.

[0219] For example, if a user returns home from work and the system recognizes their fatigue level, it can automatically create a relaxing environment. If the weather is good, it could adjust the humidity to a suitable level and activate a device that emits a relaxing scent. Another example of a prompt message would be, "Generate instructions to create a relaxing lighting and music environment for the user."

[0220] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0221] Step 1:

[0222] The server retrieves the user's profile data and work history. This data includes past task history, schedules, and vital sign information from wearable devices. Based on the entered data, a database is updated to predict the user's current emotional state.

[0223] Step 2:

[0224] The device uses an emotion recognition engine to analyze the user's emotional state in real time. Voice tone and facial expression data are sent to the device as input, which is then analyzed to identify the user's emotions. The analysis result outputs the emotional state (e.g., stress, relaxation).

[0225] Step 3:

[0226] The server re-evaluates task priorities using a generative AI model based on emotional state data. The server receives emotional state data as input, analyzes the current task list based on this data, and resets priorities. The optimized list is then displayed to the user as output.

[0227] Step 4:

[0228] To adjust the home environment that users use on a daily basis, the device operates devices via a smart home appliance control system. For example, if the entered emotional state is "fatigue," it will activate a music playback device and play relaxing music. It will also output specific instructions to adjust the lighting.

[0229] Step 5:

[0230] The server adapts pre-configured prompts and suggests optimal activities for the user through a generating AI model. For example, it might generate prompts and output instructions to adjust lighting and music settings to help the user relax. The outputted instructions are then displayed to the user and executed.

[0231] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0232] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0233] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0234] [Second Embodiment]

[0235] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0236] As shown in Figure 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.

[0237] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0238] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0239] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0240] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0241] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0242] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0243] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0244] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0245] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0246] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0247] This invention is a system designed to streamline users' work, and aims for the server, terminal, and user to work together in coordination. The roles of each component are described below.

[0248] User authentication and information retrieval:

[0249] When a user accesses the system through their device, the server authenticates the user and retrieves their profile data from the database. This data includes past work history and schedule information, serving as the foundation for providing personalized support based on the user's attributes.

[0250] Task automation:

[0251] The server analyzes the acquired user data and automatically extracts and lists the daily tasks required by the user. For example, for a sales representative, it automatically picks out a list of contracts scheduled to be concluded this week and important customer visit dates. It also dynamically adjusts the priority of these tasks using a generative AI model.

[0252] Schedule management and optimization:

[0253] The server analyzes the user's work schedule and optimizes the placement of each task. It adjusts the schedule to enable efficient work execution for the user and notifies the terminal accordingly. For example, it might adjust lunch breaks to coincide with sales travel time to ensure efficient work even on tight schedules.

[0254] Meeting preparation:

[0255] The server automatically collects and organizes the necessary materials for meetings the user is scheduled to attend from the user's past work data, and edits them according to a document template. These materials are then presented to the user on their terminal for review and adjustment.

[0256] Business trip arrangements:

[0257] When a user enters their business trip schedule, the server collects information on the most suitable transportation and accommodation options based on that schedule and completes the arrangements. Booking confirmations are automatically sent to the user's device, allowing them to prepare for their trip smoothly. Specifically, the server also provides weather and access information for the destination, supporting decision-making during the trip.

[0258] Email correspondence:

[0259] The server analyzes received emails, summarizes their content, and generates a draft reply. This reply is relevant to the business context and is sent after user confirmation. This allows users to efficiently process important emails from a large volume of messages.

[0260] In this way, this system provides a series of processes in which the server effectively utilizes the user's business data and reduces the user's workload via the terminal. Ultimately, it supports improved user productivity and enables innovation in business operations.

[0261] The following describes the processing flow.

[0262] Step 1:

[0263] When a user attempts to log in from a terminal, the server verifies the authentication information, and if successful, retrieves the user's profile data from the database. This prepares the server to understand the user's role in the workplace and their habits.

[0264] Step 2:

[0265] The server utilizes an AI model generated based on the acquired profile data to extract and list tasks that the user is scheduled to perform. These tasks include scheduled meetings and projects that require progress.

[0266] Step 3:

[0267] Based on analytical data, the server optimizes the user's daily schedule and efficiently allocates tasks. For example, it makes adjustments such as inserting preparation time between important meetings to prevent them from being scheduled consecutively.

[0268] Step 4:

[0269] The server schedules meetings based on the user's work schedule and automatically creates necessary documents from the user's data and system information. This reduces the time users spend creating documents. The created documents are notified to the terminal, allowing the user to review them.

[0270] Step 5:

[0271] When the server receives a travel request from a user, it matches the user's schedule with destination information and arranges the most suitable transportation and accommodation. Once the booking is complete, the travel plan is notified on the user's device, allowing them to confidently incorporate it into their schedule.

[0272] Step 6:

[0273] The server analyzes received emails, determines their importance, and prioritizes them. Furthermore, it understands the content of the emails and automatically generates draft replies. These draft replies are presented to the user via their device, allowing them to make minor adjustments before sending.

[0274] This series of steps will free users from tedious daily tasks, allowing them to focus on their core responsibilities.

[0275] (Example 1)

[0276] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0277] In today's workplace, improving work efficiency and productivity are crucial challenges. However, manual task management, scheduling, meeting preparation, and travel arrangements consume a great deal of time and effort, placing a significant burden on users. Furthermore, users are required to efficiently process the vast amount of information received via email. In this situation, users find it difficult to concentrate on their own work, and there is a need for support to perform tasks efficiently and smoothly.

[0278] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in the first embodiment is realized by the following means.

[0279] In this invention, the server includes means for acquiring user information, means for extracting and analyzing business activities based on the acquired user information, and means for optimizing a schedule based on the analysis result. As a result, the user can efficiently manage his / her own business and effectively utilize time. Also, by automating business plans and schedules, it is possible to reduce the burden on the user and improve the productivity of the business.

[0280] "User information" refers to identification data and profile information related to users registered in the system.

[0281] "Business activities" refers to the collection of all operations and transaction processes related to the duties that users perform daily.

[0282] "Analysis" refers to the act of finding patterns and trends based on the acquired data and deepening understanding.

[0283] "Schedule" refers to a time allocation plan for efficiently arranging the business activities of users.

[0284] "Automation" refers to making operations that were previously performed manually executable under the control of machines or computers.

[0285] "Information arrangement" refers to the act of collecting necessary materials and data according to the purpose and arranging them in a user-friendly form.

[0286] "Arrangement" refers to the act of preparing necessary preparations and procedures and promoting things toward a goal.

[0287] "Electronic communication" refers to a message exchange means for transmitting and receiving information in a digital format such as e-mail.

[0288] A "draft reply" is the content of a proposed response to be sent in response to an received electronic communication.

[0289] "Generative AI technology" is a technology that uses artificial intelligence to generate new information and data.

[0290] A "work plan" is a strategic plan that systematically organizes and executes job activities aimed at achieving specific goals.

[0291] "Travel information" refers to all necessary data related to travel and accommodation, including departure point, destination, mode of transport, etc.

[0292] This invention is a system designed to streamline user operations and improve productivity, and it operates in a manner in which a server, terminal, and user interact with each other. A specific example of this system is shown below.

[0293] The server authenticates user information when a user accesses the system through a terminal. This process can utilize, for example, cloud-based authentication services or authentication algorithms. Once the user is successfully authenticated, the server retrieves user information from the database. This information includes work history, schedules, and profile data.

[0294] Next, the server analyzes business activities based on user information. Using Python's Pandas library and natural language processing tools, it analyzes the data and lists daily tasks. A generative AI model is used in this data analysis process to dynamically determine the priority of each task.

[0295] For example, a sales representative might list their customer visit dates and contract signing dates for the week and prioritize them. This allows the user to intuitively understand which tasks should be prioritized.

[0296] Schedule optimization involves the server rearranging the user's work schedule and making adjustments to ensure efficient work execution. Optimization tools are used to generate a personalized schedule. The terminal receives this optimized schedule and notifies the user.

[0297] Furthermore, the server automatically collects the necessary materials for meeting preparation and presents them to the terminal in an organized format according to a template. Natural language processing technology is used to analyze the materials, making them easily adjustable for the user.

[0298] In the business trip arrangement process, when a user enters their travel information, the server searches for and arranges the most suitable transportation and accommodation based on that information. Various APIs are used to provide users with the latest information, supporting efficient business trip preparation. This allows for quick decision-making during the business trip.

[0299] Finally, the server analyzes the email and generates a draft reply using a generative AI model. This draft reply is relevant to the business context and can be modified by the user as needed before being sent via their device.

[0300] For example, if a sales representative wants to check their priority tasks for the week, they would enter the following:

[0301] "What are this week's top priorities?"

[0302] Examples of prompt statements include the following:

[0303] "Please list your top priority tasks for this week as a sales representative. Include the estimated time and priority for each task."

[0304] In this way, the system utilizes servers, terminals, and generative AI technology to enable users to efficiently manage their work.

[0305] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0306] Step 1:

[0307] When the user accesses the system through the terminal, the terminal sends the user's authentication information to the server. The server starts the authentication process using the user ID and password. This involves communicating in a secure connection and executing the authentication service. If the authentication is successful, the server accesses the database and retrieves the user information. The input is the user's login information, and the output is the user profile and work history.

[0308] Step 2:

[0309] The server analyzes the business activities based on the retrieved user information. Thereby, a task list for the user is generated. The input is the user's past work history, and the output is the task list that the user should perform. Specifically, data analysis is performed using Python's Pandas, and the generated AI model is utilized to determine the task priorities. The user can check the generated task list on the terminal.

[0310] Step 3:

[0311] The server optimizes the user's schedule based on the task list. The input is the task list, and the optimized schedule is the output. The server uses optimization tools and combines the generated AI model to formulate an efficient business plan. The terminal is notified of this schedule, and the user can check and adjust the schedule on the terminal.

[0312] Step 4:

[0313] The server collects and organizes the necessary data to prepare the meeting materials that the user plans to participate in. The input is the past business data, and the output is the meeting materials based on the template. The data is analyzed using natural language processing tools, and the materials are presented to the terminal so that the user can check and modify them.

[0314] Step 5:

[0315] When a user enters their business trip information into a terminal, the server receives it and arranges the most suitable transportation and accommodation. The server uses an API to collect travel information and find the best options. The input is the user's business trip schedule, and the output is a booking confirmation notification. This allows users to efficiently prepare for their business trips.

[0316] Step 6:

[0317] The server analyzes received emails and generates suggested replies. The input is the received email, and the output is the generated suggested reply. It utilizes a generative AI model and natural language processing technology to summarize the email content and suggest appropriate replies. Users can review these on their devices, modify them as needed, and send them.

[0318] (Application Example 1)

[0319] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0320] In today's business environment, users need to efficiently handle a wide variety of tasks while making critical decisions within limited timeframes. However, the sheer volume of information, the time and effort required to manage transaction records and work schedules, and the difficulty in prioritizing and optimizing plans all hinder user productivity. This is particularly true in electronic payment operations, where rapid and accurate transaction planning and customer communication are essential, necessitating systems that address these challenges.

[0321] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0322] In this invention, the server includes means for acquiring user information, means for extracting and analyzing tasks based on the acquired user information, means for optimizing the schedule based on the analysis results, means for automating tasks and supporting information creation and placement settings, means for automatically arranging transportation and accommodation, means for analyzing electronic documents and generating response plans, means for reading user transaction records and analyzing business history, and means for dynamically generating and optimizing transaction plans using a generation AI model. This makes it possible to efficiently manage diverse business tasks and improve user productivity.

[0323] "Means for acquiring user information" refers to a function that collects user-related information, such as user profiles and past work data, and makes it available within the system.

[0324] "Means for extracting and analyzing tasks" refers to a function that identifies necessary business tasks from acquired user information and evaluates and analyzes them.

[0325] "Methods for optimizing schedules" refer to functions that efficiently allocate and manage users' work tasks, optimizing the use of time and resources.

[0326] "Means of automating tasks and supporting information creation and placement settings" refers to functions that automate parts of business tasks and support the preparation of meeting materials, visit arrangements, and other similar tasks.

[0327] "Methods for automatically arranging transportation and accommodation" refers to functions that automatically make reservations for available transportation and accommodation based on business trips and travel plans.

[0328] "Means for analyzing electronic documents and generating response drafts" refers to a function that analyzes received emails and other documents and automatically suggests response content.

[0329] "A means of reading user transaction records and analyzing business history" refers to a function that acquires a user's past transaction data and analyzes patterns and trends related to their business based on that data.

[0330] "A means of dynamically generating and optimizing trading plans using a generative AI model" refers to a function that utilizes artificial intelligence technology to formulate and improve the optimal trading plan for the current situation in real time.

[0331] The system that implements this application example is centered around a server program built on the Python Flask framework, using PostgreSQL as its database. On smartphones, the user interface is built using React Native.

[0332] The server first retrieves user information when a user accesses it through their terminal. This includes user profile data and past work history. Based on the retrieved information, it uses a generative AI model to extract and analyze work tasks relevant to the user. Once the necessary tasks are identified, the server optimizes the schedule based on them.

[0333] By analyzing users' transaction records and using a generative AI model, we dynamically generate and optimize transaction plans. This process makes it possible to propose the best transaction strategy tailored to the current business situation.

[0334] Furthermore, the server organizes the user's work tasks, analyzes electronic documents, and generates necessary materials and draft replies. This allows users to carry out their work efficiently and effectively. It also automatically arranges transportation and accommodation, supporting users in preparing for business trips.

[0335] For example, when a user plans their next campaign, the system predicts the necessary product inventory based on past data and automatically generates a related transaction plan. This allows them to schedule negotiations with suppliers at the appropriate time and maximize profits.

[0336] An example of a prompt for the generating AI model is: "Analyze the transaction data from the past three months and generate the optimal transaction schedule and inventory forecast for the next quarter."

[0337] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0338] Step 1:

[0339] The server authenticates users accessing through the terminal. The input includes a username and password, which the server compares against the registered information in the database to verify the user's legitimacy. During this process, user profile data is retrieved from the database and prepared for use in the next processing step. The output indicates whether authentication was successful or unsuccessful.

[0340] Step 2:

[0341] The server extracts relevant business tasks based on the acquired user profile data. The input is the user's profile data, and the output is a list of tasks relevant to the user's future work. Using a generative AI model, high-priority tasks are identified by dynamically determining task priorities based on the user's past work history.

[0342] Step 3:

[0343] The server optimizes the schedule based on the task list. The input is a prioritized task list, and the output is an optimized schedule. The generative AI model maximizes the efficiency of time and resource utilization and implements optimal scheduling. For example, it efficiently schedules sales visits and minimizes travel time.

[0344] Step 4:

[0345] The server analyzes emails and other necessary documents and automatically generates draft replies and supporting materials. The input is the received electronic documents, and the output is AI-generated draft replies and supporting material templates. Using a generation AI model, the content of the documents is analyzed to create contextually appropriate replies. During this process, emails are also organized according to their priority.

[0346] Step 5:

[0347] This system analyzes the user's transaction history and dynamically generates and optimizes transaction plans. The input is the user's past transaction data, and the output is an optimized transaction plan. The generating AI model analyzes past transaction patterns and presents the optimal transaction strategy in real time. Based on this, the user can then schedule their next business opportunity.

[0348] Step 6:

[0349] The server automatically arranges transportation and accommodation based on the business trip schedule. The input is business trip information provided by the user, and the output is booking confirmation information. The system uses external APIs to collect transportation and accommodation options and suggests the best choices to the user. After reviewing the suggestions, the user can easily prepare for their business trip.

[0350] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0351] This invention is a system that utilizes user emotion recognition to improve work efficiency and provide an appropriate work environment. This system consists of a server, a terminal, and an emotion engine, which are designed to work together to reduce the user's workload.

[0352] User recognition and data acquisition:

[0353] When a user accesses the system through their device, the server first authenticates the user and collects their profile data. This data includes the user's job information, past work history, schedule, etc., and forms the basis for providing personalized support.

[0354] Emotion recognition:

[0355] The server uses an emotion engine installed in the terminal to monitor the user's emotional state in real time. The emotion engine analyzes the user's input data, vital signs from the wearable device, voice, and facial expressions to identify the user's current emotion.

[0356] Task management and optimization:

[0357] The server adjusts task priorities using a generative AI model, taking into account the user's emotional state. For example, if the server determines that the user is stressed, it will either postpone low-priority tasks or prioritize assigning easier tasks.

[0358] Schedule adjustment:

[0359] Based on emotional data, the server optimizes the work schedule. For example, if a user is feeling fatigued, a short break is added to the schedule. Furthermore, to enhance concentration when working on specific tasks, it recommends music and suggests environmental settings that match the user's emotions.

[0360] Meeting preparation:

[0361] The server uses feedback from the emotion engine to prepare for the meeting. If the user is feeling anxious, it suggests relaxation techniques and provides materials to help them prepare for the meeting.

[0362] Business trip arrangements:

[0363] When a user plans a business trip, the server uses emotion recognition results to suggest comfortable modes of transportation and accommodations. Even when long-distance travel is involved, arrangements are made with the user's comfort as a top priority.

[0364] Email correspondence:

[0365] When users process emails, the server advises them to avoid difficult replies depending on their emotions, or, if it determines they are in a calm state, encourages them to prioritize replying to higher-priority emails.

[0366] In this way, this system, which incorporates an emotion engine, aims to improve the quality of work by taking into account the user's emotional state. As a result, improvements in employee satisfaction and productivity are expected.

[0367] The following describes the processing flow.

[0368] Step 1:

[0369] When a user logs into a terminal, the server verifies the user's authentication information and retrieves profile data from the database based on the results. This profile contains various data related to the user's work.

[0370] Step 2:

[0371] The server activates the emotion engine from the terminal and collects user emotion data in real time. The emotion engine identifies the user's emotional state by analyzing facial recognition, voice tone, and user input speed.

[0372] Step 3:

[0373] Based on the acquired emotional data, the server re-evaluates the prioritization of the user's daily tasks. Specifically, if data indicating stress is detected, the server prioritizes simpler tasks or adjusts the work plan to reduce stress.

[0374] Step 4:

[0375] The system notifies the user of an optimized schedule via the device. For example, if emotional data indicates fatigue, the server suggests a set amount of rest time and presents that schedule to the user.

[0376] Step 5:

[0377] The server uses emotional data to support meeting preparation. If a user is feeling nervous, it automatically generates materials and relaxation techniques to alleviate the tension and delivers them to the user via their device.

[0378] Step 6:

[0379] When preparing for a business trip, the user enters their travel information into their device. Based on emotional data, the server automatically arranges transportation and accommodations that prioritize comfort, and notifies the user of the details.

[0380] Step 7:

[0381] In analyzing incoming emails, the server utilizes an emotion engine to understand the user's emotional state and adjust the priority of suggested replies accordingly. For example, if the user is relaxed, the email might include a message urging them to respond quickly to important emails.

[0382] Through this series of processes, a system that incorporates emotion recognition capabilities takes into account the user's emotional state and provides support aimed at improving work efficiency and reducing mental burden.

[0383] (Example 2)

[0384] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0385] In today's work environment, there is a growing need for work support systems that take employees' emotional states into consideration. Traditional systems do not take emotions into account, resulting in insufficient task management and reduced mental burden. Solving this problem is essential.

[0386] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0387] In this invention, the server includes means for acquiring user identification information, means for adjusting task priorities according to the user's emotional state using a generative AI model, and means for supporting document creation and meeting preparation according to the user's emotional state. This enables efficient task management and stress reduction that takes into account the user's emotional state.

[0388] "User identification information" refers to attribute information necessary to identify a user. This information includes user ID, authentication information, job data, etc.

[0389] A "generative AI model" refers to an artificial intelligence program that uses machine learning techniques to analyze data patterns and make predictions and suggestions. This model plays a role in adjusting task priorities based on the user's work status.

[0390] "Emotional state" refers to data that indicates the user's mental or emotional condition. This data is obtained by analyzing voice, facial expressions, vital signs, etc.

[0391] "Adjusting task priorities" refers to the process of rearranging the order and importance of a user's work tasks based on their emotional state. This adjustment is done to improve the user's efficiency.

[0392] "Supporting document creation and meeting preparation" refers to providing support to help users prepare necessary documents and arrange meetings to ensure their work proceeds smoothly.

[0393] This system is an advanced business support system designed to improve work efficiency based on the user's emotional state. It primarily operates by combining a server, terminals, and an emotion engine.

[0394] First, when a user accesses the system via a terminal, the server obtains the user's identification information. The terminal has a built-in emotion engine that analyzes the user's emotional state using speech recognition software and image processing technology. Information obtained from voice data and facial expressions is important for determining the user's real-time mental state.

[0395] Next, the server uses a generative AI model to adjust task priorities based on the user's emotional state. The generative AI model suggests the most appropriate task assignments based on the user's past work data and current emotional state. This model enables more accurate task prioritization by explicitly indicating what decisions are needed from the AI ​​through prompt statements. For example, the instruction "Suggest the best task assignment for a user who is stressed" plays a crucial role here.

[0396] Within this system, the server also optimizes the schedule based on the user's emotional state. To this end, the server may add short breaks to the schedule or recommend music to enhance concentration while working.

[0397] Furthermore, if a user has a meeting or business trip scheduled, the server automatically suggests and prepares necessary materials, optimal transportation, and accommodation based on sentiment analysis. This reduces the burden on users in preparing for work and arranging business trips.

[0398] Ultimately, in email processing, the server considers the user's emotional state to generate the most appropriate reply and suggests email responses based on their importance. This entire process can reduce employee stress and improve work efficiency.

[0399] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0400] Step 1:

[0401] When a user logs into the system via a terminal, the server receives the user's identification information as input data. This authenticates the user. If authentication is successful, the server retrieves the user's job information, work history, and schedule data from the database as output.

[0402] Step 2:

[0403] An emotion engine built into the device monitors the user's emotional state in real time. Input data includes the user's voice, facial expressions, and biometric information from wearable devices. Based on this data, the device applies an emotion analysis algorithm to identify the user's current emotion. This identified emotional state is then sent to the server as output.

[0404] Step 3:

[0405] The server inputs the user's identification information and emotional state received from the emotion engine into a generative AI model. The generative AI model learns from past data and uses the prompt "Suggestion for optimal task placement for a user in a stressed state" to output the optimal task priority for the user. Based on this output, the server optimizes the task schedule.

[0406] Step 4:

[0407] The server adjusts the work schedule based on the user's emotional state. Input data includes information about the user's fatigue level and concentration level. The server provides output such as suggesting short breaks or recommending relaxing music. The terminal receives this information and notifies the user.

[0408] Step 5:

[0409] When users plan meetings or business trips, the server uses the entered schedule information and sentiment data to suggest suitable modes of transportation and accommodations. This suggestion also assists with booking procedures, ensuring users enjoy a convenient and hassle-free experience.

[0410] Step 6:

[0411] In processing emails, the server receives emails opened by users as input data. After analyzing the email content along with the emotional state, it outputs suggested replies. High-priority emails prompt for a quick response, while emails requiring a more complex reply receive warnings tailored to the emotional state of the user.

[0412] (Application Example 2)

[0413] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0414] In modern homes and workplaces, individual users face diverse emotional states and workloads, requiring efficient support tailored to their individual needs. Ideally, within the home, the living environment and conversation content should be adjusted to the user's emotions, but a suitable system for this is lacking. In this context, technology that recognizes emotions and supports work and daily life is essential.

[0415] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0416] In this invention, the server includes means for acquiring user information, means for extracting and analyzing tasks based on the acquired user information, and means for optimizing the schedule based on the analysis results. This makes it possible to optimize the user's work and home activities according to their emotional state.

[0417] "User information" is a general term for the data that a system collects to identify a user and understand their work history and emotional state.

[0418] "Emotional state" refers to the user's psychological state at that moment, analyzed based on their facial expressions, tone of voice, and other vital signs.

[0419] A "task" refers to an individual task or activity that a user must perform in their daily life or work.

[0420] "Optimizing the schedule" refers to efficiently rearranging the day's activities based on the user's emotional state and work priorities.

[0421] "Automation" refers to a process in which existing procedures are performed automatically rather than manually, through the intervention of a system.

[0422] "Adjusting the home environment" refers to robots and devices appropriately controlling lighting, music, conversations, and other elements within the home according to the user's emotional state.

[0423] "Recognizing emotions" refers to the technical process by which a system analyzes psychological characteristics derived from user input information to identify the user's current emotions.

[0424] This invention is a system that recognizes a user's emotional state in real time and provides support tailored to their individual circumstances. This system primarily consists of a server, a terminal, and an emotion recognition engine.

[0425] The server first acquires user information, and then extracts and analyzes tasks based on that information. This is achieved using hardware (such as sensors like cameras and microphones) that collects the user's work history and emotional state data. The emotion recognition engine processes the data acquired by these sensors and identifies the emotional state from facial expressions and tone of voice.

[0426] Furthermore, the device automatically prioritizes tasks and optimizes the schedule based on emotion recognition. By utilizing a generative AI model, it can suggest simple tasks if the user is feeling stressed. In addition, a smart home appliance control system is used to adjust the environment within the home. For example, if it determines that relaxation is needed, the music playback device will play calming music and the lighting will be adjusted to a softer tone.

[0427] For example, if a user returns home from work and the system recognizes their fatigue level, it can automatically create a relaxing environment. If the weather is good, it could adjust the humidity to a suitable level and activate a device that emits a relaxing scent. Another example of a prompt message would be, "Generate instructions to create a relaxing lighting and music environment for the user."

[0428] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0429] Step 1:

[0430] The server retrieves the user's profile data and work history. This data includes past task history, schedules, and vital sign information from wearable devices. Based on the entered data, a database is updated to predict the user's current emotional state.

[0431] Step 2:

[0432] The device uses an emotion recognition engine to analyze the user's emotional state in real time. Voice tone and facial expression data are sent to the device as input, which is then analyzed to identify the user's emotions. The analysis result outputs the emotional state (e.g., stress, relaxation).

[0433] Step 3:

[0434] The server re-evaluates task priorities using a generative AI model based on emotional state data. The server receives emotional state data as input, analyzes the current task list based on this data, and resets priorities. The optimized list is then displayed to the user as output.

[0435] Step 4:

[0436] To adjust the home environment that users use on a daily basis, the device operates devices via a smart home appliance control system. For example, if the entered emotional state is "fatigue," it will activate a music playback device and play relaxing music. It will also output specific instructions to adjust the lighting.

[0437] Step 5:

[0438] The server adapts pre-configured prompts and suggests optimal activities for the user through a generating AI model. For example, it might generate prompts and output instructions to adjust lighting and music settings to help the user relax. The outputted instructions are then displayed to the user and executed.

[0439] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0440] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0441] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0442] [Third Embodiment]

[0443] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0444] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0445] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0446] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0447] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0448] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0449] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0450] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0451] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0452] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0453] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0454] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0455] This invention is a system designed to streamline users' work, and aims for the server, terminal, and user to work together in coordination. The roles of each component are described below.

[0456] User authentication and information retrieval:

[0457] When a user accesses the system through their device, the server authenticates the user and retrieves their profile data from the database. This data includes past work history and schedule information, serving as the foundation for providing personalized support based on the user's attributes.

[0458] Task automation:

[0459] The server analyzes the acquired user data and automatically extracts and lists the daily tasks required by the user. For example, for a sales representative, it automatically picks out a list of contracts scheduled to be concluded this week and important customer visit dates. It also dynamically adjusts the priority of these tasks using a generative AI model.

[0460] Schedule management and optimization:

[0461] The server analyzes the user's work schedule and optimizes the placement of each task. It adjusts the schedule to enable efficient work execution for the user and notifies the terminal accordingly. For example, it might adjust lunch breaks to coincide with sales travel time to ensure efficient work even on tight schedules.

[0462] Meeting preparation:

[0463] The server automatically collects and organizes the necessary materials for meetings the user is scheduled to attend from the user's past work data, and edits them according to a document template. These materials are then presented to the user on their terminal for review and adjustment.

[0464] Business trip arrangements:

[0465] When a user enters their business trip schedule, the server collects information on the most suitable transportation and accommodation options based on that schedule and completes the arrangements. Booking confirmations are automatically sent to the user's device, allowing them to prepare for their trip smoothly. Specifically, the server also provides weather and access information for the destination, supporting decision-making during the trip.

[0466] Email correspondence:

[0467] The server analyzes received emails, summarizes their content, and generates a draft reply. This reply is relevant to the business context and is sent after user confirmation. This allows users to efficiently process important emails from a large volume of messages.

[0468] In this way, this system provides a series of processes in which the server effectively utilizes the user's business data and reduces the user's workload via the terminal. Ultimately, it supports improved user productivity and enables innovation in business operations.

[0469] The following describes the processing flow.

[0470] Step 1:

[0471] When a user attempts to log in from a terminal, the server verifies the authentication information, and if successful, retrieves the user's profile data from the database. This prepares the server to understand the user's role in the workplace and their habits.

[0472] Step 2:

[0473] The server utilizes an AI model generated based on the acquired profile data to extract and list tasks that the user is scheduled to perform. These tasks include scheduled meetings and projects that require progress.

[0474] Step 3:

[0475] Based on analytical data, the server optimizes the user's daily schedule and efficiently allocates tasks. For example, it makes adjustments such as inserting preparation time between important meetings to prevent them from being scheduled consecutively.

[0476] Step 4:

[0477] The server schedules meetings based on the user's work schedule and automatically creates necessary documents from the user's data and system information. This reduces the time users spend creating documents. The created documents are notified to the terminal, allowing the user to review them.

[0478] Step 5:

[0479] When the server receives a travel request from a user, it matches the user's schedule with destination information and arranges the most suitable transportation and accommodation. Once the booking is complete, the travel plan is notified on the user's device, allowing them to confidently incorporate it into their schedule.

[0480] Step 6:

[0481] The server analyzes received emails, determines their importance, and prioritizes them. Furthermore, it understands the content of the emails and automatically generates draft replies. These draft replies are presented to the user via their device, allowing them to make minor adjustments before sending.

[0482] This series of steps will free users from tedious daily tasks, allowing them to focus on their core responsibilities.

[0483] (Example 1)

[0484] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0485] In today's workplace, improving work efficiency and productivity are crucial challenges. However, manual task management, scheduling, meeting preparation, and travel arrangements consume a great deal of time and effort, placing a significant burden on users. Furthermore, users are required to efficiently process the vast amount of information received via email. In this situation, users find it difficult to concentrate on their own work, and there is a need for support to perform tasks efficiently and smoothly.

[0486] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0487] In this invention, the server includes means for acquiring user information, means for extracting and analyzing work activities based on the acquired user information, and means for optimizing the timetable based on the analysis results. This enables users to efficiently manage their work and make effective use of their time. Furthermore, by automating work planning and scheduling, it is possible to reduce the burden on users and improve work productivity.

[0488] "User information" refers to identification data and profile information related to users registered in the system.

[0489] "Business activities" refer to the collection of all tasks and administrative processes related to the job that users perform on a daily basis.

[0490] "Analysis" is the act of finding patterns and trends based on acquired data and deepening one's understanding of it.

[0491] A "timetable" is a plan of time allocation to efficiently schedule the work activities of users.

[0492] "Automation" refers to making tasks that were previously performed manually possible through the control of machines or computers.

[0493] "Information organization" is the act of collecting necessary materials and data according to a purpose and arranging them in a format that is easy to use.

[0494] "Arranging" refers to the act of making the necessary preparations and procedures and moving things forward towards a goal.

[0495] "Electronic communication" refers to a means of exchanging messages that send and receive information in digital format, such as email.

[0496] A "draft reply" is the content of a proposed response to be sent in response to an received electronic communication.

[0497] "Generative AI technology" is a technology that uses artificial intelligence to generate new information and data.

[0498] A "work plan" is a strategic plan that systematically organizes and executes job activities aimed at achieving specific goals.

[0499] "Travel information" refers to all necessary data related to travel and accommodation, including departure point, destination, mode of transport, etc.

[0500] This invention is a system designed to streamline user operations and improve productivity, and it operates in a manner in which a server, terminal, and user interact with each other. A specific example of this system is shown below.

[0501] The server authenticates user information when a user accesses the system through a terminal. This process can utilize, for example, cloud-based authentication services or authentication algorithms. Once the user is successfully authenticated, the server retrieves user information from the database. This information includes work history, schedules, and profile data.

[0502] Next, the server analyzes business activities based on user information. Using Python's Pandas library and natural language processing tools, it analyzes the data and lists daily tasks. A generative AI model is used in this data analysis process to dynamically determine the priority of each task.

[0503] For example, a sales representative might list their customer visit dates and contract signing dates for the week and prioritize them. This allows the user to intuitively understand which tasks should be prioritized.

[0504] Schedule optimization involves the server rearranging the user's work schedule and making adjustments to ensure efficient work execution. Optimization tools are used to generate a personalized schedule. The terminal receives this optimized schedule and notifies the user.

[0505] Furthermore, the server automatically collects the necessary materials for meeting preparation and presents them to the terminal in an organized format according to a template. Natural language processing technology is used to analyze the materials, making them easily adjustable for the user.

[0506] In the business trip arrangement process, when a user enters their travel information, the server searches for and arranges the most suitable transportation and accommodation based on that information. Various APIs are used to provide users with the latest information, supporting efficient business trip preparation. This allows for quick decision-making during the business trip.

[0507] Finally, the server analyzes the email and generates a draft reply using a generative AI model. This draft reply is relevant to the business context and can be modified by the user as needed before being sent via their device.

[0508] For example, if a sales representative wants to check their priority tasks for the week, they would enter the following:

[0509] "What are this week's top priorities?"

[0510] Examples of prompt statements include the following:

[0511] "Please list your top priority tasks for this week as a sales representative. Include the estimated time and priority for each task."

[0512] In this way, the system utilizes servers, terminals, and generative AI technology to enable users to efficiently manage their work.

[0513] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0514] Step 1:

[0515] When a user accesses the system through a terminal, the terminal sends the user's authentication information to the server. The server initiates the authentication process using the user ID and password. This involves secure communication and the execution of an authentication service. If authentication is successful, the server accesses the database and retrieves user information. The input is the user's login information, and the output is the user profile and work history.

[0516] Step 2:

[0517] The server analyzes the user's work activities based on the acquired user information. This generates a task list for the user. The input is the user's past work history, and the output is a list of tasks the user must complete. Specifically, it uses Python's Pandas library for data analysis and a generated AI model to determine task priorities. The user can view the generated task list on their terminal.

[0518] Step 3:

[0519] The server optimizes the user's schedule based on the task list. The input is the task list, and the output is the optimized schedule. The server uses optimization tools and a generative AI model to create an efficient work plan. This schedule is notified to the terminal, allowing the user to view and adjust the schedule on their terminal.

[0520] Step 4:

[0521] The server collects and organizes the necessary data to prepare meeting materials for meetings that users are scheduled to attend. The input is historical business data, and the output is meeting materials based on a template. Natural language processing tools are used to analyze the data, and the materials are presented to the user's terminal for review and modification.

[0522] Step 5:

[0523] When a user enters their business trip information into a terminal, the server receives it and arranges the most suitable transportation and accommodation. The server uses an API to collect travel information and find the best options. The input is the user's business trip schedule, and the output is a booking confirmation notification. This allows users to efficiently prepare for their business trips.

[0524] Step 6:

[0525] The server analyzes received emails and generates suggested replies. The input is the received email, and the output is the generated suggested reply. It utilizes a generative AI model and natural language processing technology to summarize the email content and suggest appropriate replies. Users can review these on their devices, modify them as needed, and send them.

[0526] (Application Example 1)

[0527] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0528] In today's business environment, users need to efficiently handle a wide variety of tasks while making critical decisions within limited timeframes. However, the sheer volume of information, the time and effort required to manage transaction records and work schedules, and the difficulty in prioritizing and optimizing plans all hinder user productivity. This is particularly true in electronic payment operations, where rapid and accurate transaction planning and customer communication are essential, necessitating systems that address these challenges.

[0529] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0530] In this invention, the server includes means for acquiring user information, means for extracting and analyzing tasks based on the acquired user information, means for optimizing the schedule based on the analysis results, means for automating tasks and supporting information creation and placement settings, means for automatically arranging transportation and accommodation, means for analyzing electronic documents and generating response plans, means for reading user transaction records and analyzing business history, and means for dynamically generating and optimizing transaction plans using a generation AI model. This makes it possible to efficiently manage diverse business tasks and improve user productivity.

[0531] "Means for acquiring user information" refers to a function that collects user-related information, such as user profiles and past work data, and makes it available within the system.

[0532] "Means for extracting and analyzing tasks" refers to a function that identifies necessary business tasks from acquired user information and evaluates and analyzes them.

[0533] "Methods for optimizing schedules" refer to functions that efficiently allocate and manage users' work tasks, optimizing the use of time and resources.

[0534] "Means of automating tasks and supporting information creation and placement settings" refers to functions that automate parts of business tasks and support the preparation of meeting materials, visit arrangements, and other similar tasks.

[0535] "Methods for automatically arranging transportation and accommodation" refers to functions that automatically make reservations for available transportation and accommodation based on business trips and travel plans.

[0536] "Means for analyzing electronic documents and generating response drafts" refers to a function that analyzes received emails and other documents and automatically suggests response content.

[0537] "A means of reading user transaction records and analyzing business history" refers to a function that acquires a user's past transaction data and analyzes patterns and trends related to their business based on that data.

[0538] "A means of dynamically generating and optimizing trading plans using a generative AI model" refers to a function that utilizes artificial intelligence technology to formulate and improve the optimal trading plan for the current situation in real time.

[0539] The system that implements this application example is centered around a server program built on the Python Flask framework, using PostgreSQL as its database. On smartphones, the user interface is built using React Native.

[0540] The server first retrieves user information when a user accesses it through their terminal. This includes user profile data and past work history. Based on the retrieved information, it uses a generative AI model to extract and analyze work tasks relevant to the user. Once the necessary tasks are identified, the server optimizes the schedule based on them.

[0541] By analyzing users' transaction records and using a generative AI model, we dynamically generate and optimize transaction plans. This process makes it possible to propose the best transaction strategy tailored to the current business situation.

[0542] Furthermore, the server organizes the user's work tasks, analyzes electronic documents, and generates necessary materials and draft replies. This allows users to carry out their work efficiently and effectively. It also automatically arranges transportation and accommodation, supporting users in preparing for business trips.

[0543] For example, when a user plans their next campaign, the system predicts the necessary product inventory based on past data and automatically generates a related transaction plan. This allows them to schedule negotiations with suppliers at the appropriate time and maximize profits.

[0544] An example of a prompt for the generating AI model is: "Analyze the transaction data from the past three months and generate the optimal transaction schedule and inventory forecast for the next quarter."

[0545] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0546] Step 1:

[0547] The server authenticates users accessing through the terminal. The input includes a username and password, which the server compares against the registered information in the database to verify the user's legitimacy. During this process, user profile data is retrieved from the database and prepared for use in the next processing step. The output indicates whether authentication was successful or unsuccessful.

[0548] Step 2:

[0549] The server extracts relevant business tasks based on the acquired user profile data. The input is the user's profile data, and the output is a list of tasks relevant to the user's future work. Using a generative AI model, high-priority tasks are identified by dynamically determining task priorities based on the user's past work history.

[0550] Step 3:

[0551] The server optimizes the schedule based on the task list. The input is a prioritized task list, and the output is an optimized schedule. The generative AI model maximizes the efficiency of time and resource utilization and implements optimal scheduling. For example, it efficiently schedules sales visits and minimizes travel time.

[0552] Step 4:

[0553] The server analyzes emails and other necessary documents and automatically generates draft replies and supporting materials. The input is the received electronic documents, and the output is AI-generated draft replies and supporting material templates. Using a generation AI model, the content of the documents is analyzed to create contextually appropriate replies. During this process, emails are also organized according to their priority.

[0554] Step 5:

[0555] This system analyzes the user's transaction history and dynamically generates and optimizes transaction plans. The input is the user's past transaction data, and the output is an optimized transaction plan. The generating AI model analyzes past transaction patterns and presents the optimal transaction strategy in real time. Based on this, the user can then schedule their next business opportunity.

[0556] Step 6:

[0557] The server automatically arranges transportation and accommodation based on the business trip schedule. The input is business trip information provided by the user, and the output is booking confirmation information. The system uses external APIs to collect transportation and accommodation options and suggests the best choices to the user. After reviewing the suggestions, the user can easily prepare for their business trip.

[0558] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0559] This invention is a system that utilizes user emotion recognition to improve work efficiency and provide an appropriate work environment. This system consists of a server, a terminal, and an emotion engine, which are designed to work together to reduce the user's workload.

[0560] User recognition and data acquisition:

[0561] When a user accesses the system through their device, the server first authenticates the user and collects their profile data. This data includes the user's job information, past work history, schedule, etc., and forms the basis for providing personalized support.

[0562] Emotion recognition:

[0563] The server uses an emotion engine installed in the terminal to monitor the user's emotional state in real time. The emotion engine analyzes the user's input data, vital signs from the wearable device, voice, and facial expressions to identify the user's current emotion.

[0564] Task management and optimization:

[0565] The server adjusts task priorities using a generative AI model, taking into account the user's emotional state. For example, if the server determines that the user is stressed, it will either postpone low-priority tasks or prioritize assigning easier tasks.

[0566] Schedule adjustment:

[0567] Based on emotional data, the server optimizes the work schedule. For example, if a user is feeling fatigued, a short break is added to the schedule. Furthermore, to enhance concentration when working on specific tasks, it recommends music and suggests environmental settings that match the user's emotions.

[0568] Meeting preparation:

[0569] The server uses feedback from the emotion engine to prepare for the meeting. If the user is feeling anxious, it suggests relaxation techniques and provides materials to help them prepare for the meeting.

[0570] Business trip arrangements:

[0571] When a user plans a business trip, the server uses emotion recognition results to suggest comfortable modes of transportation and accommodations. Even when long-distance travel is involved, arrangements are made with the user's comfort as a top priority.

[0572] Email correspondence:

[0573] When users process emails, the server advises them to avoid difficult replies depending on their emotions, or, if it determines they are in a calm state, encourages them to prioritize replying to higher-priority emails.

[0574] In this way, this system, which incorporates an emotion engine, aims to improve the quality of work by taking into account the user's emotional state. As a result, improvements in employee satisfaction and productivity are expected.

[0575] The following describes the processing flow.

[0576] Step 1:

[0577] When a user logs into a terminal, the server verifies the user's authentication information and retrieves profile data from the database based on the results. This profile contains various data related to the user's work.

[0578] Step 2:

[0579] The server activates the emotion engine from the terminal and collects user emotion data in real time. The emotion engine identifies the user's emotional state by analyzing facial recognition, voice tone, and user input speed.

[0580] Step 3:

[0581] Based on the acquired emotional data, the server re-evaluates the prioritization of the user's daily tasks. Specifically, if data indicating stress is detected, the server prioritizes simpler tasks or adjusts the work plan to reduce stress.

[0582] Step 4:

[0583] The system notifies the user of an optimized schedule via the device. For example, if emotional data indicates fatigue, the server suggests a set amount of rest time and presents that schedule to the user.

[0584] Step 5:

[0585] The server uses emotional data to support meeting preparation. If a user is feeling nervous, it automatically generates materials and relaxation techniques to alleviate the tension and delivers them to the user via their device.

[0586] Step 6:

[0587] When preparing for a business trip, the user enters their travel information into their device. Based on emotional data, the server automatically arranges transportation and accommodations that prioritize comfort, and notifies the user of the details.

[0588] Step 7:

[0589] In analyzing incoming emails, the server utilizes an emotion engine to understand the user's emotional state and adjust the priority of suggested replies accordingly. For example, if the user is relaxed, the email might include a message urging them to respond quickly to important emails.

[0590] Through this series of processes, a system that incorporates emotion recognition capabilities takes into account the user's emotional state and provides support aimed at improving work efficiency and reducing mental burden.

[0591] (Example 2)

[0592] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0593] In today's work environment, there is a growing need for work support systems that take employees' emotional states into consideration. Traditional systems do not take emotions into account, resulting in insufficient task management and reduced mental burden. Solving this problem is essential.

[0594] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0595] In this invention, the server includes means for acquiring user identification information, means for adjusting task priorities according to the user's emotional state using a generative AI model, and means for supporting document creation and meeting preparation according to the user's emotional state. This enables efficient task management and stress reduction that takes into account the user's emotional state.

[0596] "User identification information" refers to attribute information necessary to identify a user. This information includes user ID, authentication information, job data, etc.

[0597] A "generative AI model" refers to an artificial intelligence program that uses machine learning techniques to analyze data patterns and make predictions and suggestions. This model plays a role in adjusting task priorities based on the user's work status.

[0598] "Emotional state" refers to data that indicates the user's mental or emotional condition. This data is obtained by analyzing voice, facial expressions, vital signs, etc.

[0599] "Adjusting task priorities" refers to the process of rearranging the order and importance of a user's work tasks based on their emotional state. This adjustment is done to improve the user's efficiency.

[0600] "Supporting document creation and meeting preparation" refers to providing support to help users prepare necessary documents and arrange meetings to ensure their work proceeds smoothly.

[0601] This system is an advanced business support system designed to improve work efficiency based on the user's emotional state. It primarily operates by combining a server, terminals, and an emotion engine.

[0602] First, when a user accesses the system via a terminal, the server obtains the user's identification information. The terminal has a built-in emotion engine that analyzes the user's emotional state using speech recognition software and image processing technology. Information obtained from voice data and facial expressions is important for determining the user's real-time mental state.

[0603] Next, the server uses a generative AI model to adjust task priorities based on the user's emotional state. The generative AI model suggests the most appropriate task assignments based on the user's past work data and current emotional state. This model enables more accurate task prioritization by explicitly indicating what decisions are needed from the AI ​​through prompt statements. For example, the instruction "Suggest the best task assignment for a user who is stressed" plays a crucial role here.

[0604] Within this system, the server also optimizes the schedule based on the user's emotional state. To this end, the server may add short breaks to the schedule or recommend music to enhance concentration while working.

[0605] Furthermore, if a user has a meeting or business trip scheduled, the server automatically suggests and prepares necessary materials, optimal transportation, and accommodation based on sentiment analysis. This reduces the burden on users in preparing for work and arranging business trips.

[0606] Ultimately, in email processing, the server considers the user's emotional state to generate the most appropriate reply and suggests email responses based on their importance. This entire process can reduce employee stress and improve work efficiency.

[0607] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0608] Step 1:

[0609] When a user logs into the system via a terminal, the server receives the user's identification information as input data. This authenticates the user. If authentication is successful, the server retrieves the user's job information, work history, and schedule data from the database as output.

[0610] Step 2:

[0611] An emotion engine built into the device monitors the user's emotional state in real time. Input data includes the user's voice, facial expressions, and biometric information from wearable devices. Based on this data, the device applies an emotion analysis algorithm to identify the user's current emotion. This identified emotional state is then sent to the server as output.

[0612] Step 3:

[0613] The server inputs the user's identification information and emotional state received from the emotion engine into a generative AI model. The generative AI model learns from past data and uses the prompt "Suggestion for optimal task placement for a user in a stressed state" to output the optimal task priority for the user. Based on this output, the server optimizes the task schedule.

[0614] Step 4:

[0615] The server adjusts the work schedule based on the user's emotional state. Input data includes information about the user's fatigue level and concentration level. The server provides output such as suggesting short breaks or recommending relaxing music. The terminal receives this information and notifies the user.

[0616] Step 5:

[0617] When users plan meetings or business trips, the server uses the entered schedule information and sentiment data to suggest suitable modes of transportation and accommodations. This suggestion also assists with booking procedures, ensuring users enjoy a convenient and hassle-free experience.

[0618] Step 6:

[0619] In processing emails, the server receives emails opened by users as input data. After analyzing the email content along with the emotional state, it outputs suggested replies. High-priority emails prompt for a quick response, while emails requiring a more complex reply receive warnings tailored to the emotional state of the user.

[0620] (Application Example 2)

[0621] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0622] In modern homes and workplaces, individual users face diverse emotional states and workloads, requiring efficient support tailored to their individual needs. Ideally, within the home, the living environment and conversation content should be adjusted to the user's emotions, but a suitable system for this is lacking. In this context, technology that recognizes emotions and supports work and daily life is essential.

[0623] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0624] In this invention, the server includes means for acquiring user information, means for extracting and analyzing tasks based on the acquired user information, and means for optimizing the schedule based on the analysis results. This makes it possible to optimize the user's work and home activities according to their emotional state.

[0625] "User information" is a general term for the data that a system collects to identify a user and understand their work history and emotional state.

[0626] "Emotional state" refers to the user's psychological state at that moment, analyzed based on their facial expressions, tone of voice, and other vital signs.

[0627] A "task" refers to an individual task or activity that a user must perform in their daily life or work.

[0628] "Optimizing the schedule" refers to efficiently rearranging the day's activities based on the user's emotional state and work priorities.

[0629] "Automation" refers to a process in which existing procedures are performed automatically rather than manually, through the intervention of a system.

[0630] "Adjusting the home environment" refers to robots and devices appropriately controlling lighting, music, conversations, and other elements within the home according to the user's emotional state.

[0631] "Recognizing emotions" refers to the technical process by which a system analyzes psychological characteristics derived from user input information to identify the user's current emotions.

[0632] This invention is a system that recognizes a user's emotional state in real time and provides support tailored to their individual circumstances. This system primarily consists of a server, a terminal, and an emotion recognition engine.

[0633] The server first acquires user information, and then extracts and analyzes tasks based on that information. This is achieved using hardware (such as sensors like cameras and microphones) that collects the user's work history and emotional state data. The emotion recognition engine processes the data acquired by these sensors and identifies the emotional state from facial expressions and tone of voice.

[0634] Furthermore, the device automatically prioritizes tasks and optimizes the schedule based on emotion recognition. By utilizing a generative AI model, it can suggest simple tasks if the user is feeling stressed. In addition, a smart home appliance control system is used to adjust the environment within the home. For example, if it determines that relaxation is needed, the music playback device will play calming music and the lighting will be adjusted to a softer tone.

[0635] For example, if a user returns home from work and the system recognizes their fatigue level, it can automatically create a relaxing environment. If the weather is good, it could adjust the humidity to a suitable level and activate a device that emits a relaxing scent. Another example of a prompt message would be, "Generate instructions to create a relaxing lighting and music environment for the user."

[0636] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0637] Step 1:

[0638] The server retrieves the user's profile data and work history. This data includes past task history, schedules, and vital sign information from wearable devices. Based on the entered data, a database is updated to predict the user's current emotional state.

[0639] Step 2:

[0640] The device uses an emotion recognition engine to analyze the user's emotional state in real time. Voice tone and facial expression data are sent to the device as input, which is then analyzed to identify the user's emotions. The analysis result outputs the emotional state (e.g., stress, relaxation).

[0641] Step 3:

[0642] The server re-evaluates task priorities using a generative AI model based on emotional state data. The server receives emotional state data as input, analyzes the current task list based on this data, and resets priorities. The optimized list is then displayed to the user as output.

[0643] Step 4:

[0644] To adjust the home environment that users use on a daily basis, the device operates devices via a smart home appliance control system. For example, if the entered emotional state is "fatigue," it will activate a music playback device and play relaxing music. It will also output specific instructions to adjust the lighting.

[0645] Step 5:

[0646] The server adapts pre-configured prompts and suggests optimal activities for the user through a generating AI model. For example, it might generate prompts and output instructions to adjust lighting and music settings to help the user relax. The outputted instructions are then displayed to the user and executed.

[0647] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0648] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0649] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0650] [Fourth Embodiment]

[0651] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0652] As shown in Figure 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.

[0653] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0654] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0655] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0656] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0657] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0658] The controlled 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0659] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0660] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0661] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0662] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0663] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0664] This invention is a system designed to streamline users' work, and aims for the server, terminal, and user to work together in coordination. The roles of each component are described below.

[0665] User authentication and information retrieval:

[0666] When a user accesses the system through their device, the server authenticates the user and retrieves their profile data from the database. This data includes past work history and schedule information, serving as the foundation for providing personalized support based on the user's attributes.

[0667] Task automation:

[0668] The server analyzes the acquired user data and automatically extracts and lists the daily tasks required by the user. For example, for a sales representative, it automatically picks out a list of contracts scheduled to be concluded this week and important customer visit dates. It also dynamically adjusts the priority of these tasks using a generative AI model.

[0669] Schedule management and optimization:

[0670] The server analyzes the user's work schedule and optimizes the placement of each task. It adjusts the schedule to enable efficient work execution for the user and notifies the terminal accordingly. For example, it might adjust lunch breaks to coincide with sales travel time to ensure efficient work even on tight schedules.

[0671] Meeting preparation:

[0672] The server automatically collects and organizes the necessary materials for meetings the user is scheduled to attend from the user's past work data, and edits them according to a document template. These materials are then presented to the user on their terminal for review and adjustment.

[0673] Business trip arrangements:

[0674] When a user enters their business trip schedule, the server collects information on the most suitable transportation and accommodation options based on that schedule and completes the arrangements. Booking confirmations are automatically sent to the user's device, allowing them to prepare for their trip smoothly. Specifically, the server also provides weather and access information for the destination, supporting decision-making during the trip.

[0675] Email correspondence:

[0676] The server analyzes received emails, summarizes their content, and generates a draft reply. This reply is relevant to the business context and is sent after user confirmation. This allows users to efficiently process important emails from a large volume of messages.

[0677] In this way, this system provides a series of processes in which the server effectively utilizes the user's business data and reduces the user's workload via the terminal. Ultimately, it supports improved user productivity and enables innovation in business operations.

[0678] The following describes the processing flow.

[0679] Step 1:

[0680] When a user attempts to log in from a terminal, the server verifies the authentication information, and if successful, retrieves the user's profile data from the database. This prepares the server to understand the user's role in the workplace and their habits.

[0681] Step 2:

[0682] The server utilizes an AI model generated based on the acquired profile data to extract and list tasks that the user is scheduled to perform. These tasks include scheduled meetings and projects that require progress.

[0683] Step 3:

[0684] Based on analytical data, the server optimizes the user's daily schedule and efficiently allocates tasks. For example, it makes adjustments such as inserting preparation time between important meetings to prevent them from being scheduled consecutively.

[0685] Step 4:

[0686] The server schedules meetings based on the user's work schedule and automatically creates necessary documents from the user's data and system information. This reduces the time users spend creating documents. The created documents are notified to the terminal, allowing the user to review them.

[0687] Step 5:

[0688] When the server receives a travel request from a user, it matches the user's schedule with destination information and arranges the most suitable transportation and accommodation. Once the booking is complete, the travel plan is notified on the user's device, allowing them to confidently incorporate it into their schedule.

[0689] Step 6:

[0690] The server analyzes received emails, determines their importance, and prioritizes them. Furthermore, it understands the content of the emails and automatically generates draft replies. These draft replies are presented to the user via their device, allowing them to make minor adjustments before sending.

[0691] This series of steps will free users from tedious daily tasks, allowing them to focus on their core responsibilities.

[0692] (Example 1)

[0693] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0694] In today's workplace, improving work efficiency and productivity are crucial challenges. However, manual task management, scheduling, meeting preparation, and travel arrangements consume a great deal of time and effort, placing a significant burden on users. Furthermore, users are required to efficiently process the vast amount of information received via email. In this situation, users find it difficult to concentrate on their own work, and there is a need for support to perform tasks efficiently and smoothly.

[0695] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0696] In this invention, the server includes means for acquiring user information, means for extracting and analyzing work activities based on the acquired user information, and means for optimizing the timetable based on the analysis results. This enables users to efficiently manage their work and make effective use of their time. Furthermore, by automating work planning and scheduling, it is possible to reduce the burden on users and improve work productivity.

[0697] "User information" refers to identification data and profile information related to users registered in the system.

[0698] "Business activities" refer to the collection of all tasks and administrative processes related to the job that users perform on a daily basis.

[0699] "Analysis" is the act of finding patterns and trends based on acquired data and deepening one's understanding of it.

[0700] A "timetable" is a plan of time allocation to efficiently schedule the work activities of users.

[0701] "Automation" refers to making tasks that were previously performed manually possible through the control of machines or computers.

[0702] "Information organization" is the act of collecting necessary materials and data according to a purpose and arranging them in a format that is easy to use.

[0703] "Arranging" refers to the act of making the necessary preparations and procedures and moving things forward towards a goal.

[0704] "Electronic communication" refers to a means of exchanging messages that send and receive information in digital format, such as email.

[0705] A "draft reply" is the content of a proposed response to be sent in response to an received electronic communication.

[0706] "Generative AI technology" is a technology that uses artificial intelligence to generate new information and data.

[0707] A "work plan" is a strategic plan that systematically organizes and executes job activities aimed at achieving specific goals.

[0708] "Travel information" refers to all necessary data related to travel and accommodation, including departure point, destination, mode of transport, etc.

[0709] This invention is a system designed to streamline user operations and improve productivity, and it operates in a manner in which a server, terminal, and user interact with each other. A specific example of this system is shown below.

[0710] The server authenticates user information when a user accesses the system through a terminal. This process can utilize, for example, cloud-based authentication services or authentication algorithms. Once the user is successfully authenticated, the server retrieves user information from the database. This information includes work history, schedules, and profile data.

[0711] Next, the server analyzes business activities based on user information. Using Python's Pandas library and natural language processing tools, it analyzes the data and lists daily tasks. A generative AI model is used in this data analysis process to dynamically determine the priority of each task.

[0712] For example, a sales representative might list their customer visit dates and contract signing dates for the week and prioritize them. This allows the user to intuitively understand which tasks should be prioritized.

[0713] Schedule optimization involves the server rearranging the user's work schedule and making adjustments to ensure efficient work execution. Optimization tools are used to generate a personalized schedule. The terminal receives this optimized schedule and notifies the user.

[0714] Furthermore, the server automatically collects the necessary materials for meeting preparation and presents them to the terminal in an organized format according to a template. Natural language processing technology is used to analyze the materials, making them easily adjustable for the user.

[0715] In the business trip arrangement process, when a user enters their travel information, the server searches for and arranges the most suitable transportation and accommodation based on that information. Various APIs are used to provide users with the latest information, supporting efficient business trip preparation. This allows for quick decision-making during the business trip.

[0716] Finally, the server analyzes the email and generates a draft reply using a generative AI model. This draft reply is relevant to the business context and can be modified by the user as needed before being sent via their device.

[0717] For example, if a sales representative wants to check their priority tasks for the week, they would enter the following:

[0718] "What are this week's top priorities?"

[0719] Examples of prompt statements include the following:

[0720] "Please list your top priority tasks for this week as a sales representative. Include the estimated time and priority for each task."

[0721] In this way, the system utilizes servers, terminals, and generative AI technology to enable users to efficiently manage their work.

[0722] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0723] Step 1:

[0724] When a user accesses the system through a terminal, the terminal sends the user's authentication information to the server. The server initiates the authentication process using the user ID and password. This involves secure communication and the execution of an authentication service. If authentication is successful, the server accesses the database and retrieves user information. The input is the user's login information, and the output is the user profile and work history.

[0725] Step 2:

[0726] The server analyzes the user's work activities based on the acquired user information. This generates a task list for the user. The input is the user's past work history, and the output is a list of tasks the user must complete. Specifically, it uses Python's Pandas library for data analysis and a generated AI model to determine task priorities. The user can view the generated task list on their terminal.

[0727] Step 3:

[0728] The server optimizes the user's schedule based on the task list. The input is the task list, and the output is the optimized schedule. The server uses optimization tools and a generative AI model to create an efficient work plan. This schedule is notified to the terminal, allowing the user to view and adjust the schedule on their terminal.

[0729] Step 4:

[0730] The server collects and organizes the necessary data to prepare meeting materials for meetings that users are scheduled to attend. The input is historical business data, and the output is meeting materials based on a template. Natural language processing tools are used to analyze the data, and the materials are presented to the user's terminal for review and modification.

[0731] Step 5:

[0732] When a user enters their business trip information into a terminal, the server receives it and arranges the most suitable transportation and accommodation. The server uses an API to collect travel information and find the best options. The input is the user's business trip schedule, and the output is a booking confirmation notification. This allows users to efficiently prepare for their business trips.

[0733] Step 6:

[0734] The server analyzes received emails and generates suggested replies. The input is the received email, and the output is the generated suggested reply. It utilizes a generative AI model and natural language processing technology to summarize the email content and suggest appropriate replies. Users can review these on their devices, modify them as needed, and send them.

[0735] (Application Example 1)

[0736] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0737] In today's business environment, users need to efficiently handle a wide variety of tasks while making critical decisions within limited timeframes. However, the sheer volume of information, the time and effort required to manage transaction records and work schedules, and the difficulty in prioritizing and optimizing plans all hinder user productivity. This is particularly true in electronic payment operations, where rapid and accurate transaction planning and customer communication are essential, necessitating systems that address these challenges.

[0738] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0739] In this invention, the server includes means for acquiring user information, means for extracting and analyzing tasks based on the acquired user information, means for optimizing the schedule based on the analysis results, means for automating tasks and supporting information creation and placement settings, means for automatically arranging transportation and accommodation, means for analyzing electronic documents and generating response plans, means for reading user transaction records and analyzing business history, and means for dynamically generating and optimizing transaction plans using a generation AI model. This makes it possible to efficiently manage diverse business tasks and improve user productivity.

[0740] "Means for acquiring user information" refers to a function that collects user-related information, such as user profiles and past work data, and makes it available within the system.

[0741] "Means for extracting and analyzing tasks" refers to a function that identifies necessary business tasks from acquired user information and evaluates and analyzes them.

[0742] "Methods for optimizing schedules" refer to functions that efficiently allocate and manage users' work tasks, optimizing the use of time and resources.

[0743] "Means of automating tasks and supporting information creation and placement settings" refers to functions that automate parts of business tasks and support the preparation of meeting materials, visit arrangements, and other similar tasks.

[0744] "Methods for automatically arranging transportation and accommodation" refers to functions that automatically make reservations for available transportation and accommodation based on business trips and travel plans.

[0745] "Means for analyzing electronic documents and generating response drafts" refers to a function that analyzes received emails and other documents and automatically suggests response content.

[0746] "A means of reading user transaction records and analyzing business history" refers to a function that acquires a user's past transaction data and analyzes patterns and trends related to their business based on that data.

[0747] "A means of dynamically generating and optimizing trading plans using a generative AI model" refers to a function that utilizes artificial intelligence technology to formulate and improve the optimal trading plan for the current situation in real time.

[0748] The system that implements this application example is centered around a server program built on the Python Flask framework, using PostgreSQL as its database. On smartphones, the user interface is built using React Native.

[0749] The server first retrieves user information when a user accesses it through their terminal. This includes user profile data and past work history. Based on the retrieved information, it uses a generative AI model to extract and analyze work tasks relevant to the user. Once the necessary tasks are identified, the server optimizes the schedule based on them.

[0750] By analyzing users' transaction records and using a generative AI model, we dynamically generate and optimize transaction plans. This process makes it possible to propose the best transaction strategy tailored to the current business situation.

[0751] Furthermore, the server organizes the user's work tasks, analyzes electronic documents, and generates necessary materials and draft replies. This allows users to carry out their work efficiently and effectively. It also automatically arranges transportation and accommodation, supporting users in preparing for business trips.

[0752] For example, when a user plans their next campaign, the system predicts the necessary product inventory based on past data and automatically generates a related transaction plan. This allows them to schedule negotiations with suppliers at the appropriate time and maximize profits.

[0753] An example of a prompt for the generating AI model is: "Analyze the transaction data from the past three months and generate the optimal transaction schedule and inventory forecast for the next quarter."

[0754] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0755] Step 1:

[0756] The server authenticates users accessing through the terminal. The input includes a username and password, which the server compares against the registered information in the database to verify the user's legitimacy. During this process, user profile data is retrieved from the database and prepared for use in the next processing step. The output indicates whether authentication was successful or unsuccessful.

[0757] Step 2:

[0758] The server extracts relevant business tasks based on the acquired user profile data. The input is the user's profile data, and the output is a list of tasks relevant to the user's future work. Using a generative AI model, high-priority tasks are identified by dynamically determining task priorities based on the user's past work history.

[0759] Step 3:

[0760] The server optimizes the schedule based on the task list. The input is a prioritized task list, and the output is an optimized schedule. The generative AI model maximizes the efficiency of time and resource utilization and implements optimal scheduling. For example, it efficiently schedules sales visits and minimizes travel time.

[0761] Step 4:

[0762] The server analyzes emails and other necessary documents and automatically generates draft replies and supporting materials. The input is the received electronic documents, and the output is AI-generated draft replies and supporting material templates. Using a generation AI model, the content of the documents is analyzed to create contextually appropriate replies. During this process, emails are also organized according to their priority.

[0763] Step 5:

[0764] This system analyzes the user's transaction history and dynamically generates and optimizes transaction plans. The input is the user's past transaction data, and the output is an optimized transaction plan. The generating AI model analyzes past transaction patterns and presents the optimal transaction strategy in real time. Based on this, the user can then schedule their next business opportunity.

[0765] Step 6:

[0766] The server automatically arranges transportation and accommodation based on the business trip schedule. The input is business trip information provided by the user, and the output is booking confirmation information. The system uses external APIs to collect transportation and accommodation options and suggests the best choices to the user. After reviewing the suggestions, the user can easily prepare for their business trip.

[0767] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0768] This invention is a system that utilizes user emotion recognition to improve work efficiency and provide an appropriate work environment. This system consists of a server, a terminal, and an emotion engine, which are designed to work together to reduce the user's workload.

[0769] User recognition and data acquisition:

[0770] When a user accesses the system through their device, the server first authenticates the user and collects their profile data. This data includes the user's job information, past work history, schedule, etc., and forms the basis for providing personalized support.

[0771] Emotion recognition:

[0772] The server uses an emotion engine installed in the terminal to monitor the user's emotional state in real time. The emotion engine analyzes the user's input data, vital signs from the wearable device, voice, and facial expressions to identify the user's current emotion.

[0773] Task management and optimization:

[0774] The server adjusts task priorities using a generative AI model, taking into account the user's emotional state. For example, if the server determines that the user is stressed, it will either postpone low-priority tasks or prioritize assigning easier tasks.

[0775] Schedule adjustment:

[0776] Based on emotional data, the server optimizes the work schedule. For example, if a user is feeling fatigued, a short break is added to the schedule. Furthermore, to enhance concentration when working on specific tasks, it recommends music and suggests environmental settings that match the user's emotions.

[0777] Meeting preparation:

[0778] The server uses feedback from the emotion engine to prepare for the meeting. If the user is feeling anxious, it suggests relaxation techniques and provides materials to help them prepare for the meeting.

[0779] Business trip arrangements:

[0780] When a user plans a business trip, the server uses emotion recognition results to suggest comfortable modes of transportation and accommodations. Even when long-distance travel is involved, arrangements are made with the user's comfort as a top priority.

[0781] Email correspondence:

[0782] When users process emails, the server advises them to avoid difficult replies depending on their emotions, or, if it determines they are in a calm state, encourages them to prioritize replying to higher-priority emails.

[0783] In this way, this system, which incorporates an emotion engine, aims to improve the quality of work by taking into account the user's emotional state. As a result, improvements in employee satisfaction and productivity are expected.

[0784] The following describes the processing flow.

[0785] Step 1:

[0786] When a user logs into a terminal, the server verifies the user's authentication information and retrieves profile data from the database based on the results. This profile contains various data related to the user's work.

[0787] Step 2:

[0788] The server activates the emotion engine from the terminal and collects user emotion data in real time. The emotion engine identifies the user's emotional state by analyzing facial recognition, voice tone, and user input speed.

[0789] Step 3:

[0790] Based on the acquired emotional data, the server re-evaluates the prioritization of the user's daily tasks. Specifically, if data indicating stress is detected, the server prioritizes simpler tasks or adjusts the work plan to reduce stress.

[0791] Step 4:

[0792] The system notifies the user of an optimized schedule via the device. For example, if emotional data indicates fatigue, the server suggests a set amount of rest time and presents that schedule to the user.

[0793] Step 5:

[0794] The server uses emotional data to support meeting preparation. If a user is feeling nervous, it automatically generates materials and relaxation techniques to alleviate the tension and delivers them to the user via their device.

[0795] Step 6:

[0796] When preparing for a business trip, the user enters their travel information into their device. Based on emotional data, the server automatically arranges transportation and accommodations that prioritize comfort, and notifies the user of the details.

[0797] Step 7:

[0798] In analyzing incoming emails, the server utilizes an emotion engine to understand the user's emotional state and adjust the priority of suggested replies accordingly. For example, if the user is relaxed, the email might include a message urging them to respond quickly to important emails.

[0799] Through this series of processes, a system that incorporates emotion recognition capabilities takes into account the user's emotional state and provides support aimed at improving work efficiency and reducing mental burden.

[0800] (Example 2)

[0801] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0802] In today's work environment, there is a growing need for work support systems that take employees' emotional states into consideration. Traditional systems do not take emotions into account, resulting in insufficient task management and reduced mental burden. Solving this problem is essential.

[0803] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0804] In this invention, the server includes means for acquiring user identification information, means for adjusting task priorities according to the user's emotional state using a generative AI model, and means for supporting document creation and meeting preparation according to the user's emotional state. This enables efficient task management and stress reduction that takes into account the user's emotional state.

[0805] "User identification information" refers to attribute information necessary to identify a user. This information includes user ID, authentication information, job data, etc.

[0806] A "generative AI model" refers to an artificial intelligence program that uses machine learning techniques to analyze data patterns and make predictions and suggestions. This model plays a role in adjusting task priorities based on the user's work status.

[0807] "Emotional state" refers to data that indicates the user's mental or emotional condition. This data is obtained by analyzing voice, facial expressions, vital signs, etc.

[0808] "Adjusting task priorities" refers to the process of rearranging the order and importance of a user's work tasks based on their emotional state. This adjustment is done to improve the user's efficiency.

[0809] "Supporting document creation and meeting preparation" refers to providing support to help users prepare necessary documents and arrange meetings to ensure their work proceeds smoothly.

[0810] This system is an advanced business support system designed to improve work efficiency based on the user's emotional state. It primarily operates by combining a server, terminals, and an emotion engine.

[0811] First, when a user accesses the system via a terminal, the server obtains the user's identification information. The terminal has a built-in emotion engine that analyzes the user's emotional state using speech recognition software and image processing technology. Information obtained from voice data and facial expressions is important for determining the user's real-time mental state.

[0812] Next, the server uses a generative AI model to adjust task priorities based on the user's emotional state. The generative AI model suggests the most appropriate task assignments based on the user's past work data and current emotional state. This model enables more accurate task prioritization by explicitly indicating what decisions are needed from the AI ​​through prompt statements. For example, the instruction "Suggest the best task assignment for a user who is stressed" plays a crucial role here.

[0813] Within this system, the server also optimizes the schedule based on the user's emotional state. To this end, the server may add short breaks to the schedule or recommend music to enhance concentration while working.

[0814] Furthermore, if a user has a meeting or business trip scheduled, the server automatically suggests and prepares necessary materials, optimal transportation, and accommodation based on sentiment analysis. This reduces the burden on users in preparing for work and arranging business trips.

[0815] Ultimately, in email processing, the server considers the user's emotional state to generate the most appropriate reply and suggests email responses based on their importance. This entire process can reduce employee stress and improve work efficiency.

[0816] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0817] Step 1:

[0818] When a user logs into the system via a terminal, the server receives the user's identification information as input data. This authenticates the user. If authentication is successful, the server retrieves the user's job information, work history, and schedule data from the database as output.

[0819] Step 2:

[0820] An emotion engine built into the device monitors the user's emotional state in real time. Input data includes the user's voice, facial expressions, and biometric information from wearable devices. Based on this data, the device applies an emotion analysis algorithm to identify the user's current emotion. This identified emotional state is then sent to the server as output.

[0821] Step 3:

[0822] The server inputs the user's identification information and emotional state received from the emotion engine into a generative AI model. The generative AI model learns from past data and uses the prompt "Suggestion for optimal task placement for a user in a stressed state" to output the optimal task priority for the user. Based on this output, the server optimizes the task schedule.

[0823] Step 4:

[0824] The server adjusts the work schedule based on the user's emotional state. Input data includes information about the user's fatigue level and concentration level. The server provides output such as suggesting short breaks or recommending relaxing music. The terminal receives this information and notifies the user.

[0825] Step 5:

[0826] When users plan meetings or business trips, the server uses the entered schedule information and sentiment data to suggest suitable modes of transportation and accommodations. This suggestion also assists with booking procedures, ensuring users enjoy a convenient and hassle-free experience.

[0827] Step 6:

[0828] In processing emails, the server receives emails opened by users as input data. After analyzing the email content along with the emotional state, it outputs suggested replies. High-priority emails prompt for a quick response, while emails requiring a more complex reply receive warnings tailored to the emotional state of the user.

[0829] (Application Example 2)

[0830] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0831] In modern homes and workplaces, individual users face diverse emotional states and workloads, requiring efficient support tailored to their individual needs. Ideally, within the home, the living environment and conversation content should be adjusted to the user's emotions, but a suitable system for this is lacking. In this context, technology that recognizes emotions and supports work and daily life is essential.

[0832] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0833] In this invention, the server includes means for acquiring user information, means for extracting and analyzing tasks based on the acquired user information, and means for optimizing the schedule based on the analysis results. This makes it possible to optimize the user's work and home activities according to their emotional state.

[0834] "User information" is a general term for the data that a system collects to identify a user and understand their work history and emotional state.

[0835] "Emotional state" refers to the user's psychological state at that moment, analyzed based on their facial expressions, tone of voice, and other vital signs.

[0836] A "task" refers to an individual task or activity that a user must perform in their daily life or work.

[0837] "Optimizing the schedule" refers to efficiently rearranging the day's activities based on the user's emotional state and work priorities.

[0838] "Automation" refers to a process in which existing procedures are performed automatically rather than manually, through the intervention of a system.

[0839] "Adjusting the home environment" refers to robots and devices appropriately controlling lighting, music, conversations, and other elements within the home according to the user's emotional state.

[0840] "Recognizing emotions" refers to the technical process by which a system analyzes psychological characteristics derived from user input information to identify the user's current emotions.

[0841] This invention is a system that recognizes a user's emotional state in real time and provides support tailored to their individual circumstances. This system primarily consists of a server, a terminal, and an emotion recognition engine.

[0842] The server first acquires user information, and then extracts and analyzes tasks based on that information. This is achieved using hardware (such as sensors like cameras and microphones) that collects the user's work history and emotional state data. The emotion recognition engine processes the data acquired by these sensors and identifies the emotional state from facial expressions and tone of voice.

[0843] Furthermore, the device automatically prioritizes tasks and optimizes the schedule based on emotion recognition. By utilizing a generative AI model, it can suggest simple tasks if the user is feeling stressed. In addition, a smart home appliance control system is used to adjust the environment within the home. For example, if it determines that relaxation is needed, the music playback device will play calming music and the lighting will be adjusted to a softer tone.

[0844] For example, if a user returns home from work and the system recognizes their fatigue level, it can automatically create a relaxing environment. If the weather is good, it could adjust the humidity to a suitable level and activate a device that emits a relaxing scent. Another example of a prompt message would be, "Generate instructions to create a relaxing lighting and music environment for the user."

[0845] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0846] Step 1:

[0847] The server retrieves the user's profile data and work history. This data includes past task history, schedules, and vital sign information from wearable devices. Based on the entered data, a database is updated to predict the user's current emotional state.

[0848] Step 2:

[0849] The device uses an emotion recognition engine to analyze the user's emotional state in real time. Voice tone and facial expression data are sent to the device as input, which is then analyzed to identify the user's emotions. The analysis result outputs the emotional state (e.g., stress, relaxation).

[0850] Step 3:

[0851] The server re-evaluates task priorities using a generative AI model based on emotional state data. The server receives emotional state data as input, analyzes the current task list based on this data, and resets priorities. The optimized list is then displayed to the user as output.

[0852] Step 4:

[0853] To adjust the home environment that users use on a daily basis, the device operates devices via a smart home appliance control system. For example, if the entered emotional state is "fatigue," it will activate a music playback device and play relaxing music. It will also output specific instructions to adjust the lighting.

[0854] Step 5:

[0855] The server adapts pre-configured prompts and suggests optimal activities for the user through a generating AI model. For example, it might generate prompts and output instructions to adjust lighting and music settings to help the user relax. The outputted instructions are then displayed to the user and executed.

[0856] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0857] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0858] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0859] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0860] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0861] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0862] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0863] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0864] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0865] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0866] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0867] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0868] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0869] 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.

[0870] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0871] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0872] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0873] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0874] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0875] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0876] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0877] The following is further disclosed regarding the embodiments described above.

[0878] (Claim 1)

[0879] Means of obtaining user information,

[0880] A method for extracting and analyzing tasks based on acquired user information,

[0881] A means of optimizing the schedule based on the analysis results,

[0882] A means to automate tasks and assist with document creation and meeting scheduling,

[0883] A means of automatically arranging transportation and accommodation,

[0884] A means of analyzing emails and generating response suggestions,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, comprising means for learning data related to the user's work and improving the accuracy of support.

[0888] (Claim 3)

[0889] The system according to claim 1, comprising means for proposing an optimal business trip plan based on business trip information entered by the user.

[0890] "Example 1"

[0891] (Claim 1)

[0892] A device for acquiring user information,

[0893] A device that extracts and analyzes business activities based on acquired user information,

[0894] A device that optimizes the timetable based on the analysis results,

[0895] A device that automates business activities and assists with information organization and meeting arrangements,

[0896] A device that automatically arranges transportation and accommodation,

[0897] A device that analyzes electronic communications and generates a response,

[0898] A device that generates customized business plans using generative AI technology,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, comprising a device that learns information related to the user's job duties and improves the accuracy of the support.

[0902] (Claim 3)

[0903] The system according to claim 1, comprising a device that suggests an optimal business travel plan based on travel information entered by the user.

[0904] "Application Example 1"

[0905] (Claim 1)

[0906] Means of obtaining user information,

[0907] A method for extracting and analyzing tasks based on acquired user information,

[0908] A means of optimizing the schedule based on the analysis results,

[0909] A means to automate tasks and support information creation and placement settings,

[0910] A means of automatically arranging transportation and accommodation,

[0911] A means for analyzing electronic documents and generating a draft reply,

[0912] A means of reading user transaction records and analyzing business history,

[0913] A method for dynamically generating and optimizing trading plans using a generative AI model,

[0914] A system that includes this.

[0915] (Claim 2)

[0916] The system according to claim 1, comprising means for learning information related to user activity and improving the accuracy of the support function.

[0917] (Claim 3)

[0918] The system according to claim 1, comprising means for proposing an optimal business activity plan based on business information entered by the user.

[0919] "Example 2 of combining an emotion engine"

[0920] (Claim 1)

[0921] Means for obtaining user identification information,

[0922] A means of organizing and analyzing business processes based on acquired user identification information and emotional state,

[0923] A means of adjusting the priority of tasks according to emotional state using a generative AI model,

[0924] A means to optimize work schedules based on analysis results,

[0925] A means to support document creation and meeting preparation according to the user's emotional state,

[0926] A method for automatically suggesting transportation and accommodation based on sentiment analysis,

[0927] A means for analyzing electronic communications and generating reply content,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, comprising means for learning the user's emotional state and work-related information, and improving the accuracy of the support provided.

[0931] (Claim 3)

[0932] The system according to claim 1, comprising means for proposing an optimal travel plan based on travel information entered by the user.

[0933] "Application example 2 when combining with an emotional engine"

[0934] (Claim 1)

[0935] Means of obtaining user information,

[0936] A method for extracting and analyzing tasks based on acquired user information,

[0937] A means of optimizing the schedule based on the analysis results,

[0938] A means to automate tasks and assist with document creation and meeting scheduling,

[0939] A means of automatically arranging transportation and accommodation,

[0940] A means of analyzing emails and generating response suggestions,

[0941] A means of recognizing the user's emotions and adjusting the home environment and providing conversational support according to their emotional state,

[0942] A system that includes this.

[0943] (Claim 2)

[0944] A means to learn from user business data and improve the accuracy of support,

[0945] The system according to claim 1, comprising means for selecting optimal music based on the user's emotions and for performing household operations based on those emotions.

[0946] (Claim 3)

[0947] A means of proposing the optimal business trip plan based on the business trip information entered by the user,

[0948] The system according to claim 1, comprising means for suggesting daily life activities in response to emotions. [Explanation of Symbols]

[0949] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of obtaining user information, A method for extracting and analyzing tasks based on acquired user information, A means of optimizing the schedule based on the analysis results, A means to automate tasks and support information creation and placement settings, A means of automatically arranging transportation and accommodation, A means for analyzing electronic documents and generating a draft reply, A means of reading user transaction records and analyzing business history, A method for dynamically generating and optimizing trading plans using a generative AI model, A system that includes this.

2. The system according to claim 1, comprising means for learning information related to user activity and improving the accuracy of the support function.

3. The system according to claim 1, comprising means for proposing an optimal business activity plan based on business information entered by the user.

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