system

Abstract

We provide the system. [Solution] A means of providing personalized schedule management, A means to automatically perform individualized meeting preparation, Methods for efficiently arranging business trips, A system that includes this.

Description

【Technical Field】 【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 steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In a modern corporate environment, improving individual productivity is an important theme. However, general employees who are overwhelmed by their busy daily work have a problem that they cannot fully concentrate on their original work. Specifically, routine tasks such as schedule management, meeting preparation, and business trip arrangements put pressure on time, and as a result, efficient business performance is hindered, which is the problem. 【Means for Solving the Problems】 【0005】 To solve this problem, the present invention proposes a system including an information processing device that provides individualized schedule management, automation of meeting preparation, and efficient business trip arrangements. In addition, by using a generative AI model to optimize tasks and automate individual routine tasks based on user data, the burden on employees is reduced, and efficient business performance is supported. 【0006】 "Personalized schedule management" refers to a method of adjusting and managing schedules according to each user's needs and circumstances. 【0007】 "Meeting preparation automation" refers to the process of automatically collecting and creating the necessary materials and information for a meeting. 【0008】 "Arranging business trips" refers to the process of efficiently securing transportation and accommodation for business trips as needed. 【0009】 An "information processing device" is a device that receives data, processes it, and provides useful information to the user. 【0010】 A "generative AI model" is an artificial intelligence-based algorithm that generates optimal suggestions or solutions based on data. 【0011】 Task optimization is the process of adjusting the priorities and assignments of tasks to maximize the efficiency of resources and time. 【0012】 "Automation of routine tasks" is a technology that improves efficiency by automatically executing standard business processes that are frequently repeated. 【0013】 "User data" refers to information about a user that the system uses to provide personalized services. [Brief explanation of the drawing] 【0014】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This 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 an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Embodiments for Carrying Out the Invention】 【0015】 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. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, 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), and APU (Accelerated Processing Unit). 【0018】 In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor. 【0019】 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. 【0020】 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). 【0021】 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." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 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. 【0025】 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). 【0026】 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. 【0027】 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. 【0028】 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. 【0029】 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. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 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. 【0032】 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. 【0033】 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. 【0034】 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". 【0035】 This invention is an information processing system that provides personalized support using a generative AI model. The system mainly consists of a user terminal, an information processing server, and a generative AI model. The user inputs information related to their daily work into the terminal, and this information is collected and stored on the server. 【0036】 User actions 【0037】 Users interact with the system through a dedicated application by entering information about their schedules and tasks into their terminals. This information is used to plan and execute automated tasks, allowing users to focus on their core responsibilities. 【0038】 Device functions 【0039】 The terminal collects information from the user and sends it to the server. Furthermore, it displays optimized task suggestions and notifications returned from the server and the generated AI model to the user. This allows the user to work more efficiently. 【0040】 Server Processing 【0041】 The server functions as the primary information processing unit, managing user data, communicating with the generative AI model, and storing information. The server sends data to the generative AI model and receives suggestions for task management, meeting preparation, and travel arrangements. 【0042】 Generative AI Models 【0043】 The generative AI model analyzes user data and returns optimized task suggestions to the server. These suggestions include schedule optimization and task prioritization, designed to help users utilize their time efficiently. 【0044】 Specific example 【0045】 For example, if a user requests, "Please check next week's meeting schedule and help me prepare," the server sends this request to a generative AI model. The generative AI model analyzes the user's schedule and meeting content and automatically generates the necessary materials and agenda for the meeting. The terminal displays this information to the user, and the meeting preparation is completed once the user confirms and approves it. This entire process allows the user to work efficiently. 【0046】 Thus, this system aims to improve users' work efficiency by providing automated support, primarily in scheduling, meeting preparation, and travel arrangements. 【0047】 The following describes the processing flow. 【0048】 Step 1: 【0049】 The user enters information about their schedule and tasks into the terminal. The terminal then formats this information and prepares it for transmission to the server. 【0050】 Step 2: 【0051】 The terminal sends data received from the user to the server. The server receives the data and stores it in a database for each user. 【0052】 Step 3: 【0053】 The server analyzes the stored user data and prepares to send the data to the generated AI model as needed. 【0054】 Step 4: 【0055】 The server requests the generative AI model to optimize schedules and prioritize tasks. The generative AI model analyzes these tasks and creates personalized suggestions optimized for each user. 【0056】 Step 5: 【0057】 The generative AI model returns the task suggestions it has created to the server. The server receives these suggestions and reformats them to suit the user's needs. 【0058】 Step 6: 【0059】 The server sends optimized task suggestions to the terminal. The terminal notifies the user of this information and displays it for the user to review. 【0060】 Step 7: 【0061】 Users review the proposed schedules and tasks on their devices and approve or modify them as needed. This ensures that the user's decisions are reflected in the system. 【0062】 Step 8: 【0063】 Based on the schedule and tasks approved by the user, the server initiates the necessary processes for automatically generating meeting invitation emails and arranging travel arrangements. The data is processed, and the user is notified of the final confirmation. 【0064】 (Example 1) 【0065】 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." 【0066】 In today's work environment, users spend considerable time and effort managing a wide range of schedules, coordinating tasks, preparing for meetings, and arranging business trips. These tasks significantly reduce productivity and prevent users from focusing on their core responsibilities. To address these issues and improve user efficiency, a means of automating these tasks and efficiently providing optimized solutions is necessary. 【0067】 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. 【0068】 In this invention, the server includes means for collecting user input information, means for transmitting this information to a generating artificial intelligence model for analysis, and means for generating and displaying optimized schedules and task suggestions based on the analysis results. This enables the automation of schedule and task management, allowing users to concentrate on important tasks. 【0069】 "User input information" refers to information related to daily tasks, such as schedules, tasks, and notes, that users provide to the system using their terminals. 【0070】 A "terminal" is a device used by users to input information and to receive suggestions and notifications from servers and generated AI models. 【0071】 A "server" is an information processing unit that aggregates information from users, communicates with the generated artificial intelligence model, and returns analysis results to the user as needed. 【0072】 A "generative artificial intelligence model" is a set of algorithms and computational methods that analyze user data to generate optimized schedules and task suggestions. 【0073】 "Optimization suggestions" are proposals for schedules and task plans designed to streamline the user's work management, generated based on the results of analysis by a generative artificial intelligence model. 【0074】 This invention is an efficient business support system using a generative AI model. The system is implemented in a form in which the user utilizes terminals, servers, and generative artificial intelligence models in conjunction to efficiently perform their tasks. 【0075】 Users input information such as schedules, tasks, meetings, and business trips using the terminal. The terminal has the function to transfer this input information to a server via the network. The user interface is designed to be user-friendly and intuitive for the user inputting the information. 【0076】 The server securely records the received user information in a database. The server then sends a prompt message containing the user information to the generative artificial intelligence model. For example, a prompt message such as "Please check the meeting schedule for next week and help me prepare" from the user is generated and passed to the generative artificial intelligence model. 【0077】 The generative artificial intelligence model analyzes received prompt messages and optimizes tasks based on user information. For example, it automatically generates materials and agenda items to be used in next week's meeting and creates a schedule proposal. Machine learning algorithms are used for internal calculations, enabling sophisticated suggestions based on work content and historical data. 【0078】 The server returns the generated business proposals to the terminal, making them visible to the user. The terminal notifies the user of the proposed schedule and tasks, and requests confirmation and approval. For example, the terminal displays information necessary for the user, such as, "Here are the materials needed for next week's meeting." 【0079】 Through this system, users can enjoy increased efficiency through automation, allowing them to focus on other important tasks. An example of a prompt message would be a request such as, "Please prepare the necessary materials for the next meeting," to which the system would respond promptly. 【0080】 Thus, this invention aims to improve the user's work efficiency by providing automated support, primarily for schedule management, meeting preparation, and travel arrangements. 【0081】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0082】 Step 1: 【0083】 Users input information about their schedules and tasks through a terminal. This input includes the date, time, location, and details of the task. The terminal saves this information to a local database, preparing it for subsequent processing. 【0084】 Step 2: 【0085】 The terminal transfers the entered information to the server. During this process, the terminal uses a secure communication protocol to ensure the safe transmission of user data. The server temporarily stores the received information in preparation for the processing step. 【0086】 Step 3: 【0087】 The server generates an appropriate prompt based on the received user data. The prompt specifies a concrete task and prepares it for transmission to the AI ​​model. For example, it might generate a message such as, "Please prepare the materials needed for next week's meeting." 【0088】 Step 4: 【0089】 The server sends the generated prompt text to the generative artificial intelligence model. The generative AI model analyzes user data based on the prompt text and optimizes schedules and tasks. Specifically, it uses machine learning algorithms to analyze past data and generate optimal meeting materials and task suggestions. 【0090】 Step 5: 【0091】 The generative AI model returns the analysis results to the server. The server receives these results and formats the data into a format usable by the user. The formatted results include optimized schedule and task suggestions. 【0092】 Step 6: 【0093】 The server sends the formatted data to the terminal. The terminal displays the received data to the user, providing information that can be used in specific tasks. For example, it might notify the user with a message like, "Here are the materials needed for next week's meeting," allowing the user to review and take action. 【0094】 (Application Example 1) 【0095】 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." 【0096】 The duties of store staff in physical stores are diverse, requiring them to efficiently handle tasks such as inventory management, sales strategies, and customer service. However, the heavy workload of these tasks can easily lead to a deterioration of the working environment for staff and a decline in the quality of customer service. Furthermore, the inability to make quick suggestions for improvement can result in missed sales opportunities. There is a need for solutions to these problems and improve the efficiency of store staff's work. 【0097】 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. 【0098】 In this invention, the server includes information processing means for providing individualized business management, information processing means for automatically improving the efficiency of store operations, and information processing means for supporting inventory management and sales strategies. This makes it possible to reduce the workload at physical stores and improve the quality of customer service. 【0099】 "Personalized task management" is an information processing technology that provides optimized task management methods tailored to each user and business environment. 【0100】 "Streamlining store operations" refers to information processing technology that enables various tasks in physical stores to be performed effectively with minimal time and resources. 【0101】 "Support for inventory management and sales strategies" refers to information processing technology that effectively supports inventory management and sales activity planning. 【0102】 A "generative AI model" is a computational model of artificial intelligence that generates appropriate suggestions and support based on input information. 【0103】 An "information processing device" refers to a system of hardware and software for receiving, processing, and providing data. 【0104】 The system for implementing this invention mainly consists of a server, a user terminal, and a generative AI model. The user uses the terminal to input information related to their daily work. This includes checking inventory status, customer interaction history, and product order information. The server receives this information and transmits the data to the generative AI model. 【0105】 The server functions as the primary information processing unit, managing user input data, communicating with the generative AI model, and storing information. The server also receives optimized business suggestions from the generative AI model and sends them to the user terminal. The specific hardware used by the server includes a database server and network interfaces, while the software used includes a generative AI model written in Python and a data management system. 【0106】 The generating AI model analyzes data sent from the server and optimizes business suggestions. For example, the model can propose sales strategies for each product based on inventory data and historical sales data, or generate optimal customer service methods. This allows users to carry out their daily tasks more efficiently. 【0107】 For example, if a user requests to "check the arrival status of new products for next week and develop a sales strategy," the server sends a request to the generating AI model. The model analyzes store inventory data and past sales data and proposes an optimized sales strategy for the new products. An example of a prompt to the generating AI model would be, "New products are scheduled to arrive next week. Please suggest a recommended sales strategy based on past data." This allows the user to refer to the suggestions and implement the most suitable sales strategy. 【0108】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0109】 Step 1: 【0110】 Users input work-related information using a terminal. This information includes inventory status, customer interaction history, and product order requests. This information is entered by the user through an application and sent to the server. 【0111】 Step 2: 【0112】 The server receives information from the user and stores it in the database. Here, the server verifies the integrity of the input data and stores the information in the appropriate table in the database. At this point, the data management system used by the server saves the input data. 【0113】 Step 3: 【0114】 The server sends the stored data to the generating AI model. Here, the server prepares the necessary input data, including prompts, and converts it into a format that the generating AI model can parse. Through this process, the server optimizes the input to the AI ​​model. 【0115】 Step 4: 【0116】 The generation AI model analyzes data sent from the server and generates business proposals. The AI ​​model uses the received data to execute a process that generates optimized proposals regarding inventory management and sales strategies. 【0117】 Step 5: 【0118】 After the AI ​​model generates proposals, the server receives these proposals and sends them to the user's terminal. Since the proposals include specific sales strategies and inventory management methods, the server provides them in a format that is easy for the user to understand. 【0119】 Step 6: 【0120】 The user reviews the proposed solutions via their device and proceeds with the necessary implementation procedures. At this stage, the user can make business decisions based on the AI ​​model's suggestions. 【0121】 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. 【0122】 This invention is an information processing system that streamlines users' daily tasks and provides optimized support tailored to their individual emotional states. The system consists of a user terminal, an information processing server, a generative AI model, and an emotion engine. 【0123】 User actions 【0124】 Users input schedules and tasks through their devices, and also provide emotional data using cameras and sensors. The devices collect this input information and emotional data and send it to a server for processing. 【0125】 Device functions 【0126】 The device transfers user-provided data and emotional data to the server. It also displays schedule suggestions and task adjustment information sent from the server and generative AI models, helping users maximize their work efficiency. 【0127】 Server Processing 【0128】 The server centrally manages user data and emotional data and requests analysis from a generative AI model. Based on the results received from the generative AI, the server adjusts the priority and content of tasks. At this time, the emotional engine is used to construct schedules and tasks that take the user's emotional state into consideration. 【0129】 Generative AI Models 【0130】 The generative AI model analyzes user data to suggest optimal schedules and tasks. The emotion engine tracks changes in the user's emotions and provides information to appropriately adjust task content and priorities. 【0131】 Specific example 【0132】 For example, if the system determines that a user is in a stressful situation, the emotion engine works with a generative AI model to suggest rescheduling less important meetings or reducing the number of tasks per day. On the other hand, if the user is relaxed, the system can suggest assigning them more tasks than usual. 【0133】 This system aims to further improve operational efficiency by incorporating an emotion engine, enabling flexible responses that respond to users' emotions. 【0134】 The following describes the processing flow. 【0135】 Step 1: 【0136】 The user uses the device to input schedule and task information and activates a camera or sensor to collect emotional data. This allows the necessary data to be collected. 【0137】 Step 2: 【0138】 The device sends information entered by the user and data acquired from the emotion sensor to the server. This data reflects the user's current state. 【0139】 Step 3: 【0140】 The server analyzes the received data to understand the user's current tasks and schedule status. The server then passes the analyzed data to a generating AI model and requests an optimal task management plan. 【0141】 Step 4: 【0142】 The generative AI model generates optimal schedules and task suggestions for the user based on user data and emotion data. An emotion engine is used here to make adjustments that take into account the user's emotional state. 【0143】 Step 5: 【0144】 The server receives suggestions from the generated AI model, formats them into task proposals and schedules optimized for emotions, and sends them to the terminal. 【0145】 Step 6: 【0146】 The terminal displays the proposal sent from the server to the user. The user can review this proposal and approve or modify it as needed. 【0147】 Step 7: 【0148】 User-approved schedules and task adjustments are fed back to the server, and the final state is reflected before execution. If further feedback is needed, the process is repeated for adjustments. 【0149】 Step 8: 【0150】 The emotion engine continuously monitors the user's emotional state and, as needed, feeds data back to the server and generative AI models, enabling optimal task adjustments in real time. 【0151】 (Example 2) 【0152】 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." 【0153】 In today's work environment, scheduling and task adjustments that ignore users' emotional states are a factor that reduces work efficiency. Furthermore, conventional information processing systems have difficulty providing individualized work plans based on emotional data, which presents a challenge in maximizing user performance. 【0154】 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. 【0155】 In this invention, the server includes means for generating a work plan according to the user's emotional state, means for transmitting collected emotional data, means for optimizing the schedule using a generation AI model, and means for adjusting task priorities based on the emotional data. This makes it possible to provide a flexible work plan that takes the user's emotional state into consideration. 【0156】 "User emotional state" refers to information that indicates the emotions and psychological state a user is experiencing at a specific point in time. 【0157】 "Means for generating business plans" refers to devices or software that have the function of structuring a user's schedule and tasks in a way that allows them to be executed efficiently. 【0158】 "Means for transmitting emotional data" refers to a device or software equipped with communication functions for sending data related to a user's emotional state to a processing unit or external device. 【0159】 "Means of optimizing schedules using generative AI models" refers to devices or software that utilize artificial intelligence to adjust a user's schedule to the optimal form. 【0160】 "Means for adjusting task priorities based on emotional data" refers to a device or software that has the function of dynamically changing the execution order and importance of tasks, taking into account the user's emotional state. 【0161】 This invention is an information processing system that streamlines users' daily tasks and provides optimized support according to the user's emotional state. The system consists of a terminal, an information processing server, a generative AI model, and an emotion engine. 【0162】 Users input schedules and tasks through their devices. Sentimental data is collected using cameras and sensors. The device then organizes the collected schedule information, task information, and sentimental data and sends it to a server. For this process, devices such as smartphones and tablets are used. 【0163】 The server centrally manages user data received from terminals and requests analysis from a generative AI model using prompt messages. An example of a prompt message is, "Considering the user's current stress level, please suggest the optimal schedule for tomorrow." The generative AI model utilizes, for example, machine learning algorithms and artificial intelligence platforms to generate schedule and task suggestions that are optimal for the user's emotional state. 【0164】 The server further refines the schedules and task suggestions received from the generated AI model and sends them to the terminal. The terminal then presents these to the user, providing an optimal work plan. In this process, the emotion engine plays a role in dynamically adjusting the priority and content of tasks based on the user's emotional data. 【0165】 For example, if a user is determined to be experiencing a high level of stress, the system will suggest rescheduling meetings or adjusting the number of tasks. In this way, the system optimizes work processes while taking into account the user's emotional state. 【0166】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0167】 Step 1: 【0168】 The device collects schedule and task information entered by the user, as well as emotional data obtained through the camera and sensors. Inputs include meeting appointments entered by the user in their calendar app and heart rate recorded by sensors. This information is organized into a digital format and prepared for further processing. 【0169】 Step 2: 【0170】 The device sends organized schedule and task information, as well as sentiment data, to the server. The input is a digital data package. Specifically, the device transmits data over the internet using the HTTPS protocol. The output is a data packet that reaches a specific endpoint on the server. 【0171】 Step 3: 【0172】 The server stores the received data in a database and generates prompt messages for the generating AI model. The input is the entire user data received from the terminal. The server uses this to generate prompt messages such as "Suggest a schedule for the next day that reflects the user's stress level" and sends them to the generating AI model. 【0173】 Step 4: 【0174】 The generative AI model generates optimal schedule and task suggestions based on prompt messages and user data received from the server. The input consists of prompt messages and user data, and data analysis is performed using natural language processing and machine learning algorithms. The output is a schedule proposal that takes the user's emotional state into consideration. 【0175】 Step 5: 【0176】 The server further refines the suggestions received from the generating AI model and prepares them to be sent to the user's terminal in the most optimal form. The input is the schedule suggestion from the generating AI model. Adjustments are made to this, taking into account the user's actual schedule and the importance of the tasks, and the final schedule information is obtained as output. 【0177】 Step 6: 【0178】 The terminal displays the user the adjusted schedule and task information sent from the server. The input is communication data from the server, which the terminal converts into a user-friendly format and displays on the screen. The output is a notification, such as "The 2 PM meeting has been rescheduled to next week." 【0179】 (Application Example 2) 【0180】 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". 【0181】 Traditional scheduling management systems struggle to respond flexibly to users' emotional states and cannot provide an environment optimized for individual emotions and situations. Furthermore, there is a lack of a consistent platform that can handle stress management and environmental adjustments during travel. 【0182】 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. 【0183】 In this invention, the server includes information processing means for providing individualized time management, information processing means for automatically performing individualized meeting preparations, information processing means for efficiently planning travel, and control means for dynamically adjusting the environment based on emotional state. This enables flexible schedule management and environmental adjustments during travel in accordance with the user's emotional state. 【0184】 "Personalized time management" is the process of adjusting schedules according to each user's specific needs and circumstances to provide an efficient timetable. 【0185】 "Personalized meeting preparation" is a feature that automatically organizes the necessary information and materials according to each user's role and objectives. 【0186】 "Travel planning" is a procedure that takes into account the user's destination and circumstances to propose the optimal travel route and means of transportation. 【0187】 "Dynamic environment adjustment based on emotional state" refers to operations that sense the user's emotions and psychological state in real time and appropriately change the physical or digital environment accordingly. 【0188】 "Information processing means" refers to devices and methods for collecting, analyzing, and managing data. 【0189】 A "control mechanism" is a system that manages and adjusts various settings and behaviors of a system under specific conditions. 【0190】 In implementing this invention, a server plays a central role. The server is equipped with multiple information processing and control means for personalized time management, meeting preparation, travel planning, and environmental adjustment based on emotional state. Specifically, the server is preferably set up in a cloud computing environment where a generative AI model operates, analyzing user data to propose optimal tasks and schedules. 【0191】 The terminals play a role in transmitting user data and emotional information to the server. These terminals include smartphones and in-vehicle devices. These terminals are equipped with cameras and sensors, and facial recognition technology using tools such as OpenCV is utilized to sense the user's emotional state. This information is analyzed by an AI model built with TENSORFLOW®. 【0192】 As a concrete example, if the device detects the user's face and recognizes an expression indicating fatigue, the server analyzes the user's calendar and work schedule. Based on this, it can automatically postpone meetings or change the travel route to suggest a quieter alternative. It can also adjust entertainment options, such as music playback, using APIs like Spotify. 【0193】 An example of a prompt might be: "Generate guidelines for developing a system that optimizes the in-car environment based on emotional state. Include entertainment and navigation systems that adapt to the driver's stress and relaxation levels." Based on this prompt, the server's AI model can propose the optimal strategy. 【0194】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0195】 Step 1: 【0196】 The user activates the camera and sensors through the device and inputs emotional data and schedule information. 【0197】 Input: User's face image, schedule data 【0198】 Output: Processing data packets 【0199】 Specifically, the device uses its camera to capture the user's face and extracts facial expression information from the image using OpenCV. Simultaneously, it also collects schedule data entered by the user. 【0200】 Step 2: 【0201】 The device packages the collected emotional data and schedule information and sends it to the server. 【0202】 Input: Processing data packet 【0203】 Output: Sent data 【0204】 The device encodes this data over the internet and securely transmits it to the server. 【0205】 Step 3: 【0206】 The server analyzes the received data and supplies it to the generated AI model. 【0207】 Input: Submitted data 【0208】 Output: Input data for the AI ​​model 【0209】 Specifically, the server decodes the data packets and inputs the user's emotional state into an AI model built with TensorFlow. 【0210】 Step 4: 【0211】 The generative AI model proposes the optimal schedule and tasks based on the received data. 【0212】 Input: Input data for the AI ​​model 【0213】 Output: Schedule optimization proposal 【0214】 The model takes the user's emotional state into account, re-evaluates priorities, and generates the most suitable task management plan. 【0215】 Step 5: 【0216】 The server generates movement plans and environmental adjustment instructions based on the analysis results from the AI ​​model and sends them to the terminal. 【0217】 Input: Schedule optimization proposal 【0218】 Output: Instructions for environmental adjustments and travel planning. 【0219】 The server uses Google® Maps API and entertainment APIs to create route and music playback plans in response to user requests and sends those instructions back to the device. 【0220】 Step 6: 【0221】 The terminal displays instructions received from the server to the user and performs the necessary adjustments. 【0222】 Input: Instructions for environmental adjustments and travel planning. 【0223】 Output: Adjusted schedule and in-car environment 【0224】 Based on the information it receives, the device displays suggestions to the user as visual information and performs actions such as music playback and route changes. 【0225】 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. 【0226】 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. 【0227】 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. 【0228】 [Second Embodiment] 【0229】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0230】 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. 【0231】 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). 【0232】 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. 【0233】 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. 【0234】 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). 【0235】 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. 【0236】 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. 【0237】 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. 【0238】 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. 【0239】 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. 【0240】 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". 【0241】 This invention is an information processing system that provides personalized support using a generative AI model. The system mainly consists of a user terminal, an information processing server, and a generative AI model. The user inputs information related to their daily work into the terminal, and this information is collected and stored on the server. 【0242】 User actions 【0243】 Users interact with the system through a dedicated application by entering information about their schedules and tasks into their terminals. This information is used to plan and execute automated tasks, allowing users to focus on their core responsibilities. 【0244】 Device functions 【0245】 The terminal collects information from the user and sends it to the server. Furthermore, it displays optimized task suggestions and notifications returned from the server and the generated AI model to the user. This allows the user to work more efficiently. 【0246】 Server Processing 【0247】 The server functions as the primary information processing unit, managing user data, communicating with the generative AI model, and storing information. The server sends data to the generative AI model and receives suggestions for task management, meeting preparation, and travel arrangements. 【0248】 Generative AI Models 【0249】 The generative AI model analyzes user data and returns optimized task suggestions to the server. These suggestions include schedule optimization and task prioritization, designed to help users utilize their time efficiently. 【0250】 Specific example 【0251】 For example, if a user requests, "Please check next week's meeting schedule and help me prepare," the server sends this request to a generative AI model. The generative AI model analyzes the user's schedule and meeting content and automatically generates the necessary materials and agenda for the meeting. The terminal displays this information to the user, and the meeting preparation is completed once the user confirms and approves it. This entire process allows the user to work efficiently. 【0252】 Thus, this system aims to improve users' work efficiency by providing automated support, primarily in scheduling, meeting preparation, and travel arrangements. 【0253】 The following describes the processing flow. 【0254】 Step 1: 【0255】 The user enters information about their schedule and tasks into the terminal. The terminal then formats this information and prepares it for transmission to the server. 【0256】 Step 2: 【0257】 The terminal sends data received from the user to the server. The server receives the data and stores it in a database for each user. 【0258】 Step 3: 【0259】 The server analyzes the stored user data and prepares to send the data to the generated AI model as needed. 【0260】 Step 4: 【0261】 The server requests the generative AI model to optimize schedules and prioritize tasks. The generative AI model analyzes these tasks and creates personalized suggestions optimized for each user. 【0262】 Step 5: 【0263】 The generative AI model returns the task suggestions it has created to the server. The server receives these suggestions and reformats them to suit the user's needs. 【0264】 Step 6: 【0265】 The server sends optimized task suggestions to the terminal. The terminal notifies the user of this information and displays it for the user to review. 【0266】 Step 7: 【0267】 Users review the proposed schedules and tasks on their devices and approve or modify them as needed. This ensures that the user's decisions are reflected in the system. 【0268】 Step 8: 【0269】 Based on the schedule and tasks approved by the user, the server initiates the necessary processes for automatically generating meeting invitation emails and arranging travel arrangements. The data is processed, and the user is notified of the final confirmation. 【0270】 (Example 1) 【0271】 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." 【0272】 In today's work environment, users spend considerable time and effort managing a wide range of schedules, coordinating tasks, preparing for meetings, and arranging business trips. These tasks significantly reduce productivity and prevent users from focusing on their core responsibilities. To address these issues and improve user efficiency, a means of automating these tasks and efficiently providing optimized solutions is necessary. 【0273】 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. 【0274】 In this invention, the server includes means for collecting user input information, means for transmitting this information to a generating artificial intelligence model for analysis, and means for generating and displaying optimized schedules and task suggestions based on the analysis results. This enables the automation of schedule and task management, allowing users to concentrate on important tasks. 【0275】 "User input information" refers to information related to daily tasks, such as schedules, tasks, and notes, that users provide to the system using their terminals. 【0276】 A "terminal" is a device used by users to input information and to receive suggestions and notifications from servers and generated AI models. 【0277】 A "server" is an information processing unit that aggregates information from users, communicates with the generated artificial intelligence model, and returns analysis results to the user as needed. 【0278】 A "generative artificial intelligence model" is a set of algorithms and computational methods that analyze user data to generate optimized schedules and task suggestions. 【0279】 "Optimization suggestions" are proposals for schedules and task plans designed to streamline the user's work management, generated based on the results of analysis by a generative artificial intelligence model. 【0280】 This invention is an efficient business support system using a generative AI model. The system is implemented in a form in which the user utilizes terminals, servers, and generative artificial intelligence models in conjunction to efficiently perform their tasks. 【0281】 Users input information such as schedules, tasks, meetings, and business trips using the terminal. The terminal has the function to transfer this input information to a server via the network. The user interface is designed to be user-friendly and intuitive for the user inputting the information. 【0282】 The server securely records the received user information in a database. The server then sends a prompt message containing the user information to the generative artificial intelligence model. For example, a prompt message such as "Please check the meeting schedule for next week and help me prepare" from the user is generated and passed to the generative artificial intelligence model. 【0283】 The artificial intelligence model analyzes the received prompt text and optimizes business operations based on user information. For example, it automatically generates materials and topics to be used in next week's meeting and creates schedule proposals. Machine learning algorithms are used for internal calculations, and advanced proposals based on business content and past data are made. 【0284】 The server returns the generated business proposals to the terminal and visualizes them for the user. The terminal notifies the user of the proposed schedule and tasks and requests confirmation and approval. As a specific example, necessary information for the user is displayed on the terminal in the form of "The materials required for next week's meeting are here". 【0285】 Through this system, users can enjoy the efficiency brought by business automation and can concentrate on other important tasks. As an example of a prompt text, a request such as "Please prepare the materials required for the next meeting" can be considered, and the system responds promptly to this. 【0286】 In this way, the present invention aims to provide automated support centered around schedule management, meeting preparation, business trip arrangements, etc., and improve the business efficiency of users. 【0287】 The flow of specific processing in Example 1 will be described using FIG. 11. 【0288】 Step 1: 【0289】 The user inputs information regarding the schedule and tasks through the terminal. The input information includes details of the date and time, location, and content. The terminal saves this information in the local database to prepare for subsequent processing. 【0290】 Step 2: 【0291】 The terminal transfers the entered information to the server. During this process, the terminal uses a secure communication protocol to ensure the safe transmission of user data. The server temporarily stores the received information in preparation for the processing step. 【0292】 Step 3: 【0293】 The server generates an appropriate prompt based on the received user data. The prompt specifies a concrete task and prepares it for transmission to the AI ​​model. For example, it might generate a message such as, "Please prepare the materials needed for next week's meeting." 【0294】 Step 4: 【0295】 The server sends the generated prompt text to the generative artificial intelligence model. The generative AI model analyzes user data based on the prompt text and optimizes schedules and tasks. Specifically, it uses machine learning algorithms to analyze past data and generate optimal meeting materials and task suggestions. 【0296】 Step 5: 【0297】 The generative AI model returns the analysis results to the server. The server receives these results and formats the data into a format usable by the user. The formatted results include optimized schedule and task suggestions. 【0298】 Step 6: 【0299】 The server sends the formatted data to the terminal. The terminal displays the received data to the user, providing information that can be used in specific tasks. For example, it might notify the user with a message like, "Here are the materials needed for next week's meeting," allowing the user to review and take action. 【0300】 (Application Example 1) 【0301】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal". 【0302】 The tasks of store employees in physical stores cover a wide range, and it is necessary to efficiently perform tasks such as inventory management, sales strategies, and customer service. However, due to these heavy workloads, the working environment of employees is likely to deteriorate, and the quality of customer service may decline. In addition, since rapid business proposals cannot be made, sales opportunities may be missed. There is a need for means to solve this problem and improve the work efficiency of employees. 【0303】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0304】 In this invention, the server includes information processing means for providing individualized business management, information processing means for automatically improving the efficiency of store operations, and information processing means for supporting inventory and sales strategies. This makes it possible to reduce the workload in physical stores and improve the quality of customer service. 【0305】 "Individualized business management" is an information processing technology that provides a management method for operations optimized according to each user and business environment. 【0306】 "Improving the efficiency of store operations" is an information processing technology that enables various tasks in physical stores to be effectively performed with minimal time and resources. 【0307】 "Supporting inventory and sales strategies" is an information processing technology that effectively supports inventory management of goods and planning of sales activities. 【0308】 "Generative AI model" is a computational model of artificial intelligence that generates appropriate proposals and support based on input information. 【0309】 "Information processing device" refers to a system of hardware and software for receiving, processing data, and providing results. 【0310】 The system for implementing this invention mainly consists of a server, a user terminal, and a generative AI model. The user uses the terminal to input information related to their daily work. This includes checking inventory status, customer interaction history, and product order information. The server receives this information and transmits the data to the generative AI model. 【0311】 The server functions as the primary information processing unit, managing user input data, communicating with the generative AI model, and storing information. The server also receives optimized business suggestions from the generative AI model and sends them to the user terminal. The specific hardware used by the server includes a database server and network interfaces, while the software used includes a generative AI model written in Python and a data management system. 【0312】 The generating AI model analyzes data sent from the server and optimizes business suggestions. For example, the model can propose sales strategies for each product based on inventory data and historical sales data, or generate optimal customer service methods. This allows users to carry out their daily tasks more efficiently. 【0313】 For example, if a user requests to "check the arrival status of new products for next week and develop a sales strategy," the server sends a request to the generating AI model. The model analyzes store inventory data and past sales data and proposes an optimized sales strategy for the new products. An example of a prompt to the generating AI model would be, "New products are scheduled to arrive next week. Please suggest a recommended sales strategy based on past data." This allows the user to refer to the suggestions and implement the most suitable sales strategy. 【0314】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0315】 Step 1: 【0316】 Users input work-related information using a terminal. This information includes inventory status, customer interaction history, and product order requests. This information is entered by the user through an application and sent to the server. 【0317】 Step 2: 【0318】 The server receives information from the user and stores it in the database. Here, the server verifies the integrity of the input data and stores the information in the appropriate table in the database. At this point, the data management system used by the server saves the input data. 【0319】 Step 3: 【0320】 The server sends the stored data to the generating AI model. Here, the server prepares the necessary input data, including prompts, and converts it into a format that the generating AI model can parse. Through this process, the server optimizes the input to the AI ​​model. 【0321】 Step 4: 【0322】 The generation AI model analyzes data sent from the server and generates business proposals. The AI ​​model uses the received data to execute a process that generates optimized proposals regarding inventory management and sales strategies. 【0323】 Step 5: 【0324】 After the AI ​​model generates proposals, the server receives these proposals and sends them to the user's terminal. Since the proposals include specific sales strategies and inventory management methods, the server provides them in a format that is easy for the user to understand. 【0325】 Step 6: 【0326】 The user reviews the proposed solutions via their device and proceeds with the necessary implementation procedures. At this stage, the user can make business decisions based on the AI ​​model's suggestions. 【0327】 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. 【0328】 This invention is an information processing system that streamlines users' daily tasks and provides optimized support tailored to their individual emotional states. The system consists of a user terminal, an information processing server, a generative AI model, and an emotion engine. 【0329】 User actions 【0330】 Users input schedules and tasks through their devices, and also provide emotional data using cameras and sensors. The devices collect this input information and emotional data and send it to a server for processing. 【0331】 Device functions 【0332】 The device transfers user-provided data and emotional data to the server. It also displays schedule suggestions and task adjustment information sent from the server and generative AI models, helping users maximize their work efficiency. 【0333】 Server Processing 【0334】 The server centrally manages user data and emotional data and requests analysis from a generative AI model. Based on the results received from the generative AI, the server adjusts the priority and content of tasks. At this time, the emotional engine is used to construct schedules and tasks that take the user's emotional state into consideration. 【0335】 Generative AI Models 【0336】 The generative AI model analyzes user data to suggest optimal schedules and tasks. The emotion engine tracks changes in the user's emotions and provides information to appropriately adjust task content and priorities. 【0337】 Specific example 【0338】 For example, if the system determines that a user is in a stressful situation, the emotion engine works with a generative AI model to suggest rescheduling less important meetings or reducing the number of tasks per day. On the other hand, if the user is relaxed, the system can suggest assigning them more tasks than usual. 【0339】 This system aims to further improve operational efficiency by incorporating an emotion engine, enabling flexible responses that respond to users' emotions. 【0340】 The following describes the processing flow. 【0341】 Step 1: 【0342】 The user uses the device to input schedule and task information and activates a camera or sensor to collect emotional data. This allows the necessary data to be collected. 【0343】 Step 2: 【0344】 The device sends information entered by the user and data acquired from the emotion sensor to the server. This data reflects the user's current state. 【0345】 Step 3: 【0346】 The server analyzes the received data to understand the user's current tasks and schedule status. The server then passes the analyzed data to a generating AI model and requests an optimal task management plan. 【0347】 Step 4: 【0348】 The generative AI model generates optimal schedules and task suggestions for the user based on user data and emotion data. An emotion engine is used here to make adjustments that take into account the user's emotional state. 【0349】 Step 5: 【0350】 The server receives suggestions from the generated AI model, formats them into task proposals and schedules optimized for emotions, and sends them to the terminal. 【0351】 Step 6: 【0352】 The terminal displays the proposal sent from the server to the user. The user can review this proposal and approve or modify it as needed. 【0353】 Step 7: 【0354】 User-approved schedules and task adjustments are fed back to the server, and the final state is reflected before execution. If further feedback is needed, the process is repeated for adjustments. 【0355】 Step 8: 【0356】 The emotion engine continuously monitors the user's emotional state and, as needed, feeds data back to the server and generative AI models, enabling optimal task adjustments in real time. 【0357】 (Example 2) 【0358】 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". 【0359】 In today's work environment, scheduling and task adjustments that ignore users' emotional states are a factor that reduces work efficiency. Furthermore, conventional information processing systems have difficulty providing individualized work plans based on emotional data, which presents a challenge in maximizing user performance. 【0360】 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. 【0361】 In this invention, the server includes means for generating a work plan according to the user's emotional state, means for transmitting collected emotional data, means for optimizing the schedule using a generation AI model, and means for adjusting task priorities based on the emotional data. This makes it possible to provide a flexible work plan that takes the user's emotional state into consideration. 【0362】 "User emotional state" refers to information that indicates the emotions and psychological state a user is experiencing at a specific point in time. 【0363】 "Means for generating business plans" refers to devices or software that have the function of structuring a user's schedule and tasks in a way that allows them to be executed efficiently. 【0364】 "Means for transmitting emotional data" refers to a device or software equipped with communication functions for sending data related to a user's emotional state to a processing unit or external device. 【0365】 "Means of optimizing schedules using generative AI models" refers to devices or software that utilize artificial intelligence to adjust a user's schedule to the optimal form. 【0366】 "Means for adjusting task priorities based on emotional data" refers to a device or software that has the function of dynamically changing the execution order and importance of tasks, taking into account the user's emotional state. 【0367】 This invention is an information processing system that streamlines users' daily tasks and provides optimized support according to the user's emotional state. The system consists of a terminal, an information processing server, a generative AI model, and an emotion engine. 【0368】 Users input schedules and tasks through their devices. Sentimental data is collected using cameras and sensors. The device then organizes the collected schedule information, task information, and sentimental data and sends it to a server. For this process, devices such as smartphones and tablets are used. 【0369】 The server centrally manages user data received from terminals and requests analysis from a generative AI model using prompt messages. An example of a prompt message is, "Considering the user's current stress level, please suggest the optimal schedule for tomorrow." The generative AI model utilizes, for example, machine learning algorithms and artificial intelligence platforms to generate schedule and task suggestions that are optimal for the user's emotional state. 【0370】 The server further refines the schedules and task suggestions received from the generated AI model and sends them to the terminal. The terminal then presents these to the user, providing an optimal work plan. In this process, the emotion engine plays a role in dynamically adjusting the priority and content of tasks based on the user's emotional data. 【0371】 For example, if a user is determined to be experiencing a high level of stress, the system will suggest rescheduling meetings or adjusting the number of tasks. In this way, the system optimizes work processes while taking into account the user's emotional state. 【0372】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0373】 Step 1: 【0374】 The device collects schedule and task information entered by the user, as well as emotional data obtained through the camera and sensors. Inputs include meeting appointments entered by the user in their calendar app and heart rate recorded by sensors. This information is organized into a digital format and prepared for further processing. 【0375】 Step 2: 【0376】 The device sends organized schedule and task information, as well as sentiment data, to the server. The input is a digital data package. Specifically, the device transmits data over the internet using the HTTPS protocol. The output is a data packet that reaches a specific endpoint on the server. 【0377】 Step 3: 【0378】 The server stores the received data in a database and generates prompt messages for the generating AI model. The input is the entire user data received from the terminal. The server uses this to generate prompt messages such as "Suggest a schedule for the next day that reflects the user's stress level" and sends them to the generating AI model. 【0379】 Step 4: 【0380】 The generative AI model generates optimal schedule and task suggestions based on prompt messages and user data received from the server. The input consists of prompt messages and user data, and data analysis is performed using natural language processing and machine learning algorithms. The output is a schedule proposal that takes the user's emotional state into consideration. 【0381】 Step 5: 【0382】 The server further refines the suggestions received from the generating AI model and prepares them to be sent to the user's terminal in the most optimal form. The input is the schedule suggestion from the generating AI model. Adjustments are made to this, taking into account the user's actual schedule and the importance of the tasks, and the final schedule information is obtained as output. 【0383】 Step 6: 【0384】 The terminal displays the user the adjusted schedule and task information sent from the server. The input is communication data from the server, which the terminal converts into a user-friendly format and displays on the screen. The output is a notification, such as "The 2 PM meeting has been rescheduled to next week." 【0385】 (Application Example 2) 【0386】 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." 【0387】 Traditional scheduling management systems struggle to respond flexibly to users' emotional states and cannot provide an environment optimized for individual emotions and situations. Furthermore, there is a lack of a consistent platform that can handle stress management and environmental adjustments during travel. 【0388】 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. 【0389】 In this invention, the server includes information processing means for providing individualized time management, information processing means for automatically performing individualized meeting preparations, information processing means for efficiently planning travel, and control means for dynamically adjusting the environment based on emotional state. This enables flexible schedule management and environmental adjustments during travel in accordance with the user's emotional state. 【0390】 "Personalized time management" is the process of adjusting schedules according to each user's specific needs and circumstances to provide an efficient timetable. 【0391】 "Personalized meeting preparation" is a feature that automatically organizes the necessary information and materials according to each user's role and objectives. 【0392】 "Travel planning" is a procedure that takes into account the user's destination and circumstances to propose the optimal travel route and means of transportation. 【0393】 "Dynamic environment adjustment based on emotional state" refers to operations that sense the user's emotions and psychological state in real time and appropriately change the physical or digital environment accordingly. 【0394】 "Information processing means" refers to devices and methods for collecting, analyzing, and managing data. 【0395】 A "control mechanism" is a system that manages and adjusts various settings and behaviors of a system under specific conditions. 【0396】 In implementing this invention, a server plays a central role. The server is equipped with multiple information processing and control means for personalized time management, meeting preparation, travel planning, and environmental adjustment based on emotional state. Specifically, the server is preferably set up in a cloud computing environment where a generative AI model operates, analyzing user data to propose optimal tasks and schedules. 【0397】 The terminals play a role in transmitting user data and emotional information to the server. These terminals include smartphones and in-car devices. These terminals are equipped with cameras and sensors, and facial recognition technology using tools such as OpenCV is employed to sense the user's emotional state. This information is then analyzed by an AI model built with TensorFlow. 【0398】 As a concrete example, if the device detects the user's face and recognizes an expression indicating fatigue, the server analyzes the user's calendar and work schedule. Based on this, it can automatically postpone meetings or change the travel route to suggest a quieter alternative. It can also adjust entertainment options, such as music playback, using APIs like Spotify. 【0399】 An example of a prompt might be: "Generate guidelines for developing a system that optimizes the in-car environment based on emotional state. Include entertainment and navigation systems that adapt to the driver's stress and relaxation levels." Based on this prompt, the server's AI model can propose the optimal strategy. 【0400】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0401】 Step 1: 【0402】 The user activates the camera and sensors through the device and inputs emotional data and schedule information. 【0403】 Input: User's face image, schedule data 【0404】 Output: Processing data packets 【0405】 Specifically, the device uses its camera to capture the user's face and extracts facial expression information from the image using OpenCV. Simultaneously, it also collects schedule data entered by the user. 【0406】 Step 2: 【0407】 The device packages the collected emotional data and schedule information and sends it to the server. 【0408】 Input: Processing data packet 【0409】 Output: Sent data 【0410】 The device encodes this data over the internet and securely transmits it to the server. 【0411】 Step 3: 【0412】 The server analyzes the received data and supplies it to the generated AI model. 【0413】 Input: Submitted data 【0414】 Output: Input data for the AI ​​model 【0415】 Specifically, the server decodes the data packets and inputs the user's emotional state into an AI model built with TensorFlow. 【0416】 Step 4: 【0417】 The generative AI model proposes the optimal schedule and tasks based on the received data. 【0418】 Input: Input data for the AI ​​model 【0419】 Output: Schedule optimization proposal 【0420】 The model takes the user's emotional state into account, re-evaluates priorities, and generates the most suitable task management plan. 【0421】 Step 5: 【0422】 The server generates movement plans and environmental adjustment instructions based on the analysis results from the AI ​​model and sends them to the terminal. 【0423】 Input: Schedule optimization proposal 【0424】 Output: Instructions for environmental adjustments and travel planning. 【0425】 The server uses Google Maps API and entertainment APIs to create route and music playback plans based on user requests and sends those instructions back to the device. 【0426】 Step 6: 【0427】 The terminal displays instructions received from the server to the user and performs the necessary adjustments. 【0428】 Input: Instructions for environmental adjustments and travel planning. 【0429】 Output: Adjusted schedule and in-car environment 【0430】 Based on the information it receives, the device displays suggestions to the user as visual information and performs actions such as music playback and route changes. 【0431】 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. 【0432】 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. 【0433】 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. 【0434】 [Third Embodiment] 【0435】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0436】 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. 【0437】 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). 【0438】 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. 【0439】 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. 【0440】 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). 【0441】 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. 【0442】 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. 【0443】 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. 【0444】 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. 【0445】 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. 【0446】 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". 【0447】 This invention is an information processing system that provides personalized support using a generative AI model. The system mainly consists of a user terminal, an information processing server, and a generative AI model. The user inputs information related to their daily work into the terminal, and this information is collected and stored on the server. 【0448】 User actions 【0449】 Users interact with the system through a dedicated application by entering information about their schedules and tasks into their terminals. This information is used to plan and execute automated tasks, allowing users to focus on their core responsibilities. 【0450】 Device functions 【0451】 The terminal collects information from the user and sends it to the server. Furthermore, it displays optimized task suggestions and notifications returned from the server and the generated AI model to the user. This allows the user to work more efficiently. 【0452】 Server Processing 【0453】 The server functions as the primary information processing unit, managing user data, communicating with the generative AI model, and storing information. The server sends data to the generative AI model and receives suggestions for task management, meeting preparation, and travel arrangements. 【0454】 Generative AI Models 【0455】 The generative AI model analyzes user data and returns optimized task suggestions to the server. These suggestions include schedule optimization and task prioritization, designed to help users utilize their time efficiently. 【0456】 Specific example 【0457】 For example, if a user requests, "Please check next week's meeting schedule and help me prepare," the server sends this request to a generative AI model. The generative AI model analyzes the user's schedule and meeting content and automatically generates the necessary materials and agenda for the meeting. The terminal displays this information to the user, and the meeting preparation is completed once the user confirms and approves it. This entire process allows the user to work efficiently. 【0458】 Thus, this system aims to improve users' work efficiency by providing automated support, primarily in scheduling, meeting preparation, and travel arrangements. 【0459】 The following describes the processing flow. 【0460】 Step 1: 【0461】 The user enters information about their schedule and tasks into the terminal. The terminal then formats this information and prepares it for transmission to the server. 【0462】 Step 2: 【0463】 The terminal sends data received from the user to the server. The server receives the data and stores it in a database for each user. 【0464】 Step 3: 【0465】 The server analyzes the stored user data and prepares to send the data to the generated AI model as needed. 【0466】 Step 4: 【0467】 The server requests the generative AI model to optimize schedules and prioritize tasks. The generative AI model analyzes these tasks and creates personalized suggestions optimized for each user. 【0468】 Step 5: 【0469】 The generative AI model returns the task suggestions it has created to the server. The server receives these suggestions and reformats them to suit the user's needs. 【0470】 Step 6: 【0471】 The server sends optimized task suggestions to the terminal. The terminal notifies the user of this information and displays it for the user to review. 【0472】 Step 7: 【0473】 Users review the proposed schedules and tasks on their devices and approve or modify them as needed. This ensures that the user's decisions are reflected in the system. 【0474】 Step 8: 【0475】 Based on the schedule and tasks approved by the user, the server initiates the necessary processes for automatically generating meeting invitation emails and arranging travel arrangements. The data is processed, and the user is notified of the final confirmation. 【0476】 (Example 1) 【0477】 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." 【0478】 In today's work environment, users spend considerable time and effort managing a wide range of schedules, coordinating tasks, preparing for meetings, and arranging business trips. These tasks significantly reduce productivity and prevent users from focusing on their core responsibilities. To address these issues and improve user efficiency, a means of automating these tasks and efficiently providing optimized solutions is necessary. 【0479】 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. 【0480】 In this invention, the server includes means for collecting user input information, means for transmitting this information to a generating artificial intelligence model for analysis, and means for generating and displaying optimized schedules and task suggestions based on the analysis results. This enables the automation of schedule and task management, allowing users to concentrate on important tasks. 【0481】 "User input information" refers to information related to daily tasks, such as schedules, tasks, and notes, that users provide to the system using their terminals. 【0482】 A "terminal" is a device used by users to input information and to receive suggestions and notifications from servers and generated AI models. 【0483】 A "server" is an information processing unit that aggregates information from users, communicates with the generated artificial intelligence model, and returns analysis results to the user as needed. 【0484】 A "generative artificial intelligence model" is a set of algorithms and computational methods that analyze user data to generate optimized schedules and task suggestions. 【0485】 "Optimization suggestions" are proposals for schedules and task plans designed to streamline the user's work management, generated based on the results of analysis by a generative artificial intelligence model. 【0486】 This invention is an efficient business support system using a generative AI model. The system is implemented in a form in which the user utilizes terminals, servers, and generative artificial intelligence models in conjunction to efficiently perform their tasks. 【0487】 Users input information such as schedules, tasks, meetings, and business trips using the terminal. The terminal has the function to transfer this input information to a server via the network. The user interface is designed to be user-friendly and intuitive for the user inputting the information. 【0488】 The server securely records the received user information in a database. The server then sends a prompt message containing the user information to the generative artificial intelligence model. For example, a prompt message such as "Please check the meeting schedule for next week and help me prepare" from the user is generated and passed to the generative artificial intelligence model. 【0489】 The generative artificial intelligence model analyzes received prompt messages and optimizes tasks based on user information. For example, it automatically generates materials and agenda items to be used in next week's meeting and creates a schedule proposal. Machine learning algorithms are used for internal calculations, enabling sophisticated suggestions based on work content and historical data. 【0490】 The server returns the generated business proposals to the terminal, making them visible to the user. The terminal notifies the user of the proposed schedule and tasks, and requests confirmation and approval. For example, the terminal displays information necessary for the user, such as, "Here are the materials needed for next week's meeting." 【0491】 Through this system, users can enjoy increased efficiency through automation, allowing them to focus on other important tasks. An example of a prompt message would be a request such as, "Please prepare the necessary materials for the next meeting," to which the system would respond promptly. 【0492】 Thus, this invention aims to improve the user's work efficiency by providing automated support, primarily for schedule management, meeting preparation, and travel arrangements. 【0493】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0494】 Step 1: 【0495】 Users input information about their schedules and tasks through a terminal. This input includes the date, time, location, and details of the task. The terminal saves this information to a local database, preparing it for subsequent processing. 【0496】 Step 2: 【0497】 The terminal transfers the entered information to the server. During this process, the terminal uses a secure communication protocol to ensure the safe transmission of user data. The server temporarily stores the received information in preparation for the processing step. 【0498】 Step 3: 【0499】 The server generates an appropriate prompt based on the received user data. The prompt specifies a concrete task and prepares it for transmission to the AI ​​model. For example, it might generate a message such as, "Please prepare the materials needed for next week's meeting." 【0500】 Step 4: 【0501】 The server sends the generated prompt text to the generative artificial intelligence model. The generative AI model analyzes user data based on the prompt text and optimizes schedules and tasks. Specifically, it uses machine learning algorithms to analyze past data and generate optimal meeting materials and task suggestions. 【0502】 Step 5: 【0503】 The generative AI model returns the analysis results to the server. The server receives these results and formats the data into a format usable by the user. The formatted results include optimized schedule and task suggestions. 【0504】 Step 6: 【0505】 The server sends the formatted data to the terminal. The terminal displays the received data to the user, providing information that can be used in specific tasks. For example, it might notify the user with a message like, "Here are the materials needed for next week's meeting," allowing the user to review and take action. 【0506】 (Application Example 1) 【0507】 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." 【0508】 The duties of store staff in physical stores are diverse, requiring them to efficiently handle tasks such as inventory management, sales strategies, and customer service. However, the heavy workload of these tasks can easily lead to a deterioration of the working environment for staff and a decline in the quality of customer service. Furthermore, the inability to make quick suggestions for improvement can result in missed sales opportunities. There is a need for solutions to these problems and improve the efficiency of store staff's work. 【0509】 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. 【0510】 In this invention, the server includes information processing means for providing individualized business management, information processing means for automatically improving the efficiency of store operations, and information processing means for supporting inventory management and sales strategies. This makes it possible to reduce the workload at physical stores and improve the quality of customer service. 【0511】 "Personalized task management" is an information processing technology that provides optimized task management methods tailored to each user and business environment. 【0512】 "Streamlining store operations" refers to information processing technology that enables various tasks in physical stores to be performed effectively with minimal time and resources. 【0513】 "Support for inventory management and sales strategies" refers to information processing technology that effectively supports inventory management and sales activity planning. 【0514】 A "generative AI model" is a computational model of artificial intelligence that generates appropriate suggestions and support based on input information. 【0515】 An "information processing device" refers to a system of hardware and software for receiving, processing, and providing data. 【0516】 The system for implementing this invention mainly consists of a server, a user terminal, and a generative AI model. The user uses the terminal to input information related to their daily work. This includes checking inventory status, customer interaction history, and product order information. The server receives this information and transmits the data to the generative AI model. 【0517】 The server functions as the primary information processing unit, managing user input data, communicating with the generative AI model, and storing information. The server also receives optimized business suggestions from the generative AI model and sends them to the user terminal. The specific hardware used by the server includes a database server and network interfaces, while the software used includes a generative AI model written in Python and a data management system. 【0518】 The generating AI model analyzes data sent from the server and optimizes business suggestions. For example, the model can propose sales strategies for each product based on inventory data and historical sales data, or generate optimal customer service methods. This allows users to carry out their daily tasks more efficiently. 【0519】 For example, if a user requests to "check the arrival status of new products for next week and develop a sales strategy," the server sends a request to the generating AI model. The model analyzes store inventory data and past sales data and proposes an optimized sales strategy for the new products. An example of a prompt to the generating AI model would be, "New products are scheduled to arrive next week. Please suggest a recommended sales strategy based on past data." This allows the user to refer to the suggestions and implement the most suitable sales strategy. 【0520】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0521】 Step 1: 【0522】 Users input work-related information using a terminal. This information includes inventory status, customer interaction history, and product order requests. This information is entered by the user through an application and sent to the server. 【0523】 Step 2: 【0524】 The server receives information from the user and stores it in the database. Here, the server verifies the integrity of the input data and stores the information in the appropriate table in the database. At this point, the data management system used by the server saves the input data. 【0525】 Step 3: 【0526】 The server sends the stored data to the generating AI model. Here, the server prepares the necessary input data, including prompts, and converts it into a format that the generating AI model can parse. Through this process, the server optimizes the input to the AI ​​model. 【0527】 Step 4: 【0528】 The generation AI model analyzes data sent from the server and generates business proposals. The AI ​​model uses the received data to execute a process that generates optimized proposals regarding inventory management and sales strategies. 【0529】 Step 5: 【0530】 After the AI ​​model generates proposals, the server receives these proposals and sends them to the user's terminal. Since the proposals include specific sales strategies and inventory management methods, the server provides them in a format that is easy for the user to understand. 【0531】 Step 6: 【0532】 The user reviews the proposed solutions via their device and proceeds with the necessary implementation procedures. At this stage, the user can make business decisions based on the AI ​​model's suggestions. 【0533】 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. 【0534】 This invention is an information processing system that streamlines users' daily tasks and provides optimized support tailored to their individual emotional states. The system consists of a user terminal, an information processing server, a generative AI model, and an emotion engine. 【0535】 User actions 【0536】 Users input schedules and tasks through their devices, and also provide emotional data using cameras and sensors. The devices collect this input information and emotional data and send it to a server for processing. 【0537】 Device functions 【0538】 The device transfers user-provided data and emotional data to the server. It also displays schedule suggestions and task adjustment information sent from the server and generative AI models, helping users maximize their work efficiency. 【0539】 Server Processing 【0540】 The server centrally manages user data and emotional data and requests analysis from a generative AI model. Based on the results received from the generative AI, the server adjusts the priority and content of tasks. At this time, the emotional engine is used to construct schedules and tasks that take the user's emotional state into consideration. 【0541】 Generative AI Models 【0542】 The generative AI model analyzes user data to suggest optimal schedules and tasks. The emotion engine tracks changes in the user's emotions and provides information to appropriately adjust task content and priorities. 【0543】 Specific example 【0544】 For example, if the system determines that a user is in a stressful situation, the emotion engine works with a generative AI model to suggest rescheduling less important meetings or reducing the number of tasks per day. On the other hand, if the user is relaxed, the system can suggest assigning them more tasks than usual. 【0545】 This system aims to further improve operational efficiency by incorporating an emotion engine, enabling flexible responses that respond to users' emotions. 【0546】 The following describes the processing flow. 【0547】 Step 1: 【0548】 The user uses the device to input schedule and task information and activates a camera or sensor to collect emotional data. This allows the necessary data to be collected. 【0549】 Step 2: 【0550】 The device sends information entered by the user and data acquired from the emotion sensor to the server. This data reflects the user's current state. 【0551】 Step 3: 【0552】 The server analyzes the received data to understand the user's current tasks and schedule status. The server then passes the analyzed data to a generating AI model and requests an optimal task management plan. 【0553】 Step 4: 【0554】 The generative AI model generates optimal schedules and task suggestions for the user based on user data and emotion data. An emotion engine is used here to make adjustments that take into account the user's emotional state. 【0555】 Step 5: 【0556】 The server receives suggestions from the generated AI model, formats them into task proposals and schedules optimized for emotions, and sends them to the terminal. 【0557】 Step 6: 【0558】 The terminal displays the proposal sent from the server to the user. The user can review this proposal and approve or modify it as needed. 【0559】 Step 7: 【0560】 User-approved schedules and task adjustments are fed back to the server, and the final state is reflected before execution. If further feedback is needed, the process is repeated for adjustments. 【0561】 Step 8: 【0562】 The emotion engine continuously monitors the user's emotional state and, as needed, feeds data back to the server and generative AI models, enabling optimal task adjustments in real time. 【0563】 (Example 2) 【0564】 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." 【0565】 In today's work environment, scheduling and task adjustments that ignore users' emotional states are a factor that reduces work efficiency. Furthermore, conventional information processing systems have difficulty providing individualized work plans based on emotional data, which presents a challenge in maximizing user performance. 【0566】 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. 【0567】 In this invention, the server includes means for generating a work plan according to the user's emotional state, means for transmitting collected emotional data, means for optimizing the schedule using a generation AI model, and means for adjusting task priorities based on the emotional data. This makes it possible to provide a flexible work plan that takes the user's emotional state into consideration. 【0568】 "User emotional state" refers to information that indicates the emotions and psychological state a user is experiencing at a specific point in time. 【0569】 "Means for generating business plans" refers to devices or software that have the function of structuring a user's schedule and tasks in a way that allows them to be executed efficiently. 【0570】 "Means for transmitting emotional data" refers to a device or software equipped with communication functions for sending data related to a user's emotional state to a processing unit or external device. 【0571】 "Means of optimizing schedules using generative AI models" refers to devices or software that utilize artificial intelligence to adjust a user's schedule to the optimal form. 【0572】 "Means for adjusting task priorities based on emotional data" refers to a device or software that has the function of dynamically changing the execution order and importance of tasks, taking into account the user's emotional state. 【0573】 This invention is an information processing system that streamlines users' daily tasks and provides optimized support according to the user's emotional state. The system consists of a terminal, an information processing server, a generative AI model, and an emotion engine. 【0574】 Users input schedules and tasks through their devices. Sentimental data is collected using cameras and sensors. The device then organizes the collected schedule information, task information, and sentimental data and sends it to a server. For this process, devices such as smartphones and tablets are used. 【0575】 The server centrally manages user data received from terminals and requests analysis from a generative AI model using prompt messages. An example of a prompt message is, "Considering the user's current stress level, please suggest the optimal schedule for tomorrow." The generative AI model utilizes, for example, machine learning algorithms and artificial intelligence platforms to generate schedule and task suggestions that are optimal for the user's emotional state. 【0576】 The server further refines the schedules and task suggestions received from the generated AI model and sends them to the terminal. The terminal then presents these to the user, providing an optimal work plan. In this process, the emotion engine plays a role in dynamically adjusting the priority and content of tasks based on the user's emotional data. 【0577】 For example, if a user is determined to be experiencing a high level of stress, the system will suggest rescheduling meetings or adjusting the number of tasks. In this way, the system optimizes work processes while taking into account the user's emotional state. 【0578】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0579】 Step 1: 【0580】 The device collects schedule and task information entered by the user, as well as emotional data obtained through the camera and sensors. Inputs include meeting appointments entered by the user in their calendar app and heart rate recorded by sensors. This information is organized into a digital format and prepared for further processing. 【0581】 Step 2: 【0582】 The device sends organized schedule and task information, as well as sentiment data, to the server. The input is a digital data package. Specifically, the device transmits data over the internet using the HTTPS protocol. The output is a data packet that reaches a specific endpoint on the server. 【0583】 Step 3: 【0584】 The server stores the received data in a database and generates prompt messages for the generating AI model. The input is the entire user data received from the terminal. The server uses this to generate prompt messages such as "Suggest a schedule for the next day that reflects the user's stress level" and sends them to the generating AI model. 【0585】 Step 4: 【0586】 The generative AI model generates optimal schedule and task suggestions based on prompt messages and user data received from the server. The input consists of prompt messages and user data, and data analysis is performed using natural language processing and machine learning algorithms. The output is a schedule proposal that takes the user's emotional state into consideration. 【0587】 Step 5: 【0588】 The server further refines the suggestions received from the generating AI model and prepares them to be sent to the user's terminal in the most optimal form. The input is the schedule suggestion from the generating AI model. Adjustments are made to this, taking into account the user's actual schedule and the importance of the tasks, and the final schedule information is obtained as output. 【0589】 Step 6: 【0590】 The terminal displays the user the adjusted schedule and task information sent from the server. The input is communication data from the server, which the terminal converts into a user-friendly format and displays on the screen. The output is a notification, such as "The 2 PM meeting has been rescheduled to next week." 【0591】 (Application Example 2) 【0592】 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." 【0593】 Traditional scheduling management systems struggle to respond flexibly to users' emotional states and cannot provide an environment optimized for individual emotions and situations. Furthermore, there is a lack of a consistent platform that can handle stress management and environmental adjustments during travel. 【0594】 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. 【0595】 In this invention, the server includes information processing means for providing individualized time management, information processing means for automatically performing individualized meeting preparations, information processing means for efficiently planning travel, and control means for dynamically adjusting the environment based on emotional state. This enables flexible schedule management and environmental adjustments during travel in accordance with the user's emotional state. 【0596】 "Personalized time management" is the process of adjusting schedules according to each user's specific needs and circumstances to provide an efficient timetable. 【0597】 "Personalized meeting preparation" is a feature that automatically organizes the necessary information and materials according to each user's role and objectives. 【0598】 "Travel planning" is a procedure that takes into account the user's destination and circumstances to propose the optimal travel route and means of transportation. 【0599】 "Dynamic environment adjustment based on emotional state" refers to operations that sense the user's emotions and psychological state in real time and appropriately change the physical or digital environment accordingly. 【0600】 "Information processing means" refers to devices and methods for collecting, analyzing, and managing data. 【0601】 A "control mechanism" is a system that manages and adjusts various settings and behaviors of a system under specific conditions. 【0602】 In implementing this invention, a server plays a central role. The server is equipped with multiple information processing and control means for personalized time management, meeting preparation, travel planning, and environmental adjustment based on emotional state. Specifically, the server is preferably set up in a cloud computing environment where a generative AI model operates, analyzing user data to propose optimal tasks and schedules. 【0603】 The terminals play a role in transmitting user data and emotional information to the server. These terminals include smartphones and in-car devices. These terminals are equipped with cameras and sensors, and facial recognition technology using tools such as OpenCV is employed to sense the user's emotional state. This information is then analyzed by an AI model built with TensorFlow. 【0604】 As a concrete example, if the device detects the user's face and recognizes an expression indicating fatigue, the server analyzes the user's calendar and work schedule. Based on this, it can automatically postpone meetings or change the travel route to suggest a quieter alternative. It can also adjust entertainment options, such as music playback, using APIs like Spotify. 【0605】 An example of a prompt might be: "Generate guidelines for developing a system that optimizes the in-car environment based on emotional state. Include entertainment and navigation systems that adapt to the driver's stress and relaxation levels." Based on this prompt, the server's AI model can propose the optimal strategy. 【0606】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0607】 Step 1: 【0608】 The user activates the camera and sensors through the device and inputs emotional data and schedule information. 【0609】 Input: User's face image, schedule data 【0610】 Output: Processing data packets 【0611】 Specifically, the device uses its camera to capture the user's face and extracts facial expression information from the image using OpenCV. Simultaneously, it also collects schedule data entered by the user. 【0612】 Step 2: 【0613】 The device packages the collected emotional data and schedule information and sends it to the server. 【0614】 Input: Processing data packet 【0615】 Output: Sent data 【0616】 The device encodes this data over the internet and securely transmits it to the server. 【0617】 Step 3: 【0618】 The server analyzes the received data and supplies it to the generated AI model. 【0619】 Input: Submitted data 【0620】 Output: Input data for the AI ​​model 【0621】 Specifically, the server decodes the data packets and inputs the user's emotional state into an AI model built with TensorFlow. 【0622】 Step 4: 【0623】 The generative AI model proposes the optimal schedule and tasks based on the received data. 【0624】 Input: Input data for the AI ​​model 【0625】 Output: Schedule optimization proposal 【0626】 The model takes the user's emotional state into account, re-evaluates priorities, and generates the most suitable task management plan. 【0627】 Step 5: 【0628】 The server generates movement plans and environmental adjustment instructions based on the analysis results from the AI ​​model and sends them to the terminal. 【0629】 Input: Schedule optimization proposal 【0630】 Output: Instructions for environmental adjustments and travel planning. 【0631】 The server uses Google Maps API and entertainment APIs to create route and music playback plans based on user requests and sends those instructions back to the device. 【0632】 Step 6: 【0633】 The terminal displays instructions received from the server to the user and performs the necessary adjustments. 【0634】 Input: Instructions for environmental adjustments and travel planning. 【0635】 Output: Adjusted schedule and in-car environment 【0636】 Based on the information it receives, the device displays suggestions to the user as visual information and performs actions such as music playback and route changes. 【0637】 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. 【0638】 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. 【0639】 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. 【0640】 [Fourth Embodiment] 【0641】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0642】 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. 【0643】 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). 【0644】 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. 【0645】 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. 【0646】 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). 【0647】 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. 【0648】 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. 【0649】 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. 【0650】 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. 【0651】 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. 【0652】 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. 【0653】 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". 【0654】 This invention is an information processing system that provides personalized support using a generative AI model. The system mainly consists of a user terminal, an information processing server, and a generative AI model. The user inputs information related to their daily work into the terminal, and this information is collected and stored on the server. 【0655】 User actions 【0656】 Users interact with the system through a dedicated application by entering information about their schedules and tasks into their terminals. This information is used to plan and execute automated tasks, allowing users to focus on their core responsibilities. 【0657】 Device functions 【0658】 The terminal collects information from the user and sends it to the server. Furthermore, it displays optimized task suggestions and notifications returned from the server and the generated AI model to the user. This allows the user to work more efficiently. 【0659】 Server Processing 【0660】 The server functions as the primary information processing unit, managing user data, communicating with the generative AI model, and storing information. The server sends data to the generative AI model and receives suggestions for task management, meeting preparation, and travel arrangements. 【0661】 Generative AI Models 【0662】 The generative AI model analyzes user data and returns optimized task suggestions to the server. These suggestions include schedule optimization and task prioritization, designed to help users utilize their time efficiently. 【0663】 Specific example 【0664】 For example, if a user requests, "Please check next week's meeting schedule and help me prepare," the server sends this request to a generative AI model. The generative AI model analyzes the user's schedule and meeting content and automatically generates the necessary materials and agenda for the meeting. The terminal displays this information to the user, and the meeting preparation is completed once the user confirms and approves it. This entire process allows the user to work efficiently. 【0665】 Thus, this system aims to improve users' work efficiency by providing automated support, primarily in scheduling, meeting preparation, and travel arrangements. 【0666】 The following describes the processing flow. 【0667】 Step 1: 【0668】 The user enters information about their schedule and tasks into the terminal. The terminal then formats this information and prepares it for transmission to the server. 【0669】 Step 2: 【0670】 The terminal sends data received from the user to the server. The server receives the data and stores it in a database for each user. 【0671】 Step 3: 【0672】 The server analyzes the stored user data and prepares to send the data to the generated AI model as needed. 【0673】 Step 4: 【0674】 The server requests the generative AI model to optimize schedules and prioritize tasks. The generative AI model analyzes these tasks and creates personalized suggestions optimized for each user. 【0675】 Step 5: 【0676】 The generative AI model returns the task suggestions it has created to the server. The server receives these suggestions and reformats them to suit the user's needs. 【0677】 Step 6: 【0678】 The server sends optimized task suggestions to the terminal. The terminal notifies the user of this information and displays it for the user to review. 【0679】 Step 7: 【0680】 Users review the proposed schedules and tasks on their devices and approve or modify them as needed. This ensures that the user's decisions are reflected in the system. 【0681】 Step 8: 【0682】 Based on the schedule and tasks approved by the user, the server initiates the necessary processes for automatically generating meeting invitation emails and arranging travel arrangements. The data is processed, and the user is notified of the final confirmation. 【0683】 (Example 1) 【0684】 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". 【0685】 In today's work environment, users spend considerable time and effort managing a wide range of schedules, coordinating tasks, preparing for meetings, and arranging business trips. These tasks significantly reduce productivity and prevent users from focusing on their core responsibilities. To address these issues and improve user efficiency, a means of automating these tasks and efficiently providing optimized solutions is necessary. 【0686】 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. 【0687】 In this invention, the server includes means for collecting user input information, means for transmitting this information to a generating artificial intelligence model for analysis, and means for generating and displaying optimized schedules and task suggestions based on the analysis results. This enables the automation of schedule and task management, allowing users to concentrate on important tasks. 【0688】 "User input information" refers to information related to daily tasks, such as schedules, tasks, and notes, that users provide to the system using their terminals. 【0689】 A "terminal" is a device used by users to input information and to receive suggestions and notifications from servers and generated AI models. 【0690】 A "server" is an information processing unit that aggregates information from users, communicates with the generated artificial intelligence model, and returns analysis results to the user as needed. 【0691】 A "generative artificial intelligence model" is a set of algorithms and computational methods that analyze user data to generate optimized schedules and task suggestions. 【0692】 "Optimization suggestions" are proposals for schedules and task plans designed to streamline the user's work management, generated based on the results of analysis by a generative artificial intelligence model. 【0693】 This invention is an efficient business support system using a generative AI model. The system is implemented in a form in which the user utilizes terminals, servers, and generative artificial intelligence models in conjunction to efficiently perform their tasks. 【0694】 Users input information such as schedules, tasks, meetings, and business trips using the terminal. The terminal has the function to transfer this input information to a server via the network. The user interface is designed to be user-friendly and intuitive for the user inputting the information. 【0695】 The server securely records the received user information in a database. The server then sends a prompt message containing the user information to the generative artificial intelligence model. For example, a prompt message such as "Please check the meeting schedule for next week and help me prepare" from the user is generated and passed to the generative artificial intelligence model. 【0696】 The generative artificial intelligence model analyzes received prompt messages and optimizes tasks based on user information. For example, it automatically generates materials and agenda items to be used in next week's meeting and creates a schedule proposal. Machine learning algorithms are used for internal calculations, enabling sophisticated suggestions based on work content and historical data. 【0697】 The server returns the generated business proposals to the terminal, making them visible to the user. The terminal notifies the user of the proposed schedule and tasks, and requests confirmation and approval. For example, the terminal displays information necessary for the user, such as, "Here are the materials needed for next week's meeting." 【0698】 Through this system, users can enjoy increased efficiency through automation, allowing them to focus on other important tasks. An example of a prompt message would be a request such as, "Please prepare the necessary materials for the next meeting," to which the system would respond promptly. 【0699】 Thus, this invention aims to improve the user's work efficiency by providing automated support, primarily for schedule management, meeting preparation, and travel arrangements. 【0700】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0701】 Step 1: 【0702】 Users input information about their schedules and tasks through a terminal. This input includes the date, time, location, and details of the task. The terminal saves this information to a local database, preparing it for subsequent processing. 【0703】 Step 2: 【0704】 The terminal transfers the entered information to the server. During this process, the terminal uses a secure communication protocol to ensure the safe transmission of user data. The server temporarily stores the received information in preparation for the processing step. 【0705】 Step 3: 【0706】 The server generates an appropriate prompt based on the received user data. The prompt specifies a concrete task and prepares it for transmission to the AI ​​model. For example, it might generate a message such as, "Please prepare the materials needed for next week's meeting." 【0707】 Step 4: 【0708】 The server sends the generated prompt text to the generative artificial intelligence model. The generative AI model analyzes user data based on the prompt text and optimizes schedules and tasks. Specifically, it uses machine learning algorithms to analyze past data and generate optimal meeting materials and task suggestions. 【0709】 Step 5: 【0710】 The generative AI model returns the analysis results to the server. The server receives these results and formats the data into a format usable by the user. The formatted results include optimized schedule and task suggestions. 【0711】 Step 6: 【0712】 The server sends the formatted data to the terminal. The terminal displays the received data to the user, providing information that can be used in specific tasks. For example, it might notify the user with a message like, "Here are the materials needed for next week's meeting," allowing the user to review and take action. 【0713】 (Application Example 1) 【0714】 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". 【0715】 The duties of store staff in physical stores are diverse, requiring them to efficiently handle tasks such as inventory management, sales strategies, and customer service. However, the heavy workload of these tasks can easily lead to a deterioration of the working environment for staff and a decline in the quality of customer service. Furthermore, the inability to make quick suggestions for improvement can result in missed sales opportunities. There is a need for solutions to these problems and improve the efficiency of store staff's work. 【0716】 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. 【0717】 In this invention, the server includes information processing means for providing individualized business management, information processing means for automatically improving the efficiency of store operations, and information processing means for supporting inventory management and sales strategies. This makes it possible to reduce the workload at physical stores and improve the quality of customer service. 【0718】 "Personalized task management" is an information processing technology that provides optimized task management methods tailored to each user and business environment. 【0719】 "Streamlining store operations" refers to information processing technology that enables various tasks in physical stores to be performed effectively with minimal time and resources. 【0720】 "Support for inventory management and sales strategies" refers to information processing technology that effectively supports inventory management and sales activity planning. 【0721】 A "generative AI model" is a computational model of artificial intelligence that generates appropriate suggestions and support based on input information. 【0722】 An "information processing device" refers to a system of hardware and software for receiving, processing, and providing data. 【0723】 The system for implementing this invention mainly consists of a server, a user terminal, and a generative AI model. The user uses the terminal to input information related to their daily work. This includes checking inventory status, customer interaction history, and product order information. The server receives this information and transmits the data to the generative AI model. 【0724】 The server functions as the primary information processing unit, managing user input data, communicating with the generative AI model, and storing information. The server also receives optimized business suggestions from the generative AI model and sends them to the user terminal. The specific hardware used by the server includes a database server and network interfaces, while the software used includes a generative AI model written in Python and a data management system. 【0725】 The generating AI model analyzes data sent from the server and optimizes business suggestions. For example, the model can propose sales strategies for each product based on inventory data and historical sales data, or generate optimal customer service methods. This allows users to carry out their daily tasks more efficiently. 【0726】 For example, if a user requests to "check the arrival status of new products for next week and develop a sales strategy," the server sends a request to the generating AI model. The model analyzes store inventory data and past sales data and proposes an optimized sales strategy for the new products. An example of a prompt to the generating AI model would be, "New products are scheduled to arrive next week. Please suggest a recommended sales strategy based on past data." This allows the user to refer to the suggestions and implement the most suitable sales strategy. 【0727】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0728】 Step 1: 【0729】 Users input work-related information using a terminal. This information includes inventory status, customer interaction history, and product order requests. This information is entered by the user through an application and sent to the server. 【0730】 Step 2: 【0731】 The server receives information from the user and stores it in the database. Here, the server verifies the integrity of the input data and stores the information in the appropriate table in the database. At this point, the data management system used by the server saves the input data. 【0732】 Step 3: 【0733】 The server sends the stored data to the generating AI model. Here, the server prepares the necessary input data, including prompts, and converts it into a format that the generating AI model can parse. Through this process, the server optimizes the input to the AI ​​model. 【0734】 Step 4: 【0735】 The generation AI model analyzes data sent from the server and generates business proposals. The AI ​​model uses the received data to execute a process that generates optimized proposals regarding inventory management and sales strategies. 【0736】 Step 5: 【0737】 After the AI ​​model generates proposals, the server receives these proposals and sends them to the user's terminal. Since the proposals include specific sales strategies and inventory management methods, the server provides them in a format that is easy for the user to understand. 【0738】 Step 6: 【0739】 The user reviews the proposed solutions via their device and proceeds with the necessary implementation procedures. At this stage, the user can make business decisions based on the AI ​​model's suggestions. 【0740】 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. 【0741】 This invention is an information processing system that streamlines users' daily tasks and provides optimized support tailored to their individual emotional states. The system consists of a user terminal, an information processing server, a generative AI model, and an emotion engine. 【0742】 User actions 【0743】 Users input schedules and tasks through their devices, and also provide emotional data using cameras and sensors. The devices collect this input information and emotional data and send it to a server for processing. 【0744】 Device functions 【0745】 The device transfers user-provided data and emotional data to the server. It also displays schedule suggestions and task adjustment information sent from the server and generative AI models, helping users maximize their work efficiency. 【0746】 Server Processing 【0747】 The server centrally manages user data and emotional data and requests analysis from a generative AI model. Based on the results received from the generative AI, the server adjusts the priority and content of tasks. At this time, the emotional engine is used to construct schedules and tasks that take the user's emotional state into consideration. 【0748】 Generative AI Models 【0749】 The generative AI model analyzes user data to suggest optimal schedules and tasks. The emotion engine tracks changes in the user's emotions and provides information to appropriately adjust task content and priorities. 【0750】 Specific example 【0751】 For example, if the system determines that a user is in a stressful situation, the emotion engine works with a generative AI model to suggest rescheduling less important meetings or reducing the number of tasks per day. On the other hand, if the user is relaxed, the system can suggest assigning them more tasks than usual. 【0752】 This system aims to further improve operational efficiency by incorporating an emotion engine, enabling flexible responses that respond to users' emotions. 【0753】 The following describes the processing flow. 【0754】 Step 1: 【0755】 The user uses the device to input schedule and task information and activates a camera or sensor to collect emotional data. This allows the necessary data to be collected. 【0756】 Step 2: 【0757】 The device sends information entered by the user and data acquired from the emotion sensor to the server. This data reflects the user's current state. 【0758】 Step 3: 【0759】 The server analyzes the received data to understand the user's current tasks and schedule status. The server then passes the analyzed data to a generating AI model and requests an optimal task management plan. 【0760】 Step 4: 【0761】 The generative AI model generates optimal schedules and task suggestions for the user based on user data and emotion data. An emotion engine is used here to make adjustments that take into account the user's emotional state. 【0762】 Step 5: 【0763】 The server receives suggestions from the generated AI model, formats them into task proposals and schedules optimized for emotions, and sends them to the terminal. 【0764】 Step 6: 【0765】 The terminal displays the proposal sent from the server to the user. The user can review this proposal and approve or modify it as needed. 【0766】 Step 7: 【0767】 User-approved schedules and task adjustments are fed back to the server, and the final state is reflected before execution. If further feedback is needed, the process is repeated for adjustments. 【0768】 Step 8: 【0769】 The emotion engine continuously monitors the user's emotional state and, as needed, feeds data back to the server and generative AI models, enabling optimal task adjustments in real time. 【0770】 (Example 2) 【0771】 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". 【0772】 In today's work environment, scheduling and task adjustments that ignore users' emotional states are a factor that reduces work efficiency. Furthermore, conventional information processing systems have difficulty providing individualized work plans based on emotional data, which presents a challenge in maximizing user performance. 【0773】 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. 【0774】 In this invention, the server includes means for generating a work plan according to the user's emotional state, means for transmitting collected emotional data, means for optimizing the schedule using a generation AI model, and means for adjusting task priorities based on the emotional data. This makes it possible to provide a flexible work plan that takes the user's emotional state into consideration. 【0775】 "User emotional state" refers to information that indicates the emotions and psychological state a user is experiencing at a specific point in time. 【0776】 "Means for generating business plans" refers to devices or software that have the function of structuring a user's schedule and tasks in a way that allows them to be executed efficiently. 【0777】 "Means for transmitting emotional data" refers to a device or software equipped with communication functions for sending data related to a user's emotional state to a processing unit or external device. 【0778】 "Means of optimizing schedules using generative AI models" refers to devices or software that utilize artificial intelligence to adjust a user's schedule to the optimal form. 【0779】 "Means for adjusting task priorities based on emotional data" refers to a device or software that has the function of dynamically changing the execution order and importance of tasks, taking into account the user's emotional state. 【0780】 This invention is an information processing system that streamlines users' daily tasks and provides optimized support according to the user's emotional state. The system consists of a terminal, an information processing server, a generative AI model, and an emotion engine. 【0781】 Users input schedules and tasks through their devices. Sentimental data is collected using cameras and sensors. The device then organizes the collected schedule information, task information, and sentimental data and sends it to a server. For this process, devices such as smartphones and tablets are used. 【0782】 The server centrally manages user data received from terminals and requests analysis from a generative AI model using prompt messages. An example of a prompt message is, "Considering the user's current stress level, please suggest the optimal schedule for tomorrow." The generative AI model utilizes, for example, machine learning algorithms and artificial intelligence platforms to generate schedule and task suggestions that are optimal for the user's emotional state. 【0783】 The server further refines the schedules and task suggestions received from the generated AI model and sends them to the terminal. The terminal then presents these to the user, providing an optimal work plan. In this process, the emotion engine plays a role in dynamically adjusting the priority and content of tasks based on the user's emotional data. 【0784】 For example, if a user is determined to be experiencing a high level of stress, the system will suggest rescheduling meetings or adjusting the number of tasks. In this way, the system optimizes work processes while taking into account the user's emotional state. 【0785】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0786】 Step 1: 【0787】 The device collects schedule and task information entered by the user, as well as emotional data obtained through the camera and sensors. Inputs include meeting appointments entered by the user in their calendar app and heart rate recorded by sensors. This information is organized into a digital format and prepared for further processing. 【0788】 Step 2: 【0789】 The device sends organized schedule and task information, as well as sentiment data, to the server. The input is a digital data package. Specifically, the device transmits data over the internet using the HTTPS protocol. The output is a data packet that reaches a specific endpoint on the server. 【0790】 Step 3: 【0791】 The server stores the received data in a database and generates prompt messages for the generating AI model. The input is the entire user data received from the terminal. The server uses this to generate prompt messages such as "Suggest a schedule for the next day that reflects the user's stress level" and sends them to the generating AI model. 【0792】 Step 4: 【0793】 The generative AI model generates optimal schedule and task suggestions based on prompt messages and user data received from the server. The input consists of prompt messages and user data, and data analysis is performed using natural language processing and machine learning algorithms. The output is a schedule proposal that takes the user's emotional state into consideration. 【0794】 Step 5: 【0795】 The server further refines the suggestions received from the generating AI model and prepares them to be sent to the user's terminal in the most optimal form. The input is the schedule suggestion from the generating AI model. Adjustments are made to this, taking into account the user's actual schedule and the importance of the tasks, and the final schedule information is obtained as output. 【0796】 Step 6: 【0797】 The terminal displays the user the adjusted schedule and task information sent from the server. The input is communication data from the server, which the terminal converts into a user-friendly format and displays on the screen. The output is a notification, such as "The 2 PM meeting has been rescheduled to next week." 【0798】 (Application Example 2) 【0799】 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". 【0800】 Traditional scheduling management systems struggle to respond flexibly to users' emotional states and cannot provide an environment optimized for individual emotions and situations. Furthermore, there is a lack of a consistent platform that can handle stress management and environmental adjustments during travel. 【0801】 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. 【0802】 In this invention, the server includes information processing means for providing individualized time management, information processing means for automatically performing individualized meeting preparations, information processing means for efficiently planning travel, and control means for dynamically adjusting the environment based on emotional state. This enables flexible schedule management and environmental adjustments during travel in accordance with the user's emotional state. 【0803】 "Personalized time management" is the process of adjusting schedules according to each user's specific needs and circumstances to provide an efficient timetable. 【0804】 "Personalized meeting preparation" is a feature that automatically organizes the necessary information and materials according to each user's role and objectives. 【0805】 "Travel planning" is a procedure that takes into account the user's destination and circumstances to propose the optimal travel route and means of transportation. 【0806】 "Dynamic environment adjustment based on emotional state" refers to operations that sense the user's emotions and psychological state in real time and appropriately change the physical or digital environment accordingly. 【0807】 "Information processing means" refers to devices and methods for collecting, analyzing, and managing data. 【0808】 A "control mechanism" is a system that manages and adjusts various settings and behaviors of a system under specific conditions. 【0809】 In implementing this invention, a server plays a central role. The server is equipped with multiple information processing and control means for personalized time management, meeting preparation, travel planning, and environmental adjustment based on emotional state. Specifically, the server is preferably set up in a cloud computing environment where a generative AI model operates, analyzing user data to propose optimal tasks and schedules. 【0810】 The terminals play a role in transmitting user data and emotional information to the server. These terminals include smartphones and in-car devices. These terminals are equipped with cameras and sensors, and facial recognition technology using tools such as OpenCV is employed to sense the user's emotional state. This information is then analyzed by an AI model built with TensorFlow. 【0811】 As a concrete example, if the device detects the user's face and recognizes an expression indicating fatigue, the server analyzes the user's calendar and work schedule. Based on this, it can automatically postpone meetings or change the travel route to suggest a quieter alternative. It can also adjust entertainment options, such as music playback, using APIs like Spotify. 【0812】 An example of a prompt might be: "Generate guidelines for developing a system that optimizes the in-car environment based on emotional state. Include entertainment and navigation systems that adapt to the driver's stress and relaxation levels." Based on this prompt, the server's AI model can propose the optimal strategy. 【0813】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0814】 Step 1: 【0815】 The user activates the camera and sensors through the device and inputs emotional data and schedule information. 【0816】 Input: User's face image, schedule data 【0817】 Output: Processing data packets 【0818】 Specifically, the device uses its camera to capture the user's face and extracts facial expression information from the image using OpenCV. Simultaneously, it also collects schedule data entered by the user. 【0819】 Step 2: 【0820】 The device packages the collected emotional data and schedule information and sends it to the server. 【0821】 Input: Processing data packet 【0822】 Output: Sent data 【0823】 The device encodes this data over the internet and securely transmits it to the server. 【0824】 Step 3: 【0825】 The server analyzes the received data and supplies it to the generated AI model. 【0826】 Input: Submitted data 【0827】 Output: Input data for the AI ​​model 【0828】 Specifically, the server decodes the data packets and inputs the user's emotional state into an AI model built with TensorFlow. 【0829】 Step 4: 【0830】 The generative AI model proposes the optimal schedule and tasks based on the received data. 【0831】 Input: Input data for the AI ​​model 【0832】 Output: Schedule optimization proposal 【0833】 The model takes the user's emotional state into account, re-evaluates priorities, and generates the most suitable task management plan. 【0834】 Step 5: 【0835】 The server generates movement plans and environmental adjustment instructions based on the analysis results from the AI ​​model and sends them to the terminal. 【0836】 Input: Schedule optimization proposal 【0837】 Output: Instructions for environmental adjustments and travel planning. 【0838】 The server uses Google Maps API and entertainment APIs to create route and music playback plans based on user requests and sends those instructions back to the device. 【0839】 Step 6: 【0840】 The terminal displays instructions received from the server to the user and performs the necessary adjustments. 【0841】 Input: Instructions for environmental adjustments and travel planning. 【0842】 Output: Adjusted schedule and in-car environment 【0843】 Based on the information it receives, the device displays suggestions to the user as visual information and performs actions such as music playback and route changes. 【0844】 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. 【0845】 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. 【0846】 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. 【0847】 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. 【0848】 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. 【0849】 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. 【0850】 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. 【0851】 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. 【0852】 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." 【0853】 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. 【0854】 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. 【0855】 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. 【0856】 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. 【0857】 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. 【0858】 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. 【0859】 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. 【0860】 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. 【0861】 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. 【0862】 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. 【0863】 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. 【0864】 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 as being incorporated by reference. 【0865】 The following is further disclosed regarding the embodiments described above. 【0866】 (Claim 1) 【0867】 An information processing device that provides personalized schedule management, 【0868】 An information processing device that automatically performs individualized meeting preparation, 【0869】 An information processing device for efficiently arranging business trips, 【0870】 A system that includes this. 【0871】 (Claim 2) 【0872】 The system according to claim 1, which optimizes a task using a generative AI model. 【0873】 (Claim 3) 【0874】 The system according to claim 1, which automates routine tasks based on user data. 【0875】 "Example 1" 【0876】 (Claim 1) 【0877】 A means of collecting user input information via a terminal, 【0878】 A means of sending this information to a generated artificial intelligence model via a server for analysis, 【0879】 A means for generating and displaying optimization suggestions for schedules and tasks based on the analysis results on a terminal, 【0880】 A system that includes this. 【0881】 (Claim 2) 【0882】 The system according to claim 1, which optimizes tasks using a generative artificial intelligence model and supports meeting preparation based on user instructions. 【0883】 (Claim 3) 【0884】 The system according to claim 1, which automates routine tasks based on user data and manages the information on a server. 【0885】 "Application Example 1" 【0886】 (Claim 1) 【0887】 An information processing device that provides individualized business management, 【0888】 An information processing device that automatically streamlines store operations, 【0889】 An information processing device that supports inventory management and sales strategies, 【0890】 A system that includes this. 【0891】 (Claim 2) 【0892】 The system according to claim 1, which optimizes business proposals using a generative AI model. 【0893】 (Claim 3) 【0894】 The system according to claim 1, which automates business support based on user input. 【0895】 "Example 2 of combining an emotion engine" 【0896】 (Claim 1) 【0897】 A means for generating a work plan that corresponds to the user's emotional state, 【0898】 A means of transmitting the collected emotional data, 【0899】 A method for optimizing schedules using a generative AI model, 【0900】 A means of adjusting task priorities based on emotional data, 【0901】 A system that includes this. 【0902】 (Claim 2) 【0903】 The system according to claim 1, which uses a generative AI model to perform optimization that takes into account the user's emotional state. 【0904】 (Claim 3) 【0905】 The system according to claim 1, which automates routine tasks based on user data and sentiment data. 【0906】 "Application example 2 when combining with an emotional engine" 【0907】 (Claim 1) 【0908】 An information processing device that provides individualized time management, 【0909】 An information processing device that automatically performs individualized meeting preparation, 【0910】 An information processing device for efficiently planning travel, 【0911】 A control device that performs dynamic environmental adjustments based on emotional state, 【0912】 A system that includes this. 【0913】 (Claim 2) 【0914】 The system according to claim 1, which optimizes a task using a generative AI model. 【0915】 (Claim 3) 【0916】 The system according to claim 1, which automates routine tasks based on user information. [Explanation of symbols] 【0917】 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

[Claim 1] A means of providing personalized schedule management, A means to automate individualized meeting preparation, Methods for efficiently arranging business trips, A system that includes this. [Claim 2] The system according to claim 1, which optimizes a task using a generative AI model. [Claim 3] The system according to claim 1, which automates routine tasks based on user data.

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