system

Abstract

We provide the system. [Solution] A means for generating defined configuration data based on a configuration request received from an information processing device, Means for transmitting the generated configuration data to the information processing device, In multiple autonomously functioning terminals, means for analyzing the aforementioned configuration data and automatically executing the necessary settings, A means for centrally controlling and monitoring the settings of multiple terminals in a public management device in real time, Means for recording the results of the aforementioned settings and saving them in a history database, 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 and includes 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] The setting work of an information processing device is complicated and time-consuming, so users have to expend a great deal of labor. In addition, manual setting may induce human errors and increase security risks. The lack of consistency in the setting work in enterprises and individuals is also a problem, which increases the management cost. When the setting itself is not properly performed, there is a problem of accompanying risks of unexpected system failures and data leaks. It is necessary to solve these problems and provide a method for realizing efficient and safe setting work.

Means for Solving the Problems

[0005] This invention provides a system that receives configuration requests from an information processing device, generates the corresponding configuration data, and transmits it. An adjacent information processing device analyzes the received data and automatically performs the configuration task. Furthermore, the system records the results of the configuration task and stores them in a history database, which can be used for troubleshooting purposes. This system includes means to verify that the generated configuration data conforms to security standards and organizational policies, enabling secure configuration. This reduces the effort required from the user, ensures configuration consistency, and minimizes security risks.

[0006] An "information processing device" is an electronic device, such as a computer or smartphone, that processes data and performs operations in response to user requests.

[0007] A "configuration request" refers to a request or command made by a user to a system in order to configure the information processing device, and includes data related to changing or initializing settings.

[0008] "Configuration data" refers to information necessary for configuring the information processing device, and includes specific configuration details such as network settings and application installation procedures.

[0009] "Analysis" is the process of breaking down received data, understanding its contents, and identifying the necessary processing.

[0010] "Automatic execution" means that the system mechanically performs a series of configuration tasks without requiring manual intervention from the user.

[0011] A "history database" is a database that records and stores past configuration work and operation results, and can be referenced during troubleshooting and audits.

[0012] A "security standard" is a set of general or specific security guidelines and protocols designed to maintain the confidentiality, integrity, and availability of information. [Brief explanation of the drawing]

[0013] [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] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention is a system that automates the configuration of an information processing device using an AI agent, and consists of a central server, a terminal that performs configuration, and a user that makes configuration requests.

[0035] The server is responsible for centrally managing all configuration requests. Specifically, when a user sets up a new device or reconfigures an existing one, the server receives the relevant configuration requests. This includes network settings and security policy enforcement. The server refers to an internal database, generates appropriate configuration data based on the latest security standards and organizational policies, and sends it to the device.

[0036] The terminal has the ability to receive configuration data sent from the server, analyze it, and automatically implement specified configuration tasks. This process includes automatic configuration of network connections, installation of new software, and system security settings. Because it has a built-in AI agent, the terminal can maximize the efficiency of configuration tasks. Furthermore, the terminal records the results of configuration execution in a history database, making it available for future troubleshooting and auditing.

[0037] This system significantly reduces the burden on users. For example, when a user receives a new smartphone, it will automatically connect to the company network and have necessary applications and security settings installed with just a few simple steps. This allows users to start using the device immediately.

[0038] This system is particularly effective when deployed on a large scale in enterprise environments. It allows for consistent control of equipment management across the entire workforce, including the simultaneous configuration of new devices and the application of new policies to existing devices. Therefore, this system significantly contributes to increased productivity and reduced management costs.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] When a user needs to configure a new device or wants to reconfigure an existing one, they connect to the network and send a configuration request to the server. This request includes the device type and the required configuration information.

[0042] Step 2:

[0043] The server receives configuration requests from users and generates the necessary configuration data based on device identification information and requirements. The server references its internal, up-to-date security policies and standard configuration guidelines.

[0044] Step 3:

[0045] The server sends the generated configuration data to the specified terminal. This data includes instructions for configuration, network information, and information about the software to be installed.

[0046] Step 4:

[0047] The device receives configuration data sent from the server and uses an AI agent to analyze the data. Through this analysis, it identifies which settings are needed and determines their priority.

[0048] Step 5:

[0049] Based on the analysis results, the device will automatically begin configuration tasks. This includes configuring network settings, installing new applications, and updating existing security settings.

[0050] Step 6:

[0051] Once the terminal confirms that all configuration tasks are complete, it records the results in detail and saves them as a log file in the history database. The log includes the configuration tasks performed and their success status.

[0052] Step 7:

[0053] The server receives a notification from the terminal that the setup is complete and notifies the user that the setup was completed successfully. This allows the user to start using the device immediately.

[0054] (Example 1)

[0055] 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."

[0056] In today's information processing environments, rapid and consistent configuration management of numerous devices is essential. However, traditional manual configuration management is time-consuming, labor-intensive, and prone to errors. Therefore, improving the efficiency and accuracy of configuration work is a crucial challenge.

[0057] 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.

[0058] In this invention, the server includes means for generating defined configuration data based on a configuration request received from an information processing device, means for transmitting the generated configuration data to the information processing device, and means for analyzing the configuration data and automatically executing the necessary configurations in an adjacent information processing device. This enables rapid and consistent automatic configuration for a large number of devices.

[0059] An "information processing device" refers to a computer or device that processes, manages, and stores data.

[0060] A "configuration request" is an instruction from a user or system to change or apply settings to a device or software.

[0061] "Configuration data" refers to data containing specific settings applied to an information processing device.

[0062] An "adjacent information processing device" is an information processing device that is connected to a server via a network in order to receive and analyze configuration data.

[0063] A "database" is a collection of data that systematically stores settings, their execution results, and other information so that it can be referenced later.

[0064] An "AI agent" is a type of artificial intelligence that automatically performs processes involving learning and decision-making, with the aim of streamlining setup tasks.

[0065] "Security standards" are rules and guidelines established to ensure the security of information processing equipment and data.

[0066] "Organizational policies" define the standard procedures, rules, and guidelines that are in place within a particular organization.

[0067] "Troubleshooting" refers to the procedures and actions taken to resolve system malfunctions and anomalies.

[0068] This invention is an automated configuration system for an information processing device incorporating an AI agent. The system consists of a server, a terminal that performs configuration, and a user that sends configuration requests.

[0069] The server receives configuration requests from information processing devices. For example, if a user wants to configure a new device, the server parses the request in the database and prepares the appropriate configuration data. The database incorporates the latest security standards and organizational policies. The server then sends the generated configuration data to the device.

[0070] The terminal has the ability to receive configuration data sent from the server, appropriately analyze its contents, and execute actions automatically. In this process, an AI agent plays a crucial role, making the configuration work more efficient and accurate. Specifically, the terminal performs operations such as initializing network settings, installing necessary applications, and applying security policies. Furthermore, after completing the configuration, the terminal records the results in a history database for future analysis and troubleshooting.

[0071] When users receive a new device, they can initiate a setup request through the system, and the device will be ready for immediate use with minimal or no complex operations required. For example, when a user receives a new smartphone, they can perform a few simple steps to automatically connect the smartphone to the company network and quickly apply the necessary apps and settings.

[0072] An example of a prompt statement when using a generative AI model is the instruction, "Initialize network settings for new employees and install standard software." In this way, by utilizing generative AI models and prompt statements, the system can achieve highly efficient automation of configuration.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The user issues a configuration request.

[0076] When a user wants to configure a new device, they send a configuration request to the server via a dedicated application or web interface.

[0077] Input: The configuration request entered by the user.

[0078] Output: Configuration request data sent to the server.

[0079] Step 2:

[0080] The server receives and parses the request.

[0081] The server analyzes the configuration request received from the user. The server accesses an internal database to check the device type and the required configuration.

[0082] Input: Configuration request data submitted by the user.

[0083] Output: A list of settings based on the analysis and a template for the generated configuration data.

[0084] Step 3:

[0085] The server generates configuration data.

[0086] Based on the analysis results, the server generates the configuration data necessary for setting up the device. This includes network configuration information and security configurations.

[0087] Input: Analysis results and reference data obtained from the database.

[0088] Output: Configuration data to be sent to the terminal.

[0089] Step 4:

[0090] Sending configuration data from the server to the terminal.

[0091] The server sends the generated configuration data to the appropriate terminal. The data is transmitted using a secure communication channel.

[0092] Input: Generated configuration data.

[0093] Output: Sends configuration data that the terminal should receive.

[0094] Step 5:

[0095] The device receives and analyzes the configuration data.

[0096] The terminal receives configuration data sent from the server and analyzes its contents. An AI agent supports the analysis process.

[0097] Input: Configuration data sent from the server.

[0098] Output: A list of setup steps.

[0099] Step 6:

[0100] The device will automatically perform the setup.

[0101] The device automatically performs the necessary configurations based on the analyzed setup procedures. This includes application installation and network configuration.

[0102] Input: A list of setup steps.

[0103] Output: The settings performed and their results.

[0104] Step 7:

[0105] The device records the settings results.

[0106] The device records the results of the settings performed in detail and stores them in a database. This allows for future troubleshooting and audits.

[0107] Input: The result of the settings that were applied.

[0108] Output: Settings history stored in the history database.

[0109] Step 8:

[0110] Notify the user that the setup is complete.

[0111] The user will be notified from their device that the setup is complete and will receive confirmation that the device is ready for immediate use.

[0112] Input: Notification of completion of setup from the device.

[0113] Output: Notification message to the user.

[0114] (Application Example 1)

[0115] 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."

[0116] In smart cities, when numerous information processing devices are deployed simultaneously, effectively and quickly managing the settings of these devices is crucial. However, traditional manual or partially automated configuration management is prone to errors and difficult to operate efficiently. Furthermore, sophisticated management methods are necessary to ensure configuration consistency while maintaining security. These challenges must be addressed to streamline the deployment and management of devices in public management systems.

[0117] 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.

[0118] In this invention, the server includes means for generating defined configuration data based on a configuration request received from an information processing device, means for transmitting the generated configuration data to the information processing device, and means for analyzing the configuration data and automatically executing the necessary configurations in a plurality of autonomously functioning terminals. This makes it possible to manage a plurality of information processing devices quickly and effectively.

[0119] An "information processing device" is a device that performs data input, processing, and output, and in particular has the function of sending configuration requests to a server, analyzing the received configuration data, and executing the process.

[0120] A "configuration request" refers to an instruction issued by a user or device to a server in order to change or define new settings for an information processing device.

[0121] "Configuration data" refers to specific configuration information that a server generates based on a configuration request and that an information processing device applies.

[0122] "Means" refers to processes or devices designed to achieve a specific function, and in this invention includes components that enable the generation, transmission, and execution of step-by-step settings.

[0123] A "server" is a computer system that provides services over a network, and its role is to receive configuration requests and generate appropriate configuration data.

[0124] A "history database" is a database that records the results of past configurations and stores information that can be referenced for future troubleshooting and auditing purposes.

[0125] "Real-time" means that there is virtually no delay between the occurrence of an event and its analysis, processing, and response, and in this invention, it enables immediate monitoring of the device's status.

[0126] This invention provides a system for efficiently managing the settings of information processing devices in smart cities. The system mainly consists of a server, terminals, and users.

[0127] The server functions as the central management unit on the network. Based on configuration requests received from users, the server first parses the requests and generates configuration data that complies with the organization's policies and environmental standards. The server then transmits this generated data to numerous autonomous terminals. As hardware, the server is equipped with a high-performance processor and sufficient memory, and uses a database management system (e.g., SQL Server) to process and store historical data.

[0128] The terminal analyzes configuration data received from the server and automatically performs the necessary settings on the target device. The terminal also monitors the results of each configuration operation in real time and sends the data to the server's history database. The terminal is equipped with AI agent software and uses a machine learning model (generative AI model) in response to prompts to determine the optimal configuration method.

[0129] As an administrator operating the system, the user can initiate the entire setup process by entering simple prompts into the system. Specifically, by sending a prompt such as "New camera setup (resolution: 1080p, frame rate: 30fps)" to the server, the server will respond immediately and automatically proceed with the setup process.

[0130] This system streamlines the management of complex and extensive devices in smart cities, minimizing configuration errors. It also maintains reliability and efficiency even in mass deployments.

[0131] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0132] Step 1:

[0133] The server parses the prompt message received from the user. It receives a prompt message (e.g., "New Camera Setup") as input and extracts the necessary configuration parameters based on it. It uses a generative AI model to select a template suitable for the configuration. The output is generated configuration data, including the configuration template.

[0134] Step 2:

[0135] The server creates a detailed configuration file based on the generated configuration data. This process verifies the configuration in accordance with environmental standards and organizational policies, and confirms compliance with security standards. The output is a detailed configuration file ready to be sent to the terminal.

[0136] Step 3:

[0137] The server sends a detailed configuration file to multiple terminals over the network. Each terminal receives the configuration file, parses it, and automatically starts the necessary hardware configuration and software installation. The input to each terminal is the received configuration file, and the output is the progress of the configuration process.

[0138] Step 4:

[0139] The terminal monitors the configuration progress in real time and sends feedback to the server if any errors or configuration inconsistencies occur. This process verifies the completion status of each configuration and prepares to record it in the history database.

[0140] Step 5:

[0141] The terminal sends the result to the server once the setup is successfully completed. The server receives this and stores it in its history database. The input is the completion report from the terminal, and the output is the recorded history data.

[0142] Step 6:

[0143] Users can audit device configurations and past change history by accessing the server and checking the history database. The input for this step is a request to access the database, and the output is a set of historical information provided to the user.

[0144] 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.

[0145] This invention provides a personalized configuration experience by combining a system that automates the configuration of information processing equipment with an emotion engine that recognizes user emotions. The system mainly consists of a server, a terminal, and an emotion engine.

[0146] The server receives configuration requests from each information processing device and is responsible for generating appropriate configuration data. Based on the database, the server references security standards and organizational policies to prepare configuration information according to the request. This configuration data is personalized based on the analysis results of the sentiment engine.

[0147] The device receives configuration data sent from the server and automatically performs the configuration process. During this process, the emotion engine on the device analyzes the user's emotional state in real time. The emotion engine analyzes user input such as voice tone and facial expressions to determine whether the user is relaxed or stressed.

[0148] Depending on the user's emotional state, the device optimizes the setup process. For example, if the user is stressed, it provides more detailed notifications to aid understanding, while if the user is relaxed, it completes the setup more quickly. This allows the user to have a flexible setup experience tailored to their situation.

[0149] For example, when a user is setting up a new laptop, if the emotion engine detects stress from the user's tone of voice, the device will add a step that explains the setup process in detail. Conversely, if the emotion engine detects positive emotions, it will simplify notifications and shorten the setup time. This improves the user experience while maintaining formal consistency.

[0150] The following describes the processing flow.

[0151] Step 1:

[0152] To begin setting up a new device, the user connects the device to the network and sends a setup request to the server via the terminal. This request may include assistance with necessary customization information and the user's current emotional state.

[0153] Step 2:

[0154] The server receives configuration requests from users and generates configuration data based on those requests, taking into account the device's characteristics and the organization's policies. In doing so, the server incorporates configuration information to ensure compliance with the latest security standards.

[0155] Step 3:

[0156] The server sends the generated configuration data to the terminal. This data includes network settings, a list of recommended applications, and security settings.

[0157] Step 4:

[0158] The device receives configuration data sent from the server and activates an emotion engine to analyze the user's emotional state in real time. It identifies the user's emotions using speech recognition and facial expression analysis via a camera.

[0159] Step 5:

[0160] The device adjusts the setup process based on the analysis results of the emotion engine. For example, if it determines that the user is stressed, it provides detailed guidance to make the process easier to understand. Conversely, if the user is relaxed, it simplifies the setup procedure and allows for quick execution.

[0161] Step 6:

[0162] Once the setup is complete, the device records the results in detail and saves them to a history database. This allows for future troubleshooting and reference of the history.

[0163] Step 7:

[0164] The server receives completion notifications from the terminal and notifies the user of the completion status of the setup. Based on feedback from the emotion engine, the notification is provided in an appropriate format. For example, if the user was stressed, the server will provide an announcement that explains in detail the benefits of completing the setup and the next steps.

[0165] (Example 2)

[0166] 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."

[0167] In modern information processing systems, providing a personalized setup experience tailored to each user's individual needs and emotional state is crucial for improving user satisfaction. However, conventional systems lacked the technology to automatically optimize the setup process based on user emotions, resulting in a failure to adequately respond to situations where users felt stressed or, conversely, relaxed.

[0168] 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.

[0169] In this invention, the server includes means for generating defined configuration data based on configuration requests received from an information processing device, means for analyzing the user's emotional state and personalizing the configuration data based on that emotional analysis, and means for adjusting the configuration process according to the user's emotional state and optimizing the user experience. This makes it possible to provide a flexible configuration experience that responds to the user's emotions.

[0170] An "information processing device" is a general term for a device that has the functions of inputting, processing, storing, and outputting data.

[0171] A "configuration request" is a request that specifies the instructions or conditions necessary for an information processing device to operate according to specific conditions or parameters.

[0172] "Configuration data" refers to a dataset containing specific parameters and conditions necessary to control the operation of an information processing device.

[0173] "Adjacent information processing devices" refer to information processing devices that can communicate directly with each other via a network or physical connection.

[0174] "Analysis" is the act of extracting received data or information and converting it into a form that is easy to understand.

[0175] "Emotional state" refers to the user's psychological and physiological responses, and is an indicator that indicates their emotions at that time.

[0176] Personalization is the process of optimizing information and services to suit the individual needs and circumstances of each user, and adjusting them to be individually adapted.

[0177] A "history database" is a type of database used to store records of past operation results, events, and configuration data.

[0178] "Troubleshooting" is a method for diagnosing system or equipment failures and problems and finding solutions.

[0179] This invention is a system that automates the settings of an information processing device according to the user's emotional state, thereby providing a personalized experience. It mainly consists of a server, a terminal, and an emotion engine. Details of each element are as follows:

[0180] The server receives configuration requests from information processing devices via the network. Based on these requests, the server accesses the database and generates appropriate configuration data while referencing security standards and organizational policies. By utilizing a generative AI model, efficient generation and optimization of configuration data are achieved. This generated data is then personalized based on user sentiment analysis obtained through an emotion engine.

[0181] The terminal receives configuration data sent from the server and automatically performs the configuration process. An emotion engine integrated into the terminal analyzes the user's voice tone and facial expressions to understand their emotional state in real time. The emotion engine determines the user's level of tension or relaxation and adjusts the configuration process accordingly.

[0182] As a concrete example, consider the scenario of setting up a new computer. When a user unboxes the new computer and begins the initial setup, the device's built-in emotion engine detects from the user's tone of voice that they are feeling stressed. In this case, the device displays additional information to make the setup process easier to understand. On the other hand, if the user is relaxed, notifications are simplified, and the setup time is shortened.

[0183] An example of a prompt for a generative AI model would be, "If a user is setting up a new computer in a relaxed state, how should you optimize the setup process?" This prompt allows the generative AI model to provide optimal setup instructions that take emotional states into account.

[0184] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0185] Step 1:

[0186] The server receives configuration requests from information processing devices. The input is a configuration request sent over the network, which includes the device type and required configuration items. As output, the server parses the received requests and extracts the appropriate information for the next processing step. Specifically, it determines the priority of the requests and identifies which configuration data is needed.

[0187] Step 2:

[0188] The server accesses the database and generates appropriate configuration data in response to configuration requests. The input is the parsed request content, and the output is configuration data that conforms to security standards and organizational policies. A generation AI model is used to optimize the data and correct inconsistencies. This process involves reviewing the logic of the instructions and combining appropriate parameters.

[0189] Step 3:

[0190] The server personalizes the settings data based on the analysis results of the emotion engine. The input is the user's emotional state data provided by the emotion engine, and the output is personalized settings data that is appropriate for the user's current situation. Specifically, the server adds detailed guidance information when the user is experiencing stress.

[0191] Step 4:

[0192] The server sends personalized configuration data to the terminal. The input is the generated configuration data, and the output is the data packets received by the terminal. To enhance communication reliability, redundant data checks are performed to prevent transmission errors.

[0193] Step 5:

[0194] The terminal receives configuration data sent from the server and begins analysis. The input is the received data, and the output is a set of specific instructions necessary for automatic configuration. The terminal verifies data integrity and supplements any missing information to efficiently execute the procedure.

[0195] Step 6:

[0196] The on-device emotion engine analyzes the user's emotional state in real time. Input is the user's voice tone and facial expression data, and output is the analysis result indicating the current emotional state. The emotion engine utilizes noise cancellation to remove ambient noise and perform accurate emotion analysis.

[0197] Step 7:

[0198] The device adjusts the setup process according to the user's emotional state. The input is the emotional state, which is updated in real time, and the output is a dynamic setup procedure to optimize the user experience. For example, if the user is feeling anxious, the device will display step-by-step instructions.

[0199] Step 8:

[0200] The terminal notifies the user of the progress of the setup process. Inputs include the completion rate and estimated time, while output is a notification message. Visual and audio information are combined to aid user understanding.

[0201] (Application Example 2)

[0202] 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".

[0203] In today's advanced information society, numerous devices and systems are used, making their setup and management increasingly complex. In particular, interactive settings based on user emotional states are difficult to implement, which can delay the adjustment of personalized living environments. Therefore, there is a need to provide a flexible and efficient setup process that takes user emotions into consideration.

[0204] 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.

[0205] In this invention, the server includes means for generating defined configuration information based on a configuration request received from an information processing device, means for transmitting the generated configuration information to the information processing device, and means for evaluating the user's emotional state using emotion analysis means and optimizing the configuration process based on the evaluation. This enables the automatic execution of personalized configurations that correspond to the user's emotional state.

[0206] An "information processing device" is a device used for inputting, processing, and outputting data, and includes computers and servers.

[0207] A "configuration request" is a request sent to an information processing device to perform specific settings or adjustments.

[0208] "Configuration information" refers to information that includes data and instructions necessary to control the operation and functions of an information processing device.

[0209] "Emotional analysis means" refers to functions or devices that analyze a user's voice, facial expressions, behavior, etc., and evaluate their emotional state.

[0210] "Evaluation" is the act of determining the value or state of something based on collected data and according to specific criteria.

[0211] "Optimizing the setup process" means adjusting the setup procedure efficiently and appropriately in order to improve the user experience.

[0212] "Controlling the living environment" refers to the act of adjusting physical environmental elements such as light, sound, and temperature to provide a comfortable living space.

[0213] A "history database" is a database that records past settings and their results, making them searchable and referential.

[0214] This invention relates to a system for optimizing the setting process in an information processing device based on the user's emotional state. The system includes a server, a terminal, and an emotion analysis means.

[0215] The server receives a configuration request from the information processing device and generates configuration information based on the database, in accordance with security standards and organizational policies. The generated configuration information is then sent to the terminal.

[0216] The device receives configuration information and automatically performs the configuration process, using emotion analysis tools to evaluate the user's emotional state in real time. This evaluation is performed, for example, by analyzing voice tone using Google® Cloud Speech-to-Text and analyzing facial expression data using the Google Cloud Vision API. Depending on the user's emotions, the device adjusts the configuration process and controls the living environment to provide a relaxed environment.

[0217] For example, if the device detects the user's stress level from their voice tone while they are at home, it will immediately change the lighting to a warmer color and play calming music.

[0218] When using a generative AI model, for example, it might generate prompts like this: "Based on sentiment analysis, what smart home commands should be generated to automatically set up a relaxing environment for the user who will be returning home soon?"

[0219] This makes it possible to automatically create a comfortable environment that is adapted to the individual emotional state of each user.

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

[0221] Step 1:

[0222] The server receives configuration requests sent from the information processing device. The input is the configuration request from the information processing device, and the output is the trigger for generating configuration information corresponding to the request. As part of the data processing, a process is performed to extract the request content as parameters.

[0223] Step 2:

[0224] The server references the database and generates appropriate configuration information based on security standards and organizational policies. Inputs are configuration requests and database information, while output is the generated configuration information. The configuration information is parsed based on the requests and customized according to the established standards.

[0225] Step 3:

[0226] The server sends the generated configuration information to the terminal. The input is the generated configuration information, and the output is the completion of transmission to the terminal. The data calculation includes the procedure of packetizing and transmitting the configuration information.

[0227] Step 4:

[0228] The terminal analyzes the configuration information received from the server and automatically executes the settings. The input is the configuration information from the server, and the output is the change in the configuration state. Specifically, the terminal changes device settings and user profiles.

[0229] Step 5:

[0230] The device uses emotion analysis to evaluate the user's voice tone and facial expressions in real time. Input is the user's voice and facial expression data, and output is the evaluation result of their emotional state. This utilizes voice analysis and facial recognition technologies.

[0231] Step 6:

[0232] The device optimizes the settings process and adjusts the living environment based on the evaluated emotional state. The input is the result of the emotional state evaluation, and the output is the change in the living environment settings. Specific actions include adjusting the lighting and playing music.

[0233] Step 7:

[0234] The terminal records the results of the implemented configuration in a history database. The input is the state data after the configuration change, and the output is an update to the history data. This step can be used for later troubleshooting.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] [Second Embodiment]

[0239] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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.

[0248] 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.

[0249] 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.

[0250] 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".

[0251] This invention is a system that automates the configuration of an information processing device using an AI agent, and consists of a central server, a terminal that performs configuration, and a user that makes configuration requests.

[0252] The server is responsible for centrally managing all configuration requests. Specifically, when a user sets up a new device or reconfigures an existing one, the server receives the relevant configuration requests. This includes network settings and security policy enforcement. The server refers to an internal database, generates appropriate configuration data based on the latest security standards and organizational policies, and sends it to the device.

[0253] The terminal has the ability to receive configuration data sent from the server, analyze it, and automatically implement specified configuration tasks. This process includes automatic configuration of network connections, installation of new software, and system security settings. Because it has a built-in AI agent, the terminal can maximize the efficiency of configuration tasks. Furthermore, the terminal records the results of configuration execution in a history database, making it available for future troubleshooting and auditing.

[0254] This system significantly reduces the burden on users. For example, when a user receives a new smartphone, it will automatically connect to the company network and have necessary applications and security settings installed with just a few simple steps. This allows users to start using the device immediately.

[0255] This system is particularly effective when deployed on a large scale in enterprise environments. It allows for consistent control of equipment management across the entire workforce, including the simultaneous configuration of new devices and the application of new policies to existing devices. Therefore, this system significantly contributes to increased productivity and reduced management costs.

[0256] The following describes the processing flow.

[0257] Step 1:

[0258] When a user needs to configure a new device or wants to reconfigure an existing one, they connect to the network and send a configuration request to the server. This request includes the device type and the required configuration information.

[0259] Step 2:

[0260] The server receives configuration requests from users and generates the necessary configuration data based on device identification information and requirements. The server references its internal, up-to-date security policies and standard configuration guidelines.

[0261] Step 3:

[0262] The server sends the generated configuration data to the specified terminal. This data includes instructions for configuration, network information, and information about the software to be installed.

[0263] Step 4:

[0264] The device receives configuration data sent from the server and uses an AI agent to analyze the data. Through this analysis, it identifies which settings are needed and determines their priority.

[0265] Step 5:

[0266] Based on the analysis results, the device will automatically begin configuration tasks. This includes configuring network settings, installing new applications, and updating existing security settings.

[0267] Step 6:

[0268] Once the terminal confirms that all configuration tasks are complete, it records the results in detail and saves them as a log file in the history database. The log includes the configuration tasks performed and their success status.

[0269] Step 7:

[0270] The server receives a notification from the terminal that the setup is complete and notifies the user that the setup was completed successfully. This allows the user to start using the device immediately.

[0271] (Example 1)

[0272] 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."

[0273] In today's information processing environments, rapid and consistent configuration management of numerous devices is essential. However, traditional manual configuration management is time-consuming, labor-intensive, and prone to errors. Therefore, improving the efficiency and accuracy of configuration work is a crucial challenge.

[0274] 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.

[0275] In this invention, the server includes means for generating defined configuration data based on a configuration request received from an information processing device, means for transmitting the generated configuration data to the information processing device, and means for analyzing the configuration data and automatically executing the necessary configurations in an adjacent information processing device. This enables rapid and consistent automatic configuration for a large number of devices.

[0276] An "information processing device" refers to a computer or device that processes, manages, and stores data.

[0277] A "configuration request" is an instruction from a user or system to change or apply settings to a device or software.

[0278] "Configuration data" refers to data containing specific settings applied to an information processing device.

[0279] An "adjacent information processing device" is an information processing device that is connected to a server via a network in order to receive and analyze configuration data.

[0280] A "database" is a collection of data that systematically stores settings, their execution results, and other information so that it can be referenced later.

[0281] An "AI agent" is a type of artificial intelligence that automatically performs processes involving learning and judgment for the purpose of improving the efficiency of setup operations.

[0282] A "security standard" is a rule or guideline established to ensure the security of information processing devices and data.

[0283] An "organization's policy" defines the standard procedures, rules, and guidelines applied within a specific organization.

[0284] "Fault countermeasures" refer to procedures and actions for resolving system malfunctions and abnormalities.

[0285] This invention is a system for automating the setup of an information processing device incorporating an AI agent. The system consists of a server, a terminal that executes the setup, and a user who issues a setup request.

[0286] The server receives a setup request from the information processing device. For example, when a user desires to set up a new device, the server analyzes the request in the database and executes the process of preparing appropriate setup data. The database incorporates the latest security standards and the organization's policy. The server transmits the generated setup data to the terminal.

[0287] The terminal has the ability to receive the setup data transmitted from the server, appropriately analyze the content, and automatically execute it. At this time, the AI agent发挥其效力,使设置工作更高效、准确地进行。具体而言,终端包括网络设置初始化、安装必要应用程序以及应用安全策略等操作。终端在设置完成后,还会将结果记录到历史数据库中,以供将来分析和故障排除使用。

[0288] When users receive a new device, they can initiate a setup request through the system, and the device will be ready for immediate use with minimal or no complex operations required. For example, when a user receives a new smartphone, they can perform a few simple steps to automatically connect the smartphone to the company network and quickly apply the necessary apps and settings.

[0289] An example of a prompt statement when using a generative AI model is the instruction, "Initialize network settings for new employees and install standard software." In this way, by utilizing generative AI models and prompt statements, the system can achieve highly efficient automation of configuration.

[0290] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0291] Step 1:

[0292] The user issues a configuration request.

[0293] When a user wants to configure a new device, they send a configuration request to the server via a dedicated application or web interface.

[0294] Input: The configuration request entered by the user.

[0295] Output: Configuration request data sent to the server.

[0296] Step 2:

[0297] The server receives and parses the request.

[0298] The server analyzes the configuration request received from the user. The server accesses an internal database to check the device type and the required configuration.

[0299] Input: Configuration request data submitted by the user.

[0300] Output: A list of configured settings based on the analysis and a template for the generated configuration data.

[0301] Step 3:

[0302] The server generates configuration data

[0303] The server generates the configuration data required for device configuration based on the analysis results. This includes network configuration information and security settings.

[0304] Input: Analysis results and reference data obtained from the database.

[0305] Output: Configuration data to be sent to the terminal.

[0306] Step 4:

[0307] The server sends the configuration data to the terminal

[0308] The server sends the generated configuration data to the appropriate terminal. The data is sent using a secure communication channel.

[0309] Input: Generated configuration data.

[0310] Output: Transmission of the configuration data to be received by the terminal.

[0311] Step 5:

[0312] The terminal receives and analyzes the configuration data

[0313] The terminal receives the configuration data sent from the server and analyzes its content. The AI agent supports the analysis process.

[0314] Input: Configuration data sent from the server.

[0315] Output: A list of setup steps.

[0316] Step 6:

[0317] The device will automatically perform the setup.

[0318] The device automatically performs the necessary configurations based on the analyzed setup procedures. This includes application installation and network configuration.

[0319] Input: A list of setup steps.

[0320] Output: The settings performed and their results.

[0321] Step 7:

[0322] The device records the settings results.

[0323] The device records the results of the settings performed in detail and stores them in a database. This allows for future troubleshooting and audits.

[0324] Input: The result of the settings that were applied.

[0325] Output: Settings history stored in the history database.

[0326] Step 8:

[0327] Notify the user that the setup is complete.

[0328] The user will be notified from their device that the setup is complete and will receive confirmation that the device is ready for immediate use.

[0329] Input: Notification of completion of setup from the device.

[0330] Output: Notification message to the user.

[0331] (Application Example 1)

[0332] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0333] In smart cities, when numerous information processing devices are deployed simultaneously, effectively and quickly managing the settings of these devices is crucial. However, traditional manual or partially automated configuration management is prone to errors and difficult to operate efficiently. Furthermore, sophisticated management methods are necessary to ensure configuration consistency while maintaining security. These challenges must be addressed to streamline the deployment and management of devices in public management systems.

[0334] 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.

[0335] In this invention, the server includes means for generating defined configuration data based on a configuration request received from an information processing device, means for transmitting the generated configuration data to the information processing device, and means for analyzing the configuration data and automatically executing the necessary configurations in a plurality of autonomously functioning terminals. This makes it possible to manage a plurality of information processing devices quickly and effectively.

[0336] An "information processing device" is a device that performs data input, processing, and output, and in particular has the function of sending configuration requests to a server, analyzing the received configuration data, and executing the process.

[0337] A "configuration request" refers to an instruction issued by a user or device to a server in order to change or define new settings for an information processing device.

[0338] "Configuration data" refers to specific configuration information that a server generates based on a configuration request and that an information processing device applies.

[0339] "Means" refers to processes or devices designed to achieve a specific function, and in this invention includes components that enable the generation, transmission, and execution of step-by-step settings.

[0340] A "server" is a computer system that provides services over a network, and its role is to receive configuration requests and generate appropriate configuration data.

[0341] A "history database" is a database that records the results of past configurations and stores information that can be referenced for future troubleshooting and auditing purposes.

[0342] "Real-time" means that there is virtually no delay between the occurrence of an event and its analysis, processing, and response, and in this invention, it enables immediate monitoring of the device's status.

[0343] This invention provides a system for efficiently managing the settings of information processing devices in smart cities. The system mainly consists of a server, terminals, and users.

[0344] The server functions as the central management unit on the network. Based on configuration requests received from users, the server first parses the requests and generates configuration data that complies with the organization's policies and environmental standards. The server then transmits this generated data to numerous autonomous terminals. As hardware, the server is equipped with a high-performance processor and sufficient memory, and uses a database management system (e.g., SQL Server) to process and store historical data.

[0345] The terminal analyzes configuration data received from the server and automatically performs the necessary settings on the target device. The terminal also monitors the results of each configuration operation in real time and sends the data to the server's history database. The terminal is equipped with AI agent software and uses a machine learning model (generative AI model) in response to prompts to determine the optimal configuration method.

[0346] As an administrator operating the system, the user can initiate the entire setup process by entering simple prompts into the system. Specifically, by sending a prompt such as "New camera setup (resolution: 1080p, frame rate: 30fps)" to the server, the server will respond immediately and automatically proceed with the setup process.

[0347] This system streamlines the management of complex and extensive devices in smart cities, minimizing configuration errors. It also maintains reliability and efficiency even in mass deployments.

[0348] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0349] Step 1:

[0350] The server parses the prompt message received from the user. It receives a prompt message (e.g., "New Camera Setup") as input and extracts the necessary configuration parameters based on it. It uses a generative AI model to select a template suitable for the configuration. The output is generated configuration data, including the configuration template.

[0351] Step 2:

[0352] The server creates a detailed configuration file based on the generated configuration data. This process verifies the configuration in accordance with environmental standards and organizational policies, and confirms compliance with security standards. The output is a detailed configuration file ready to be sent to the terminal.

[0353] Step 3:

[0354] The server sends a detailed configuration file to multiple terminals over the network. Each terminal receives the configuration file, parses it, and automatically starts the necessary hardware configuration and software installation. The input to each terminal is the received configuration file, and the output is the progress of the configuration process.

[0355] Step 4:

[0356] The terminal monitors the configuration progress in real time and sends feedback to the server if any errors or configuration inconsistencies occur. This process verifies the completion status of each configuration and prepares to record it in the history database.

[0357] Step 5:

[0358] The terminal sends the result to the server once the setup is successfully completed. The server receives this and stores it in its history database. The input is the completion report from the terminal, and the output is the recorded history data.

[0359] Step 6:

[0360] Users can audit device configurations and past change history by accessing the server and checking the history database. The input for this step is a request to access the database, and the output is a set of historical information provided to the user.

[0361] 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.

[0362] This invention provides a personalized configuration experience by combining a system that automates the configuration of information processing equipment with an emotion engine that recognizes user emotions. The system mainly consists of a server, a terminal, and an emotion engine.

[0363] The server receives configuration requests from each information processing device and is responsible for generating appropriate configuration data. Based on the database, the server references security standards and organizational policies to prepare configuration information according to the request. This configuration data is personalized based on the analysis results of the sentiment engine.

[0364] The device receives configuration data sent from the server and automatically performs the configuration process. During this process, the emotion engine on the device analyzes the user's emotional state in real time. The emotion engine analyzes user input such as voice tone and facial expressions to determine whether the user is relaxed or stressed.

[0365] Depending on the user's emotional state, the device optimizes the setup process. For example, if the user is stressed, it provides more detailed notifications to aid understanding, while if the user is relaxed, it completes the setup more quickly. This allows the user to have a flexible setup experience tailored to their situation.

[0366] For example, when a user is setting up a new laptop, if the emotion engine detects stress from the user's tone of voice, the device will add a step that explains the setup process in detail. Conversely, if the emotion engine detects positive emotions, it will simplify notifications and shorten the setup time. This improves the user experience while maintaining formal consistency.

[0367] The following describes the processing flow.

[0368] Step 1:

[0369] To begin setting up a new device, the user connects the device to the network and sends a setup request to the server via the terminal. This request may include assistance with necessary customization information and the user's current emotional state.

[0370] Step 2:

[0371] The server receives configuration requests from users and generates configuration data based on those requests, taking into account the device's characteristics and the organization's policies. In doing so, the server incorporates configuration information to ensure compliance with the latest security standards.

[0372] Step 3:

[0373] The server sends the generated configuration data to the terminal. This data includes network settings, a list of recommended applications, and security settings.

[0374] Step 4:

[0375] The device receives configuration data sent from the server and activates an emotion engine to analyze the user's emotional state in real time. It identifies the user's emotions using speech recognition and facial expression analysis via a camera.

[0376] Step 5:

[0377] The device adjusts the setup process based on the analysis results of the emotion engine. For example, if it determines that the user is stressed, it provides detailed guidance to make the process easier to understand. Conversely, if the user is relaxed, it simplifies the setup procedure and allows for quick execution.

[0378] Step 6:

[0379] Once the setup is complete, the device records the results in detail and saves them to a history database. This allows for future troubleshooting and reference of the history.

[0380] Step 7:

[0381] The server receives completion notifications from the terminal and notifies the user of the completion status of the setup. Based on feedback from the emotion engine, the notification is provided in an appropriate format. For example, if the user was stressed, the server will provide an announcement that explains in detail the benefits of completing the setup and the next steps.

[0382] (Example 2)

[0383] 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".

[0384] In modern information processing systems, providing a personalized setup experience tailored to each user's individual needs and emotional state is crucial for improving user satisfaction. However, conventional systems lacked the technology to automatically optimize the setup process based on user emotions, resulting in a failure to adequately respond to situations where users felt stressed or, conversely, relaxed.

[0385] 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.

[0386] In this invention, the server includes means for generating defined configuration data based on configuration requests received from an information processing device, means for analyzing the user's emotional state and personalizing the configuration data based on that emotional analysis, and means for adjusting the configuration process according to the user's emotional state and optimizing the user experience. This makes it possible to provide a flexible configuration experience that responds to the user's emotions.

[0387] An "information processing device" is a general term for a device that has the functions of inputting, processing, storing, and outputting data.

[0388] A "configuration request" is a request that specifies the instructions or conditions necessary for an information processing device to operate according to specific conditions or parameters.

[0389] "Configuration data" refers to a dataset containing specific parameters and conditions necessary to control the operation of an information processing device.

[0390] "Adjacent information processing devices" refer to information processing devices that can communicate directly with each other via a network or physical connection.

[0391] "Analysis" is the act of extracting received data or information and converting it into a form that is easy to understand.

[0392] "Emotional state" refers to the user's psychological and physiological responses, and is an indicator that indicates their emotions at that time.

[0393] Personalization is the process of optimizing information and services to suit the individual needs and circumstances of each user, and adjusting them to be individually adapted.

[0394] A "history database" is a type of database used to store records of past operation results, events, and configuration data.

[0395] "Troubleshooting" is a method for diagnosing system or equipment failures and problems and finding solutions.

[0396] This invention is a system that automates the settings of an information processing device according to the user's emotional state, thereby providing a personalized experience. It mainly consists of a server, a terminal, and an emotion engine. Details of each element are as follows:

[0397] The server receives configuration requests from information processing devices via the network. Based on these requests, the server accesses the database and generates appropriate configuration data while referencing security standards and organizational policies. By utilizing a generative AI model, efficient generation and optimization of configuration data are achieved. This generated data is then personalized based on user sentiment analysis obtained through an emotion engine.

[0398] The terminal receives configuration data sent from the server and automatically performs the configuration process. An emotion engine integrated into the terminal analyzes the user's voice tone and facial expressions to understand their emotional state in real time. The emotion engine determines the user's level of tension or relaxation and adjusts the configuration process accordingly.

[0399] As a concrete example, consider the scenario of setting up a new computer. When a user unboxes the new computer and begins the initial setup, the device's built-in emotion engine detects from the user's tone of voice that they are feeling stressed. In this case, the device displays additional information to make the setup process easier to understand. On the other hand, if the user is relaxed, notifications are simplified, and the setup time is shortened.

[0400] An example of a prompt for a generative AI model would be, "If a user is setting up a new computer in a relaxed state, how should you optimize the setup process?" This prompt allows the generative AI model to provide optimal setup instructions that take emotional states into account.

[0401] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0402] Step 1:

[0403] The server receives configuration requests from information processing devices. The input is a configuration request sent over the network, which includes the device type and required configuration items. As output, the server parses the received requests and extracts the appropriate information for the next processing step. Specifically, it determines the priority of the requests and identifies which configuration data is needed.

[0404] Step 2:

[0405] The server accesses the database and generates appropriate configuration data in response to configuration requests. The input is the parsed request content, and the output is configuration data that conforms to security standards and organizational policies. A generation AI model is used to optimize the data and correct inconsistencies. This process involves reviewing the logic of the instructions and combining appropriate parameters.

[0406] Step 3:

[0407] The server personalizes the settings data based on the analysis results of the emotion engine. The input is the user's emotional state data provided by the emotion engine, and the output is personalized settings data that is appropriate for the user's current situation. Specifically, the server adds detailed guidance information when the user is experiencing stress.

[0408] Step 4:

[0409] The server sends personalized configuration data to the terminal. The input is the generated configuration data, and the output is the data packets received by the terminal. To enhance communication reliability, redundant data checks are performed to prevent transmission errors.

[0410] Step 5:

[0411] The terminal receives configuration data sent from the server and begins analysis. The input is the received data, and the output is a set of specific instructions necessary for automatic configuration. The terminal verifies data integrity and supplements any missing information to efficiently execute the procedure.

[0412] Step 6:

[0413] The on-device emotion engine analyzes the user's emotional state in real time. Input is the user's voice tone and facial expression data, and output is the analysis result indicating the current emotional state. The emotion engine utilizes noise cancellation to remove ambient noise and perform accurate emotion analysis.

[0414] Step 7:

[0415] The device adjusts the setup process according to the user's emotional state. The input is the emotional state, which is updated in real time, and the output is a dynamic setup procedure to optimize the user experience. For example, if the user is feeling anxious, the device will display step-by-step instructions.

[0416] Step 8:

[0417] The terminal notifies the user of the progress of the setup process. Inputs include the completion rate and estimated time, while output is a notification message. Visual and audio information are combined to aid user understanding.

[0418] (Application Example 2)

[0419] 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 as the "terminal".

[0420] In today's advanced information society, numerous devices and systems are used, making their setup and management increasingly complex. In particular, interactive settings based on user emotional states are difficult to implement, which can delay the adjustment of personalized living environments. Therefore, there is a need to provide a flexible and efficient setup process that takes user emotions into consideration.

[0421] 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.

[0422] In this invention, the server includes means for generating defined configuration information based on a configuration request received from an information processing device, means for transmitting the generated configuration information to the information processing device, and means for evaluating the user's emotional state using emotion analysis means and optimizing the configuration process based on the evaluation. This enables the automatic execution of personalized configurations that correspond to the user's emotional state.

[0423] An "information processing device" is a device used for inputting, processing, and outputting data, and includes computers and servers.

[0424] A "configuration request" is a request sent to an information processing device to perform specific settings or adjustments.

[0425] "Configuration information" refers to information that includes data and instructions necessary to control the operation and functions of an information processing device.

[0426] "Emotional analysis means" refers to functions or devices that analyze a user's voice, facial expressions, behavior, etc., and evaluate their emotional state.

[0427] "Evaluation" is the act of determining the value or state of something based on collected data and according to specific criteria.

[0428] "Optimizing the setup process" means adjusting the setup procedure efficiently and appropriately in order to improve the user experience.

[0429] "Controlling the living environment" refers to the act of adjusting physical environmental elements such as light, sound, and temperature to provide a comfortable living space.

[0430] A "history database" is a database that records past settings and their results, making them searchable and referential.

[0431] This invention relates to a system for optimizing the setting process in an information processing device based on the user's emotional state. The system includes a server, a terminal, and an emotion analysis means.

[0432] The server receives a configuration request from the information processing device and generates configuration information based on the database, in accordance with security standards and organizational policies. The generated configuration information is then sent to the terminal.

[0433] The device receives configuration information and automatically performs the setup process, while simultaneously evaluating the user's emotional state in real time using emotion analysis tools. This evaluation is performed, for example, by analyzing voice tone using Google Cloud Speech-to-Text and analyzing facial expression data using the Google Cloud Vision API. Depending on the user's emotions, the device adjusts the setup process and controls the living environment to provide a relaxed environment.

[0434] For example, if the device detects the user's stress level from their voice tone while they are at home, it will immediately change the lighting to a warmer color and play calming music.

[0435] When using a generative AI model, for example, it might generate prompts like this: "Based on sentiment analysis, what smart home commands should be generated to automatically set up a relaxing environment for the user who will be returning home soon?"

[0436] This makes it possible to automatically create a comfortable environment that is adapted to the individual emotional state of each user.

[0437] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0438] Step 1:

[0439] The server receives configuration requests sent from the information processing device. The input is the configuration request from the information processing device, and the output is the trigger for generating configuration information corresponding to the request. As part of the data processing, a process is performed to extract the request content as parameters.

[0440] Step 2:

[0441] The server references the database and generates appropriate configuration information based on security standards and organizational policies. Inputs are configuration requests and database information, while output is the generated configuration information. The configuration information is parsed based on the requests and customized according to the established standards.

[0442] Step 3:

[0443] The server sends the generated configuration information to the terminal. The input is the generated configuration information, and the output is the completion of transmission to the terminal. The data calculation includes the procedure of packetizing and transmitting the configuration information.

[0444] Step 4:

[0445] The terminal analyzes the configuration information received from the server and automatically executes the settings. The input is the configuration information from the server, and the output is the change in the configuration state. Specifically, the terminal changes device settings and user profiles.

[0446] Step 5:

[0447] The device uses emotion analysis to evaluate the user's voice tone and facial expressions in real time. Input is the user's voice and facial expression data, and output is the evaluation result of their emotional state. This utilizes voice analysis and facial recognition technologies.

[0448] Step 6:

[0449] The device optimizes the settings process and adjusts the living environment based on the evaluated emotional state. The input is the result of the emotional state evaluation, and the output is the change in the living environment settings. Specific actions include adjusting the lighting and playing music.

[0450] Step 7:

[0451] The terminal records the results of the implemented configuration in a history database. The input is the state data after the configuration change, and the output is an update to the history data. This step can be used for later troubleshooting.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] [Third Embodiment]

[0456] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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).

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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".

[0468] This invention is a system that automates the configuration of an information processing device using an AI agent, and consists of a central server, a terminal that performs configuration, and a user that makes configuration requests.

[0469] The server is responsible for centrally managing all configuration requests. Specifically, when a user sets up a new device or reconfigures an existing one, the server receives the relevant configuration requests. This includes network settings and security policy enforcement. The server refers to an internal database, generates appropriate configuration data based on the latest security standards and organizational policies, and sends it to the device.

[0470] The terminal has the ability to receive configuration data sent from the server, analyze it, and automatically implement specified configuration tasks. This process includes automatic configuration of network connections, installation of new software, and system security settings. Because it has a built-in AI agent, the terminal can maximize the efficiency of configuration tasks. Furthermore, the terminal records the results of configuration execution in a history database, making it available for future troubleshooting and auditing.

[0471] This system significantly reduces the burden on users. For example, when a user receives a new smartphone, it will automatically connect to the company network and have necessary applications and security settings installed with just a few simple steps. This allows users to start using the device immediately.

[0472] This system is particularly effective when deployed on a large scale in enterprise environments. It allows for consistent control of equipment management across the entire workforce, including the simultaneous configuration of new devices and the application of new policies to existing devices. Therefore, this system significantly contributes to increased productivity and reduced management costs.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] When a user needs to configure a new device or wants to reconfigure an existing one, they connect to the network and send a configuration request to the server. This request includes the device type and the required configuration information.

[0476] Step 2:

[0477] The server receives configuration requests from users and generates the necessary configuration data based on device identification information and requirements. The server references its internal, up-to-date security policies and standard configuration guidelines.

[0478] Step 3:

[0479] The server sends the generated configuration data to the specified terminal. This data includes instructions for configuration, network information, and information about the software to be installed.

[0480] Step 4:

[0481] The device receives configuration data sent from the server and uses an AI agent to analyze the data. Through this analysis, it identifies which settings are needed and determines their priority.

[0482] Step 5:

[0483] Based on the analysis results, the device will automatically begin configuration tasks. This includes configuring network settings, installing new applications, and updating existing security settings.

[0484] Step 6:

[0485] Once the terminal confirms that all configuration tasks are complete, it records the results in detail and saves them as a log file in the history database. The log includes the configuration tasks performed and their success status.

[0486] Step 7:

[0487] The server receives a notification from the terminal that the setup is complete and notifies the user that the setup was completed successfully. This allows the user to start using the device immediately.

[0488] (Example 1)

[0489] 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."

[0490] In today's information processing environments, rapid and consistent configuration management of numerous devices is essential. However, traditional manual configuration management is time-consuming, labor-intensive, and prone to errors. Therefore, improving the efficiency and accuracy of configuration work is a crucial challenge.

[0491] 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.

[0492] In this invention, the server includes means for generating defined configuration data based on a configuration request received from an information processing device, means for transmitting the generated configuration data to the information processing device, and means for analyzing the configuration data and automatically executing the necessary configurations in an adjacent information processing device. This enables rapid and consistent automatic configuration for a large number of devices.

[0493] An "information processing device" refers to a computer or device that processes, manages, and stores data.

[0494] A "configuration request" is an instruction from a user or system to change or apply settings to a device or software.

[0495] "Configuration data" refers to data containing specific settings applied to an information processing device.

[0496] An "adjacent information processing device" is an information processing device that is connected to a server via a network in order to receive and analyze configuration data.

[0497] A "database" is a collection of data that systematically stores settings, their execution results, and other information so that it can be referenced later.

[0498] An "AI agent" is a type of artificial intelligence that automatically performs processes involving learning and decision-making, with the aim of streamlining setup tasks.

[0499] "Security standards" are rules and guidelines established to ensure the security of information processing equipment and data.

[0500] "Organizational policies" define the standard procedures, rules, and guidelines that are in place within a particular organization.

[0501] "Troubleshooting" refers to the procedures and actions taken to resolve system malfunctions and anomalies.

[0502] This invention is an automated configuration system for an information processing device incorporating an AI agent. The system consists of a server, a terminal that performs configuration, and a user that sends configuration requests.

[0503] The server receives configuration requests from information processing devices. For example, if a user wants to configure a new device, the server parses the request in the database and prepares the appropriate configuration data. The database incorporates the latest security standards and organizational policies. The server then sends the generated configuration data to the device.

[0504] The terminal has the ability to receive configuration data sent from the server, appropriately analyze its contents, and execute actions automatically. In this process, an AI agent plays a crucial role, making the configuration work more efficient and accurate. Specifically, the terminal performs operations such as initializing network settings, installing necessary applications, and applying security policies. Furthermore, after completing the configuration, the terminal records the results in a history database for future analysis and troubleshooting.

[0505] When users receive a new device, they can initiate a setup request through the system, and the device will be ready for immediate use with minimal or no complex operations required. For example, when a user receives a new smartphone, they can perform a few simple steps to automatically connect the smartphone to the company network and quickly apply the necessary apps and settings.

[0506] An example of a prompt statement when using a generative AI model is the instruction, "Initialize network settings for new employees and install standard software." In this way, by utilizing generative AI models and prompt statements, the system can achieve highly efficient automation of configuration.

[0507] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0508] Step 1:

[0509] The user issues a configuration request.

[0510] When a user wants to configure a new device, they send a configuration request to the server via a dedicated application or web interface.

[0511] Input: The configuration request entered by the user.

[0512] Output: Configuration request data sent to the server.

[0513] Step 2:

[0514] The server receives and parses the request.

[0515] The server analyzes the configuration request received from the user. The server accesses an internal database to check the device type and the required configuration.

[0516] Input: Configuration request data submitted by the user.

[0517] Output: A list of settings based on the analysis and a template for the generated configuration data.

[0518] Step 3:

[0519] The server generates configuration data.

[0520] Based on the analysis results, the server generates the configuration data necessary for setting up the device. This includes network configuration information and security configurations.

[0521] Input: Analysis results and reference data obtained from the database.

[0522] Output: Configuration data to be sent to the terminal.

[0523] Step 4:

[0524] Sending configuration data from the server to the terminal.

[0525] The server sends the generated configuration data to the appropriate terminal. The data is transmitted using a secure communication channel.

[0526] Input: Generated configuration data.

[0527] Output: Sends configuration data that the terminal should receive.

[0528] Step 5:

[0529] The device receives and analyzes the configuration data.

[0530] The terminal receives configuration data sent from the server and analyzes its contents. An AI agent supports the analysis process.

[0531] Input: Configuration data sent from the server.

[0532] Output: A list of setup steps.

[0533] Step 6:

[0534] The device will automatically perform the setup.

[0535] The device automatically performs the necessary configurations based on the analyzed setup procedures. This includes application installation and network configuration.

[0536] Input: A list of setup steps.

[0537] Output: The settings performed and their results.

[0538] Step 7:

[0539] The device records the settings results.

[0540] The device records the results of the settings performed in detail and stores them in a database. This allows for future troubleshooting and audits.

[0541] Input: The result of the settings that were applied.

[0542] Output: Settings history stored in the history database.

[0543] Step 8:

[0544] Notify the user that the setup is complete.

[0545] The user will be notified from their device that the setup is complete and will receive confirmation that the device is ready for immediate use.

[0546] Input: Notification of completion of setup from the device.

[0547] Output: Notification message to the user.

[0548] (Application Example 1)

[0549] 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."

[0550] In smart cities, when numerous information processing devices are deployed simultaneously, effectively and quickly managing the settings of these devices is crucial. However, traditional manual or partially automated configuration management is prone to errors and difficult to operate efficiently. Furthermore, sophisticated management methods are necessary to ensure configuration consistency while maintaining security. These challenges must be addressed to streamline the deployment and management of devices in public management systems.

[0551] 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.

[0552] In this invention, the server includes means for generating defined configuration data based on a configuration request received from an information processing device, means for transmitting the generated configuration data to the information processing device, and means for analyzing the configuration data and automatically executing the necessary configurations in a plurality of autonomously functioning terminals. This makes it possible to manage a plurality of information processing devices quickly and effectively.

[0553] An "information processing device" is a device that performs data input, processing, and output, and in particular has the function of sending configuration requests to a server, analyzing the received configuration data, and executing the process.

[0554] A "configuration request" refers to an instruction issued by a user or device to a server in order to change or define new settings for an information processing device.

[0555] "Configuration data" refers to specific configuration information that a server generates based on a configuration request and that an information processing device applies.

[0556] "Means" refers to processes or devices designed to achieve a specific function, and in this invention includes components that enable the generation, transmission, and execution of step-by-step settings.

[0557] A "server" is a computer system that provides services over a network, and its role is to receive configuration requests and generate appropriate configuration data.

[0558] A "history database" is a database that records the results of past configurations and stores information that can be referenced for future troubleshooting and auditing purposes.

[0559] "Real-time" means that there is virtually no delay between the occurrence of an event and its analysis, processing, and response, and in this invention, it enables immediate monitoring of the device's status.

[0560] This invention provides a system for efficiently managing the settings of information processing devices in smart cities. The system mainly consists of a server, terminals, and users.

[0561] The server functions as the central management unit on the network. Based on configuration requests received from users, the server first parses the requests and generates configuration data that complies with the organization's policies and environmental standards. The server then transmits this generated data to numerous autonomous terminals. As hardware, the server is equipped with a high-performance processor and sufficient memory, and uses a database management system (e.g., SQL Server) to process and store historical data.

[0562] The terminal analyzes configuration data received from the server and automatically performs the necessary settings on the target device. The terminal also monitors the results of each configuration operation in real time and sends the data to the server's history database. The terminal is equipped with AI agent software and uses a machine learning model (generative AI model) in response to prompts to determine the optimal configuration method.

[0563] As an administrator operating the system, the user can initiate the entire setup process by entering simple prompts into the system. Specifically, by sending a prompt such as "New camera setup (resolution: 1080p, frame rate: 30fps)" to the server, the server will respond immediately and automatically proceed with the setup process.

[0564] This system streamlines the management of complex and extensive devices in smart cities, minimizing configuration errors. It also maintains reliability and efficiency even in mass deployments.

[0565] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0566] Step 1:

[0567] The server parses the prompt message received from the user. It receives a prompt message (e.g., "New Camera Setup") as input and extracts the necessary configuration parameters based on it. It uses a generative AI model to select a template suitable for the configuration. The output is generated configuration data, including the configuration template.

[0568] Step 2:

[0569] The server creates a detailed configuration file based on the generated configuration data. This process verifies the configuration in accordance with environmental standards and organizational policies, and confirms compliance with security standards. The output is a detailed configuration file ready to be sent to the terminal.

[0570] Step 3:

[0571] The server sends a detailed configuration file to multiple terminals over the network. Each terminal receives the configuration file, parses it, and automatically starts the necessary hardware configuration and software installation. The input to each terminal is the received configuration file, and the output is the progress of the configuration process.

[0572] Step 4:

[0573] The terminal monitors the configuration progress in real time and sends feedback to the server if any errors or configuration inconsistencies occur. This process verifies the completion status of each configuration and prepares to record it in the history database.

[0574] Step 5:

[0575] The terminal sends the result to the server once the setup is successfully completed. The server receives this and stores it in its history database. The input is the completion report from the terminal, and the output is the recorded history data.

[0576] Step 6:

[0577] Users can audit device configurations and past change history by accessing the server and checking the history database. The input for this step is a request to access the database, and the output is a set of historical information provided to the user.

[0578] 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.

[0579] This invention provides a personalized configuration experience by combining a system that automates the configuration of information processing equipment with an emotion engine that recognizes user emotions. The system mainly consists of a server, a terminal, and an emotion engine.

[0580] The server receives configuration requests from each information processing device and is responsible for generating appropriate configuration data. Based on the database, the server references security standards and organizational policies to prepare configuration information according to the request. This configuration data is personalized based on the analysis results of the sentiment engine.

[0581] The device receives configuration data sent from the server and automatically performs the configuration process. During this process, the emotion engine on the device analyzes the user's emotional state in real time. The emotion engine analyzes user input such as voice tone and facial expressions to determine whether the user is relaxed or stressed.

[0582] Depending on the user's emotional state, the device optimizes the setup process. For example, if the user is stressed, it provides more detailed notifications to aid understanding, while if the user is relaxed, it completes the setup more quickly. This allows the user to have a flexible setup experience tailored to their situation.

[0583] For example, when a user is setting up a new laptop, if the emotion engine detects stress from the user's tone of voice, the device will add a step that explains the setup process in detail. Conversely, if the emotion engine detects positive emotions, it will simplify notifications and shorten the setup time. This improves the user experience while maintaining formal consistency.

[0584] The following describes the processing flow.

[0585] Step 1:

[0586] To begin setting up a new device, the user connects the device to the network and sends a setup request to the server via the terminal. This request may include assistance with necessary customization information and the user's current emotional state.

[0587] Step 2:

[0588] The server receives configuration requests from users and generates configuration data based on those requests, taking into account the device's characteristics and the organization's policies. In doing so, the server incorporates configuration information to ensure compliance with the latest security standards.

[0589] Step 3:

[0590] The server sends the generated configuration data to the terminal. This data includes network settings, a list of recommended applications, and security settings.

[0591] Step 4:

[0592] The device receives configuration data sent from the server and activates an emotion engine to analyze the user's emotional state in real time. It identifies the user's emotions using speech recognition and facial expression analysis via a camera.

[0593] Step 5:

[0594] The device adjusts the setup process based on the analysis results of the emotion engine. For example, if it determines that the user is stressed, it provides detailed guidance to make the process easier to understand. Conversely, if the user is relaxed, it simplifies the setup procedure and allows for quick execution.

[0595] Step 6:

[0596] Once the setup is complete, the device records the results in detail and saves them to a history database. This allows for future troubleshooting and reference of the history.

[0597] Step 7:

[0598] The server receives completion notifications from the terminal and notifies the user of the completion status of the setup. Based on feedback from the emotion engine, the notification is provided in an appropriate format. For example, if the user was stressed, the server will provide an announcement that explains in detail the benefits of completing the setup and the next steps.

[0599] (Example 2)

[0600] 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."

[0601] In modern information processing systems, providing a personalized setup experience tailored to each user's individual needs and emotional state is crucial for improving user satisfaction. However, conventional systems lacked the technology to automatically optimize the setup process based on user emotions, resulting in a failure to adequately respond to situations where users felt stressed or, conversely, relaxed.

[0602] 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.

[0603] In this invention, the server includes means for generating defined configuration data based on configuration requests received from an information processing device, means for analyzing the user's emotional state and personalizing the configuration data based on that emotional analysis, and means for adjusting the configuration process according to the user's emotional state and optimizing the user experience. This makes it possible to provide a flexible configuration experience that responds to the user's emotions.

[0604] An "information processing device" is a general term for a device that has the functions of inputting, processing, storing, and outputting data.

[0605] A "configuration request" is a request that specifies the instructions or conditions necessary for an information processing device to operate according to specific conditions or parameters.

[0606] "Configuration data" refers to a dataset containing specific parameters and conditions necessary to control the operation of an information processing device.

[0607] "Adjacent information processing devices" refer to information processing devices that can communicate directly with each other via a network or physical connection.

[0608] "Analysis" is the act of extracting received data or information and converting it into a form that is easy to understand.

[0609] "Emotional state" refers to the user's psychological and physiological responses, and is an indicator that indicates their emotions at that time.

[0610] Personalization is the process of optimizing information and services to suit the individual needs and circumstances of each user, and adjusting them to be individually adapted.

[0611] A "history database" is a type of database used to store records of past operation results, events, and configuration data.

[0612] "Troubleshooting" is a method for diagnosing system or equipment failures and problems and finding solutions.

[0613] This invention is a system that automates the settings of an information processing device according to the user's emotional state, thereby providing a personalized experience. It mainly consists of a server, a terminal, and an emotion engine. Details of each element are as follows:

[0614] The server receives configuration requests from information processing devices via the network. Based on these requests, the server accesses the database and generates appropriate configuration data while referencing security standards and organizational policies. By utilizing a generative AI model, efficient generation and optimization of configuration data are achieved. This generated data is then personalized based on user sentiment analysis obtained through an emotion engine.

[0615] The terminal receives configuration data sent from the server and automatically performs the configuration process. An emotion engine integrated into the terminal analyzes the user's voice tone and facial expressions to understand their emotional state in real time. The emotion engine determines the user's level of tension or relaxation and adjusts the configuration process accordingly.

[0616] As a concrete example, consider the scenario of setting up a new computer. When a user unboxes the new computer and begins the initial setup, the device's built-in emotion engine detects from the user's tone of voice that they are feeling stressed. In this case, the device displays additional information to make the setup process easier to understand. On the other hand, if the user is relaxed, notifications are simplified, and the setup time is shortened.

[0617] An example of a prompt for a generative AI model would be, "If a user is setting up a new computer in a relaxed state, how should you optimize the setup process?" This prompt allows the generative AI model to provide optimal setup instructions that take emotional states into account.

[0618] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0619] Step 1:

[0620] The server receives configuration requests from information processing devices. The input is a configuration request sent over the network, which includes the device type and required configuration items. As output, the server parses the received requests and extracts the appropriate information for the next processing step. Specifically, it determines the priority of the requests and identifies which configuration data is needed.

[0621] Step 2:

[0622] The server accesses the database and generates appropriate configuration data in response to configuration requests. The input is the parsed request content, and the output is configuration data that conforms to security standards and organizational policies. A generation AI model is used to optimize the data and correct inconsistencies. This process involves reviewing the logic of the instructions and combining appropriate parameters.

[0623] Step 3:

[0624] The server personalizes the settings data based on the analysis results of the emotion engine. The input is the user's emotional state data provided by the emotion engine, and the output is personalized settings data that is appropriate for the user's current situation. Specifically, the server adds detailed guidance information when the user is experiencing stress.

[0625] Step 4:

[0626] The server sends personalized configuration data to the terminal. The input is the generated configuration data, and the output is the data packets received by the terminal. To enhance communication reliability, redundant data checks are performed to prevent transmission errors.

[0627] Step 5:

[0628] The terminal receives configuration data sent from the server and begins analysis. The input is the received data, and the output is a set of specific instructions necessary for automatic configuration. The terminal verifies data integrity and supplements any missing information to efficiently execute the procedure.

[0629] Step 6:

[0630] The on-device emotion engine analyzes the user's emotional state in real time. Input is the user's voice tone and facial expression data, and output is the analysis result indicating the current emotional state. The emotion engine utilizes noise cancellation to remove ambient noise and perform accurate emotion analysis.

[0631] Step 7:

[0632] The device adjusts the setup process according to the user's emotional state. The input is the emotional state, which is updated in real time, and the output is a dynamic setup procedure to optimize the user experience. For example, if the user is feeling anxious, the device will display step-by-step instructions.

[0633] Step 8:

[0634] The terminal notifies the user of the progress of the setup process. Inputs include the completion rate and estimated time, while output is a notification message. Visual and audio information are combined to aid user understanding.

[0635] (Application Example 2)

[0636] 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."

[0637] In today's advanced information society, numerous devices and systems are used, making their setup and management increasingly complex. In particular, interactive settings based on user emotional states are difficult to implement, which can delay the adjustment of personalized living environments. Therefore, there is a need to provide a flexible and efficient setup process that takes user emotions into consideration.

[0638] 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.

[0639] In this invention, the server includes means for generating defined configuration information based on a configuration request received from an information processing device, means for transmitting the generated configuration information to the information processing device, and means for evaluating the user's emotional state using emotion analysis means and optimizing the configuration process based on the evaluation. This enables the automatic execution of personalized configurations that correspond to the user's emotional state.

[0640] An "information processing device" is a device used for inputting, processing, and outputting data, and includes computers and servers.

[0641] A "configuration request" is a request sent to an information processing device to perform specific settings or adjustments.

[0642] "Configuration information" refers to information that includes data and instructions necessary to control the operation and functions of an information processing device.

[0643] "Emotional analysis means" refers to functions or devices that analyze a user's voice, facial expressions, behavior, etc., and evaluate their emotional state.

[0644] "Evaluation" is the act of determining the value or state of something based on collected data and according to specific criteria.

[0645] "Optimizing the setup process" means adjusting the setup procedure efficiently and appropriately in order to improve the user experience.

[0646] "Controlling the living environment" refers to the act of adjusting physical environmental elements such as light, sound, and temperature to provide a comfortable living space.

[0647] A "history database" is a database that records past settings and their results, making them searchable and referential.

[0648] This invention relates to a system for optimizing the setting process in an information processing device based on the user's emotional state. The system includes a server, a terminal, and an emotion analysis means.

[0649] The server receives a configuration request from the information processing device and generates configuration information based on the database, in accordance with security standards and organizational policies. The generated configuration information is then sent to the terminal.

[0650] The device receives configuration information and automatically performs the setup process, while simultaneously evaluating the user's emotional state in real time using emotion analysis tools. This evaluation is performed, for example, by analyzing voice tone using Google Cloud Speech-to-Text and analyzing facial expression data using the Google Cloud Vision API. Depending on the user's emotions, the device adjusts the setup process and controls the living environment to provide a relaxed environment.

[0651] For example, if the device detects the user's stress level from their voice tone while they are at home, it will immediately change the lighting to a warmer color and play calming music.

[0652] When using a generative AI model, for example, it might generate prompts like this: "Based on sentiment analysis, what smart home commands should be generated to automatically set up a relaxing environment for the user who will be returning home soon?"

[0653] This makes it possible to automatically create a comfortable environment that is adapted to the individual emotional state of each user.

[0654] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0655] Step 1:

[0656] The server receives configuration requests sent from the information processing device. The input is the configuration request from the information processing device, and the output is the trigger for generating configuration information corresponding to the request. As part of the data processing, a process is performed to extract the request content as parameters.

[0657] Step 2:

[0658] The server references the database and generates appropriate configuration information based on security standards and organizational policies. Inputs are configuration requests and database information, while output is the generated configuration information. The configuration information is parsed based on the requests and customized according to the established standards.

[0659] Step 3:

[0660] The server sends the generated configuration information to the terminal. The input is the generated configuration information, and the output is the completion of transmission to the terminal. The data calculation includes the procedure of packetizing and transmitting the configuration information.

[0661] Step 4:

[0662] The terminal analyzes the configuration information received from the server and automatically executes the settings. The input is the configuration information from the server, and the output is the change in the configuration state. Specifically, the terminal changes device settings and user profiles.

[0663] Step 5:

[0664] The device uses emotion analysis to evaluate the user's voice tone and facial expressions in real time. Input is the user's voice and facial expression data, and output is the evaluation result of their emotional state. This utilizes voice analysis and facial recognition technologies.

[0665] Step 6:

[0666] The device optimizes the settings process and adjusts the living environment based on the evaluated emotional state. The input is the result of the emotional state evaluation, and the output is the change in the living environment settings. Specific actions include adjusting the lighting and playing music.

[0667] Step 7:

[0668] The terminal records the results of the implemented configuration in a history database. The input is the state data after the configuration change, and the output is an update to the history data. This step can be used for later troubleshooting.

[0669] 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.

[0670] 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.

[0671] 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.

[0672] [Fourth Embodiment]

[0673] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0674] 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.

[0675] 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).

[0676] 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.

[0677] 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.

[0678] 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).

[0679] 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.

[0680] 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.

[0681] 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.

[0682] 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.

[0683] 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.

[0684] 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.

[0685] 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".

[0686] This invention is a system that automates the configuration of an information processing device using an AI agent, and consists of a central server, a terminal that performs configuration, and a user that makes configuration requests.

[0687] The server is responsible for centrally managing all configuration requests. Specifically, when a user sets up a new device or reconfigures an existing one, the server receives the relevant configuration requests. This includes network settings and security policy enforcement. The server refers to an internal database, generates appropriate configuration data based on the latest security standards and organizational policies, and sends it to the device.

[0688] The terminal has the ability to receive configuration data sent from the server, analyze it, and automatically implement specified configuration tasks. This process includes automatic configuration of network connections, installation of new software, and system security settings. Because it has a built-in AI agent, the terminal can maximize the efficiency of configuration tasks. Furthermore, the terminal records the results of configuration execution in a history database, making it available for future troubleshooting and auditing.

[0689] This system significantly reduces the burden on users. For example, when a user receives a new smartphone, it will automatically connect to the company network and have necessary applications and security settings installed with just a few simple steps. This allows users to start using the device immediately.

[0690] This system is particularly effective when deployed on a large scale in enterprise environments. It allows for consistent control of equipment management across the entire workforce, including the simultaneous configuration of new devices and the application of new policies to existing devices. Therefore, this system significantly contributes to increased productivity and reduced management costs.

[0691] The following describes the processing flow.

[0692] Step 1:

[0693] When a user needs to configure a new device or wants to reconfigure an existing one, they connect to the network and send a configuration request to the server. This request includes the device type and the required configuration information.

[0694] Step 2:

[0695] The server receives configuration requests from users and generates the necessary configuration data based on device identification information and requirements. The server references its internal, up-to-date security policies and standard configuration guidelines.

[0696] Step 3:

[0697] The server sends the generated configuration data to the specified terminal. This data includes instructions for configuration, network information, and information about the software to be installed.

[0698] Step 4:

[0699] The device receives configuration data sent from the server and uses an AI agent to analyze the data. Through this analysis, it identifies which settings are needed and determines their priority.

[0700] Step 5:

[0701] Based on the analysis results, the device will automatically begin configuration tasks. This includes configuring network settings, installing new applications, and updating existing security settings.

[0702] Step 6:

[0703] Once the terminal confirms that all configuration tasks are complete, it records the results in detail and saves them as a log file in the history database. The log includes the configuration tasks performed and their success status.

[0704] Step 7:

[0705] The server receives a notification from the terminal that the setup is complete and notifies the user that the setup was completed successfully. This allows the user to start using the device immediately.

[0706] (Example 1)

[0707] 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".

[0708] In today's information processing environments, rapid and consistent configuration management of numerous devices is essential. However, traditional manual configuration management is time-consuming, labor-intensive, and prone to errors. Therefore, improving the efficiency and accuracy of configuration work is a crucial challenge.

[0709] 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.

[0710] In this invention, the server includes means for generating defined configuration data based on a configuration request received from an information processing device, means for transmitting the generated configuration data to the information processing device, and means for analyzing the configuration data and automatically executing the necessary configurations in an adjacent information processing device. This enables rapid and consistent automatic configuration for a large number of devices.

[0711] An "information processing device" refers to a computer or device that processes, manages, and stores data.

[0712] A "configuration request" is an instruction from a user or system to change or apply settings to a device or software.

[0713] "Configuration data" refers to data containing specific settings applied to an information processing device.

[0714] An "adjacent information processing device" is an information processing device that is connected to a server via a network in order to receive and analyze configuration data.

[0715] A "database" is a collection of data that systematically stores settings, their execution results, and other information so that it can be referenced later.

[0716] An "AI agent" is a type of artificial intelligence that automatically performs processes involving learning and decision-making, with the aim of streamlining setup tasks.

[0717] "Security standards" are rules and guidelines established to ensure the security of information processing equipment and data.

[0718] "Organizational policies" define the standard procedures, rules, and guidelines that are in place within a particular organization.

[0719] "Troubleshooting" refers to the procedures and actions taken to resolve system malfunctions and anomalies.

[0720] This invention is an automated configuration system for an information processing device incorporating an AI agent. The system consists of a server, a terminal that performs configuration, and a user that sends configuration requests.

[0721] The server receives configuration requests from information processing devices. For example, if a user wants to configure a new device, the server parses the request in the database and prepares the appropriate configuration data. The database incorporates the latest security standards and organizational policies. The server then sends the generated configuration data to the device.

[0722] The terminal has the ability to receive configuration data sent from the server, appropriately analyze its contents, and execute actions automatically. In this process, an AI agent plays a crucial role, making the configuration work more efficient and accurate. Specifically, the terminal performs operations such as initializing network settings, installing necessary applications, and applying security policies. Furthermore, after completing the configuration, the terminal records the results in a history database for future analysis and troubleshooting.

[0723] When users receive a new device, they can initiate a setup request through the system, and the device will be ready for immediate use with minimal or no complex operations required. For example, when a user receives a new smartphone, they can perform a few simple steps to automatically connect the smartphone to the company network and quickly apply the necessary apps and settings.

[0724] An example of a prompt statement when using a generative AI model is the instruction, "Initialize network settings for new employees and install standard software." In this way, by utilizing generative AI models and prompt statements, the system can achieve highly efficient automation of configuration.

[0725] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0726] Step 1:

[0727] The user issues a configuration request.

[0728] When a user wants to configure a new device, they send a configuration request to the server via a dedicated application or web interface.

[0729] Input: The configuration request entered by the user.

[0730] Output: Configuration request data sent to the server.

[0731] Step 2:

[0732] The server receives and parses the request.

[0733] The server analyzes the configuration request received from the user. The server accesses an internal database to check the device type and the required configuration.

[0734] Input: Configuration request data submitted by the user.

[0735] Output: A list of settings based on the analysis and a template for the generated configuration data.

[0736] Step 3:

[0737] The server generates configuration data.

[0738] Based on the analysis results, the server generates the configuration data necessary for setting up the device. This includes network configuration information and security configurations.

[0739] Input: Analysis results and reference data obtained from the database.

[0740] Output: Configuration data to be sent to the terminal.

[0741] Step 4:

[0742] Sending configuration data from the server to the terminal.

[0743] The server sends the generated configuration data to the appropriate terminal. The data is transmitted using a secure communication channel.

[0744] Input: Generated configuration data.

[0745] Output: Sends configuration data that the terminal should receive.

[0746] Step 5:

[0747] The device receives and analyzes the configuration data.

[0748] The terminal receives configuration data sent from the server and analyzes its contents. An AI agent supports the analysis process.

[0749] Input: Configuration data sent from the server.

[0750] Output: A list of setup steps.

[0751] Step 6:

[0752] The device will automatically perform the setup.

[0753] The device automatically performs the necessary configurations based on the analyzed setup procedures. This includes application installation and network configuration.

[0754] Input: A list of setup steps.

[0755] Output: The settings performed and their results.

[0756] Step 7:

[0757] The device records the settings results.

[0758] The device records the results of the settings performed in detail and stores them in a database. This allows for future troubleshooting and audits.

[0759] Input: The result of the settings that were applied.

[0760] Output: Settings history stored in the history database.

[0761] Step 8:

[0762] Notify the user that the setup is complete.

[0763] The user will be notified from their device that the setup is complete and will receive confirmation that the device is ready for immediate use.

[0764] Input: Notification of completion of setup from the device.

[0765] Output: Notification message to the user.

[0766] (Application Example 1)

[0767] 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".

[0768] In smart cities, when numerous information processing devices are deployed simultaneously, effectively and quickly managing the settings of these devices is crucial. However, traditional manual or partially automated configuration management is prone to errors and difficult to operate efficiently. Furthermore, sophisticated management methods are necessary to ensure configuration consistency while maintaining security. These challenges must be addressed to streamline the deployment and management of devices in public management systems.

[0769] 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.

[0770] In this invention, the server includes means for generating defined configuration data based on a configuration request received from an information processing device, means for transmitting the generated configuration data to the information processing device, and means for analyzing the configuration data and automatically executing the necessary configurations in a plurality of autonomously functioning terminals. This makes it possible to manage a plurality of information processing devices quickly and effectively.

[0771] An "information processing device" is a device that performs data input, processing, and output, and in particular has the function of sending configuration requests to a server, analyzing the received configuration data, and executing the process.

[0772] A "configuration request" refers to an instruction issued by a user or device to a server in order to change or define new settings for an information processing device.

[0773] "Configuration data" refers to specific configuration information that a server generates based on a configuration request and that an information processing device applies.

[0774] "Means" refers to processes or devices designed to achieve a specific function, and in this invention includes components that enable the generation, transmission, and execution of step-by-step settings.

[0775] A "server" is a computer system that provides services over a network, and its role is to receive configuration requests and generate appropriate configuration data.

[0776] A "history database" is a database that records the results of past configurations and stores information that can be referenced for future troubleshooting and auditing purposes.

[0777] "Real-time" means that there is virtually no delay between the occurrence of an event and its analysis, processing, and response, and in this invention, it enables immediate monitoring of the device's status.

[0778] This invention provides a system for efficiently managing the settings of information processing devices in smart cities. The system mainly consists of a server, terminals, and users.

[0779] The server functions as the central management unit on the network. Based on configuration requests received from users, the server first parses the requests and generates configuration data that complies with the organization's policies and environmental standards. The server then transmits this generated data to numerous autonomous terminals. As hardware, the server is equipped with a high-performance processor and sufficient memory, and uses a database management system (e.g., SQL Server) to process and store historical data.

[0780] The terminal analyzes configuration data received from the server and automatically performs the necessary settings on the target device. The terminal also monitors the results of each configuration operation in real time and sends the data to the server's history database. The terminal is equipped with AI agent software and uses a machine learning model (generative AI model) in response to prompts to determine the optimal configuration method.

[0781] As an administrator operating the system, the user can initiate the entire setup process by entering simple prompts into the system. Specifically, by sending a prompt such as "New camera setup (resolution: 1080p, frame rate: 30fps)" to the server, the server will respond immediately and automatically proceed with the setup process.

[0782] This system streamlines the management of complex and extensive devices in smart cities, minimizing configuration errors. It also maintains reliability and efficiency even in mass deployments.

[0783] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0784] Step 1:

[0785] The server parses the prompt message received from the user. It receives a prompt message (e.g., "New Camera Setup") as input and extracts the necessary configuration parameters based on it. It uses a generative AI model to select a template suitable for the configuration. The output is generated configuration data, including the configuration template.

[0786] Step 2:

[0787] The server creates a detailed configuration file based on the generated configuration data. This process verifies the configuration in accordance with environmental standards and organizational policies, and confirms compliance with security standards. The output is a detailed configuration file ready to be sent to the terminal.

[0788] Step 3:

[0789] The server sends a detailed configuration file to multiple terminals over the network. Each terminal receives the configuration file, parses it, and automatically starts the necessary hardware configuration and software installation. The input to each terminal is the received configuration file, and the output is the progress of the configuration process.

[0790] Step 4:

[0791] The terminal monitors the configuration progress in real time and sends feedback to the server if any errors or configuration inconsistencies occur. This process verifies the completion status of each configuration and prepares to record it in the history database.

[0792] Step 5:

[0793] The terminal sends the result to the server once the setup is successfully completed. The server receives this and stores it in its history database. The input is the completion report from the terminal, and the output is the recorded history data.

[0794] Step 6:

[0795] Users can audit device configurations and past change history by accessing the server and checking the history database. The input for this step is a request to access the database, and the output is a set of historical information provided to the user.

[0796] 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.

[0797] This invention provides a personalized configuration experience by combining a system that automates the configuration of information processing equipment with an emotion engine that recognizes user emotions. The system mainly consists of a server, a terminal, and an emotion engine.

[0798] The server receives configuration requests from each information processing device and is responsible for generating appropriate configuration data. Based on the database, the server references security standards and organizational policies to prepare configuration information according to the request. This configuration data is personalized based on the analysis results of the sentiment engine.

[0799] The device receives configuration data sent from the server and automatically performs the configuration process. During this process, the emotion engine on the device analyzes the user's emotional state in real time. The emotion engine analyzes user input such as voice tone and facial expressions to determine whether the user is relaxed or stressed.

[0800] Depending on the user's emotional state, the device optimizes the setup process. For example, if the user is stressed, it provides more detailed notifications to aid understanding, while if the user is relaxed, it completes the setup more quickly. This allows the user to have a flexible setup experience tailored to their situation.

[0801] For example, when a user is setting up a new laptop, if the emotion engine detects stress from the user's tone of voice, the device will add a step that explains the setup process in detail. Conversely, if the emotion engine detects positive emotions, it will simplify notifications and shorten the setup time. This improves the user experience while maintaining formal consistency.

[0802] The following describes the processing flow.

[0803] Step 1:

[0804] To begin setting up a new device, the user connects the device to the network and sends a setup request to the server via the terminal. This request may include assistance with necessary customization information and the user's current emotional state.

[0805] Step 2:

[0806] The server receives configuration requests from users and generates configuration data based on those requests, taking into account the device's characteristics and the organization's policies. In doing so, the server incorporates configuration information to ensure compliance with the latest security standards.

[0807] Step 3:

[0808] The server sends the generated configuration data to the terminal. This data includes network settings, a list of recommended applications, and security settings.

[0809] Step 4:

[0810] The device receives configuration data sent from the server and activates an emotion engine to analyze the user's emotional state in real time. It identifies the user's emotions using speech recognition and facial expression analysis via a camera.

[0811] Step 5:

[0812] The device adjusts the setup process based on the analysis results of the emotion engine. For example, if it determines that the user is stressed, it provides detailed guidance to make the process easier to understand. Conversely, if the user is relaxed, it simplifies the setup procedure and allows for quick execution.

[0813] Step 6:

[0814] Once the setup is complete, the device records the results in detail and saves them to a history database. This allows for future troubleshooting and reference of the history.

[0815] Step 7:

[0816] The server receives completion notifications from the terminal and notifies the user of the completion status of the setup. Based on feedback from the emotion engine, the notification is provided in an appropriate format. For example, if the user was stressed, the server will provide an announcement that explains in detail the benefits of completing the setup and the next steps.

[0817] (Example 2)

[0818] 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".

[0819] In modern information processing systems, providing a personalized setup experience tailored to each user's individual needs and emotional state is crucial for improving user satisfaction. However, conventional systems lacked the technology to automatically optimize the setup process based on user emotions, resulting in a failure to adequately respond to situations where users felt stressed or, conversely, relaxed.

[0820] 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.

[0821] In this invention, the server includes means for generating defined configuration data based on configuration requests received from an information processing device, means for analyzing the user's emotional state and personalizing the configuration data based on that emotional analysis, and means for adjusting the configuration process according to the user's emotional state and optimizing the user experience. This makes it possible to provide a flexible configuration experience that responds to the user's emotions.

[0822] An "information processing device" is a general term for a device that has the functions of inputting, processing, storing, and outputting data.

[0823] A "configuration request" is a request that specifies the instructions or conditions necessary for an information processing device to operate according to specific conditions or parameters.

[0824] "Configuration data" refers to a dataset containing specific parameters and conditions necessary to control the operation of an information processing device.

[0825] "Adjacent information processing devices" refer to information processing devices that can communicate directly with each other via a network or physical connection.

[0826] "Analysis" is the act of extracting received data or information and converting it into a form that is easy to understand.

[0827] "Emotional state" refers to the user's psychological and physiological responses, and is an indicator that indicates their emotions at that time.

[0828] Personalization is the process of optimizing information and services to suit the individual needs and circumstances of each user, and adjusting them to be individually adapted.

[0829] A "history database" is a type of database used to store records of past operation results, events, and configuration data.

[0830] "Troubleshooting" is a method for diagnosing system or equipment failures and problems and finding solutions.

[0831] This invention is a system that automates the settings of an information processing device according to the user's emotional state, thereby providing a personalized experience. It mainly consists of a server, a terminal, and an emotion engine. Details of each element are as follows:

[0832] The server receives configuration requests from information processing devices via the network. Based on these requests, the server accesses the database and generates appropriate configuration data while referencing security standards and organizational policies. By utilizing a generative AI model, efficient generation and optimization of configuration data are achieved. This generated data is then personalized based on user sentiment analysis obtained through an emotion engine.

[0833] The terminal receives configuration data sent from the server and automatically performs the configuration process. An emotion engine integrated into the terminal analyzes the user's voice tone and facial expressions to understand their emotional state in real time. The emotion engine determines the user's level of tension or relaxation and adjusts the configuration process accordingly.

[0834] As a concrete example, consider the scenario of setting up a new computer. When a user unboxes the new computer and begins the initial setup, the device's built-in emotion engine detects from the user's tone of voice that they are feeling stressed. In this case, the device displays additional information to make the setup process easier to understand. On the other hand, if the user is relaxed, notifications are simplified, and the setup time is shortened.

[0835] An example of a prompt for a generative AI model would be, "If a user is setting up a new computer in a relaxed state, how should you optimize the setup process?" This prompt allows the generative AI model to provide optimal setup instructions that take emotional states into account.

[0836] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0837] Step 1:

[0838] The server receives configuration requests from information processing devices. The input is a configuration request sent over the network, which includes the device type and required configuration items. As output, the server parses the received requests and extracts the appropriate information for the next processing step. Specifically, it determines the priority of the requests and identifies which configuration data is needed.

[0839] Step 2:

[0840] The server accesses the database and generates appropriate configuration data in response to configuration requests. The input is the parsed request content, and the output is configuration data that conforms to security standards and organizational policies. A generation AI model is used to optimize the data and correct inconsistencies. This process involves reviewing the logic of the instructions and combining appropriate parameters.

[0841] Step 3:

[0842] The server personalizes the settings data based on the analysis results of the emotion engine. The input is the user's emotional state data provided by the emotion engine, and the output is personalized settings data that is appropriate for the user's current situation. Specifically, the server adds detailed guidance information when the user is experiencing stress.

[0843] Step 4:

[0844] The server sends personalized configuration data to the terminal. The input is the generated configuration data, and the output is the data packets received by the terminal. To enhance communication reliability, redundant data checks are performed to prevent transmission errors.

[0845] Step 5:

[0846] The terminal receives configuration data sent from the server and begins analysis. The input is the received data, and the output is a set of specific instructions necessary for automatic configuration. The terminal verifies data integrity and supplements any missing information to efficiently execute the procedure.

[0847] Step 6:

[0848] The on-device emotion engine analyzes the user's emotional state in real time. Input is the user's voice tone and facial expression data, and output is the analysis result indicating the current emotional state. The emotion engine utilizes noise cancellation to remove ambient noise and perform accurate emotion analysis.

[0849] Step 7:

[0850] The device adjusts the setup process according to the user's emotional state. The input is the emotional state, which is updated in real time, and the output is a dynamic setup procedure to optimize the user experience. For example, if the user is feeling anxious, the device will display step-by-step instructions.

[0851] Step 8:

[0852] The terminal notifies the user of the progress of the setup process. Inputs include the completion rate and estimated time, while output is a notification message. Visual and audio information are combined to aid user understanding.

[0853] (Application Example 2)

[0854] 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".

[0855] In today's advanced information society, numerous devices and systems are used, making their setup and management increasingly complex. In particular, interactive settings based on user emotional states are difficult to implement, which can delay the adjustment of personalized living environments. Therefore, there is a need to provide a flexible and efficient setup process that takes user emotions into consideration.

[0856] 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.

[0857] In this invention, the server includes means for generating defined configuration information based on a configuration request received from an information processing device, means for transmitting the generated configuration information to the information processing device, and means for evaluating the user's emotional state using emotion analysis means and optimizing the configuration process based on the evaluation. This enables the automatic execution of personalized configurations that correspond to the user's emotional state.

[0858] An "information processing device" is a device used for inputting, processing, and outputting data, and includes computers and servers.

[0859] A "configuration request" is a request sent to an information processing device to perform specific settings or adjustments.

[0860] "Configuration information" refers to information that includes data and instructions necessary to control the operation and functions of an information processing device.

[0861] "Emotional analysis means" refers to functions or devices that analyze a user's voice, facial expressions, behavior, etc., and evaluate their emotional state.

[0862] "Evaluation" is the act of determining the value or state of something based on collected data and according to specific criteria.

[0863] "Optimizing the setup process" means adjusting the setup procedure efficiently and appropriately in order to improve the user experience.

[0864] "Controlling the living environment" refers to the act of adjusting physical environmental elements such as light, sound, and temperature to provide a comfortable living space.

[0865] A "history database" is a database that records past settings and their results, making them searchable and referential.

[0866] This invention relates to a system for optimizing the setting process in an information processing device based on the user's emotional state. The system includes a server, a terminal, and an emotion analysis means.

[0867] The server receives a configuration request from the information processing device and generates configuration information based on the database, in accordance with security standards and organizational policies. The generated configuration information is then sent to the terminal.

[0868] The device receives configuration information and automatically performs the setup process, while simultaneously evaluating the user's emotional state in real time using emotion analysis tools. This evaluation is performed, for example, by analyzing voice tone using Google Cloud Speech-to-Text and analyzing facial expression data using the Google Cloud Vision API. Depending on the user's emotions, the device adjusts the setup process and controls the living environment to provide a relaxed environment.

[0869] For example, if the device detects the user's stress level from their voice tone while they are at home, it will immediately change the lighting to a warmer color and play calming music.

[0870] When using a generative AI model, for example, it might generate prompts like this: "Based on sentiment analysis, what smart home commands should be generated to automatically set up a relaxing environment for the user who will be returning home soon?"

[0871] This makes it possible to automatically create a comfortable environment that is adapted to the individual emotional state of each user.

[0872] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0873] Step 1:

[0874] The server receives configuration requests sent from the information processing device. The input is the configuration request from the information processing device, and the output is the trigger for generating configuration information corresponding to the request. As part of the data processing, a process is performed to extract the request content as parameters.

[0875] Step 2:

[0876] The server references the database and generates appropriate configuration information based on security standards and organizational policies. Inputs are configuration requests and database information, while output is the generated configuration information. The configuration information is parsed based on the requests and customized according to the established standards.

[0877] Step 3:

[0878] The server sends the generated configuration information to the terminal. The input is the generated configuration information, and the output is the completion of transmission to the terminal. The data calculation includes the procedure of packetizing and transmitting the configuration information.

[0879] Step 4:

[0880] The terminal analyzes the configuration information received from the server and automatically executes the settings. The input is the configuration information from the server, and the output is the change in the configuration state. Specifically, the terminal changes device settings and user profiles.

[0881] Step 5:

[0882] The device uses emotion analysis to evaluate the user's voice tone and facial expressions in real time. Input is the user's voice and facial expression data, and output is the evaluation result of their emotional state. This utilizes voice analysis and facial recognition technologies.

[0883] Step 6:

[0884] The device optimizes the settings process and adjusts the living environment based on the evaluated emotional state. The input is the result of the emotional state evaluation, and the output is the change in the living environment settings. Specific actions include adjusting the lighting and playing music.

[0885] Step 7:

[0886] The terminal records the results of the implemented configuration in a history database. The input is the state data after the configuration change, and the output is an update to the history data. This step can be used for later troubleshooting.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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."

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0908] The following is further disclosed regarding the embodiments described above.

[0909] (Claim 1)

[0910] A means for generating defined configuration data based on a configuration request received from an information processing device,

[0911] Means for transmitting the generated configuration data to the information processing device,

[0912] In an adjacent information processing device, means for analyzing the setting data and automatically executing the necessary settings,

[0913] Means for recording the results of the aforementioned settings and saving them in a history database,

[0914] A system that includes this.

[0915] (Claim 2)

[0916] The system according to claim 1, further comprising means for verifying that the generated configuration data conforms to security standards and organizational policies.

[0917] (Claim 3)

[0918] The system according to claim 1, further comprising means for using the setting results stored in the history database for troubleshooting.

[0919] "Example 1"

[0920] (Claim 1)

[0921] A means for generating defined configuration data based on a configuration request received from an information processing device,

[0922] Means for transmitting the generated configuration data to the information processing device,

[0923] In an adjacent information processing device, means for analyzing the setting data and automatically executing the necessary settings,

[0924] Means for recording the results of the aforementioned settings and saving them in a database,

[0925] A means of notifying the user that the setup is complete,

[0926] A method to maximize the efficiency of setup work by incorporating an AI agent,

[0927] A system that includes this.

[0928] (Claim 2)

[0929] The system according to claim 1, further comprising means for verifying that the generated configuration data conforms to security standards and organizational policies.

[0930] (Claim 3)

[0931] The system according to claim 1, further comprising means for using the setting results stored in the database for fault countermeasures.

[0932] "Application Example 1"

[0933] (Claim 1)

[0934] A means for generating defined configuration data based on a configuration request received from an information processing device,

[0935] Means for transmitting the generated configuration data to the information processing device,

[0936] In multiple autonomously functioning terminals, means for analyzing the aforementioned configuration data and automatically executing the necessary settings,

[0937] A means for centrally controlling and monitoring the settings of multiple terminals in a public management device in real time,

[0938] Means for recording the results of the aforementioned settings and saving them in a history database,

[0939] A system that includes this.

[0940] (Claim 2)

[0941] The system according to claim 1, further comprising means for verifying that the generated configuration data conforms to environmental standards and organizational policies.

[0942] (Claim 3)

[0943] The system according to claim 1, further comprising means for using the setting results stored in the history database for troubleshooting.

[0944] "Example 2 of combining an emotion engine"

[0945] (Claim 1)

[0946] A means for generating defined configuration data based on a configuration request received from an information processing device,

[0947] Means for transmitting the generated configuration data to the information processing device,

[0948] In an adjacent information processing device, means for analyzing the setting data and automatically executing the necessary settings,

[0949] A means of analyzing the user's emotional state and personalizing setting data based on that emotional analysis,

[0950] A means of optimizing the user experience by adjusting the setting process according to the user's emotional state,

[0951] Means for recording the results of the aforementioned settings and saving them in a history database,

[0952] A system that includes this.

[0953] (Claim 2)

[0954] The system according to claim 1, further comprising means for verifying that the generated configuration data conforms to security standards and organizational policies.

[0955] (Claim 3)

[0956] The system according to claim 1, further comprising means for using the setting results stored in the history database for troubleshooting.

[0957] "Application example 2 when combining with an emotional engine"

[0958] (Claim 1)

[0959] A means for generating defined configuration information based on a configuration request received from an information processing device,

[0960] Means for transmitting the generated configuration information to the information processing device,

[0961] In an adjacent information processing device, means for analyzing the setting information and automatically executing the necessary settings,

[0962] A means for evaluating the user's emotional state using emotion analysis methods and optimizing the setting process based on that evaluation,

[0963] Based on the optimized setting process described above, means for controlling the living environment,

[0964] Means for recording the results of the aforementioned settings and saving them in a history database,

[0965] A system that includes this.

[0966] (Claim 2)

[0967] The system according to claim 1, further comprising means for verifying that the generated configuration information conforms to security standards and organizational policies.

[0968] (Claim 3)

[0969] The system according to claim 1, further comprising means for using the setting results stored in the history database for problem solving. [Explanation of Symbols]

[0970] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for generating defined configuration data based on a configuration request received from an information processing device, Means for transmitting the generated configuration data to the information processing device, In multiple autonomously functioning terminals, means for analyzing the aforementioned configuration data and automatically executing the necessary settings, A means for centrally controlling and monitoring the settings of multiple terminals in a public management device in real time, Means for recording the results of the aforementioned settings and saving them in a history database, A system that includes this.

2. The system according to claim 1, further comprising means for confirming that the generated configuration data conforms to environmental standards and organizational policies.

3. The system according to claim 1, further comprising means for using the setting results stored in the history database for troubleshooting.

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