system

Abstract

We provide the system. [Solution] A means of providing an interface for users to make detailed privacy settings for individual information elements, In order to selectively share personal attributes according to the aforementioned settings, a means for processing information elements, A database means for storing and managing access rights for the aforementioned information elements, An artificial intelligence agent means that provides customized functions based on the user's privacy settings, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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] In recent years, personalized services using information processing devices have become widespread. Along with this, the protection of users' personal information and privacy has become an important issue. Some users are concerned about the unintentional sharing of their personal information, and there is a need to appropriately restrict information access according to individual users. However, in conventional technologies, there is a situation where it is difficult for users themselves to manage information in detail, and there is a problem that there is a lack of safe and intuitive information management means.

Means for Solving the Problems

[0005] This invention provides a means for users to select their information access scope in an information processing device, and constructs a system that protects user privacy by appropriately controlling information access based on that selection. Specifically, it provides a means for receiving settings to control access based on the type of information selected by the user, and stores and manages these settings in a database. Then, it proposes a system that verifies access permissions based on the stored settings and provides appropriate services to the user using the permitted information, thereby reducing concerns about privacy. Furthermore, it solves the problem by configuring the system so that the latest information access control is always in place by saving and updating the settings again in the database whenever they are changed.

[0006] An "information processing device" is an electronic device that receives user input and processes data based on that input.

[0007] A "user" is an individual or group that operates an information processing device and is the entity involved in the settings and receiving services.

[0008] "Types of information" refers to various data categories related to the user, such as age, location information, contact information, and purchase history.

[0009] "Access control settings" are options that define rules and policies for how information processing devices manage access to users' personal information.

[0010] A "database" is a system for organizing, structuring, storing, and managing information in a digital format.

[0011] "To manage" means to properly store data and continuously maintain it so that it can be quickly accessed when needed.

[0012] "Authorized information" refers to data that has been authorized by the user to be accessed and is made available by the information processing device.

[0013] "Providing a service" means that an information processing device executes or provides the functions and information requested by the user. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and 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, when an emotion engine is combined. [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled 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.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled 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.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention provides a system that allows users to properly manage their privacy and enjoy services safely by precisely setting their own information access scope through an information processing device. This system primarily operates through the coordinated operation of three elements: a terminal, a server, and the user.

[0036] First, users use the interface on their device to select the types of information they want to share (e.g., age, location, contacts, purchase history). Options include "share," "restrict," and "don't share," allowing users to manage their privacy by setting preferences for each piece of information.

[0037] The device temporarily saves the user's selected settings locally before sending them to the server. The server receives this information and stores it in a database to manage access permissions for each user. This stored information is then used in conjunction with subsystems such as AI agents to ensure that only authorized information is used.

[0038] The server provides the AI ​​agent with updated settings as needed, based on the user's configuration. When requested by the user, the AI ​​agent retrieves the latest settings from the server and accesses the information according to the user's privacy settings. This allows the AI ​​agent to use permitted information to appropriately provide customized services to the user.

[0039] For example, if a user sets their location information sharing to "not shared," the AI ​​agent will not access their location information and will provide services based on other permitted information. On the other hand, if the user sets their schedule information to "shared," the AI ​​agent can notify the user of schedule-based reminders.

[0040] This system allows users to flexibly access the services they need while ensuring their privacy is securely protected. This reduces the risk of information leaks, allowing users to use AI agents with peace of mind.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user accesses the device's privacy settings screen, where the device displays the available information categories. For each information category (e.g., age, location, contacts, purchase history), the user selects one of three options: "Share," "Restrict," or "Don't Share."

[0044] Step 2:

[0045] The device temporarily saves the user's selected privacy settings locally. This saving process occurs when all settings have been completed.

[0046] Step 3:

[0047] The device sends the saved privacy settings to the server using a secure protocol. After sending, the device receives a notification that the transmission is complete before proceeding to the next step.

[0048] Step 4:

[0049] The server checks the privacy settings received from the device and stores them in a database. The database stores different settings information for each user.

[0050] Step 5:

[0051] When a user requests information services, the server retrieves the user's privacy settings from the database and provides them to the AI ​​agent.

[0052] Step 6:

[0053] The AI ​​agent analyzes the configuration information received from the server and provides services based only on the information authorized by the user. For example, if schedule information is shared, the AI ​​agent will use that information to set reminders.

[0054] Step 7:

[0055] When a user changes their settings, the device sends those changes back to the server. The server updates the existing settings with the new settings, keeping them up-to-date.

[0056] (Example 1)

[0057] 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."

[0058] Conventional information processing systems often suffer from insufficient user privacy settings and cumbersome settings management, making it difficult for users to manage their information and access services with peace of mind. In particular, there is a lack of mechanisms to ensure the safe and efficient use of only authorized information.

[0059] 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.

[0060] In this invention, the server includes means for the user to set privacy settings for the type of information provided via an information processing device, means for temporarily saving the settings to local storage and securely transmitting them to the server, and means for providing the AI ​​agent with the user's latest settings and executing customized services based on the permitted information. This enables the user to receive secure and optimized services while flexibly managing their own privacy.

[0061] An "information processing device" is a device used by users to process and manage digital information, and includes computers, smartphones, and other similar devices.

[0062] "Privacy settings" refer to settings that allow users to choose and control the scope and method of sharing their information.

[0063] "Local storage" refers to a memory area within an information processing device used to temporarily or permanently store data.

[0064] A "server" is a computing device that provides services on a network and shares data and applications with other devices.

[0065] A "database" is a collection of data that is systematically stored and managed to allow efficient access to digital information.

[0066] An "AI agent" is a program or system that uses artificial intelligence technology to autonomously perform specific tasks and provide services to users.

[0067] "Customized service" refers to the process of providing services that are individually tailored to the user's specific requirements and settings.

[0068] "Authorized information" refers to information that a user has authorized to access or use for a specific purpose.

[0069] This system is an information processing system that allows users to precisely control the scope of their information disclosure and receive secure, personalized services. It operates through the close cooperation of three elements: the user, the terminal, and the server.

[0070] First, the user uses a terminal, which is an information processing device, to configure privacy settings for their information via an interface. The terminal accepts the privacy settings and temporarily stores them in local storage. The software used on the terminal includes a user interface and features that allow users to intuitively select settings. The hardware that this terminal is expected to support is a typical computer or smartphone.

[0071] Next, the terminal sends the saved configuration information to the server using a secure protocol (e.g., SSL / TLS). After receiving this information, the server stores it in a database, associated with the user identifier. A relational database management system (RDBMS) is used for this database; suitable examples include PostgreSQL and MySQL®.

[0072] Furthermore, the server provides the AI ​​agent with the latest privacy settings in response to user requests. The AI ​​agent then uses a generated AI model to provide the user with customized services based on the permitted information. This ensures that the services provided by the AI ​​agent are tailored to the individual needs of each user.

[0073] For example, if a user sets their location information to "not shared," the AI ​​agent can provide services based on other permitted information (e.g., schedule information) without accessing that information. Users can send requests to the AI ​​agent using prompt messages. A concrete example of a prompt message might be, "Please provide the necessary information for our next meeting, but please avoid my current location."

[0074] In this way, the system can efficiently provide necessary services while firmly protecting user privacy.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] Users configure their privacy settings through the device interface. This allows them to select "Share," "Restrict," or "Don't Share" for each type of information they provide (e.g., age, location). This process generates user settings input, which is temporarily stored in local storage in JSON format.

[0078] Step 2:

[0079] The terminal sends the saved configuration information to the server using a security protocol (SSL / TLS). This input information is encrypted along with the user identifier. The server receives the encrypted data, decrypts it, and stores it in the database. At this stage, the database outputs information that classifies and manages access rights for each user.

[0080] Step 3:

[0081] The server provides the user's latest privacy settings in response to a request from the AI ​​agent. In this process, the server retrieves the privacy settings based on the relevant user identifier from the database and forwards them to the AI ​​agent. The output data represents the privacy settings used by the AI ​​agent. Based on these settings, the AI ​​agent creates a response to the user's request.

[0082] Step 4:

[0083] The user sends a service request to the AI ​​agent using a prompt message. The AI ​​agent uses the received prompt message and the privacy settings provided by the server as input, and utilizes a generated AI model to perform the corresponding processing. The output of this data processing is customized service information that conforms to the user's settings. The AI ​​agent provides this information to the user to deliver personalized services.

[0084] This series of processing steps allows users to access safe and efficient information services while maintaining their privacy.

[0085] (Application Example 1)

[0086] 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."

[0087] A major challenge with conventional electronic payment systems is their inability to flexibly accommodate users' diverse privacy needs. Specifically, there is a lack of mechanisms to fulfill users' desires to selectively share only certain information or to have fine-grained control over how their data is handled. Furthermore, there is a need for information provision that reduces the risk of data leaks without compromising convenience.

[0088] 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.

[0089] In this invention, the server includes means for providing an interface for users to make detailed privacy settings for individual information elements; means for processing information elements to selectively share personal attributes according to the settings; database means for storing and managing access rights for the information elements; and artificial intelligence agent means for providing customized functions based on the user's privacy settings. This makes it possible to use payment services efficiently and securely while responding to the user's detailed privacy requests.

[0090] An "interface" refers to the user interface or method of operation used when a user configures privacy settings for information elements.

[0091] "Personal attributes" refer to information elements about the user, including, for example, credit card information, purchase history, and location information.

[0092] An "information element" is a unit of data handled by a system, and refers to the specific information that users choose to provide.

[0093] "Processing" refers to the process by which a system processes and provides information elements based on the user's privacy settings.

[0094] A "database means" is a systemic structure for efficiently storing and managing users' privacy settings and access rights to information elements.

[0095] An "artificial intelligence agent" is a technological entity that analyzes necessary information based on the user's privacy settings and generates appropriate services and responses.

[0096] The system to realize this application primarily operates through the collaboration of a terminal, a server, and an artificial intelligence agent. The terminal uses frontend technologies such as Vue.js or React to provide users with an interface for setting privacy settings. This allows users to intuitively and precisely configure access permissions for personal attributes (e.g., credit card information, purchase history, location information).

[0097] The configured information is received by a backend using Node.js and Express and stored in MongoDB. The server uses this database to manage user configuration information. This enables selective access control to specified information elements, creating a mechanism that appropriately protects user privacy.

[0098] The artificial intelligence agent is built using machine learning libraries such as TENSORFLOW® and processes information based on the user's privacy settings obtained from the server. For example, if a user has set their settings not to share their location information, this agent can utilize other available personal attributes without referring to location information to provide customized services. This enables the realization of services and responses optimized for each individual user.

[0099] As a concrete example, when a user conducts e-commerce, they could provide only their credit card information to a specific store, while keeping other information (such as purchase history or location information) private. This would allow for a safe and comfortable shopping experience without compromising user privacy.

[0100] An example of a prompt for a generated AI model is: "Explain how an AI agent for an electronic payment system with enhanced privacy management can provide the optimal process for providing only credit card information based on user preferences and keeping purchase history private."

[0101] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0102] Step 1:

[0103] The device displays an interface for the user to configure their privacy settings. Through this interface, the user selects access permissions for personal attributes (e.g., credit card information, purchase history, location information). The input is the user's privacy selection, and configuration data is generated based on this selection. The output is the generated configuration data.

[0104] Step 2:

[0105] The device sends user-configured privacy settings data to the backend. Here, it receives privacy settings data as input. The device executes a communication process to send this data to the server, securely transmitting the settings data. The output is the settings data received by the server.

[0106] Step 3:

[0107] The server stores the received privacy settings data in a database and manages it by classifying it for each user. The input is the settings data sent from the terminal, and the output is the settings information stored in the database. The server strictly manages this data and records the access rights for each user.

[0108] Step 4:

[0109] The server's artificial intelligence agent retrieves relevant configuration information from the database when a service request is received from a user. The input is the user's request, and the output is the extracted configuration information. Based on the latest settings, this agent determines which information is available.

[0110] Step 5:

[0111] The artificial intelligence agent performs appropriate information analysis based on the user's privacy settings, processes the necessary information, and provides customized services. The input consists of configuration information and user requests, and the output is the customized service result. Specifically, it uses machine learning algorithms to analyze information and generates the optimal response based on the system's requirements.

[0112] 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.

[0113] This invention provides a system that dynamically adjusts information access control according to the user's emotional state and optimizes service provision by incorporating a new emotion engine into a conventional information processing device. This system is implemented with a terminal, a server, and an emotion engine as its main components.

[0114] Users configure their privacy settings through their device and choose how much of their information they want to share. The device saves these settings locally, then sends them to a server, which stores the settings in a database. Based on this stored information, the AI ​​agent provides appropriate services using only the information authorized by the user.

[0115] Furthermore, the emotion engine operates on the device and analyzes the user's emotional state from their voice, facial expressions, and input speed. The analyzed emotional information is sent to the server, where dynamic access control settings are adjusted according to the user's current emotional state. For example, if the emotion engine determines that the user is stressed, it restricts access to information and changes settings to enhance privacy.

[0116] The server uses the emotional information transmitted from the emotion engine to process data and optimize the content and method of the services to be provided. This allows for the provision of information and support tailored to the user's emotional state. For example, if the AI ​​agent detects that the user is feeling down, it will provide gentle voice guidance and recommend relaxing content.

[0117] For example, if the emotion engine detects that a user is experiencing stress at work, the server will temporarily minimize access to that user's data while providing services to alleviate that stress. This makes it possible to simultaneously protect privacy and provide user-centric services.

[0118] Thus, the present invention dynamically manages information access based on user emotion analysis and realizes the provision of appropriate services. With this system, users can safely enjoy flexible services that are tailored to their own emotions.

[0119] The following describes the processing flow.

[0120] Step 1:

[0121] Users can choose how much of their information they want to share on their device's privacy settings screen. The device saves this setting locally.

[0122] Step 2:

[0123] The device sends locally stored privacy settings to the server. This transmission is performed using a secure communication protocol.

[0124] Step 3:

[0125] The server stores the privacy settings received from the device in a database. This allows for centralized management of settings that differ for each user.

[0126] Step 4:

[0127] The emotion engine built into the device analyzes the user's voice, facial expressions, input speed, etc., to identify their emotional state in real time.

[0128] Step 5:

[0129] The emotion engine sends the analyzed emotional state to the server. This emotional information is used to dynamically adjust privacy settings.

[0130] Step 6:

[0131] The server determines the appropriate information access settings based on emotional information and updates them as needed. These settings fluctuate according to the user's emotions.

[0132] Step 7:

[0133] The AI ​​agent, having received emotional information and updated access settings from the server, will provide services within the scope of the permitted information. The services will be optimized to match the user's emotional state.

[0134] Step 8:

[0135] When a user reports new privacy settings or emotional states, the device sends this information back to the server, which then updates its database. This iterative process ensures the system continuously provides services that respect user privacy and emotions.

[0136] (Example 2)

[0137] 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 as the "terminal".

[0138] In conventional information processing systems, information access was controlled solely based on the user's privacy settings, and dynamic adjustments were not made in response to the user's emotional state. As a result, information provision and service optimization adapted to the user's emotional state were insufficient, leading to a problem of not being able to improve user satisfaction.

[0139] 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.

[0140] In this invention, the server includes means for receiving settings that control access to information based on the type of information selected by the user in the information processing device; means for storing the settings in a database and managing them for each user; means for confirming access permissions to information based on the user's settings and providing services based on the permitted information; means for determining the user's emotional state using a computing device equipped with an emotion engine that analyzes the user's voice, facial expressions, and input speed; and means for dynamically adjusting information access based on the emotional state and modifying the settings in the database in order to provide optimal services. This enables flexible information access management and optimal service provision in accordance with the user's emotional state.

[0141] An "information processing device" refers to a computing system used for collecting, storing, analyzing, processing, and transmitting data, and is operated based on user instructions.

[0142] A "database" refers to an information management system that systematically collects and stores information, and allows for searching and updating as needed.

[0143] An "emotion engine" refers to software or hardware that analyzes information such as the user's voice, facial expressions, and input speed to infer or determine the user's emotional state.

[0144] "Access control" refers to a mechanism that sets and manages the necessary permissions and parameters for users or systems to access information, and allows access only within the permitted scope.

[0145] "Dynamic adjustment of information access" refers to a procedure or function that changes the scope of access permissions to information in real time based on the user's situation, emotions, and other variables.

[0146] "Providing optimal service" refers to the process of proposing and delivering information and solutions in a way that is most appropriate to the user's needs and emotional state.

[0147] This invention is a system that uses an information processing device to achieve dynamic control of information access according to the user's emotional state. The main components are a terminal, a server, and an emotion engine.

[0148] The device provides an interface for users to enter their privacy settings. Users specify the scope and sharing of information they wish to make public. This setting information is stored on the device, encrypted, and sent to the server.

[0149] The server stores received privacy settings in a database and manages them on a per-user basis. The database is protected with a high level of security and serves as the basis for access control.

[0150] The emotion engine installed on the device analyzes the user's emotions through voice recognition technology, facial recognition technology, and input speed monitoring. The hardware used here is a high-performance CPU and GPU, enabling real-time data processing.

[0151] The analyzed emotion data is sent to the server, which then dynamically adjusts the user's access control settings based on this information. For example, if the server determines that the user is experiencing stress, access restrictions will be strengthened and privacy-focused settings will be applied.

[0152] The server also uses a generative AI model to provide services adapted to emotional information. Specifically, if it determines that a user is feeling down, it will recommend gentle voice guidance or relaxation content. This ensures that users can receive appropriate services with peace of mind.

[0153] For example, when a user is experiencing stress at work, the emotion engine detects this, and the server temporarily restricts access to information to a minimum while simultaneously providing information that helps reduce stress. This system provides personalized support to users, achieving a balance between privacy and convenience.

[0154] As an example of a prompt, the system is asked, "What is the best content to recommend when the system determines that the user is in a stressed state?" Based on this, the generating AI model selects the appropriate response and optimizes the service.

[0155] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0156] Step 1:

[0157] The user enters their privacy settings using an interface on their device. Specific inputs include the types of information they want to make public and the scope of that information. The device encrypts the entered settings and stores them locally. The output is the encrypted privacy settings, which are then prepared for transmission to the server.

[0158] Step 2:

[0159] The device sends saved privacy settings to the server. The input is encrypted settings data. The server receives this data and stores it in a database. During the storage process, the data is indexed and converted into a format that allows for efficient searching and management. The output is user-specific privacy settings data stored in the database.

[0160] Step 3:

[0161] The emotion engine built into the device collects the user's voice, facial expressions, and input speed in real time. This biometric data serves as input. The emotion engine analyzes this data to estimate the user's current emotional state. Specific data processing includes voice processing algorithms and facial recognition algorithms. The output is the analyzed emotional data, which is used in the next step.

[0162] Step 4:

[0163] The device securely transmits the analyzed emotion data to the server. This data is processed as input by the server. Based on the received emotion data, the server dynamically adjusts the privacy settings in its database. Specifically, this involves changing access restrictions to adapt to the user's emotional state. The output is the updated access control settings.

[0164] Step 5:

[0165] The server combines updated access control settings and sentiment data to generate service content tailored to the user. A generative AI model then performs calculations to provide the user with the most suitable content and guidance. Specifically, this includes recommendations for gentle voice guidance and relaxing content. The output is a customized service suggestion delivered to the user's device.

[0166] (Application Example 2)

[0167] 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".

[0168] Conventional information processing systems have found it difficult to dynamically adjust services in response to users' emotional states, making it challenging to provide personalized services. Furthermore, the lack of mechanisms to adjust information access control based on users' emotional states has made balancing privacy protection with service flexibility a significant challenge.

[0169] 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.

[0170] In this invention, the server includes means for receiving settings to control access to information based on the type of information selected by the user, means for storing the settings in a database and managing them for each user, and means for analyzing the user's emotional state, dynamically adjusting the access control to the information based on the analysis results, and providing a service appropriate to the user. This makes it possible to achieve both flexible service provision that responds to the user's emotions and enhanced privacy.

[0171] An "information processing device" is a device that receives, analyzes, and stores data, and provides specific functions or services based on that data.

[0172] A "user" is an individual or group that uses an information processing device to access information or services.

[0173] "Access control" refers to restrictions and settings that determine whether a user can access certain information.

[0174] "Saving settings to a database" refers to the process of accumulating setting information selected and entered by users so that it can be referenced later.

[0175] "Emotional state" refers to the state of a user's psychological and emotional response, and is analyzed from factors such as voice, facial expressions, and input speed.

[0176] "Providing a service" refers to the act of supplying information, functions, or support to users in accordance with their requests and circumstances.

[0177] In a form for carrying out the invention, the server, as an information processing device, provides personalized services tailored to the user's emotional state. The server collects necessary data through a specific user interface to accept information access control settings based on the user's choices. It then stores the collected setting information in a database and manages information corresponding to individual users.

[0178] The device includes an emotion engine that analyzes the user's voice, facial expressions, and input speed, allowing it to understand the user's emotional state in real time. The emotion engine is based on hardware such as Raspberry Pi and Jetson Nano, and utilizes cloud AI services such as Google Cloud AI and AWS for voice recognition and facial expression analysis.

[0179] Based on the user's emotion analysis results, the server dynamically adjusts access control to information and provides services tailored to the user as needed. For example, if the server determines that the user is stressed, it will enhance privacy and provide relaxation music.

[0180] As a concrete example, in a nursing home, residents can receive soothing music through smart glasses, and caregivers are notified of situations requiring immediate attention. In this way, flexible services tailored to the emotional state of the residents become available.

[0181] When using a generative AI model, you can use prompt statements like the following:

[0182] Analyze users' emotional states in real time and suggest what kind of content to provide when they are feeling stressed.

[0183] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0184] Step 1:

[0185] The device acquires the user's voice, facial expressions, and input speed through sensors and microphones. This data is analyzed by an emotion engine. Audio and video data are used as input, and emotional state tags (e.g., stress, relaxation) are generated as output. The emotion engine performs data processing and calculations using cloud AI services such as Google Cloud AI and AWS.

[0186] Step 2:

[0187] The device sends the analyzed emotional state to the server. The input includes emotional state tags and associated user identification information. The server receives this information and compares it with the user's privacy settings stored in the database. The output is a set of adjusted information access settings.

[0188] Step 3:

[0189] The server dynamically adjusts information access and optimizes the service based on the user's emotions. Inputs include emotional state and privacy settings. Specifically, it strengthens access restrictions for stressed users and changes the content provided to relaxing music and suggestions. The output is the generated optimized service content.

[0190] Step 4:

[0191] As feedback to the user, optimized services and content are provided through smart devices (e.g., smart glasses and smartphones). Input includes service details transmitted from the server, and output is the actual content the user receives (e.g., music, visual guides). The user receives this, relaxes, and enjoys a comfortable environment.

[0192] In this way, a system is realized in which servers, terminals, and users work together to provide services that respond to emotions in real time.

[0193] 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.

[0194] 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.

[0195] 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.

[0196] [Second Embodiment]

[0197] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0198] 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.

[0199] 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).

[0200] 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.

[0201] 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.

[0202] 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).

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] 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".

[0209] This invention provides a system that allows users to properly manage their privacy and enjoy services safely by precisely setting their own information access scope through an information processing device. This system primarily operates through the coordinated operation of three elements: a terminal, a server, and the user.

[0210] First, users use the interface on their device to select the types of information they want to share (e.g., age, location, contacts, purchase history). Options include "share," "restrict," and "don't share," allowing users to manage their privacy by setting preferences for each piece of information.

[0211] The device temporarily saves the user's selected settings locally before sending them to the server. The server receives this information and stores it in a database to manage access permissions for each user. This stored information is then used in conjunction with subsystems such as AI agents to ensure that only authorized information is used.

[0212] The server provides the AI ​​agent with updated settings as needed, based on the user's configuration. When requested by the user, the AI ​​agent retrieves the latest settings from the server and accesses the information according to the user's privacy settings. This allows the AI ​​agent to use permitted information to appropriately provide customized services to the user.

[0213] For example, if a user sets their location information sharing to "not shared," the AI ​​agent will not access their location information and will provide services based on other permitted information. On the other hand, if the user sets their schedule information to "shared," the AI ​​agent can notify the user of schedule-based reminders.

[0214] This system allows users to flexibly access the services they need while ensuring their privacy is securely protected. This reduces the risk of information leaks, allowing users to use AI agents with peace of mind.

[0215] The following describes the processing flow.

[0216] Step 1:

[0217] The user accesses the device's privacy settings screen, where the device displays the available information categories. For each information category (e.g., age, location, contacts, purchase history), the user selects one of the following options: "Share," "Restrict," or "Don't Share."

[0218] Step 2:

[0219] The device temporarily saves the user's selected privacy settings locally. This saving process occurs when all settings have been completed.

[0220] Step 3:

[0221] The device sends the saved privacy settings to the server using a secure protocol. After sending, the device receives a notification that the transmission is complete before proceeding to the next step.

[0222] Step 4:

[0223] The server checks the privacy settings received from the device and stores them in a database. The database stores different settings information for each user.

[0224] Step 5:

[0225] When a user requests information services, the server retrieves the user's privacy settings from the database and provides them to the AI ​​agent.

[0226] Step 6:

[0227] The AI ​​agent analyzes configuration information received from the server and provides services based only on information authorized by the user. For example, if schedule information is shared, the AI ​​agent will use that information to set reminders.

[0228] Step 7:

[0229] When a user changes their settings, the device sends those changes back to the server. The server updates the existing settings with the new settings, keeping them up-to-date.

[0230] (Example 1)

[0231] 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."

[0232] Conventional information processing systems often suffer from insufficient user privacy settings and cumbersome settings management, making it difficult for users to manage their information and access services with peace of mind. In particular, there is a lack of mechanisms to ensure the safe and efficient use of only authorized information.

[0233] 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.

[0234] In this invention, the server includes means for the user to set privacy settings for the type of information provided via an information processing device, means for temporarily saving the settings to local storage and securely transmitting them to the server, and means for providing the AI ​​agent with the user's latest settings and executing customized services based on the permitted information. This enables the user to receive secure and optimized services while flexibly managing their own privacy.

[0235] An "information processing device" is a device used by users to process and manage digital information, and includes computers, smartphones, and other similar devices.

[0236] "Privacy settings" refer to settings that allow users to choose and control the scope and method of sharing their information.

[0237] "Local storage" refers to a memory area within an information processing device used to temporarily or permanently store data.

[0238] A "server" is a computing device that provides services on a network and shares data and applications with other devices.

[0239] A "database" is a collection of data that is systematically stored and managed to allow efficient access to digital information.

[0240] An "AI agent" is a program or system that uses artificial intelligence technology to autonomously perform specific tasks and provide services to users.

[0241] "Customized service" refers to the process of providing services that are individually tailored to the user's specific requirements and settings.

[0242] "Authorized information" refers to information that a user has authorized to access or use for a specific purpose.

[0243] This system is an information processing system that allows users to precisely control the scope of their information disclosure and receive secure, personalized services. It operates through the close cooperation of three elements: the user, the terminal, and the server.

[0244] First, the user uses a terminal, which is an information processing device, to configure privacy settings for their information via an interface. The terminal accepts the privacy settings and temporarily stores them in local storage. The software used on the terminal includes a user interface and features that allow users to intuitively select settings. The hardware that this terminal is expected to support is a typical computer or smartphone.

[0245] Next, the terminal sends the saved configuration information to the server using a secure protocol (e.g., SSL / TLS). After receiving this information, the server stores it in a database, associated with the user identifier. A relational database management system (RDBMS) is used for this database; suitable examples include PostgreSQL and MySQL.

[0246] Furthermore, the server provides the AI ​​agent with the latest privacy settings in response to user requests. The AI ​​agent then uses a generated AI model to provide the user with customized services based on the permitted information. This ensures that the services provided by the AI ​​agent are tailored to the individual needs of each user.

[0247] For example, if a user sets their location information to "not shared," the AI ​​agent can provide services based on other permitted information (e.g., schedule information) without accessing that information. Users can send requests to the AI ​​agent using prompt messages. A concrete example of a prompt message might be, "Please provide the necessary information for our next meeting, but please avoid my current location."

[0248] In this way, the system can efficiently provide necessary services while firmly protecting user privacy.

[0249] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0250] Step 1:

[0251] Users configure their privacy settings through the device interface. This allows them to select "Share," "Restrict," or "Don't Share" for each type of information they provide (e.g., age, location). This process generates user settings input, which is temporarily stored in local storage in JSON format.

[0252] Step 2:

[0253] The terminal sends the saved configuration information to the server using a security protocol (SSL / TLS). This input information is encrypted along with the user identifier. The server receives the encrypted data, decrypts it, and stores it in the database. At this stage, the database outputs information that classifies and manages access rights for each user.

[0254] Step 3:

[0255] The server provides the user's latest privacy settings in response to a request from the AI ​​agent. In this process, the server retrieves the privacy settings based on the relevant user identifier from the database and forwards them to the AI ​​agent. The output data represents the privacy settings used by the AI ​​agent. Based on these settings, the AI ​​agent creates a response to the user's request.

[0256] Step 4:

[0257] The user sends a service request to the AI ​​agent using a prompt message. The AI ​​agent uses the received prompt message and the privacy settings provided by the server as input, and utilizes a generated AI model to perform the corresponding processing. The output of this data processing is customized service information that conforms to the user's settings. The AI ​​agent provides this information to the user to deliver personalized services.

[0258] This series of processing steps allows users to access safe and efficient information services while maintaining their privacy.

[0259] (Application Example 1)

[0260] 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."

[0261] A major challenge with conventional electronic payment systems is their inability to flexibly accommodate users' diverse privacy needs. Specifically, there is a lack of mechanisms to fulfill users' desires to selectively share only certain information or to have fine-grained control over how their data is handled. Furthermore, there is a need for information provision that reduces the risk of data leaks without compromising convenience.

[0262] 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.

[0263] In this invention, the server includes means for providing an interface for users to make detailed privacy settings for individual information elements; means for processing information elements to selectively share personal attributes according to the settings; database means for storing and managing access rights for the information elements; and artificial intelligence agent means for providing customized functions based on the user's privacy settings. This makes it possible to use payment services efficiently and securely while responding to the user's detailed privacy requests.

[0264] An "interface" refers to the user interface or method of operation used when a user configures privacy settings for information elements.

[0265] "Personal attributes" refer to information elements about the user, including, for example, credit card information, purchase history, and location information.

[0266] An "information element" is a unit of data handled by a system, and refers to the specific information that users choose to provide.

[0267] "Processing" refers to the process by which a system processes and provides information elements based on the user's privacy settings.

[0268] A "database means" is a systemic structure for efficiently storing and managing users' privacy settings and access rights to information elements.

[0269] An "artificial intelligence agent" is a technological entity that analyzes necessary information based on the user's privacy settings and generates appropriate services and responses.

[0270] The system to realize this application primarily operates through the collaboration of a terminal, a server, and an artificial intelligence agent. The terminal uses frontend technologies such as Vue.js or React to provide users with an interface for setting privacy settings. This allows users to intuitively and precisely configure access permissions for personal attributes (e.g., credit card information, purchase history, location information).

[0271] The configured information is received by a backend using Node.js and Express and stored in MongoDB. The server uses this database to manage user configuration information. This enables selective access control to specified information elements, creating a mechanism that appropriately protects user privacy.

[0272] The artificial intelligence agent is built using machine learning libraries such as TensorFlow and processes information based on the user's privacy settings obtained from the server. For example, if a user has set their settings not to share their location, this agent can utilize other available personal attributes without referring to location information to provide customized services. This enables the delivery of services and responses optimized for each individual user.

[0273] As a concrete example, when a user conducts e-commerce, they could provide only their credit card information to a specific store, while keeping other information (such as purchase history or location information) private. This would allow for a safe and comfortable shopping experience without compromising user privacy.

[0274] An example of a prompt for a generated AI model is: "Explain how an AI agent for an electronic payment system with enhanced privacy management can provide the optimal process for providing only credit card information based on user preferences and keeping purchase history private."

[0275] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0276] Step 1:

[0277] The device displays an interface for the user to configure their privacy settings. Through this interface, the user selects access permissions for personal attributes (e.g., credit card information, purchase history, location information). The input is the user's privacy selection, and configuration data is generated based on this selection. The output is the generated configuration data.

[0278] Step 2:

[0279] The device sends user-configured privacy settings data to the backend. Here, it receives privacy settings data as input. The device executes a communication process to send this data to the server, securely transmitting the settings data. The output is the settings data received by the server.

[0280] Step 3:

[0281] The server stores the received privacy setting data in a database, classifies and manages it for each user. The input is the setting data sent from the terminal, and the output is the setting information stored in the database. The server strictly manages this data and records the access rights for each user.

[0282] Step 4:

[0283] When there is a service request from the user, the artificial intelligence agent of the server obtains the corresponding setting information from the database. The input is the user's request, and the output is the extraction result of the setting information. This agent determines which information is available based on the latest settings.

[0284] Step 5:

[0285] The artificial intelligence agent performs appropriate information analysis based on the user's privacy settings, processes the necessary information, and provides a customized service. The input is the setting information and the user request, and the output is the customized service result. As specific operations, it analyzes information using machine learning algorithms and generates an optimal response from the system's provided conditions.

[0286] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0287] The present invention is a system that, in a conventional information processing apparatus, newly combines an emotion engine to dynamically adjust information access control according to the user's emotional state and optimize service provision. This system is implemented with a terminal, a server, and an emotion engine as main components.

[0288] Users configure their privacy settings through their device and choose how much of their information they want to share. The device saves these settings locally, then sends them to a server, which stores the settings in a database. Based on this stored information, the AI ​​agent provides appropriate services using only the information authorized by the user.

[0289] Furthermore, the emotion engine operates on the device and analyzes the user's emotional state from their voice, facial expressions, and input speed. The analyzed emotional information is sent to the server, where dynamic access control settings are adjusted according to the user's current emotional state. For example, if the emotion engine determines that the user is stressed, it restricts access to information and changes settings to enhance privacy.

[0290] The server uses the emotional information transmitted from the emotion engine to process data and optimize the content and method of the services to be provided. This allows for the provision of information and support tailored to the user's emotional state. For example, if the AI ​​agent detects that the user is feeling down, it will provide gentle voice guidance and recommend relaxing content.

[0291] For example, if the emotion engine detects that a user is experiencing stress at work, the server will temporarily minimize access to that user's data while providing services to alleviate that stress. This makes it possible to simultaneously protect privacy and provide user-centric services.

[0292] Thus, the present invention dynamically manages information access based on user emotion analysis and realizes the provision of appropriate services. With this system, users can safely enjoy flexible services that are tailored to their own emotions.

[0293] The following describes the processing flow.

[0294] Step 1:

[0295] The user selects how much to disclose their information on the privacy settings screen of the terminal. The terminal locally stores this setting.

[0296] Step 2:

[0297] The terminal sends the locally stored privacy settings to the server. This transmission is carried out using a secure communication protocol.

[0298] Step 3:

[0299] The server stores the privacy settings received from the terminal in the database. This enables unified management of different settings for each user.

[0300] Step 4:

[0301] The emotion engine installed on the terminal analyzes the user's voice, facial expressions, input speed, etc., and identifies the emotional state in real time.

[0302] Step 5:

[0303] The emotion engine sends the analyzed emotional state to the server. The emotional information is utilized for dynamic adjustment of the privacy settings.

[0304] Step 6:

[0305] Based on the emotional information, the server determines the appropriate information access settings at that time and updates the settings as necessary. These settings vary according to the user's emotions.

[0306] Step 7:

[0307] The AI agent that has received the emotional information and the updated access settings from the server provides services within the permitted range of information. The services are optimized according to the user's emotional state.

[0308] Step 8:

[0309] When a user reports new privacy settings or emotional states, the device sends this information back to the server, which then updates its database. This iterative process ensures the system continuously provides services that respect user privacy and emotions.

[0310] (Example 2)

[0311] 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".

[0312] In conventional information processing systems, information access was controlled solely based on the user's privacy settings, and dynamic adjustments were not made in response to the user's emotional state. As a result, information provision and service optimization adapted to the user's emotional state were insufficient, leading to a problem of not being able to improve user satisfaction.

[0313] 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.

[0314] In this invention, the server includes means for receiving settings that control access to information based on the type of information selected by the user in the information processing device; means for storing the settings in a database and managing them for each user; means for confirming access permissions to information based on the user's settings and providing services based on the permitted information; means for determining the user's emotional state using a computing device equipped with an emotion engine that analyzes the user's voice, facial expressions, and input speed; and means for dynamically adjusting information access based on the emotional state and modifying the settings in the database in order to provide optimal services. This enables flexible information access management and optimal service provision in accordance with the user's emotional state.

[0315] An "information processing device" refers to a computing system used for collecting, storing, analyzing, processing, and transmitting data, and is operated based on user instructions.

[0316] A "database" refers to an information management system that systematically collects and stores information, and allows for searching and updating as needed.

[0317] An "emotion engine" refers to software or hardware that analyzes information such as the user's voice, facial expressions, and input speed to infer or determine the user's emotional state.

[0318] "Access control" refers to a mechanism that sets and manages the necessary permissions and parameters for users or systems to access information, and allows access only within the permitted scope.

[0319] "Dynamic adjustment of information access" refers to a procedure or function that changes the scope of access permissions to information in real time based on the user's situation, emotions, and other variables.

[0320] "Providing optimal service" refers to the process of proposing and delivering information and solutions in a way that is most appropriate to the user's needs and emotional state.

[0321] This invention is a system that uses an information processing device to achieve dynamic control of information access according to the user's emotional state. The main components are a terminal, a server, and an emotion engine.

[0322] The device provides an interface for users to enter their privacy settings. Users specify the scope and sharing of information they wish to make public. This setting information is stored on the device, encrypted, and sent to the server.

[0323] The server stores received privacy settings in a database and manages them on a per-user basis. The database is protected with a high level of security and serves as the basis for access control.

[0324] The emotion engine installed on the device analyzes the user's emotions through voice recognition technology, facial recognition technology, and input speed monitoring. The hardware used here is a high-performance CPU and GPU, enabling real-time data processing.

[0325] The analyzed emotion data is sent to the server, which then dynamically adjusts the user's access control settings based on this information. For example, if the server determines that the user is experiencing stress, access restrictions will be strengthened and privacy-focused settings will be applied.

[0326] The server also uses a generative AI model to provide services adapted to emotional information. Specifically, if it determines that a user is feeling down, it will recommend gentle voice guidance or relaxation content. This ensures that users can receive appropriate services with peace of mind.

[0327] For example, when a user is experiencing stress at work, the emotion engine detects this, and the server temporarily restricts access to information to a minimum while simultaneously providing information that helps reduce stress. This system provides personalized support to users, achieving a balance between privacy and convenience.

[0328] As an example of a prompt, the system is asked, "What is the best content to recommend when the system determines that the user is in a stressed state?" Based on this, the generating AI model selects the appropriate response and optimizes the service.

[0329] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0330] Step 1:

[0331] The user enters their privacy settings using an interface on their device. Specific inputs include the types of information they want to make public and the scope of that information. The device encrypts the entered settings and stores them locally. The output is the encrypted privacy settings, which are then prepared for transmission to the server.

[0332] Step 2:

[0333] The device sends saved privacy settings to the server. The input is encrypted settings data. The server receives this data and stores it in a database. During the storage process, the data is indexed and converted into a format that allows for efficient searching and management. The output is user-specific privacy settings data stored in the database.

[0334] Step 3:

[0335] The emotion engine built into the device collects the user's voice, facial expressions, and input speed in real time. This biometric data serves as input. The emotion engine analyzes this data to estimate the user's current emotional state. Specific data processing includes voice processing algorithms and facial recognition algorithms. The output is the analyzed emotional data, which is used in the next step.

[0336] Step 4:

[0337] The device securely transmits the analyzed emotion data to the server. This data is processed as input by the server. Based on the received emotion data, the server dynamically adjusts the privacy settings in its database. Specifically, this involves changing access restrictions to adapt to the user's emotional state. The output is the updated access control settings.

[0338] Step 5:

[0339] The server combines updated access control settings and sentiment data to generate service content tailored to the user. A generative AI model then performs calculations to provide the user with the most suitable content and guidance. Specifically, this includes recommendations for gentle voice guidance and relaxing content. The output is a customized service suggestion delivered to the user's device.

[0340] (Application Example 2)

[0341] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0342] Conventional information processing systems have found it difficult to dynamically adjust services in response to users' emotional states, making it challenging to provide personalized services. Furthermore, the lack of mechanisms to adjust information access control based on users' emotional states has made balancing privacy protection with service flexibility a significant challenge.

[0343] 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.

[0344] In this invention, the server includes means for receiving settings to control access to information based on the type of information selected by the user, means for storing the settings in a database and managing them for each user, and means for analyzing the user's emotional state, dynamically adjusting the access control to the information based on the analysis results, and providing a service appropriate to the user. This makes it possible to achieve both flexible service provision that responds to the user's emotions and enhanced privacy.

[0345] An "information processing device" is a device that receives, analyzes, and stores data, and provides specific functions or services based on that data.

[0346] A "user" is an individual or group that uses an information processing device to access information or services.

[0347] "Access control" refers to restrictions and settings that determine whether a user can access certain information.

[0348] "Saving settings to a database" refers to the process of accumulating setting information selected and entered by users so that it can be referenced later.

[0349] "Emotional state" refers to the state of a user's psychological and emotional response, and is analyzed from factors such as voice, facial expressions, and input speed.

[0350] "Providing a service" refers to the act of supplying information, functions, or support to users in accordance with their requests and circumstances.

[0351] In a form for carrying out the invention, the server, as an information processing device, provides personalized services tailored to the user's emotional state. The server collects necessary data through a specific user interface to accept information access control settings based on the user's choices. It then stores the collected setting information in a database and manages information corresponding to individual users.

[0352] The device includes an emotion engine that analyzes the user's voice, facial expressions, and input speed, allowing it to understand the user's emotional state in real time. The emotion engine is based on hardware such as Raspberry Pi and Jetson Nano, while voice recognition and facial expression analysis utilize cloud AI services such as Google Cloud AI and AWS.

[0353] Based on the user's emotion analysis results, the server dynamically adjusts access control to information and provides services tailored to the user as needed. For example, if the server determines that the user is stressed, it will enhance privacy and provide relaxation music.

[0354] As a concrete example, in a nursing home, residents can receive soothing music through smart glasses, and caregivers are notified of situations requiring immediate attention. In this way, flexible services tailored to the emotional state of the residents become available.

[0355] When using a generative AI model, you can use prompt statements like the following:

[0356] Analyze users' emotional states in real time and suggest what kind of content to provide when they are feeling stressed.

[0357] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0358] Step 1:

[0359] The device acquires the user's voice, facial expressions, and input speed through sensors and microphones. This data is analyzed by an emotion engine. Audio and video data are used as input, and emotional state tags (e.g., stress, relaxation) are generated as output. The emotion engine performs data processing and calculations using cloud AI services such as Google Cloud AI and AWS.

[0360] Step 2:

[0361] The device sends the analyzed emotional state to the server. The input includes emotional state tags and associated user identification information. The server receives this information and compares it with the user's privacy settings stored in the database. The output is a set of adjusted information access settings.

[0362] Step 3:

[0363] The server dynamically adjusts information access and optimizes the service based on the user's emotions. Inputs include emotional state and privacy settings. Specifically, it strengthens access restrictions for stressed users and changes the content provided to relaxing music and suggestions. The output is the generated optimized service content.

[0364] Step 4:

[0365] As feedback to the user, optimized services and content are provided through smart devices (e.g., smart glasses and smartphones). Input includes service details transmitted from the server, and output is the actual content the user receives (e.g., music, visual guides). The user receives this, relaxes, and enjoys a comfortable environment.

[0366] In this way, a system is realized in which servers, terminals, and users work together to provide services that respond to emotions in real time.

[0367] 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.

[0368] 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.

[0369] 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.

[0370] [Third Embodiment]

[0371] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0372] 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.

[0373] 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).

[0374] 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.

[0375] 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.

[0376] 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).

[0377] 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.

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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".

[0383] This invention provides a system that allows users to properly manage their privacy and enjoy services safely by precisely setting their own information access scope through an information processing device. This system primarily operates through the coordinated operation of three elements: a terminal, a server, and the user.

[0384] First, users use the interface on their device to select the types of information they want to share (e.g., age, location, contacts, purchase history). Options include "share," "restrict," and "don't share," allowing users to manage their privacy by setting preferences for each piece of information.

[0385] The device temporarily saves the user's selected settings locally before sending them to the server. The server receives this information and stores it in a database to manage access permissions for each user. This stored information is then used in conjunction with subsystems such as AI agents to ensure that only authorized information is used.

[0386] The server provides the AI ​​agent with updated settings as needed, based on the user's configuration. When requested by the user, the AI ​​agent retrieves the latest settings from the server and accesses the information according to the user's privacy settings. This allows the AI ​​agent to use permitted information to appropriately provide customized services to the user.

[0387] For example, if a user sets their location information sharing to "not shared," the AI ​​agent will not access their location information and will provide services based on other permitted information. On the other hand, if the user sets their schedule information to "shared," the AI ​​agent can notify the user of schedule-based reminders.

[0388] This system allows users to flexibly access the services they need while ensuring their privacy is securely protected. This reduces the risk of information leaks, allowing users to use AI agents with peace of mind.

[0389] The following describes the processing flow.

[0390] Step 1:

[0391] The user accesses the device's privacy settings screen, where the device displays the available information categories. For each information category (e.g., age, location, contacts, purchase history), the user selects one of the following options: "Share," "Restrict," or "Don't Share."

[0392] Step 2:

[0393] The device temporarily saves the user's selected privacy settings locally. This saving process occurs when all settings have been completed.

[0394] Step 3:

[0395] The device sends the saved privacy settings to the server using a secure protocol. After sending, the device receives a notification that the transmission is complete before proceeding to the next step.

[0396] Step 4:

[0397] The server checks the privacy settings received from the device and stores them in a database. The database stores different settings information for each user.

[0398] Step 5:

[0399] When a user requests information services, the server retrieves the user's privacy settings from the database and provides them to the AI ​​agent.

[0400] Step 6:

[0401] The AI ​​agent analyzes configuration information received from the server and provides services based only on information authorized by the user. For example, if schedule information is shared, the AI ​​agent will use that information to set reminders.

[0402] Step 7:

[0403] When a user changes their settings, the device sends those changes back to the server. The server updates the existing settings with the new settings, keeping them up-to-date.

[0404] (Example 1)

[0405] 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."

[0406] Conventional information processing systems often suffer from insufficient user privacy settings and cumbersome settings management, making it difficult for users to manage their information and access services with peace of mind. In particular, there is a lack of mechanisms to ensure the safe and efficient use of only authorized information.

[0407] 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.

[0408] In this invention, the server includes means for the user to set privacy settings for the type of information provided via an information processing device, means for temporarily saving the settings to local storage and securely transmitting them to the server, and means for providing the AI ​​agent with the user's latest settings and executing customized services based on the permitted information. This enables the user to receive secure and optimized services while flexibly managing their own privacy.

[0409] An "information processing device" is a device used by users to process and manage digital information, and includes computers, smartphones, and other similar devices.

[0410] "Privacy settings" refer to settings that allow users to choose and control the scope and method of sharing their information.

[0411] "Local storage" refers to a memory area within an information processing device used to temporarily or permanently store data.

[0412] A "server" is a computing device that provides services on a network and shares data and applications with other devices.

[0413] A "database" is a collection of data that is systematically stored and managed to allow efficient access to digital information.

[0414] An "AI agent" is a program or system that uses artificial intelligence technology to autonomously perform specific tasks and provide services to users.

[0415] "Customized service" refers to the process of providing services that are individually tailored to the user's specific requirements and settings.

[0416] "Authorized information" refers to information that a user has authorized to access or use for a specific purpose.

[0417] This system is an information processing system that allows users to precisely control the scope of their information disclosure and receive secure, personalized services. It operates through the close cooperation of three elements: the user, the terminal, and the server.

[0418] First, the user uses a terminal, which is an information processing device, to configure privacy settings for their information via an interface. The terminal accepts the privacy settings and temporarily stores them in local storage. The software used on the terminal includes a user interface and features that allow users to intuitively select settings. The hardware that this terminal is expected to support is a typical computer or smartphone.

[0419] Next, the terminal sends the saved configuration information to the server using a secure protocol (e.g., SSL / TLS). After receiving this information, the server stores it in a database, associated with the user identifier. A relational database management system (RDBMS) is used for this database; suitable examples include PostgreSQL and MySQL.

[0420] Furthermore, the server provides the AI ​​agent with the latest privacy settings in response to user requests. The AI ​​agent then uses a generated AI model to provide the user with customized services based on the permitted information. This ensures that the services provided by the AI ​​agent are tailored to the individual needs of each user.

[0421] For example, if a user sets their location information to "not shared," the AI ​​agent can provide services based on other permitted information (e.g., schedule information) without accessing that information. Users can send requests to the AI ​​agent using prompt messages. A concrete example of a prompt message might be, "Please provide the necessary information for our next meeting, but please avoid my current location."

[0422] In this way, the system can efficiently provide necessary services while firmly protecting user privacy.

[0423] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0424] Step 1:

[0425] Users configure their privacy settings through the device interface. This allows them to select "Share," "Restrict," or "Don't Share" for each type of information they provide (e.g., age, location). This process generates user settings input, which is temporarily stored in local storage in JSON format.

[0426] Step 2:

[0427] The terminal sends the saved configuration information to the server using a security protocol (SSL / TLS). This input information is encrypted along with the user identifier. The server receives the encrypted data, decrypts it, and stores it in the database. At this stage, the database outputs information that classifies and manages access rights for each user.

[0428] Step 3:

[0429] The server provides the user's latest privacy settings in response to a request from the AI ​​agent. In this process, the server retrieves the privacy settings based on the relevant user identifier from the database and forwards them to the AI ​​agent. The output data represents the privacy settings used by the AI ​​agent. Based on these settings, the AI ​​agent creates a response to the user's request.

[0430] Step 4:

[0431] The user sends a service request to the AI ​​agent using a prompt message. The AI ​​agent uses the received prompt message and the privacy settings provided by the server as input, and utilizes a generated AI model to perform the corresponding processing. The output of this data processing is customized service information that conforms to the user's settings. The AI ​​agent provides this information to the user to deliver personalized services.

[0432] This series of processing steps allows users to access safe and efficient information services while maintaining their privacy.

[0433] (Application Example 1)

[0434] 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."

[0435] A major challenge with conventional electronic payment systems is their inability to flexibly accommodate users' diverse privacy needs. Specifically, there is a lack of mechanisms to fulfill users' desires to selectively share only certain information or to have fine-grained control over how their data is handled. Furthermore, there is a need for information provision that reduces the risk of data leaks without compromising convenience.

[0436] 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.

[0437] In this invention, the server includes means for providing an interface for users to make detailed privacy settings for individual information elements; means for processing information elements to selectively share personal attributes according to the settings; database means for storing and managing access rights for the information elements; and artificial intelligence agent means for providing customized functions based on the user's privacy settings. This makes it possible to use payment services efficiently and securely while responding to the user's detailed privacy requests.

[0438] An "interface" refers to the user interface or method of operation used when a user configures privacy settings for information elements.

[0439] "Personal attributes" refer to information elements about the user, including, for example, credit card information, purchase history, and location information.

[0440] An "information element" is a unit of data handled by a system, and refers to the specific information that users choose to provide.

[0441] "Processing" refers to the process by which a system processes and provides information elements based on the user's privacy settings.

[0442] A "database means" is a systemic structure for efficiently storing and managing users' privacy settings and access rights to information elements.

[0443] An "artificial intelligence agent" is a technological entity that analyzes necessary information based on the user's privacy settings and generates appropriate services and responses.

[0444] The system to realize this application primarily operates through the collaboration of a terminal, a server, and an artificial intelligence agent. The terminal uses frontend technologies such as Vue.js or React to provide users with an interface for setting privacy settings. This allows users to intuitively and precisely configure access permissions for personal attributes (e.g., credit card information, purchase history, location information).

[0445] The configured information is received by a backend using Node.js and Express and stored in MongoDB. The server uses this database to manage user configuration information. This enables selective access control to specified information elements, creating a mechanism that appropriately protects user privacy.

[0446] The artificial intelligence agent is built using machine learning libraries such as TensorFlow and processes information based on the user's privacy settings obtained from the server. For example, if a user has set their settings not to share their location, this agent can utilize other available personal attributes without referring to location information to provide customized services. This enables the delivery of services and responses optimized for each individual user.

[0447] As a concrete example, when a user conducts e-commerce, they could provide only their credit card information to a specific store, while keeping other information (such as purchase history or location information) private. This would allow for a safe and comfortable shopping experience without compromising user privacy.

[0448] An example of a prompt for a generated AI model is: "Explain how an AI agent for an electronic payment system with enhanced privacy management can provide the optimal process for providing only credit card information based on user preferences and keeping purchase history private."

[0449] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0450] Step 1:

[0451] The device displays an interface for the user to configure their privacy settings. Through this interface, the user selects access permissions for personal attributes (e.g., credit card information, purchase history, location information). The input is the user's privacy selection, and configuration data is generated based on this selection. The output is the generated configuration data.

[0452] Step 2:

[0453] The device sends user-configured privacy settings data to the backend. Here, it receives privacy settings data as input. The device executes a communication process to send this data to the server, securely transmitting the settings data. The output is the settings data received by the server.

[0454] Step 3:

[0455] The server stores the received privacy settings data in a database and manages it by classifying it for each user. The input is the settings data sent from the terminal, and the output is the settings information stored in the database. The server strictly manages this data and records the access rights for each user.

[0456] Step 4:

[0457] The server's artificial intelligence agent retrieves relevant configuration information from the database when a service request is received from a user. The input is the user's request, and the output is the extracted configuration information. Based on the latest settings, this agent determines which information is available.

[0458] Step 5:

[0459] The artificial intelligence agent performs appropriate information analysis based on the user's privacy settings, processes the necessary information, and provides customized services. The input consists of configuration information and user requests, and the output is the customized service result. Specifically, it uses machine learning algorithms to analyze information and generates the optimal response based on the system's requirements.

[0460] 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.

[0461] This invention provides a system that dynamically adjusts information access control according to the user's emotional state and optimizes service provision by incorporating a new emotion engine into a conventional information processing device. This system is implemented with a terminal, a server, and an emotion engine as its main components.

[0462] Users configure their privacy settings through their device and choose how much of their information they want to share. The device saves these settings locally, then sends them to a server, which stores the settings in a database. Based on this stored information, the AI ​​agent provides appropriate services using only the information authorized by the user.

[0463] Furthermore, the emotion engine operates on the device and analyzes the user's emotional state from their voice, facial expressions, and input speed. The analyzed emotional information is sent to the server, where dynamic access control settings are adjusted according to the user's current emotional state. For example, if the emotion engine determines that the user is stressed, it restricts access to information and changes settings to enhance privacy.

[0464] The server uses the emotional information transmitted from the emotion engine to process data and optimize the content and method of the services to be provided. This allows for the provision of information and support tailored to the user's emotional state. For example, if the AI ​​agent detects that the user is feeling down, it will provide gentle voice guidance and recommend relaxing content.

[0465] For example, if the emotion engine detects that a user is experiencing stress at work, the server will temporarily minimize access to that user's data while providing services to alleviate that stress. This makes it possible to simultaneously protect privacy and provide user-centric services.

[0466] Thus, the present invention dynamically manages information access based on user emotion analysis and realizes the provision of appropriate services. With this system, users can safely enjoy flexible services that are tailored to their own emotions.

[0467] The following describes the processing flow.

[0468] Step 1:

[0469] Users can choose how much of their information they want to share on their device's privacy settings screen. The device saves this setting locally.

[0470] Step 2:

[0471] The device sends locally stored privacy settings to the server. This transmission is performed using a secure communication protocol.

[0472] Step 3:

[0473] The server stores the privacy settings received from the device in a database. This allows for centralized management of settings that differ for each user.

[0474] Step 4:

[0475] The emotion engine built into the device analyzes the user's voice, facial expressions, input speed, etc., to identify their emotional state in real time.

[0476] Step 5:

[0477] The emotion engine sends the analyzed emotional state to the server. This emotional information is used to dynamically adjust privacy settings.

[0478] Step 6:

[0479] The server determines the appropriate information access settings based on emotional information and updates them as needed. These settings fluctuate according to the user's emotions.

[0480] Step 7:

[0481] The AI ​​agent, having received emotional information and updated access settings from the server, will provide services within the scope of the permitted information. The services will be optimized to match the user's emotional state.

[0482] Step 8:

[0483] When a user reports new privacy settings or emotional states, the device sends this information back to the server, which then updates its database. This iterative process ensures the system continuously provides services that respect user privacy and emotions.

[0484] (Example 2)

[0485] 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."

[0486] In conventional information processing systems, information access was controlled solely based on the user's privacy settings, and dynamic adjustments were not made in response to the user's emotional state. As a result, information provision and service optimization adapted to the user's emotional state were insufficient, leading to a problem of not being able to improve user satisfaction.

[0487] 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.

[0488] In this invention, the server includes means for receiving settings that control access to information based on the type of information selected by the user in the information processing device; means for storing the settings in a database and managing them for each user; means for confirming access permissions to information based on the user's settings and providing services based on the permitted information; means for determining the user's emotional state using a computing device equipped with an emotion engine that analyzes the user's voice, facial expressions, and input speed; and means for dynamically adjusting information access based on the emotional state and modifying the settings in the database in order to provide optimal services. This enables flexible information access management and optimal service provision in accordance with the user's emotional state.

[0489] An "information processing device" refers to a computing system used for collecting, storing, analyzing, processing, and transmitting data, and is operated based on user instructions.

[0490] A "database" refers to an information management system that systematically collects and stores information, and allows for searching and updating as needed.

[0491] An "emotion engine" refers to software or hardware that analyzes information such as the user's voice, facial expressions, and input speed to infer or determine the user's emotional state.

[0492] "Access control" refers to a mechanism that sets and manages the necessary permissions and parameters for users or systems to access information, and allows access only within the permitted scope.

[0493] "Dynamic adjustment of information access" refers to a procedure or function that changes the scope of access permissions to information in real time based on the user's situation, emotions, and other variables.

[0494] "Providing optimal service" refers to the process of proposing and delivering information and solutions in a way that is most appropriate to the user's needs and emotional state.

[0495] This invention is a system that uses an information processing device to achieve dynamic control of information access according to the user's emotional state. The main components are a terminal, a server, and an emotion engine.

[0496] The device provides an interface for users to enter their privacy settings. Users specify the scope and sharing of information they wish to make public. This setting information is stored on the device, encrypted, and sent to the server.

[0497] The server stores received privacy settings in a database and manages them on a per-user basis. The database is protected with a high level of security and serves as the basis for access control.

[0498] The emotion engine installed on the device analyzes the user's emotions through voice recognition technology, facial recognition technology, and input speed monitoring. The hardware used here is a high-performance CPU and GPU, enabling real-time data processing.

[0499] The analyzed emotion data is sent to the server, which then dynamically adjusts the user's access control settings based on this information. For example, if the server determines that the user is experiencing stress, access restrictions will be strengthened and privacy-focused settings will be applied.

[0500] The server also uses a generative AI model to provide services adapted to emotional information. Specifically, if it determines that a user is feeling down, it will recommend gentle voice guidance or relaxation content. This ensures that users can receive appropriate services with peace of mind.

[0501] For example, when a user is experiencing stress at work, the emotion engine detects this, and the server temporarily restricts access to information to a minimum while simultaneously providing information that helps reduce stress. This system provides personalized support to users, achieving a balance between privacy and convenience.

[0502] As an example of a prompt, the system is asked, "What is the best content to recommend when the system determines that the user is in a stressed state?" Based on this, the generating AI model selects the appropriate response and optimizes the service.

[0503] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0504] Step 1:

[0505] The user enters their privacy settings using an interface on their device. Specific inputs include the types of information they want to make public and the scope of that information. The device encrypts the entered settings and stores them locally. The output is the encrypted privacy settings, which are then prepared for transmission to the server.

[0506] Step 2:

[0507] The device sends saved privacy settings to the server. The input is encrypted settings data. The server receives this data and stores it in a database. During the storage process, the data is indexed and converted into a format that allows for efficient searching and management. The output is user-specific privacy settings data stored in the database.

[0508] Step 3:

[0509] The emotion engine built into the device collects the user's voice, facial expressions, and input speed in real time. This biometric data serves as input. The emotion engine analyzes this data to estimate the user's current emotional state. Specific data processing includes voice processing algorithms and facial recognition algorithms. The output is the analyzed emotional data, which is used in the next step.

[0510] Step 4:

[0511] The device securely transmits the analyzed emotion data to the server. This data is processed as input by the server. Based on the received emotion data, the server dynamically adjusts the privacy settings in its database. Specifically, this involves changing access restrictions to adapt to the user's emotional state. The output is the updated access control settings.

[0512] Step 5:

[0513] The server combines updated access control settings and sentiment data to generate service content tailored to the user. A generative AI model then performs calculations to provide the user with the most suitable content and guidance. Specifically, this includes recommendations for gentle voice guidance and relaxing content. The output is a customized service suggestion delivered to the user's device.

[0514] (Application Example 2)

[0515] 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."

[0516] Conventional information processing systems have found it difficult to dynamically adjust services in response to users' emotional states, making it challenging to provide personalized services. Furthermore, the lack of mechanisms to adjust information access control based on users' emotional states has made balancing privacy protection with service flexibility a significant challenge.

[0517] 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.

[0518] In this invention, the server includes means for receiving settings to control access to information based on the type of information selected by the user, means for storing the settings in a database and managing them for each user, and means for analyzing the user's emotional state, dynamically adjusting the access control to the information based on the analysis results, and providing a service appropriate to the user. This makes it possible to achieve both flexible service provision that responds to the user's emotions and enhanced privacy.

[0519] An "information processing device" is a device that receives, analyzes, and stores data, and provides specific functions or services based on that data.

[0520] A "user" is an individual or group that uses an information processing device to access information or services.

[0521] "Access control" refers to restrictions and settings that determine whether a user can access certain information.

[0522] "Saving settings to a database" refers to the process of accumulating setting information selected and entered by users so that it can be referenced later.

[0523] "Emotional state" refers to the state of a user's psychological and emotional response, and is analyzed from factors such as voice, facial expressions, and input speed.

[0524] "Providing a service" refers to the act of supplying information, functions, or support to users in accordance with their requests and circumstances.

[0525] In a form for carrying out the invention, the server, as an information processing device, provides personalized services tailored to the user's emotional state. The server collects necessary data through a specific user interface to accept information access control settings based on the user's choices. It then stores the collected setting information in a database and manages information corresponding to individual users.

[0526] The device includes an emotion engine that analyzes the user's voice, facial expressions, and input speed, allowing it to understand the user's emotional state in real time. The emotion engine is based on hardware such as Raspberry Pi and Jetson Nano, while voice recognition and facial expression analysis utilize cloud AI services such as Google Cloud AI and AWS.

[0527] Based on the user's emotion analysis results, the server dynamically adjusts access control to information and provides services tailored to the user as needed. For example, if the server determines that the user is stressed, it will enhance privacy and provide relaxation music.

[0528] As a concrete example, in a nursing home, residents can receive soothing music through smart glasses, and caregivers are notified of situations requiring immediate attention. In this way, flexible services tailored to the emotional state of the residents become available.

[0529] When using a generative AI model, you can use prompt statements like the following:

[0530] Analyze users' emotional states in real time and suggest what kind of content to provide when they are feeling stressed.

[0531] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0532] Step 1:

[0533] The device acquires the user's voice, facial expressions, and input speed through sensors and microphones. This data is analyzed by an emotion engine. Audio and video data are used as input, and emotional state tags (e.g., stress, relaxation) are generated as output. The emotion engine performs data processing and calculations using cloud AI services such as Google Cloud AI and AWS.

[0534] Step 2:

[0535] The device sends the analyzed emotional state to the server. The input includes emotional state tags and associated user identification information. The server receives this information and compares it with the user's privacy settings stored in the database. The output is a set of adjusted information access settings.

[0536] Step 3:

[0537] The server dynamically adjusts information access and optimizes the service based on the user's emotions. Inputs include emotional state and privacy settings. Specifically, it strengthens access restrictions for stressed users and changes the content provided to relaxing music and suggestions. The output is the generated optimized service content.

[0538] Step 4:

[0539] As feedback to the user, optimized services and content are provided through smart devices (e.g., smart glasses and smartphones). Input includes service details transmitted from the server, and output is the actual content the user receives (e.g., music, visual guides). The user receives this, relaxes, and enjoys a comfortable environment.

[0540] In this way, a system is realized in which servers, terminals, and users work together to provide services that respond to emotions in real time.

[0541] 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.

[0542] 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.

[0543] 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.

[0544] [Fourth Embodiment]

[0545] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0546] 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.

[0547] 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).

[0548] 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.

[0549] 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.

[0550] 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).

[0551] 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.

[0552] 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.

[0553] 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.

[0554] 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.

[0555] 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.

[0556] 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.

[0557] 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".

[0558] This invention provides a system that allows users to properly manage their privacy and enjoy services safely by precisely setting their own information access scope through an information processing device. This system primarily operates through the coordinated operation of three elements: a terminal, a server, and the user.

[0559] First, users use the interface on their device to select the types of information they want to share (e.g., age, location, contacts, purchase history). Options include "share," "restrict," and "don't share," allowing users to manage their privacy by setting preferences for each piece of information.

[0560] The device temporarily saves the user's selected settings locally before sending them to the server. The server receives this information and stores it in a database to manage access permissions for each user. This stored information is then used in conjunction with subsystems such as AI agents to ensure that only authorized information is used.

[0561] The server provides the AI ​​agent with updated settings as needed, based on the user's configuration. When requested by the user, the AI ​​agent retrieves the latest settings from the server and accesses the information according to the user's privacy settings. This allows the AI ​​agent to use permitted information to appropriately provide customized services to the user.

[0562] For example, if a user sets their location information sharing to "not shared," the AI ​​agent will not access their location information and will provide services based on other permitted information. On the other hand, if the user sets their schedule information to "shared," the AI ​​agent can notify the user of schedule-based reminders.

[0563] This system allows users to flexibly access the services they need while ensuring their privacy is securely protected. This reduces the risk of information leaks, allowing users to use AI agents with peace of mind.

[0564] The following describes the processing flow.

[0565] Step 1:

[0566] The user accesses the device's privacy settings screen, where the device displays the available information categories. For each information category (e.g., age, location, contacts, purchase history), the user selects one of the following options: "Share," "Restrict," or "Don't Share."

[0567] Step 2:

[0568] The device temporarily saves the user's selected privacy settings locally. This saving process occurs when all settings have been completed.

[0569] Step 3:

[0570] The device sends the saved privacy settings to the server using a secure protocol. After sending, the device receives a notification that the transmission is complete before proceeding to the next step.

[0571] Step 4:

[0572] The server checks the privacy settings received from the device and stores them in a database. The database stores different settings information for each user.

[0573] Step 5:

[0574] When a user requests information services, the server retrieves the user's privacy settings from the database and provides them to the AI ​​agent.

[0575] Step 6:

[0576] The AI ​​agent analyzes configuration information received from the server and provides services based only on information authorized by the user. For example, if schedule information is shared, the AI ​​agent will use that information to set reminders.

[0577] Step 7:

[0578] When a user changes their settings, the device sends those changes back to the server. The server updates the existing settings with the new settings, keeping them up-to-date.

[0579] (Example 1)

[0580] 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".

[0581] Conventional information processing systems often suffer from insufficient user privacy settings and cumbersome settings management, making it difficult for users to manage their information and access services with peace of mind. In particular, there is a lack of mechanisms to ensure the safe and efficient use of only authorized information.

[0582] 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.

[0583] In this invention, the server includes means for the user to set privacy settings for the type of information provided via an information processing device, means for temporarily saving the settings to local storage and securely transmitting them to the server, and means for providing the AI ​​agent with the user's latest settings and executing customized services based on the permitted information. This enables the user to receive secure and optimized services while flexibly managing their own privacy.

[0584] An "information processing device" is a device used by users to process and manage digital information, and includes computers, smartphones, and other similar devices.

[0585] "Privacy settings" refer to settings that allow users to choose and control the scope and method of sharing their information.

[0586] "Local storage" refers to a memory area within an information processing device used to temporarily or permanently store data.

[0587] A "server" is a computing device that provides services on a network and shares data and applications with other devices.

[0588] A "database" is a collection of data that is systematically stored and managed to allow efficient access to digital information.

[0589] An "AI agent" is a program or system that uses artificial intelligence technology to autonomously perform specific tasks and provide services to users.

[0590] "Customized service" refers to the process of providing services that are individually tailored to the user's specific requirements and settings.

[0591] "Authorized information" refers to information that a user has authorized to access or use for a specific purpose.

[0592] This system is an information processing system that allows users to precisely control the scope of their information disclosure and receive secure, personalized services. It operates through the close cooperation of three elements: the user, the terminal, and the server.

[0593] First, the user uses a terminal, which is an information processing device, to configure privacy settings for their information via an interface. The terminal accepts the privacy settings and temporarily stores them in local storage. The software used on the terminal includes a user interface and features that allow users to intuitively select settings. The hardware that this terminal is expected to support is a typical computer or smartphone.

[0594] Next, the terminal sends the saved configuration information to the server using a secure protocol (e.g., SSL / TLS). After receiving this information, the server stores it in a database, associated with the user identifier. A relational database management system (RDBMS) is used for this database; suitable examples include PostgreSQL and MySQL.

[0595] Furthermore, the server provides the AI ​​agent with the latest privacy settings in response to user requests. The AI ​​agent then uses a generated AI model to provide the user with customized services based on the permitted information. This ensures that the services provided by the AI ​​agent are tailored to the individual needs of each user.

[0596] For example, if a user sets their location information to "not shared," the AI ​​agent can provide services based on other permitted information (e.g., schedule information) without accessing that information. Users can send requests to the AI ​​agent using prompt messages. A concrete example of a prompt message might be, "Please provide the necessary information for our next meeting, but please avoid my current location."

[0597] In this way, the system can efficiently provide necessary services while firmly protecting user privacy.

[0598] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0599] Step 1:

[0600] Users configure their privacy settings through the device interface. This allows them to select "Share," "Restrict," or "Don't Share" for each type of information they provide (e.g., age, location). This process generates user settings input, which is temporarily stored in local storage in JSON format.

[0601] Step 2:

[0602] The terminal sends the saved configuration information to the server using a security protocol (SSL / TLS). This input information is encrypted along with the user identifier. The server receives the encrypted data, decrypts it, and stores it in the database. At this stage, the database outputs information that classifies and manages access rights for each user.

[0603] Step 3:

[0604] The server provides the user's latest privacy settings in response to a request from the AI ​​agent. In this process, the server retrieves the privacy settings based on the relevant user identifier from the database and forwards them to the AI ​​agent. The output data represents the privacy settings used by the AI ​​agent. Based on these settings, the AI ​​agent creates a response to the user's request.

[0605] Step 4:

[0606] The user sends a service request to the AI ​​agent using a prompt message. The AI ​​agent uses the received prompt message and the privacy settings provided by the server as input, and utilizes a generated AI model to perform the corresponding processing. The output of this data processing is customized service information that conforms to the user's settings. The AI ​​agent provides this information to the user to deliver personalized services.

[0607] This series of processing steps allows users to access safe and efficient information services while maintaining their privacy.

[0608] (Application Example 1)

[0609] 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".

[0610] A major challenge with conventional electronic payment systems is their inability to flexibly accommodate users' diverse privacy needs. Specifically, there is a lack of mechanisms to fulfill users' desires to selectively share only certain information or to have fine-grained control over how their data is handled. Furthermore, there is a need for information provision that reduces the risk of data leaks without compromising convenience.

[0611] 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.

[0612] In this invention, the server includes means for providing an interface for users to make detailed privacy settings for individual information elements; means for processing information elements to selectively share personal attributes according to the settings; database means for storing and managing access rights for the information elements; and artificial intelligence agent means for providing customized functions based on the user's privacy settings. This makes it possible to use payment services efficiently and securely while responding to the user's detailed privacy requests.

[0613] An "interface" refers to the user interface or method of operation used when a user configures privacy settings for information elements.

[0614] "Personal attributes" refer to information elements about the user, including, for example, credit card information, purchase history, and location information.

[0615] An "information element" is a unit of data handled by a system, and refers to the specific information that users choose to provide.

[0616] "Processing" refers to the process by which a system processes and provides information elements based on the user's privacy settings.

[0617] A "database means" is a systemic structure for efficiently storing and managing users' privacy settings and access rights to information elements.

[0618] An "artificial intelligence agent" is a technological entity that analyzes necessary information based on the user's privacy settings and generates appropriate services and responses.

[0619] The system to realize this application primarily operates through the collaboration of a terminal, a server, and an artificial intelligence agent. The terminal uses frontend technologies such as Vue.js or React to provide users with an interface for setting privacy settings. This allows users to intuitively and precisely configure access permissions for personal attributes (e.g., credit card information, purchase history, location information).

[0620] The configured information is received by a backend using Node.js and Express and stored in MongoDB. The server uses this database to manage user configuration information. This enables selective access control to specified information elements, creating a mechanism that appropriately protects user privacy.

[0621] The artificial intelligence agent is built using machine learning libraries such as TensorFlow and processes information based on the user's privacy settings obtained from the server. For example, if a user has set their settings not to share their location, this agent can utilize other available personal attributes without referring to location information to provide customized services. This enables the delivery of services and responses optimized for each individual user.

[0622] As a concrete example, when a user conducts e-commerce, they could provide only their credit card information to a specific store, while keeping other information (such as purchase history or location information) private. This would allow for a safe and comfortable shopping experience without compromising user privacy.

[0623] An example of a prompt for a generated AI model is: "Explain how an AI agent for an electronic payment system with enhanced privacy management can provide the optimal process for providing only credit card information based on user preferences and keeping purchase history private."

[0624] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0625] Step 1:

[0626] The device displays an interface for the user to configure their privacy settings. Through this interface, the user selects access permissions for personal attributes (e.g., credit card information, purchase history, location information). The input is the user's privacy selection, and configuration data is generated based on this selection. The output is the generated configuration data.

[0627] Step 2:

[0628] The device sends user-configured privacy settings data to the backend. Here, it receives privacy settings data as input. The device executes a communication process to send this data to the server, securely transmitting the settings data. The output is the settings data received by the server.

[0629] Step 3:

[0630] The server stores the received privacy settings data in a database and manages it by classifying it for each user. The input is the settings data sent from the terminal, and the output is the settings information stored in the database. The server strictly manages this data and records the access rights for each user.

[0631] Step 4:

[0632] The server's artificial intelligence agent retrieves relevant configuration information from the database when a service request is received from a user. The input is the user's request, and the output is the extracted configuration information. Based on the latest settings, this agent determines which information is available.

[0633] Step 5:

[0634] The artificial intelligence agent performs appropriate information analysis based on the user's privacy settings, processes the necessary information, and provides customized services. The input consists of configuration information and user requests, and the output is the customized service result. Specifically, it uses machine learning algorithms to analyze information and generates the optimal response based on the system's requirements.

[0635] 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.

[0636] This invention provides a system that dynamically adjusts information access control according to the user's emotional state and optimizes service provision by incorporating a new emotion engine into a conventional information processing device. This system is implemented with a terminal, a server, and an emotion engine as its main components.

[0637] Users configure their privacy settings through their device and choose how much of their information they want to share. The device saves these settings locally, then sends them to a server, which stores the settings in a database. Based on this stored information, the AI ​​agent provides appropriate services using only the information authorized by the user.

[0638] Furthermore, the emotion engine operates on the device and analyzes the user's emotional state from their voice, facial expressions, and input speed. The analyzed emotional information is sent to the server, where dynamic access control settings are adjusted according to the user's current emotional state. For example, if the emotion engine determines that the user is stressed, it restricts access to information and changes settings to enhance privacy.

[0639] The server uses the emotional information transmitted from the emotion engine to process data and optimize the content and method of the services to be provided. This allows for the provision of information and support tailored to the user's emotional state. For example, if the AI ​​agent detects that the user is feeling down, it will provide gentle voice guidance and recommend relaxing content.

[0640] For example, if the emotion engine detects that a user is experiencing stress at work, the server will temporarily minimize access to that user's data while providing services to alleviate that stress. This makes it possible to simultaneously protect privacy and provide user-centric services.

[0641] Thus, the present invention dynamically manages information access based on user emotion analysis and realizes the provision of appropriate services. With this system, users can safely enjoy flexible services that are tailored to their own emotions.

[0642] The following describes the processing flow.

[0643] Step 1:

[0644] Users can choose how much of their information they want to share on their device's privacy settings screen. The device saves this setting locally.

[0645] Step 2:

[0646] The device sends locally stored privacy settings to the server. This transmission is performed using a secure communication protocol.

[0647] Step 3:

[0648] The server stores the privacy settings received from the device in a database. This allows for centralized management of settings that differ for each user.

[0649] Step 4:

[0650] The emotion engine built into the device analyzes the user's voice, facial expressions, input speed, etc., to identify their emotional state in real time.

[0651] Step 5:

[0652] The emotion engine sends the analyzed emotional state to the server. This emotional information is used to dynamically adjust privacy settings.

[0653] Step 6:

[0654] The server determines the appropriate information access settings based on emotional information and updates them as needed. These settings fluctuate according to the user's emotions.

[0655] Step 7:

[0656] The AI ​​agent, having received emotional information and updated access settings from the server, will provide services within the scope of the permitted information. The services will be optimized to match the user's emotional state.

[0657] Step 8:

[0658] When a user reports new privacy settings or emotional states, the device sends this information back to the server, which then updates its database. This iterative process ensures the system continuously provides services that respect user privacy and emotions.

[0659] (Example 2)

[0660] 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".

[0661] In conventional information processing systems, information access was controlled solely based on the user's privacy settings, and dynamic adjustments were not made in response to the user's emotional state. As a result, information provision and service optimization adapted to the user's emotional state were insufficient, leading to a problem of not being able to improve user satisfaction.

[0662] 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.

[0663] In this invention, the server includes means for receiving settings that control access to information based on the type of information selected by the user in the information processing device; means for storing the settings in a database and managing them for each user; means for confirming access permissions to information based on the user's settings and providing services based on the permitted information; means for determining the user's emotional state using a computing device equipped with an emotion engine that analyzes the user's voice, facial expressions, and input speed; and means for dynamically adjusting information access based on the emotional state and modifying the settings in the database in order to provide optimal services. This enables flexible information access management and optimal service provision in accordance with the user's emotional state.

[0664] An "information processing device" refers to a computing system used for collecting, storing, analyzing, processing, and transmitting data, and is operated based on user instructions.

[0665] A "database" refers to an information management system that systematically collects and stores information, and allows for searching and updating as needed.

[0666] An "emotion engine" refers to software or hardware that analyzes information such as the user's voice, facial expressions, and input speed to infer or determine the user's emotional state.

[0667] "Access control" refers to a mechanism that sets and manages the necessary permissions and parameters for users or systems to access information, and allows access only within the permitted scope.

[0668] "Dynamic adjustment of information access" refers to a procedure or function that changes the scope of access permissions to information in real time based on the user's situation, emotions, and other variables.

[0669] "Providing optimal service" refers to the process of proposing and delivering information and solutions in a way that is most appropriate to the user's needs and emotional state.

[0670] This invention is a system that uses an information processing device to achieve dynamic control of information access according to the user's emotional state. The main components are a terminal, a server, and an emotion engine.

[0671] The device provides an interface for users to enter their privacy settings. Users specify the scope and sharing of information they wish to make public. This setting information is stored on the device, encrypted, and sent to the server.

[0672] The server stores received privacy settings in a database and manages them on a per-user basis. The database is protected with a high level of security and serves as the basis for access control.

[0673] The emotion engine installed on the device analyzes the user's emotions through voice recognition technology, facial recognition technology, and input speed monitoring. The hardware used here is a high-performance CPU and GPU, enabling real-time data processing.

[0674] The analyzed emotion data is sent to the server, which then dynamically adjusts the user's access control settings based on this information. For example, if the server determines that the user is experiencing stress, access restrictions will be strengthened and privacy-focused settings will be applied.

[0675] The server also uses a generative AI model to provide services adapted to emotional information. Specifically, if it determines that a user is feeling down, it will recommend gentle voice guidance or relaxation content. This ensures that users can receive appropriate services with peace of mind.

[0676] For example, when a user is experiencing stress at work, the emotion engine detects this, and the server temporarily restricts access to information to a minimum while simultaneously providing information that helps reduce stress. This system provides personalized support to users, achieving a balance between privacy and convenience.

[0677] As an example of a prompt, the system is asked, "What is the best content to recommend when the system determines that the user is in a stressed state?" Based on this, the generating AI model selects the appropriate response and optimizes the service.

[0678] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0679] Step 1:

[0680] The user enters their privacy settings using an interface on their device. Specific inputs include the types of information they want to make public and the scope of that information. The device encrypts the entered settings and stores them locally. The output is the encrypted privacy settings, which are then prepared for transmission to the server.

[0681] Step 2:

[0682] The device sends saved privacy settings to the server. The input is encrypted settings data. The server receives this data and stores it in a database. During the storage process, the data is indexed and converted into a format that allows for efficient searching and management. The output is user-specific privacy settings data stored in the database.

[0683] Step 3:

[0684] The emotion engine built into the device collects the user's voice, facial expressions, and input speed in real time. This biometric data serves as input. The emotion engine analyzes this data to estimate the user's current emotional state. Specific data processing includes voice processing algorithms and facial recognition algorithms. The output is the analyzed emotional data, which is used in the next step.

[0685] Step 4:

[0686] The device securely transmits the analyzed emotion data to the server. This data is processed as input by the server. Based on the received emotion data, the server dynamically adjusts the privacy settings in its database. Specifically, this involves changing access restrictions to adapt to the user's emotional state. The output is the updated access control settings.

[0687] Step 5:

[0688] The server combines updated access control settings and sentiment data to generate service content tailored to the user. A generative AI model then performs calculations to provide the user with the most suitable content and guidance. Specifically, this includes recommendations for gentle voice guidance and relaxing content. The output is a customized service suggestion delivered to the user's device.

[0689] (Application Example 2)

[0690] 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".

[0691] Conventional information processing systems have found it difficult to dynamically adjust services in response to users' emotional states, making it challenging to provide personalized services. Furthermore, the lack of mechanisms to adjust information access control based on users' emotional states has made balancing privacy protection with service flexibility a significant challenge.

[0692] 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.

[0693] In this invention, the server includes means for receiving settings to control access to information based on the type of information selected by the user, means for storing the settings in a database and managing them for each user, and means for analyzing the user's emotional state, dynamically adjusting the access control to the information based on the analysis results, and providing a service appropriate to the user. This makes it possible to achieve both flexible service provision that responds to the user's emotions and enhanced privacy.

[0694] An "information processing device" is a device that receives, analyzes, and stores data, and provides specific functions or services based on that data.

[0695] A "user" is an individual or group that uses an information processing device to access information or services.

[0696] "Access control" refers to restrictions and settings that determine whether a user can access certain information.

[0697] "Saving settings to a database" refers to the process of accumulating setting information selected and entered by users so that it can be referenced later.

[0698] "Emotional state" refers to the state of a user's psychological and emotional response, and is analyzed from factors such as voice, facial expressions, and input speed.

[0699] "Providing a service" refers to the act of supplying information, functions, or support to users in accordance with their requests and circumstances.

[0700] In a form for carrying out the invention, the server, as an information processing device, provides personalized services tailored to the user's emotional state. The server collects necessary data through a specific user interface to accept information access control settings based on the user's choices. It then stores the collected setting information in a database and manages information corresponding to individual users.

[0701] The device includes an emotion engine that analyzes the user's voice, facial expressions, and input speed, allowing it to understand the user's emotional state in real time. The emotion engine is based on hardware such as Raspberry Pi and Jetson Nano, while voice recognition and facial expression analysis utilize cloud AI services such as Google Cloud AI and AWS.

[0702] Based on the user's emotion analysis results, the server dynamically adjusts access control to information and provides services tailored to the user as needed. For example, if the server determines that the user is stressed, it will enhance privacy and provide relaxation music.

[0703] As a concrete example, in a nursing home, residents can receive soothing music through smart glasses, and caregivers are notified of situations requiring immediate attention. In this way, flexible services tailored to the emotional state of the residents become available.

[0704] When using a generative AI model, you can use prompt statements like the following:

[0705] Analyze users' emotional states in real time and suggest what kind of content to provide when they are feeling stressed.

[0706] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0707] Step 1:

[0708] The device acquires the user's voice, facial expressions, and input speed through sensors and microphones. This data is analyzed by an emotion engine. Audio and video data are used as input, and emotional state tags (e.g., stress, relaxation) are generated as output. The emotion engine performs data processing and calculations using cloud AI services such as Google Cloud AI and AWS.

[0709] Step 2:

[0710] The device sends the analyzed emotional state to the server. The input includes emotional state tags and associated user identification information. The server receives this information and compares it with the user's privacy settings stored in the database. The output is a set of adjusted information access settings.

[0711] Step 3:

[0712] The server dynamically adjusts information access and optimizes the service based on the user's emotions. Inputs include emotional state and privacy settings. Specifically, it strengthens access restrictions for stressed users and changes the content provided to relaxing music and suggestions. The output is the generated optimized service content.

[0713] Step 4:

[0714] As feedback to the user, optimized services and content are provided through smart devices (e.g., smart glasses and smartphones). Input includes service details transmitted from the server, and output is the actual content the user receives (e.g., music, visual guides). The user receives this, relaxes, and enjoys a comfortable environment.

[0715] In this way, a system is realized in which servers, terminals, and users work together to provide services that respond to emotions in real time.

[0716] 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.

[0717] 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.

[0718] 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.

[0719] 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.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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."

[0725] 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.

[0726] 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.

[0727] 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.

[0728] 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.

[0729] 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.

[0730] 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.

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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.

[0735] 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.

[0736] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0737] The following is further disclosed regarding the embodiments described above.

[0738] (Claim 1)

[0739] An information processing device includes means for receiving settings to control access to information based on the type of information selected by the user,

[0740] A means of saving the aforementioned settings in a database and managing them for each user,

[0741] A means for verifying access permissions for information based on the user's settings and providing services based on the permitted information,

[0742] A system that includes this.

[0743] (Claim 2)

[0744] The system according to claim 1, wherein the information processing device updates and saves the database again when the settings are changed.

[0745] (Claim 3)

[0746] The system according to claim 1, wherein the information processing device periodically checks the user settings obtained from the database when providing the service.

[0747] "Example 1"

[0748] (Claim 1)

[0749] A means by which users can set privacy settings for the types of information they provide via an information processing device,

[0750] A means of temporarily saving the aforementioned settings to local storage and securely sending them to the server,

[0751] The server has means for storing the transmitted settings in a database and managing them based on the user identifier,

[0752] The server provides the AI ​​agent with the user's latest settings and means to perform customized services based on the permitted information.

[0753] A system that includes this.

[0754] (Claim 2)

[0755] The system according to claim 1, wherein the server or information processing device updates the settings in the database again when there is a change in the privacy settings.

[0756] (Claim 3)

[0757] The system according to claim 1, wherein the information processing device periodically retrieves and verifies the user's settings from the database when the AI ​​agent provides a service.

[0758] "Application Example 1"

[0759] (Claim 1)

[0760] A means of providing an interface for users to make detailed privacy settings for individual information elements,

[0761] In order to selectively share personal attributes according to the aforementioned settings, a means for processing information elements,

[0762] A database means for storing and managing access rights for the aforementioned information elements,

[0763] An artificial intelligence agent means that provides customized functions based on the user's privacy settings,

[0764] A system that includes this.

[0765] (Claim 2)

[0766] The system according to claim 1, comprising means for modifying information based on the settings such that personal attributes are provided only under specific conditions.

[0767] (Claim 3)

[0768] The system according to claim 1, wherein an artificial intelligence agent performs information analysis based on the privacy settings and generates a personalized response for each user.

[0769] "Example 2 of combining an emotion engine"

[0770] (Claim 1)

[0771] An information processing device includes means for receiving settings to control access to information based on the type of information selected by the user,

[0772] A means of saving the aforementioned settings in a database and managing them for each user,

[0773] A means for verifying access permissions for information based on the user's settings and providing services based on the permitted information,

[0774] A means for determining the user's emotional state using a computing device equipped with an emotion engine that analyzes the user's voice, facial expressions, and input speed,

[0775] Means for dynamically adjusting information access based on the aforementioned emotional state and modifying settings within the database in order to provide the optimal service,

[0776] A system that includes this.

[0777] (Claim 2)

[0778] The system according to claim 1, wherein if the aforementioned settings are changed, the database is updated and saved again.

[0779] (Claim 3)

[0780] The system according to claim 1, wherein when providing the aforementioned service, the user settings obtained from the database are periodically checked.

[0781] "Application example 2 when combining with an emotional engine"

[0782] (Claim 1)

[0783] An information processing device includes means for receiving settings to control access to information based on the type of information selected by the user,

[0784] A means of saving the aforementioned settings in a database and managing them for each user,

[0785] A means for analyzing the emotional state of the user, dynamically adjusting information access control based on the analysis results, and providing a service suitable for the user,

[0786] A means for verifying access permissions for information based on the user's settings and providing services based on the permitted information,

[0787] A system that includes this.

[0788] (Claim 2)

[0789] The system according to claim 1, wherein the information processing device updates and saves the database again when the settings are changed.

[0790] (Claim 3)

[0791] The system according to claim 1, wherein when the information processing device provides the service, it periodically checks the user settings obtained from the database and also checks the results of access control adjustments based on user sentiment analysis. [Explanation of Symbols]

[0792] 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 of providing an interface for users to make detailed privacy settings for individual information elements, In order to selectively share personal attributes according to the aforementioned settings, a means for processing information elements, A database means for storing and managing access rights for the aforementioned information elements, An artificial intelligence agent means that provides customized functions based on the user's privacy settings, A system that includes this.

2. The system according to claim 1, comprising means for modifying information based on the settings such that personal attributes are provided only under specific conditions.

3. The system according to claim 1, in which an artificial intelligence agent performs information analysis based on the privacy settings and generates a personalized response for each user.

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