system

Abstract

We provide the system. [Solution] An interface for receiving natural language requests from parents, A natural language processing means that analyzes the aforementioned request and generates usage restriction settings for the digital device, Control means for applying the generated settings to a digital device, A monitoring means for monitoring the usage patterns of digital devices and detecting inappropriate use, A notification means that generates an alert based on the aforementioned monitoring results and notifies the parent, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, with the increase in children's use of digital devices, appropriate management of this is required. On the other hand, there are problems such as the complexity of settings and the difficulty of operations that parents face when using conventional parental control systems, the lack of response to individual needs, and the difficulty of understanding and confirming the setting contents. Therefore, there is a need to provide a method that allows parents to easily and flexibly manage the use of digital devices.

Means for Solving the Problems

[0005] This invention provides a system equipped with natural language processing means that receives requests from parents in natural language, analyzes them, and generates restrictions on the use of digital devices. Furthermore, by including control means for applying the generated settings to the digital devices, monitoring means for monitoring usage patterns and detecting inappropriate use, and notification means for generating alerts and notifying parents based on the results, it enables parents to easily manage their children's use of digital devices. In addition, by providing a function to report the current settings in natural language and recommend content based on the child's interests, flexible management is possible according to family policies and the child's development.

[0006] An "interface means" is an input device or system for receiving requests from a parent in natural language.

[0007] "Natural language processing means" refers to a technology or system for analyzing a natural language request received and generating specific usage restriction settings for digital devices based on that analysis.

[0008] "Control means" refers to a device or system that performs the function of applying the generated usage restriction settings to a digital device.

[0009] "Monitoring means" refers to techniques or systems for observing the usage patterns of digital devices and detecting inappropriate use or abnormalities.

[0010] A "notification device" is a device or system that has the function of generating alerts based on monitoring and notifying the parent.

[0011] A "verification device" is a device or system that has the function of reporting the current settings of a digital device to the parent in natural language.

[0012] A "recommendation tool" is a device or system for providing appropriate content based on a user's interests and usage history. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

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

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

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

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

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

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention provides an AI-powered parental control system that allows parents to easily and flexibly manage their children's use of digital devices.

[0035] Specifically, parents can make requests in natural language, supporting intuitive instructions such as "disable internet access after 8 PM" or "allow a specific app to be used for a limited time." These requests are sent to a server, where a natural language processing module parses them and converts them into specific operational instructions.

[0036] Based on the analyzed requests, the server generates digital device usage restrictions and sets the associated policies. This allows for control over the time periods and application access for digital devices.

[0037] Furthermore, the device monitors usage patterns and reports to the server if it detects inappropriate use or similar behavior. This automatically sends an alert to the parent user when abnormal activity is detected.

[0038] In addition, if parents want to know the current settings, they can ask questions using natural language. In response to inquiries such as "Please tell me what the current settings are," the server proactively reports the settings, providing reassurance.

[0039] Furthermore, it includes a feature that recommends content tailored to children's interests, such as recommending educational apps and appropriate entertainment content to the device, thereby promoting healthy device use.

[0040] In this way, by making full use of AI agents, we are providing a model that allows parents to more optimally manage their children's digital use.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user enters and submits a request regarding parental control settings in natural language.

[0044] Step 2:

[0045] The server analyzes the natural language request received from the user. Natural language processing technology is used for the analysis, converting the request content into specific function configuration instructions.

[0046] Step 3:

[0047] The server generates a digital device usage restriction policy based on the analysis results. This policy includes settings for usage time and access restrictions.

[0048] Step 4:

[0049] The server sends the generated usage restriction policy to the terminal.

[0050] Step 5:

[0051] The device applies the received policy settings to the device's management system and activates the specified restrictions. These include time limits and application controls.

[0052] Step 6:

[0053] The device monitors device usage in real time. If inappropriate use or abnormal access is detected, it records it and reports it to the server.

[0054] Step 7:

[0055] The server generates an alert based on the detected anomaly and notifies the user. The notification is sent via methods such as email or push notification.

[0056] Step 8:

[0057] Users can inquire about their current settings and device usage in natural language.

[0058] Step 9:

[0059] The server analyzes the current configuration and reports it to the user in an easy-to-understand format.

[0060] Step 10:

[0061] The server recommends appropriate content to the device based on interest analysis. This allows users to select content based on their interests.

[0062] (Example 1)

[0063] 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."

[0064] In modern times, the inappropriate use of digital information processing devices by children is a problem, and parents are required to effectively manage their children's use and provide them with appropriate content. However, conventional parental control systems are often cumbersome and not intuitive for parents, so there is a need for simpler and more flexible management methods.

[0065] 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.

[0066] In this invention, the server includes an interface means for receiving natural language requests from a parent, a natural language processing means for analyzing the request and generating usage restriction settings for the digital information processing device, and a control means for applying the generated settings to the digital information processing device. This allows parents to intuitively manage their child's use of the digital information processing device and flexibly set usage restriction policies.

[0067] An "interface means" is a means of receiving requests from a parent using natural language, and provides a point of contact for the user to interact with the system.

[0068] A "natural language processing means" is a means for analyzing a received natural language request and converting it into specific instructions, such as setting usage restrictions for a digital information processing device.

[0069] "Control means" refers to means for applying the generated usage restriction settings to a digital information processing device and managing the use of the device.

[0070] "Observation means" refers to means for monitoring the usage of digital information processing equipment, detecting inappropriate use, and recording the results.

[0071] A "notification method" is a means of generating a warning and notifying parents when inappropriate use is detected.

[0072] A "response mechanism" is a means of reporting the current settings of a digital information processing device in response to a parent's natural language question.

[0073] "Recommendation means" refers to a means of recommending information based on the interests of users of digital information processing devices, and promotes appropriate content use.

[0074] This invention relates to a system for parents to manage their children's use of digital information processing devices. The system is configured as follows:

[0075] First, the user (the parent) can input requests in natural language through the digital information processing device. For example, the parent can use a smartphone app to make a request through the interface such as, "Please disable internet access after 8 PM." This request is then sent to the server.

[0076] The server analyzes received requests using a generative AI model, a natural language processing tool. The generative AI model converts the requests into specific operation instructions and generates usage restriction settings. This analysis process utilizes natural language processing technology, enabling efficient interpretation of requests.

[0077] Next, the server applies the generated usage restriction settings to the digital information processing device as a control mechanism. This sets the time periods and access controls for the child's device. For example, it is possible to set it to "allow specific apps only between 9 AM and 5 PM every weekend."

[0078] Furthermore, the terminal is equipped with monitoring mechanisms to track usage, and if inappropriate use is detected, it reports the results to the server. For example, if there is an attempt to access the internet outside of the specified time, the server will be notified of the situation.

[0079] Based on its observations, the server sends alerts to parents as a means of notification. For example, it might send a notification to the parent's device stating, "Your child attempted to access the internet after 8 PM."

[0080] Furthermore, if the parent asks a question in natural language such as "What are the current settings?", the server will use a response mechanism to provide information about the current device settings. This allows the parent to always know the status of the device's settings.

[0081] Furthermore, the proposed means includes a function to recommend information based on the user's interests. For example, it can suggest educational apps or appropriate entertainment content to the device, promoting healthy device use by children.

[0082] As an example of a prompt, a parent might input a question into the system such as, "How do I set it so my child can only play games between 6 PM and 8 PM on weekdays?", and the generating AI model would then suggest a method for doing so. In this way, the present invention is configured to allow parents to implement intuitive and flexible parental controls.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users input natural language requests through a smartphone app. These requests include instructions regarding restrictions on children's use of digital information processing devices. For example, they might input a sentence like, "Please disable internet access after 8 PM," which becomes the input data. The submitted request is then sent to the server.

[0086] Step 2:

[0087] The server analyzes the received natural language request using natural language processing tools. Specifically, a generative AI model analyzes the request content and converts it into instructions for usage restriction policies. The output of this process is, for example, a specific policy setting such as "Restrict internet access after 8 PM."

[0088] Step 3:

[0089] The server sends a usage restriction policy, generated based on the analysis results, to the terminal via a control mechanism. Here, control data is created and sent to the terminal as output. Specifically, the policy is applied to the terminal's configuration module, and the device's network functionality is restricted for the specified period.

[0090] Step 4:

[0091] The terminal uses monitoring devices to observe their usage. It takes current user behavior data as input and performs calculations to determine if there is inappropriate use. If inappropriate use is detected, it creates an event log and reports it to the server. For example, if an attempt is made to access the internet outside of a specified time, the date, time, and details of the attempt are recorded in the log.

[0092] Step 5:

[0093] The server receives reports from the device, generates an alert using a notification system based on the observation results, and notifies the parent. It receives event logs from the device as input and creates a notification message for the parent as output. Specifically, it sends a notification to the parent's smartphone stating, "Your child attempted to access the internet after 8 PM."

[0094] Step 6:

[0095] When a user inquires about the current device settings, the server provides that information using a response mechanism. It receives an inquiry from the parent as input and performs calculations to retrieve the current settings information from the database. The output is detailed information about the settings, specifically a response such as, "Currently, internet access is restricted from 8 PM to 7 AM the following morning."

[0096] (Application Example 1)

[0097] 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."

[0098] In modern households, it is crucial to properly manage and ensure the safe use of children's digital devices, but there is a lack of easy-to-use tools for parents to do so. Furthermore, there is a need for healthier device use through recommendations of appropriate content based on children's usage patterns. Additionally, features that monitor children's movements within the home in real time and issue safety-conscious warnings are also necessary.

[0099] 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.

[0100] In this invention, the server includes a communication medium for receiving natural language requests from parents, a natural language analysis means for analyzing the requests and generating usage restriction settings for the information processing device, and a recommendation means for presenting information resources based on the interests of the user of the information processing device. This makes it possible for parents to intuitively configure settings and promote healthy digital device use by their children.

[0101] A "communication medium" is an environment or interface for receiving natural language requests from a parent.

[0102] "Natural language processing means" refers to a function that analyzes natural language requests from the parent and generates usage restriction settings for the information processing device.

[0103] "Information processing device" refers to all digital devices, which are devices whose use is restricted or whose settings are applied based on instructions from parents.

[0104] A "management mechanism" is a control mechanism for applying the analyzed settings to an information processing device.

[0105] A "detection means" is a device that has the function of monitoring the usage trends of an information processing device and detecting inappropriate use.

[0106] "Notification means" refers to a function that generates a warning and communicates it to the parent when inappropriate use is detected.

[0107] "Motion analysis means" refers to technology for analyzing the surrounding environment and recognizing a child's activities.

[0108] A "recommended means" is a device that has the function of presenting information resources based on the interests of the user of the information processing device.

[0109] The system of this invention is designed to implement parental control utilizing AI technology. The server receives natural language requests from parents and plays a role in managing usage restrictions on the terminal, which is an information processing device.

[0110] The server functions as a local server using a Raspberry Pi and utilizes TENSORFLOW® for natural language processing of received requests. The processed instructions are applied to the terminal by a management system. Requests from the parent are input via voice through the microphone, and the server converts the voice to text for processing.

[0111] The device monitors the surrounding environment using image analysis technologies such as OpenCV and detects the child's movements. Based on this information, the server provides feedback to the parent via voice or text to notify them of appropriate alerts.

[0112] Furthermore, based on the usage patterns of the child user, appropriate content is provided through recommendation mechanisms. This information is communicated to parents in real time through data flow control using Node-RED. For example, if a parent requests that a specific app be locked after 9 PM, the server and device will work together to comply with that instruction.

[0113] Examples of prompt messages include the following:

[0114] "Voice input: Set it so that I can't play games after 9 PM."

[0115] "Natural language processing output: Set a policy to lock game apps at 9 PM."

[0116] "Example alert: Your child is engrossed in a game, and it's past 9 PM."

[0117] "Recommendation: Show a list of learning apps for children?"

[0118] Thus, the system of the present invention helps parents intuitively manage the use of digital devices and provides a means for creating a safe and healthy digital environment.

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The user inputs a request in natural language via a microphone. This audio data is received by the server. The server converts this audio input into text data using a service such as Google® Speech-to-Text.

[0122] Step 2:

[0123] The server inputs text data into a natural language processing tool such as TensorFlow to analyze the intended usage restrictions. This analysis process converts the parent request into clear control instructions. For example, it might generate an instruction such as "Disable games after 9 PM."

[0124] Step 3:

[0125] Based on the analysis results, the server utilizes management tools to generate specific control instructions for the terminal. These control instructions are sent to the terminal as a policy to be applied directly to the device. At this time, the terminal updates the usage settings of the information processing device and applies the specified restrictions.

[0126] Step 4:

[0127] The device uses OpenCV to monitor camera input and perform motion analysis. This data is used to recognize the child's activity patterns, and if inappropriate behavior is detected, it is saved as a record of that behavior.

[0128] Step 5:

[0129] When the device detects inappropriate activity or exceeds usage time limits, it notifies the server of an alert. Based on the generated data, this alert is sent to the user (parent) via email or app notification.

[0130] Step 6:

[0131] When a user requests to check the current settings of their device, the server generates the latest settings information in natural language and notifies the parent. This allows the parent to easily understand the current settings.

[0132] Step 7:

[0133] Using a recommendation system, information resources are analyzed based on the user's interests and usage patterns. The server organizes this information and generates a list of recommended educational apps and entertainment content for parents, as in this application example. This recommendation information is converted into a format preferred by the parents and communicated to them.

[0134] 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.

[0135] This invention's system, in addition to providing parents with a means to manage their children's use of digital devices in natural language, incorporates an emotion engine that recognizes user emotions, enabling more personalized management and content delivery.

[0136] In this system, the user (parent) first issues a request in natural language regarding restrictions on the use of digital devices, which is then received and analyzed by the server. The analyzed request is then applied to the device as a restriction on its use.

[0137] Furthermore, the device is equipped with an emotion engine that analyzes the user's, or child's, emotions. For example, if a child feels stressed while using the device, that emotional information is sent to the server. Based on this emotional information, the server dynamically adjusts the digital device usage restriction settings and notifies the parent.

[0138] If the emotion engine detects that a child is showing interest in a particular situation, such as while using a learning application, the server can decide to extend the usage time. Furthermore, based on emotional information, the server selects and recommends appropriate content to the device. This results in a digital experience that is more engaging for children and optimized for learning and entertainment.

[0139] Users can receive real-time notifications of these setting changes and reports on their child's emotional state. They can also query the server in natural language about current device settings and recommended content, and the server will provide responses accordingly.

[0140] In this way, we provide a system that goes beyond conventional parental controls, enabling management and content delivery tailored to individual emotions.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] The user enters and submits a request to the system in natural language regarding restrictions on the use of digital devices.

[0144] Step 2:

[0145] The server receives natural language requests sent by users, analyzes the requests using natural language processing techniques, and converts them into specific operation instructions.

[0146] Step 3:

[0147] The server generates and determines which digital device usage restriction policies to apply based on the analyzed requests.

[0148] Step 4:

[0149] The server sends the generated usage restriction policy to the terminal of the specified digital device.

[0150] Step 5:

[0151] The device applies the received usage restriction policy to its device settings and begins to implement specific controls. For example, it might enable a setting to limit the amount of time the device can be used.

[0152] Step 6:

[0153] The device's emotion engine recognizes the emotional state of the child user in real time. This analysis uses data such as facial expressions and voice tone.

[0154] Step 7:

[0155] The server receives user emotion information sent from the emotion engine and dynamically adjusts device usage restrictions accordingly. For example, it might change settings to temporarily allow access to specific content to reduce stress.

[0156] Step 8:

[0157] The server uses emotional information to recommend the most suitable content to the user and displays it on the device.

[0158] Step 9:

[0159] The server notifies the user of changes in settings and information about the child's emotional state. This allows parents to always know what their child is doing and manage their child with peace of mind.

[0160] Step 10:

[0161] When a user queries the server in natural language about the device's current settings or sentiment analysis results, the server immediately provides a response and explains the situation.

[0162] This series of processes enables flexible and appropriate management of digital devices in response to the user's emotions.

[0163] (Example 2)

[0164] 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".

[0165] In the modern use of information processing devices, there is a lack of means for parents to properly manage their children's device use. In particular, there is a need for systems that not only limit usage time but also dynamically adjust settings based on the child's emotional state and provide appropriate content. The challenge is to create such systems that enrich and safer children's digital experiences and provide an environment where parents can manage their children's devices with peace of mind.

[0166] 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.

[0167] In this invention, the server includes communication means for receiving requests from parents in natural language, means for analyzing the requests using natural language processing technology and generating usage restriction settings for the information processing device, and means for analyzing the user's emotional state using an emotion analysis engine. This enables parents to flexibly and individually manage their child's use of digital devices based on their emotional state.

[0168] A "parent" is someone who manages their child's use of digital devices and sets appropriate restrictions and content.

[0169] "Natural language" refers to the language that parents use on a daily basis to intuitively communicate instructions and restrictions regarding digital devices.

[0170] "Communication methods" refer to the technical means used to send requests from a parent to a server, and involve exchanging information via the internet or wireless communication.

[0171] "Natural language processing means" refers to technology for analyzing received natural language requests and converting them into specific usage restriction settings.

[0172] "Information processing equipment" is a general term for digital devices used by children, and includes smartphones, tablets, and personal computers.

[0173] "Control means" refers to means for applying the generated usage restriction settings to the information processing device and controlling the operation of the device.

[0174] An "emotion analysis engine" is a technology that analyzes a user's emotions from their facial expressions and voice, and optimizes device settings based on that analysis.

[0175] "Adjustment means" refers to technical means that dynamically change settings based on information from the emotion analysis engine, enabling device management tailored to the child's situation.

[0176] "Recommendation methods" are features that select and provide users with appropriate content and information based on emotional information.

[0177] A "notification method" is a way for a server to send setting changes and emotional information to the parent in real time, thereby communicating necessary information.

[0178] This invention is implemented as a system for parents to flexibly manage their children's use of information processing devices. This system has the function of receiving and analyzing instructions from parents in natural language and setting restrictions on the use of the information processing device based on the analysis results.

[0179] First, the user (parent) accesses the system via a smartphone or computer and enters requests regarding restrictions on the use of digital devices in natural language. For example, they can send a request such as, "Please restrict games after 9 PM every day." This request is sent to the server via communication means.

[0180] The server uses natural language processing techniques to parse this request, leveraging technologies such as "spaCy" and "Google Cloud Natural Language API." This interprets the request as data, generating specific usage restriction settings. These generated settings are then sent to the appropriate information processing device via a control mechanism and applied to the terminal.

[0181] Furthermore, the device is equipped with an emotion analysis engine that analyzes the child's emotions in real time while they are using it. For example, it can determine whether the child is feeling stressed based on their facial expressions and tone of voice. This analysis result is sent to a server, which allows the server to dynamically adjust the device usage restrictions.

[0182] The server can select appropriate content based on the child's emotional state and recommend learning materials or relaxing music that might interest them to their device. This makes the child's digital experience more personalized and enhances its educational and entertainment value.

[0183] Parents, as users, can receive real-time reports on device usage settings and their child's emotional state. This allows for intuitive management of the information device at any time. For example, by inputting a prompt such as, "I want my child to listen to relaxing music to refresh themselves more often, how can I change the device settings?" into the generative AI model, they can receive advice on appropriate restriction setting changes.

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

[0185] Step 1:

[0186] Parents, acting as users, enter requests regarding restrictions on digital device use via smartphones or computers using natural language. These requests might include phrases like, "I want to restrict gaming after 9 PM every day." The input data is in text format and is sent to the system.

[0187] Step 2:

[0188] The server receives natural language requests from its parent via a communication method. Natural language processing techniques are used to parse the received text-based requests. This analysis utilizes tools such as "spaCy" and "Google Cloud Natural Language API" to extract the purpose and conditions of the request and generate usage restriction settings. The output is a specific usage restriction policy.

[0189] Step 3:

[0190] The server uses control mechanisms to send the generated usage restriction policy to the appropriate terminal. The information sent includes instructions such as the time limit and the applications to be restricted. The terminal receives the policy and applies it to its device settings. This causes the terminal to automatically restrict applications during the specified time.

[0191] Step 4:

[0192] The device's built-in emotion analysis engine analyzes the user's emotional state in real time while the device is in use. Input data includes camera images and audio data, which are used to determine the user's emotions from their facial expressions and tone of voice. The analysis results are output as emotional information, such as whether the user is interested or stressed.

[0193] Step 5:

[0194] The server receives emotional information sent from the device. Based on this emotional information, the server uses an AI algorithm to dynamically adjust device usage restrictions. For example, if the server determines that a child is showing interest in learning, it decides to extend the usage time and notifies the parent. The notification is sent in real time to the parent's device.

[0195] Step 6:

[0196] The server selects appropriate content based on emotional information. Specifically, it chooses learning and entertainment content that is suitable for the user's interests and relaxation needs. The selected content information is sent to the device and recommended to the user. This ensures that content that is likely to interest the child is displayed on the device.

[0197] (Application Example 2)

[0198] 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".

[0199] In modern society, autonomous vehicles are expanding as a means of transportation, but they face the challenge of not being able to dynamically adjust the in-vehicle environment in response to passengers' emotions and psychological states. Currently, the in-vehicle environment settings are uniform, making it impossible to provide an optimal ride experience for individual passengers. This, in turn, hinders passenger comfort and satisfaction.

[0200] 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.

[0201] In this invention, the server includes a system interface means for receiving natural language requests from a parent; a natural language analysis means for analyzing the requests and generating usage restriction settings for the information processing device; a monitoring means for monitoring usage patterns of the information processing device and detecting inappropriate use; and a control means for performing control on the environment control device based on the user's emotional state. This makes it possible to individually optimize the in-vehicle environment based on the emotions of passengers and improve their comfort.

[0202] "System interface means" refers to means that provide input devices and communication protocols for receiving requests from parents in natural language.

[0203] "Natural language analysis means" refers to means that use language analysis techniques to analyze received requests and generate usage restriction settings for information processing devices.

[0204] "Control means" refers to means for actually applying the generated usage restriction settings of the information processing device to the device and controlling its operation according to the settings.

[0205] "Monitoring means" refers to means for monitoring the usage status of information processing equipment and detecting inappropriate use.

[0206] A "notification means" is a means of notifying the parent of an alarm generated based on the monitoring results.

[0207] An "environmental control device" is a device that adjusts the physical environment inside a vehicle based on the user's emotional state.

[0208] The system for realizing this invention has the function of dynamically adjusting the in-vehicle environment based on passengers' emotions. The server utilizes an emotion engine and uses software such as OpenCV and Google Cloud Speech-to-Text to analyze the emotional state from passengers' voices and facial expressions.

[0209] The server analyzes passengers' emotions in real time and issues instructions to the vehicle's environmental control system based on the results. This automatically adjusts the in-car environment, including lighting, temperature, and music, according to the passengers' psychological state. Specifically, if the emotion engine detects that a passenger wants to relax, the lighting can be changed to a warmer color and relaxing music can be played.

[0210] The device acquires data through the in-car camera and microphone and sends it to a server. The server uses this data to perform emotion recognition and implements environmental control based on the results. Users do not need to do anything in particular and can enjoy a natural riding experience.

[0211] A concrete example would be a prompt message such as, "If the system detects that the passenger is tired, change the car's lighting to a warm color and play relaxing music." Based on this prompt message, the system can provide an optimized environment based on the passenger's emotions.

[0212] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0213] Step 1:

[0214] The terminal uses cameras and microphones installed inside the vehicle to acquire video and audio data of passengers in real time. The input is data from the cameras and microphones, and the output is data transmission to the server. After acquiring the data, the terminal sends it to the server.

[0215] Step 2:

[0216] The server analyzes the received video data using OpenCV and converts the audio data to text using Google Cloud Speech-to-Text. The input for this step is the video and audio data sent from the terminal, and the output is the analyzed emotional state. The emotion engine identifies the user's emotions based on this data.

[0217] Step 3:

[0218] The server generates instructions for the in-car environmental control system based on the analyzed emotional state. The input in this case is the emotional state output by the emotion engine, and the output is the environmental control instruction. For example, the server might generate an instruction such as "Play relaxing music and change the lighting to a warm color."

[0219] Step 4:

[0220] The environmental control system receives instructions from the server and adjusts the in-vehicle environment. The input for this step is the control instructions from the server, and the output is the adjusted in-vehicle environment. Specifically, this might involve playing music or changing the lighting.

[0221] Step 5:

[0222] The user experiences a tuned in-car environment. There is no explicit input in this step; the output is the comfortable ride the user experiences. The user enjoys an environment optimized by the system.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] [Second Embodiment]

[0227] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0228] 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.

[0229] 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).

[0230] 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.

[0231] 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.

[0232] 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).

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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".

[0239] This invention provides an AI-powered parental control system that allows parents to easily and flexibly manage their children's use of digital devices.

[0240] Specifically, parents can make requests in natural language, supporting intuitive instructions such as "disable internet access after 8 PM" or "allow a specific app to be used for a limited time." These requests are sent to a server, where a natural language processing module parses them and converts them into specific operational instructions.

[0241] Based on the analyzed requests, the server generates digital device usage restrictions and sets the associated policies. This allows for control over the time periods and application access for digital devices.

[0242] Furthermore, the device monitors usage patterns and reports to the server if it detects inappropriate use or similar behavior. This automatically sends an alert to the parent user when abnormal activity is detected.

[0243] In addition, if parents want to know the current settings, they can ask questions using natural language. In response to inquiries such as "Please tell me what the current settings are," the server proactively reports the settings, providing reassurance.

[0244] Furthermore, it includes a feature that recommends content tailored to children's interests, such as recommending educational apps and appropriate entertainment content to the device, thereby promoting healthy device use.

[0245] In this way, by making full use of AI agents, we are providing a model that allows parents to more optimally manage their children's digital use.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user enters and submits a request regarding parental control settings in natural language.

[0249] Step 2:

[0250] The server analyzes the natural language request received from the user. Natural language processing technology is used for the analysis, converting the request content into specific function configuration instructions.

[0251] Step 3:

[0252] The server generates a digital device usage restriction policy based on the analysis results. This policy includes settings for usage time and access restrictions.

[0253] Step 4:

[0254] The server sends the generated usage restriction policy to the terminal.

[0255] Step 5:

[0256] The device applies the received policy settings to the device's management system and activates the specified restrictions. These include time limits and application controls.

[0257] Step 6:

[0258] The device monitors device usage in real time. If inappropriate use or abnormal access is detected, it records it and reports it to the server.

[0259] Step 7:

[0260] The server generates an alert based on the detected anomaly and notifies the user. The notification is sent via methods such as email or push notification.

[0261] Step 8:

[0262] Users can inquire about their current settings and device usage in natural language.

[0263] Step 9:

[0264] The server analyzes the current configuration and reports it to the user in an easy-to-understand format.

[0265] Step 10:

[0266] The server recommends appropriate content to the device based on interest analysis. This allows users to select content based on their interests.

[0267] (Example 1)

[0268] 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."

[0269] In modern times, the inappropriate use of digital information processing devices by children is a problem, and parents are required to effectively manage their children's use and provide them with appropriate content. However, conventional parental control systems are often cumbersome and not intuitive for parents, so there is a need for simpler and more flexible management methods.

[0270] 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.

[0271] In this invention, the server includes an interface means for receiving natural language requests from a parent, a natural language processing means for analyzing the request and generating usage restriction settings for the digital information processing device, and a control means for applying the generated settings to the digital information processing device. This allows parents to intuitively manage their child's use of the digital information processing device and flexibly set usage restriction policies.

[0272] An "interface means" is a means of receiving requests from a parent using natural language, and provides a point of contact for the user to interact with the system.

[0273] A "natural language processing means" is a means for analyzing a received natural language request and converting it into specific instructions, such as setting usage restrictions for a digital information processing device.

[0274] "Control means" refers to means for applying the generated usage restriction settings to a digital information processing device and managing the use of the device.

[0275] "Observation means" refers to means for monitoring the usage of digital information processing equipment, detecting inappropriate use, and recording the results.

[0276] A "notification method" is a means of generating a warning and notifying parents when inappropriate use is detected.

[0277] A "response mechanism" is a means of reporting the current settings of a digital information processing device in response to a parent's natural language question.

[0278] "Recommendation means" refers to a means of recommending information based on the interests of users of digital information processing devices, and promotes appropriate content use.

[0279] This invention relates to a system for parents to manage their children's use of digital information processing devices. The system is configured as follows:

[0280] First, the user (the parent) can input requests in natural language through the digital information processing device. For example, the parent can use a smartphone app to make a request through the interface such as, "Please disable internet access after 8 PM." This request is then sent to the server.

[0281] The server analyzes received requests using a generative AI model, a natural language processing tool. The generative AI model converts the requests into specific operation instructions and generates usage restriction settings. This analysis process utilizes natural language processing technology, enabling efficient interpretation of requests.

[0282] Next, the server applies the generated usage restriction settings to the digital information processing device as control means. As a result, time zones and access control for use are imposed on the child's terminal. As a specific example, it is possible to set "permit a specific application only between 9:00 am and 5:00 pm every weekend".

[0283] Furthermore, the terminal includes observation means for monitoring the usage situation, and when inappropriate use is detected, the result is reported to the server. For example, if there is an attempt to access the Internet outside the specified time, the situation is notified to the server.

[0284] Based on the observation result, the server sends an alert to the parent as notification means. For example, a notification with the content "Your child has attempted to access the Internet after 8:00 pm" is sent to the parent's terminal.

[0285] Also, when the parent asks a question in natural language such as "Tell me the current settings", the server uses response means to provide information on the current device settings. As a result, the parent can always grasp the setting status of the device.

[0286] Furthermore, it has a function of recommending information based on the interests of the user of the digital information processing device using recommendation means. For example, educational applications and appropriate entertainment content can be proposed to the terminal, and healthy use of the device by children can be promoted.

[0287] As an example of a prompt sentence, when the parent inputs a question to the system such as "Tell me how to set it so that the child can play games only from 6:00 pm to 8:00 pm on weekdays", the generation AI model proposes a setting method related to this. Thus, the present invention is configured so that the parent can intuitively perform flexible parental control.

[0288] The flow of the specific process in Example 1 will be described using FIG. 11.

[0289] Step 1:

[0290] Users input natural language requests through a smartphone app. These requests include instructions regarding restrictions on children's use of digital information processing devices. For example, they might input a sentence like, "Please disable internet access after 8 PM," which becomes the input data. The submitted request is then sent to the server.

[0291] Step 2:

[0292] The server analyzes the received natural language request using natural language processing tools. Specifically, a generative AI model analyzes the request content and converts it into instructions for usage restriction policies. The output of this process is, for example, a specific policy setting such as "Restrict internet access after 8 PM."

[0293] Step 3:

[0294] The server sends a usage restriction policy, generated based on the analysis results, to the terminal via a control mechanism. Here, control data is created and sent to the terminal as output. Specifically, the policy is applied to the terminal's configuration module, and the device's network functionality is restricted for the specified period.

[0295] Step 4:

[0296] The terminal uses monitoring devices to observe their usage. It takes current user behavior data as input and performs calculations to determine if there is inappropriate use. If inappropriate use is detected, it creates an event log and reports it to the server. For example, if an attempt is made to access the internet outside of a specified time, the date, time, and details of the attempt are recorded in the log.

[0297] Step 5:

[0298] The server receives reports from the device, generates an alert using a notification system based on the observation results, and notifies the parent. It receives event logs from the device as input and creates a notification message for the parent as output. Specifically, it sends a notification to the parent's smartphone stating, "Your child attempted to access the internet after 8 PM."

[0299] Step 6:

[0300] When a user inquires about the current device settings, the server provides that information using a response mechanism. It receives an inquiry from the parent as input and performs calculations to retrieve the current settings information from the database. The output is detailed information about the settings, specifically a response such as, "Currently, internet access is restricted from 8 PM to 7 AM the following morning."

[0301] (Application Example 1)

[0302] 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."

[0303] In modern households, it is crucial to properly manage and ensure the safe use of children's digital devices, but there is a lack of easy-to-use tools for parents to do so. Furthermore, there is a need for healthier device use through recommendations of appropriate content based on children's usage patterns. Additionally, features that monitor children's movements within the home in real time and issue safety-conscious warnings are also necessary.

[0304] 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.

[0305] In this invention, the server includes a communication medium for receiving a request in natural language from a parent, a natural language analysis means for analyzing the request and generating a usage restriction setting for an information processing device, and a recommendation means for presenting information resources based on the interests of the user of the information processing device. Thereby, it becomes possible for the parent to intuitively make settings and promote the healthy use of digital devices by children.

[0306] The "communication medium" is an environment or interface for receiving a natural language request from a parent.

[0307] The "natural language analysis means" refers to a function that analyzes a request in natural language from a parent and generates a usage restriction setting for an information processing device.

[0308] The "information processing device" refers to all digital devices, and is a device to which usage restrictions and settings are applied upon receiving instructions from a parent.

[0309] The "management means" is a control mechanism for applying the analyzed settings to an information processing device.

[0310] The "detection means" is a device having a function of monitoring the usage tendency of an information processing device and detecting inappropriate usage.

[0311] The "notification means" is a function of generating a warning when inappropriate usage is detected and communicating it to the parent.

[0312] The "behavior analysis means" is a technology for analyzing the surrounding environment and recognizing the activities of children.

[0313] The "recommendation means" is a device having a function of presenting information resources based on the interests of the user of an information processing device.

[0314] The system of this invention is for realizing parental control utilizing AI technology. The server receives a natural language request from a parent and plays a role in managing usage restrictions for a terminal which is an information processing device.

[0315] The server functions as a local server using a Raspberry Pi and utilizes TensorFlow to perform natural language processing on received requests. The parsed instructions are then applied to the terminal by a management mechanism. Requests from the parent are input via voice through the microphone, and the server converts the voice to text for processing.

[0316] The device monitors the surrounding environment using image analysis technologies such as OpenCV and detects the child's movements. Based on this information, the server provides feedback to the parent via voice or text to notify them of appropriate alerts.

[0317] Furthermore, based on the usage patterns of the child user, appropriate content is provided through recommendation mechanisms. This information is communicated to parents in real time through data flow control using Node-RED. For example, if a parent requests that a specific app be locked after 9 PM, the server and device will work together to comply with that instruction.

[0318] Examples of prompt messages include the following:

[0319] "Voice input: Set it so that I can't play games after 9 PM."

[0320] "Natural language processing output: Set a policy to lock game apps at 9 PM."

[0321] "Example alert: Your child is engrossed in a game, and it's past 9 PM."

[0322] "Recommendation: Show a list of learning apps for children?"

[0323] Thus, the system of the present invention helps parents intuitively manage the use of digital devices and provides a means for creating a safe and healthy digital environment.

[0324] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0325] Step 1:

[0326] The user inputs a request in natural language via a microphone. This audio data is received by the server. The server converts this audio input into text data using a service such as Google Speech-to-Text.

[0327] Step 2:

[0328] The server inputs text data into a natural language processing tool such as TensorFlow to analyze the intended usage restrictions. This analysis process converts the parent request into clear control instructions. For example, it might generate an instruction such as "Disable games after 9 PM."

[0329] Step 3:

[0330] Based on the analysis results, the server utilizes management tools to generate specific control instructions for the terminal. These control instructions are sent to the terminal as a policy to be applied directly to the device. At this time, the terminal updates the usage settings of the information processing device and applies the specified restrictions.

[0331] Step 4:

[0332] The device uses OpenCV to monitor camera input and perform motion analysis. This data is used to recognize the child's activity patterns, and if inappropriate behavior is detected, it is saved as a record of that behavior.

[0333] Step 5:

[0334] When the device detects inappropriate activity or exceeds usage time limits, it notifies the server of an alert. Based on the generated data, this alert is sent to the user (parent) via email or app notification.

[0335] Step 6:

[0336] When a user requests to check the current settings of their device, the server generates the latest settings information in natural language and notifies the parent. This allows the parent to easily understand the current settings.

[0337] Step 7:

[0338] Using a recommendation system, information resources are analyzed based on the user's interests and usage patterns. The server organizes this information and generates a list of recommended educational apps and entertainment content for parents, as in this application example. This recommendation information is converted into a format preferred by the parents and communicated to them.

[0339] 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.

[0340] This invention's system, in addition to providing parents with a means to manage their children's use of digital devices in natural language, incorporates an emotion engine that recognizes user emotions, enabling more personalized management and content delivery.

[0341] In this system, the user (parent) first issues a request in natural language regarding restrictions on the use of digital devices, which is then received and analyzed by the server. The analyzed request is then applied to the device as a restriction on its use.

[0342] Furthermore, the device is equipped with an emotion engine that analyzes the user's, or child's, emotions. For example, if a child feels stressed while using the device, that emotional information is sent to the server. Based on this emotional information, the server dynamically adjusts the digital device usage restriction settings and notifies the parent.

[0343] If the emotion engine detects that a child is showing interest in a particular situation, such as while using a learning application, the server can decide to extend the usage time. Furthermore, based on emotional information, the server selects and recommends appropriate content to the device. This results in a digital experience that is more engaging for children and optimized for learning and entertainment.

[0344] Users can receive real-time notifications of these setting changes and reports on their child's emotional state. They can also query the server in natural language about current device settings and recommended content, and the server will provide responses accordingly.

[0345] In this way, we provide a system that goes beyond conventional parental controls, enabling management and content delivery tailored to individual emotions.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] The user enters and submits a request to the system in natural language regarding restrictions on the use of digital devices.

[0349] Step 2:

[0350] The server receives natural language requests sent by users, analyzes the requests using natural language processing techniques, and converts them into specific operation instructions.

[0351] Step 3:

[0352] The server generates and determines which digital device usage restriction policies to apply based on the analyzed requests.

[0353] Step 4:

[0354] The server sends the generated usage restriction policy to the terminal of the specified digital device.

[0355] Step 5:

[0356] The device applies the received usage restriction policy to its device settings and begins to implement specific controls. For example, it might enable a setting to limit the amount of time the device can be used.

[0357] Step 6:

[0358] The device's emotion engine recognizes the emotional state of the child user in real time. This analysis uses data such as facial expressions and voice tone.

[0359] Step 7:

[0360] The server receives user emotion information sent from the emotion engine and dynamically adjusts device usage restrictions accordingly. For example, it might change settings to temporarily allow access to specific content to reduce stress.

[0361] Step 8:

[0362] The server uses emotional information to recommend the most suitable content to the user and displays it on the device.

[0363] Step 9:

[0364] The server notifies the user of changes in settings and information about the child's emotional state. This allows parents to always know what their child is doing and manage their child with peace of mind.

[0365] Step 10:

[0366] When a user queries the server in natural language about the device's current settings or sentiment analysis results, the server immediately provides a response and explains the situation.

[0367] This series of processes enables flexible and appropriate management of digital devices in response to the user's emotions.

[0368] (Example 2)

[0369] 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".

[0370] In the modern use of information processing devices, there is a lack of means for parents to properly manage their children's device use. In particular, there is a need for systems that not only limit usage time but also dynamically adjust settings based on the child's emotional state and provide appropriate content. The challenge is to create such systems that enrich and safer children's digital experiences and provide an environment where parents can manage their children's devices with peace of mind.

[0371] 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.

[0372] In this invention, the server includes communication means for receiving requests from parents in natural language, means for analyzing the requests using natural language processing technology and generating usage restriction settings for the information processing device, and means for analyzing the user's emotional state using an emotion analysis engine. This enables parents to flexibly and individually manage their child's use of digital devices based on their emotional state.

[0373] A "parent" is someone who manages their child's use of digital devices and sets appropriate restrictions and content.

[0374] "Natural language" refers to the language that parents use on a daily basis to intuitively communicate instructions and restrictions regarding digital devices.

[0375] "Communication methods" refer to the technical means used to send requests from a parent to a server, and involve exchanging information via the internet or wireless communication.

[0376] "Natural language processing means" refers to technology for analyzing received natural language requests and converting them into specific usage restriction settings.

[0377] "Information processing equipment" is a general term for digital devices used by children, and includes smartphones, tablets, and personal computers.

[0378] "Control means" refers to means for applying the generated usage restriction settings to the information processing device and controlling the operation of the device.

[0379] An "emotion analysis engine" is a technology that analyzes a user's emotions from their facial expressions and voice, and optimizes device settings based on that analysis.

[0380] "Adjustment means" refers to technical means that dynamically change settings based on information from the emotion analysis engine, enabling device management tailored to the child's situation.

[0381] "Recommendation methods" are features that select and provide users with appropriate content and information based on emotional information.

[0382] A "notification method" is a way for a server to send setting changes and emotional information to the parent in real time, thereby communicating necessary information.

[0383] This invention is implemented as a system for parents to flexibly manage their children's use of information processing devices. This system has the function of receiving and analyzing instructions from parents in natural language and setting restrictions on the use of the information processing device based on the analysis results.

[0384] First, the user (parent) accesses the system via a smartphone or computer and enters requests regarding restrictions on the use of digital devices in natural language. For example, they can send a request such as, "Please restrict games after 9 PM every day." This request is sent to the server via communication means.

[0385] The server uses natural language processing techniques to parse this request, leveraging technologies such as "spaCy" and "Google Cloud Natural Language API." This interprets the request as data, generating specific usage restriction settings. These generated settings are then sent to the appropriate information processing device via a control mechanism and applied to the terminal.

[0386] Furthermore, the device is equipped with an emotion analysis engine that analyzes the child's emotions in real time while they are using it. For example, it can determine whether the child is feeling stressed based on their facial expressions and tone of voice. This analysis result is sent to a server, which allows the server to dynamically adjust the device usage restrictions.

[0387] The server can select appropriate content based on the child's emotional state and recommend learning materials or relaxing music that might interest them to their device. This makes the child's digital experience more personalized and enhances its educational and entertainment value.

[0388] Parents, as users, can receive real-time reports on device usage settings and their child's emotional state. This allows for intuitive management of the information device at any time. For example, by inputting a prompt such as, "I want my child to listen to relaxing music to refresh themselves more often, how can I change the device settings?" into the generative AI model, they can receive advice on appropriate restriction setting changes.

[0389] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0390] Step 1:

[0391] Parents, acting as users, enter requests regarding restrictions on digital device use via smartphones or computers using natural language. These requests might include phrases like, "I want to restrict gaming after 9 PM every day." The input data is in text format and is sent to the system.

[0392] Step 2:

[0393] The server receives natural language requests from its parent via a communication method. Natural language processing techniques are used to parse the received text-based requests. This analysis utilizes tools such as "spaCy" and "Google Cloud Natural Language API" to extract the purpose and conditions of the request and generate usage restriction settings. The output is a specific usage restriction policy.

[0394] Step 3:

[0395] The server uses control mechanisms to send the generated usage restriction policy to the appropriate terminal. The information sent includes instructions such as the time limit and the applications to be restricted. The terminal receives the policy and applies it to its device settings. This causes the terminal to automatically restrict applications during the specified time.

[0396] Step 4:

[0397] The device's built-in emotion analysis engine analyzes the user's emotional state in real time while the device is in use. Input data includes camera images and audio data, which are used to determine the user's emotions from their facial expressions and tone of voice. The analysis results are output as emotional information, such as whether the user is interested or stressed.

[0398] Step 5:

[0399] The server receives emotional information sent from the device. Based on this emotional information, the server uses an AI algorithm to dynamically adjust device usage restrictions. For example, if the server determines that a child is showing interest in learning, it decides to extend the usage time and notifies the parent. The notification is sent in real time to the parent's device.

[0400] Step 6:

[0401] The server selects appropriate content based on emotional information. Specifically, it chooses learning and entertainment content that is suitable for the user's interests and relaxation needs. The selected content information is sent to the device and recommended to the user. This ensures that content that is likely to interest the child is displayed on the device.

[0402] (Application Example 2)

[0403] 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."

[0404] In modern society, autonomous vehicles are expanding as a means of transportation, but they face the challenge of not being able to dynamically adjust the in-vehicle environment in response to passengers' emotions and psychological states. Currently, the in-vehicle environment settings are uniform, making it impossible to provide an optimal ride experience for individual passengers. This, in turn, hinders passenger comfort and satisfaction.

[0405] 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.

[0406] In this invention, the server includes a system interface means for receiving natural language requests from a parent; a natural language analysis means for analyzing the requests and generating usage restriction settings for the information processing device; a monitoring means for monitoring usage patterns of the information processing device and detecting inappropriate use; and a control means for performing control on the environment control device based on the user's emotional state. This makes it possible to individually optimize the in-vehicle environment based on the emotions of passengers and improve their comfort.

[0407] "System interface means" refers to means that provide input devices and communication protocols for receiving requests from parents in natural language.

[0408] "Natural language analysis means" refers to means that use language analysis techniques to analyze received requests and generate usage restriction settings for information processing devices.

[0409] "Control means" refers to means for actually applying the generated usage restriction settings of the information processing device to the device and controlling its operation according to the settings.

[0410] "Monitoring means" refers to means for monitoring the usage status of information processing equipment and detecting inappropriate use.

[0411] A "notification means" is a means of notifying the parent of an alarm generated based on the monitoring results.

[0412] An "environmental control device" is a device that adjusts the physical environment inside a vehicle based on the user's emotional state.

[0413] The system for realizing this invention has the function of dynamically adjusting the in-vehicle environment based on passengers' emotions. The server utilizes an emotion engine and uses software such as OpenCV and Google Cloud Speech-to-Text to analyze the emotional state from passengers' voices and facial expressions.

[0414] The server analyzes passengers' emotions in real time and issues instructions to the vehicle's environmental control system based on the results. This automatically adjusts the in-car environment, including lighting, temperature, and music, according to the passengers' psychological state. Specifically, if the emotion engine detects that a passenger wants to relax, the lighting can be changed to a warmer color and relaxing music can be played.

[0415] The device acquires data through the in-car camera and microphone and sends it to a server. The server uses this data to perform emotion recognition and implements environmental control based on the results. Users do not need to do anything in particular and can enjoy a natural riding experience.

[0416] A concrete example would be a prompt message such as, "If the system detects that the passenger is tired, change the car's lighting to a warm color and play relaxing music." Based on this prompt message, the system can provide an optimized environment based on the passenger's emotions.

[0417] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0418] Step 1:

[0419] The terminal uses cameras and microphones installed inside the vehicle to acquire video and audio data of passengers in real time. The input is data from the cameras and microphones, and the output is data transmission to the server. After acquiring the data, the terminal sends it to the server.

[0420] Step 2:

[0421] The server analyzes the received video data using OpenCV and converts the audio data to text using Google Cloud Speech-to-Text. The input for this step is the video and audio data sent from the terminal, and the output is the analyzed emotional state. The emotion engine identifies the user's emotions based on this data.

[0422] Step 3:

[0423] The server generates instructions for the in-car environmental control system based on the analyzed emotional state. The input in this case is the emotional state output by the emotion engine, and the output is the environmental control instruction. For example, the server might generate an instruction such as "Play relaxing music and change the lighting to a warm color."

[0424] Step 4:

[0425] The environmental control system receives instructions from the server and adjusts the in-vehicle environment. The input for this step is the control instructions from the server, and the output is the adjusted in-vehicle environment. Specifically, this might involve playing music or changing the lighting.

[0426] Step 5:

[0427] The user experiences a tuned in-car environment. There is no explicit input in this step; the output is the comfortable ride the user experiences. The user enjoys an environment optimized by the system.

[0428] 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.

[0429] 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.

[0430] 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.

[0431] [Third Embodiment]

[0432] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0433] 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.

[0434] 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).

[0435] 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.

[0436] 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.

[0437] 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).

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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.

[0442] 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.

[0443] 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".

[0444] This invention provides an AI-powered parental control system that allows parents to easily and flexibly manage their children's use of digital devices.

[0445] Specifically, parents can make requests in natural language, supporting intuitive instructions such as "disable internet access after 8 PM" or "allow a specific app to be used for a limited time." These requests are sent to a server, where a natural language processing module parses them and converts them into specific operational instructions.

[0446] Based on the analyzed requests, the server generates digital device usage restrictions and sets the associated policies. This allows for control over the time periods and application access for digital devices.

[0447] Furthermore, the device monitors usage patterns and reports to the server if it detects inappropriate use or similar behavior. This automatically sends an alert to the parent user when abnormal activity is detected.

[0448] In addition, if parents want to know the current settings, they can ask questions using natural language. In response to inquiries such as "Please tell me what the current settings are," the server proactively reports the settings, providing reassurance.

[0449] Furthermore, it includes a feature that recommends content tailored to children's interests, such as recommending educational apps and appropriate entertainment content to the device, thereby promoting healthy device use.

[0450] In this way, by making full use of AI agents, we are providing a model that allows parents to more optimally manage their children's digital use.

[0451] The following describes the processing flow.

[0452] Step 1:

[0453] The user enters and submits a request regarding parental control settings in natural language.

[0454] Step 2:

[0455] The server analyzes the natural language request received from the user. Natural language processing technology is used for the analysis, converting the request content into specific function configuration instructions.

[0456] Step 3:

[0457] The server generates a digital device usage restriction policy based on the analysis results. This policy includes settings for usage time and access restrictions.

[0458] Step 4:

[0459] The server sends the generated usage restriction policy to the terminal.

[0460] Step 5:

[0461] The device applies the received policy settings to the device's management system and activates the specified restrictions. These include time limits and application controls.

[0462] Step 6:

[0463] The device monitors device usage in real time. If inappropriate use or abnormal access is detected, it records it and reports it to the server.

[0464] Step 7:

[0465] The server generates an alert based on the detected anomaly and notifies the user. The notification is sent via methods such as email or push notification.

[0466] Step 8:

[0467] Users can inquire about their current settings and device usage in natural language.

[0468] Step 9:

[0469] The server analyzes the current configuration and reports it to the user in an easy-to-understand format.

[0470] Step 10:

[0471] The server recommends appropriate content to the device based on interest analysis. This allows users to select content based on their interests.

[0472] (Example 1)

[0473] 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."

[0474] In modern times, the inappropriate use of digital information processing devices by children is a problem, and parents are required to effectively manage their children's use and provide them with appropriate content. However, conventional parental control systems are often cumbersome and not intuitive for parents, so there is a need for simpler and more flexible management methods.

[0475] 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.

[0476] In this invention, the server includes an interface means for receiving natural language requests from a parent, a natural language processing means for analyzing the request and generating usage restriction settings for the digital information processing device, and a control means for applying the generated settings to the digital information processing device. This allows parents to intuitively manage their child's use of the digital information processing device and flexibly set usage restriction policies.

[0477] An "interface means" is a means of receiving requests from a parent using natural language, and provides a point of contact for the user to interact with the system.

[0478] A "natural language processing means" is a means for analyzing a received natural language request and converting it into specific instructions, such as setting usage restrictions for a digital information processing device.

[0479] "Control means" refers to means for applying the generated usage restriction settings to a digital information processing device and managing the use of the device.

[0480] "Observation means" refers to means for monitoring the usage of digital information processing equipment, detecting inappropriate use, and recording the results.

[0481] A "notification method" is a means of generating a warning and notifying parents when inappropriate use is detected.

[0482] A "response mechanism" is a means of reporting the current settings of a digital information processing device in response to a parent's natural language question.

[0483] "Recommendation means" refers to a means of recommending information based on the interests of users of digital information processing devices, and promotes appropriate content use.

[0484] This invention relates to a system for parents to manage their children's use of digital information processing devices. The system is configured as follows:

[0485] First, the user (the parent) can input requests in natural language through the digital information processing device. For example, the parent can use a smartphone app to make a request through the interface such as, "Please disable internet access after 8 PM." This request is then sent to the server.

[0486] The server analyzes received requests using a generative AI model, a natural language processing tool. The generative AI model converts the requests into specific operation instructions and generates usage restriction settings. This analysis process utilizes natural language processing technology, enabling efficient interpretation of requests.

[0487] Next, the server applies the generated usage restriction settings to the digital information processing device as a control mechanism. This sets the time periods and access controls for the child's device. For example, it is possible to set it to "allow specific apps only between 9 AM and 5 PM every weekend."

[0488] Furthermore, the terminal is equipped with monitoring mechanisms to track usage, and if inappropriate use is detected, it reports the results to the server. For example, if there is an attempt to access the internet outside of the specified time, the server will be notified of the situation.

[0489] Based on its observations, the server sends alerts to parents as a means of notification. For example, it might send a notification to the parent's device stating, "Your child attempted to access the internet after 8 PM."

[0490] Furthermore, if the parent asks a question in natural language such as "What are the current settings?", the server will use a response mechanism to provide information about the current device settings. This allows the parent to always know the status of the device's settings.

[0491] Furthermore, the proposed means includes a function to recommend information based on the user's interests. For example, it can suggest educational apps or appropriate entertainment content to the device, promoting healthy device use by children.

[0492] As an example of a prompt, a parent might input a question into the system such as, "How do I set it so my child can only play games between 6 PM and 8 PM on weekdays?", and the generating AI model would then suggest a method for doing so. In this way, the present invention is configured to allow parents to implement intuitive and flexible parental controls.

[0493] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0494] Step 1:

[0495] Users input natural language requests through a smartphone app. These requests include instructions regarding restrictions on children's use of digital information processing devices. For example, they might input a sentence like, "Please disable internet access after 8 PM," which becomes the input data. The submitted request is then sent to the server.

[0496] Step 2:

[0497] The server analyzes the received natural language request using natural language processing tools. Specifically, a generative AI model analyzes the request content and converts it into instructions for usage restriction policies. The output of this process is, for example, a specific policy setting such as "Restrict internet access after 8 PM."

[0498] Step 3:

[0499] The server sends a usage restriction policy, generated based on the analysis results, to the terminal via a control mechanism. Here, control data is created and sent to the terminal as output. Specifically, the policy is applied to the terminal's configuration module, and the device's network functionality is restricted for the specified period.

[0500] Step 4:

[0501] The terminal uses monitoring devices to observe their usage. It takes current user behavior data as input and performs calculations to determine if there is inappropriate use. If inappropriate use is detected, it creates an event log and reports it to the server. For example, if an attempt is made to access the internet outside of a specified time, the date, time, and details of the attempt are recorded in the log.

[0502] Step 5:

[0503] The server receives reports from the device, generates an alert using a notification system based on the observation results, and notifies the parent. It receives event logs from the device as input and creates a notification message for the parent as output. Specifically, it sends a notification to the parent's smartphone stating, "Your child attempted to access the internet after 8 PM."

[0504] Step 6:

[0505] When a user inquires about the current device settings, the server provides that information using a response mechanism. It receives an inquiry from the parent as input and performs calculations to retrieve the current settings information from the database. The output is detailed information about the settings, specifically a response such as, "Currently, internet access is restricted from 8 PM to 7 AM the following morning."

[0506] (Application Example 1)

[0507] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0508] In modern households, it is crucial to properly manage and ensure the safe use of children's digital devices, but there is a lack of easy-to-use tools for parents to do so. Furthermore, there is a need for healthier device use through recommendations of appropriate content based on children's usage patterns. Additionally, features that monitor children's movements within the home in real time and issue safety-conscious warnings are also necessary.

[0509] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0510] In this invention, the server includes a communication medium for receiving natural language requests from parents, a natural language analysis means for analyzing the requests and generating usage restriction settings for the information processing device, and a recommendation means for presenting information resources based on the interests of the user of the information processing device. This makes it possible for parents to intuitively configure settings and promote healthy digital device use by their children.

[0511] A "communication medium" is an environment or interface for receiving natural language requests from a parent.

[0512] "Natural language processing means" refers to a function that analyzes natural language requests from the parent and generates usage restriction settings for the information processing device.

[0513] "Information processing device" refers to all digital devices, which are devices whose use is restricted or whose settings are applied based on instructions from parents.

[0514] A "management mechanism" is a control mechanism for applying the analyzed settings to an information processing device.

[0515] A "detection means" is a device that has the function of monitoring the usage trends of an information processing device and detecting inappropriate use.

[0516] "Notification means" refers to a function that generates a warning and communicates it to the parent when inappropriate use is detected.

[0517] "Motion analysis means" refers to technology for analyzing the surrounding environment and recognizing a child's activities.

[0518] A "recommended means" is a device that has the function of presenting information resources based on the interests of the user of the information processing device.

[0519] The system of this invention is designed to implement parental control utilizing AI technology. The server receives natural language requests from parents and plays a role in managing usage restrictions on the terminal, which is an information processing device.

[0520] The server functions as a local server using a Raspberry Pi and utilizes TensorFlow to perform natural language processing on received requests. The parsed instructions are then applied to the terminal by a management mechanism. Requests from the parent are input via voice through the microphone, and the server converts the voice to text for processing.

[0521] The device monitors the surrounding environment using image analysis technologies such as OpenCV and detects the child's movements. Based on this information, the server provides feedback to the parent via voice or text to notify them of appropriate alerts.

[0522] Furthermore, based on the usage patterns of the child user, appropriate content is provided through recommendation mechanisms. This information is communicated to parents in real time through data flow control using Node-RED. For example, if a parent requests that a specific app be locked after 9 PM, the server and device will work together to comply with that instruction.

[0523] Examples of prompt messages include the following:

[0524] "Voice input: Set it so that I can't play games after 9 PM."

[0525] "Natural language processing output: Set a policy to lock game apps at 9 PM."

[0526] "Example alert: Your child is engrossed in a game, and it's past 9 PM."

[0527] "Recommendation: Show a list of learning apps for children?"

[0528] Thus, the system of the present invention helps parents intuitively manage the use of digital devices and provides a means for creating a safe and healthy digital environment.

[0529] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0530] Step 1:

[0531] The user inputs a request in natural language via a microphone. This audio data is received by the server. The server converts this audio input into text data using a service such as Google Speech-to-Text.

[0532] Step 2:

[0533] The server inputs text data into a natural language processing tool such as TensorFlow to analyze the intended usage restrictions. This analysis process converts the parent request into clear control instructions. For example, it might generate an instruction such as "Disable games after 9 PM."

[0534] Step 3:

[0535] Based on the analysis results, the server utilizes management tools to generate specific control instructions for the terminal. These control instructions are sent to the terminal as a policy to be applied directly to the device. At this time, the terminal updates the usage settings of the information processing device and applies the specified restrictions.

[0536] Step 4:

[0537] The device uses OpenCV to monitor camera input and perform motion analysis. This data is used to recognize the child's activity patterns, and if inappropriate behavior is detected, it is saved as a record of that behavior.

[0538] Step 5:

[0539] When the device detects inappropriate activity or exceeds usage time limits, it notifies the server of an alert. Based on the generated data, this alert is sent to the user (parent) via email or app notification.

[0540] Step 6:

[0541] When a user requests to check the current settings of their device, the server generates the latest settings information in natural language and notifies the parent. This allows the parent to easily understand the current settings.

[0542] Step 7:

[0543] Using a recommendation system, information resources are analyzed based on the user's interests and usage patterns. The server organizes this information and generates a list of recommended educational apps and entertainment content for parents, as in this application example. This recommendation information is converted into a format preferred by the parents and communicated to them.

[0544] 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.

[0545] This invention's system, in addition to providing parents with a means to manage their children's use of digital devices in natural language, incorporates an emotion engine that recognizes user emotions, enabling more personalized management and content delivery.

[0546] In this system, the user (parent) first issues a request in natural language regarding restrictions on the use of digital devices, which is then received and analyzed by the server. The analyzed request is then applied to the device as a restriction on its use.

[0547] Furthermore, the device is equipped with an emotion engine that analyzes the user's, or child's, emotions. For example, if a child feels stressed while using the device, that emotional information is sent to the server. Based on this emotional information, the server dynamically adjusts the digital device usage restriction settings and notifies the parent.

[0548] If the emotion engine detects that a child is showing interest in a particular situation, such as while using a learning application, the server can decide to extend the usage time. Furthermore, based on emotional information, the server selects and recommends appropriate content to the device. This results in a digital experience that is more engaging for children and optimized for learning and entertainment.

[0549] Users can receive real-time notifications of these setting changes and reports on their child's emotional state. They can also query the server in natural language about current device settings and recommended content, and the server will provide responses accordingly.

[0550] In this way, we provide a system that goes beyond conventional parental controls, enabling management and content delivery tailored to individual emotions.

[0551] The following describes the processing flow.

[0552] Step 1:

[0553] The user enters and submits a request to the system in natural language regarding restrictions on the use of digital devices.

[0554] Step 2:

[0555] The server receives natural language requests sent by users, analyzes the requests using natural language processing techniques, and converts them into specific operation instructions.

[0556] Step 3:

[0557] The server generates and determines which digital device usage restriction policies to apply based on the analyzed requests.

[0558] Step 4:

[0559] The server sends the generated usage restriction policy to the terminal of the specified digital device.

[0560] Step 5:

[0561] The device applies the received usage restriction policy to its device settings and begins to implement specific controls. For example, it might enable a setting to limit the amount of time the device can be used.

[0562] Step 6:

[0563] The device's emotion engine recognizes the emotional state of the child user in real time. This analysis uses data such as facial expressions and voice tone.

[0564] Step 7:

[0565] The server receives user emotion information sent from the emotion engine and dynamically adjusts device usage restrictions accordingly. For example, it might change settings to temporarily allow access to specific content to reduce stress.

[0566] Step 8:

[0567] The server uses emotional information to recommend the most suitable content to the user and displays it on the device.

[0568] Step 9:

[0569] The server notifies the user of changes in settings and information about the child's emotional state. This allows parents to always know what their child is doing and manage their child with peace of mind.

[0570] Step 10:

[0571] When a user queries the server in natural language about the device's current settings or sentiment analysis results, the server immediately provides a response and explains the situation.

[0572] This series of processes enables flexible and appropriate management of digital devices in response to the user's emotions.

[0573] (Example 2)

[0574] 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."

[0575] In the modern use of information processing devices, there is a lack of means for parents to properly manage their children's device use. In particular, there is a need for systems that not only limit usage time but also dynamically adjust settings based on the child's emotional state and provide appropriate content. The challenge is to create such systems that enrich and safer children's digital experiences and provide an environment where parents can manage their children's devices with peace of mind.

[0576] 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.

[0577] In this invention, the server includes communication means for receiving requests from parents in natural language, means for analyzing the requests using natural language processing technology and generating usage restriction settings for the information processing device, and means for analyzing the user's emotional state using an emotion analysis engine. This enables parents to flexibly and individually manage their child's use of digital devices based on their emotional state.

[0578] A "parent" is someone who manages their child's use of digital devices and sets appropriate restrictions and content.

[0579] "Natural language" refers to the language that parents use on a daily basis to intuitively communicate instructions and restrictions regarding digital devices.

[0580] "Communication methods" refer to the technical means used to send requests from a parent to a server, and involve exchanging information via the internet or wireless communication.

[0581] "Natural language processing means" refers to technology for analyzing received natural language requests and converting them into specific usage restriction settings.

[0582] "Information processing equipment" is a general term for digital devices used by children, and includes smartphones, tablets, and personal computers.

[0583] "Control means" refers to means for applying the generated usage restriction settings to the information processing device and controlling the operation of the device.

[0584] An "emotion analysis engine" is a technology that analyzes a user's emotions from their facial expressions and voice, and optimizes device settings based on that analysis.

[0585] "Adjustment means" refers to technical means that dynamically change settings based on information from the emotion analysis engine, enabling device management tailored to the child's situation.

[0586] "Recommendation methods" are features that select and provide users with appropriate content and information based on emotional information.

[0587] A "notification method" is a way for a server to send setting changes and emotional information to the parent in real time, thereby communicating necessary information.

[0588] This invention is implemented as a system for parents to flexibly manage their children's use of information processing devices. This system has the function of receiving and analyzing instructions from parents in natural language and setting restrictions on the use of the information processing device based on the analysis results.

[0589] First, the user (parent) accesses the system via a smartphone or computer and enters requests regarding restrictions on the use of digital devices in natural language. For example, they can send a request such as, "Please restrict games after 9 PM every day." This request is sent to the server via communication means.

[0590] The server uses natural language processing techniques to parse this request, leveraging technologies such as "spaCy" and "Google Cloud Natural Language API." This interprets the request as data, generating specific usage restriction settings. These generated settings are then sent to the appropriate information processing device via a control mechanism and applied to the terminal.

[0591] Furthermore, the device is equipped with an emotion analysis engine that analyzes the child's emotions in real time while they are using it. For example, it can determine whether the child is feeling stressed based on their facial expressions and tone of voice. This analysis result is sent to a server, which allows the server to dynamically adjust the device usage restrictions.

[0592] The server can select appropriate content based on the child's emotional state and recommend learning materials or relaxing music that might interest them to their device. This makes the child's digital experience more personalized and enhances its educational and entertainment value.

[0593] Parents, as users, can receive real-time reports on device usage settings and their child's emotional state. This allows for intuitive management of the information device at any time. For example, by inputting a prompt such as, "I want my child to listen to relaxing music to refresh themselves more often, how can I change the device settings?" into the generative AI model, they can receive advice on appropriate restriction setting changes.

[0594] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0595] Step 1:

[0596] Parents, acting as users, enter requests regarding restrictions on digital device use via smartphones or computers using natural language. These requests might include phrases like, "I want to restrict gaming after 9 PM every day." The input data is in text format and is sent to the system.

[0597] Step 2:

[0598] The server receives natural language requests from its parent via a communication method. Natural language processing techniques are used to parse the received text-based requests. This analysis utilizes tools such as "spaCy" and "Google Cloud Natural Language API" to extract the purpose and conditions of the request and generate usage restriction settings. The output is a specific usage restriction policy.

[0599] Step 3:

[0600] The server uses control mechanisms to send the generated usage restriction policy to the appropriate terminal. The information sent includes instructions such as the time limit and the applications to be restricted. The terminal receives the policy and applies it to its device settings. This causes the terminal to automatically restrict applications during the specified time.

[0601] Step 4:

[0602] The device's built-in emotion analysis engine analyzes the user's emotional state in real time while the device is in use. Input data includes camera images and audio data, which are used to determine the user's emotions from their facial expressions and tone of voice. The analysis results are output as emotional information, such as whether the user is interested or stressed.

[0603] Step 5:

[0604] The server receives emotional information sent from the device. Based on this emotional information, the server uses an AI algorithm to dynamically adjust device usage restrictions. For example, if the server determines that a child is showing interest in learning, it decides to extend the usage time and notifies the parent. The notification is sent in real time to the parent's device.

[0605] Step 6:

[0606] The server selects appropriate content based on emotional information. Specifically, it chooses learning and entertainment content that is suitable for the user's interests and relaxation needs. The selected content information is sent to the device and recommended to the user. This ensures that content that is likely to interest the child is displayed on the device.

[0607] (Application Example 2)

[0608] 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."

[0609] In modern society, autonomous vehicles are expanding as a means of transportation, but they face the challenge of not being able to dynamically adjust the in-vehicle environment in response to passengers' emotions and psychological states. Currently, the in-vehicle environment settings are uniform, making it impossible to provide an optimal ride experience for individual passengers. This, in turn, hinders passenger comfort and satisfaction.

[0610] 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.

[0611] In this invention, the server includes a system interface means for receiving natural language requests from a parent; a natural language analysis means for analyzing the requests and generating usage restriction settings for the information processing device; a monitoring means for monitoring usage patterns of the information processing device and detecting inappropriate use; and a control means for performing control on the environment control device based on the user's emotional state. This makes it possible to individually optimize the in-vehicle environment based on the emotions of passengers and improve their comfort.

[0612] "System interface means" refers to means that provide input devices and communication protocols for receiving requests from parents in natural language.

[0613] "Natural language analysis means" refers to means that use language analysis techniques to analyze received requests and generate usage restriction settings for information processing devices.

[0614] "Control means" refers to means for actually applying the generated usage restriction settings of the information processing device to the device and controlling its operation according to the settings.

[0615] "Monitoring means" refers to means for monitoring the usage status of information processing equipment and detecting inappropriate use.

[0616] A "notification means" is a means of notifying the parent of an alarm generated based on the monitoring results.

[0617] An "environmental control device" is a device that adjusts the physical environment inside a vehicle based on the user's emotional state.

[0618] The system for realizing this invention has the function of dynamically adjusting the in-vehicle environment based on passengers' emotions. The server utilizes an emotion engine and uses software such as OpenCV and Google Cloud Speech-to-Text to analyze the emotional state from passengers' voices and facial expressions.

[0619] The server analyzes passengers' emotions in real time and issues instructions to the vehicle's environmental control system based on the results. This automatically adjusts the in-car environment, including lighting, temperature, and music, according to the passengers' psychological state. Specifically, if the emotion engine detects that a passenger wants to relax, the lighting can be changed to a warmer color and relaxing music can be played.

[0620] The device acquires data through the in-car camera and microphone and sends it to a server. The server uses this data to perform emotion recognition and implements environmental control based on the results. Users do not need to do anything in particular and can enjoy a natural riding experience.

[0621] A concrete example would be a prompt message such as, "If the system detects that the passenger is tired, change the car's lighting to a warm color and play relaxing music." Based on this prompt message, the system can provide an optimized environment based on the passenger's emotions.

[0622] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0623] Step 1:

[0624] The terminal uses cameras and microphones installed inside the vehicle to acquire video and audio data of passengers in real time. The input is data from the cameras and microphones, and the output is data transmission to the server. After acquiring the data, the terminal sends it to the server.

[0625] Step 2:

[0626] The server analyzes the received video data using OpenCV and converts the audio data to text using Google Cloud Speech-to-Text. The input for this step is the video and audio data sent from the terminal, and the output is the analyzed emotional state. The emotion engine identifies the user's emotions based on this data.

[0627] Step 3:

[0628] The server generates instructions for the in-car environmental control system based on the analyzed emotional state. The input in this case is the emotional state output by the emotion engine, and the output is the environmental control instruction. For example, the server might generate an instruction such as "Play relaxing music and change the lighting to a warm color."

[0629] Step 4:

[0630] The environmental control system receives instructions from the server and adjusts the in-vehicle environment. The input for this step is the control instructions from the server, and the output is the adjusted in-vehicle environment. Specifically, this might involve playing music or changing the lighting.

[0631] Step 5:

[0632] The user experiences a tuned in-car environment. There is no explicit input in this step; the output is the comfortable ride the user experiences. The user enjoys an environment optimized by the system.

[0633] 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.

[0634] 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.

[0635] 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.

[0636] [Fourth Embodiment]

[0637] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0638] 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.

[0639] 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).

[0640] 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.

[0641] 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.

[0642] 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).

[0643] 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.

[0644] 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.

[0645] 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.

[0646] 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.

[0647] 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.

[0648] 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.

[0649] 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".

[0650] This invention provides an AI-powered parental control system that allows parents to easily and flexibly manage their children's use of digital devices.

[0651] Specifically, parents can make requests in natural language, supporting intuitive instructions such as "disable internet access after 8 PM" or "allow a specific app to be used for a limited time." These requests are sent to a server, where a natural language processing module parses them and converts them into specific operational instructions.

[0652] Based on the analyzed requests, the server generates digital device usage restrictions and sets the associated policies. This allows for control over the time periods and application access for digital devices.

[0653] Furthermore, the device monitors usage patterns and reports to the server if it detects inappropriate use or similar behavior. This automatically sends an alert to the parent user when abnormal activity is detected.

[0654] In addition, if parents want to know the current settings, they can ask questions using natural language. In response to inquiries such as "Please tell me what the current settings are," the server proactively reports the settings, providing reassurance.

[0655] Furthermore, it includes a feature that recommends content tailored to children's interests, such as recommending educational apps and appropriate entertainment content to the device, thereby promoting healthy device use.

[0656] In this way, by making full use of AI agents, we are providing a model that allows parents to more optimally manage their children's digital use.

[0657] The following describes the processing flow.

[0658] Step 1:

[0659] The user enters and submits a request regarding parental control settings in natural language.

[0660] Step 2:

[0661] The server analyzes the natural language request received from the user. Natural language processing technology is used for the analysis, converting the request content into specific function configuration instructions.

[0662] Step 3:

[0663] The server generates a digital device usage restriction policy based on the analysis results. This policy includes settings for usage time and access restrictions.

[0664] Step 4:

[0665] The server sends the generated usage restriction policy to the terminal.

[0666] Step 5:

[0667] The device applies the received policy settings to the device's management system and activates the specified restrictions. These include time limits and application controls.

[0668] Step 6:

[0669] The device monitors device usage in real time. If inappropriate use or abnormal access is detected, it records it and reports it to the server.

[0670] Step 7:

[0671] The server generates an alert based on the detected anomaly and notifies the user. The notification is sent via methods such as email or push notification.

[0672] Step 8:

[0673] Users can inquire about their current settings and device usage in natural language.

[0674] Step 9:

[0675] The server analyzes the current configuration and reports it to the user in an easy-to-understand format.

[0676] Step 10:

[0677] The server recommends appropriate content to the device based on interest analysis. This allows users to select content based on their interests.

[0678] (Example 1)

[0679] 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".

[0680] In modern times, the inappropriate use of digital information processing devices by children is a problem, and parents are required to effectively manage their children's use and provide them with appropriate content. However, conventional parental control systems are often cumbersome and not intuitive for parents, so there is a need for simpler and more flexible management methods.

[0681] 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.

[0682] In this invention, the server includes an interface means for receiving natural language requests from a parent, a natural language processing means for analyzing the request and generating usage restriction settings for the digital information processing device, and a control means for applying the generated settings to the digital information processing device. This allows parents to intuitively manage their child's use of the digital information processing device and flexibly set usage restriction policies.

[0683] An "interface means" is a means of receiving requests from a parent using natural language, and provides a point of contact for the user to interact with the system.

[0684] A "natural language processing means" is a means for analyzing a received natural language request and converting it into specific instructions, such as setting usage restrictions for a digital information processing device.

[0685] "Control means" refers to means for applying the generated usage restriction settings to a digital information processing device and managing the use of the device.

[0686] "Observation means" refers to means for monitoring the usage of digital information processing equipment, detecting inappropriate use, and recording the results.

[0687] A "notification method" is a means of generating a warning and notifying parents when inappropriate use is detected.

[0688] A "response mechanism" is a means of reporting the current settings of a digital information processing device in response to a parent's natural language question.

[0689] "Recommendation means" refers to a means of recommending information based on the interests of users of digital information processing devices, and promotes appropriate content use.

[0690] This invention relates to a system for parents to manage their children's use of digital information processing devices. The system is configured as follows:

[0691] First, the user (the parent) can input requests in natural language through the digital information processing device. For example, the parent can use a smartphone app to make a request through the interface such as, "Please disable internet access after 8 PM." This request is then sent to the server.

[0692] The server analyzes received requests using a generative AI model, a natural language processing tool. The generative AI model converts the requests into specific operation instructions and generates usage restriction settings. This analysis process utilizes natural language processing technology, enabling efficient interpretation of requests.

[0693] Next, the server applies the generated usage restriction settings to the digital information processing device as a control mechanism. This sets the time periods and access controls for the child's device. For example, it is possible to set it to "allow specific apps only between 9 AM and 5 PM every weekend."

[0694] Furthermore, the terminal is equipped with monitoring mechanisms to track usage, and if inappropriate use is detected, it reports the results to the server. For example, if there is an attempt to access the internet outside of the specified time, the server will be notified of the situation.

[0695] Based on its observations, the server sends alerts to parents as a means of notification. For example, it might send a notification to the parent's device stating, "Your child attempted to access the internet after 8 PM."

[0696] Furthermore, if the parent asks a question in natural language such as "What are the current settings?", the server will use a response mechanism to provide information about the current device settings. This allows the parent to always know the status of the device's settings.

[0697] Furthermore, the proposed means includes a function to recommend information based on the user's interests. For example, it can suggest educational apps or appropriate entertainment content to the device, promoting healthy device use by children.

[0698] As an example of a prompt, a parent might input a question into the system such as, "How do I set it so my child can only play games between 6 PM and 8 PM on weekdays?", and the generating AI model would then suggest a method for doing so. In this way, the present invention is configured to allow parents to implement intuitive and flexible parental controls.

[0699] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0700] Step 1:

[0701] Users input natural language requests through a smartphone app. These requests include instructions regarding restrictions on children's use of digital information processing devices. For example, they might input a sentence like, "Please disable internet access after 8 PM," which becomes the input data. The submitted request is then sent to the server.

[0702] Step 2:

[0703] The server analyzes the received natural language request using natural language processing tools. Specifically, a generative AI model analyzes the request content and converts it into instructions for usage restriction policies. The output of this process is, for example, a specific policy setting such as "Restrict internet access after 8 PM."

[0704] Step 3:

[0705] The server sends a usage restriction policy, generated based on the analysis results, to the terminal via a control mechanism. Here, control data is created and sent to the terminal as output. Specifically, the policy is applied to the terminal's configuration module, and the device's network functionality is restricted for the specified period.

[0706] Step 4:

[0707] The terminal uses monitoring devices to observe their usage. It takes current user behavior data as input and performs calculations to determine if there is inappropriate use. If inappropriate use is detected, it creates an event log and reports it to the server. For example, if an attempt is made to access the internet outside of a specified time, the date, time, and details of the attempt are recorded in the log.

[0708] Step 5:

[0709] The server receives reports from the device, generates an alert using a notification system based on the observation results, and notifies the parent. It receives event logs from the device as input and creates a notification message for the parent as output. Specifically, it sends a notification to the parent's smartphone stating, "Your child attempted to access the internet after 8 PM."

[0710] Step 6:

[0711] When a user inquires about the current device settings, the server provides that information using a response mechanism. It receives an inquiry from the parent as input and performs calculations to retrieve the current settings information from the database. The output is detailed information about the settings, specifically a response such as, "Currently, internet access is restricted from 8 PM to 7 AM the following morning."

[0712] (Application Example 1)

[0713] 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".

[0714] In modern households, it is crucial to properly manage and ensure the safe use of children's digital devices, but there is a lack of easy-to-use tools for parents to do so. Furthermore, there is a need for healthier device use through recommendations of appropriate content based on children's usage patterns. Additionally, features that monitor children's movements within the home in real time and issue safety-conscious warnings are also necessary.

[0715] 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.

[0716] In this invention, the server includes a communication medium for receiving natural language requests from parents, a natural language analysis means for analyzing the requests and generating usage restriction settings for the information processing device, and a recommendation means for presenting information resources based on the interests of the user of the information processing device. This makes it possible for parents to intuitively configure settings and promote healthy digital device use by their children.

[0717] A "communication medium" is an environment or interface for receiving natural language requests from a parent.

[0718] "Natural language processing means" refers to a function that analyzes natural language requests from the parent and generates usage restriction settings for the information processing device.

[0719] "Information processing device" refers to all digital devices, which are devices whose use is restricted or whose settings are applied based on instructions from parents.

[0720] A "management mechanism" is a control mechanism for applying the analyzed settings to an information processing device.

[0721] A "detection means" is a device that has the function of monitoring the usage trends of an information processing device and detecting inappropriate use.

[0722] "Notification means" refers to a function that generates a warning and communicates it to the parent when inappropriate use is detected.

[0723] "Motion analysis means" refers to technology for analyzing the surrounding environment and recognizing a child's activities.

[0724] A "recommended means" is a device that has the function of presenting information resources based on the interests of the user of the information processing device.

[0725] The system of this invention is designed to implement parental control utilizing AI technology. The server receives natural language requests from parents and plays a role in managing usage restrictions on the terminal, which is an information processing device.

[0726] The server functions as a local server using a Raspberry Pi and utilizes TensorFlow to perform natural language processing on received requests. The parsed instructions are then applied to the terminal by a management mechanism. Requests from the parent are input via voice through the microphone, and the server converts the voice to text for processing.

[0727] The device monitors the surrounding environment using image analysis technologies such as OpenCV and detects the child's movements. Based on this information, the server provides feedback to the parent via voice or text to notify them of appropriate alerts.

[0728] Furthermore, based on the usage patterns of the child user, appropriate content is provided through recommendation mechanisms. This information is communicated to parents in real time through data flow control using Node-RED. For example, if a parent requests that a specific app be locked after 9 PM, the server and device will work together to comply with that instruction.

[0729] Examples of prompt messages include the following:

[0730] "Voice input: Set it so that I can't play games after 9 PM."

[0731] "Natural language processing output: Set a policy to lock game apps at 9 PM."

[0732] "Example alert: Your child is engrossed in a game, and it's past 9 PM."

[0733] "Recommendation: Show a list of learning apps for children?"

[0734] Thus, the system of the present invention helps parents intuitively manage the use of digital devices and provides a means for creating a safe and healthy digital environment.

[0735] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0736] Step 1:

[0737] The user inputs a request in natural language via a microphone. This audio data is received by the server. The server converts this audio input into text data using a service such as Google Speech-to-Text.

[0738] Step 2:

[0739] The server inputs text data into a natural language processing tool such as TensorFlow to analyze the intended usage restrictions. This analysis process converts the parent request into clear control instructions. For example, it might generate an instruction such as "Disable games after 9 PM."

[0740] Step 3:

[0741] Based on the analysis results, the server utilizes management tools to generate specific control instructions for the terminal. These control instructions are sent to the terminal as a policy to be applied directly to the device. At this time, the terminal updates the usage settings of the information processing device and applies the specified restrictions.

[0742] Step 4:

[0743] The device uses OpenCV to monitor camera input and perform motion analysis. This data is used to recognize the child's activity patterns, and if inappropriate behavior is detected, it is saved as a record of that behavior.

[0744] Step 5:

[0745] When the device detects inappropriate activity or exceeds usage time limits, it notifies the server of an alert. Based on the generated data, this alert is sent to the user (parent) via email or app notification.

[0746] Step 6:

[0747] When a user requests to check the current settings of their device, the server generates the latest settings information in natural language and notifies the parent. This allows the parent to easily understand the current settings.

[0748] Step 7:

[0749] Using a recommendation system, information resources are analyzed based on the user's interests and usage patterns. The server organizes this information and generates a list of recommended educational apps and entertainment content for parents, as in this application example. This recommendation information is converted into a format preferred by the parents and communicated to them.

[0750] 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.

[0751] This invention's system, in addition to providing parents with a means to manage their children's use of digital devices in natural language, incorporates an emotion engine that recognizes user emotions, enabling more personalized management and content delivery.

[0752] In this system, the user (parent) first issues a request in natural language regarding restrictions on the use of digital devices, which is then received and analyzed by the server. The analyzed request is then applied to the device as a restriction on its use.

[0753] Furthermore, the device is equipped with an emotion engine that analyzes the user's, or child's, emotions. For example, if a child feels stressed while using the device, that emotional information is sent to the server. Based on this emotional information, the server dynamically adjusts the digital device usage restriction settings and notifies the parent.

[0754] If the emotion engine detects that a child is showing interest in a particular situation, such as while using a learning application, the server can decide to extend the usage time. Furthermore, based on emotional information, the server selects and recommends appropriate content to the device. This results in a digital experience that is more engaging for children and optimized for learning and entertainment.

[0755] Users can receive real-time notifications of these setting changes and reports on their child's emotional state. They can also query the server in natural language about current device settings and recommended content, and the server will provide responses accordingly.

[0756] In this way, we provide a system that goes beyond conventional parental controls, enabling management and content delivery tailored to individual emotions.

[0757] The following describes the processing flow.

[0758] Step 1:

[0759] The user enters and submits a request to the system in natural language regarding restrictions on the use of digital devices.

[0760] Step 2:

[0761] The server receives natural language requests sent by users, analyzes the requests using natural language processing techniques, and converts them into specific operation instructions.

[0762] Step 3:

[0763] The server generates and determines which digital device usage restriction policies to apply based on the analyzed requests.

[0764] Step 4:

[0765] The server sends the generated usage restriction policy to the terminal of the specified digital device.

[0766] Step 5:

[0767] The device applies the received usage restriction policy to its device settings and begins to implement specific controls. For example, it might enable a setting to limit the amount of time the device can be used.

[0768] Step 6:

[0769] The device's emotion engine recognizes the emotional state of the child user in real time. This analysis uses data such as facial expressions and voice tone.

[0770] Step 7:

[0771] The server receives user emotion information sent from the emotion engine and dynamically adjusts device usage restrictions accordingly. For example, it might change settings to temporarily allow access to specific content to reduce stress.

[0772] Step 8:

[0773] The server uses emotional information to recommend the most suitable content to the user and displays it on the device.

[0774] Step 9:

[0775] The server notifies the user of changes in settings and information about the child's emotional state. This allows parents to always know what their child is doing and manage their child with peace of mind.

[0776] Step 10:

[0777] When a user queries the server in natural language about the device's current settings or sentiment analysis results, the server immediately provides a response and explains the situation.

[0778] This series of processes enables flexible and appropriate management of digital devices in response to the user's emotions.

[0779] (Example 2)

[0780] 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".

[0781] In the modern use of information processing devices, there is a lack of means for parents to properly manage their children's device use. In particular, there is a need for systems that not only limit usage time but also dynamically adjust settings based on the child's emotional state and provide appropriate content. The challenge is to create such systems that enrich and safer children's digital experiences and provide an environment where parents can manage their children's devices with peace of mind.

[0782] 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.

[0783] In this invention, the server includes communication means for receiving requests from parents in natural language, means for analyzing the requests using natural language processing technology and generating usage restriction settings for the information processing device, and means for analyzing the user's emotional state using an emotion analysis engine. This enables parents to flexibly and individually manage their child's use of digital devices based on their emotional state.

[0784] A "parent" is someone who manages their child's use of digital devices and sets appropriate restrictions and content.

[0785] "Natural language" refers to the language that parents use on a daily basis to intuitively communicate instructions and restrictions regarding digital devices.

[0786] "Communication methods" refer to the technical means used to send requests from a parent to a server, and involve exchanging information via the internet or wireless communication.

[0787] "Natural language processing means" refers to technology for analyzing received natural language requests and converting them into specific usage restriction settings.

[0788] "Information processing equipment" is a general term for digital devices used by children, and includes smartphones, tablets, and personal computers.

[0789] "Control means" refers to means for applying the generated usage restriction settings to the information processing device and controlling the operation of the device.

[0790] An "emotion analysis engine" is a technology that analyzes a user's emotions from their facial expressions and voice, and optimizes device settings based on that analysis.

[0791] "Adjustment means" refers to technical means that dynamically change settings based on information from the emotion analysis engine, enabling device management tailored to the child's situation.

[0792] "Recommendation methods" are features that select and provide users with appropriate content and information based on emotional information.

[0793] A "notification method" is a way for a server to send setting changes and emotional information to the parent in real time, thereby communicating necessary information.

[0794] This invention is implemented as a system for parents to flexibly manage their children's use of information processing devices. This system has the function of receiving and analyzing instructions from parents in natural language and setting restrictions on the use of the information processing device based on the analysis results.

[0795] First, the user (parent) accesses the system via a smartphone or computer and enters requests regarding restrictions on the use of digital devices in natural language. For example, they can send a request such as, "Please restrict games after 9 PM every day." This request is sent to the server via communication means.

[0796] The server uses natural language processing techniques to parse this request, leveraging technologies such as "spaCy" and "Google Cloud Natural Language API." This interprets the request as data, generating specific usage restriction settings. These generated settings are then sent to the appropriate information processing device via a control mechanism and applied to the terminal.

[0797] Furthermore, the device is equipped with an emotion analysis engine that analyzes the child's emotions in real time while they are using it. For example, it can determine whether the child is feeling stressed based on their facial expressions and tone of voice. This analysis result is sent to a server, which allows the server to dynamically adjust the device usage restrictions.

[0798] The server can select appropriate content based on the child's emotional state and recommend learning materials or relaxing music that might interest them to their device. This makes the child's digital experience more personalized and enhances its educational and entertainment value.

[0799] Parents, as users, can receive real-time reports on device usage settings and their child's emotional state. This allows for intuitive management of the information device at any time. For example, by inputting a prompt such as, "I want my child to listen to relaxing music to refresh themselves more often, how can I change the device settings?" into the generative AI model, they can receive advice on appropriate restriction setting changes.

[0800] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0801] Step 1:

[0802] Parents, acting as users, enter requests regarding restrictions on digital device use via smartphones or computers using natural language. These requests might include phrases like, "I want to restrict gaming after 9 PM every day." The input data is in text format and is sent to the system.

[0803] Step 2:

[0804] The server receives natural language requests from its parent via a communication method. Natural language processing techniques are used to parse the received text-based requests. This analysis utilizes tools such as "spaCy" and "Google Cloud Natural Language API" to extract the purpose and conditions of the request and generate usage restriction settings. The output is a specific usage restriction policy.

[0805] Step 3:

[0806] The server uses control mechanisms to send the generated usage restriction policy to the appropriate terminal. The information sent includes instructions such as the time limit and the applications to be restricted. The terminal receives the policy and applies it to its device settings. This causes the terminal to automatically restrict applications during the specified time.

[0807] Step 4:

[0808] The device's built-in emotion analysis engine analyzes the user's emotional state in real time while the device is in use. Input data includes camera images and audio data, which are used to determine the user's emotions from their facial expressions and tone of voice. The analysis results are output as emotional information, such as whether the user is interested or stressed.

[0809] Step 5:

[0810] The server receives emotional information sent from the device. Based on this emotional information, the server uses an AI algorithm to dynamically adjust device usage restrictions. For example, if the server determines that a child is showing interest in learning, it decides to extend the usage time and notifies the parent. The notification is sent in real time to the parent's device.

[0811] Step 6:

[0812] The server selects appropriate content based on emotional information. Specifically, it chooses learning and entertainment content that is suitable for the user's interests and relaxation needs. The selected content information is sent to the device and recommended to the user. This ensures that content that is likely to interest the child is displayed on the device.

[0813] (Application Example 2)

[0814] 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".

[0815] In modern society, autonomous vehicles are expanding as a means of transportation, but they face the challenge of not being able to dynamically adjust the in-vehicle environment in response to passengers' emotions and psychological states. Currently, the in-vehicle environment settings are uniform, making it impossible to provide an optimal ride experience for individual passengers. This, in turn, hinders passenger comfort and satisfaction.

[0816] 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.

[0817] In this invention, the server includes a system interface means for receiving natural language requests from a parent; a natural language analysis means for analyzing the requests and generating usage restriction settings for the information processing device; a monitoring means for monitoring usage patterns of the information processing device and detecting inappropriate use; and a control means for performing control on the environment control device based on the user's emotional state. This makes it possible to individually optimize the in-vehicle environment based on the emotions of passengers and improve their comfort.

[0818] "System interface means" refers to means that provide input devices and communication protocols for receiving requests from parents in natural language.

[0819] "Natural language analysis means" refers to means that use language analysis techniques to analyze received requests and generate usage restriction settings for information processing devices.

[0820] "Control means" refers to means for actually applying the generated usage restriction settings of the information processing device to the device and controlling its operation according to the settings.

[0821] "Monitoring means" refers to means for monitoring the usage status of information processing equipment and detecting inappropriate use.

[0822] A "notification means" is a means of notifying the parent of an alarm generated based on the monitoring results.

[0823] An "environmental control device" is a device that adjusts the physical environment inside a vehicle based on the user's emotional state.

[0824] The system for realizing this invention has the function of dynamically adjusting the in-vehicle environment based on passengers' emotions. The server utilizes an emotion engine and uses software such as OpenCV and Google Cloud Speech-to-Text to analyze the emotional state from passengers' voices and facial expressions.

[0825] The server analyzes passengers' emotions in real time and issues instructions to the vehicle's environmental control system based on the results. This automatically adjusts the in-car environment, including lighting, temperature, and music, according to the passengers' psychological state. Specifically, if the emotion engine detects that a passenger wants to relax, the lighting can be changed to a warmer color and relaxing music can be played.

[0826] The device acquires data through the in-car camera and microphone and sends it to a server. The server uses this data to perform emotion recognition and implements environmental control based on the results. Users do not need to do anything in particular and can enjoy a natural riding experience.

[0827] A concrete example would be a prompt message such as, "If the system detects that the passenger is tired, change the car's lighting to a warm color and play relaxing music." Based on this prompt message, the system can provide an optimized environment based on the passenger's emotions.

[0828] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0829] Step 1:

[0830] The terminal uses cameras and microphones installed inside the vehicle to acquire video and audio data of passengers in real time. The input is data from the cameras and microphones, and the output is data transmission to the server. After acquiring the data, the terminal sends it to the server.

[0831] Step 2:

[0832] The server analyzes the received video data using OpenCV and converts the audio data to text using Google Cloud Speech-to-Text. The input for this step is the video and audio data sent from the terminal, and the output is the analyzed emotional state. The emotion engine identifies the user's emotions based on this data.

[0833] Step 3:

[0834] The server generates instructions for the in-car environmental control system based on the analyzed emotional state. The input in this case is the emotional state output by the emotion engine, and the output is the environmental control instruction. For example, the server might generate an instruction such as "Play relaxing music and change the lighting to a warm color."

[0835] Step 4:

[0836] The environmental control system receives instructions from the server and adjusts the in-vehicle environment. The input for this step is the control instructions from the server, and the output is the adjusted in-vehicle environment. Specifically, this might involve playing music or changing the lighting.

[0837] Step 5:

[0838] The user experiences a tuned in-car environment. There is no explicit input in this step; the output is the comfortable ride the user experiences. The user enjoys an environment optimized by the system.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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."

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0860] The following is further disclosed regarding the embodiments described above.

[0861] (Claim 1)

[0862] An interface for receiving natural language requests from parents,

[0863] A natural language processing means that analyzes the aforementioned request and generates usage restriction settings for the digital device,

[0864] Control means for applying the generated settings to a digital device,

[0865] A monitoring means for monitoring the usage patterns of digital devices and detecting inappropriate use,

[0866] A notification means that generates an alert based on the aforementioned monitoring results and notifies the parent,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] The system according to claim 1, further comprising a means for confirming the current settings status to the parent in natural language.

[0870] (Claim 3)

[0871] The system according to claim 1, further comprising a recommendation means for recommending content based on the interests of users of a digital device.

[0872] "Example 1"

[0873] (Claim 1)

[0874] An interface for receiving natural language requests from parents,

[0875] A natural language processing means that analyzes the aforementioned request and generates usage restriction settings for the digital information processing device,

[0876] Control means for applying the generated settings to a digital information processing device,

[0877] An observation means for monitoring the usage status of a digital information processing device, detecting inappropriate use, and recording the results,

[0878] A notification means that generates a warning based on the aforementioned observation results and notifies the parent,

[0879] A response mechanism that reports the current device settings in response to a parent's natural language question,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, further comprising suggestion means for recommending information based on the interests of users of a digital information processing device.

[0883] (Claim 3)

[0884] The system according to claim 1, comprising means for automatically recording information regarding inappropriate device use and periodically providing such information to a parent.

[0885] "Application Example 1"

[0886] (Claim 1)

[0887] A communication medium that accepts requests from parents in natural language,

[0888] A natural language processing means that analyzes the aforementioned request and generates usage restriction settings for the information processing device,

[0889] A management means for applying the generated settings to the information processing device,

[0890] A detection means for monitoring the usage trends of an information processing device and detecting inappropriate use,

[0891] A notification means that generates a warning based on the detection result and communicates it to the parent,

[0892] A motion analysis means that analyzes the surrounding environment and recognizes the child's activities,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, further comprising a query means for reporting the current settings status to the parent in natural language.

[0896] (Claim 3)

[0897] The system according to claim 1, further comprising a recommendation means for presenting information resources based on the interests of the user of the information processing device.

[0898] "Example 2 of combining an emotion engine"

[0899] (Claim 1)

[0900] A means of communication that accepts requests from parents in natural language,

[0901] A natural language processing means that analyzes the aforementioned request and generates usage restriction settings for the information processing device,

[0902] Control means for applying the generated settings to the information processing device,

[0903] An analysis means that analyzes the user's emotional state using an emotion analysis engine installed in an information processing device,

[0904] An adjustment means that dynamically adjusts usage restrictions based on emotional information obtained by the analysis means,

[0905] A recommendation method that selects information appropriate to the user's emotions and provides it to an information processing device,

[0906] A notification method that notifies parents in real time of setting adjustment results and emotional information,

[0907] A system that includes this.

[0908] (Claim 2)

[0909] The system according to claim 1, further comprising a means for confirming the current settings status to the parent in natural language.

[0910] (Claim 3)

[0911] The system according to claim 1, further comprising a recommendation means for recommending information based on the interests of the user of the information processing device.

[0912] "Application example 2 when combining with an emotional engine"

[0913] (Claim 1)

[0914] A system interface means for receiving natural language requests from parents,

[0915] A natural language processing means that analyzes the aforementioned request and generates usage restriction settings for the information processing device,

[0916] Control means for applying the generated settings to the information processing device,

[0917] A monitoring means for monitoring the usage patterns of an information processing device and detecting inappropriate use,

[0918] A notification means that generates an alarm based on the aforementioned monitoring results and notifies the parent,

[0919] A control means that performs control on an environmental control device based on the user's emotional state,

[0920] A system that includes this.

[0921] (Claim 2)

[0922] The system according to claim 1, further comprising a means for confirming the current settings status to the parent in natural language.

[0923] (Claim 3)

[0924] The system according to claim 1, further comprising a recommendation means for recommending information based on the interests of users of the information processing device. [Explanation of symbols]

[0925] 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. An interface for receiving natural language requests from parents, A natural language processing means that analyzes the aforementioned request and generates usage restriction settings for the digital device, Control means for applying the generated settings to a digital device, A monitoring means for monitoring the usage patterns of digital devices and detecting inappropriate use, A notification means that generates an alert based on the aforementioned monitoring results and notifies the parent, A system that includes this.

2. The system according to claim 1, further comprising a means for confirming the current settings status to the parent in natural language.

3. The system according to claim 1, further comprising a recommendation means for recommending content based on the interests of users of a digital device.

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