WO2023106686A1

WO2023106686A1 - Method and device for managing use of electronic device

Info

Publication number: WO2023106686A1
Application number: PCT/KR2022/018378
Authority: WO
Inventors: 김영은; 이다영; 정순천; 조재홍; 차한나
Original assignee: 삼성전자 주식회사
Priority date: 2021-12-08
Filing date: 2022-11-21
Publication date: 2023-06-15

Abstract

A method for managing the use of an electronic device according to one embodiment of the present invention may comprise a step of acquiring information about a user of the electronic device and information about an administrator of the electronic device. The method for managing the use of an electronic device according to one embodiment of the present invention may comprise a step of acquiring management conditions for the electronic device, the management conditions being identified from an artificial intelligence model on the basis of the acquired information about the user and information about the administrator. The method for managing the use of an electronic device according to one embodiment of the present invention may comprise a step of controlling the electronic device on the basis of the acquired management criteria.

Description

Method and apparatus for managing use of electronic devices

When a separate administrator, not the user of the electronic device, manages the user's electronic device, the user and the management subject are distinguished and the user needs the administrator's supervision/control over the use of the electronic device. A representative example is a parental control system that manages a mobile phone.

A method for controlling the use of the electronic device by the manager of the electronic device may prevent a user from being exposed to inappropriate content or excessively using the electronic device.

If the setting authority for the user device is simply provided to the administrator, it may be difficult to effectively manage the user device because the administrator must directly check the usage history, make a judgment, control based on the judgment, and set a one-time control rule. .

If the manager of the electronic device has to directly control the electronic device every time, real-time monitoring and management may be difficult when the manager of the electronic device is not with the user of the electronic device. In addition, it is inconvenient for an administrator to check information on all functions and installed applications of an electronic device and directly set management conditions.

A method for managing use of an electronic device according to an embodiment of the present disclosure may include acquiring information about a user of the electronic device and information about a manager of the electronic device. A method for managing the use of an electronic device according to an embodiment of the present disclosure includes acquiring a management condition of an electronic device identified from an artificial intelligence model based on the obtained information about a user and information about a manager. can include A method for managing use of an electronic device according to an embodiment of the present disclosure may include controlling the electronic device based on the acquired management criterion.

An electronic device according to an embodiment of the present disclosure includes a communication unit; a storage unit for storing a program including at least one instruction; and at least one processor executing at least one instruction stored in the storage unit. At least one processor according to an embodiment of the present disclosure may obtain information about a user of the electronic device and information about a manager of the electronic device by executing at least one command. At least one processor according to an embodiment of the present disclosure may obtain a management condition of an electronic device obtained from an artificial intelligence model based on the obtained information about a user and information about a manager by executing at least one command. can At least one processor according to an embodiment of the present disclosure may control the electronic device based on the acquired management criterion by executing at least one command.

Meanwhile, according to one embodiment of the present disclosure, a computer-readable recording medium recording a program for executing the above-described method is provided.

1 illustrates a screen of an application through which an administrator manages a user's use of an electronic device, according to an embodiment of the present disclosure.

2 is a diagram illustrating an example of an electronic device management system according to an embodiment of the present disclosure.

3 illustrates a configuration diagram of an electronic device and a server for determining a management condition in an electronic device management system according to an embodiment of the present disclosure.

4 is a flowchart of a method for an electronic device to control a device according to an embodiment of the present disclosure.

5 is an operation flowchart of an electronic device and a server in an electronic device management system according to an embodiment of the present disclosure.

6 is an operation flowchart of a first electronic device, a second electronic device, and a server in an electronic device management system according to an embodiment of the present disclosure.

7 is a flowchart of a method for an electronic device to control a device according to an embodiment of the present disclosure.

8 is an electronic device use time recommendation model according to an embodiment of the present disclosure.

9 is a learning result of a use time recommendation model according to an embodiment of the present disclosure.

10 is a diagram for explaining a method of controlling an electronic device based on an electronic device use context according to an embodiment of the present disclosure.

11 is a diagram for explaining a harmful text monitoring model according to an embodiment of the present disclosure.

12 is a diagram for explaining a method of controlling an electronic device based on a distance between a user and an electronic device according to an embodiment of the present disclosure.

13 is a diagram for explaining a method of controlling an electronic device based on a user's posture for using an electronic device, according to an embodiment of the present disclosure.

14 is a diagram for explaining a developmental examination system according to an embodiment of the present disclosure.

15 illustrates a configuration diagram of an electronic device and a server in a developmental examination system according to an embodiment of the present disclosure.

16 illustrates a language development test model according to an embodiment of the present disclosure.

17 is a flowchart of a method of performing a development test by an electronic device according to an embodiment of the present disclosure.

18 is a diagram for explaining an operation of a method of performing a development test using an electronic device, according to an embodiment of the present disclosure.

19 illustrates a language development test result screen according to an embodiment of the present disclosure.

20 is a block diagram of an electronic device according to an embodiment of the present disclosure.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

In describing the embodiments, descriptions of technical contents that are well known in the technical field to which the present disclosure belongs and are not directly related to the present disclosure will be omitted. This is to more clearly convey the gist of the present disclosure without obscuring it by omitting unnecessary description.

For the same reason, in the accompanying drawings, some components are exaggerated, omitted, or schematically illustrated. Also, the size of each component does not entirely reflect the actual size. In each figure, the same reference number is assigned to the same or corresponding component.

Advantages and features of the present disclosure, and methods for achieving them, will become clear with reference to embodiments described below in detail in conjunction with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms, but only the present embodiments make the present disclosure complete, and those of ordinary skill in the art to which the present disclosure belongs It is provided to fully inform the scope of the present disclosure, which is only defined by the scope of the claims. Like reference numbers designate like elements throughout the specification.

At this time, it will be understood that each block of the process flow chart diagrams and combinations of the flow chart diagrams can be performed by computer program instructions. These computer program instructions may be embodied in a processor of a general purpose computer, special purpose computer, or other programmable data processing equipment, so that the instructions executed by the processor of the computer or other programmable data processing equipment are described in the flowchart block(s). It creates means to perform functions. These computer program instructions may also be stored in a computer usable or computer readable memory that can be directed to a computer or other programmable data processing equipment to implement functionality in a particular way, such that the computer usable or computer readable memory The instructions stored in are also capable of producing an article of manufacture containing instruction means that perform the functions described in the flowchart block(s). The computer program instructions can also be loaded on a computer or other programmable data processing equipment, so that a series of operational steps are performed on the computer or other programmable data processing equipment to create a computer-executed process to generate computer or other programmable data processing equipment. Instructions for performing processing equipment may also provide steps for performing the functions described in the flowchart block(s).

Additionally, each block may represent a module, segment, or portion of code that includes one or more executable instructions for executing specified logical function(s). It should also be noted that in some alternative implementations it is possible for the functions mentioned in the blocks to occur out of order. For example, two blocks shown in succession may in fact be executed substantially concurrently, or the blocks may sometimes be executed in reverse order depending on their function.

At this time, the term '~unit' used in this embodiment means software or a hardware component such as FPGA or ASIC, and '~unit' performs certain roles. However, '~ part' is not limited to software or hardware. '~bu' may be configured to be in an addressable storage medium and may be configured to reproduce one or more processors. Therefore, as an example, '~unit' refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, and procedures. , subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. Functions provided within components and '~units' may be combined into smaller numbers of components and '~units' or further separated into additional components and '~units'. In addition, components and '~units' may be implemented to play one or more CPUs in a device or a secure multimedia card. Also, in the embodiment, '~ unit' may include one or more processors.

When it is said that a certain part "includes" a certain component throughout the present disclosure, it means that it may further include other components, not excluding other components unless otherwise stated. In addition, terms such as “~unit” and “~module” described in this specification refer to a unit that processes at least one function or operation, which may be implemented as hardware or software or a combination of hardware and software. .

Throughout the specification, when a part is said to be “connected” to another part, this includes not only the case where it is “directly connected” but also the case where it is “electrically connected” with another element in between. . In addition, when a part "includes" a certain component, it means that it may further include other components, not excluding other components unless otherwise stated.

The expression “configured to (or configured to)” used in this specification means, depending on the situation, for example, “suitable for”, “having the capacity to” ”, “designed to”, “adapted to”, “made to”, or “capable of”. The term “configured (or set) to” may not necessarily mean only “specifically designed to” hardware. Instead, in some contexts, the expression "a system configured to" may mean that the system "is capable of" in conjunction with other devices or components. For example, the phrase "a processor configured (or configured) to perform A, B, and C" can be used by a dedicated processor (eg, embedded processor) to perform those operations, or by executing one or more software programs stored in memory; It may mean a general-purpose processor (eg, CPU or application processor) capable of performing corresponding operations.

Hereinafter, the present disclosure will be described in detail with reference to the accompanying drawings.

The administrator manages the user's electronic device when the user and management subject are distinguished and the user needs the manager's supervision/control over the use of the electronic device. control) system. The method for the administrator to manage the user's electronic device includes a method of installing and managing an application for managing the electronic device, a method of directly managing the electronic device at the system level of the OS, or a method of managing the electronic device through a browser. It may include, but is not limited to.

According to an embodiment, an electronic device may refer to a device used by a user. For example, an electronic device may mean a user equipment (UE), a remote terminal, a wireless terminal, or a user device. Electronic devices may include, but are not limited to, TVs, mobile phones, tablets, and laptop computers.

A user refers to a user of an electronic device. An administrator means a subject who monitors the use of a user's electronic device and, if necessary, manages and controls the use of the user's electronic device. Administrators typically include parents, but are not limited thereto, and include all subjects who can become guardians of electronic device users.

Referring to FIG. 1 , parents, as administrators, may manage their children's use of electronic devices.

According to an embodiment of the present disclosure, a parent may manage use of a child's electronic device by locking or unlocking the electronic device through a personal identification number (PIN) or an authentication method using biometric information. The biometric authentication method may include a user authentication method through fingerprint recognition, face recognition, or iris recognition.

According to an embodiment of the present disclosure, parents may manage whether applications are installed on their children's electronic devices, and manage whether each installed application is used. According to another embodiment, a parent may manage the use time of a child's electronic device or the use time of each application installed on the electronic device. Alternatively, parents can check and monitor their children's electronic device use history. For example, when a child installs or runs a restricted application or attempts access to a restricted website, the electronic device may provide a notification to the parent, and the parent who checks the notification can execute the application or visit the website. You can decide whether to allow access or not. Alternatively, the parent can identify the current location of the electronic device to check the current location of the child, or access real-time recording information of the place where the child is located (eg, a public institution or a child care facility such as a daycare center or kindergarten) to determine the location of the child. You can check the current status. In this case, authentication or registration may be required to access photographic information of the corresponding place. According to an embodiment of the present disclosure, parents may directly control their children's electronic devices to manage their children's use of electronic devices, or A separate electronic device may be used to manage a child's electronic device. When a parent manages a child's electronic device using a separate electronic device (manager device), the child's electronic device can be managed by installing an application for the administrator device on the administrator device and controlling the application installed on the user device. there is.

A method for controlling the use of the electronic device by the manager of the electronic device may prevent a user from being exposed to inappropriate content or excessively using the electronic device. However, if the setting authority for the user device is simply provided to the administrator, it is difficult to effectively manage the user device because the administrator must directly check the usage details, determine, control based on the judgment, and set one-time control rules. can

For example, when a user, a child, requests use of a restricted application while a parent manager is at work, the electronic device may transmit a message requesting permission to use the application to the parent's mobile phone. However, if the parent is busy with other important tasks, the message cannot be immediately viewed or the application cannot be set to be used immediately.

In addition, if the use of the electronic device is stopped unilaterally during use, the use of the application is stopped, or the provision of content is stopped, the user's desire to use the electronic device may rather be strengthened, and the negative user experience (Ux) for the parental management system , user experience) can be formed.

In addition, such a unilateral and fixed management method may rather weaken a user's ability to self-regulate using an electronic device. Self-regulation ability can be strengthened through constant practice and training, but if it is managed to be used according to the fixed conditions set by the manager, the opportunity for training is fundamentally blocked.

2 is a diagram illustrating an example of an electronic device management system according to an embodiment of the present disclosure. Referring to FIG. 2 , an electronic device management system according to an embodiment of the present disclosure may include a user device 1000, a manager device 2000, and an artificial intelligence (AI) model 3000 that determines electronic device management conditions. . In this case, the artificial intelligence model 3000 is an artificial intelligence training model, and may be a model for educating users 1500 of the electronic device 1000 on the use of the electronic device 1000.

As described above, if the manager 2500 has to directly control the user device 1000 every time, real-time monitoring and management may be difficult when the manager 2500 is not with the user 1500. According to an embodiment of the present disclosure, when the administrator 2500 manages and supervises the use of the electronic device 1000 by the user 1500, the artificial intelligence model 3000 analyzes, learns, and imitates under what conditions and in what way, the administrator 2500 The management conditions can be judged and set individually, and the burden of management, supervision, and control can be reduced.

In this way, if the management conditions are determined using the artificial intelligence model 3000, even if the manager 2500 is not with or paying attention to the user 1500, the artificial intelligence can supervise the user 1500's usage history and usage situation in real time, In other words, problems caused by inappropriate use can be prevented before they occur, or use can be intervened as soon as they occur.

In addition, when using the electronic device management system according to an embodiment of the present disclosure, the user 1500 can self-regulate the use of the electronic device rather than simply allowing the manager 2500 to limit the use of the electronic device and set authority. Pedagogical principles can be applied to improve In addition, instead of applying the same management principle to all users 1500, an artificial intelligence model 3000 can be created according to each user-manager combination, and the created artificial intelligence model 3000 can be advanced through learning. The artificial intelligence model 3000 performs initial settings based on user information such as the user's own temperament, disposition, behavior pattern, taste, and interest keywords, and administrator information such as the parenting environment, parenting values, and conflict mediation method, Afterwards, it can be learned based on usage history, end-of-use analysis, and user interaction analysis.

By determining the management conditions of the user device 1000 using the artificial intelligence model 3000, it is possible to educate the user how to use the electronic device 1000 based on pedagogical principles rather than simple device control, and to provide an intervention method for using the electronic device 1000. . Pedagogical principle is a general term for methodologies for educating 1500 users with inexperienced self-regulation skills on how to use the electronic device 1000 correctly and mediating the use of the electronic device 1000. Include all possible intervention methods.

The artificial intelligence model 3000 according to an embodiment of the present disclosure may obtain manager information and user information for determining management conditions of the electronic device 1000, and determine electronic device management conditions based on the obtained manager information and user information. .

According to an embodiment of the present disclosure, the manager 2500 inputs manager information and user information to a separate manager device 2000 instead of the electronic device 1000, and the artificial intelligence model 3000 obtains the manager information and user information from the manager device 2000. can

According to an embodiment of the present disclosure, when a plurality of managers exist, each of the plurality of managers may have management priority or have different control rights. According to an embodiment of the present disclosure, a manager may input user information into the electronic device 1000 and manager information into the manager device 2000 . In this case, the artificial intelligence model 3000 may acquire user information from the electronic device 1000 and manager information from the manager device 2000 .

According to an embodiment of the present disclosure, the manager device 2000 may be a wearable device worn on a user's body, such as a smart watch or augmented reality (AR) glasses. Alternatively, the manager device 2000 includes both a mobile device and a wearable device, and the mobile device monitors and controls the user device 1000 and transmits a monitoring result or control result to the wearable device, or monitors settings input by an administrator through the wearable device, or Operate to transmit control settings to the mobile device.

According to an embodiment of the present disclosure, the manager 2500 directly inputs manager information and user information to the electronic device 1000 without a separate manager device 2000, and the artificial intelligence model 3000 obtains the manager information and user information from the electronic device 1000. can When the artificial intelligence model 3000 obtains manager information and user information from the electronic device 1000, the manager device 2000 may be omitted from the device management system.

An electronic device management system according to an embodiment of the present disclosure analyzes whether a manager 2500 manages/supervises user 1500's use of an electronic device 1000 under what conditions and in what manner mediation is performed using an artificial intelligence model 3000. By learning and learning the management conditions determined by the manager, the burden of the manager directly determining and determining the management conditions or methods can be reduced.

An electronic device management system according to an embodiment of the present disclosure uses an artificial intelligence model 3000 to supervise a user's use of an electronic device in real time even when the administrator is in a different space from the user or cannot control it in real time, and misuse of the electronic device. You can prevent problems before they occur or intervene as soon as they occur.

The electronic device management system according to an embodiment of the present disclosure may improve a user's self-regulation ability by inducing use suspension, rather than coercive and unilateral use suspension, using the artificial intelligence model 3000. In order to induce a user to stop using the electronic device 1000, the electronic device management system according to an embodiment of the present disclosure provides a storytelling technique for a positive user experience (UX), a real-time remote interaction of an administrator (eg, In the process of inducing suspension of use, the user's usage time or usage conditions can be flexibly changed by negotiating with the user within the scope permitted by the administrator.

An electronic device management system according to an embodiment of the present disclosure may generate and train an artificial intelligence model 3000 based on each manager-user combination without applying the same condition to all users using the artificial intelligence model 3000. . The artificial intelligence model 3000 may include an electronic device usage habit training model that trains the electronic device 1000 usage habits of 1500 electronic device users.

An electronic device management system according to an embodiment of the present disclosure is based on user information such as a user's own temperament and inclination, behavior pattern, taste, and interest keywords, and manager information such as a manager's parenting environment, parenting values, and intervention method. After the initial setting of the device usage habit training model is completed, the electronic device usage habit training model may be trained based on the usage history, use end point, and interaction information between the user and the electronic device.

According to an embodiment of the present disclosure, the electronic device usage habit training model includes not only user information and manager information, but also the user's electronic device 1000 usage environment (eg, main use place or main use time zone) or characteristics of the electronic device 1000 ( For example, it may be initially set by additionally using environment information such as type or performance).

The electronic device management system according to an embodiment of the present disclosure may select and reflect a GUI with a high user preference based on user information such as a user's own temperament and inclination, behavior pattern, taste, and interest keyword. For example, if the user is a preschool boy and the permitted use time has expired, the electronic device selects the most preferred character by referring to data of users of the same age, sex, temperament, and disposition as the user, and selects the character electronically. The user may end use of the electronic device by outputting a voice prompting the user to end use of the device.

When a plurality of administrators exist, even for the same user, the user-manager type may be different according to the relationship between the plurality of managers and the propensity of each of the plurality of managers, so the artificial intelligence model 3000 for managing the user device 1000 is It may be applied differently to each of a plurality of managers.

In addition, the electronic device management system according to an embodiment may collect and analyze a manager's inclination, and may guide the manager to modify the manager's child-rearing attitude or control the user's use of the electronic device based on an appropriate criterion. For example, if a manager is an indifferent or neglectful parent as a result of the Baumlind parenting attitude test, the manager may be guided to become a democratic parent based on the result of the parenting attitude test.

According to an embodiment of the present disclosure, when there are a plurality of managers, each manager can manage the user's electronic device 1000, and the user's electronic device 1000 can be managed using a plurality of manager devices. Also, when the electronic device 1000 has a plurality of users, the electronic device 1000 may separately manage control conditions and use details for each of the plurality of users. The electronic device 1000 may create at least one account (or profile) of each manager and an account (or profile) of each of at least one user, and manage the account (or profile) by linking the manager information and user information. .

Referring to FIG. 3 , the electronic device 1000 may include a manager information acquisition module 1100, a user information acquisition module 1300, and a user-administrator type determination module 1500. The server 3000 may be an artificial intelligence server and may include a management condition determination module 3100 and a database 3300.

The manager information acquisition module 1100 may include a manager basic information acquisition module 1101, an intervention method acquisition module 1103, and a parenting attitude information acquisition module 1105.

The manager basic information is basic information for identifying the manager, and may include, for example, the manager's name, date of birth (DOB), gender, relationship with a user, and basic information required for system use. In addition, the manager's basic information can be used as information for estimating the intervention method or parenting attitude. For example, since a manager's mediation method or parenting attitude may be different depending on the age or gender of the manager, or the relationship with the user, the electronic device 1000 may be affected by the mediation method or By reflecting statistical information on parenting attitudes, the moderation method or parenting attitude of managers can be estimated.

The manager basic information may include the manager's biometric information (eg, face, fingerprint, or iris), and the electronic device 1000 may identify the manager using a sensor provided in the electronic device 1000 . For example, when the electronic device 1000 photographs a face using a camera and compares a face included in the photographed image with a face included in manager basic information to identify a registered manager, information related to the account of the identified manager. The mediation method information means information on how the manager mediates in a conflict situation in which the user is in conflict with the user, or information on how the administrator solves the problem when a problem occurs while the user is using the electronic device. do.

Parenting attitude information refers to information about the parent manager's parenting attitude toward the child user.

According to an embodiment, the manager's mediation method information or parenting attitude information may be obtained based on a result of a parental parenting value test and a related test result.

According to an embodiment, the manager's mediation method information or parenting attitude information may be obtained based on a control history of using an electronic device.

The user information acquisition module 1300 may include a user basic information acquisition module 1301 , a usage method acquisition module 1303 , and a temperament and inclination acquisition module 1305 .

Basic user information is information for identifying a user, and may include, for example, basic information necessary for using the electronic device 1000, such as the user's name, date of birth, gender, or health information. According to an embodiment of the present disclosure, the electronic device 1000 may obtain health-related information of a user. For example, when a user has color blindness or color weakness, the electronic device 1000 may obtain related information or information about the user's eyesight.

In addition, user basic information can be used as information for estimating the usage method, temperament, and propensity. For example, since the user's usage method, temperament, and inclination may differ depending on the user's age or gender, the electronic device 1000 reflects statistical information on other users of the same age and gender to reflect the user's usage method, temperament, and disposition. tendency can be inferred.

The basic user information may include the user's biometric information (eg, face, fingerprint, iris, etc.), and the electronic device 1000 photographs the face using a sensor provided in the electronic device 1000 and includes it in the photographed image. When a registered user is identified by comparing the registered face with the face included in the basic user information, management conditions related to the account of the identified user may be applied.

The information on the user's electronic device usage method may include, but is not limited to, the user's electronic device usage time, usage pattern, usage time for each application, and viewing distance of the electronic device. According to an embodiment of the present disclosure, information about a user's electronic device usage method may be obtained based on a result of checking the electronic device usage status. When there are multiple users of the electronic device 1000, information on how the electronic device is used for each of the plurality of users can be managed separately, and information on how each of the plurality of users uses the electronic device is stored in the electronic device. It can be saved to your account.

According to an embodiment of the present disclosure, information on the user's temperament and inclination may be obtained based on the user's behavior pattern, taste, and user's interest keyword. According to an embodiment of the present disclosure, information on a user's temperament and inclination may be obtained based on a result of a child temperament test. In this case, the user's behavioral pattern, taste, user's interest keyword, and child temperament test result may be determined based on information about the user input by the manager.

According to an embodiment, information about a user's electronic device usage method or information about a user's temperament and inclination may be obtained based on a user's electronic device usage history.

The user-manager type determination module 1500 may determine the user-manager type based on the manager information obtained in the manager information acquisition module 1100 and the user information obtained in the user information acquisition module 1300 . The user-manager type may be determined based on the manager's parenting style determined based on the manager information and the user temperament determined based on the user information. For example, if a parent's parenting style is democratic, it may be an optimal parenting attitude for a child who is independent and has high self-restraint, since it is highly acceptable to the child's needs. However, indefinitely accommodating the needs of children who do not have high self-restraint can become neglect and adversely affect the child's development. Therefore, it is necessary to determine electronic device management criteria based on the user-manager type determined based on the manager's upbringing style and user temperament.

When there are a plurality of users, the electronic device 1000 may determine a user-manager type for each of the plurality of users based on basic information, a usage method, temperament, and inclination of each of the plurality of users. When there are a plurality of managers, the electronic device 1000 may determine a user-manager type for each of the plurality of managers based on basic information, mediation method, and parenting attitude of each of the plurality of managers. In addition, when there are a plurality of managers and users, the electronic device 1000 provides a plurality of managers based on basic information, usage, temperament, and propensity of each of the plurality of users and basic information, mediation method, and parenting attitude of each of the plurality of managers. A user-administrator type for each of the user and the plurality of administrators may be determined.

According to an embodiment of the present disclosure, the first electronic device may determine a first user and a first manager having a parent-child relationship, the first user as a first type child and the first manager as a first type parent. Alternatively, the second electronic device may determine that the second user is a second type child and the second manager is a second type parent. These typologies are not fixed or defined, and may be added to or modified according to child development or psychological development studies.

In addition, the user-manager type determination criterion is a parent-child type determination criterion such as Enneagram or Baumlind, or an individual such as TCI (Temperament and Character Inventory), MMPI (Minnesota Multiphasic Personality Inventory) or MBTI (Myers-Briggs Type Indicator). A criterion for determining a relationship type according to inclination or a model for measuring a relationship type may be used.

According to an embodiment of the present disclosure, the electronic device 1000 may update the firmware of the user-administrator type determination module 1500 through download after initial setting, and may add an additional user-administrator type check/determination criterion. Addition of the user-administrator type inspection/determination criterion may be performed at the request of the electronic device manager, and may be accompanied by separate billing in some cases.

The electronic device 1000 may transfer the user-manager type output from the user-manager type determination module to the server 3000 .

The server 3000 may obtain a user-manager type determined based on manager information and user information from the electronic device 1000 and determine an electronic device management condition based on the determined user-manager type.

The management condition determination module 3100 of the server 3000 may determine the management condition based on the user-manager type obtained from the electronic device 1000 . According to an embodiment of the present disclosure, when the user-manager type of the first electronic device is that the first user is a Q-V type child and the first manager is an A-F type parent, the management condition determination module 3100 determines the management of the first electronic device. As the criterion, the first type management criterion may be selected. Also, if the user-manager type of the second electronic device is that the second user is an R-W type child and the second manager is a B-G type parent, the management condition determination module 3100 determines the second type of management based on the management criterion of the second electronic device. You can choose a criterion.

In the electronic device management method according to the present disclosure, as a method for inferring or predicting electronic device management criteria, artificial intelligence is used to recommend/execute electronic device management criteria by using electronic device user information and electronic device manager information data. Intelligence models are available. The processor of the electronic device 1000 may perform a preprocessing process on the data, convert it into a form suitable for use as an input of an artificial intelligence model, and transmit the data to the server 3000. Alternatively, the processor of the server 3000 may perform a preprocessing process on the data received from the electronic device 1000 to convert it into a form suitable for use as an input of an artificial intelligence model. AI models can be created through learning. Here, being made through learning means that a basic artificial intelligence model is learned using a plurality of learning data by a learning algorithm, so that a predefined action rule or artificial intelligence model set to perform a desired characteristic (or purpose) is created. means burden. An artificial intelligence model may be composed of a plurality of neural network layers. Each of the plurality of neural network layers has a plurality of weight values, and a neural network operation is performed through an operation between an operation result of a previous layer and a plurality of weight values.

Inference prediction is a technology that judges information and logically infers and predicts it. It includes Knowledge based Reasoning, Optimization Prediction, Preference-based Planning, and Recommendation. include

The database 3300 refers to a memory in which data for learning an artificial intelligence model is stored.

Functions related to artificial intelligence according to the present disclosure are operated through a processor and a memory. A processor may consist of one or a plurality of processors. In this case, the one or more processors may be a general-purpose processor such as a CPU, an AP, or a digital signal processor (DSP), a graphics-only processor such as a GPU or a vision processing unit (VPU), or an artificial intelligence-only processor such as an NPU. One or more processors control input data to be processed according to predefined operating rules or artificial intelligence models stored in a memory. Alternatively, when one or more processors are processors dedicated to artificial intelligence, the processors dedicated to artificial intelligence may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

A predefined action rule or an artificial intelligence model is characterized in that it is created through learning. Here, being made through learning means that a basic artificial intelligence model is learned using a plurality of learning data by a learning algorithm, so that a predefined action rule or artificial intelligence model set to perform a desired characteristic (or purpose) is created. means burden. Such learning may be performed in the device itself in which artificial intelligence according to the present disclosure is performed, or through a separate server and/or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the above examples.

An artificial intelligence model may be composed of a plurality of neural network layers. Each of the plurality of neural network layers has a plurality of weight values, and a neural network operation is performed through an operation between an operation result of a previous layer and a plurality of weight values. A plurality of weights possessed by a plurality of neural network layers may be optimized by a learning result of an artificial intelligence model. For example, a plurality of weights may be updated so that a loss value or a cost value obtained from an artificial intelligence model is reduced or minimized during a learning process. The artificial neural network may include a deep neural network (DNN), for example, a Convolutional Neural Network (CNN), a Deep Neural Network (DNN), a Recurrent Neural Network (RNN), a Restricted Boltzmann Machine (RBM), A deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), or deep Q-networks, but is not limited to the above examples.

The artificial intelligence model 3000 may obtain manager information for determining management criteria for the electronic device 1000 .

Manager information may include manager basic information, information on mediation methods, and parenting attitudes.

User information may include user basic information, information on the user's electronic device usage method, and information on the user's temperament and inclination.

The electronic device management criteria include the user's posture of using the electronic device 1000, the distance between the user and the electronic device 1000 (critical minimum distance), the user's usage time of the electronic device 1000, and the user's electronic device 1000 dependence. /This may include settings of characters to be provided to the user for addiction diagnosis and mediation of use, or setting of additional services that the electronic device 1000 can provide.

The criterion for the user's device usage time may include, but is not limited to, maximum usage time per day, maximum usage time per day, maximum usage time per application, usage time per session, and combinations thereof.

The electronic device 1000 may provide the determined electronic device management criteria to the manager and modify the electronic device management criteria based on the manager's input.

In step 401, the electronic device 1000 may acquire user information and manager information of the electronic device.

Electronic device user information may include user basic information, usage method information, and disposition/propensity information.

Basic user information is basic information for identifying a user, and may include, for example, the user's name, date of birth, gender, and basic information necessary for using the system.

The information on the user's electronic device usage method may include, but is not limited to, the user's electronic device usage time, usage pattern, usage time for each application, and viewing distance of the electronic device.

According to an embodiment of the present disclosure, information about a user's electronic device usage method may be obtained based on a result of checking the electronic device usage status.

According to an embodiment of the present disclosure, information on the user's temperament and inclination may be obtained based on the user's behavior pattern, taste, and user's interest keyword. According to an embodiment of the present disclosure, information on a user's temperament and inclination may be obtained based on a result of a child temperament test. Child temperament tests may include, but are not limited to, temperament tests such as Enneagram, TCI, MMPI, or MBTI. In addition, the user's behavior pattern, taste and interest keywords of the user, and child temperament test results may be determined based on information about the user input by the administrator.

According to an embodiment of the present disclosure, information on a user's electronic device usage method or information on the user's temperament and inclination may be obtained based on a user's electronic device usage history.

According to an embodiment of the present disclosure, the electronic device 1000 may select a character suitable for the user based on the obtained information on the user's temperament and inclination, and may use the selected character for an interaction for controlling the electronic device. For example, if the user is a 5-year-old boy and an extrovert, the electronic device 1000 may select a robot character for interaction and may operate the selected robot character to output a voice recommending discontinuation of use through a speaker when the usage time expires. there is.

According to an embodiment of the present disclosure, the electronic device 1000 may provide a customized character by combining parts of each part such as the face, arms, and legs of the character. In this case, the parts may be selected based on the user input, and the user's temperament and propensity may be more accurately estimated based on the additional information obtained in the process of selecting and combining the parts. The additional information obtained in the process of selecting and combining parts may include at least one of the color, shape, characteristics, combination order, and time taken to complete the character of the selected parts.

According to an embodiment of the present disclosure, after the initial setting of the electronic device 1000, a character or parts may be additionally downloaded and stored according to a request of a user or manager of the electronic device, and the downloaded character may be used to interact with the user of the electronic device. In the case of a child user, when interacting with a cartoon character or a toy character he or she prefers, compliance with instructions or suggestions may be higher, and the preferred character may vary depending on the developmental state or period. Accordingly, by configuring the character to be changed according to the user's preference, more effective electronic device use management may be possible.

In this case, the added character may require separate billing, and when a subscription-type purchase type is applied instead of a temporary purchase, various characters may be used at a low cost.

The electronic device manager information may include manager basic information, mediation method information, and parenting attitude information.

The manager basic information is basic information for identifying the manager, and may include, for example, the manager's name, date of birth (DOB), gender, relationship with a user, and basic information required for system use. Arbitration method information refers to information on how an administrator mediates in a conflict situation in which a user is confronted with a user. Parenting attitude information refers to information about the parent manager's parenting attitude toward the child user.

In step 402, the electronic device 1000 may acquire an electronic device management condition identified from an artificial intelligence model based on information about a user and a manager of the electronic device.

An artificial intelligence model according to an embodiment of the present disclosure may be an on-device model independently operated inside an electronic device or a server model operated in a server outside the electronic device. Alternatively, the artificial intelligence model according to an embodiment of the present disclosure may be a combination of an on-device model and a server model. For example, an on-device AI model can be responsible for inference, and a server AI model can be responsible for learning and collecting and analyzing big data. The server includes, but is not limited to, a cloud server.

When an artificial intelligence model including a server model is used, the electronic device 1000 may transmit the obtained electronic device user information and electronic device manager information to the artificial intelligence server 3000 .

According to an embodiment of the present disclosure, the electronic device 1000 may acquire electronic device user information and electronic device manager information, and transmit the obtained information to the artificial intelligence server 3000 as it is. According to another embodiment of the present disclosure, the electronic device 1000 may analyze the obtained electronic device user information and electronic device manager information, transform it into a necessary form, and transmit the same. For example, information transmitted from the electronic device 1000 to the artificial intelligence server 3000 may be user-administrator type information determined based on the obtained electronic device user information and electronic device manager information.

According to an embodiment of the present disclosure, the processor of the electronic device 1000 may perform a pre-processing process on data transmitted to the server 3000, convert the data into a form suitable for use as an input of an artificial intelligence model, and transmit the data to the server 3000.

The electronic device management condition refers to a condition for determining whether the electronic device 1000 intervenes in the use of the user's electronic device, and includes conditions for the user's electronic device usage time, user's electronic device usage history, and user's electronic device management condition. Conditions for device usage posture, diagnosis of user's dependence/addiction on the electronic device, setting of characters to be provided to the user for usage mediation, and setting of additional services that the electronic device can provide may be included. The additional service that the electronic device may provide may include at least one of a developmental examination of an electronic device user using the electronic device, monitoring of harmful content, monitoring of user posture, monitoring of the use of the electronic device while walking, and monitoring of the environment in which the electronic device is used. there is. The electronic device usage environment monitoring includes monitoring of a place where the user uses the electronic device 1000. For example, the electronic device 1000 determines whether the user is using the electronic device 1000 in a noisy place, in water or in a place with high humidity. acknowledgment can be monitored.

According to an embodiment of the present disclosure, the server 3000 may identify an electronic device management condition based on electronic device user information and electronic device manager information received from the electronic device 1000 . According to another embodiment of the present disclosure, the server 3000 may obtain a user-manager type determined based on manager information and user information from the electronic device 1000, and determine an electronic device management condition based on the determined user-manager type.

According to an embodiment of the present disclosure, the processor of the server 3000 may perform a pre-processing process on the data received from the electronic device 1000 to convert it into a form suitable for use as an input of an artificial intelligence model.

In the method for managing an electronic device according to the present disclosure, as a method for inferring or predicting electronic device management conditions, artificially recommending/executing electronic device management conditions using electronic device user information and electronic device manager information data. Intelligence models are available.

Conditions for the user's electronic device usage time may include, but are not limited to, the maximum usage time per day, the maximum usage time per day, the maximum usage time per application, the usage time per session, and combinations of each when the electronic device user uses the electronic device. it is not going to be

According to an embodiment of the present disclosure, a condition for a user's electronic device usage time may be obtained based on a usage time recommendation model. The use time recommendation model may include an electronic device use time recommendation model and an electronic device overdependency diagnosis model that recommends an appropriate use time based on user information, and the user's electronic device dependence/addiction using the electronic self-government overdependency diagnosis model Diagnosis may be performed when the electronic device starts to be used. An electronic device usage time recommendation model and an electronic device usage time recommendation model learning method according to an embodiment of the present disclosure will be described later with reference to FIGS. 7 and 8 .

The conditions for the user's use of the electronic device may include conditions for harmfulness of the content provided to the user through the electronic device 1000 and a control method of the electronic device 1000 when the content provided to the user is determined to be harmful. there is.

According to an embodiment of the present disclosure, the condition for the user's electronic device use history may include a condition for determining whether or not harmful content is present by utilizing multiple pieces of information that can be collected and analyzed by the electronic device 1000 .

The condition for the user's posture of using the electronic device may be based on the posture of the user of the electronic device 1000 using the electronic device, the distance between the electronic device 1000 and the user, or the eye blink cycle of the user of the electronic device 1000. may include a condition for determining whether is appropriate. For example, the electronic device 1000 determines the user's posture, such as whether the user is using the electronic device 1000 while lying down or whether there is only a turtle neck or a side of the spine, based on the degree of inclination of the user's upper body, the angle of the upper body and neck, or the angle of the shoulder. can judge In addition, the electronic device 1000 may determine that the user's posture for using the electronic device is inappropriate when the distance between the electronic device 1000 and the user is equal to or less than a predetermined minimum threshold distance or the user's eye blink cycle is equal to or less than the predetermined cycle. At this time, the electronic device 1000 may determine the user's posture of using the electronic device based on the electronic device posture determination model.

In step 403, the electronic device may control the electronic device based on the electronic device management condition.

The electronic device 1000 may monitor the user's use of the electronic device. According to an embodiment of the present disclosure, the electronic device 1000 monitors the user's use of the electronic device 1000 in real time, and if the user's current usage state of the electronic device 1000 deviates from the electronic device management condition, the electronic device 1000 is based on the electronic device management condition. 1000 can be controlled.

According to an embodiment of the present disclosure, control of the electronic device of the electronic device 1000 may include not only direct control for the electronic device 1000 to change the use state of the electronic device, but also control for inducing a change in the use state of the electronic device to a user. there is. For example, if the user is a child, the electronic device 1000 may control the electronic device 1000 to display a character liked by the child on a portion of the screen and transmit a voice indicating that the usage time of the electronic device has been exceeded by the corresponding character. there is. Alternatively, the electronic device 1000 may control the electronic device 1000 to display a message recommending a change in the posture of using the electronic device on the screen.

According to an embodiment of the present disclosure, the electronic device 1000 may display on the screen of the electronic device 1000 whether or not the electronic device management method is executed while the electronic device management method is being executed. For example, when an electronic device management application is executed, the electronic device 1000 displays a character selected based on user information or manager information on the screen of the electronic device 1000, and the character displays a usage state of the electronic device 1000 (eg, The electronic device 1000 may be controlled to indicate whether an electronic device management method is executed, a user name, remaining use time, or whether a control condition is satisfied. In addition, the electronic device 1000 controls the electronic device 1000 to output a message (voice or visual) that induces the corresponding character to change the user's use state of the electronic device (eg, end use, change content, or change posture). can do.

According to an embodiment of the present disclosure, the electronic device 1000 may determine a method of displaying a usage state of the electronic device 1000 in consideration of a user's cognitive characteristics. For example, if the user is an infant, voice is output instead of text display in consideration of the infant's cognitive ability, and in the case of remaining time, a circle or bar-type graphic (e.g., The remaining time can be displayed using the grass bar). Alternatively, the remaining time may be indicated using object graphics familiar to young children rather than figure graphics. For example, the amount of food (fruit or drink, etc.) is displayed as a graphic animation according to the remaining time, objects (character's belongings, etc.) It can be displayed as a graphic animation. In addition, when an intervention method using storytelling, an interactive interaction, and a gradual mediation method are used in consideration of the animistic thinking characteristics of children, a more effective change in electronic device use status can be induced.

According to an embodiment of the present disclosure, the electronic device 1000 may control the electronic device 1000 based on the user's electronic device usage time condition and the user's current electronic device usage status.

The user's usage time of the electronic device may be monitored, and an output for notifying the user of the corresponding content may be transmitted at predetermined intervals or when the remaining time is less than or equal to a threshold time. In this way, by providing a notification to the user before the user's usage time of the electronic device is exhausted, the user can be alerted and induced to organize the usage details. As described above, the type of output to notify the user may be determined based on user information (eg, age or cognitive ability).

According to an embodiment of the present disclosure, the electronic device 1000 actually uses a certain percentage of the time (eg, 75% of 1 hour, 45 minutes) or before a certain time from the time when the use time is expected to be exhausted (eg, 45 minutes). For example, 10 minutes prior to the expected time of exhaustion) notification may be provided. At this time, the notification provided to the user may induce interaction (interaction) with the user, and includes visual, auditory, or multi-sensory interaction and any interaction method.

According to an embodiment of the present disclosure, the electronic device 1000 may identify whether the electronic device 1000 has voluntarily terminated based on whether the user terminated use before the use time was exhausted or continued use until the use time was exhausted according to the output of the electronic device. , AI models can be learned based on voluntary termination.

Conditions for the user's use of the electronic device may include conditions for harmfulness of content provided to the user through the electronic device 1000 and a control method of the electronic device 1000 when the content provided to the user is determined to be harmful. .

According to an embodiment of the present disclosure, the electronic device 1000 may determine harmfulness of an image included in content provided to a user. The electronic device 1000 may capture a screen provided to the user at a predetermined cycle and recognize text and images included in the captured screen using an image analysis model. As a result of video analysis, if a harmful image or text is included, it may be decided not to provide the video to the user. At this time, the video may include a web page as well as a still image and a moving picture.

According to an embodiment of the present disclosure, the electronic device 1000 may determine whether to provide the corresponding content to the user by referring to age information (eg, PG rating set for a video) set for the content provided to the user.

According to an embodiment of the present disclosure, the electronic device 1000 determines the harmfulness of the text included in the screen provided to the user in order to prevent a situation in which the user is a child and is continuously exposed to the harmful text due to not recognizing the harmful text. can do. The electronic device 1000 may capture a screen provided to the user at predetermined intervals and recognize text (characters) included in the captured screen using a text recognition model. If the recognized text includes harmful text, the electronic device 1000 does not provide the selected content even if the user selects the text and its surrounding content (for example, touching a hyperlinked text or selecting a related video). (eg, masking the input for the corresponding text and its surrounding content). A text monitoring and learning method according to an embodiment of the present disclosure will be described later with reference to FIG. 10 .

According to an embodiment of the present disclosure, the electronic device 1000 may determine harmfulness of sound included in content provided to the user. The electronic device 1000 analyzes the sound provided to the user using the sound recognition model, and if the result of the sound analysis includes a harmful sound (eg, a gunshot, slang, profanity, etc.), the electronic device 1000 may determine not to provide the sound to the user. there is.

According to an embodiment of the present disclosure, the electronic device 1000 may monitor usage history of the electronic device user of the electronic device based on multiple pieces of information that can be collected and analyzed by the electronic device, and determine whether or not there is harmful content. The multi-information that can be collected and analyzed by the electronic device 1000 includes all types of information that the electronic device 1000 can identify, such as images, texts, and sounds, and the electronic device 1000 stops the user from using the electronic device based on the multi-information. All actions to mediate and intervene in the user's use of the electronic device may be provided, such as inducing the use of the electronic device.

For example, while monitoring the use of an electronic device in real time, if it is determined that harmful text or images are included, the electronic device 1000 turns off the backlight of the display of the electronic device, stops the operation of the electronic device, or displays a harmful image. Direct control, such as mosaicking text or harmful images, or skipping parts containing harmful text or images, as well as outputting a voice suggesting the user to use other content or instructing parents to ask for help Additional control such as outputting a voice may be performed.

Alternatively, if it is determined that part of the content includes harmful text or harmful images, the electronic device 1000 deletes only the harmful text or harmful image parts and synthesizes the area from which the harmful content is deleted with the background to provide seamless content. can do. In this case, since the user does not recognize that the harmful content is blocked, the user's resistance to the manager's management of the electronic device 1000 is reduced.

The conditions for the posture of using the electronic device are the posture of the user of the electronic device 1000 using the electronic device, the distance between the electronic device 1000 and the user, the conditions for the blinking cycle of the user of the electronic device 1000, and the posture of using the electronic device determined to be inappropriate. In this case, the control method of the electronic device 1000 may be included.

According to an embodiment of the present disclosure, the electronic device 1000 may determine a user's posture for using the electronic device. A condition for the user's posture for using the electronic device may be determined based on an analysis result of multiple pieces of information that may be collected from a camera and an angle sensor in the electronic device 1000 .

The user's posture for using the electronic device may include information about a pose the user takes when using the electronic device 1000, a distance between the electronic device 1000 and the user, and information on eye blinking of the user of the electronic device.

360 to 1000 electronic devices? When a camera is included, the electronic device 1000 may obtain a multi-faceted image captured from the front, side, or rear side, and may obtain user posture (pose) information based on the obtained multi-faceted image. According to an embodiment of the present disclosure, the electronic device 1000 compares a predetermined reference posture with posture information of the user, and based on the result, determines whether the posture of the user needs to be corrected and how to correct the posture of the user. can A detailed method of measuring, by the electronic device 1000, the distance between the electronic device 1000 and the user and the blinking cycle of the user of the electronic device will be described later with reference to FIGS. 12 and 13 .

When it is determined that the user's posture for using the electronic device is inappropriate, the electronic device 1000 may determine to request the user to correct the posture. The electronic device 1000 outputs multi-sensory instructions in addition to visual (eg, display notification or character transmission, etc.) and auditory (eg, sound notification or character utterance, etc.) instructions in order to request the user to correct the posture. can do.

If the electronic device 1000 is used for a long time in a specific pose (for example, the head is bent forward), not only musculoskeletal diseases such as scoliosis, carpal tunnel syndrome, or turtle neck, but also eye diseases such as increased intraocular pressure may occur. Accordingly, when the user of the electronic device maintains the same pose for more than a predetermined threshold time, the electronic device 1000 according to an embodiment of the present disclosure may output a sensory interaction recommending that the user change a pose or take a correct posture. there is. In this case, the output sensory interaction may be related to a predetermined character selected by the user, and an animation and voice may be output in which the character displayed on the screen changes posture, stretches, or performs gymnastics.

According to an embodiment of the present disclosure, the electronic device 1000 may include at least one sensor capable of recognizing a finger on the front or side, and the electronic device 1000 of the user is detected based on sensing information obtained from the at least one sensor. It can obtain gripping status and provide guidance on the correct gripping method. At this time, at least one sensor may be a fingerprint recognition sensor.

If the electronic device 1000 is used at an excessively short distance, eye diseases such as myopia and strabismus may occur. Therefore, according to an embodiment of the present disclosure, when the distance between the electronic device 1000 and the user of the electronic device is within a predetermined threshold distance, the electronic device 1000 may output a sensory interaction recommending the user to locate the electronic device farther away. there is. At this time, the electronic device 1000 captures the user's face with the electronic device's camera, identifies the location of the user's two pupils and the distance between the two pupils by using a pupil detection vision model in the captured face image, and identifies the electronic device 1000 and the distance between the two pupils. It may be determined whether the distance between the user's eyes is within a threshold distance. Dry eye syndrome is a representative symptom of visual terminal (DVT) syndrome, and occurs when the eye blink cycle is prolonged when using an electronic device. The electronic device 1000 may adjust the brightness of the display of the electronic device 1000 based on at least one of the brightness of the display of the electronic device 1000, the brightness of the surroundings of the electronic device 1000, the elapsed time of using the electronic device, or the type of content used by the electronic device. For example, when a user uses the electronic device 1000 for a long time in a place with low ambient light, the electronic device 1000 predicts the user's eye fatigue according to the ambient light and the brightness of the display of the electronic device 1000, and adjusts the brightness of the display of the electronic device 1000 to the user. It can be determined and controlled at an appropriate level that does not strain the eyes.

In the case of a child user whose self-regulation ability is not mature, the eye blink cycle may become longer due to over-immersion. Therefore, the electronic device 1000 according to an embodiment of the present disclosure measures the eye blinking cycle of the electronic device user, and if the blinking cycle of the electronic device user is longer than a predetermined threshold cycle, the electronic device 1000 instructs the user to close his/her eyes for a while and read the electronic device. A sensory interaction recommending stopping use of the device 1000 may be output. At this time, the electronic device 1000 identifies the user's eye blink pattern using a convolutional neural network-based vision model that detects eye blinks, and determines that the user is overfocused when the eye blink cycle is longer than the critical cycle. there is. Alternatively, the electronic device 1000 may determine whether the user of the electronic device is over-immersed based on whether the user's mouth is opened or closed, which is determined by using the oral cavity detection model in the captured face image.

If it is determined that the user of the electronic device is overinvolved, the electronic device 1000 may output a predetermined sound or graphic to arouse the user's attention. In this case, the output sound or graphic may be related to a predetermined character selected by the user. If the user is a child, the electronic device 1000 may temporarily stop using the electronic device, and then display an animation in which a character displayed on the screen blinks or hurts the eyes, or outputs a related voice.

According to an embodiment of the present disclosure, the electronic device 1000 outputs an instruction recommending posture correction to the user, and if the posture is not corrected after a predetermined period of time, the electronic device 1000 temporarily pauses the electronic device to allow the user to adjust the posture in stages. Use of electronic devices can induce posture correction.

Referring to FIG. 5 , when an artificial intelligence model including a server model is used in an electronic management system according to an embodiment of the present disclosure, the electronic device management system may include an electronic device 1000 and an artificial intelligence server 3000. there is. The server 3000 may be an artificial intelligence server. In the description of FIG. 5 , contents overlapping those of FIGS. 3 and 4 may be omitted.

In the embodiment disclosed in FIG. 5 , when a user who is a child uses a mobile device (for example, a mobile phone or tablet) of a manager who is a parent, or a parent manager uses a mobile device of a child user to provide user information and manager information. It can be assumed that the case of inputting .

The electronic device management system according to an embodiment of the present disclosure, when the start of use of the electronic device 1000 is confirmed, the analysis result of the use history at the time of the previous use, the history of the previous use history being reflected in the management conditions, and the available history of the current use (time and application) can be provided to administrators or users.

In step 501, the electronic device 1000 may obtain electronic device user information and manager information.

Electronic device user information may include user basic information, usage method information, and disposition/propensity information. The electronic device manager information may include manager basic information, mediation method information, and parenting attitude information.

In step 502, the electronic device 1000 may transmit the obtained electronic device user information and electronic device manager information to the artificial intelligence server 3000.

According to an embodiment of the present disclosure, the electronic device 1000 may acquire electronic device user information and electronic device manager information, and transmit the obtained information to the artificial intelligence server 3000 as it is. The artificial intelligence server 3000 receiving the electronic device user information and manager information from the electronic device 1000 may determine the user-manager type based on the user information and the electronic device manager information.

According to another embodiment of the present disclosure, the electronic device 1000 may analyze the obtained electronic device user information and electronic device manager information, transform it into a necessary form, and transmit it. For example, information transmitted from the electronic device 1000 to the artificial intelligence server 3000 may be user-administrator type information determined based on the obtained electronic device user information and electronic device manager information.

In step 503, the artificial intelligence server 3000 may acquire electronic device management conditions.

According to an embodiment of the present disclosure, the processor of the artificial intelligence server 3000 may perform a pre-processing process on the data received from the electronic device 1000 to convert it into a form suitable for use as an input of an artificial intelligence model.

According to an embodiment of the present disclosure, the condition for the user's electronic device use history may include a condition for determining whether or not harmful content is present by utilizing multiple pieces of information that can be collected and analyzed by the electronic device.

Conditions for the user's posture of using the electronic device include the posture of the user of the electronic device 1000 using the electronic device, the distance between the electronic device 1000 and the user, the conditions for the eye blink cycle of the user of the electronic device 1000, and the improper posture of using the electronic device. When it is determined that the electronic device 1000 may include a control method.

In step 504, the artificial intelligence server 3000 may transmit electronic device management conditions to the electronic device 1000.

In steps 505 to 506, the electronic device 1000 may monitor usage of the electronic device and control the electronic device.

According to an embodiment of the present disclosure, the electronic device 1000 monitors the user's usage of the electronic device 1000 in real time based on the electronic device management conditions acquired from the server, and the user's current usage state of the electronic device 1000 determines the electronic device management conditions. When out of range, the electronic device 1000 may be controlled based on the electronic device management conditions.

According to an embodiment of the present disclosure, control of the electronic device of the electronic device 1000 may include not only direct control for the electronic device 1000 to change the use state of the electronic device, but also control for inducing a change in the use state of the electronic device to a user. there is. For example, if the user is a child, the electronic device 1000 may control the electronic device 1000 to display a character liked by the child on a portion of the screen and transmit a voice indicating that the usage time of the electronic device has been exceeded by the corresponding character. there is. Alternatively, the electronic device 1000 may display a message or image recommending changing the posture of using the electronic device on the screen, or control the electronic device 1000 to display an icon or vibrate to call attention to the user regarding the use of the electronic device. can If the user's state of use of the electronic device violates the electronic device management condition unconsciously, the user may be induced to voluntarily comply with the electronic device management condition when the user's attention is aroused.

According to an embodiment of the present disclosure, the electronic device 1000 determines the electronic device 1000 based on the user's electronic device usage time condition, the user's electronic device usage history condition, and the user's current electronic device usage condition condition. can control.

In step 507, the electronic device 1000 may transmit interaction information and action data between the user and the electronic device 1000 to the artificial intelligence server 3000.

Interaction information between the user and the electronic device refers to information related to all interactions provided to the user in order to control the user's use of the electronic device. The interaction induces posture correction based on an interaction provided to induce use of an electronic device based on a usage time condition, an interaction provided to induce use of other content based on a usage history condition, and a usage posture condition. It may include the interaction provided to do so. In addition, the interaction may include all of visual, auditory, multi-sensory interactions, and other interactions.

The action data refers to data on actions taken by the user while using the electronic device and data obtained by analyzing the user's actions while the user is using the electronic device. For example, if the electronic device 1000 provides an interaction for inducing termination of use before the usage time ends, and the user ends the use in response to the interaction, the electronic device responds to the user's 'end' action and the corresponding 'end' action. 'Action can be judged as an arbitrary termination according to an interaction and converted into data and stored.

The electronic device 1000 may store not only the user's use history of the electronic device, but also interaction information and action data between the user and the electronic device. For example, the electronic device 1000 includes the user's method of using the electronic device, the history of questions and responses uttered by the user from the start of use to the end of use, the user's posture in using the electronic device, whether or not the electronic device voluntarily terminated in response to intervention within the end of use, Alternatively, information such as the user's acceptability of the electronic device use arbitration attempt (eg, the user's response to the electronic device use arbitration attempt, the type of response, or the time taken to respond) may be stored in the internal memory.

In steps 508 to 509, the artificial intelligence server 3000 may learn an artificial intelligence model based on the received interaction information and action data and update electronic device management conditions.

The artificial intelligence server 3000 learns an artificial intelligence model by analyzing interaction information and action data between the user and the electronic device received from the electronic device 1000 . For example, the artificial intelligence server 3000 includes the user's electronic device usage method, the history of questions and responses uttered by the user from the start of use to the end of use, the user's posture in using the electronic device, and whether or not the user terminated voluntarily in response to intervention within the end time of use. AI models can be learned based on

The artificial intelligence server 3000 acquires updated electronic device management conditions based on the learned artificial intelligence model.

The artificial intelligence server 3000 may store interaction information and action data between the user and the electronic device received from the electronic device 1000, and the stored data is an artificial intelligence model for the next use of the electronic device as well as for establishing a mid- to long-term education plan. can be reflected in The artificial intelligence server 3000 according to the present disclosure learns an artificial intelligence model using statistical information about interaction information and action data of other users of the same age and gender, and manages an electronic device based on the learned artificial intelligence model. can be obtained.

In step 510, the artificial intelligence server 3000 may deliver updated electronic device management conditions to the electronic device 1000.

After acquiring the updated electronic device management conditions, the electronic device management system repeats steps 505 to 510 so that the electronic device 1000 can monitor and control the electronic device based on the updated electronic device management conditions.

Referring to FIG. 6 , the electronic device management system according to an embodiment of the present disclosure further includes a second electronic device in addition to the first electronic device and the server, wherein the first electronic device is a user device and the second electronic device is a manager. can mean a device.

In the embodiment disclosed in FIG. 6 , it may be assumed that a manager who is a parent uses a separate electronic device (second electronic device) to manage a child user's mobile device (first electronic device). When a manager as a parent uses a separate electronic device, real-time confirmation of a control state and setting of new conditions are possible even when the manager and the user are not in the same space.

If there is a second electronic device, that is, a separate manager device, the manager obtains the first electronic device user information and manager information through the second electronic device and transfers the information to the server, obtains and monitors the first electronic device control result, and , can feedback. The server 3000 may be an artificial intelligence server, and in FIG. 6, overlapping content with FIGS. 3 to 5 may be omitted.

In step 601, the second electronic device 2000 may obtain user information and manager information of the first electronic device.

In step 602, the second electronic device 2000 may transmit the acquired first electronic device user information and electronic device manager information to the artificial intelligence server 3000.

According to another embodiment of the present disclosure, the first electronic device obtains first electronic device user information and transmits it to the artificial intelligence server 3000, and the second electronic device obtains first electronic device manager information and transmits it to the artificial intelligence server 3000. It can be transmitted, but this is not shown.

In step 603, the artificial intelligence server 3000 may obtain a first electronic device management condition.

In step 604, the artificial intelligence server 3000 may transmit a first electronic device management condition to the electronic device 1000.

In steps 605 to 606, the first electronic device 1000 may monitor usage of the first electronic device and control the first electronic device.

According to an embodiment of the present disclosure, the first electronic device 1000 monitors the user's use of the first electronic device 1000 in real time, and if the user's current usage state of the first electronic device 1000 exceeds the first electronic device management condition, a 1 The electronic device 1000 may be controlled based on an electronic device management condition.

According to an embodiment of the present disclosure, control of the electronic device of the electronic device 1000 may include not only direct control for the electronic device 1000 to change the use state of the electronic device, but also control for inducing a change in the use state of the electronic device to a user. there is. For example, if the user is a child, the electronic device 1000 may control the electronic device 1000 to display a character liked by the child on a portion of the screen and transmit a voice indicating that the usage time of the electronic device has been exceeded by the corresponding character. there is. Alternatively, the electronic device 1000 may control the electronic device 1000 to display a user interface (UI) recommending a change in the posture of using the electronic device on the screen.

In step 607, the first electronic device 1000 may transmit interaction information and action data between the user and the first electronic device 1000 to the artificial intelligence server 3000.

Interaction information between the user and the electronic device refers to information related to all interactions provided to the user in order to control the user's use of the electronic device. The action data refers to data obtained by analyzing an action in which a user's intention is reflected while the user uses the electronic device.

In steps 608 to 609, the first electronic device 1000 may transmit the first electronic device control result to the second electronic device, and the second electronic device 2000 may display the first electronic device control result. Through steps 608 to 609, the manager of the first electronic device can check the control result of the first electronic device received from the second electronic device in real time.

In step 610, the second electronic device 2000 may transmit feedback on the first electronic device control result to the artificial intelligence server 3000.

Based on the control result of the first electronic device identified in step 609, the manager of the first electronic device provides feedback on the control result of the first electronic device using the second electronic device when additional control is required or when control conditions are changed. may be transmitted to the artificial intelligence server 3000. The feedback on the first electronic device control result may include the appropriateness of the first electronic device control, satisfaction with the first electronic device control result, whether the first electronic device control condition needs additional modification, or the first electronic device control condition additionally modified content. may include at least one of them.

According to an embodiment of the present disclosure, the second electronic device is a first electronic device management condition manually changed by a manager of the first electronic device or first electronic device user information and manager information modified by a manager of the first electronic device. may be transmitted to the artificial intelligence server 3000 to update the first electronic device management condition.

According to an embodiment of the present disclosure, the artificial intelligence server 3000 transmits a feedback request for the current electronic device management condition to the second electronic device 2000 at a predetermined cycle, and responds to the current electronic device management condition from the second electronic device 2000. You may receive a request for feedback. Alternatively, the artificial intelligence server 3000 provides feedback on the current electronic device management conditions when it is necessary to change the electronic device management conditions for the first 1000 users (for example, when the user reaches the age at which the developmental stage changes). A request may be transmitted, and a feedback request for a current electronic device management condition may be received from the second electronic device 2000 .

In steps 611 and 612, the artificial intelligence server 3000 learns an artificial intelligence model based on the interaction information and action data received from the first electronic device and the feedback on the control result of the first electronic device received from the second electronic device. , the first electronic device management condition may be updated.

In step 613, the artificial intelligence server 3000 may transfer the updated first electronic device management condition to the first electronic device 1000. Also, the artificial intelligence server 3000 may transfer the updated first electronic device management condition to the second electronic device 2000 if necessary.

Upon obtaining the updated electronic device management conditions, the electronic device management system repeats steps 605 to 513 so that the first electronic device 1000 can monitor and control the first electronic device based on the updated first electronic device management conditions. can Also, the second electronic device that has obtained the updated first electronic device management condition may provide the updated first electronic device management condition to the manager.

7 is a flowchart of a method for an electronic device to control a device in the electronic management system according to the embodiment disclosed in FIG. 5 .

In step 701, the electronic device 1000 may obtain user information and manager information of the electronic device.

In step 702, the electronic device 1000 may obtain the identified electronic device management conditions from the artificial intelligence model based on the information about the user and the manager of the electronic device.

When an artificial intelligence model including a server model is used, the electronic device 1000 transmits the obtained electronic device user information and electronic device manager information to the artificial intelligence server 3000, and from the artificial intelligence server 3000, information about the user of the electronic device and An electronic device management condition identified from the artificial intelligence model may be obtained based on the manager information.

In steps 703 to 705, the electronic device 1000 may monitor usage of the electronic device and control the electronic device.

According to an embodiment of the present disclosure, the electronic device 1000 monitors the user's use of the electronic device 1000 in real time based on the electronic device management condition acquired from the server (step 703), and the user's current electronic device 1000 usage state is It is determined whether the device management condition is satisfied (step 704), and if the user's current use state of the electronic device 1000 does not satisfy the electronic device management condition, the electronic device 1000 is controlled based on the electronic device management condition (step 705). can do.

According to an embodiment of the present disclosure, control of the electronic device of the electronic device 1000 may include not only direct control for the electronic device 1000 to change the use state of the electronic device, but also control for inducing a change in the use state of the electronic device to a user. there is.

In step 706, the electronic device 1000 may obtain updated electronic device management conditions.

The electronic device management condition may be updated based on an artificial intelligence model learned based on interaction information and action data between the user and the electronic device 1000 of the electronic device 1000 .

When an artificial intelligence model including a server model is used, the electronic device 1000 transmits interaction information and action data between the user and the electronic device 1000 to the artificial intelligence server 3000, and the artificial intelligence server 3000 transmits information between the user and the electronic device 1000. An updated electronic device management condition obtained from an artificial intelligence model learned based on the interaction information and action data may be obtained.

Thereafter, the electronic device 1000 that obtains the updated electronic device management conditions repeats steps 703 to 706 based on the updated electronic device management conditions, so that the electronic device 1000 monitors the electronic device based on the updated electronic device management conditions. and can be controlled.

Hereinafter, specific methods for determining electronic device management conditions will be described.

The electronic device usage time recommendation model according to an embodiment of the present disclosure outputs a recommended usage time suitable for the user's age when age information of the user is input. Age information of the user may include date of birth, age, and month age information. For example, age information for a child under the age of two may mean age information for a child older than 2 years old. The recommended use time may include a single use time of the electronic device, a daily use time of the electronic device, and a use time for each application.

For example, the electronic device usage time recommendation model may use the age of children aged 2 to 7 years old and average usage time per time as learning data. For the two factors, the correlation between usage time per month according to the age of the month is learned through methods such as linear regression, and the model acquired through learning can be used as a recommended usage time model.

The electronic device management system according to an embodiment of the present disclosure may additionally use an electronic device overdependency diagnosis model. The electronic device overdependence diagnostic model according to an embodiment of the present disclosure outputs whether the user is at risk of electronic device overdependence when user age information and user average usage time information are input. The user's average usage time may include a one-time average usage time and a daily average usage time.

For example, the electronic device overdependency diagnosis model may use the age of children aged 2 to 7 years, the average usage time per time, and smart device overdependency diagnosis data as learning data. This is a model learned using a linear support vector machine (SVM) for the corresponding data. It is linearly divided into two clusters in a flat space composed of monthly age and average usage time per time, and the one with more data diagnosed as overdependency, respectively. It is possible to infer whether the user is overdependent on a smart device by classifying into an overdependency risk group and a lesser one into a normal group.

When the administrator inputs the user's age and single use time, the electronic device overdependence diagnosis model outputs whether the user is at risk of smart device overdependence, and the electronic device 1000 displays it on the screen, so that the administrator can determine the user's smart device You can ask them to check whether they are at risk of overdependence.

The graph shown in FIG. 9 is the relationship between the age of a child and the average usage time of a smart device. If the user's usage time per month for each month is near the linear regression line of the recommended usage time model, it can be determined that there is no risk of overdependence. . On the other hand, if the user's monthly usage time for each month is located on the plane (upper plane) with more average usage time among the planes divided by the overdependency diagnosis model support vector, it can be determined as an overdependency risk group.

For example, when user A and user B are 36-month-old infants, the recommended usage time for one time may be determined to be 10 minutes based on the recommended usage time linear regression line. Also, it is assumed that user A's average usage time per time is 23 minutes and user B's average usage time per time is 10 minutes. User A's one-time usage time is located above the support vector of the overdependency diagnosis model for the 36-month-old, so user A can be determined as a risk group for overdependency. On the other hand, user B's one-time use time is located below the support vector of the overdependency diagnosis model for the 36-month-old, so it can be determined that user B is not in the general children's group, that is, not in the overdependency risk group.

According to an embodiment of the present disclosure, when the user's developmental characteristics are lower or higher than those of the same-month-old peer group as a result of the developmental examination of the user, the usage time recommendation model is used based on the user's actual developmental characteristics according to the developmental examination result. Can you recommend a time.

If the use of the electronic device is terminated immediately and forcibly when the use time of the electronic device is terminated, it may adversely affect the user's experience and cause the user to form an antipathy toward the electronic device management system as a whole. Accordingly, the electronic device management system according to an embodiment of the present disclosure may analyze the context of the electronic device use state and terminate the use of the electronic device based on the analyzed context.

Referring to FIG. 10 , an electronic device 1000 may include an electronic device use time input module 1001 , an electronic device use state context analysis module 1002 , an electronic device use time analysis module 1003 , and an electronic device use end module 1004 .

In particular, when the user is a child, since the child may not be accustomed to ending the use of the electronic device at a fixed time, the user is instructed to terminate the use of the electronic device based on the current state (context) of the media, content or game being used. By inducing, the child can stop using the electronic device without conflict with the guardian.

For example, it is assumed that a guardian who is a manager inputs 20 minutes of an electronic device usage time and a child who is a user watches a 22-minute video. The manager may set the electronic device use time to 20 minutes through the electronic device use time input module 1001 . The electronic device use time analysis module 1003 analyzes the user's electronic device use time and continuously checks whether 20 minutes of the electronic device use time input by the manager has elapsed.

For 20 minutes of the electronic device use time input by the administrator, the electronic device use state context analysis module 1002 may analyze the context of the user's electronic device use state in real time. In the disclosed embodiment, when the usage time of the electronic device ends, the electronic device usage state context analysis module 1002 may determine that about 2 minutes remain for the video being watched by the user. In this case, even if 20 minutes of the electronic device use time input by the administrator elapses, it may be preferable to allow the user to watch all remaining videos rather than immediately stop using the electronic device. Accordingly, the electronic device use state context analysis module 1002 may transmit context information indicating that an end point of the video being viewed by the user is near to the electronic device use time analysis module 1003 . The electronic device use time analysis module extends the electronic device use time according to the end time of the video, and the electronic device use end module 1004 controls the electronic device to end the use of the electronic device according to the extended electronic device use time.

According to an embodiment of the present disclosure, the electronic device usage state context analysis module 1002 monitors the remaining time of the video being watched by the user and the usable time of the electronic device, so that the remaining time of the video being watched exceeds the available time of the electronic device. If you do, you can adjust the playback speed (x speed) of the video. For example, if the remaining time of the video being watched is 10 minutes and the available time of the electronic device is 8 minutes, the playback speed of the video can be adjusted to 1.25 times so that the content playback can be terminated when the electronic device usage time ends. Alternatively, the electronic device use state context analysis module 1002 monitors the remaining time of the video being watched by the user and the available time of using the electronic device, and if the remaining time of the video being watched exceeds the available time of using the electronic device, the second half of the content being played part of can be deleted. For example, if the remaining time of the video being watched is 10 minutes and the available time of the electronic device is 8 minutes, 2 minutes of low importance among the remaining videos may be deleted so that content reproduction is terminated when the electronic device usage time ends. In this case, a portion to be deleted among the remaining videos may be determined based on a result of analyzing the context of the content. For example, by analyzing the use state context of a plurality of users for the corresponding content, a portion with a large number of fast-forward or skipped histories may be determined as a portion to be deleted.

According to an embodiment of the present disclosure, the electronic device usage time is included in the electronic device management condition obtained using the artificial intelligence model as described above, as well as the time directly input by the administrator through the electronic device usage time input module 1001. This may mean the time of using an electronic device.

According to an embodiment of the present disclosure, the extended use time of the electronic device may be determined within a predetermined threshold time set by an administrator. For example, if the extension threshold time set by the manager is 5 minutes and the remaining time of the video is 8 minutes, the electronic device 1000 may determine not to extend the electronic device use time.

According to an embodiment of the present disclosure, whether to extend the electronic device use time may be determined based on a ratio of a preset electronic device use time and a remaining time of a video, and the extension of the electronic device use time is temporary and will not be used later. It may operate to be reset to the set electronic device use time.

According to another embodiment, when the usage time of the electronic device set by the administrator is 20 minutes and the user plays an 18-minute video, the electronic device 1000 continues to play the video even if the electronic device usage time remains at the time the video playback is completed. The electronic device may be controlled to end use of the electronic device together.

According to another embodiment, when the user tries to play a new 10-minute video while the usage time of the electronic device set by the administrator is 3 minutes remaining, the electronic device 1000 provides a graphic/sound notification indicating that the video cannot be played. can be provided to the user.

11 is a diagram for explaining a harmful content monitoring model according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, the electronic device 1000 analyzes text and context included in content consumed by a user using video analysis, and if it is determined that the content is included as a result of the analysis, the electronic device 1000 may remove the objectionable content. there is.

For example, the electronic device 1000 may capture 1102 all contents 1101 displayed on the electronic device using a screen capture module. The electronic device 1000 may recognize text included in the captured screen using a text recognition model (1103), and determine harmfulness of the recognized text based on a harmful text database (1104). The electronic device 1000 performs a masking process (1105) on the text determined to be harmful using a masking module, and displays (1106) a screen on which the harmful text is masked on the electronic device. The masking process is to process only the part determined to be harmful content (for example, blur or mosaic), or to remove the entire part containing the harmful content from the content (for example, to delete or skip the corresponding time in the video), Methods of removing objects determined to be harmful content and combining them with the background may all be included, but are not limited thereto. When an object determined to be harmful content is removed and combined with the background, the user does not recognize that the harmful content is blocked, so the user's reluctance to the manager's management of the electronic device 1000 is reduced.

A harmful content monitoring model according to an embodiment of the present disclosure may be learned based on an evaluation (feedback) of an electronic device control result of an electronic device manager, and prediction by determining whether harmful content is included using the learned model. Accuracy can be improved. In addition, the harmful content monitoring model is updated by clustering user groups based on user criteria of similar inclinations or similar ages and updating the harmful content monitoring model based on evaluation statistics on the control result of the administrator's electronic device for each group of users. The prediction accuracy of can be further improved.

As described above, by using such a harmful text monitoring model, it is possible to prevent a situation in which a user is continuously exposed to harmful text because he/she does not recognize the harmful text, especially when the user is a child.

The distance of 1000 between the user and the electronic device may be measured using at least one of an ultrasonic sensor, an infrared sensor, a LIDAR (LIght Detection And Ranging) sensor, a RADAR (Radio Detection And Ranging) sensor, or an image sensor. .

The ultrasonic sensor measures the distance based on the time taken from emitting ultrasonic waves to receiving a reflected wave or the wavelength of the received reflected wave. Infrared sensors use electromagnetic waves with a longer wavelength than visible light, and infrared rays are safe because they have a longer wavelength and lower energy. A short-distance measurement sensor using infrared rays irradiates infrared rays from the sensor and measures the distance according to the intensity of the reflected infrared rays. The LiDAR sensor has a narrow detection range, but uses a laser with strong linearity, so the probability of distortion is low, so the error range is only a millimeter unit because the accuracy is higher than that of a camera or radar. In addition, lidar has a higher horizontal azimuth than cameras or radars, so it can accurately measure altitude and direction, has excellent ability to detect small objects, and can detect temperature or material distribution. The radar sensor may determine the existence, direction distance, and speed of a target by measuring a reflected wave returning after the irradiated electromagnetic wave hits the target. Because radio waves are used, sensitivity to the surrounding environment is low, allowing stable measurement. The image sensor typically has a camera and can photograph an object to identify its existence, location, and size.

When using an electronic device, when the distance between the user and the electronic device is too far or too short, it is necessary to control the electronic device based on the distance between the user and the electronic device. For example, if the distance between the user and the electronic device is too close, the electronic device 1000 may dim the screen or block the screen to induce the user to place the electronic device away from the eyes to protect the user's eyesight. there is. Conversely, when the distance between the user and the electronic device is too great, the electronic device 1000 may adjust (enlarge) the size of content displayed on the screen to automatically provide a screen of an appropriate size to the user.

Alternatively, the electronic device 1000 uses a video modeling method to play an animation in which a predetermined character moves the electronic device away when the distance between the user and the electronic device is too short, and the distance between the user and the electronic device is too short. In the case of being far away, an animation in which a predetermined character moves an electronic device closer to the viewer may be played.

Referring to FIG. 12 , an electronic device 1000 includes one or more sensors (a camera module 1005 and a proximity sensor module 1006) capable of measuring an inter-pupillary distance (IPD) of a user, an IPD analysis module 1007, and a display setting. module 1008, distance database 1009, display arbitration module 1010, and display magnification module 1011. According to an embodiment of the present disclosure, the camera module 1005 transfers the captured user face image to the IPD analysis module 1007; The proximity sensor module 1006 transfers the sensed value of proximity between the user and the electronic device to the IPD analysis module 1007 . The IPD analysis module 1007 may obtain the user's IPD based on the user's face image obtained from the camera module 1005 and the sensing value obtained from the proximity sensor module 1006 and may measure the distance between the user and the electronic device.

The IPD analysis module 1007 transfers the measured distance between the user and the electronic device to the display setting module 1008, and the display setting module 1008 may set a display control method based on the distance between the user and the electronic device. More specifically, when the distance between the user and the electronic device is excessively close to a predetermined threshold or less, the display setting module 1008 dims the screen or blocks the screen using the display arbitration module 1010 so that the user is not connected to the electronic device. The device can be directed away from the eye. Conversely, when the distance between the user and the electronic device is below a predetermined threshold or excessively far, the display setting module 1008 determines the distance between the user and the electronic device and the database for the display size according to the distance stored in the distance database 1009. A display magnification ratio may be determined, and the display magnification module 1011 may provide an enlarged screen to the user according to the determined magnification ratio.

If the electronic device 1000 is used at an excessively short distance, eye diseases such as myopia and strabismus may occur. Accordingly, according to an embodiment of the present disclosure, when the distance between the electronic device 1000 and the user of the electronic device is within a predetermined threshold distance, the electronic device 1000 may output an interaction recommending the user to locate the electronic device farther away. .

Referring to FIG. 13 , an electronic device 1000 according to an embodiment of the present disclosure that controls an electronic device based on a user's posture using the electronic device includes a camera module 1005, a pupil detection model 1012, a distance measurement module 1013, and an eye blink detection model. 1014, an eye blink period measurement module 1015, and a display 1016.

According to an embodiment of the present disclosure, the electronic device 1000 detects pupil location information from the user's face image captured from the camera module 1005 using the pupil detection model 1012 and detects pupil location information using the distance measurement module 1013. The distance between the user and the electronic device 1000 may be measured based on the location information of . In this case, as shown in FIG. 12 , the electronic device 1000 may measure the distance between the user and the electronic device 1000 by additionally using sensing data acquired using the proximity sensor module 1006 in addition to the camera module 1005 .

If the distance between the user and the electronic device is too close, the electronic device 1000 may dim the display 1016 or block the output of the display 1016 to induce the user to place the electronic device away from the user's eyes, and the distance between the user and the electronic device may decrease. If it is too far away, the size of the contents displayed on the display 1016 may be adjusted (enlarged) to automatically provide a screen of an appropriate size to the user.

According to an embodiment of the present disclosure, when the distance between the user and the electronic device is too short, the electronic device 1000 transmits a voice informing that a predetermined character is to locate the electronic device far away, or recommends that the electronic device be located far away. message or image can be displayed on the screen. Alternatively, if the distance between the user and the electronic device is too short, the electronic device 1000 may call the user's attention to the use of the electronic device by pausing playback of the currently playing content, displaying an icon, or vibrating. .

If the user's state of use of the electronic device violates the electronic device management conditions unintentionally, the user may be induced to voluntarily comply with the electronic device management conditions if the user's attention is aroused. The device 1000 may detect eye blinks using the eye blink detection model 1014 and measure the eye blink cycle using the eye blink period measuring module 1015 from the user's face image and video captured from the camera module 1005 .

The electronic device 1000 according to an embodiment of the present disclosure, when the measured eye-blink period of the electronic device user is longer than a predetermined threshold period, provides a sensory interaction recommending the user to close their eyes for a while and stop using the electronic device 1000. can be printed out. At this time, the electronic device 1000 identifies the user's eye blink pattern using a convolutional neural network-based vision model that detects eye blinks, and determines that the user is overfocused when the eye blink cycle is longer than the critical cycle. there is.

According to an embodiment of the present disclosure, when it is determined that the user is overinvolved, the electronic device 1000 controls the display screen to blink (blinking), displays a notification on the display screen that induces eye blinking, or blinks the eyes. A predetermined animation for exercise may be played to arouse the user's attention and induce eye blinking. Also, when the user is a child, the electronic device 1000 may temporarily stop using the electronic device, and then display an animation in which a character displayed on the screen blinks or hurts the eyes, or outputs a voice as sound.

According to an embodiment of the present disclosure, after the electronic device 1000 outputs an instruction recommending a posture correction to the user, if the posture is not corrected after a predetermined period of time, the display 1016 is darkened or the output of the display 1016 is blocked. Through this, it is possible to induce the user to correct the posture of using the electronic device step by step.

In the case of young children, development tests are conducted regularly to check the development status, and if the development status differs from the average of the same age group by more than a certain range, the guardian seeks more active intervention to supplement the development of the infant child.

In the developmental test or cognitive test, when a peculiarity is found through screening, it is common to conduct several close examinations, and the test is performed by visiting a hospital or testing institution directly.

In this conventional test method, there is a high possibility that the condition of the test subject on the day of the test, communication between the examinee and the examinee, and the atmosphere of the test site affect the test results. There is a problem in that it is difficult to obtain accurate test results.

In addition, when a test is performed by visiting an inspection institution, since as many tests as possible must be performed during one visit, if the test is conducted for a long time, fatigue of the inspected person may be accumulated and the test result may be contaminated.

In an environment in which the use of electronic devices such as smart phones is common and the age of use is gradually decreasing, when a developmental test is performed in a daily environment using an electronic device, the test subject may be in a more familiar and comfortable situation or not aware of what is being tested. It is inspected in the same state, so more stable and reliable test results can be obtained. In addition, various types of inspections in more diverse fields are possible by using the user's electronic device use history and use data as inspection data, rather than a question-and-answer type inspection method.

In particular, in the case of a user who essentially needs a cognitive/language development test but has difficulty in proceeding with the test (for example, when the user has a cognitive impairment, etc.) or a user who lacks the cost or time required for the development test, the embodiment of the present disclosure The developmental examination method according to can be used more effectively.

In addition, if necessary, non-face-to-face examinations may be conducted with the attending physician, counselor, or clinical psychologist through video. At this time, if the preference information of the test subject (electronic device user) is used, the test subject's psychological resistance to the test can be reduced. According to an embodiment of the present disclosure, a more flexible and flexible examination can be performed by constructing and displaying an animation of a predetermined character selected by a test subject on a screen while modulating and outputting an actual examiner's voice as the voice of the corresponding character in real time.

In the case of performing a developmental test or cognitive test through an electronic device used every day, even when an additional test is required, sufficient test results may be obtained by performing a small test every day instead of performing many tests at once. In addition, user preference information can be used to increase the liking for developmental/cognitive tests, and in the case of children, user participation can be improved by personalizing developmental test items adaptively to the user by using the usual preferred characters. .

In order to improve the degree of participation and reliability in the developmental/cognitive test, the developmental test system according to an embodiment of the present disclosure may provide a reward to the user according to the degree of participation in the test or the reliability of the test. For example, the developmental testing system according to an embodiment of the present disclosure may be a coin usable within the developmental testing system, an item applicable to a user character, or an external system when participating in the test or having a test reliability of a predetermined score or higher. can provide exchangeable items (eg, NFTs, etc.).

Referring to FIG. 14 , the developmental examination system according to an embodiment of the present disclosure may include a user, an electronic device, and a developmental examination server 4000 . The electronic device 1000 may include a language expression analysis module 1012 , a non-verbal expression analysis module 1013 , a usage history analysis module 1014 , and a development test result providing module 1015 . The development examination server 4000 may include a language development evaluation module 4001, a non-verbal development evaluation module 4002, a comprehensive development analysis module 4003, and a total user DB 4004. The development test server 4000 according to an embodiment of the present disclosure may be included in the artificial intelligence server 3000 for determining electronic device management conditions or may be implemented in a hardware-integrated form.

The language expression analysis module 1012 obtains a result of analyzing a language expression based on a speech of an electronic device user by using a conversation system. The non-verbal expression analysis module 1013 obtains a non-verbal expression analysis result based on the user's posture, expression, and face recognition.

The linguistic expression of the user of the electronic device may be obtained by analyzing speech received through a microphone provided in the electronic device 1000 using a conversation system. For example, the electronic device 1000 may output development test items through a speaker, obtain a user's voice response to the development test items through a microphone, and analyze the acquired voice. At this time, the development test items may be output after being modulated into the parent's voice or the user's preferred character's voice. Alternatively, if there are questions to be added in addition to the normalized developmental test questions, the electronic device 1000 may output the parent's voice input or modulate the text input into the parent's voice or the user's preferred character's voice and output it. In the method for managing the use of an electronic device according to the disclosure, as a method for recognizing a user's voice and interpreting an intention for a developmental test, a voice signal, which is an analog signal, is received through a voice capture module (eg, a microphone), , ASR (Automatic Speech Recognition) model can be used to convert speech into computer-readable text. The user's utterance intention may be obtained by interpreting the converted text using a natural language understanding (NLU) model. Here, the ASR model or NLU model may be an artificial intelligence model. The artificial intelligence model can be processed by an artificial intelligence processor designed with a hardware structure specialized for the processing of artificial intelligence models. AI models can be created through learning. Here, being made through learning means that a basic artificial intelligence model is learned using a plurality of learning data by a learning algorithm, so that a predefined action rule or artificial intelligence model set to perform a desired characteristic (or purpose) is created. means burden. An artificial intelligence model may be composed of a plurality of neural network layers. Each of the plurality of neural network layers has a plurality of weight values, and a neural network operation is performed through an operation between an operation result of a previous layer and a plurality of weight values.

Linguistic understanding is a technology that recognizes and applies/processes human language/text, and includes natural language processing, machine translation, dialog system, question answering, and voice recognition. /Includes Speech Recognition/Synthesis, etc.

The non-verbal expression of the user of the electronic device may be obtained by analyzing an image captured through a camera provided in the electronic device 1000 . For example, the electronic device 1000 may capture an image or video of the user through a camera, analyze the captured image or video, obtain the user's expression, and infer emotions.

According to an embodiment of the present disclosure, the electronic device 1000 may capture a motion picture of the user using a camera and determine the physical development of the user. For example, as a result of analyzing a video of a user's motion, when it is determined that the user's gross and fine muscle development is delayed compared to the standard for the corresponding age, the electronic device 1000 transmits the determination result through the electronic device 1000 or a manager device. can provide

In the method for managing the use of an electronic device according to the present disclosure, as a method for recognizing a user's non-verbal expression, user image data captured through a camera is used as input data for an artificial intelligence model, and an image or a face in an image Output data obtained by recognizing facial expressions may be obtained. AI models can be created through learning. Here, being made through learning means that a basic artificial intelligence model is learned using a plurality of learning data by a learning algorithm, so that a predefined action rule or artificial intelligence model set to perform a desired characteristic (or purpose) is created. means burden. An artificial intelligence model may be composed of a plurality of neural network layers. Each of the plurality of neural network layers has a plurality of weight values, and a neural network operation is performed through an operation between an operation result of a previous layer and a plurality of weight values.

Visual understanding is a technology that recognizes and processes objects as if they were human eyes, and includes object recognition, object tracking, image retrieval, human recognition, and scene recognition. , spatial understanding (3D Reconstruction/Localization), and image enhancement (Image Enhancement).

The language expression analysis module 1012 transmits the acquired language expression analysis result to the language development evaluation module 4001 of the development test server 4000, and the non-verbal expression analysis module 1013 transmits the obtained non-verbal expression analysis result to the non-verbal development test server 4000. Send to evaluation module 4002.

The usage history analysis module 1014 of the electronic device 1000 analyzes the usage history based on all of the user's electronic device usage history data, such as search records and viewing history, and transmits the analysis result to the comprehensive developmental analysis module 4003 of the development test server 4000. In addition, the language development evaluation module 4001 and the non-verbal development evaluation module 4002 transmit development evaluation results to the comprehensive development analysis module 4003, respectively.

The comprehensive developmental analysis module 4003 comprehensively analyzes the user's development based on the usage history analysis result obtained from the electronic device 1000 and the developmental evaluation result obtained from the

developmental evaluation modules

4001 and 4002, and analyzes the analysis result as total user data. It can be passed to base 4004 for storage. In addition, the comprehensive development analysis module 4003 may analyze the development of the user by referring to and comparing the development analysis results of other users of the same age.

The development test result providing module 1015 of the electronic device 1000 may obtain a development test result for the user from the user DB 4004 of the development test server 4000 and provide the user's development test result so that the administrator can confirm the result. For example, the development test result providing module 1015 may create a report on the user's developmental status, display it on a display screen, store it in a memory (not shown) of the electronic device 1000, or send it to a preset administrator's e-mail address. there is.

Referring to FIG. 15 , the electronic device 1000 includes a manager information acquisition module 1100, a user information acquisition module 1300, a usage information acquisition module 1600, and a display 1200. The usage information acquisition module 1600 includes a language expression analysis module 1012 and a non-verbal expression analysis. module 1013, usage history analysis module 1014.

The development test server 4000 may include a comprehensive development analysis module 4003 and a total user database 4004 , and the comprehensive development analysis module 4003 may include a language development evaluation module 4001 and a non-verbal development evaluation module 4002 .

In FIG. 15, a detailed description of contents overlapping with those of FIGS. 3 and 14 may be omitted.

The user information acquisition module 1300 acquires user information, and the user information may include user basic information, usage method information, and temperament and propensity information. The usage information acquisition module 1600 acquires usage information, and the usage information may include a result of analyzing a language expression, a result of analyzing a non-verbal expression, and a result of analyzing a usage history.

The language expression analysis module 1012 obtains a result of analyzing a language expression based on a speech of an electronic device user by using a conversation system. The non-verbal expression analysis module 1013 obtains a non-verbal expression analysis result based on the user's posture, expression, and face recognition. The usage history analysis module 1014 of the electronic device 1000 analyzes the usage history based on all of the user's electronic device usage history data, such as search history and viewing history.

The linguistic expression of the user of the electronic device may be obtained by analyzing speech received through a microphone provided in the electronic device 1000 using a conversation system. The non-verbal expression of the user of the electronic device may be obtained by analyzing an image captured through a camera provided in the electronic device 1000 .

The electronic device 1000 transmits user information acquired through the user information acquisition unit 1300 and usage information obtained through the usage information acquisition module 1600 to the developmental test server 4000 .

The comprehensive developmental analysis module 4003 of the developmental examination server 4000 may obtain a developmental examination result based on user information and usage information received from the electronic device 1000 . More specifically, the comprehensive development analysis module 4003 comprehensively analyzes the user's development based on the language development evaluation results obtained in the language development evaluation module 4001 and the non-verbal development evaluation results obtained in the non-verbal development evaluation module 4002. The result can be transferred to the entire user database 4004 for storage. In addition, the comprehensive development analysis module 4003 may analyze the development of the user by referring to and comparing the development analysis results of other users of the same age.

The developmental examination server 4000 transmits the user's developmental examination result obtained from the comprehensive developmental analysis module to the electronic device 1000, and the electronic device 1000 displays the received developmental examination result on the display 1200 to provide the developmental examination result to the manager or user. can

Referring to FIG. 16 , a language development test model according to an embodiment of the present disclosure may include a sentence vectorization model 1601, a morpheme analysis model 1602, a convolutional neural network model 1603, and a language development test model 1604.

The language development test model uses sentence vectors obtained by vectorizing speech data of sentences using a sentence vectorization model (eg, Gensim model) and speech data using a morphological analysis model to determine the language development level of parts of speech tagged sentences. Based on this, it is used as learning data.

Table 1 shows an example of utterance data.

[Table 1]

Table 2 shows sentences in which the speech data of Table 1 is tagged with parts of speech.

[Table 2]

Table 3 shows a training data set generated using the sentence vector (X_train) of the speech data in Table 1 and the language development level (Y_train) of the part-of-speech tagged sentence in Table 2.

[Table 3]

The convolutional neural network model 1604 is trained using a learning data set obtained using the sentence vectorization model 1601 and the morphological analysis model 1602, and a language development test model 1605 can be extracted. When the user's speech data is input, the extracted language development test model 1605 may output the user's language development level.

According to an embodiment of the present disclosure, a language development test model may be performed whenever a user starts using the electronic device 1000, and the electronic device 1000 may transmit a question for interactive interaction and request an answer from the user. . For example, the electronic device 1000 includes not only test-type questions for checking the user's language development status, but also information-gathering questions necessary for controlling the electronic device suitable for the user, such as the user's interest or preferred content, and simple interest-inducing. In addition to type questions, any questions that can be used to induce users to speak can be sent out.

A question may be input by a manager, and the electronic device 1000 may modulate the manager's voice input or text input into the voice of a character preferred by the user and output the modulated voice. For example, if there is something the parent manager wants to check about the child's institutional life (friendship relationship, accurate confirmation of abuse, etc.), or if they want to check the child's psychological state or a gift they want to receive, the parent manager inputs By modulating a question into the voice of a child's favorite character and outputting it, the child can answer without objection.

The electronic device 1000 may obtain an access right and function right consent for each function (module) of the electronic device, if necessary, before performing the development test.

In FIG. 17, descriptions of overlapping contents with those of FIGS. 14 to 16 may be omitted.

In step 1701, the electronic device 1000 acquires user information of the electronic device.

User information of the electronic device may include information about the user's name, age, temperament, and taste.

In step 1702, the electronic device 1000 obtains electronic device usage information of the electronic device user.

The electronic device usage information of the electronic device user may include a history of using the electronic device by the electronic device user. For example, the electronic device user's content use history, application use history, and shopping history may be included.

In step 1703, the electronic device 1000 obtains a development test result based on user information and usage information.

The electronic device 1000 may determine a question type based on information about the user's age. For example, if the user is a 5-year-old child, they may choose a closed-ended question type. Unlike closed-ended questions that can be answered using questions, open-ended questions that can be answered freely may not be appropriate for users with low intellectual levels or young children.

In addition, the electronic device 1000 selects a keyword (eg, the name of the user's favorite content or character name) to be used when performing a development test based on the user's temperament, taste information, and electronic device use information, and , the question can be determined. For example, if the user is a 5-year-old child and 'Tayo the Little Bus' is determined to be the most watched video in the content history, the electronic device 1000 selects #Tayo, #Rani, and #Rogi as the keywords of the question and , You can decide on a closed-ended multiple-choice question, “Who do you like more in XX, Tayo, Lani or Rogi?” When the age of the user increases, the electronic device 1000 may select an open-ended question or a multiple-choice question, and keywords and questions are determined based on the age or age of the user.

When a question for the development test is determined, the electronic device 1000 may output the determined question as sound through a speaker or display the determined question in text or graphics through a display.

When the user responds to a question of the electronic device 1000, the electronic device 1000 may acquire the user's speech through a microphone, analyze the obtained user speech, and perform a development test. For example, to the question of the electronic device 1000 “Who do you like more, Rani or Rogi in Tayo?”, if the user answers “I like Rani more”, the subject, predicate, and object are appropriately used It is possible to obtain a language development test result according to the user's age by determining whether or not he or she uses comparative degrees appropriately.

According to an embodiment of the present disclosure, the electronic device 1000 may transmit the acquired user information and device use information of the user to the development test server 4000 and obtain a development test result from the development test server 4000 . The development test server 4000 may perform a development test based on user information received from the electronic device 1000 and device usage information of the user.

In step 1704, the electronic device 1000 provides the obtained development test result.

The electronic device 1000 generates a graphic or document based on the obtained development test and provides it so that the administrator can check the user's development test result. The development test result may include a comparison result with other users in the peer group.

According to an embodiment of the present disclosure, in the case of a test item or question that is difficult to check during normal use or requires additional check because the user does not respond, the test can be performed through content that may be of interest to the user, such as a mini game. there is.

For example, the electronic device 1000 lets the user hear the sound of a dog barking 'wow!' and outputs a question, "Hey XX, what is this sound?" can be checked.

Alternatively, the electronic device 1000 may show pictures of various fruits to the user and output a question, "Hey XX, which fruit do you like the most?" to check whether the user can express what he or she prefers. .

Alternatively, the electronic device 1000 may show pictures of two animals of different sizes to the user, and output a question, "XX, which of the two is taller?" to confirm whether the user can use the comparative degree.

According to an embodiment of the present disclosure, the electronic device 1000 may directly present a question related to the user's cognitive/developmental status to the administrator to check the developmental status. For example, the electronic device 1000 displays the question “Can you use 'negative words' such as not-, not-, no-, and can't-?” can be checked.

Referring to FIG. 19 , language development test results according to an embodiment of the present disclosure include a comprehensive developmental analysis result, an interactive interactive question and user's answer for the developmental test, and language development obtained based on the user's answer. Can include inspection results and comments.

The first language development test result screen, as a result of comprehensive development analysis, may display which area of development test was performed, how the test result of each area was derived, and recommended responses to the test result manager.

If an additional test or a more precise result is required as a result of the user's cognitive/developmental test, the response recommended to the manager may include a phrase recommending a detailed test.

The second language development test result screen is an example of an interactive interactive question and a user's answer for the language development test. The language development test according to an embodiment of the present disclosure may obtain natural speech data of the user on a daily basis through daily questions and evaluate language development when the electronic device 1000 starts to be used.

Since the user may not be able to read text if the user is an infant, the electronic device 100 outputs the question as a voice using a speaker, obtains the user's answer using a microphone, and uses the acquired user speech data as a language development test model. level of language development.

The third language development test result screen shows the user's language development test result obtained based on the user's speech data. The language development test may be performed on a daily basis based on user's speech data obtained on a daily basis, and the result may be displayed as a graph. At this time, the user's language development test result may include comparison with the average of other children of the same age.

In this way, by providing the basis for the number of inspections, inspection history, and inspection results, the reliability of the results can be increased, and the manager can more easily identify the part that the user needs to supplement.

As shown in FIG. 20 , an electronic device 1000 according to an embodiment of the present disclosure may include a processor 1700, a memory 1800, and a communication unit 1900. However, not all illustrated components are essential components. The electronic device 1000 may be implemented with more components than those illustrated, or the electronic device 1000 may be implemented with fewer components.

Hereinafter, the above components are examined in turn.

The processor 1700 typically controls overall operations of the electronic device 1000 . For example, the processor 1700 executes programs stored in the memory 1900 to overall control the manager information acquisition module 1100, the user information acquisition module 1300, the user-administrator type determination module, the usage information acquisition module 1700, and the display 1200. can

According to one embodiment of the present disclosure, the processor 1700 may include an artificial intelligence (AI) processor for generating a learning network model, but is not limited thereto. According to an embodiment of the present disclosure, the AI processor may be implemented as a separate chip from the processor 1700. According to an embodiment of the present disclosure, the AI processor may be a general-purpose chip.

According to an embodiment of the present disclosure, the processor 1700 may obtain user information and manager information of the electronic device, determine a user-manager type based on the acquired information, and determine an artificial intelligence based on the determined user-manager type. Electronic device management conditions obtained from the model may be acquired.

An artificial intelligence model according to an embodiment of the present disclosure may be an on-device model independently operated inside an electronic device or a server model operated in a server outside the electronic device. Alternatively, the artificial intelligence model according to an embodiment of the present disclosure may be a combination of an on-device model and a server model.

According to an embodiment of the present disclosure, the processor 1700 may control the electronic device based on the acquired electronic device management condition.

According to an embodiment of the present disclosure, the processor 1700 may obtain user information of the electronic device and information about the user's use of the electronic device, and may obtain a development test result based on the obtained user information and usage information. The development test may include a language development test and a non-verbal development test, and may be performed in the electronic device 1000 or in a separate development test server 4000 .

The memory 1800 stores various types of information necessary for the processor 1700 to control the electronic device 1000 .

According to an embodiment, user information, manager information, and user-manager type information may be stored in the memory 1800 . Also, the memory 1800 may store user electronic device use information and electronic device control history information of the electronic device 1000 . When an on-device artificial intelligence model is used to determine electronic device management conditions, the memory 1800 may store various data and training data for generating an artificial intelligence model.

The memory 1800 may store programs for processing and control of the processor 1700 and may store input/output data.

The memory 30 is a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (eg SD or XD memory, etc.), RAM (RAM, Random Access Memory) SRAM (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk , an optical disk, and at least one type of storage medium. Programs stored in the memory 1800 can be classified into a plurality of modules according to their functions.

The communication unit 1900 may include one or more components enabling communication between the electronic device 1000 and the artificial intelligence server 3000, the electronic device 1000 and the development test server 4000, or the electronic device 1000 and the manager device 2000. For example, the communication unit 1900 may include a short range communication unit (not shown).

The short-range wireless communication unit includes a Bluetooth communication unit, a Bluetooth Low Energy (BLE) communication unit, a Near Field Communication unit (WLAN) communication unit, a Zigbee communication unit, an infrared (IrDA) It may include a Data Association (Data Association) communication unit, a Wi-Fi Direct (WFD) communication unit, an ultra wideband (UWB) communication unit, an Ant+ communication unit, etc., but is not limited thereto.

The communication unit 1900 may obtain software for controlling the electronic device 1000 from a server device (not shown).

For example, when firmware for operating each module of the processor 1700 is updated, the communication unit 1700 may download the updated firmware from a server device and transmit the updated firmware to the processor 1700 . Alternatively, when a function performed by the processor 1700 is added, the communication unit 1900 may download software related to the added function from the server device and deliver it to the processor 1700.

The device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-temporary storage medium' only means that it is a tangible device and does not contain signals (e.g., electromagnetic waves), and this term refers to the case where data is stored semi-permanently in the storage medium and temporary It does not discriminate if it is saved as . For example, a 'non-temporary storage medium' may include a buffer in which data is temporarily stored.

According to one embodiment, the method according to various embodiments disclosed in this document may be provided by being included in a computer program product. Computer program products may be traded between sellers and buyers as commodities. A computer program product is distributed in the form of a machine-readable storage medium (eg compact disc read only memory (CD-ROM)), distributed as a web plug-in, or via an application store or on two user devices (eg compact disc read only memory (CD-ROM)). : It can be distributed (e.g., downloaded or uploaded) online, directly between smartphones. In the case of online distribution, at least a part of a computer program product (eg, a downloadable app) is stored on a device-readable storage medium, such as a manufacturer's server, an application store's server, or a relay server's memory. It can be temporarily stored or created temporarily.

Claims

In the method for managing the use of the electronic device 1000,

obtaining (401) information about a user 1500 of the electronic device 1000 and information about a manager 2500 of the electronic device;

acquiring (402) a management condition of the electronic device identified from an artificial intelligence model based on the obtained information about the user and the information about the manager; and

Controlling (403) the electronic device based on the acquired management criterion.
According to claim 1,

The management condition includes at least one of a management condition for the user's electronic device use time, a management condition for the contents of use, and a management condition for the user's posture.
According to claim 2,

The management condition for the content of use includes determining whether the content displayed on the electronic device is harmful.
According to claim 2,

The management condition for the use posture includes at least one of determination of the posture of the user, a distance between the electronic device and the user, and a blink cycle of the user.
The method of claim 1, wherein the method,

determining a temperament of the user and a parenting style of the manager based on the information about the user and the information about the manager; and

Further comprising determining a type between the user and the manager based on the temperament of the user and the parenting style of the manager;

The method of claim 1 , wherein the management condition of the electronic device is identified based on a type between the user and the manager.
According to claim 1,

At least one of the information on the user and the information on the manager is obtained from an external device.
The method of claim 1, wherein the method,

Acquiring an updated management condition identified by using an artificial intelligence model learned based on the electronic device control history.
In the electronic device 1000,

communication unit 1900;

a storage unit 1800 for storing a program including at least one instruction; and

including at least one processor 1700 executing at least one instruction stored in the storage unit;

By the at least one processor 1700 executing the at least one command,

Obtaining (401) information about a user 1500 of the electronic device 1000 and information about a manager 2500 of the electronic device,

Obtaining management conditions of the electronic device obtained from an artificial intelligence model based on the obtained information about the user and information about the manager (402);

Controlling (403) the electronic device based on the obtained management criterion.
According to claim 8,

The management condition includes at least one of a management condition for the user's electronic device use time, a management condition for the content of use, and a management condition for the user's posture.
According to claim 9,

The management condition for the content of use includes determining whether the content displayed on the electronic device is harmful.
According to claim 9,

The management condition for the use posture includes at least one of a distance between the electronic device and the user, and a determination of an eye blink cycle of the user.
The method of claim 8, wherein the at least one processor,

Based on the information about the user and the information about the manager, determine the type between the user and the manager;

The management condition of the electronic device is identified based on a type between the user and the manager.
According to claim 9,

At least one of the information on the user and the information on the manager is obtained from an external device.
The method of claim 9, wherein the at least one processor,

Acquiring an updated management condition identified by using an artificial intelligence model learned based on the electronic device control history.
A computer-readable recording medium on which a program for performing the method of claim 1 is recorded on a computer.