system

Abstract

The system according to this embodiment aims to comprehensively manage the owner's safety and respond quickly in emergencies. [Solution] The system according to the embodiment comprises a schedule management unit, a crisis detection unit, a notification unit, a fraud detection unit and a crime detection unit, an alert transmission unit, and a character setting unit. The schedule management unit manages the owner's schedule. The crisis detection unit detects the owner's crisis. The notification unit makes a notification based on the crisis detected by the crisis detection unit. The fraud detection unit and crime detection unit detect fraud and crime. The alert transmission unit sends an alert to the guardian based on the results detected by the fraud detection unit and crime detection unit. The character setting unit sets a friendly character.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the prior art, there was a problem that a system for comprehensively managing the safety of the owner and quickly responding in an emergency was not sufficiently provided.

[0005] The system according to the embodiment aims to comprehensively manage the safety of the owner and quickly respond in an emergency.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a schedule management unit, a crisis detection unit, a notification unit, a fraud detection unit and a crime detection unit, an alert transmission unit, and a character setting unit. The schedule management unit manages the owner's schedule. The crisis detection unit detects the owner's crisis. The notification unit makes a notification based on the crisis detected by the crisis detection unit. The fraud detection unit and crime detection unit detect fraud and crime. The alert transmission unit sends an alert to the guardian based on the results detected by the fraud detection unit and crime detection unit. The character setting unit sets a friendly character. [Effects of the Invention]

[0007] The system according to this embodiment comprehensively manages the owner's safety and can respond quickly in emergencies. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9]This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The monitoring service system according to an embodiment of the present invention is a system that uses an AI assistant to support the owner's daily life and, in emergencies, makes a decision to contact the police or fire department on its own. This monitoring service system supports the owner's daily life by managing the owner's schedule, searching for information, and offering advice on problems. Furthermore, it detects when the owner is in danger and makes a decision to contact the police or fire department on its own. For example, it automatically detects kidnapping, sudden illness, or traffic accidents and makes an emergency call. It also sends an alert to the guardian when it detects fraud or becoming a victim (or perpetrator) of a crime. By giving it a friendly character, it aims to become a presence that helps people's lives in a way similar to a companion or partner. For example, when the owner enters an appointment, the monitoring service system registers that appointment in the calendar and sets a reminder. Also, when the owner searches for necessary information, the monitoring service system collects information from the internet and provides it to the owner. Furthermore, when the owner seeks advice on problems, the monitoring service system provides appropriate advice. Next, the monitoring service system detects when the owner is in danger. For example, if the owner suddenly falls ill and collapses, the monitoring service system will detect the owner's abnormal movements and make an emergency call. Also, if the owner is kidnapped, the monitoring service system will track the owner's location and notify the police. Furthermore, if the owner is involved in a traffic accident, the monitoring service system will detect the accident and notify the fire department. The monitoring service system can also detect fraud and crime (both victim and perpetrator). For example, if the owner receives a fraudulent phone call, the monitoring service system will analyze the content and, if it determines that it is potentially fraudulent, will send an alert to the guardian. Furthermore, if the owner becomes a victim of a crime, the monitoring service system will detect the situation and send an alert to the guardian. Finally, the monitoring service system can be given a friendly character. For example, the owner can set the appearance and voice of their favorite character. This makes the monitoring service system a companion or partner that helps people's lives. In this way, the monitoring service system can support the owner's daily life and respond quickly and appropriately in emergencies.

[0029] The monitoring service system according to this embodiment comprises a schedule management unit, a crisis detection unit, a notification unit, a fraud detection unit and a crime detection unit, an alert transmission unit, and a character setting unit. The schedule management unit manages the owner's schedule. When the owner enters an appointment, the schedule management unit registers the appointment in the calendar and sets a reminder. For example, if the owner enters a meeting appointment, the schedule management unit registers the appointment in the calendar and sets a reminder before the meeting. The schedule management unit can also register an event appointment in the calendar and set a reminder before the event if the owner enters an event appointment. Furthermore, the schedule management unit can also register a task appointment in the calendar and set a reminder before the task if the owner enters a task appointment. The crisis detection unit detects when the owner is in danger. The crisis detection unit detects that the owner's movements are abnormal and makes an emergency call. For example, if the owner collapses due to a sudden illness, the crisis detection unit detects that their movements are abnormal and makes an emergency call. Furthermore, the crisis detection unit can track the owner's location and notify the police if the owner is kidnapped. Additionally, the crisis detection unit can detect the situation if the owner is involved in a traffic accident and notify the fire department. The reporting unit makes a report based on the crisis detected by the crisis detection unit. The reporting unit tracks the owner's location and notifies the police. For example, if the owner is kidnapped, the reporting unit tracks their location and notifies the police. Also, if the owner collapses due to sudden illness, the reporting unit can track their location and notify the fire department. Furthermore, if the owner is involved in a traffic accident, the reporting unit can track their location and notify the fire department. The fraud detection unit and crime detection unit detect fraud and crime. The fraud detection unit analyzes the content of fraudulent phone calls and sends an alert to the guardian if it determines there is a possibility of fraud. For example, if the owner receives a fraudulent phone call, the fraud detection unit analyzes its content and sends an alert to the guardian if it determines there is a possibility of fraud. Furthermore, the fraud detection unit can analyze the content of fraudulent emails received by the owner and, if it determines that they are potentially fraudulent, can send an alert to the guardian.Furthermore, the fraud detection unit can analyze the content of a message if the owner receives a fraudulent message, and if it determines that it is potentially fraudulent, it can send an alert to the guardian. The crime detection unit can detect if the owner is a victim of a crime and send an alert to the guardian. For example, if the owner is assaulted, the crime detection unit can detect the situation and send an alert to the guardian. The crime detection unit can also detect if the owner is a victim of theft and send an alert to the guardian. Furthermore, if the owner is a victim of fraud, the crime detection unit can detect the situation and send an alert to the guardian. The alert transmission unit sends alerts to the guardian based on the results detected by the fraud detection unit and the crime detection unit. For example, if the fraud detection unit determines that it is potentially fraudulent, the alert transmission unit will send an alert to the guardian. Furthermore, if the crime detection unit detects that the owner has been a victim of a crime, the alert transmission unit can send an alert to the guardian. Furthermore, the alert transmission unit can also send alerts to guardians based on the results detected by the fraud detection unit and the crime detection unit. The character setting unit allows for the creation of a friendly character. The character setting unit allows the user to set the appearance and voice of their favorite character. For example, the character setting unit can set the appearance and voice of the user's favorite anime character. It can also set the appearance and voice of the user's favorite game character. Furthermore, it can also set the appearance and voice of the user's favorite movie character. As a result, the monitoring service system according to this embodiment can support the user's daily life and respond quickly and appropriately in emergencies.

[0030] The Schedule Management Unit manages the owner's schedule. When the owner enters an appointment, the Schedule Management Unit registers the appointment in the calendar and sets a reminder. For example, if the owner enters a meeting appointment, the Schedule Management Unit registers the appointment in the calendar and sets a reminder before the meeting. The Schedule Management Unit can also register an event appointment in the calendar and set a reminder before the event if the owner enters an event appointment. Furthermore, if the owner enters a task appointment, the Schedule Management Unit can register that task in the calendar and set a reminder before the task is completed. To efficiently manage the owner's schedule, the Schedule Management Unit can synchronize across multiple devices. For example, appointments entered by the owner on their smartphone are automatically reflected on their PC and tablet. This allows the owner to check their latest schedule from any device. The Schedule Management Unit can also analyze the owner's past schedule data and find patterns. For example, if the owner tends to schedule meetings on a specific day of the week, the Schedule Management Unit can recognize this pattern and automatically suggest the next meeting date. Furthermore, the schedule management unit can provide optimal time management advice based on the owner's schedule. For example, if the owner has a busy schedule, the schedule management unit can suggest break times and support the owner's health management. In this way, the schedule management unit can efficiently manage the owner's schedule and improve the quality of daily life.

[0031] The crisis detection unit detects when the owner is in danger. It detects abnormal movements of the owner and initiates an emergency call. For example, if the owner collapses due to sudden illness, the crisis detection unit will detect the abnormal movements and initiate an emergency call. Furthermore, if the owner is kidnapped, the crisis detection unit can track their location and notify the police. Additionally, if the owner is involved in a traffic accident, the crisis detection unit can detect the situation and notify the fire department. The crisis detection unit utilizes acceleration sensors and gyroscopes to monitor the owner's movements in real time. This allows for immediate detection of abnormalities if the owner's movements exhibit an unusual pattern. For example, if the owner suddenly collapses, the acceleration sensor will detect the sudden movement, and the crisis detection unit will recognize the abnormality. The crisis detection unit can also monitor the owner's biometric information, such as heart rate and body temperature. This allows for a rapid response in the event of a sudden change in the owner's health. For example, if the owner's heart rate suddenly increases, the pinch detection unit will detect the anomaly and initiate an emergency call. Furthermore, the pinch detection unit can constantly track the owner's location and detect abnormal movement patterns. For instance, if the owner deviates significantly from their normal range of activity, the pinch detection unit will recognize the anomaly and notify the police. This ensures the owner's safety and allows for a swift and appropriate response in emergencies.

[0032] The reporting unit makes an emergency call based on an emergency detected by the emergency detection unit. The reporting unit tracks the owner's location and notifies the police. For example, if the owner is kidnapped, the reporting unit tracks their location and notifies the police. The reporting unit can also track the owner's location and notify the fire department if the owner collapses due to sudden illness. Furthermore, if the owner is involved in a traffic accident, the reporting unit can track their location and notify the fire department. The reporting unit uses GPS technology to accurately track the owner's location. This allows the unit to know the owner's current location in real time and respond quickly in emergencies. For example, if the owner is kidnapped, the reporting unit continuously tracks the owner's location and provides it to the police. In addition to the owner's location, the reporting unit can also report the owner's health status and surrounding environment. For example, if the owner collapses due to sudden illness, the reporting unit provides biometric information such as the owner's heart rate and body temperature to the fire department to support a rapid response. Furthermore, the reporting unit can calculate the optimal rescue route based on the owner's location information and provide it to the rescue team. This allows the reporting unit to ensure the owner's safety and respond quickly and appropriately in emergencies.

[0033] The fraud detection unit and crime detection unit detect fraud and crime. The fraud detection unit analyzes the content of fraudulent phone calls and sends an alert to the guardian if it determines that there is a possibility of fraud. For example, if the owner receives a fraudulent phone call, the fraud detection unit analyzes the content and sends an alert to the guardian if it determines that there is a possibility of fraud. The fraud detection unit can also analyze the content of fraudulent emails received by the owner and send an alert to the guardian if it determines that there is a possibility of fraud. Furthermore, if the owner receives a fraudulent message, the fraud detection unit can analyze the content and send an alert to the guardian if it determines that there is a possibility of fraud. The crime detection unit detects when the owner becomes a victim of a crime and sends an alert to the guardian. For example, if the owner is assaulted, the crime detection unit detects the situation and sends an alert to the guardian. The crime detection unit can also detect when the owner is a victim of theft and send an alert to the guardian. Furthermore, the crime detection unit can also detect if the owner has been a victim of fraud and send an alert to the guardian. The fraud detection unit uses natural language processing technology to analyze the content of phone calls, emails, and messages received by the owner. This allows it to quickly detect potentially fraudulent content and send an alert to the guardian. For example, the fraud detection unit analyzes the audio of phone calls received by the owner to detect potentially fraudulent keywords and phrases. It also analyzes the text of emails and messages received by the owner to detect potentially fraudulent content. The crime detection unit uses cameras and sensors to monitor the owner's behavior and surrounding environment and detect abnormal situations. This allows it to quickly detect if the owner has been a victim of crime and send an alert to the guardian. For example, if the owner is assaulted, the crime detection unit can detect the situation with a camera and send an alert to the guardian. It can also detect if the owner is a victim of theft with a sensor and send an alert to the guardian. This allows the fraud detection unit and crime detection unit to ensure the owner's safety and take swift and appropriate action.

[0034] The alert transmission unit sends alerts to parents based on the results detected by the fraud detection unit and the crime detection unit. For example, the alert transmission unit sends an alert to parents if the fraud detection unit determines there is a possibility of fraud. The alert transmission unit can also send an alert to parents if the crime detection unit detects that a crime has occurred. Furthermore, the alert transmission unit can send alerts to parents based on the results detected by the fraud detection unit and the crime detection unit. The alert transmission unit utilizes multiple communication methods to quickly and reliably send alerts to parents. For example, the alert transmission unit uses the notification function of smartphones to send alerts to parents. It can also send alerts to parents via email or SMS. Furthermore, the alert transmission unit can send alerts via voice calls. This allows the alert transmission unit to quickly and reliably send alerts to parents and ensure the safety of the owner. The alert transmission unit also provides detailed information in its alerts to enable parents to respond quickly. For example, the alert system notifies parents of the details and how to deal with a potential scam. It also notifies parents of the details and how to deal with a crime if it is detected. This allows the alert system to provide parents with timely and appropriate information, ensuring the safety of the owner.

[0035] The character setting section allows users to create approachable characters. The character setting section allows users to set the appearance and voice of their favorite characters. For example, the character setting section allows users to set the appearance and voice of their favorite anime character. It also allows users to set the appearance and voice of their favorite game character. Furthermore, it allows users to set the appearance and voice of their favorite movie character. The character setting section provides a rich character library to help users create approachable characters. This allows users to select and set characters according to their preferences. For example, the character setting section offers characters from various genres, such as anime characters, game characters, and movie characters. The character setting section also allows users to customize the character's appearance and voice. For example, users can freely change the character's hairstyle, clothing, and voice tone. Furthermore, the character setting section allows users to set the character's movements and expressions. This allows users to create their own original characters and create an approachable environment. The character setting section also allows users to set the character's personality and speaking style according to their preferences. For example, if the owner prefers a lively character, they can set the character's personality and way of speaking to be lively. This allows the character setting unit to create a character that the owner finds approachable and that can support their daily life in a fun way.

[0036] The schedule management unit can register appointments entered by the user into the calendar and set reminders. For example, if the user enters a meeting, the schedule management unit can register the appointment into the calendar and set a reminder before the meeting. The schedule management unit can also register events entered by the user into the calendar and set reminders before the event. Furthermore, if the user enters a task, the schedule management unit can register that task into the calendar and set a reminder before the task. This allows for efficient management of the user's schedule and prevents forgetting appointments by setting reminders. Some or all of the above processes in the schedule management unit may be performed using AI, for example, or not using AI. For example, the schedule management unit can input the appointments entered by the user into the AI, which can then register them into the calendar and set reminders.

[0037] The crisis detection unit can detect abnormal movements of the owner and initiate an emergency call. For example, if the owner collapses due to a sudden illness, the crisis detection unit can detect the abnormal movements and initiate an emergency call. Furthermore, if the owner is kidnapped, the crisis detection unit can track their location and notify the police. Additionally, if the owner is involved in a traffic accident, the crisis detection unit can detect the situation and notify the fire department. This allows for a rapid response by detecting abnormal movements of the owner and initiating an emergency call. Some or all of the above-described processes in the crisis detection unit may be performed using AI, or without AI. For example, the crisis detection unit can input data on the owner's movements into an AI, which can then detect the abnormality and initiate an emergency call.

[0038] The reporting unit can track the owner's location and report it to the police. For example, if the owner is kidnapped, the reporting unit can track their location and report it to the police. Furthermore, if the owner collapses due to a sudden illness, the reporting unit can track their location and report it to the fire department. In addition, if the owner is involved in a traffic accident, the reporting unit can track their location and report it to the fire department. This allows for a swift response by tracking the owner's location and reporting it to the police. Some or all of the above processes in the reporting unit may be performed using AI, or not. For example, the reporting unit can input the owner's location information into an AI, which can then select a recipient and make the report.

[0039] The fraud detection unit can analyze the content of fraudulent phone calls and, if it determines that there is a possibility of fraud, can send an alert to the guardian. For example, if the owner receives a fraudulent phone call, the fraud detection unit can analyze its content and, if it determines that there is a possibility of fraud, send an alert to the guardian. The fraud detection unit can also analyze the content of fraudulent emails received by the owner and, if it determines that there is a possibility of fraud, send an alert to the guardian. Furthermore, if the owner receives a fraudulent message, the fraud detection unit can analyze its content and, if it determines that there is a possibility of fraud, send an alert to the guardian. In this way, by analyzing the content of fraudulent phone calls and sending alerts to guardians if it determines that there is a possibility of fraud, fraud can be prevented. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the content of a fraudulent phone call into an AI, which can determine the possibility of fraud and send an alert to the guardian.

[0040] The crime detection unit can detect if the owner has been a victim of a crime and send an alert to the guardian. For example, if the owner has been assaulted, the crime detection unit can detect the situation and send an alert to the guardian. It can also detect if the owner has been a victim of theft and send an alert to the guardian. Furthermore, if the owner has been a victim of fraud, the crime detection unit can detect the situation and send an alert to the guardian. This allows for a swift response when the owner is a victim of a crime by detecting the situation and sending an alert to the guardian. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or not using AI. For example, the crime detection unit can input the circumstances of the crime into the AI, which can detect the crime and send an alert to the guardian.

[0041] The character setting unit allows the owner to set the appearance and voice of their favorite character. For example, the character setting unit can set the appearance and voice of the owner's favorite anime character. It can also set the appearance and voice of the owner's favorite game character. Furthermore, it can also set the appearance and voice of the owner's favorite movie character. This allows for the provision of a more approachable character by allowing the owner to set the appearance and voice of their favorite character. Some or all of the above processing in the character setting unit may be performed using AI, for example, or not. For example, the character setting unit can input the appearance and voice of the character chosen by the owner into the AI, and the AI ​​can perform the settings.

[0042] The schedule management unit can analyze the owner's past schedule history and propose the optimal schedule. For example, the schedule management unit can propose the next appointment based on the owner's frequently performed past appointments. It can also propose the optimal break times based on the owner's past schedule. Furthermore, the schedule management unit can analyze the owner's past schedule and propose an efficient schedule. In this way, it is possible to propose the optimal schedule by analyzing the owner's past schedule history. Some or all of the above processes in the schedule management unit may be performed using AI, for example, or not using AI. For example, the schedule management unit can input the owner's past schedule data into AI, and the AI ​​can propose the optimal schedule.

[0043] The schedule management unit can automatically adjust schedule priorities based on the owner's current activity status. For example, if the owner is currently busy, the schedule management unit will prioritize notifying them of important appointments. It can also delay reminder notifications if the owner is currently relaxing. Furthermore, it can refrain from sending reminder notifications if the owner is currently traveling. This enables efficient schedule management by automatically adjusting schedule priorities based on the owner's current activity status. Some or all of the above processes in the schedule management unit may be performed using AI, for example, or without AI. For example, the schedule management unit can input the owner's current activity data into the AI, which can then automatically adjust schedule priorities.

[0044] The schedule management unit can suggest local events related to the schedule, taking into account the owner's geographical location. For example, if the owner is in a specific region, the schedule management unit can suggest events held in that region. Furthermore, if the owner is traveling, the schedule management unit can suggest tourist attractions at their travel destination. Additionally, if the owner is on a business trip, the schedule management unit can suggest business events at their destination. This makes it possible to suggest relevant local events by considering the owner's geographical location. Some or all of the above processing in the schedule management unit may be performed using AI, for example, or without AI. For example, the schedule management unit can input the owner's geographical location into an AI, which can then suggest local events.

[0045] The schedule management unit can analyze the owner's social media activity and add relevant events and appointments to the schedule. For example, the schedule management unit can add events the owner plans to attend as posted on social media. It can also suggest events the owner has shown interest in as posted on social media. Furthermore, the schedule management unit can add events that the owner's friends will be attending as well. This makes it possible to add relevant events and appointments by analyzing the owner's social media activity. Some or all of the above processes in the schedule management unit may be performed using AI, for example, or not. For example, the schedule management unit can input the owner's social media data into an AI, which can then add relevant events and appointments to the schedule.

[0046] The pinch detection unit can analyze the owner's past behavior patterns to improve the accuracy of detecting abnormal behavior. For example, the pinch detection unit optimizes the algorithm for detecting abnormal behavior based on the owner's past behavior patterns. The pinch detection unit can also detect early signs of abnormal behavior from the owner's past behavior patterns. Furthermore, the pinch detection unit can analyze the owner's past behavior patterns to improve the accuracy of detecting abnormal behavior. As a result, the accuracy of detecting abnormal behavior is improved by analyzing the owner's past behavior patterns. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or without AI. For example, the pinch detection unit can input the owner's past behavior data into AI, which can then improve the accuracy of detecting abnormal behavior.

[0047] The pinch detection unit can monitor the owner's biometric information (heart rate, body temperature, etc.) in real time and detect abnormalities. For example, the pinch detection unit can detect a pinch if the owner's heart rate is abnormally high. It can also detect a pinch if the owner's body temperature is abnormally low. Furthermore, the pinch detection unit can monitor the owner's biometric information in real time and detect abnormalities. This enables early detection of abnormalities by monitoring the owner's biometric information in real time. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or without AI. For example, the pinch detection unit can input the owner's biometric information into AI, which can then detect abnormalities.

[0048] The pinch detection unit can prioritize the detection of abnormal behavior in specific areas by considering the owner's geographical location information. For example, if the owner is in a dangerous area, the pinch detection unit will prioritize detecting abnormal behavior. The pinch detection unit can also lower the sensitivity of abnormal behavior detection when the owner is at home. Furthermore, the pinch detection unit can also prioritize the detection of abnormal behavior when the owner is in a public place. This makes it possible to prioritize the detection of abnormal behavior in specific areas by considering the owner's geographical location information. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or without AI. For example, the pinch detection unit can input the owner's geographical location information into the AI, which can then prioritize the detection of abnormal behavior.

[0049] The pinch detection unit can analyze the owner's social media activity and detect signs of abnormal behavior early. For example, the pinch detection unit detects a pinch if the owner makes an unusual post on social media. The pinch detection unit can also detect a pinch if the owner exhibits unusual behavior on social media. Furthermore, the pinch detection unit can analyze the owner's social media activity and detect signs of abnormal behavior early. This allows for the early detection of signs of abnormal behavior by analyzing the owner's social media activity. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or without AI. For example, the pinch detection unit can input the owner's social media data into AI, which can then detect signs of abnormal behavior early.

[0050] The reporting unit can analyze the owner's past reporting history and select the most suitable reporting destination. For example, the reporting unit can select the most suitable reporting destination based on the destinations the owner has previously reported to. The reporting unit can also suggest the most suitable reporting destination based on the owner's past reporting history. Furthermore, the reporting unit can analyze the owner's past reporting history and select the most suitable reporting destination. This makes it possible to select the most suitable reporting destination by analyzing the owner's past reporting history. Some or all of the above processing in the reporting unit may be performed using AI, for example, or without AI. For example, the reporting unit can input the owner's past reporting data into AI, and the AI ​​can select the most suitable reporting destination.

[0051] The reporting unit can automatically generate reporting content based on the owner's current situation. For example, if the owner collapses due to a sudden illness, the reporting unit will include the owner's health status in the reporting content. The reporting unit can also include details of the accident if the owner is involved in a traffic accident. Furthermore, if the owner is kidnapped, the reporting unit can include the owner's location information in the reporting content. This enables quick and appropriate reporting by automatically generating reporting content based on the owner's current situation. Some or all of the above processing in the reporting unit may be performed using AI, for example, or without AI. For example, the reporting unit can input data on the owner's current situation into AI, which can then automatically generate reporting content.

[0052] The reporting unit can select the most appropriate reporting destination by considering the owner's geographical location. For example, if the owner is in a specific area, the reporting unit will report to the police station in that area. Furthermore, if the owner is traveling, the reporting unit can report to the police station at their travel destination. Additionally, if the owner is on a business trip, the reporting unit can report to the police station at their business trip destination. This allows for the selection of the most appropriate reporting destination by considering the owner's geographical location. Some or all of the above processing in the reporting unit may be performed using AI, or not. For example, the reporting unit can input the owner's geographical location into the AI, which can then select the most appropriate reporting destination.

[0053] The reporting unit can analyze the owner's social media activity and add relevant information to the report. For example, if the owner makes an unusual post on social media, the reporting unit will include that content in the report. The reporting unit can also include details of any unusual behavior exhibited by the owner on social media. Furthermore, the reporting unit can analyze the owner's social media activity and add relevant information to the report. This allows the reporting unit to add relevant information to the report by analyzing the owner's social media activity. Some or all of the above processing in the reporting unit may be performed using AI, for example, or not. For example, the reporting unit can input the owner's social media data into an AI, which can then add relevant information to the report.

[0054] The fraud detection unit can analyze the owner's past communication history and detect signs of fraud early. For example, the fraud detection unit optimizes an algorithm for detecting signs of fraud based on the owner's past communication history. The fraud detection unit can also detect signs of fraud early from the owner's past communication history. Furthermore, the fraud detection unit can analyze the owner's past communication history and detect signs of fraud early. This allows for early detection of signs of fraud by analyzing the owner's past communication history. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's past communication data into AI, which can then detect signs of fraud early.

[0055] The fraud detection unit can analyze the owner's current communication content in real time and determine the possibility of fraud. For example, the fraud detection unit can analyze messages received by the owner in real time and determine the possibility of fraud. It can also analyze the content of phone calls the owner is currently making in real time and determine the possibility of fraud. Furthermore, the fraud detection unit can analyze emails received by the owner in real time and determine the possibility of fraud. This allows for a rapid determination of the possibility of fraud by analyzing the owner's current communication content in real time. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's current communication data into AI, which can then determine the possibility of fraud.

[0056] The fraud detection unit can prioritize detecting the possibility of fraud in a specific area by considering the owner's geographical location information. For example, the fraud detection unit will prioritize detecting the possibility of fraud if the owner is in a dangerous area. The fraud detection unit can also lower the sensitivity of fraud detection if the owner is at home. Furthermore, the fraud detection unit can also prioritize detecting the possibility of fraud if the owner is in a public place. In this way, by considering the owner's geographical location information, the fraud detection unit can prioritize detecting the possibility of fraud in a specific area. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's geographical location information into AI, which can then prioritize detecting the possibility of fraud.

[0057] The fraud detection unit can analyze the owner's social media activity and detect signs of fraud early. For example, the fraud detection unit can detect signs of fraud if the owner makes unusual posts on social media. It can also detect signs of fraud if the owner exhibits unusual behavior on social media. Furthermore, the fraud detection unit can analyze the owner's social media activity and detect signs of fraud early. This allows for early detection of signs of fraud by analyzing the owner's social media activity. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's social media data into AI, which can then detect signs of fraud early.

[0058] The crime detection unit can analyze the owner's past behavioral history and detect signs of crime early. For example, the crime detection unit optimizes an algorithm for detecting signs of crime based on the owner's past behavioral history. The crime detection unit can also detect signs of crime early from the owner's past behavioral history. Furthermore, the crime detection unit can analyze the owner's past behavioral history and detect signs of crime early. This allows for the early detection of signs of crime by analyzing the owner's past behavioral history. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's past behavioral data into AI, which can then detect signs of crime early.

[0059] The crime detection unit can analyze the owner's current behavior in real time and determine the possibility of a crime. For example, the crime detection unit can determine the possibility of a crime if the owner exhibits unusual behavior. It can also determine the possibility of a crime if the owner is in a dangerous location. Furthermore, the crime detection unit can analyze the owner's current behavior in real time and determine the possibility of a crime. This allows for a rapid determination of the possibility of a crime by analyzing the owner's current behavior in real time. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's current behavior data into AI, which can then determine the possibility of a crime.

[0060] The crime detection unit can prioritize the detection of potential crimes in specific areas by considering the owner's geographical location information. For example, if the owner is in a dangerous area, the crime detection unit will prioritize the detection of potential crimes. The crime detection unit can also lower the sensitivity of crime detection if the owner is at home. Furthermore, the crime detection unit can also prioritize the detection of potential crimes if the owner is in a public place. In this way, by considering the owner's geographical location information, it is possible to prioritize the detection of potential crimes in specific areas. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's geographical location information into AI, which can then prioritize the detection of potential crimes.

[0061] The crime detection unit can analyze the owner's social media activity and detect signs of crime early. For example, the crime detection unit can detect signs of crime if the owner makes unusual posts on social media. It can also detect signs of crime if the owner exhibits unusual behavior on social media. Furthermore, the crime detection unit can analyze the owner's social media activity and detect signs of crime early. This allows for the early detection of signs of crime by analyzing the owner's social media activity. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's social media data into AI, which can then detect signs of crime early.

[0062] The alert sending unit can analyze the owner's past alert history and select the optimal alert recipient. For example, the alert sending unit can select the optimal alert recipient based on the recipients to whom the owner has previously sent alerts. The alert sending unit can also suggest the optimal alert recipient based on the owner's past alert history. Furthermore, the alert sending unit can analyze the owner's past alert history and select the optimal alert recipient. This makes it possible to select the optimal alert recipient by analyzing the owner's past alert history. Some or all of the above processing in the alert sending unit may be performed using AI, for example, or without AI. For example, the alert sending unit can input the owner's past alert data into AI, and the AI ​​can select the optimal alert recipient.

[0063] The alert sending unit can select the optimal alert destination by considering the owner's geographical location. For example, if the owner is in a specific area, the alert sending unit will send an alert to the police station in that area. Furthermore, if the owner is traveling, the alert sending unit can send an alert to the police station at their travel destination. In addition, if the owner is on a business trip, the alert sending unit can send an alert to the police station at their business trip destination. This allows for the selection of the optimal alert destination by considering the owner's geographical location. Some or all of the above processing in the alert sending unit may be performed using AI, or not. For example, the alert sending unit can input the owner's geographical location into the AI, which can then select the optimal alert destination.

[0064] The character setting unit can analyze the owner's past character setting history and suggest the most suitable character. For example, the character setting unit can suggest the most suitable character based on the characters the owner has set in the past. It can also suggest the most suitable character based on the owner's past character setting history. Furthermore, the character setting unit can analyze the owner's past character setting history and suggest the most suitable character. This makes it possible to suggest the most suitable character by analyzing the owner's past character setting history. Some or all of the above processing in the character setting unit may be performed using AI, for example, or without AI. For example, the character setting unit can input the owner's past character data into AI, and the AI ​​can suggest the most suitable character.

[0065] The character design unit can suggest local characters by taking into account the owner's geographical location. For example, if the owner is in a specific region, the character design unit can suggest a local character for that region. Furthermore, if the owner is traveling, the character design unit can suggest a local character for their travel destination. Additionally, if the owner is on a business trip, the character design unit can suggest a local character for their business trip destination. This makes it possible to suggest local characters by considering the owner's geographical location. Some or all of the above processing in the character design unit may be performed using AI, or not. For example, the character design unit can input the owner's geographical location into the AI, which can then suggest local characters.

[0066] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0067] The monitoring service system can monitor the owner's health status and notify medical institutions if an abnormality is detected. For example, it can regularly measure the owner's heart rate and blood pressure, and notify medical institutions if abnormal values ​​are detected. It can also send a reminder if the owner forgets to take their medication and notify medical institutions if necessary. Furthermore, if the owner needs a regular check-up, the scheduling department can automatically set a reminder and make an appointment with a medical institution. This ensures that the owner's health status is constantly monitored, enabling prompt medical response.

[0068] The monitoring service system can monitor the owner's sleep patterns and provide an optimal sleep environment. For example, it can detect the owner's movements during sleep and evaluate the quality of sleep. It can also automatically adjust room temperature and lighting to ensure the owner sleeps comfortably. Furthermore, it can support the owner's awakening with gradually brightening lights and soothing music that match their wake-up time. This can improve the owner's sleep quality and support a healthy lifestyle.

[0069] The monitoring service system can record the owner's meals and manage their nutritional balance. For example, when the owner enters their meals, the system records the contents and evaluates the nutritional balance. It can also suggest appropriate meals based on the owner's health condition. Furthermore, if the owner needs to consume a specific nutrient, the system can suggest ingredients and recipes containing that nutrient. This enables appropriate dietary management to support the owner's health.

[0070] The monitoring service system can analyze the owner's hobbies and interests and suggest relevant events and activities. For example, if the owner is interested in music, it can suggest nearby concerts and music events. If the owner is interested in sports, it can suggest local sporting events and matches. Furthermore, if the owner is interested in art, it can suggest museum and gallery exhibitions. This makes it possible to suggest events and activities tailored to the owner's hobbies and interests.

[0071] The monitoring service system can analyze the owner's movement patterns and suggest safe routes. For example, it can analyze the routes the owner uses for commuting to work or school and suggest routes with a low risk of traffic accidents or crime. It can also suggest safe sightseeing routes when the owner is traveling. Furthermore, if the owner is traveling at night, it can suggest well-lit, busy routes. This improves the safety of the owner's movements.

[0072] The following briefly describes the processing flow for example form 1.

[0073] Step 1: The schedule management unit manages the owner's schedule. When the owner enters an appointment, the schedule management unit registers that appointment in the calendar and sets a reminder. For example, when an appointment for a meeting, event, or task is entered, each appointment is registered in the calendar and a reminder is set in advance. Step 2: The crisis detection unit detects when the owner is in danger. It detects abnormal movements by the owner and initiates an emergency call. For example, if the owner collapses due to sudden illness, is kidnapped, or is involved in a traffic accident, the unit detects the situation and notifies the appropriate authorities. Step 3: The reporting unit makes a report based on the crisis detected by the crisis detection unit. It tracks the owner's location and reports to the police and fire department. For example, it reports to the appropriate agency depending on the situation, such as kidnapping, sudden illness, or traffic accident. Step 4: The fraud detection unit and crime detection unit detect fraud and crime. The fraud detection unit analyzes the content of fraudulent phone calls, emails, and messages, and sends an alert to the parent if it determines that there is a possibility of fraud. The crime detection unit detects if the owner has been a victim of a crime and sends an alert to the parent. Step 5: The alert sending unit sends alerts to parents based on the results detected by the fraud detection unit and the crime detection unit. For example, it sends an alert to parents if it determines that there is a possibility of fraud or if a crime has been detected. Step 6: The character setting section allows you to create a friendly character. You can set the appearance and voice of your favorite character. For example, you can set the appearance and voice of an anime character, game character, or movie character.

[0074] (Example of form 2) The monitoring service system according to an embodiment of the present invention is a system that uses an AI assistant to support the owner's daily life and, in emergencies, makes a decision to contact the police or fire department on its own. This monitoring service system supports the owner's daily life by managing the owner's schedule, searching for information, and offering advice on problems. Furthermore, it detects when the owner is in danger and makes a decision to contact the police or fire department on its own. For example, it automatically detects kidnapping, sudden illness, or traffic accidents and makes an emergency call. It also sends an alert to the guardian when it detects fraud or becoming a victim (or perpetrator) of a crime. By giving it a friendly character, it aims to become a presence that helps people's lives in a way similar to a companion or partner. For example, when the owner enters an appointment, the monitoring service system registers that appointment in the calendar and sets a reminder. Also, when the owner searches for necessary information, the monitoring service system collects information from the internet and provides it to the owner. Furthermore, when the owner seeks advice on problems, the monitoring service system provides appropriate advice. Next, the monitoring service system detects when the owner is in danger. For example, if the owner suddenly falls ill and collapses, the monitoring service system will detect the owner's abnormal movements and make an emergency call. Also, if the owner is kidnapped, the monitoring service system will track the owner's location and notify the police. Furthermore, if the owner is involved in a traffic accident, the monitoring service system will detect the accident and notify the fire department. The monitoring service system can also detect fraud and crime (both victim and perpetrator). For example, if the owner receives a fraudulent phone call, the monitoring service system will analyze the content and, if it determines that it is potentially fraudulent, will send an alert to the guardian. Furthermore, if the owner becomes a victim of a crime, the monitoring service system will detect the situation and send an alert to the guardian. Finally, the monitoring service system can be given a friendly character. For example, the owner can set the appearance and voice of their favorite character. This makes the monitoring service system a companion or partner that helps people's lives. In this way, the monitoring service system can support the owner's daily life and respond quickly and appropriately in emergencies.

[0075] The monitoring service system according to this embodiment comprises a schedule management unit, a crisis detection unit, a notification unit, a fraud detection unit and a crime detection unit, an alert transmission unit, and a character setting unit. The schedule management unit manages the owner's schedule. When the owner enters an appointment, the schedule management unit registers the appointment in the calendar and sets a reminder. For example, if the owner enters a meeting appointment, the schedule management unit registers the appointment in the calendar and sets a reminder before the meeting. The schedule management unit can also register an event appointment in the calendar and set a reminder before the event if the owner enters an event appointment. Furthermore, the schedule management unit can also register a task appointment in the calendar and set a reminder before the task if the owner enters a task appointment. The crisis detection unit detects when the owner is in danger. The crisis detection unit detects that the owner's movements are abnormal and makes an emergency call. For example, if the owner collapses due to a sudden illness, the crisis detection unit detects that their movements are abnormal and makes an emergency call. Furthermore, the crisis detection unit can track the owner's location and notify the police if the owner is kidnapped. Additionally, the crisis detection unit can detect the situation if the owner is involved in a traffic accident and notify the fire department. The reporting unit makes a report based on the crisis detected by the crisis detection unit. The reporting unit tracks the owner's location and notifies the police. For example, if the owner is kidnapped, the reporting unit tracks their location and notifies the police. Also, if the owner collapses due to sudden illness, the reporting unit can track their location and notify the fire department. Furthermore, if the owner is involved in a traffic accident, the reporting unit can track their location and notify the fire department. The fraud detection unit and crime detection unit detect fraud and crime. The fraud detection unit analyzes the content of fraudulent phone calls and sends an alert to the guardian if it determines there is a possibility of fraud. For example, if the owner receives a fraudulent phone call, the fraud detection unit analyzes its content and sends an alert to the guardian if it determines there is a possibility of fraud. Furthermore, the fraud detection unit can analyze the content of fraudulent emails received by the owner and, if it determines that they are potentially fraudulent, can send an alert to the guardian.Furthermore, the fraud detection unit can analyze the content of a message if the owner receives a fraudulent message, and if it determines that it is potentially fraudulent, it can send an alert to the guardian. The crime detection unit can detect if the owner is a victim of a crime and send an alert to the guardian. For example, if the owner is assaulted, the crime detection unit can detect the situation and send an alert to the guardian. The crime detection unit can also detect if the owner is a victim of theft and send an alert to the guardian. Furthermore, if the owner is a victim of fraud, the crime detection unit can detect the situation and send an alert to the guardian. The alert transmission unit sends alerts to the guardian based on the results detected by the fraud detection unit and the crime detection unit. For example, if the fraud detection unit determines that it is potentially fraudulent, the alert transmission unit will send an alert to the guardian. Furthermore, if the crime detection unit detects that the owner has been a victim of a crime, the alert transmission unit can send an alert to the guardian. Furthermore, the alert transmission unit can also send alerts to guardians based on the results detected by the fraud detection unit and the crime detection unit. The character setting unit allows for the creation of a friendly character. The character setting unit allows the user to set the appearance and voice of their favorite character. For example, the character setting unit can set the appearance and voice of the user's favorite anime character. It can also set the appearance and voice of the user's favorite game character. Furthermore, it can also set the appearance and voice of the user's favorite movie character. As a result, the monitoring service system according to this embodiment can support the user's daily life and respond quickly and appropriately in emergencies.

[0076] The Schedule Management Unit manages the owner's schedule. When the owner enters an appointment, the Schedule Management Unit registers the appointment in the calendar and sets a reminder. For example, if the owner enters a meeting appointment, the Schedule Management Unit registers the appointment in the calendar and sets a reminder before the meeting. The Schedule Management Unit can also register an event appointment in the calendar and set a reminder before the event if the owner enters an event appointment. Furthermore, if the owner enters a task appointment, the Schedule Management Unit can register that task in the calendar and set a reminder before the task is completed. To efficiently manage the owner's schedule, the Schedule Management Unit can synchronize across multiple devices. For example, appointments entered by the owner on their smartphone are automatically reflected on their PC and tablet. This allows the owner to check their latest schedule from any device. The Schedule Management Unit can also analyze the owner's past schedule data and find patterns. For example, if the owner tends to schedule meetings on a specific day of the week, the Schedule Management Unit can recognize this pattern and automatically suggest the next meeting date. Furthermore, the schedule management unit can provide optimal time management advice based on the owner's schedule. For example, if the owner has a busy schedule, the schedule management unit can suggest break times and support the owner's health management. In this way, the schedule management unit can efficiently manage the owner's schedule and improve the quality of daily life.

[0077] The crisis detection unit detects when the owner is in danger. It detects abnormal movements of the owner and initiates an emergency call. For example, if the owner collapses due to sudden illness, the crisis detection unit will detect the abnormal movements and initiate an emergency call. Furthermore, if the owner is kidnapped, the crisis detection unit can track their location and notify the police. Additionally, if the owner is involved in a traffic accident, the crisis detection unit can detect the situation and notify the fire department. The crisis detection unit utilizes acceleration sensors and gyroscopes to monitor the owner's movements in real time. This allows for immediate detection of abnormalities if the owner's movements exhibit an unusual pattern. For example, if the owner suddenly collapses, the acceleration sensor will detect the sudden movement, and the crisis detection unit will recognize the abnormality. The crisis detection unit can also monitor the owner's biometric information, such as heart rate and body temperature. This allows for a rapid response in the event of a sudden change in the owner's health. For example, if the owner's heart rate suddenly increases, the pinch detection unit will detect the anomaly and initiate an emergency call. Furthermore, the pinch detection unit can constantly track the owner's location and detect abnormal movement patterns. For instance, if the owner deviates significantly from their normal range of activity, the pinch detection unit will recognize the anomaly and notify the police. This ensures the owner's safety and allows for a swift and appropriate response in emergencies.

[0078] The reporting unit makes an emergency call based on an emergency detected by the emergency detection unit. The reporting unit tracks the owner's location and notifies the police. For example, if the owner is kidnapped, the reporting unit tracks their location and notifies the police. The reporting unit can also track the owner's location and notify the fire department if the owner collapses due to sudden illness. Furthermore, if the owner is involved in a traffic accident, the reporting unit can track their location and notify the fire department. The reporting unit uses GPS technology to accurately track the owner's location. This allows the unit to know the owner's current location in real time and respond quickly in emergencies. For example, if the owner is kidnapped, the reporting unit continuously tracks the owner's location and provides it to the police. In addition to the owner's location, the reporting unit can also report the owner's health status and surrounding environment. For example, if the owner collapses due to sudden illness, the reporting unit provides biometric information such as the owner's heart rate and body temperature to the fire department to support a rapid response. Furthermore, the reporting unit can calculate the optimal rescue route based on the owner's location information and provide it to the rescue team. This allows the reporting unit to ensure the owner's safety and respond quickly and appropriately in emergencies.

[0079] The fraud detection unit and crime detection unit detect fraud and crime. The fraud detection unit analyzes the content of fraudulent phone calls and sends an alert to the guardian if it determines that there is a possibility of fraud. For example, if the owner receives a fraudulent phone call, the fraud detection unit analyzes the content and sends an alert to the guardian if it determines that there is a possibility of fraud. The fraud detection unit can also analyze the content of fraudulent emails received by the owner and send an alert to the guardian if it determines that there is a possibility of fraud. Furthermore, if the owner receives a fraudulent message, the fraud detection unit can analyze the content and send an alert to the guardian if it determines that there is a possibility of fraud. The crime detection unit detects when the owner becomes a victim of a crime and sends an alert to the guardian. For example, if the owner is assaulted, the crime detection unit detects the situation and sends an alert to the guardian. The crime detection unit can also detect when the owner is a victim of theft and send an alert to the guardian. Furthermore, the crime detection unit can also detect if the owner has been a victim of fraud and send an alert to the guardian. The fraud detection unit uses natural language processing technology to analyze the content of phone calls, emails, and messages received by the owner. This allows it to quickly detect potentially fraudulent content and send an alert to the guardian. For example, the fraud detection unit analyzes the audio of phone calls received by the owner to detect potentially fraudulent keywords and phrases. It also analyzes the text of emails and messages received by the owner to detect potentially fraudulent content. The crime detection unit uses cameras and sensors to monitor the owner's behavior and surrounding environment and detect abnormal situations. This allows it to quickly detect if the owner has been a victim of crime and send an alert to the guardian. For example, if the owner is assaulted, the crime detection unit can detect the situation with a camera and send an alert to the guardian. It can also detect if the owner is a victim of theft with a sensor and send an alert to the guardian. This allows the fraud detection unit and crime detection unit to ensure the owner's safety and take swift and appropriate action.

[0080] The alert transmission unit sends alerts to parents based on the results detected by the fraud detection unit and the crime detection unit. For example, the alert transmission unit sends an alert to parents if the fraud detection unit determines there is a possibility of fraud. The alert transmission unit can also send an alert to parents if the crime detection unit detects that a crime has occurred. Furthermore, the alert transmission unit can send alerts to parents based on the results detected by the fraud detection unit and the crime detection unit. The alert transmission unit utilizes multiple communication methods to quickly and reliably send alerts to parents. For example, the alert transmission unit uses the notification function of smartphones to send alerts to parents. It can also send alerts to parents via email or SMS. Furthermore, the alert transmission unit can send alerts via voice calls. This allows the alert transmission unit to quickly and reliably send alerts to parents and ensure the safety of the owner. The alert transmission unit also provides detailed information in its alerts to enable parents to respond quickly. For example, the alert system notifies parents of the details and how to deal with a potential scam. It also notifies parents of the details and how to deal with a crime if it is detected. This allows the alert system to provide parents with timely and appropriate information, ensuring the safety of the owner.

[0081] The character setting section allows users to create approachable characters. The character setting section allows users to set the appearance and voice of their favorite characters. For example, the character setting section allows users to set the appearance and voice of their favorite anime character. It also allows users to set the appearance and voice of their favorite game character. Furthermore, it allows users to set the appearance and voice of their favorite movie character. The character setting section provides a rich character library to help users create approachable characters. This allows users to select and set characters according to their preferences. For example, the character setting section offers characters from various genres, such as anime characters, game characters, and movie characters. The character setting section also allows users to customize the character's appearance and voice. For example, users can freely change the character's hairstyle, clothing, and voice tone. Furthermore, the character setting section allows users to set the character's movements and expressions. This allows users to create their own original characters and create an approachable environment. The character setting section also allows users to set the character's personality and speaking style according to their preferences. For example, if the owner prefers a lively character, they can set the character's personality and way of speaking to be lively. This allows the character setting unit to create a character that the owner finds approachable and that can support their daily life in a fun way.

[0082] The schedule management unit can register appointments entered by the user into the calendar and set reminders. For example, if the user enters a meeting, the schedule management unit can register the appointment into the calendar and set a reminder before the meeting. The schedule management unit can also register events entered by the user into the calendar and set reminders before the event. Furthermore, if the user enters a task, the schedule management unit can register that task into the calendar and set a reminder before the task. This allows for efficient management of the user's schedule and prevents forgetting appointments by setting reminders. Some or all of the above processes in the schedule management unit may be performed using AI, for example, or not using AI. For example, the schedule management unit can input the appointments entered by the user into the AI, which can then register them into the calendar and set reminders.

[0083] The crisis detection unit can detect abnormal movements of the owner and initiate an emergency call. For example, if the owner collapses due to a sudden illness, the crisis detection unit can detect the abnormal movements and initiate an emergency call. Furthermore, if the owner is kidnapped, the crisis detection unit can track their location and notify the police. Additionally, if the owner is involved in a traffic accident, the crisis detection unit can detect the situation and notify the fire department. This allows for a rapid response by detecting abnormal movements of the owner and initiating an emergency call. Some or all of the above-described processes in the crisis detection unit may be performed using AI, or without AI. For example, the crisis detection unit can input data on the owner's movements into an AI, which can then detect the abnormality and initiate an emergency call.

[0084] The reporting unit can track the owner's location and report it to the police. For example, if the owner is kidnapped, the reporting unit can track their location and report it to the police. Furthermore, if the owner collapses due to a sudden illness, the reporting unit can track their location and report it to the fire department. In addition, if the owner is involved in a traffic accident, the reporting unit can track their location and report it to the fire department. This allows for a swift response by tracking the owner's location and reporting it to the police. Some or all of the above processes in the reporting unit may be performed using AI, or not. For example, the reporting unit can input the owner's location information into an AI, which can then select a recipient and make the report.

[0085] The fraud detection unit can analyze the content of fraudulent phone calls and, if it determines that there is a possibility of fraud, can send an alert to the guardian. For example, if the owner receives a fraudulent phone call, the fraud detection unit can analyze its content and, if it determines that there is a possibility of fraud, send an alert to the guardian. The fraud detection unit can also analyze the content of fraudulent emails received by the owner and, if it determines that there is a possibility of fraud, send an alert to the guardian. Furthermore, if the owner receives a fraudulent message, the fraud detection unit can analyze its content and, if it determines that there is a possibility of fraud, send an alert to the guardian. In this way, by analyzing the content of fraudulent phone calls and sending alerts to guardians if it determines that there is a possibility of fraud, fraud can be prevented. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the content of a fraudulent phone call into an AI, which can determine the possibility of fraud and send an alert to the guardian.

[0086] The crime detection unit can detect if the owner has been a victim of a crime and send an alert to the guardian. For example, if the owner has been assaulted, the crime detection unit can detect the situation and send an alert to the guardian. It can also detect if the owner has been a victim of theft and send an alert to the guardian. Furthermore, if the owner has been a victim of fraud, the crime detection unit can detect the situation and send an alert to the guardian. This allows for a swift response when the owner is a victim of a crime by detecting the situation and sending an alert to the guardian. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or not using AI. For example, the crime detection unit can input the circumstances of the crime into the AI, which can detect the crime and send an alert to the guardian.

[0087] The character setting unit allows the owner to set the appearance and voice of their favorite character. For example, the character setting unit can set the appearance and voice of the owner's favorite anime character. It can also set the appearance and voice of the owner's favorite game character. Furthermore, it can also set the appearance and voice of the owner's favorite movie character. This allows for the provision of a more approachable character by allowing the owner to set the appearance and voice of their favorite character. Some or all of the above processing in the character setting unit may be performed using AI, for example, or not. For example, the character setting unit can input the appearance and voice of the character chosen by the owner into the AI, and the AI ​​can perform the settings.

[0088] The schedule management unit can estimate the owner's emotions and adjust the reminder notification method based on the estimated emotions. For example, if the owner is stressed, the schedule management unit can send a reminder notification with a calming sound. If the owner is relaxed, the schedule management unit can send a reminder notification with a cheerful sound. Furthermore, if the owner is in a hurry, the schedule management unit can send a reminder notification with a short, concise sound. This allows for more appropriate notifications by adjusting the reminder notification method according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the schedule management unit may be performed using AI, or not using AI. For example, the schedule management unit can input the owner's emotion data into the AI, and the AI ​​can adjust the reminder notification method.

[0089] The schedule management unit can analyze the owner's past schedule history and propose the optimal schedule. For example, the schedule management unit can propose the next appointment based on the owner's frequently performed past appointments. It can also propose the optimal break times based on the owner's past schedule. Furthermore, the schedule management unit can analyze the owner's past schedule and propose an efficient schedule. In this way, it is possible to propose the optimal schedule by analyzing the owner's past schedule history. Some or all of the above processes in the schedule management unit may be performed using AI, for example, or not using AI. For example, the schedule management unit can input the owner's past schedule data into AI, and the AI ​​can propose the optimal schedule.

[0090] The schedule management unit can automatically adjust schedule priorities based on the owner's current activity status. For example, if the owner is currently busy, the schedule management unit will prioritize notifying them of important appointments. It can also delay reminder notifications if the owner is currently relaxing. Furthermore, it can refrain from sending reminder notifications if the owner is currently traveling. This enables efficient schedule management by automatically adjusting schedule priorities based on the owner's current activity status. Some or all of the above processes in the schedule management unit may be performed using AI, for example, or without AI. For example, the schedule management unit can input the owner's current activity data into the AI, which can then automatically adjust schedule priorities.

[0091] The schedule management unit can estimate the owner's emotions and change the schedule display format based on the estimated emotions. For example, if the owner is stressed, the schedule management unit can provide a simple and highly visible display format. If the owner is having fun, the schedule management unit can also provide a colorful and visually pleasing display format. Furthermore, if the owner is tired, the schedule management unit can provide a display format with calming colors. This allows for a more appropriate display by changing the schedule display format according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the schedule management unit may be performed using AI, or not using AI. For example, the schedule management unit can input the owner's emotion data into the AI, and the AI ​​can change the schedule display format.

[0092] The schedule management unit can suggest local events related to the schedule, taking into account the owner's geographical location. For example, if the owner is in a specific region, the schedule management unit can suggest events held in that region. Furthermore, if the owner is traveling, the schedule management unit can suggest tourist attractions at their travel destination. Additionally, if the owner is on a business trip, the schedule management unit can suggest business events at their destination. This makes it possible to suggest relevant local events by considering the owner's geographical location. Some or all of the above processing in the schedule management unit may be performed using AI, for example, or without AI. For example, the schedule management unit can input the owner's geographical location into an AI, which can then suggest local events.

[0093] The schedule management unit can analyze the owner's social media activity and add relevant events and appointments to the schedule. For example, the schedule management unit can add events the owner plans to attend as posted on social media. It can also suggest events the owner has shown interest in as posted on social media. Furthermore, the schedule management unit can add events that the owner's friends will be attending as well. This makes it possible to add relevant events and appointments by analyzing the owner's social media activity. Some or all of the above processes in the schedule management unit may be performed using AI, for example, or not. For example, the schedule management unit can input the owner's social media data into an AI, which can then add relevant events and appointments to the schedule.

[0094] The pinch detection unit can estimate the owner's emotions and adjust the sensitivity of the pinch detection based on the estimated emotions. For example, if the owner is tense, the pinch detection unit can increase the sensitivity of the pinch detection. Conversely, if the owner is relaxed, the pinch detection unit can also decrease the sensitivity of the pinch detection. Furthermore, if the owner is excited, the pinch detection unit can set the sensitivity of the pinch detection to a moderate level. This allows for more appropriate pinch detection by adjusting the sensitivity of the pinch detection according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the pinch detection unit may be performed using AI, or not using AI. For example, the pinch detection unit can input the owner's emotion data into the AI, and the AI ​​can adjust the sensitivity of the pinch detection.

[0095] The pinch detection unit can analyze the owner's past behavior patterns to improve the accuracy of detecting abnormal behavior. For example, the pinch detection unit optimizes the algorithm for detecting abnormal behavior based on the owner's past behavior patterns. The pinch detection unit can also detect early signs of abnormal behavior from the owner's past behavior patterns. Furthermore, the pinch detection unit can analyze the owner's past behavior patterns to improve the accuracy of detecting abnormal behavior. As a result, the accuracy of detecting abnormal behavior is improved by analyzing the owner's past behavior patterns. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or without AI. For example, the pinch detection unit can input the owner's past behavior data into AI, which can then improve the accuracy of detecting abnormal behavior.

[0096] The pinch detection unit can monitor the owner's biometric information (heart rate, body temperature, etc.) in real time and detect abnormalities. For example, the pinch detection unit can detect a pinch if the owner's heart rate is abnormally high. It can also detect a pinch if the owner's body temperature is abnormally low. Furthermore, the pinch detection unit can monitor the owner's biometric information in real time and detect abnormalities. This enables early detection of abnormalities by monitoring the owner's biometric information in real time. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or without AI. For example, the pinch detection unit can input the owner's biometric information into AI, which can then detect abnormalities.

[0097] The pinch detection unit can estimate the owner's emotions and change the method of notifying of a pinch based on the estimated emotions. For example, if the owner is tense, the pinch detection unit will notify of a pinch with a gentle sound. If the owner is relaxed, the pinch detection unit can also notify of a pinch with a bright sound. Furthermore, if the owner is in a hurry, the pinch detection unit can notify of a pinch with a short, concise sound. This allows for more appropriate notifications by changing the method of notification of a pinch according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or not using AI. For example, the pinch detection unit can input the owner's emotion data into the AI, and the AI ​​can change the method of notifying of a pinch.

[0098] The pinch detection unit can prioritize the detection of abnormal behavior in specific areas by considering the owner's geographical location information. For example, if the owner is in a dangerous area, the pinch detection unit will prioritize detecting abnormal behavior. The pinch detection unit can also lower the sensitivity of abnormal behavior detection when the owner is at home. Furthermore, the pinch detection unit can also prioritize the detection of abnormal behavior when the owner is in a public place. This makes it possible to prioritize the detection of abnormal behavior in specific areas by considering the owner's geographical location information. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or without AI. For example, the pinch detection unit can input the owner's geographical location information into the AI, which can then prioritize the detection of abnormal behavior.

[0099] The pinch detection unit can analyze the owner's social media activity and detect signs of abnormal behavior early. For example, the pinch detection unit detects a pinch if the owner makes an unusual post on social media. The pinch detection unit can also detect a pinch if the owner exhibits unusual behavior on social media. Furthermore, the pinch detection unit can analyze the owner's social media activity and detect signs of abnormal behavior early. This allows for the early detection of signs of abnormal behavior by analyzing the owner's social media activity. Some or all of the above processing in the pinch detection unit may be performed using AI, for example, or without AI. For example, the pinch detection unit can input the owner's social media data into AI, which can then detect signs of abnormal behavior early.

[0100] The notification unit can estimate the owner's emotions and adjust the urgency of the notification based on the estimated emotions. For example, if the owner is tense, the notification unit can increase the urgency of the notification. Conversely, if the owner is relaxed, the notification unit can decrease the urgency of the notification. Furthermore, if the owner is excited, the notification unit can set the urgency of the notification to a moderate level. This allows for more appropriate notifications by adjusting the urgency of the notification according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the notification unit may be performed using AI or not using AI. For example, the notification unit can input the owner's emotion data into an AI, which can then adjust the urgency of the notification.

[0101] The reporting unit can analyze the owner's past reporting history and select the most suitable reporting destination. For example, the reporting unit can select the most suitable reporting destination based on the destinations the owner has previously reported to. The reporting unit can also suggest the most suitable reporting destination based on the owner's past reporting history. Furthermore, the reporting unit can analyze the owner's past reporting history and select the most suitable reporting destination. This makes it possible to select the most suitable reporting destination by analyzing the owner's past reporting history. Some or all of the above processing in the reporting unit may be performed using AI, for example, or without AI. For example, the reporting unit can input the owner's past reporting data into AI, and the AI ​​can select the most suitable reporting destination.

[0102] The reporting unit can automatically generate reporting content based on the owner's current situation. For example, if the owner collapses due to a sudden illness, the reporting unit will include the owner's health status in the reporting content. The reporting unit can also include details of the accident if the owner is involved in a traffic accident. Furthermore, if the owner is kidnapped, the reporting unit can include the owner's location information in the reporting content. This enables quick and appropriate reporting by automatically generating reporting content based on the owner's current situation. Some or all of the above processing in the reporting unit may be performed using AI, for example, or without AI. For example, the reporting unit can input data on the owner's current situation into AI, which can then automatically generate reporting content.

[0103] The notification unit can estimate the owner's emotions and change the method of notification (phone call, message, etc.) based on the estimated emotions. For example, if the owner is nervous, the notification unit will make a phone call. If the owner is relaxed, the notification unit can also make a message. Furthermore, if the owner is in a hurry, the notification unit can select a method of notification that allows for quick reporting. This allows for more appropriate reporting by changing the method of notification according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the notification unit may be performed using AI or not using AI. For example, the notification unit can input the owner's emotion data into the AI, and the AI ​​can change the method of notification.

[0104] The reporting unit can select the most appropriate reporting destination by considering the owner's geographical location. For example, if the owner is in a specific area, the reporting unit will report to the police station in that area. Furthermore, if the owner is traveling, the reporting unit can report to the police station at their travel destination. Additionally, if the owner is on a business trip, the reporting unit can report to the police station at their business trip destination. This allows for the selection of the most appropriate reporting destination by considering the owner's geographical location. Some or all of the above processing in the reporting unit may be performed using AI, or not. For example, the reporting unit can input the owner's geographical location into the AI, which can then select the most appropriate reporting destination.

[0105] The reporting unit can analyze the owner's social media activity and add relevant information to the report. For example, if the owner makes an unusual post on social media, the reporting unit will include that content in the report. The reporting unit can also include details of any unusual behavior exhibited by the owner on social media. Furthermore, the reporting unit can analyze the owner's social media activity and add relevant information to the report. This allows the reporting unit to add relevant information to the report by analyzing the owner's social media activity. Some or all of the above processing in the reporting unit may be performed using AI, for example, or not. For example, the reporting unit can input the owner's social media data into an AI, which can then add relevant information to the report.

[0106] The fraud detection unit can estimate the owner's emotions and adjust the sensitivity of fraud detection based on the estimated emotions. For example, if the owner is tense, the fraud detection unit can increase the sensitivity of fraud detection. Conversely, if the owner is relaxed, the fraud detection unit can decrease the sensitivity of fraud detection. Furthermore, if the owner is excited, the fraud detection unit can set the sensitivity of fraud detection to a moderate level. This allows for more appropriate fraud detection by adjusting the sensitivity of fraud detection according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's emotion data into an AI, which can then adjust the sensitivity of fraud detection.

[0107] The fraud detection unit can analyze the owner's past communication history and detect signs of fraud early. For example, the fraud detection unit optimizes an algorithm for detecting signs of fraud based on the owner's past communication history. The fraud detection unit can also detect signs of fraud early from the owner's past communication history. Furthermore, the fraud detection unit can analyze the owner's past communication history and detect signs of fraud early. This allows for early detection of signs of fraud by analyzing the owner's past communication history. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's past communication data into AI, which can then detect signs of fraud early.

[0108] The fraud detection unit can analyze the owner's current communication content in real time and determine the possibility of fraud. For example, the fraud detection unit can analyze messages received by the owner in real time and determine the possibility of fraud. It can also analyze the content of phone calls the owner is currently making in real time and determine the possibility of fraud. Furthermore, the fraud detection unit can analyze emails received by the owner in real time and determine the possibility of fraud. This allows for a rapid determination of the possibility of fraud by analyzing the owner's current communication content in real time. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's current communication data into AI, which can then determine the possibility of fraud.

[0109] The fraud detection unit can estimate the owner's emotions and change the fraud warning method based on the estimated emotions. For example, if the owner is tense, the fraud detection unit can issue a fraud warning with a gentle sound. It can also issue a fraud warning with a bright sound if the owner is relaxed. Furthermore, if the owner is in a hurry, the fraud detection unit can issue a fraud warning with a short, concise sound. This allows for more appropriate warnings by changing the fraud warning method according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the fraud detection unit may be performed using AI, or not. For example, the fraud detection unit can input the owner's emotion data into an AI, which can then change the fraud warning method.

[0110] The fraud detection unit can prioritize detecting the possibility of fraud in a specific area by considering the owner's geographical location information. For example, the fraud detection unit will prioritize detecting the possibility of fraud if the owner is in a dangerous area. The fraud detection unit can also lower the sensitivity of fraud detection if the owner is at home. Furthermore, the fraud detection unit can also prioritize detecting the possibility of fraud if the owner is in a public place. In this way, by considering the owner's geographical location information, the fraud detection unit can prioritize detecting the possibility of fraud in a specific area. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's geographical location information into AI, which can then prioritize detecting the possibility of fraud.

[0111] The fraud detection unit can analyze the owner's social media activity and detect signs of fraud early. For example, the fraud detection unit can detect signs of fraud if the owner makes unusual posts on social media. It can also detect signs of fraud if the owner exhibits unusual behavior on social media. Furthermore, the fraud detection unit can analyze the owner's social media activity and detect signs of fraud early. This allows for early detection of signs of fraud by analyzing the owner's social media activity. Some or all of the above processing in the fraud detection unit may be performed using AI, for example, or without AI. For example, the fraud detection unit can input the owner's social media data into AI, which can then detect signs of fraud early.

[0112] The crime detection unit can estimate the owner's emotions and adjust the sensitivity of crime detection based on the estimated emotions. For example, if the owner is tense, the crime detection unit can increase the sensitivity of crime detection. Conversely, if the owner is relaxed, the crime detection unit can decrease the sensitivity of crime detection. Furthermore, if the owner is excited, the crime detection unit can set the sensitivity of crime detection to a moderate level. This allows for more appropriate crime detection by adjusting the sensitivity of crime detection according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's emotion data into an AI, which can then adjust the sensitivity of crime detection.

[0113] The crime detection unit can analyze the owner's past behavioral history and detect signs of crime early. For example, the crime detection unit optimizes an algorithm for detecting signs of crime based on the owner's past behavioral history. The crime detection unit can also detect signs of crime early from the owner's past behavioral history. Furthermore, the crime detection unit can analyze the owner's past behavioral history and detect signs of crime early. This allows for the early detection of signs of crime by analyzing the owner's past behavioral history. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's past behavioral data into AI, which can then detect signs of crime early.

[0114] The crime detection unit can analyze the owner's current behavior in real time and determine the possibility of a crime. For example, the crime detection unit can determine the possibility of a crime if the owner exhibits unusual behavior. It can also determine the possibility of a crime if the owner is in a dangerous location. Furthermore, the crime detection unit can analyze the owner's current behavior in real time and determine the possibility of a crime. This allows for a rapid determination of the possibility of a crime by analyzing the owner's current behavior in real time. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's current behavior data into AI, which can then determine the possibility of a crime.

[0115] The crime detection unit can estimate the owner's emotions and modify the crime warning method based on the estimated emotions. For example, if the owner is tense, the crime detection unit can issue a crime warning with a gentle sound. It can also issue a crime warning with a bright sound if the owner is relaxed. Furthermore, if the owner is in a hurry, the crime detection unit can issue a crime warning with a short, concise sound. This allows for more appropriate warnings by changing the crime warning method according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the crime detection unit may be performed using AI, or not. For example, the crime detection unit can input the owner's emotion data into an AI, which can then modify the crime warning method.

[0116] The crime detection unit can prioritize the detection of potential crimes in specific areas by considering the owner's geographical location information. For example, if the owner is in a dangerous area, the crime detection unit will prioritize the detection of potential crimes. The crime detection unit can also lower the sensitivity of crime detection if the owner is at home. Furthermore, the crime detection unit can also prioritize the detection of potential crimes if the owner is in a public place. In this way, by considering the owner's geographical location information, it is possible to prioritize the detection of potential crimes in specific areas. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's geographical location information into AI, which can then prioritize the detection of potential crimes.

[0117] The crime detection unit can analyze the owner's social media activity and detect signs of crime early. For example, the crime detection unit can detect signs of crime if the owner makes unusual posts on social media. It can also detect signs of crime if the owner exhibits unusual behavior on social media. Furthermore, the crime detection unit can analyze the owner's social media activity and detect signs of crime early. This allows for the early detection of signs of crime by analyzing the owner's social media activity. Some or all of the above processing in the crime detection unit may be performed using AI, for example, or without AI. For example, the crime detection unit can input the owner's social media data into AI, which can then detect signs of crime early.

[0118] The alert sending unit can estimate the owner's emotions and adjust the alert sending method based on the estimated emotions. For example, if the owner is tense, the alert sending unit can send an alert with a calm sound. It can also send an alert with a bright sound if the owner is relaxed. Furthermore, if the owner is in a hurry, the alert sending unit can send an alert with a short, concise sound. This allows for more appropriate alert delivery by adjusting the alert sending method according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the alert sending unit may be performed using AI, or not. For example, the alert sending unit can input the owner's emotion data into the AI, which can then adjust the alert sending method.

[0119] The alert sending unit can analyze the owner's past alert history and select the optimal alert recipient. For example, the alert sending unit can select the optimal alert recipient based on the recipients to whom the owner has previously sent alerts. The alert sending unit can also suggest the optimal alert recipient based on the owner's past alert history. Furthermore, the alert sending unit can analyze the owner's past alert history and select the optimal alert recipient. This makes it possible to select the optimal alert recipient by analyzing the owner's past alert history. Some or all of the above processing in the alert sending unit may be performed using AI, for example, or without AI. For example, the alert sending unit can input the owner's past alert data into AI, and the AI ​​can select the optimal alert recipient.

[0120] The alert sending unit can estimate the owner's emotions and determine the priority of alerts based on the estimated emotions. For example, if the owner is tense, the alert sending unit can increase the priority of the alert. Conversely, if the owner is relaxed, the alert sending unit can also decrease the priority of the alert. Furthermore, if the owner is excited, the alert sending unit can set the priority to a medium level. This allows for more appropriate alert delivery by determining the priority of alerts according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the alert sending unit may be performed using AI or not using AI. For example, the alert sending unit can input the owner's emotion data into an AI, which can then determine the priority of alerts.

[0121] The alert sending unit can select the optimal alert destination by considering the owner's geographical location. For example, if the owner is in a specific area, the alert sending unit will send an alert to the police station in that area. Furthermore, if the owner is traveling, the alert sending unit can send an alert to the police station at their travel destination. In addition, if the owner is on a business trip, the alert sending unit can send an alert to the police station at their business trip destination. This allows for the selection of the optimal alert destination by considering the owner's geographical location. Some or all of the above processing in the alert sending unit may be performed using AI, or not. For example, the alert sending unit can input the owner's geographical location into the AI, which can then select the optimal alert destination.

[0122] The character setting unit can estimate the owner's emotions and adjust the character's expression based on the estimated emotions. For example, if the owner is nervous, the character setting unit can display a character with a calm expression. It can also display a character with a cheerful expression if the owner is relaxed. Furthermore, it can display a character with an energetic expression if the owner is excited. This allows for a more approachable character by adjusting the character's expression according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the character setting unit may be performed using AI, or not. For example, the character setting unit can input the owner's emotion data into the AI, which can then adjust the character's expression.

[0123] The character setting unit can analyze the owner's past character setting history and suggest the most suitable character. For example, the character setting unit can suggest the most suitable character based on the characters the owner has set in the past. It can also suggest the most suitable character based on the owner's past character setting history. Furthermore, the character setting unit can analyze the owner's past character setting history and suggest the most suitable character. This makes it possible to suggest the most suitable character by analyzing the owner's past character setting history. Some or all of the above processing in the character setting unit may be performed using AI, for example, or without AI. For example, the character setting unit can input the owner's past character data into AI, and the AI ​​can suggest the most suitable character.

[0124] The character setting unit can estimate the owner's emotions and change the character's appearance and voice based on the estimated emotions. For example, if the owner is nervous, the character setting unit can set a character with a calm voice. It can also set a character with a cheerful voice if the owner is relaxed. Furthermore, it can set a character with an energetic voice if the owner is excited. This allows for a more approachable character by changing the character's appearance and voice according to the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. The generative AI is, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processes in the character setting unit may be performed using AI, or not. For example, the character setting unit can input the owner's emotion data into the AI, which can then change the character's appearance and voice.

[0125] The character design unit can suggest local characters by taking into account the owner's geographical location. For example, if the owner is in a specific region, the character design unit can suggest a local character for that region. Furthermore, if the owner is traveling, the character design unit can suggest a local character for their travel destination. Additionally, if the owner is on a business trip, the character design unit can suggest a local character for their business trip destination. This makes it possible to suggest local characters by considering the owner's geographical location. Some or all of the above processing in the character design unit may be performed using AI, or not. For example, the character design unit can input the owner's geographical location into the AI, which can then suggest local characters.

[0126] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0127] The monitoring service system can monitor the owner's health status and notify medical institutions if an abnormality is detected. For example, it can regularly measure the owner's heart rate and blood pressure, and notify medical institutions if abnormal values ​​are detected. It can also send a reminder if the owner forgets to take their medication and notify medical institutions if necessary. Furthermore, if the owner needs a regular check-up, the scheduling department can automatically set a reminder and make an appointment with a medical institution. This ensures that the owner's health status is constantly monitored, enabling prompt medical response.

[0128] The monitoring service system can estimate the owner's emotions and suggest music and videos based on those estimates. For example, if the owner is stressed, it can suggest relaxing music or videos. If the owner is having fun, it can suggest cheerful music or videos. Furthermore, if the owner is sad, it can suggest music or videos to soothe their mood. This makes it possible to provide entertainment tailored to the owner's emotions. Emotion estimation is achieved using an emotion engine or generative AI.

[0129] The monitoring service system can monitor the owner's sleep patterns and provide an optimal sleep environment. For example, it can detect the owner's movements during sleep and evaluate the quality of sleep. It can also automatically adjust room temperature and lighting to ensure the owner sleeps comfortably. Furthermore, it can support the owner's awakening with gradually brightening lights and soothing music that match their wake-up time. This can improve the owner's sleep quality and support a healthy lifestyle.

[0130] The monitoring service system can estimate the owner's emotions and adjust its communication method based on those estimates. For example, if the owner is stressed, it will speak in a calm tone. If the owner is relaxed, it can speak in a cheerful tone. Furthermore, if the owner is in a hurry, it can send a short, concise message. This enables appropriate communication tailored to the owner's emotions. Emotion estimation is achieved using an emotion engine or generative AI, among other methods.

[0131] The monitoring service system can record the owner's meals and manage their nutritional balance. For example, when the owner enters their meals, the system records the contents and evaluates the nutritional balance. It can also suggest appropriate meals based on the owner's health condition. Furthermore, if the owner needs to consume a specific nutrient, the system can suggest ingredients and recipes containing that nutrient. This enables appropriate dietary management to support the owner's health.

[0132] The monitoring service system can estimate the owner's emotions and suggest exercise programs based on those estimates. For example, if the owner is feeling stressed, it can suggest relaxing yoga or stretching. If the owner is feeling energetic, it can suggest running or aerobics. Furthermore, if the owner is tired, it can suggest light walking or relaxation exercises. This makes it possible to provide an appropriate exercise program tailored to the owner's emotions. Emotion estimation is achieved using an emotion engine or generative AI.

[0133] The monitoring service system can analyze the owner's hobbies and interests and suggest relevant events and activities. For example, if the owner is interested in music, it can suggest nearby concerts and music events. If the owner is interested in sports, it can suggest local sporting events and matches. Furthermore, if the owner is interested in art, it can suggest museum and gallery exhibitions. This makes it possible to suggest events and activities tailored to the owner's hobbies and interests.

[0134] The monitoring service system can estimate the owner's emotions and suggest relaxation methods based on those estimates. For example, if the owner is feeling stressed, it can suggest deep breathing or meditation. If the owner is feeling tense, it can suggest relaxing music or aromatherapy. Furthermore, if the owner is tired, it can suggest a massage or a warm bath. This makes it possible to provide appropriate relaxation methods tailored to the owner's emotions. Emotion estimation is achieved using an emotion engine or generative AI.

[0135] The monitoring service system can analyze the owner's movement patterns and suggest safe routes. For example, it can analyze the routes the owner uses for commuting to work or school and suggest routes with a low risk of traffic accidents or crime. It can also suggest safe sightseeing routes when the owner is traveling. Furthermore, if the owner is traveling at night, it can suggest well-lit, busy routes. This improves the safety of the owner's movements.

[0136] The monitoring service system can estimate the owner's emotions and suggest learning programs based on those emotions. For example, if the owner wants to improve their concentration, it can suggest effective learning methods in a short amount of time. If the owner is relaxed, it can suggest a fun learning program. Furthermore, if the owner is stressed, it can suggest a program that allows them to learn while relaxing. This makes it possible to provide appropriate learning programs tailored to the owner's emotions. Emotion estimation is achieved using an emotion engine or generative AI.

[0137] The following briefly describes the processing flow for example form 2.

[0138] Step 1: The schedule management unit manages the owner's schedule. When the owner enters an appointment, the schedule management unit registers that appointment in the calendar and sets a reminder. For example, when an appointment for a meeting, event, or task is entered, each appointment is registered in the calendar and a reminder is set in advance. Step 2: The crisis detection unit detects when the owner is in danger. It detects abnormal movements by the owner and initiates an emergency call. For example, if the owner collapses due to sudden illness, is kidnapped, or is involved in a traffic accident, the unit detects the situation and notifies the appropriate authorities. Step 3: The reporting unit makes a report based on the crisis detected by the crisis detection unit. It tracks the owner's location and reports to the police and fire department. For example, it reports to the appropriate agency depending on the situation, such as kidnapping, sudden illness, or traffic accident. Step 4: The fraud detection unit and crime detection unit detect fraud and crime. The fraud detection unit analyzes the content of fraudulent phone calls, emails, and messages, and sends an alert to the parent if it determines that there is a possibility of fraud. The crime detection unit detects if the owner has been a victim of a crime and sends an alert to the parent. Step 5: The alert sending unit sends alerts to parents based on the results detected by the fraud detection unit and the crime detection unit. For example, it sends an alert to parents if it determines that there is a possibility of fraud or if a crime has been detected. Step 6: The character setting section allows you to create a friendly character. You can set the appearance and voice of your favorite character. For example, you can set the appearance and voice of an anime character, game character, or movie character.

[0139] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0140] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0141] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0142] Each of the multiple elements mentioned above, including the schedule management unit, pinch detection unit, notification unit, fraud detection unit, crime detection unit, alert transmission unit, and character setting unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the schedule management unit is implemented by the control unit 46A of the smart device 14, which registers the owner's schedule in a calendar and sets reminders. The pinch detection unit uses the camera 42 and sensors of the smart device 14 to detect the owner's movements and detect abnormalities. The notification unit is implemented by the identification processing unit 290 of the data processing unit 12, which notifies the police or fire department in emergencies. The fraud detection unit and crime detection unit are implemented by the identification processing unit 290 of the data processing unit 12, which analyze the possibility of fraud or crime. The alert transmission unit is implemented by the control unit 46A of the smart device 14, which sends alerts to the guardian. The character setting unit is implemented by the control unit 46A of the smart device 14, which sets the appearance and voice of the owner's favorite character. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0143] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0144] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0145] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0146] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0147] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0148] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0149] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0150] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0151] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0152] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0153] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0154] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0155] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0156] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0157] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0158] Each of the multiple elements mentioned above, including the schedule management unit, pinch detection unit, notification unit, fraud detection unit, crime detection unit, alert transmission unit, and character setting unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the schedule management unit is implemented by the control unit 46A of the smart glasses 214, which registers the owner's schedule in a calendar and sets reminders. The pinch detection unit detects the owner's movements using the camera 42 and sensors of the smart glasses 214 and detects abnormalities. The notification unit is implemented by the identification processing unit 290 of the data processing unit 12, which notifies the police or fire department in emergencies. The fraud detection unit and crime detection unit are implemented by the identification processing unit 290 of the data processing unit 12, which analyze the possibility of fraud or crime. The alert transmission unit is implemented by the control unit 46A of the smart glasses 214, which sends alerts to guardians. The character setting unit is implemented by the control unit 46A of the smart glasses 214, which sets the appearance and voice of the owner's favorite character. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0159] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0160] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0161] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0162] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0163] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0164] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0165] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0166] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0167] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0168] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0169] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0170] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0171] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0172] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0173] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0174] Each of the multiple elements described above, including the schedule management unit, pinch detection unit, notification unit, fraud detection unit, crime detection unit, alert transmission unit, and character setting unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the schedule management unit is implemented by the control unit 46A of the headset terminal 314, which registers the owner's schedule in the calendar and sets reminders. The pinch detection unit uses the camera 42 and sensors of the headset terminal 314 to detect the owner's movements and detect abnormalities. The notification unit is implemented by the identification processing unit 290 of the data processing unit 12, which notifies the police or fire department in emergencies. The fraud detection unit and crime detection unit are implemented by the identification processing unit 290 of the data processing unit 12, which analyze the possibility of fraud or crime. The alert transmission unit is implemented by the control unit 46A of the headset terminal 314, which sends alerts to the guardian. The character setting unit is implemented by the control unit 46A of the headset terminal 314, which sets the appearance and voice of the owner's favorite character. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0175] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0176] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0177] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0178] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0179] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0180] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0181] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0182] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0183] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0184] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0185] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0186] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0187] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0188] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0189] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0190] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0191] Each of the multiple elements mentioned above, including the schedule management unit, pinch detection unit, notification unit, fraud detection unit, crime detection unit, alert transmission unit, and character setting unit, is implemented in at least one of the robot 414 and the data processing unit 12. For example, the schedule management unit is implemented by the control unit 46A of the robot 414, which registers the owner's schedule in a calendar and sets reminders. The pinch detection unit uses the camera 42 and sensors of the robot 414 to detect the owner's movements and detect abnormalities. The notification unit is implemented by the identification processing unit 290 of the data processing unit 12, which notifies the police or fire department in emergencies. The fraud detection unit and crime detection unit are implemented by the identification processing unit 290 of the data processing unit 12, which analyze the possibility of fraud or crime. The alert transmission unit is implemented by the control unit 46A of the robot 414, which sends alerts to the guardian. The character setting unit is implemented by the control unit 46A of the robot 414, which sets the appearance and voice of the owner's favorite character. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0192] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0193] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0194] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0195] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0196] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0197] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0198] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0199] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0200] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0201] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0202] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0203] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0204] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0205] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0206] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0207] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0208] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0209] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0210] (Note 1) The schedule management department manages the owner's schedule, A crisis detection unit that detects when the owner is in danger, A notification unit that issues a notification based on a pinch detected by the aforementioned pinch detection unit, Fraud detection unit and crime detection unit that detect fraud and crime, An alert transmission unit that sends an alert to a guardian based on the results detected by the fraud detection unit and the crime detection unit, It includes a character setting section for creating approachable characters. A system characterized by the following features. (Note 2) The aforementioned schedule management unit, When the owner enters an appointment, it registers that appointment in the calendar and sets a reminder. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned pinch detection unit is The device detects abnormal movements by the owner and initiates an emergency call. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned reporting unit, Track the owner's location and report it to the police. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned fraud detection unit The system analyzes the content of fraudulent phone calls and sends an alert to parents if it is determined to be potentially fraudulent. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned crime detection unit, If the owner becomes a victim of a crime, the system will detect the situation and send an alert to the guardian. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned character design section is, The owner can customize the appearance and voice of their favorite character. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned schedule management unit, It estimates the owner's emotions and adjusts the way reminders are notified based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned schedule management unit, It analyzes the owner's past schedule history and proposes the optimal schedule. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned schedule management unit, The schedule is automatically prioritized based on the owner's current activity status. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned schedule management unit, It estimates the owner's emotions and changes the schedule display format based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned schedule management unit, Taking the owner's geographical location into consideration, it suggests local events relevant to the schedule. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned schedule management unit, Analyze the owner's social media activity and add relevant events and appointments to the schedule. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned pinch detection unit is It estimates the owner's emotions and adjusts the sensitivity of danger detection based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned pinch detection unit is Analyze the owner's past behavioral patterns to improve the accuracy of detecting abnormal behavior. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned pinch detection unit is It monitors the owner's biometric information in real time and detects abnormalities. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned pinch detection unit is It estimates the owner's emotions and changes the way it notifies the user of emergencies based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned pinch detection unit is By considering the owner's geographical location, abnormal behavior in specific areas is prioritized for detection. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned pinch detection unit is Analyze the owner's social media activity to detect signs of abnormal behavior early. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned reporting unit, The system estimates the owner's emotions and adjusts the urgency of the call based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned reporting unit, The system analyzes the owner's past reporting history and selects the most appropriate reporting destination. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned reporting unit, The system automatically generates the report content based on the owner's current situation. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned reporting unit, The system estimates the owner's emotions and modifies the reporting method based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned reporting unit, The system selects the most appropriate reporting destination, taking into account the owner's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned reporting unit, Analyze the owner's social media activity and add relevant information to the report. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned fraud detection unit It estimates the owner's emotions and adjusts the sensitivity of fraud detection based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned fraud detection unit By analyzing the owner's past communication history, signs of fraud can be detected early. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned fraud detection unit The system analyzes the owner's current communications in real time to determine the possibility of fraud. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned fraud detection unit It estimates the owner's emotions and modifies the fraud warning method based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned fraud detection unit By considering the owner's geographical location, the system prioritizes detecting potential fraud in specific areas. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned fraud detection unit Analyze the owner's social media activity to detect signs of fraud early. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned crime detection unit, It estimates the owner's emotions and adjusts the sensitivity of crime detection based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned crime detection unit, By analyzing the owner's past behavioral history, signs of criminal activity can be detected early. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned crime detection unit, The system analyzes the owner's current actions in real time to determine the possibility of criminal activity. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned crime detection unit, It estimates the owner's emotions and modifies the crime warning method based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned crime detection unit, By considering the owner's geographical location, the system prioritizes detecting potential crimes in specific areas. The system described in Appendix 1, characterized by the features described herein. (Note 37) The aforementioned crime detection unit, Analyze the owner's social media activity to detect signs of crime early. The system described in Appendix 1, characterized by the features described herein. (Note 38) The alert transmission unit, It estimates the owner's emotions and adjusts how alerts are sent based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 39) The alert transmission unit, The system analyzes the owner's past alert history and selects the optimal recipient for sending alerts. The system described in Appendix 1, characterized by the features described herein. (Note 40) The alert transmission unit, It estimates the owner's emotions and prioritizes alerts based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 41) The alert transmission unit, The system selects the optimal alert destination by considering the owner's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 42) The aforementioned character design section is, It estimates the owner's emotions and adjusts the character's expression based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 43) The aforementioned character design section is, It analyzes the owner's past character creation history and suggests the most suitable character. The system described in Appendix 1, characterized by the features described herein. (Note 44) The aforementioned character design section is, It estimates the owner's emotions and changes the character's appearance and voice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 45) The aforementioned character design section is, We will suggest local characters, taking into account the owner's geographical location. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0211] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The schedule management department manages the owner's schedule, A crisis detection unit that detects when the owner is in danger, A notification unit that issues a notification based on a pinch detected by the aforementioned pinch detection unit, Fraud detection unit and crime detection unit that detect fraud and crime, An alert transmission unit that sends an alert to a guardian based on the results detected by the fraud detection unit and the crime detection unit, It includes a character setting section for creating approachable characters. A system characterized by the following features.

2. The aforementioned schedule management unit, When the owner enters an appointment, it registers that appointment in the calendar and sets a reminder. The system according to feature 1.

3. The aforementioned pinch detection unit is The device detects abnormal movements by the owner and initiates an emergency call. The system according to feature 1.

4. The aforementioned reporting unit, Track the owner's location and report it to the police. The system according to feature 1.

5. The aforementioned fraud detection unit The system analyzes the content of fraudulent phone calls and sends an alert to parents if it is determined to be potentially fraudulent. The system according to feature 1.

6. The aforementioned crime detection unit, If the owner becomes a victim of a crime, the system will detect the situation and send an alert to the guardian. The system according to feature 1.

7. The aforementioned character design section is, The owner can customize the appearance and voice of their favorite character. The system according to feature 1.

8. The aforementioned schedule management unit, It estimates the owner's emotions and adjusts the way reminders are notified based on those emotions. The system according to feature 1.

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