System

Abstract

An object of a system according to an embodiment is to prevent a missing child.SOLUTION: A system includes a position information acquisition unit, a distance monitoring unit, and a voice guidance unit. The position information acquisition unit acquires position information of the child. The distance monitoring unit monitors the distance to the parent's smartphone terminal. The voice guidance unit guides the child by voice.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional technology, while items to prevent children from getting lost can pinpoint the location of a lost child, there was the problem that it was difficult to prevent a child from getting lost in the first place.

[0005] The system according to the embodiment aims to prevent children from getting lost. [Means for solving the problem]

[0006] The system according to the embodiment includes a location information acquisition unit, a distance monitoring unit, and a voice guidance unit. The location information acquisition unit acquires location information of the child. The distance monitoring unit monitors the distance from the parent's smartphone device. The voice guidance unit provides voice guidance to the child. [Effects of the Invention]

[0007] The system according to the embodiment can prevent children from getting lost. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

[0017] 1, a 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also 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 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0024] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may 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 a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The AI ​​for generating lost child prevention tags according to the embodiment of the present invention is a system in which, if a child becomes separated from their parent's smartphone device or strays significantly from the route to school, the lost child prevention tag speaks to the child and guides them to their parents or a police station. This ensures the safety of children and prevents them from getting lost.

[0029] The lost child prevention tag generation AI according to the embodiment includes a location information acquisition unit, a distance monitoring unit, and a voice guidance unit. The location information acquisition unit acquires the child's location information. For example, it constantly acquires the child's current location using GPS. The location information acquisition unit can also acquire highly accurate location information indoors using Wi-Fi or Bluetooth beacons. The distance monitoring unit monitors the distance from the parent's smartphone device. For example, it issues an alert if the distance exceeds a certain distance. The distance monitoring unit can also detect obstacles between the parent and child and issue a warning if there is a visual obstruction. The voice guidance unit provides voice guidance to the child. For example, if the generation AI determines that the child may be lost, it provides guidance such as, "You are too far from your mother. Please return to your original location" or "Go to the nearest police station and ask for help." This allows the lost child prevention tag generation AI according to the embodiment to ensure the safety of children and prevent them from getting lost.

[0030] The location information acquisition unit can analyze surrounding environmental sounds, detect dangerous situations, and issue a warning. The location information acquisition unit, for example, analyzes surrounding environmental sounds and issues a warning if the child is near a busy road. For example, it detects the sound of a car engine or a horn and provides audio guidance to the child, saying, "You are in a dangerous location. Please move to a safe location." The location information acquisition unit also issues a warning if the child is near a construction site or a noisy location. For example, it detects the sound of a drill or heavy machinery and provides audio guidance to the child, saying, "You are near a construction site. Please move to a safe location." The location information acquisition unit also issues a warning if the child is in a quiet location at night. For example, it detects silence at night and provides audio guidance to the child, saying, "You are in a quiet location at night. Please move to a safe location." In this way, the safety of children can be ensured by analyzing surrounding environmental sounds, detecting dangerous situations, and issuing a warning.

[0031] The location information acquisition unit can analyze the child's movement speed and direction and issue an alert if it detects abnormal movement. For example, the location information acquisition unit analyzes the child's movement speed and issues an alert if it detects a sudden change in speed. For example, if the child suddenly starts running or stops, it notifies the parent, "Sudden movement has been detected. Please make sure you are safe." The location information acquisition unit also analyzes the child's movement direction and issues an alert if the child is moving in a certain direction for a long period of time. For example, if the child is walking in the same direction for a long period of time, it notifies the parent, "You have been moving in the same direction for a long period of time. Please make sure you are safe." The location information acquisition unit also analyzes the child's movement speed and direction and issues an alert if it detects abnormal movement. For example, if the child is moving in a zigzag pattern, it notifies the parent, "Abnormal movement has been detected. Please make sure you are safe." In this way, by analyzing the child's movement speed and direction and notifying the parent if abnormal movement is detected, it is possible to ensure the child's safety.

[0032] The location information acquisition unit can acquire highly accurate location information indoors using Wi-Fi and Bluetooth beacons in addition to GPS. The location information acquisition unit can acquire highly accurate location information indoors using, for example, Wi-Fi signal strength in addition to GPS. For example, the location of a child can be identified based on the location of a Wi-Fi access point and notified to the parent. The location information acquisition unit can also acquire highly accurate location information indoors using Bluetooth beacons. For example, the location of a child can be identified based on Bluetooth beacons in a shopping mall and notified to the parent. The location information acquisition unit can also acquire highly accurate location information indoors and outdoors by combining GPS, Wi-Fi, and Bluetooth beacons. For example, the location information can be acquired outdoors using GPS, and indoors using Wi-Fi and Bluetooth beacons and notified to the parent. In this way, the child's location can be accurately determined by acquiring highly accurate location information indoors using Wi-Fi and Bluetooth beacons in addition to GPS.

[0033] The location information acquisition unit can compare the child's location information with the location information of other children and issue a warning if the child deviates from the group. For example, the location information acquisition unit compares the child's location information with the location information of other children and issues a warning if the child deviates from the group. For example, if a child is alone during a school field trip, the unit issues a warning saying, "You are separated from the group. Please make sure you are safe." The location information acquisition unit also compares the child's location information with the location information of other children and issues a warning if the child is not within a certain range. For example, if a child is separated from other children at a playground, the unit issues a warning saying, "You are separated from other children. Please make sure you are safe." The location information acquisition unit also compares the child's location information with the location information of other children and issues a warning if the child deviates from the group. For example, if a child is alone heading in a different direction on the way home from school, the unit issues a warning saying, "You are separated from the group. Please make sure you are safe." In this way, the child's safety can be ensured by comparing the child's location information with the location information of other children and issuing a warning if the child deviates from the group.

[0034] The distance monitoring unit can analyze the movements of people in the vicinity and assess the risk of getting lost in crowded places. For example, the distance monitoring unit monitors the distance from the parent's smartphone device and analyzes the movements of people in the vicinity to assess the risk of getting lost in crowded places. For example, if the child is in a crowded shopping mall, the unit notifies the child, "It's crowded. Please check your child's location." The distance monitoring unit also analyzes the movements of people in the vicinity and assesses the risk of getting lost in crowded places. For example, if the child is in a crowded event venue, the unit notifies the child, "It's crowded. Please check your child's location." The distance monitoring unit also monitors the distance from the parent's smartphone device and analyzes the movements of people in the vicinity to assess the risk of getting lost in crowded places. For example, if the child is in a crowded station platform, the unit notifies the child, "It's crowded. Please check your child's location." In this way, the safety of children can be ensured by analyzing the movements of people in the vicinity and assessing the risk of getting lost in crowded places.

[0035] The distance monitoring unit can detect obstacles between the parent and child and issue a warning if a visual obstruction exists. For example, the distance monitoring unit detects obstacles between the parent and child and issues a warning if a visual obstruction exists. For example, if a wall or building is between them, the unit issues a warning saying, "There is a visual obstruction. Please check your child's position." In addition to monitoring the distance, the distance monitoring unit can also detect obstacles between the parent and child and issue a warning if a visual obstruction exists. For example, if a wall or shelf is between them in a shopping mall, the unit issues a warning saying, "There is a visual obstruction. Please check your child's position." In addition, the distance monitoring unit can detect obstacles between the parent and child and issue a warning if a visual obstruction exists. For example, if a tree or playground equipment is between them in a park, the unit issues a warning saying, "There is a visual obstruction. Please check your child's position." In this way, the safety of the child can be ensured by detecting obstacles between the parent and child and issuing a warning if a visual obstruction exists.

[0036] The distance monitoring unit monitors the parent's heart rate and stress level and can issue an alert if an abnormality is detected. For example, the distance monitoring unit monitors the parent's heart rate in addition to the distance from the parent's smartphone device and issues an alert if an abnormality is detected. For example, if the heart rate suddenly rises, the distance monitoring unit issues a notification saying, "Your heart rate is rising. Please check your child's location." The distance monitoring unit also monitors the parent's stress level and issues an alert if an abnormality is detected. For example, if the stress level is high, the distance monitoring unit issues a notification saying, "Your stress level is high. Please check your child's location." The distance monitoring unit also monitors the parent's heart rate and stress level and issues an alert if an abnormality is detected. For example, if the heart rate suddenly rises and the stress level is high, the distance monitoring unit issues a notification saying, "Your heart rate and stress level are abnormal. Please check your child's location." In this way, by monitoring the parent's heart rate and stress level and issuing an alert if an abnormality is detected, the safety of the parent and child can be ensured.

[0037] The distance monitoring unit can monitor the communication status between the parent and child and issue a warning if the communication is interrupted. For example, the distance monitoring unit monitors voice calls between the parent and child and issues a warning if the communication is interrupted. For example, if the call is interrupted, it notifies the device, "The voice call has been interrupted. Please check your child's location." The distance monitoring unit also monitors video calls between the parent and child and issues a warning if the communication is interrupted. For example, if the video call is interrupted, it notifies the device, "The video call has been interrupted. Please check your child's location." The distance monitoring unit also monitors the communication status between the parent and child and issues a warning if the communication is interrupted. For example, if the voice call or video call is interrupted, it notifies the device, "Communication has been interrupted. Please check your child's location." In this way, by monitoring the communication status between the parent and child and issuing a warning if the communication is interrupted, the safety of the parent and child can be ensured.

[0038] The voice guidance unit can automatically adjust the language used according to the child's age and comprehension ability. For example, when providing voice guidance to a child, the generation AI automatically adjusts the language used according to the child's age. For example, it might provide simple instructions to a toddler, such as "Go back to your mother," and instructions to an elementary school child, such as "Go back to where you were." The voice guidance unit also automatically adjusts the language used according to the child's comprehension ability. For example, it might provide detailed instructions to a child with a high level of comprehension and simple instructions to a child with a low level of comprehension. The voice guidance unit also automatically adjusts the language used according to the child's age and comprehension ability. For example, it might provide instructions such as "Go to the nearest police station and ask for help" depending on the child's age and comprehension ability. This automatically adjusts the language used according to the child's age and comprehension ability, making it possible to provide appropriate guidance to children.

[0039] The voice guidance unit can analyze the environmental sounds around the child and provide guidance at the appropriate time. For example, the generation AI of the voice guidance unit analyzes the environmental sounds around the child and provides voice guidance at the appropriate time. For example, if the surroundings are quiet, the voice guidance unit may provide guidance such as "Go back to your mother." The voice guidance unit also analyzes the environmental sounds around the child and refrains from providing voice guidance in noisy places. For example, the voice guidance unit may refrain from providing voice guidance near busy roads and provide guidance after the child has moved to a safe place. The generation AI of the voice guidance unit also analyzes the environmental sounds around the child and provides voice guidance at the appropriate time. For example, when the surroundings become quiet, the voice guidance unit may provide guidance such as "Go to the nearest police box and ask for help." In this way, by analyzing the environmental sounds around the child and providing guidance at the appropriate time, it is possible to provide appropriate guidance to the child.

[0040] The audio guidance unit can provide visual guidance in addition to audio guidance. For example, the generation AI of the audio guidance unit displays a map on the smartphone screen in addition to audio guidance to provide visual guidance to the child. For example, the unit may provide guidance such as, "Look at the map and go to the nearest police box." The audio guidance unit also displays visual guidance on the smartphone screen in addition to audio guidance. For example, the unit may provide guidance such as, "Look at the map and go back to your mother." The audio guidance unit also provides visual guidance in addition to audio guidance. For example, the generation AI may display a map on the smartphone screen and provide guidance such as, "Go down this road." In this way, by providing visual guidance in addition to audio guidance, more effective guidance can be provided to children.

[0041] The voice guidance unit supports multiple languages ​​and can accommodate children who speak different languages. For example, the generation AI of the voice guidance unit supports multiple languages ​​and provides voice guidance to children. For example, guidance is provided in a language that children can understand, such as English, Spanish, or Chinese. In addition, when providing voice guidance to children, the generation AI also accommodates children who speak different languages. For example, guidance is provided in an appropriate language depending on the child's language setting. In addition, the generation AI of the voice guidance unit supports multiple languages ​​and can accommodate children who speak different languages. For example, guidance is provided in a foreign child traveling in their native language. In this way, by supporting multiple languages ​​and accommodating children who speak different languages, appropriate guidance can be provided to a greater number of children.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The AI ​​for generating lost-prevention tags can further be equipped with a battery monitoring unit. The battery monitoring unit constantly monitors the tag's remaining battery level and notifies the parent when it gets low. For example, if the battery level drops below 20%, it will notify the parent, "The battery is low. Please charge." The battery monitoring unit can also monitor the battery's deterioration status and issue a notification urging the parent to replace the battery if it is deteriorating. For example, it will notify the parent, "The battery is deteriorating. Please consider replacing it." This allows the parent to constantly monitor the battery's status and charge or replace it at the appropriate time, thereby maintaining the functionality of the lost-prevention tag.

[0044] The AI ​​for generating lost child tags can further be equipped with a temperature monitoring unit. The temperature monitoring unit monitors the temperature around the child and issues a warning if there is an abnormal temperature change. For example, if the ambient temperature rises suddenly, it will issue a warning saying, "The ambient temperature is getting high. Please move to a cooler place." The temperature monitoring unit also issues a warning if the ambient temperature drops. For example, it will issue a warning saying, "The ambient temperature is getting low. Please move to a warmer place." This makes it possible to monitor the temperature around the child and ensure the child's safety by prompting appropriate action if there is an abnormal temperature change.

[0045] The AI ​​for generating lost child tags can also be equipped with a health monitoring unit. This monitors a child's heart rate and body temperature, and notifies parents if any abnormalities are detected. For example, if the child's heart rate suddenly rises, the unit will send a message saying, "Your heart rate is increasing. Please check your child's condition." It can also issue a warning if the child's body temperature is abnormally high or low. For example, it may send a message saying, "Your body temperature is high. Consult a doctor." or "Your body temperature is low. Move to a warmer place." This allows the AI ​​to constantly monitor a child's health and respond quickly to any abnormalities, ensuring the child's safety.

[0046] The AI ​​for generating lost child tags can further be equipped with an activity monitoring unit. The activity monitoring unit monitors a child's amount of exercise and activity patterns, and notifies parents if any abnormalities are detected. For example, if the amount of exercise is extremely low, the unit will notify parents, saying, "Your child is not getting enough exercise. Please check on your child." It will also issue a warning if the activity pattern is different from normal. For example, it will notify parents, saying, "Your activity pattern is different from normal. Please check on your child." This allows the system to constantly monitor a child's amount of exercise and activity patterns, and respond quickly if any abnormalities are detected, ensuring the child's health and safety.

[0047] The AI ​​for generating lost child tags can also be equipped with a voice recognition unit. The voice recognition unit recognizes the child's voice and notifies the parent if it detects certain keywords. For example, if a child calls out "help," the unit will notify the parent, "Your child is asking for help. Please check their location." The voice recognition unit also analyzes the tone and volume of the child's voice and issues an alert if there is an abnormality. For example, it will notify the parent, "Your child's voice is different from usual. Please check their condition." This allows the system to constantly monitor the child's voice and respond quickly if an abnormality is detected, ensuring the child's safety.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The location information acquisition unit acquires the child's location information. For example, the location information acquisition unit constantly acquires the child's current location using GPS. The location information acquisition unit can also acquire highly accurate location information indoors by using Wi-Fi or Bluetooth beacons. Step 2: The distance monitoring unit monitors the distance to the parent's smartphone. For example, it issues an alert if the distance exceeds a certain distance. The distance monitoring unit can also detect obstacles between the parent and child and issue a warning if there is a visual obstruction. Step 3: The voice guidance unit provides voice guidance to the child. For example, if the AI ​​generator determines that the child may be lost, it will provide guidance such as, "You're too far away from your mother. Return to where you came from," or "Go to the nearest police station and ask for help."

[0050] (Example 2) The AI ​​for generating lost child prevention tags according to the embodiment of the present invention is a system in which, if a child becomes separated from their parent's smartphone device or strays significantly from the route to school, the lost child prevention tag speaks to the child and guides them to their parents or a police station. This ensures the safety of children and prevents them from getting lost.

[0051] The lost child prevention tag generation AI according to the embodiment includes a location information acquisition unit, a distance monitoring unit, and a voice guidance unit. The location information acquisition unit acquires the child's location information. For example, it constantly acquires the child's current location using GPS. The location information acquisition unit can also acquire highly accurate location information indoors using Wi-Fi or Bluetooth beacons. The distance monitoring unit monitors the distance from the parent's smartphone device. For example, it issues an alert if the distance exceeds a certain distance. The distance monitoring unit can also detect obstacles between the parent and child and issue a warning if there is a visual obstruction. The voice guidance unit provides voice guidance to the child. For example, if the generation AI determines that the child may be lost, it provides guidance such as, "You are too far from your mother. Please return to your original location" or "Go to the nearest police station and ask for help." This allows the lost child prevention tag generation AI according to the embodiment to ensure the safety of children and prevent them from getting lost.

[0052] The location information acquisition unit can analyze surrounding environmental sounds, detect dangerous situations, and issue a warning. The location information acquisition unit, for example, analyzes surrounding environmental sounds and issues a warning if the child is near a busy road. For example, it detects the sound of a car engine or a horn and provides audio guidance to the child, saying, "You are in a dangerous location. Please move to a safe location." The location information acquisition unit also issues a warning if the child is near a construction site or a noisy location. For example, it detects the sound of a drill or heavy machinery and provides audio guidance to the child, saying, "You are near a construction site. Please move to a safe location." The location information acquisition unit also issues a warning if the child is in a quiet location at night. For example, it detects silence at night and provides audio guidance to the child, saying, "You are in a quiet location at night. Please move to a safe location." In this way, the safety of children can be ensured by analyzing surrounding environmental sounds, detecting dangerous situations, and issuing a warning.

[0053] The location information acquisition unit can analyze the child's movement speed and direction and issue an alert if it detects abnormal movement. For example, the location information acquisition unit analyzes the child's movement speed and issues an alert if it detects a sudden change in speed. For example, if the child suddenly starts running or stops, it notifies the parent, "Sudden movement has been detected. Please make sure you are safe." The location information acquisition unit also analyzes the child's movement direction and issues an alert if the child is moving in a certain direction for a long period of time. For example, if the child is walking in the same direction for a long period of time, it notifies the parent, "You have been moving in the same direction for a long period of time. Please make sure you are safe." The location information acquisition unit also analyzes the child's movement speed and direction and issues an alert if it detects abnormal movement. For example, if the child is moving in a zigzag pattern, it notifies the parent, "Abnormal movement has been detected. Please make sure you are safe." In this way, by analyzing the child's movement speed and direction and notifying the parent if abnormal movement is detected, it is possible to ensure the child's safety.

[0054] The location information acquisition unit can use the emotion estimation function to estimate emotions from the child's voice and facial expression and notify the parent if the child is feeling stressed or anxious. The location information acquisition unit, for example, analyzes the child's voice and notifies the parent if the child is feeling stressed or anxious using the emotion estimation function. For example, the emotion is estimated from the tone of voice and manner of speaking, and the parent is notified, saying, "Your child is feeling stressed. Please make sure they are safe." The location information acquisition unit can also analyze the child's facial expression and notify the parent if the child is feeling anxious using the emotion estimation function. For example, the emotion is estimated from the facial expression, and the parent is notified, saying, "Your child is feeling anxious. Please make sure they are safe." The location information acquisition unit can also analyze the child's voice and facial expression and notify the parent if the child is feeling stressed or anxious using the emotion estimation function. For example, the emotion is estimated from the tone of voice and facial expression, and the parent is notified, saying, "Your child is feeling stressed or anxious. Please make sure they are safe." In this way, the child's safety can be ensured by estimating emotions from the child's voice and facial expression and notifying the parent if the child is feeling stressed or anxious.

[0055] The location information acquisition unit can acquire highly accurate location information indoors using Wi-Fi and Bluetooth beacons in addition to GPS. The location information acquisition unit can acquire highly accurate location information indoors using, for example, Wi-Fi signal strength in addition to GPS. For example, the location of a child can be identified based on the location of a Wi-Fi access point and notified to the parent. The location information acquisition unit can also acquire highly accurate location information indoors using Bluetooth beacons. For example, the location of a child can be identified based on Bluetooth beacons in a shopping mall and notified to the parent. The location information acquisition unit can also acquire highly accurate location information indoors and outdoors by combining GPS, Wi-Fi, and Bluetooth beacons. For example, the location information can be acquired outdoors using GPS, and indoors using Wi-Fi and Bluetooth beacons and notified to the parent. In this way, the child's location can be accurately determined by acquiring highly accurate location information indoors using Wi-Fi and Bluetooth beacons in addition to GPS.

[0056] The location information acquisition unit can compare the child's location information with the location information of other children and issue a warning if the child deviates from the group. For example, the location information acquisition unit compares the child's location information with the location information of other children and issues a warning if the child deviates from the group. For example, if a child is alone during a school field trip, the unit issues a warning saying, "You are separated from the group. Please make sure you are safe." The location information acquisition unit also compares the child's location information with the location information of other children and issues a warning if the child is not within a certain range. For example, if a child is separated from other children at a playground, the unit issues a warning saying, "You are separated from other children. Please make sure you are safe." The location information acquisition unit also compares the child's location information with the location information of other children and issues a warning if the child deviates from the group. For example, if a child is alone heading in a different direction on the way home from school, the unit issues a warning saying, "You are separated from the group. Please make sure you are safe." In this way, the child's safety can be ensured by comparing the child's location information with the location information of other children and issuing a warning if the child deviates from the group.

[0057] The location information acquisition unit can use the emotion estimation function to notify parents whether their child is having fun at a specific location. The location information acquisition unit, for example, uses the emotion estimation function to notify parents whether their child is having fun at an amusement park. For example, the location information acquisition unit analyzes a child's laughter or excited voice and notifies the parent, "Your child is having fun at the amusement park." The location information acquisition unit also uses the emotion estimation function to notify parents whether their child is having fun at a park. For example, the location information acquisition unit analyzes a child's smile or happy facial expression and notifies the parent, "Your child is having fun at the park." The location information acquisition unit also uses the emotion estimation function to notify parents whether their child is having fun at a specific location. For example, the location information acquisition unit analyzes a child's tone of voice and facial expression and notifies the parent, "Your child is having fun at a specific location." In this way, by notifying parents whether their child is having fun at a specific location, the parents can understand the situation of their child.

[0058] The distance monitoring unit can analyze the movements of people in the vicinity and assess the risk of getting lost in crowded places. For example, the distance monitoring unit monitors the distance from the parent's smartphone device and analyzes the movements of people in the vicinity to assess the risk of getting lost in crowded places. For example, if the child is in a crowded shopping mall, the unit notifies the child, "It's crowded. Please check your child's location." The distance monitoring unit also analyzes the movements of people in the vicinity and assesses the risk of getting lost in crowded places. For example, if the child is in a crowded event venue, the unit notifies the child, "It's crowded. Please check your child's location." The distance monitoring unit also monitors the distance from the parent's smartphone device and analyzes the movements of people in the vicinity to assess the risk of getting lost in crowded places. For example, if the child is in a crowded station platform, the unit notifies the child, "It's crowded. Please check your child's location." In this way, the safety of children can be ensured by analyzing the movements of people in the vicinity and assessing the risk of getting lost in crowded places.

[0059] The distance monitoring unit can detect obstacles between the parent and child and issue a warning if a visual obstruction exists. For example, the distance monitoring unit detects obstacles between the parent and child and issues a warning if a visual obstruction exists. For example, if a wall or building is between them, the unit issues a warning saying, "There is a visual obstruction. Please check your child's position." In addition to monitoring the distance, the distance monitoring unit can also detect obstacles between the parent and child and issue a warning if a visual obstruction exists. For example, if a wall or shelf is between them in a shopping mall, the unit issues a warning saying, "There is a visual obstruction. Please check your child's position." In addition, the distance monitoring unit can detect obstacles between the parent and child and issue a warning if a visual obstruction exists. For example, if a tree or playground equipment is between them in a park, the unit issues a warning saying, "There is a visual obstruction. Please check your child's position." In this way, the safety of the child can be ensured by detecting obstacles between the parent and child and issuing a warning if a visual obstruction exists.

[0060] The distance monitoring unit can use the emotion estimation function to send a reassuring message to a child when a parent feels anxious or impatient. The distance monitoring unit, for example, uses the emotion estimation function to send a reassuring message to a child when a parent feels anxious or impatient. For example, the distance monitoring unit may provide voice guidance such as, "Mom is worried about you. Let's go back to where you were." The distance monitoring unit also analyzes the parent's emotions and sends a reassuring message to a child when the parent feels anxious or impatient. For example, the distance monitoring unit may provide voice guidance such as, "Dad is worried about you. Go to the nearest police station and ask for help." The distance monitoring unit also uses the emotion estimation function to send a reassuring message to a child when the parent feels anxious or impatient. For example, the distance monitoring unit may provide voice guidance such as, "Mom is worried about you. Please move to a safe place." In this way, the safety of parent and child can be ensured by sending a reassuring message to a child when the parent feels anxious or impatient.

[0061] The distance monitoring unit monitors the parent's heart rate and stress level and can issue an alert if an abnormality is detected. For example, the distance monitoring unit monitors the parent's heart rate in addition to the distance from the parent's smartphone device and issues an alert if an abnormality is detected. For example, if the heart rate suddenly rises, the distance monitoring unit issues a notification saying, "Your heart rate is rising. Please check your child's location." The distance monitoring unit also monitors the parent's stress level and issues an alert if an abnormality is detected. For example, if the stress level is high, the distance monitoring unit issues a notification saying, "Your stress level is high. Please check your child's location." The distance monitoring unit also monitors the parent's heart rate and stress level and issues an alert if an abnormality is detected. For example, if the heart rate suddenly rises and the stress level is high, the distance monitoring unit issues a notification saying, "Your heart rate and stress level are abnormal. Please check your child's location." In this way, by monitoring the parent's heart rate and stress level and issuing an alert if an abnormality is detected, the safety of the parent and child can be ensured.

[0062] The distance monitoring unit can monitor the communication status between the parent and child and issue a warning if the communication is interrupted. For example, the distance monitoring unit monitors voice calls between the parent and child and issues a warning if the communication is interrupted. For example, if the call is interrupted, it notifies the device, "The voice call has been interrupted. Please check your child's location." The distance monitoring unit also monitors video calls between the parent and child and issues a warning if the communication is interrupted. For example, if the video call is interrupted, it notifies the device, "The video call has been interrupted. Please check your child's location." The distance monitoring unit also monitors the communication status between the parent and child and issues a warning if the communication is interrupted. For example, if the voice call or video call is interrupted, it notifies the device, "Communication has been interrupted. Please check your child's location." In this way, by monitoring the communication status between the parent and child and issuing a warning if the communication is interrupted, the safety of the parent and child can be ensured.

[0063] The voice guidance unit can automatically adjust the language used according to the child's age and comprehension ability. For example, when providing voice guidance to a child, the generation AI automatically adjusts the language used according to the child's age. For example, it might provide simple instructions to a toddler, such as "Go back to your mother," and instructions to an elementary school child, such as "Go back to where you were." The voice guidance unit also automatically adjusts the language used according to the child's comprehension ability. For example, it might provide detailed instructions to a child with a high level of comprehension and simple instructions to a child with a low level of comprehension. The voice guidance unit also automatically adjusts the language used according to the child's age and comprehension ability. For example, it might provide instructions such as "Go to the nearest police station and ask for help" depending on the child's age and comprehension ability. This automatically adjusts the language used according to the child's age and comprehension ability, making it possible to provide appropriate guidance to children.

[0064] The voice guidance unit can analyze the environmental sounds around the child and provide guidance at the appropriate time. For example, the generation AI of the voice guidance unit analyzes the environmental sounds around the child and provides voice guidance at the appropriate time. For example, if the surroundings are quiet, the voice guidance unit may provide guidance such as "Go back to your mother." The voice guidance unit also analyzes the environmental sounds around the child and refrains from providing voice guidance in noisy places. For example, the voice guidance unit may refrain from providing voice guidance near busy roads and provide guidance after the child has moved to a safe place. The generation AI of the voice guidance unit also analyzes the environmental sounds around the child and provides voice guidance at the appropriate time. For example, when the surroundings become quiet, the voice guidance unit may provide guidance such as "Go to the nearest police box and ask for help." In this way, by analyzing the environmental sounds around the child and providing guidance at the appropriate time, it is possible to provide appropriate guidance to the child.

[0065] The voice guidance unit can use the emotion estimation function to provide voice guidance to reassure a child when he or she feels anxious or scared. The voice guidance unit, for example, uses the emotion estimation function to provide voice guidance to reassure a child when he or she feels anxious. For example, the voice guidance unit may provide guidance such as, "It's okay. Let's go back to your mother." The voice guidance unit also analyzes the child's emotions and provides voice guidance to reassure a child when he or she feels scared. For example, the voice guidance unit may provide guidance such as, "Don't be scared. Go to the nearest police station and ask for help." The voice guidance unit also uses the emotion estimation function to provide voice guidance to reassure a child when he or she feels anxious or scared. For example, the voice guidance unit may provide guidance such as, "Your mother will be there soon. Don't worry." In this way, by providing voice guidance to reassure a child when he or she feels anxious or scared, it is possible to ensure the psychological safety of the child.

[0066] The audio guidance unit can provide visual guidance in addition to audio guidance. For example, the generation AI of the audio guidance unit displays a map on the smartphone screen in addition to audio guidance to provide visual guidance to the child. For example, the unit may provide guidance such as, "Look at the map and go to the nearest police box." The audio guidance unit also displays visual guidance on the smartphone screen in addition to audio guidance. For example, the unit may provide guidance such as, "Look at the map and go back to your mother." The audio guidance unit also provides visual guidance in addition to audio guidance. For example, the generation AI may display a map on the smartphone screen and provide guidance such as, "Go down this road." In this way, by providing visual guidance in addition to audio guidance, more effective guidance can be provided to children.

[0067] The voice guidance unit supports multiple languages ​​and can accommodate children who speak different languages. For example, the generation AI of the voice guidance unit supports multiple languages ​​and provides voice guidance to children. For example, guidance is provided in a language that children can understand, such as English, Spanish, or Chinese. In addition, when providing voice guidance to children, the generation AI also accommodates children who speak different languages. For example, guidance is provided in an appropriate language depending on the child's language setting. In addition, the generation AI of the voice guidance unit supports multiple languages ​​and can accommodate children who speak different languages. For example, guidance is provided in a foreign child traveling in their native language. In this way, by supporting multiple languages ​​and accommodating children who speak different languages, appropriate guidance can be provided to a greater number of children.

[0068] The voice guidance unit can use the emotion estimation function to provide additional information about a place or suggest activities when a child is having fun at a specific place. For example, the voice guidance unit can use the emotion estimation function to provide additional information about a place when a child is having fun at an amusement park. For example, the voice guidance unit can provide guidance such as, "This attraction is recommended next." The voice guidance unit can also analyze the child's emotions and suggest activities when the child is having fun at the park. For example, the voice guidance unit can provide guidance such as, "Try playing on this playground equipment." The voice guidance unit can also use the emotion estimation function to provide additional information about a place or suggest activities when a child is having fun at a specific place. For example, the voice guidance unit can provide guidance such as, "There are other fun activities available at this place." In this way, when a child is having fun at a specific place, the voice guidance unit can provide additional information about the place or suggest activities, thereby enriching the child's experience.

[0069] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0070] The AI ​​for generating lost-prevention tags can further be equipped with a battery monitoring unit. The battery monitoring unit constantly monitors the tag's remaining battery level and notifies the parent when it gets low. For example, if the battery level drops below 20%, it will notify the parent, "The battery is low. Please charge." The battery monitoring unit can also monitor the battery's deterioration status and issue a notification urging the parent to replace the battery if it is deteriorating. For example, it will notify the parent, "The battery is deteriorating. Please consider replacing it." This allows the parent to constantly monitor the battery's status and charge or replace it at the appropriate time, thereby maintaining the functionality of the lost-prevention tag.

[0071] The AI ​​for generating lost child tags can further be equipped with a temperature monitoring unit. The temperature monitoring unit monitors the temperature around the child and issues a warning if there is an abnormal temperature change. For example, if the ambient temperature rises suddenly, it will issue a warning saying, "The ambient temperature is getting high. Please move to a cooler place." The temperature monitoring unit also issues a warning if the ambient temperature drops. For example, it will issue a warning saying, "The ambient temperature is getting low. Please move to a warmer place." This makes it possible to monitor the temperature around the child and ensure the child's safety by prompting appropriate action if there is an abnormal temperature change.

[0072] The AI ​​for generating lost child tags can also be equipped with a health monitoring unit. This monitors a child's heart rate and body temperature, and notifies parents if any abnormalities are detected. For example, if the child's heart rate suddenly rises, the unit will send a message saying, "Your heart rate is increasing. Please check your child's condition." It can also issue a warning if the child's body temperature is abnormally high or low. For example, it may send a message saying, "Your body temperature is high. Consult a doctor." or "Your body temperature is low. Move to a warmer place." This allows the AI ​​to constantly monitor a child's health and respond quickly to any abnormalities, ensuring the child's safety.

[0073] The AI ​​for generating lost child tags can further be equipped with an activity monitoring unit. The activity monitoring unit monitors a child's amount of exercise and activity patterns, and notifies parents if any abnormalities are detected. For example, if the amount of exercise is extremely low, the unit will notify parents, saying, "Your child is not getting enough exercise. Please check on your child." It will also issue a warning if the activity pattern is different from normal. For example, it will notify parents, saying, "Your activity pattern is different from normal. Please check on your child." This allows the system to constantly monitor a child's amount of exercise and activity patterns, and respond quickly if any abnormalities are detected, ensuring the child's health and safety.

[0074] The AI ​​for generating lost child tags can also be equipped with a voice recognition unit. The voice recognition unit recognizes the child's voice and notifies the parent if it detects certain keywords. For example, if a child calls out "help," the unit will notify the parent, "Your child is asking for help. Please check their location." The voice recognition unit also analyzes the tone and volume of the child's voice and issues an alert if there is an abnormality. For example, it will notify the parent, "Your child's voice is different from usual. Please check their condition." This allows the system to constantly monitor the child's voice and respond quickly if an abnormality is detected, ensuring the child's safety.

[0075] The lost child prevention tag generation AI can also use its emotion estimation function to notify parents if their child feels anxious or scared in a specific location. For example, if a child feels anxious in a dark place or a crowded place, the system will notify parents, saying, "Your child is feeling anxious. Please check their location." The emotion estimation function can also be used to issue a warning if a child feels scared in a specific location. For example, the system will notify parents, saying, "Your child is feeling scared. Please check their location." This ensures the psychological safety of children by notifying parents if their child feels anxious or scared in a specific location.

[0076] The lost child prevention tag generation AI can also use its emotion estimation function to provide additional information about a location if the child is feeling excited or happy at a particular place. For example, if a child is excited at an amusement park, the AI ​​can suggest, "This attraction is also recommended." The emotion estimation function can also be used to suggest activities if the child is feeling happy at a park. For example, the AI ​​can suggest, "This playground equipment is also fun." This allows the AI ​​to provide additional information about a location if the child is feeling excited or happy at a particular place, enriching the child's experience.

[0077] The lost child prevention tag generation AI can also use its emotion estimation function to issue a notification encouraging a child to take a break if they feel tired in a specific location. For example, if a child is tired after walking for a long time, it can prompt them to "take a short break." The emotion estimation function can also be used to encourage a child to take a break if they feel tired in a specific location. For example, it can prompt them to "take a rest on a bench." This ensures the health and safety of children by encouraging them to take a break if they feel tired in a specific location.

[0078] The lost child prevention tag generation AI can also use its emotion estimation function to provide educational information about a particular place if the child is interested in that place. For example, if a child is interested in an exhibit at a museum, the AI ​​can prompt them with, "Would you like to know more about this exhibit?". The emotion estimation function can also be used to provide information about an animal that the child is interested in at the zoo. For example, the AI ​​can prompt them with, "Would you like to know more about this animal?". In this way, if a child is interested in a particular place, educational information about that place can be provided, deepening the child's knowledge.

[0079] The lost child prevention tag generation AI can also use its emotion estimation function to make suggestions for relaxation if a child feels stressed in a specific location. For example, if a child feels stressed in a crowded place, it can advise them to "move to a quieter place." The emotion estimation function can also be used to make suggestions for relaxation if a child feels stressed in a specific location. For example, it can advise them to "take a deep breath and relax." In this way, by making suggestions for relaxation if a child feels stressed in a specific location, it is possible to ensure the child's psychological safety.

[0080] The processing flow of the second embodiment will be briefly explained below.

[0081] Step 1: The location information acquisition unit acquires the child's location information. For example, the location information acquisition unit constantly acquires the child's current location using GPS. The location information acquisition unit can also acquire highly accurate location information indoors by using Wi-Fi or Bluetooth beacons. Step 2: The distance monitoring unit monitors the distance to the parent's smartphone. For example, it issues an alert if the distance exceeds a certain distance. The distance monitoring unit can also detect obstacles between the parent and child and issue a warning if there is a visual obstruction. Step 3: The voice guidance unit provides voice guidance to the child. For example, if the AI ​​generator determines that the child may be lost, it will provide guidance such as, "You're too far away from your mother. Return to where you came from," or "Go to the nearest police station and ask for help."

[0082] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0083] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0084] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, 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.

[0085] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0086] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0087] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0088] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0089] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0090] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0091] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0092] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0093] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0094] The storage 32 stores a data generation model 58 and an 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0095] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0096] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0097] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0098] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0099] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0100] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0101] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0102] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0103] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0104] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0105] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0106] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0107] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0108] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0109] The storage 32 stores a data generation model 58 and an 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0110] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0111] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0112] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0113] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0114] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0115] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0116] 7, a 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.

[0117] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0118] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0119] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0120] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0121] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0122] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0123] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0124] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0125] The storage 32 stores a data generation model 58 and an 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0126] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0127] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0128] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0129] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0130] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0131] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0132] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0133] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0134] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0135] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0136] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0137] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0138] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0139] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0140] 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.

[0141] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0142] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0143] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific process may be a single processor.

[0144] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0145] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0146] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0147] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0148] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0149] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. Equipped with a GPS tag to prevent children from getting lost, The lost prevention tag is a location information acquisition unit that acquires location information of a child; A distance monitoring unit that monitors the distance to the parent's smartphone device; and a voice guidance unit that provides voice guidance to the child. A system characterized by:

2. The location information acquisition unit Analyzes surrounding environmental sounds, detects dangerous situations, and issues a warning 2. The system of claim 1.

3. The location information acquisition unit Analyzes the speed and direction of a child's movements and issues an alert if abnormal movements are detected.

2. The system of claim 1.

4. The location information acquisition unit Inferring emotions from the child's voice and facial expressions and notifying the parent if the child is feeling stressed or anxious 2. The system of claim 1.

5. The location information acquisition unit In addition to the GPS, the Wi-Fi and Bluetooth beacons are used to obtain highly accurate location information even indoors.

2. The system of claim 1.

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