System

Abstract

The system according to the embodiment aims to quickly and safely guide a user and ensure communication in an emergency situation.SOLUTION: A system according to an embodiment includes a generation unit, a navigation unit, and a communication unit. The generation unit generates information corresponding to the emergency scenario. The navigation unit guides the user based on the information generated by the generation unit. The communication unit performs emergency communication between the users guided by the navigation unit or between the user and the rescue team.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] Conventional technologies do not adequately provide information or communication means to guide users quickly and safely in an emergency, and there is room for improvement.

[0005] The system according to the embodiment aims to guide users quickly and safely in an emergency and ensure communication. [Means for solving the problem]

[0006] A system according to an embodiment includes a generation unit, a navigation unit, and a communication unit. The generation unit generates information corresponding to an emergency scenario. The navigation unit guides a user based on the information generated by the generation unit. The communication unit performs emergency communication between users guided by the navigation unit or between the user and a rescue team. [Effects of the Invention]

[0007] The system according to the embodiment can guide users quickly and safely in an emergency and ensure communication. [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) An emergency support system according to an embodiment of the present invention generates information corresponding to an emergency scenario, guides users to safe evacuation shelters, and performs emergency communications. The emergency support system uses a generation AI to generate information corresponding to an emergency scenario, and the AR glasses combine navigation and audio guidance to guide the user to a safe evacuation shelter. The emergency support system also performs emergency communications between users or between users and rescue teams. For example, in the event of a disaster such as an earthquake or fire, the generation AI generates information on evacuation routes and safe evacuation shelters appropriate to the situation. This information is updated in real time and provided to the user. Next, based on the generated information, the emergency support system displays evacuation routes on the AR glasses' display and provides audio guidance to the user. This allows the user to confirm the evacuation route both visually and audibly, enabling quick and safe evacuation. Furthermore, when a user encounters an emergency, the emergency support system can send emergency messages to other users or rescue teams via the AR glasses. In particular, even if the communication network is down due to a disaster, information can be shared using a dedicated wireless communication function. This allows users to communicate with others and cooperate in evacuating even in an emergency. This allows the emergency support system to guide users quickly and safely in emergency situations and ensure communication. For example, in the event of an earthquake, the generation AI will generate evacuation routes in real time, and the AR glasses will guide users based on that information. Furthermore, even if the communication network is down, users can still contact other users and rescue teams using the dedicated wireless communication function. This ensures the safety of users in emergencies.

[0029] An emergency support system according to an embodiment includes a generation unit, a navigation unit, and a communication unit. The generation unit generates information corresponding to an emergency scenario. When a disaster such as an earthquake or fire occurs, the generation unit generates information on evacuation routes and safe shelters according to the situation using, for example, a generation AI. The generation unit can also update information in real time using the generation AI and provide the information to a user. For example, the generation AI analyzes the occurrence of a disaster and generates an optimal evacuation route. The navigation unit guides a user based on the information generated by the generation unit. For example, the navigation unit displays an evacuation route on a display of AR glasses, and an audio guide instructs the user on the direction to travel. The navigation unit can also perform real-time navigation based on the generated information, taking into account the user's current location. For example, the navigation unit displays an optimal evacuation route based on the user's current location. The communication unit performs emergency communication between users guided by the navigation unit or between the user and a rescue team. The communication unit can share information using a dedicated wireless communication function, even when the communication network is down due to a disaster or other reason. In addition, when a user encounters an emergency, the communication unit can also send an emergency message to other users or a rescue team. For example, the communication unit may use a dedicated wireless communication function to send an emergency message including the user's current location information. This allows the emergency support system according to the embodiment to quickly and safely guide the user in an emergency and ensure communication.

[0030] In the event of an earthquake or fire, the generation unit can generate information on evacuation routes or safe evacuation shelters according to the situation. For example, in the event of an earthquake, the generation unit uses the generation AI to generate evacuation routes that take into account the risk of building collapse. In addition, in the event of a fire, the generation unit can also use the generation AI to generate routes that avoid the spread of smoke. Furthermore, in the event of a flood, the generation unit can also use the generation AI to generate evacuation routes to higher ground. This makes it possible to provide appropriate evacuation information in the event of a disaster. Some or all of the above-mentioned processing in the generation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the generation unit can input the disaster occurrence situation into the generation AI and have the generation AI execute information on evacuation routes and safe evacuation shelters.

[0031] The navigation unit can display an evacuation route on the display of the AR glasses based on the generated information and provide audio guidance to instruct the user on the direction of travel. For example, the navigation unit can display an evacuation route on the display of the AR glasses based on the generated information. The navigation unit can also provide audio guidance to instruct the user on the direction of travel. For example, the navigation unit can display arrows and routes on the display of the AR glasses and provide instructions such as "Turn right" through audio guidance. The navigation unit can also provide real-time navigation in consideration of the user's current location. For example, the navigation unit can display an optimal evacuation route based on the user's current location and provide audio guidance to instruct the user on the direction of travel. This allows the user to confirm the evacuation route both visually and audibly. Some or all of the above-described processing in the navigation unit can be performed using, for example, a generation AI, or can be performed without using a generation AI. For example, the navigation unit can input the generated information to a generation AI and have the generation AI display the evacuation route and provide audio guidance instructions.

[0032] The communication unit can share information using a dedicated wireless communication function even when the communication network goes down due to a disaster. For example, when the communication network goes down due to a disaster, the communication unit shares information using the dedicated wireless communication function. For example, the communication unit uses the dedicated wireless communication function to send an emergency message including the user's current location information. The communication unit can also send an emergency message to other users or a rescue team when a user encounters an emergency. For example, the communication unit uses the dedicated wireless communication function to send an emergency message including the user's current location information. This makes it possible to share information even when the communication network goes down. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI, or may be performed without using the generation AI. For example, the communication unit can input the content of the emergency message to the generation AI and cause the generation AI to send the emergency message.

[0033] The communication unit can transmit an emergency message to other users or a rescue team when a user encounters an emergency. For example, the communication unit transmits an emergency message to other users or a rescue team when a user encounters an emergency. For example, the communication unit transmits an emergency message including the user's current location information using a dedicated wireless communication function. The communication unit can also transmit an emergency message to other users or a rescue team when a user encounters an emergency. For example, the communication unit transmits an emergency message including the user's current location information using a dedicated wireless communication function. This allows for quick contact with others in an emergency. Some or all of the above-described processing in the communication unit may be performed using, for example, a generation AI, or may be performed without using the generation AI. For example, the communication unit can input the content of the emergency message to the generation AI and cause the generation AI to send the emergency message.

[0034] The generation unit can apply different information generation algorithms depending on the type of emergency. For example, in the case of an earthquake, the generation unit uses a generation AI to generate an evacuation route that takes into account the risk of building collapse. In addition, in the case of a fire, the generation unit can also use a generation AI to generate a route that avoids the spread of smoke. Furthermore, in the case of a flood, the generation unit can also use a generation AI to generate an evacuation route to higher ground. This makes it possible to provide appropriate information depending on the type of emergency. Some or all of the above-mentioned processing in the generation unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the type of emergency into the generation AI and cause the generation AI to apply an information generation algorithm.

[0035] The generation unit can improve the accuracy of the generated information by referring to past emergency data. The generation unit can improve the reliability of evacuation routes using a generation AI based on, for example, past earthquake data. The generation unit can also evaluate the safety of evacuation shelters using a generation AI based on past fire data. Furthermore, the generation unit can also evaluate the flood risk of evacuation routes using a generation AI based on past flood data. This makes it possible to improve the accuracy of the information by utilizing past data. Some or all of the above-mentioned processing in the generation unit can be performed using, for example, a generation AI, or can be performed without using a generation AI. For example, the generation unit can input past emergency data into the generation AI and have the generation AI improve the accuracy of the information.

[0036] The generation unit can generate an optimal evacuation route in real time based on the user's current location information. The generation unit, for example, uses a generation AI to generate the shortest evacuation route based on the user's current location. The generation unit can also use the generation AI to generate a safe evacuation route taking into account the user's current location and surrounding conditions. Furthermore, the generation unit can also provide real-time navigation to an evacuation shelter based on the user's current location using the generation AI. This makes it possible to provide an optimal evacuation route in real time. Some or all of the above-mentioned processing in the generation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the generation unit can input the user's current location information to the generation AI and cause the generation AI to generate an optimal evacuation route.

[0037] The generation unit can adjust the update frequency of the generated information based on the time of occurrence of the emergency. For example, immediately after the emergency occurs, the generation unit can increase the update frequency of the information using the generation AI. Furthermore, when the emergency is heading toward resolution, the generation unit can also decrease the update frequency of the information using the generation AI. Furthermore, the generation unit can dynamically adjust the update frequency of the information using the generation AI according to the progress of the emergency. This makes it possible to update the information according to the progress of the emergency. Some or all of the above-described processing in the generation unit can be performed using the generation AI, for example, or can be performed without using the generation AI. For example, the generation unit can input the time of occurrence of the emergency into the generation AI and cause the generation AI to adjust the update frequency of the information.

[0038] The generation unit can analyze the user's past evacuation history and propose an optimal evacuation route. For example, the generation unit can use a generation AI to propose an optimal evacuation route based on evacuation routes the user has used in the past. The generation unit can also use the generation AI to propose a route that avoids congestion based on the user's past evacuation history. Furthermore, the generation unit can analyze the user's past evacuation history and propose the most efficient evacuation route using the generation AI. This makes it possible to provide an optimal evacuation route by utilizing past evacuation history. Some or all of the above-described processing in the generation unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the generation unit can input the user's past evacuation history into the generation AI and have the generation AI propose an optimal evacuation route.

[0039] The generation unit can customize the display format of the generated information taking into account the user's device information. For example, if the user is using a smartphone, the generation unit can use the generation AI to provide a display format that matches the screen size. Also, if the user is using a tablet, the generation unit can use the generation AI to provide a display format optimized for a large screen. Furthermore, if the user is using a smartwatch, the generation unit can use the generation AI to provide a simple and highly visible display format. This makes it possible to provide a display format that is optimal for the user's device. Some or all of the above-described processing in the generation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the generation unit can input the user's device information into the generation AI and have the generation AI customize the display format.

[0040] During navigation, the navigation unit can adjust the timing of instructions taking into account the user's movement speed. For example, if the user is walking fast, the navigation unit can use the generation AI to advance the timing of instructions. Also, if the user is walking slowly, the navigation unit can use the generation AI to delay the timing of instructions. Furthermore, if the user stops, the navigation unit can use the generation AI to pause instructions and resume them when the user starts walking again. This makes it possible to provide appropriate instructions according to the user's movement speed. Some or all of the above-mentioned processing in the navigation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the navigation unit can input user movement speed data to the generation AI and have the generation AI adjust the timing of instructions.

[0041] During navigation, the navigation unit can acquire surrounding environmental information in real time and dynamically change the evacuation route. For example, the navigation unit can acquire surrounding traffic conditions in real time and change the evacuation route using the generation AI. The navigation unit can also evaluate the collapse risk of surrounding buildings in real time and change the evacuation route using the generation AI. Furthermore, the navigation unit can acquire the progress of a surrounding fire in real time and change the evacuation route using the generation AI. This makes it possible to provide an optimal evacuation route in real time. Some or all of the above-mentioned processing in the navigation unit may be performed using, or without, the generation AI. For example, the navigation unit can input surrounding environmental information to the generation AI and cause the generation AI to dynamically change the evacuation route.

[0042] During navigation, the navigation unit can suggest an optimal route by referring to the user's past travel history. For example, the navigation unit can use a generation AI to suggest an optimal route based on routes the user has used in the past. The navigation unit can also use a generation AI to suggest a route that avoids congestion based on the user's past travel history. Furthermore, the navigation unit can analyze the user's past travel history and suggest the most efficient route using the generation AI. This makes it possible to provide an optimal route by utilizing past travel history. Some or all of the above-mentioned processing in the navigation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the navigation unit can input the user's past travel history into the generation AI and have the generation AI suggest an optimal route.

[0043] During navigation, the navigation unit can select the optimal display method by taking into account the user's device information. For example, if the user is using a smartphone, the navigation unit can use the generation AI to provide a display method that matches the screen size. Also, if the user is using a tablet, the navigation unit can use the generation AI to provide a display method that is optimized for a large screen. Furthermore, if the user is using a smartwatch, the navigation unit can use the generation AI to provide a simple and highly visible display method. This makes it possible to provide the optimal display method for the user's device. Some or all of the above-mentioned processing in the navigation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the navigation unit can input the user's device information into the generation AI and have the generation AI select the display method.

[0044] During navigation, the navigation unit can provide region-specific evacuation information based on the user's geographical location information. For example, when the user is in a specific region, the navigation unit can use the generation AI to provide evacuation shelter information for that region. Furthermore, when the user is in a specific region, the navigation unit can also use the generation AI to provide evacuation route information for that region. Furthermore, when the user is in a specific region, the navigation unit can also use the generation AI to provide disaster risk information for that region. This allows for more appropriate evacuation by providing region-specific evacuation information. Some or all of the above-described processing in the navigation unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the navigation unit can input the user's geographical location information into the generation AI and have the generation AI provide region-specific evacuation information.

[0045] During navigation, the navigation unit can provide a multilingual guide according to the user's language setting. For example, the navigation unit automatically sets the navigation language using a generation AI based on the language setting of the user's device. The navigation unit can also provide a language switching function using the generation AI when the user uses multiple languages. Furthermore, when the user selects a specific language, the navigation unit can also use the generation AI to provide navigation in that language. This allows for the provision of a multilingual guide to accommodate users who speak different languages. Some or all of the above-described processing in the navigation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the navigation unit can input the user's language setting into the generation AI and cause the generation AI to provide a multilingual guide.

[0046] The communication unit can automatically attach the user's current location information when communicating and send the message. For example, when the user sends an emergency message, the communication unit automatically attaches the current location information using the generation AI. The communication unit can also automatically attach the current location information using the generation AI when the user contacts a rescue team. Furthermore, the communication unit can also automatically attach the current location information using the generation AI when the user contacts another user. This enables a quick response by automatically attaching the current location information. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the current location information to the generation AI when sending an emergency message and have the generation AI attach the location information.

[0047] The communication unit can select the optimal communication means by referring to past communication history when communicating. For example, the communication unit selects the optimal communication means using a generation AI based on communication means used by the user in the past. The communication unit can also select the fastest communication means from the user's past communication history using a generation AI. Furthermore, the communication unit can analyze the user's past communication history and select the most reliable communication means using a generation AI. This makes it possible to provide the optimal communication means by utilizing past communication history. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the communication unit can input past communication history into the generation AI and have the generation AI select the optimal communication means.

[0048] The communication unit can select the optimal communication protocol during communication by taking into account the user's device information. For example, if the user is using a smartphone, the communication unit can select the optimal communication protocol using the generation AI. Furthermore, if the user is using a tablet, the communication unit can also select the optimal communication protocol using the generation AI. Furthermore, if the user is using a smartwatch, the communication unit can also select the optimal communication protocol using the generation AI. This makes it possible to provide the optimal communication protocol for the user's device. Some or all of the above-mentioned processing in the communication unit can be performed using, for example, the generation AI, or can be performed without using the generation AI. For example, the communication unit can input the user's device information into the generation AI and have the generation AI select the communication protocol.

[0049] The communication unit can select a region-specific communication means based on the user's geographical location information when communicating. For example, when the user is in a specific region, the communication unit uses the generation AI to select the most reliable communication means in that region. Furthermore, when the user is in a specific region, the communication unit can also use the generation AI to select the fastest communication means in that region. Furthermore, when the user is in a specific region, the communication unit can also use the generation AI to select the most stable communication means in that region. This enables more appropriate communication by providing a region-specific communication means. Some or all of the above-described processing in the communication unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the communication unit can input the user's geographical location information into the generation AI and have the generation AI select a region-specific communication means.

[0050] During communication, the communication unit can analyze the user's social media activity and automatically share related information. For example, the communication unit automatically shares information about places where the user has checked in on social media. The communication unit can also analyze the content of the user's social media posts and automatically share related emergency information using the generation AI. Furthermore, the communication unit can also automatically share related emergency information using the generation AI, taking into account the activities of the user's friends on social media. This makes it possible to share related information by utilizing social media activity. Some or all of the above-described processing in the communication unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the user's social media activity data into the generation AI and cause the generation AI to share related information.

[0051] The communication unit can customize the communication method by reflecting the user's past feedback during communication. For example, the communication unit customizes the optimal communication method using a generation AI based on feedback provided by the user in the past. The communication unit can also select the most effective communication method using the generation AI from the user's past feedback. Furthermore, the communication unit can analyze the user's past feedback and provide the most satisfying communication method using the generation AI. This makes it possible to provide the optimal communication method by utilizing past feedback. Some or all of the above-described processing in the communication unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the user's past feedback into the generation AI and have the generation AI customize the communication method.

[0052] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0053] The generator can monitor the user's health condition and adjust the content of the generated information. For example, the generator can monitor the user's heart rate and blood pressure in real time, and if an abnormality is detected, use the generation AI to provide information on emergency medical assistance. In addition, if the user has a chronic illness, the generator can generate information on evacuation routes and shelters taking that information into account. Furthermore, the generator can provide evacuation precautions and a list of necessary medical supplies according to the user's health condition. This allows the generator to provide appropriate information according to the user's health condition.

[0054] The navigation unit can adjust the navigation instruction method according to the user's means of transportation. For example, if the user is using a car, the generation AI can be used to provide an evacuation route for vehicles. Also, if the user is using a bicycle, the generation AI can be used to provide an evacuation route specifically for bicycles. Furthermore, if the user is evacuating on foot, the generation AI can be used to provide an evacuation route specifically for pedestrians. This enables appropriate navigation according to the user's means of transportation.

[0055] The generation unit can learn the user's past evacuation behavior and improve the accuracy of the generated information. For example, the generation unit can use generation AI to suggest the optimal evacuation route based on the route the user has taken in the past. The generation unit can also use generation AI to suggest a route that avoids congestion based on the user's past evacuation behavior. Furthermore, the generation unit can analyze the user's past evacuation behavior and use generation AI to suggest the most efficient evacuation route. This makes it possible to improve the accuracy of the information by utilizing past evacuation behavior.

[0056] The communication unit can adjust the communication method taking into account the remaining battery power of the user's device. For example, when the battery power of the user's device is low, the communication unit uses the generation AI to communicate in power-saving mode. Also, when the battery power of the user's device is sufficient, the communication unit can use the generation AI to perform normal communication. Furthermore, the communication unit can adjust the frequency of communication according to the remaining battery power of the user's device. This enables appropriate communication according to the remaining battery power.

[0057] The navigation unit can suggest the optimal route by referring to the user's past travel history. For example, the navigation unit can use generation AI to suggest the optimal route based on routes the user has used in the past. The navigation unit can also use generation AI to suggest routes that avoid congestion based on the user's past travel history. Furthermore, the navigation unit can analyze the user's past travel history and use generation AI to suggest the most efficient route. This makes it possible to provide the optimal route by utilizing past travel history.

[0058] The generation unit can customize the display format of the generated information by taking into account the user's device information. For example, if the user is using a smartphone, the generation unit can use the generation AI to provide a display format that matches the screen size. Also, if the user is using a tablet, the generation unit can use the generation AI to provide a display format optimized for a large screen. Furthermore, if the user is using a smartwatch, the generation unit can use the generation AI to provide a simple, highly visible display format. This makes it possible to provide the optimal display format for the user's device.

[0059] The processing flow of the first embodiment will be briefly explained below.

[0060] Step 1: The generation unit generates information corresponding to emergency scenarios. When a disaster such as an earthquake or fire occurs, the generation unit uses the generation AI to generate information on evacuation routes and safe shelters appropriate to the situation. The generation unit can also use the generation AI to update information in real time and provide it to users. For example, the generation AI analyzes the occurrence of a disaster and generates the optimal evacuation route. Step 2: The navigation unit guides the user based on the information generated by the generation unit. The navigation unit displays the evacuation route on the AR glasses' display, and audio guidance instructs the user on which direction to proceed. The navigation unit can also perform real-time navigation based on the generated information, taking into account the user's current location. For example, the navigation unit displays the optimal evacuation route based on the user's current location. Step 3: The communication unit performs emergency communications between users guided by the navigation unit or between users and rescue teams. The communication unit uses a dedicated wireless communication function to share information even if the communication network goes down due to a disaster or other reason. The communication unit can also send emergency messages to other users or rescue teams when a user encounters an emergency. For example, the communication unit uses a dedicated wireless communication function to send an emergency message including the user's current location information.

[0061] (Example 2) An emergency support system according to an embodiment of the present invention generates information corresponding to an emergency scenario, guides users to safe evacuation shelters, and performs emergency communications. The emergency support system uses a generation AI to generate information corresponding to an emergency scenario, and the AR glasses combine navigation and audio guidance to guide the user to a safe evacuation shelter. The emergency support system also performs emergency communications between users or between users and rescue teams. For example, in the event of a disaster such as an earthquake or fire, the generation AI generates information on evacuation routes and safe evacuation shelters appropriate to the situation. This information is updated in real time and provided to the user. Next, based on the generated information, the emergency support system displays evacuation routes on the AR glasses' display and provides audio guidance to the user. This allows the user to confirm the evacuation route both visually and audibly, enabling quick and safe evacuation. Furthermore, when a user encounters an emergency, the emergency support system can send emergency messages to other users or rescue teams via the AR glasses. In particular, even if the communication network is down due to a disaster, information can be shared using a dedicated wireless communication function. This allows users to communicate with others and cooperate in evacuating even in an emergency. This allows the emergency support system to guide users quickly and safely in emergency situations and ensure communication. For example, in the event of an earthquake, the generation AI will generate evacuation routes in real time, and the AR glasses will guide users based on that information. Furthermore, even if the communication network is down, users can still contact other users and rescue teams using the dedicated wireless communication function. This ensures the safety of users in emergencies.

[0062] An emergency support system according to an embodiment includes a generation unit, a navigation unit, and a communication unit. The generation unit generates information corresponding to an emergency scenario. When a disaster such as an earthquake or fire occurs, the generation unit generates information on evacuation routes and safe shelters according to the situation using, for example, a generation AI. The generation unit can also update information in real time using the generation AI and provide the information to a user. For example, the generation AI analyzes the occurrence of a disaster and generates an optimal evacuation route. The navigation unit guides a user based on the information generated by the generation unit. For example, the navigation unit displays an evacuation route on a display of AR glasses, and an audio guide instructs the user on the direction to travel. The navigation unit can also perform real-time navigation based on the generated information, taking into account the user's current location. For example, the navigation unit displays an optimal evacuation route based on the user's current location. The communication unit performs emergency communication between users guided by the navigation unit or between the user and a rescue team. The communication unit can share information using a dedicated wireless communication function, even when the communication network is down due to a disaster or other reason. In addition, when a user encounters an emergency, the communication unit can also send an emergency message to other users or a rescue team. For example, the communication unit may use a dedicated wireless communication function to send an emergency message including the user's current location information. This allows the emergency support system according to the embodiment to quickly and safely guide the user in an emergency and ensure communication.

[0063] In the event of an earthquake or fire, the generation unit can generate information on evacuation routes or safe evacuation shelters according to the situation. For example, in the event of an earthquake, the generation unit uses the generation AI to generate evacuation routes that take into account the risk of building collapse. In addition, in the event of a fire, the generation unit can also use the generation AI to generate routes that avoid the spread of smoke. Furthermore, in the event of a flood, the generation unit can also use the generation AI to generate evacuation routes to higher ground. This makes it possible to provide appropriate evacuation information in the event of a disaster. Some or all of the above-mentioned processing in the generation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the generation unit can input the disaster occurrence situation into the generation AI and have the generation AI execute information on evacuation routes and safe evacuation shelters.

[0064] The navigation unit can display an evacuation route on the display of the AR glasses based on the generated information and provide audio guidance to instruct the user on the direction of travel. For example, the navigation unit can display an evacuation route on the display of the AR glasses based on the generated information. The navigation unit can also provide audio guidance to instruct the user on the direction of travel. For example, the navigation unit can display arrows and routes on the display of the AR glasses and provide instructions such as "Turn right" through audio guidance. The navigation unit can also provide real-time navigation in consideration of the user's current location. For example, the navigation unit can display an optimal evacuation route based on the user's current location and provide audio guidance to instruct the user on the direction of travel. This allows the user to confirm the evacuation route both visually and audibly. Some or all of the above-described processing in the navigation unit can be performed using, for example, a generation AI, or can be performed without using a generation AI. For example, the navigation unit can input the generated information to a generation AI and have the generation AI display the evacuation route and provide audio guidance instructions.

[0065] The communication unit can share information using a dedicated wireless communication function even when the communication network goes down due to a disaster. For example, when the communication network goes down due to a disaster, the communication unit shares information using the dedicated wireless communication function. For example, the communication unit uses the dedicated wireless communication function to send an emergency message including the user's current location information. The communication unit can also send an emergency message to other users or a rescue team when a user encounters an emergency. For example, the communication unit uses the dedicated wireless communication function to send an emergency message including the user's current location information. This makes it possible to share information even when the communication network goes down. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI, or may be performed without using the generation AI. For example, the communication unit can input the content of the emergency message to the generation AI and cause the generation AI to send the emergency message.

[0066] The communication unit can transmit an emergency message to other users or a rescue team when a user encounters an emergency. For example, the communication unit transmits an emergency message to other users or a rescue team when a user encounters an emergency. For example, the communication unit transmits an emergency message including the user's current location information using a dedicated wireless communication function. The communication unit can also transmit an emergency message to other users or a rescue team when a user encounters an emergency. For example, the communication unit transmits an emergency message including the user's current location information using a dedicated wireless communication function. This allows for quick contact with others in an emergency. Some or all of the above-described processing in the communication unit may be performed using, for example, a generation AI, or may be performed without using the generation AI. For example, the communication unit can input the content of the emergency message to the generation AI and cause the generation AI to send the emergency message.

[0067] The generation unit can estimate the user's emotions and adjust the level of detail of the generated information based on the estimated user emotions. For example, if the user is in a panic, the generation unit can use the generation AI to generate concise and to-the-point information. Furthermore, if the user is calm, the generation unit can also use the generation AI to provide detailed information on evacuation routes and safe shelters. Furthermore, if the user is feeling anxious, the generation unit can also use the generation AI to generate information that gives a sense of security. This allows appropriate information to be provided according to the user's emotions. The emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or generation AI. The generation AI can be, for example, a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the generation unit can be performed using, for example, the generation AI, or can be performed without using the generation AI. For example, the generation unit can input the user's emotion data into the generation AI and have the generation AI adjust the level of detail of the information.

[0068] The generation unit can apply different information generation algorithms depending on the type of emergency. For example, in the case of an earthquake, the generation unit uses a generation AI to generate an evacuation route that takes into account the risk of building collapse. In addition, in the case of a fire, the generation unit can also use a generation AI to generate a route that avoids the spread of smoke. Furthermore, in the case of a flood, the generation unit can also use a generation AI to generate an evacuation route to higher ground. This makes it possible to provide appropriate information depending on the type of emergency. Some or all of the above-mentioned processing in the generation unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the type of emergency into the generation AI and cause the generation AI to apply an information generation algorithm.

[0069] The generation unit can improve the accuracy of the generated information by referring to past emergency data. The generation unit can improve the reliability of evacuation routes using a generation AI based on, for example, past earthquake data. The generation unit can also evaluate the safety of evacuation shelters using a generation AI based on past fire data. Furthermore, the generation unit can also evaluate the flood risk of evacuation routes using a generation AI based on past flood data. This makes it possible to improve the accuracy of the information by utilizing past data. Some or all of the above-mentioned processing in the generation unit can be performed using, for example, a generation AI, or can be performed without using a generation AI. For example, the generation unit can input past emergency data into the generation AI and have the generation AI improve the accuracy of the information.

[0070] The generation unit can generate an optimal evacuation route in real time based on the user's current location information. The generation unit, for example, uses a generation AI to generate the shortest evacuation route based on the user's current location. The generation unit can also use the generation AI to generate a safe evacuation route taking into account the user's current location and surrounding conditions. Furthermore, the generation unit can also provide real-time navigation to an evacuation shelter based on the user's current location using the generation AI. This makes it possible to provide an optimal evacuation route in real time. Some or all of the above-mentioned processing in the generation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the generation unit can input the user's current location information to the generation AI and cause the generation AI to generate an optimal evacuation route.

[0071] The generation unit can estimate the user's emotions and determine the priority of information to be generated based on the estimated user emotions. For example, when the user is in a panicked state, the generation unit can use the generation AI to prioritize providing the most important information. Furthermore, when the user is calm, the generation unit can also use the generation AI to prioritize providing detailed information. Furthermore, when the user is feeling anxious, the generation unit can also use the generation AI to prioritize information that provides a sense of security. This allows the priority of information to be determined according to the user's emotions. The emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the generation unit can be performed using, for example, the generation AI, or can be performed without using the generation AI. For example, the generation unit can input the user's emotion data into the generation AI and have the generation AI determine the priority of information.

[0072] The generation unit can adjust the update frequency of the generated information based on the time of occurrence of the emergency. For example, immediately after the emergency occurs, the generation unit can increase the update frequency of the information using the generation AI. Furthermore, when the emergency is heading toward resolution, the generation unit can also decrease the update frequency of the information using the generation AI. Furthermore, the generation unit can dynamically adjust the update frequency of the information using the generation AI according to the progress of the emergency. This makes it possible to update the information according to the progress of the emergency. Some or all of the above-described processing in the generation unit can be performed using the generation AI, for example, or can be performed without using the generation AI. For example, the generation unit can input the time of occurrence of the emergency into the generation AI and cause the generation AI to adjust the update frequency of the information.

[0073] The generation unit can analyze the user's past evacuation history and propose an optimal evacuation route. For example, the generation unit can use a generation AI to propose an optimal evacuation route based on evacuation routes the user has used in the past. The generation unit can also use the generation AI to propose a route that avoids congestion based on the user's past evacuation history. Furthermore, the generation unit can analyze the user's past evacuation history and propose the most efficient evacuation route using the generation AI. This makes it possible to provide an optimal evacuation route by utilizing past evacuation history. Some or all of the above-described processing in the generation unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the generation unit can input the user's past evacuation history into the generation AI and have the generation AI propose an optimal evacuation route.

[0074] The generation unit can customize the display format of the generated information taking into account the user's device information. For example, if the user is using a smartphone, the generation unit can use the generation AI to provide a display format that matches the screen size. Also, if the user is using a tablet, the generation unit can use the generation AI to provide a display format optimized for a large screen. Furthermore, if the user is using a smartwatch, the generation unit can use the generation AI to provide a simple and highly visible display format. This makes it possible to provide a display format that is optimal for the user's device. Some or all of the above-described processing in the generation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the generation unit can input the user's device information into the generation AI and have the generation AI customize the display format.

[0075] The navigation unit can estimate the user's emotions and adjust the navigation instruction method based on the estimated user's emotions. For example, if the user is nervous, the navigation unit can use the generation AI to provide a simple, highly visible instruction method. Furthermore, if the user is relaxed, the navigation unit can also use the generation AI to provide an instruction method that includes detailed information. Furthermore, if the user is in a hurry, the navigation unit can also use the generation AI to provide an instruction method that focuses on the main points. This enables navigation instructions to be provided according to the user's emotions. The emotion estimation is realized using an emotion estimation function, for example, with an emotion engine or generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the navigation unit can be performed using, for example, the generation AI, or can be performed without using the generation AI. For example, the navigation unit can input the user's emotion data into the generation AI and have the generation AI adjust the instruction method.

[0076] During navigation, the navigation unit can adjust the timing of instructions taking into account the user's movement speed. For example, if the user is walking fast, the navigation unit can use the generation AI to advance the timing of instructions. Also, if the user is walking slowly, the navigation unit can use the generation AI to delay the timing of instructions. Furthermore, if the user stops, the navigation unit can use the generation AI to pause instructions and resume them when the user starts walking again. This makes it possible to provide appropriate instructions according to the user's movement speed. Some or all of the above-mentioned processing in the navigation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the navigation unit can input user movement speed data to the generation AI and have the generation AI adjust the timing of instructions.

[0077] During navigation, the navigation unit can acquire surrounding environmental information in real time and dynamically change the evacuation route. For example, the navigation unit can acquire surrounding traffic conditions in real time and change the evacuation route using the generation AI. The navigation unit can also evaluate the collapse risk of surrounding buildings in real time and change the evacuation route using the generation AI. Furthermore, the navigation unit can acquire the progress of a surrounding fire in real time and change the evacuation route using the generation AI. This makes it possible to provide an optimal evacuation route in real time. Some or all of the above-mentioned processing in the navigation unit may be performed using, or without, the generation AI. For example, the navigation unit can input surrounding environmental information to the generation AI and cause the generation AI to dynamically change the evacuation route.

[0078] During navigation, the navigation unit can suggest an optimal route by referring to the user's past travel history. For example, the navigation unit can use a generation AI to suggest an optimal route based on routes the user has used in the past. The navigation unit can also use a generation AI to suggest a route that avoids congestion based on the user's past travel history. Furthermore, the navigation unit can analyze the user's past travel history and suggest the most efficient route using the generation AI. This makes it possible to provide an optimal route by utilizing past travel history. Some or all of the above-mentioned processing in the navigation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the navigation unit can input the user's past travel history into the generation AI and have the generation AI suggest an optimal route.

[0079] The navigation unit can estimate the user's emotions and adjust the tone of the navigation voice guidance based on the estimated user emotions. For example, if the user is nervous, the navigation unit can use the generation AI to provide guidance in a calm voice. Also, if the user is relaxed, the navigation unit can use the generation AI to provide guidance in a cheerful voice. Furthermore, if the user is in a hurry, the navigation unit can use the generation AI to provide quick and concise voice guidance. This enables voice guidance to be provided according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the navigation unit can be performed using, for example, the generation AI, or can be performed without using the generation AI. For example, the navigation unit can input user emotion data into the generation AI and have the generation AI adjust the tone of the voice guidance.

[0080] During navigation, the navigation unit can select the optimal display method by taking into account the user's device information. For example, if the user is using a smartphone, the navigation unit can use the generation AI to provide a display method that matches the screen size. Also, if the user is using a tablet, the navigation unit can use the generation AI to provide a display method that is optimized for a large screen. Furthermore, if the user is using a smartwatch, the navigation unit can use the generation AI to provide a simple and highly visible display method. This makes it possible to provide the optimal display method for the user's device. Some or all of the above-mentioned processing in the navigation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the navigation unit can input the user's device information into the generation AI and have the generation AI select the display method.

[0081] During navigation, the navigation unit can provide region-specific evacuation information based on the user's geographical location information. For example, when the user is in a specific region, the navigation unit can use the generation AI to provide evacuation shelter information for that region. Furthermore, when the user is in a specific region, the navigation unit can also use the generation AI to provide evacuation route information for that region. Furthermore, when the user is in a specific region, the navigation unit can also use the generation AI to provide disaster risk information for that region. This allows for more appropriate evacuation by providing region-specific evacuation information. Some or all of the above-described processing in the navigation unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the navigation unit can input the user's geographical location information into the generation AI and have the generation AI provide region-specific evacuation information.

[0082] During navigation, the navigation unit can provide a multilingual guide according to the user's language setting. For example, the navigation unit automatically sets the navigation language using a generation AI based on the language setting of the user's device. The navigation unit can also provide a language switching function using the generation AI when the user uses multiple languages. Furthermore, when the user selects a specific language, the navigation unit can also use the generation AI to provide navigation in that language. This allows for the provision of a multilingual guide to accommodate users who speak different languages. Some or all of the above-described processing in the navigation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the navigation unit can input the user's language setting into the generation AI and cause the generation AI to provide a multilingual guide.

[0083] The communication unit can estimate the user's emotions and adjust the content of the emergency message based on the estimated user emotions. For example, if the user is in a panic, the communication unit can use the generation AI to send a concise and to-the-point emergency message. Furthermore, if the user is calm, the communication unit can also use the generation AI to send a detailed emergency message. Furthermore, if the user is feeling anxious, the communication unit can also use the generation AI to send a reassuring emergency message. This allows for providing an appropriate emergency message according to the user's emotions. The emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the communication unit can be performed using, for example, the generation AI, or without the generation AI. For example, the communication unit can input the user's emotion data into the generation AI and have the generation AI adjust the content of the emergency message.

[0084] The communication unit can automatically attach the user's current location information when communicating and send the message. For example, when the user sends an emergency message, the communication unit automatically attaches the current location information using the generation AI. The communication unit can also automatically attach the current location information using the generation AI when the user contacts a rescue team. Furthermore, the communication unit can also automatically attach the current location information using the generation AI when the user contacts another user. This enables a quick response by automatically attaching the current location information. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the current location information to the generation AI when sending an emergency message and have the generation AI attach the location information.

[0085] The communication unit can select the optimal communication means by referring to past communication history when communicating. For example, the communication unit selects the optimal communication means using a generation AI based on communication means used by the user in the past. The communication unit can also select the fastest communication means from the user's past communication history using a generation AI. Furthermore, the communication unit can analyze the user's past communication history and select the most reliable communication means using a generation AI. This makes it possible to provide the optimal communication means by utilizing past communication history. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the communication unit can input past communication history into the generation AI and have the generation AI select the optimal communication means.

[0086] The communication unit can select the optimal communication protocol during communication by taking into account the user's device information. For example, if the user is using a smartphone, the communication unit can select the optimal communication protocol using the generation AI. Furthermore, if the user is using a tablet, the communication unit can also select the optimal communication protocol using the generation AI. Furthermore, if the user is using a smartwatch, the communication unit can also select the optimal communication protocol using the generation AI. This makes it possible to provide the optimal communication protocol for the user's device. Some or all of the above-mentioned processing in the communication unit can be performed using, for example, the generation AI, or can be performed without using the generation AI. For example, the communication unit can input the user's device information into the generation AI and have the generation AI select the communication protocol.

[0087] The communication unit can estimate the user's emotions and prioritize emergency messages based on the estimated user emotions. For example, if the user is in a panic, the communication unit can use the generation AI to prioritize sending the most important emergency message. Furthermore, if the user is calm, the communication unit can also use the generation AI to prioritize sending detailed emergency messages. Furthermore, if the user is feeling anxious, the communication unit can also use the generation AI to prioritize sending emergency messages that provide a sense of security. This allows the priority of emergency messages to be determined according to the user's emotions. The emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the communication unit can be performed using, for example, the generation AI, or can be performed without using the generation AI. For example, the communication unit can input the user's emotion data into the generation AI and have the generation AI determine the priority of emergency messages.

[0088] The communication unit can select a region-specific communication means based on the user's geographical location information when communicating. For example, when the user is in a specific region, the communication unit uses the generation AI to select the most reliable communication means in that region. Furthermore, when the user is in a specific region, the communication unit can also use the generation AI to select the fastest communication means in that region. Furthermore, when the user is in a specific region, the communication unit can also use the generation AI to select the most stable communication means in that region. This enables more appropriate communication by providing a region-specific communication means. Some or all of the above-described processing in the communication unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the communication unit can input the user's geographical location information into the generation AI and have the generation AI select a region-specific communication means.

[0089] During communication, the communication unit can analyze the user's social media activity and automatically share related information. For example, the communication unit automatically shares information about places where the user has checked in on social media. The communication unit can also analyze the content of the user's social media posts and automatically share related emergency information using the generation AI. Furthermore, the communication unit can also automatically share related emergency information using the generation AI, taking into account the activities of the user's friends on social media. This makes it possible to share related information by utilizing social media activity. Some or all of the above-described processing in the communication unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the user's social media activity data into the generation AI and cause the generation AI to share related information.

[0090] The communication unit can customize the communication method by reflecting the user's past feedback during communication. For example, the communication unit customizes the optimal communication method using a generation AI based on feedback provided by the user in the past. The communication unit can also select the most effective communication method using the generation AI from the user's past feedback. Furthermore, the communication unit can analyze the user's past feedback and provide the most satisfying communication method using the generation AI. This makes it possible to provide the optimal communication method by utilizing past feedback. Some or all of the above-described processing in the communication unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the user's past feedback into the generation AI and have the generation AI customize the communication method. === Hard Collateral 1-1 === Each of the multiple elements including the generation unit, navigation unit, and communication unit described above is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates information corresponding to an emergency scenario using a generation AI. The navigation unit is realized by the control unit 46A of the smart device 14 and displays evacuation routes on the display of the AR glasses and instructs the user in the direction to travel using audio guidance. The communication unit is realized by the communication I / F 44 of the smart device 14 and the communication I / F 26 of the data processing device 12 and shares information using a dedicated wireless communication function. === Hard Collateral 1-2 === Each of the multiple elements including the generation unit, navigation unit, and communication unit described above is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates information corresponding to an emergency scenario using a generation AI. The navigation unit is realized by the control unit 46A of the smart glasses 214 and displays evacuation routes on the display of the AR glasses and instructs the user in the direction of travel using audio guidance. The communication unit is realized by the communication I / F 44 of the smart glasses 214 and the communication I / F 26 of the data processing device 12 and shares information using a dedicated wireless communication function. === Hard Collateral 1-3 === Each of the multiple elements including the generation unit, navigation unit, and communication unit described above is realized, for example, by at least one of the headset-type terminal 314 and the data processing device 12. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12, and generates information corresponding to an emergency scenario using a generation AI. The navigation unit is realized by the control unit 46A of the headset-type terminal 314, and displays evacuation routes on the display of the AR glasses, and instructs the user in the direction to travel using audio guidance. The communication unit is realized by the communication I / F 44 of the headset-type terminal 314 and the communication I / F 26 of the data processing device 12, and shares information using a dedicated wireless communication function. === Hard Collateral 1-4 === Each of the multiple elements including the generation unit, navigation unit, and communication unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12, and generates information corresponding to an emergency scenario using a generation AI. The navigation unit is realized by the control unit 46A of the robot 414, and displays evacuation routes on the display of the AR glasses, and instructs the user in the direction to proceed using audio guidance. The communication unit is realized by the communication I / F 44 of the robot 414 and the communication I / F 26 of the data processing device 12, and shares information using a dedicated wireless communication function.

[0091] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0092] The generator can monitor the user's health condition and adjust the content of the generated information. For example, the generator can monitor the user's heart rate and blood pressure in real time, and if an abnormality is detected, use the generation AI to provide information on emergency medical assistance. In addition, if the user has a chronic illness, the generator can generate information on evacuation routes and shelters taking that information into account. Furthermore, the generator can provide evacuation precautions and a list of necessary medical supplies according to the user's health condition. This allows the generator to provide appropriate information according to the user's health condition.

[0093] The navigation unit can adjust the navigation instruction method according to the user's means of transportation. For example, if the user is using a car, the generation AI can be used to provide an evacuation route for vehicles. Also, if the user is using a bicycle, the generation AI can be used to provide an evacuation route specifically for bicycles. Furthermore, if the user is evacuating on foot, the generation AI can be used to provide an evacuation route specifically for pedestrians. This enables appropriate navigation according to the user's means of transportation.

[0094] The communication unit can estimate the user's emotions and select the recipients of the emergency message based on the estimated user emotions. For example, if the user is in a panic, the generation AI can be used to send the emergency message to the most trusted contact. Alternatively, if the user is calm, the generation AI can be used to send the emergency message to multiple contacts. Furthermore, if the user is feeling anxious, the generation AI can be used to send the emergency message to contacts that give them a sense of security. This allows the appropriate recipient to be selected according to the user's emotions.

[0095] The generation unit can learn the user's past evacuation behavior and improve the accuracy of the generated information. For example, the generation unit can use generation AI to suggest the optimal evacuation route based on the route the user has taken in the past. The generation unit can also use generation AI to suggest a route that avoids congestion based on the user's past evacuation behavior. Furthermore, the generation unit can analyze the user's past evacuation behavior and use generation AI to suggest the most efficient evacuation route. This makes it possible to improve the accuracy of the information by utilizing past evacuation behavior.

[0096] The navigation unit can estimate the user's emotions and adjust the content of the navigation voice guidance based on the estimated user emotions. For example, if the user is nervous, the generation AI can be used to provide guidance in a calm voice. Alternatively, if the user is relaxed, the generation AI can be used to provide guidance in a cheerful voice. Furthermore, if the user is in a hurry, the generation AI can be used to provide quick and concise voice guidance. This makes it possible to provide voice guidance that corresponds to the user's emotions.

[0097] The communication unit can adjust the communication method taking into account the remaining battery power of the user's device. For example, when the battery power of the user's device is low, the communication unit uses the generation AI to communicate in power-saving mode. Also, when the battery power of the user's device is sufficient, the communication unit can use the generation AI to perform normal communication. Furthermore, the communication unit can adjust the frequency of communication according to the remaining battery power of the user's device. This enables appropriate communication according to the remaining battery power.

[0098] The generation unit can estimate the user's emotions and determine the priority of the information to be generated based on the estimated user emotions. For example, if the user is in a panic, the generation AI can be used to provide the most important information with priority. Also, if the user is calm, the generation AI can be used to provide detailed information with priority. Furthermore, if the user is feeling anxious, the generation AI can be used to provide information that gives a sense of security with priority. This makes it possible to determine the priority of information according to the user's emotions.

[0099] The navigation unit can suggest the optimal route by referring to the user's past travel history. For example, the navigation unit can use generation AI to suggest the optimal route based on routes the user has used in the past. The navigation unit can also use generation AI to suggest routes that avoid congestion based on the user's past travel history. Furthermore, the navigation unit can analyze the user's past travel history and use generation AI to suggest the most efficient route. This makes it possible to provide the optimal route by utilizing past travel history.

[0100] The communication unit can estimate the user's emotions and adjust the content of the emergency message based on the estimated user emotions. For example, if the user is in a panic, the generation AI can be used to send a concise and to-the-point emergency message. If the user is calm, the generation AI can be used to send a detailed emergency message. Furthermore, if the user is feeling anxious, the generation AI can be used to send an emergency message that provides a sense of security. This makes it possible to provide an appropriate emergency message according to the user's emotions.

[0101] The generation unit can customize the display format of the generated information by taking into account the user's device information. For example, if the user is using a smartphone, the generation unit can use the generation AI to provide a display format that matches the screen size. Also, if the user is using a tablet, the generation unit can use the generation AI to provide a display format optimized for a large screen. Furthermore, if the user is using a smartwatch, the generation unit can use the generation AI to provide a simple, highly visible display format. This makes it possible to provide the optimal display format for the user's device.

[0102] The processing flow of the second embodiment will be briefly explained below.

[0103] Step 1: The generation unit generates information corresponding to emergency scenarios. When a disaster such as an earthquake or fire occurs, the generation unit uses the generation AI to generate information on evacuation routes and safe shelters appropriate to the situation. The generation unit can also use the generation AI to update information in real time and provide it to users. For example, the generation AI analyzes the occurrence of a disaster and generates the optimal evacuation route. Step 2: The navigation unit guides the user based on the information generated by the generation unit. The navigation unit displays the evacuation route on the AR glasses' display, and audio guidance instructs the user on which direction to proceed. The navigation unit can also perform real-time navigation based on the generated information, taking into account the user's current location. For example, the navigation unit displays the optimal evacuation route based on the user's current location. Step 3: The communication unit performs emergency communications between users guided by the navigation unit or between users and rescue teams. The communication unit uses a dedicated wireless communication function to share information even if the communication network goes down due to a disaster or other reason. The communication unit can also send emergency messages to other users or rescue teams when a user encounters an emergency. For example, the communication unit uses a dedicated wireless communication function to send an emergency message including the user's current location information.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0108] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0124] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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).

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification 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 identification processing unit 290 using these models.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0140] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0141] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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).

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also 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 perform the same process as the identification processing unit 290 using these models.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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).

[0161] 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.

[0162] 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."

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] [Explanation of symbols]

[0176] 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. a generating unit that generates information corresponding to an emergency scenario; a navigation unit that guides a user based on the information generated by the generation unit; a communication unit that performs emergency communication between users guided by the navigation unit or between a user and a rescue team. A system characterized by:

2. The generation unit Generate information on evacuation routes or safe shelters according to the situation in the event of an earthquake or fire 2. The system of claim 1.

3. The navigation unit Based on the generated information, evacuation routes are displayed on the AR glasses' display, and audio guidance instructs the user on which direction to proceed.

2. The system of claim 1.

4. The communication unit Even if the communication network goes down due to a disaster, information can be shared using dedicated wireless communication functions.

2. The system of claim 1.

5. The communication unit If a user encounters an emergency, they can send an emergency message to other users or rescue teams.

2. The system of claim 1.

6. The generation unit The system estimates the user's emotions and adjusts the level of detail of the generated information based on the estimated user emotions.

2. The system of claim 1.

7. The generation unit Apply different information generation algorithms depending on the type of emergency.

2. The system of claim 1.

8. The generation unit Referencing past emergency data to improve the accuracy of generated information 2. The system of claim 1.

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