system

Abstract

We provide the system. [Solution] A means of storing personal characteristic information obtained from users, Means for obtaining and analyzing disaster-related data from external sources, A means for generating an evacuation route optimized for the user based on the aforementioned personal characteristics information and the aforementioned disaster-related data, Means for transmitting the generated evacuation route information to a user terminal, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the event of a disaster, it has been conventionally difficult to select an evacuation route suitable for the physical conditions and living environment of individual users, and general evacuation information has been insufficient. Therefore, there is a need for a technology that provides an optimized evacuation route for each user in real time. In particular, route selection that takes into account the elderly and people with disabilities is required.

Means for Solving the Problems

[0005] This invention provides a system that generates evacuation routes optimized for each user by combining personal characteristic information pre-entered by the user with the latest disaster-related data obtained from external sources. The generated evacuation routes are transmitted to the user's terminal and support real-time information updates. This enables safe and efficient evacuation tailored to individual needs.

[0006] "Personal characteristics information" is a general term for user-related data necessary for optimizing evacuation routes, such as the user's age, gender, physical condition, and place of residence.

[0007] "Disaster-related data" refers to the latest information on disasters such as earthquakes, floods, and fires obtained from external sources, and is used to identify dangerous and safe areas.

[0008] An "evacuation route" is a route intentionally selected and suggested during a disaster to ensure the user's safe evacuation, and is optimized according to the individual's characteristics.

[0009] "User terminal" refers to electronic devices such as mobile phones and tablets that users use to input information and receive evacuation route information.

[0010] "Real-time updates" refers to a function that allows the system to instantly acquire new information in response to changes in the disaster situation and quickly provide users with new evacuation routes. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4]This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0017] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. 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), or Bluetooth (registered trademark).

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0022] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0024] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0025] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0031] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0032] This invention is a system that provides users with the optimal evacuation route during a disaster. The system mainly consists of a server and user terminals and operates as follows:

[0033] Server operation

[0034] The server first receives personal information entered by the user from their device and stores it in a database. This personal information includes age, gender, physical condition, and place of residence. Next, the server collects the latest data on disasters such as earthquakes and floods through an external disaster information API. Based on this information, the server determines dangerous and safe areas. Furthermore, the server uses a generative AI to combine the user's stored personal information with disaster-related data to generate individually optimized evacuation routes. These generated evacuation routes are then sent to the user's device.

[0035] User terminal behavior

[0036] Users input their personal information using a dedicated application on their device. After this information is sent to the server, they can receive the optimal evacuation route in the event of a disaster. The device visually displays the received evacuation route on a map application and guides the user along that route. Audio guidance is also provided, making it possible to accommodate users who prefer to evacuate without relying on visual cues.

[0037] Specific example

[0038] For example, consider a scenario where an earthquake occurs in the area where user B (60 years old, female, with knee pain) lives, and an evacuation order is issued. The server takes into account B's physical condition, such as her knee pain, and analyzes evacuation routes that allow the use of elevators and avoid stairs. This evacuation route is transmitted to B's terminal, and she is supported in evacuating safely through maps and voice guidance. In this way, the present invention enables flexible disaster response that meets individual needs.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] Users launch a dedicated terminal application and enter their personal information (age, gender, physical condition, address, etc.). This information is immediately sent to the server and stored in the database.

[0042] Step 2:

[0043] The server periodically uses an external disaster information API to retrieve the latest disaster-related data. This includes detailed information on earthquakes, tsunamis, floods, and other disasters. The server analyzes the retrieved information and generates a map that identifies dangerous and safe areas.

[0044] Step 3:

[0045] When a disaster occurs or is updated, the server integrates each user's personal characteristics information with the latest disaster-related data to generate the optimal evacuation route using AI. This route selection takes into account the user's physical limitations and living environment.

[0046] Step 4:

[0047] The server sends the evacuation route generated for each user to the user's terminal in real time.

[0048] Step 5:

[0049] The device presents the received evacuation route to the user using both map display and voice guidance, helping the user evacuate via the optimal route. Based on this information, the user begins the actual evacuation.

[0050] Step 6:

[0051] While the user is evacuating, the terminal requests the latest disaster information from the server at regular intervals. If the server detects a change in the situation, it sends the newly generated optimal route back to the user's terminal, enabling a flexible response.

[0052] (Example 1)

[0053] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0054] Providing optimal evacuation routes for users with diverse individual characteristics during a disaster is not easy. In particular, it is crucial to respond quickly and flexibly according to the type and progression of the disaster. To achieve efficient evacuation, real-time information provision and route selection tailored to each user's situation are required. Solving this challenge lies in utilizing external information sources and integrating individual characteristic information.

[0055] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0056] In this invention, the server includes means for storing individual characteristic information obtained from users, means for obtaining and analyzing disaster-related information from external information sources, means for generating evacuation routes tailored to users using a generation AI based on the individual characteristic information and the disaster-related information, and means for transferring the generated evacuation route information to user equipment. This makes it possible to provide safe evacuation routes tailored to individual users in real time.

[0057] "Individual characteristic information" refers to information unique to each user, such as age, gender, physical condition, and place of residence, and is data used to optimize evacuation routes.

[0058] "External information sources" refer to APIs and other information supply services that provide disaster-related information, and are means of obtaining the latest data on the type and progress of disasters.

[0059] "Generative AI" refers to a model that uses artificial intelligence technology to generate the optimal evacuation route for a user based on input data.

[0060] An "evacuation route" is information that indicates the optimal route that a user should follow to evacuate safely during a disaster.

[0061] "User equipment" refers to mobile devices and computers that receive evacuation route information and present it visually and audibly.

[0062] Regarding embodiments for carrying out the invention, the present invention is a system that utilizes individual user characteristic information and disaster-related information from external sources during a disaster to provide an optimized evacuation route for the user. The system mainly consists of a server and a user terminal, and its operation details are described below.

[0063] The server receives individual characteristic information sent by users and stores it in its internal database. This information includes the user's age, gender, physical condition, and place of residence, and is data necessary for disaster response. The server then retrieves disaster-related information provided by external sources. These sources are APIs that provide the latest disaster information, such as earthquakes and floods.

[0064] The server uses a generative AI to generate an optimized evacuation route for each user, based on accumulated individual characteristic information and disaster-related information. The generative AI model has the ability to process large amounts of data and quickly derive routes suitable for the user's characteristics. An example of a prompt used in this process is one in the form of "Specify user ID and generate the optimal evacuation route for a specific physical condition."

[0065] The generated evacuation route is transferred to the user's device. The user's device displays the received route and provides visual guidance through a map application. In addition, voice guidance is also provided to complement the visual information and support safe evacuation. For example, if the user has a knee problem, the generated evacuation route will be designed to prioritize elevators and avoid stairs. In this way, the system provides flexible evacuation support that is tailored to individual needs and disaster situations.

[0066] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0067] Step 1:

[0068] The server receives individual characteristic information sent from the user's terminal and stores it in a database. It receives user age, gender, physical condition, and place of residence information as input, organizes and structures this data, and stores it in the database. Specifically, it analyzes the transmitted data and stores it in a disaster prevention database, associated with the user ID.

[0069] Step 2:

[0070] The server accesses disaster information APIs from external sources to retrieve current and predicted disaster-related data. As input, it identifies disaster types such as earthquakes and floods and collects the latest progress data. It analyzes the retrieved data to determine dangerous and safe areas. This allows for the development of new disaster response measures based on information obtained from external sources.

[0071] Step 3:

[0072] The server uses a generative AI to optimize evacuation routes by combining stored individual characteristic information with collected disaster-related data. The inputs used are the individual characteristic information obtained in Step 1 and the disaster data analyzed in Step 2. The generative AI model is used to calculate the optimal route tailored to each user's characteristics and define a route suitable for evacuation. Specifically, prompts such as "Generate the shortest and safest route for users with disabilities" are used.

[0073] Step 4:

[0074] The server sends the generated evacuation route to the user terminal. It receives the optimized route information generated in step 3 as input and seamlessly transfers it to the user terminal as output. This process includes sending the data in a format optimized for each individual user terminal.

[0075] Step 5:

[0076] The terminal visually displays the received evacuation route on a map application and provides voice guidance. It receives evacuation route information transmitted from a server as input and guides the user through it both visually and audibly. Specifically, it draws the route on a map and uses speech synthesis technology to provide instructions that the user should follow during evacuation.

[0077] Step 6:

[0078] The terminal requests real-time updates of disaster information from the server and receives the changed evacuation routes. It requests new disaster information or modification instructions from the server as input and receives updated evacuation routes as output. This ensures that users are provided with the most effective evacuation route information even as the situation changes.

[0079] (Application Example 1)

[0080] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0081] This invention solves the problem of enhancing user safety and security not only by providing evacuation routes tailored to individual users during disasters, but also by suggesting safe travel routes in real time during daily life. Specifically, it aims to enable rapid response during disasters and provide travel routes that are manageable according to the user's health condition.

[0082] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0083] In this invention, the server includes means for storing personal characteristic information obtained from the user, means for obtaining and analyzing disaster-related data from external information sources, and means for generating an evacuation route optimized for the user based on the personal characteristic information and the disaster-related data. This enables the user to receive appropriate travel route guidance not only during disasters but also in daily life.

[0084] "Personal characteristics information" refers to information that indicates characteristics unique to the user, such as the user's age, gender, physical condition, and place of residence.

[0085] "External information sources" refer to external means of providing information that offer data related to disasters such as earthquakes and floods.

[0086] "Disaster-related data" refers to data that includes information related to a disaster, such as the type of disaster, the location of the disaster, and its progress.

[0087] An "evacuation route" is route information that shows the path a user should take to evacuate safely.

[0088] "User terminal" refers to information processing devices used by users, such as smartphones and smart glasses.

[0089] "Means of acquiring location information in real time" refers to technical means for instantly determining the user's current location.

[0090] "Means of suggesting travel routes" refers to means of instructing users on a safe and efficient path for travel.

[0091] "Voice guide" is a function that provides information and instructions to users through voice.

[0092] This invention is a system that supports safe movement during disasters and in daily life. To realize this system, a server and a user's terminal work together.

[0093] The server first stores personal information submitted by the user in a database. This personal information includes the user's age, gender, physical condition, and place of residence. Next, the server collects disaster-related data from external sources. This data includes information about disasters such as earthquakes and floods, and is analyzed to identify high-risk areas.

[0094] Subsequently, the server uses a generation AI model to combine the user's personal characteristics information with disaster-related data to generate optimal evacuation and travel routes. The generated route information is then sent to the user's terminal.

[0095] The user terminal visually displays the received evacuation route on a map application. The terminal also features voice guidance, providing directions even in situations where visual confirmation is not possible. The terminal acquires location information in real time and uses this to provide the latest route guidance. This allows for rapid adaptation to changing circumstances.

[0096] For example, if a user receives a disaster warning while cycling, the system will immediately suggest an alternative route to support safe travel. An example of a prompt message could be: "Develop a program that suggests a safe commute route based on the user's location, health status, and real-time disaster information."

[0097] Thus, the present invention provides multi-layered support for user safety and can be widely used, from evacuation during disasters to daily travel.

[0098] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0099] Step 1:

[0100] The user uses a terminal to enter personal information, including age, gender, physical condition, and place of residence. The entered information is immediately sent to the server and stored in a database along with the user's identification information.

[0101] Step 2:

[0102] The server acquires disaster-related data in real time from external sources. This includes information on the location and progression of disasters such as earthquakes and floods. The acquired data is analyzed to identify hazardous areas. The output provides data on hazardous and safe areas.

[0103] Step 3:

[0104] The server combines stored user personal characteristics information with disaster-related data obtained in step 2. Using a generative AI model, it generates personalized and optimal evacuation and travel routes. The input is user characteristics information and disaster data, and the output is optimized route information.

[0105] Step 4:

[0106] The generated route information is sent from the server to the user's terminal. The terminal receives this information and displays it visually using a map application. Voice guidance is also utilized to provide the user with auditory guidance along their travel route.

[0107] Step 5:

[0108] The user terminal uses GPS to obtain the user's location information in real time. The location information is sent to the server and used to update the evacuation route as needed. The updated route is then guided to the user, similar to step 4.

[0109] Step 6:

[0110] Users move safely based on the route information they receive. By utilizing visual information and audio guidance, flexible evacuation is possible depending on the situation.

[0111] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0112] This invention provides a system that offers an optimized evacuation route based on a user's personal characteristics and emotional state during a disaster. In this embodiment, the system consists of three main components: a server, a user terminal, and an emotion engine.

[0113] Server operation

[0114] The server first stores personal characteristics information obtained from the user's device in a database. This information includes the user's age, gender, physical condition, and place of residence. The server also uses an external disaster information API to obtain the latest disaster-related data and determine safe and dangerous areas. Based on this data and personal characteristics information, the generating AI formulates the optimal evacuation route for each user. Furthermore, it adjusts the evacuation route and its presentation method, taking into account data from the emotion engine, and provides it in the most acceptable form for the user. The server then sends the generated evacuation route to the user's device.

[0115] User's device and the operation of the emotion engine

[0116] The user's device provides evacuation routes transmitted from the server using maps and voice guidance. During this process, the device uses an emotion engine to analyze the user's emotional state and adjusts the voice guidance and displayed messages accordingly. For example, if the user is anxious, the voice guidance tone becomes gentler and encouraging messages are displayed.

[0117] Specific example

[0118] Let's say user C (30 years old, male, constantly in a high-stress work environment) is affected by an earthquake. The server uses C's residential information and personal characteristics to determine the optimal evacuation route. Meanwhile, an emotion engine installed in C's device analyzes his emotional state in real time and recognizes that his stress levels are high. As a result, the device provides C with route guidance in a calming, relaxing voice tone and displays reassuring text messages. In this way, providing appropriate evacuation support tailored to emotions and circumstances can improve the user experience.

[0119] The following describes the processing flow.

[0120] Step 1:

[0121] Users enter personal information (age, gender, physical condition, place of residence) into the app using their device. The entered information is immediately sent to the server.

[0122] Step 2:

[0123] The server periodically retrieves the latest disaster-related data from an external disaster information API. This data includes information on earthquakes, floods, and fires. The retrieved data is analyzed within the server to identify dangerous and safe areas.

[0124] Step 3:

[0125] The server combines stored personal characteristics information with acquired disaster-related data and uses a generating AI to create the optimal evacuation route for each user. In this process, the generating AI optimizes the evacuation route to take into account the user's physical limitations.

[0126] Step 4:

[0127] Evacuation route information generated from the server is sent to the user's device. The device receives this information and visually displays the route on a map application.

[0128] Step 5:

[0129] The device's built-in emotion engine analyzes the user's emotional state in real time. This includes technology that uses the camera and microphone to recognize changes in facial expressions and voice.

[0130] Step 6:

[0131] Based on the analysis results of the emotion engine, the device adjusts the voice tone and message content of the evacuation route guidance. For example, if the user shows signs of anxiety, the guidance voice will be changed to a calmer tone, and a message such as "Don't worry, we will guide you to a safe route" will be displayed on the screen.

[0132] Step 7:

[0133] As users proceed with their evacuation, their devices continuously send update requests to the server. The server re-analyzes the evacuation route based on the new disaster information and resends the latest route if necessary. This loop ensures that users always receive the most up-to-date and optimal evacuation information.

[0134] (Example 2)

[0135] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0136] During disaster evacuations, there are challenges in providing optimal evacuation routes based on individual user attribute information and insufficient guidance tailored to users' emotional states. Therefore, it is necessary to balance evacuation safety with reducing user stress.

[0137] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0138] In this invention, the server includes means for storing attribute information obtained from the user, means for obtaining disaster-related data from an external information source and analyzing its contents, means for using a generation model that generates an evacuation route optimized for the user based on the attribute information and the disaster-related data, means for emotion recognition that analyzes the user's state, and means for transmitting the generated evacuation route information to the user device and adjusting the presented content based on the results of the emotion recognition means. This makes it possible to provide each user with a safe and acceptable evacuation route and to optimize guidance according to their emotional state.

[0139] "Attribute information" refers to information that indicates individual characteristics of a user, such as their age, gender, physical condition, and place of residence.

[0140] "External information sources" refer to external databases and APIs that provide disaster-related data.

[0141] A "generative model" refers to an algorithm or AI model that generates the optimal evacuation route for a user from acquired information.

[0142] "Emotion recognition means" refers to technologies and devices for analyzing a user's emotional state, effectively utilizing facial expressions, voice tone, and input data.

[0143] "User device" refers to a terminal or device owned by a user for receiving and displaying evacuation route information.

[0144] This invention is a system that provides each user with the most suitable evacuation route during a disaster. The system mainly consists of three main components: a server, a user terminal, and an emotion engine. Each component works together to provide personalized support to the user.

[0145] The server stores and manages attribute information obtained from the user's terminal in a database. This enables the provision of services tailored to the user's characteristics. The server also obtains disaster-related data from external sources and analyzes its contents in detail. This analysis includes diverse disaster data such as earthquakes, typhoons, and floods. The server uses a generative model to design the optimal evacuation route based on the user's attribute information and disaster data. The generative model utilizes AI technology and operates based on appropriate prompt statements. For example, a prompt statement such as "Generate the optimal evacuation route during an earthquake for a 30-year-old male user in good physical condition" will generate route instructions tailored to each user.

[0146] The user's device receives evacuation route information provided by the server and visualizes it for the user. Information is presented in an intuitively understandable format using maps and voice guidance. The device also analyzes the user's emotional state using emotion recognition technology. This analysis is used to adjust the tone and message content when the device provides evacuation routes. For example, if the system detects that the user is stressed, it will display a gentler voice tone and a reassuring message.

[0147] For example, if a user is affected by an earthquake, the server uses the user's attribute information and the latest disaster information to design a safe and efficient evacuation route. The user's terminal then provides guidance that takes their emotional state into account based on the received information, supporting the user's sense of security. Through such coordinated activities, users receive optimal support, minimizing confusion during disasters.

[0148] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0149] Step 1:

[0150] The server receives attribute information from the user's terminal. This input includes attribute information such as the user's age, gender, physical condition, and place of residence. By storing this data in a database, individual user profiles are created to prepare for future evacuation route generation.

[0151] Step 2:

[0152] The server retrieves disaster-related data from external sources. Inputs include information such as the type of disaster, location, and affected area, obtained via an API. The server analyzes this information and processes it to identify safe and dangerous areas. The analysis results are used to generate evacuation routes.

[0153] Step 3:

[0154] The server generates evacuation routes using a generative AI model. The inputs are attribute information saved in Step 1 and disaster analysis data obtained in Step 2. Based on these inputs, the generative AI model designs the optimal evacuation route using prompt messages. The output is customized evacuation route data for each user.

[0155] Step 4:

[0156] The server sends the generated evacuation route to the user's terminal. The input is the evacuation route data generated in step 3. This data is presented to the user's terminal visually and audibly.

[0157] Step 5:

[0158] The device analyzes the user's emotional state using emotion recognition technology. Inputs include the user's facial expressions, voice, and touch information. Based on this input, the device performs emotion analysis to determine the user's emotional state. The output is the emotional state information resulting from the analysis.

[0159] Step 6:

[0160] The device adjusts how it presents evacuation routes based on the user's emotional state. The input consists of the evacuation route data obtained in step 4 and the emotional state information obtained in step 5. The device provides reassuring evacuation routes by adding gentle voice guidance and encouraging messages. The output is presented to the user as optimized guidance information.

[0161] (Application Example 2)

[0162] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0163] In recent years, with the increasing frequency of natural disasters, the need for evacuation support optimized for individual users has grown. However, conventional evacuation route guidance systems have the drawback of only providing uniform guidance, without considering the individual characteristics or real-time emotional state of users. Therefore, there is a need to provide a way for users to evacuate safely and without panic during disasters.

[0164] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0165] In this invention, the server includes means for storing personal characteristic information obtained from the user, means for obtaining and analyzing disaster-related data from external sources, means for generating an evacuation route optimized for the user based on the personal characteristic information and the disaster-related data, and means for analyzing the emotional state and adjusting the tone and message of the generated evacuation route guidance. This enables safe and effective evacuation guidance tailored to the individual circumstances of the user.

[0166] "Personal characteristic information obtained from users" refers to individual attribute information necessary for optimizing evacuation routes, such as the user's age, gender, physical condition, and place of residence.

[0167] "Means for acquiring and analyzing disaster-related data from external sources" refers to information processing functions that allow a server to acquire the latest disaster occurrence information using external APIs, etc., and to determine safe and dangerous areas.

[0168] "Methods for generating optimized evacuation routes" refers to algorithms that use generation AI to formulate the optimal evacuation route for each user, based on the user's personal characteristics information and disaster-related data.

[0169] "Means for analyzing emotional states and adjusting the tone and messages of generated evacuation route guidance" refers to a process that uses an emotion engine to evaluate the user's emotions in real time and adjust the voice and display content of the guidance accordingly.

[0170] A "user terminal" refers to a device that receives evacuation route information and provides users with audio and visual guidance, such as a smartphone.

[0171] This invention realizes a system that provides users with an optimized evacuation route during a disaster. The system consists of three main components: a server, a user terminal, and an emotion engine.

[0172] The server manages a database that holds personal characteristics information obtained from users. This information includes the user's age, gender, physical condition, and place of residence. The server obtains the latest disaster-related data from an external disaster information API and analyzes it to identify safe and dangerous areas. Furthermore, it uses a generative AI model to calculate the optimal evacuation route for each user based on their personal characteristics information and disaster-related data.

[0173] The user terminal receives evacuation routes transmitted from the server, displays them visually, and presents them to the user through voice guidance. The terminal is equipped with an emotion engine that has the ability to analyze the user's emotional state in real time. This allows the system to adjust the tone of the guidance and the content of the messages according to the user's emotions, striving to reduce the user's stress.

[0174] For example, if a 30-year-old user experiences an earthquake while under high stress, the server will suggest the optimal evacuation route based on the user's location and personal characteristics. Meanwhile, the device's emotion engine analyzes the user's emotional state, and if it determines that stress levels are high, it can provide guidance in a calming tone and display reassuring messages.

[0175] An example of a prompt to be input into the generating AI model is: "Based on data to provide the optimal evacuation route for a 30-year-old male with high stress levels during a disaster, please design an appropriate evacuation route."

[0176] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0177] Step 1:

[0178] The server retrieves personal information from the user. Input includes data such as the user's age, gender, physical condition, and place of residence. The server stores this information in a database, using it as the basis for user-optimized processing. Output is the storage of this information in the database.

[0179] Step 2:

[0180] The server retrieves the latest disaster-related data from an external disaster information API. This input includes information on the current disaster type, location, safe zones, and hazardous zones. The server analyzes this data and assesses the level of risk. Based on this assessment, it generates a list of areas deemed safe. The output is the analyzed disaster data.

[0181] Step 3:

[0182] The server uses a generative AI model to formulate the optimal evacuation route, taking personal characteristics information and analyzed disaster data as input. This generative AI model calculates the optimal route based on the prompt message: "Design an appropriate evacuation route based on data to provide the optimal evacuation route for a 30-year-old male with high stress levels during a disaster." The output is evacuation route information optimized for each user.

[0183] Step 4:

[0184] The server sends the generated evacuation route information to the user terminal. The user terminal receives the evacuation route information and uses it as input. Based on this information, the terminal generates map data and displays it visually to the user. The output is a visual route display on the user screen.

[0185] Step 5:

[0186] The device uses an emotion engine to analyze the user's emotional state in real time. Input consists of voice tone and facial expression data obtained from the user. Based on this, the device analyzes the user's emotional state and adjusts the guidance tone as needed. Based on these results, it may soften the tone of voice guidance directed at the user or display encouraging messages. Output consists of adjusted voice and text messages.

[0187] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0188] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0189] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0190] [Second Embodiment]

[0191] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0192] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0193] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0194] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0195] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0196] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0197] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0198] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0199] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0200] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0201] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0202] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0203] This invention is a system that provides users with the optimal evacuation route during a disaster. The system mainly consists of a server and user terminals and operates as follows:

[0204] Server operation

[0205] The server first receives personal information entered by the user from their device and stores it in a database. This personal information includes age, gender, physical condition, and place of residence. Next, the server collects the latest data on disasters such as earthquakes and floods through an external disaster information API. Based on this information, the server determines dangerous and safe areas. Furthermore, the server uses a generative AI to combine the user's stored personal information with disaster-related data to generate individually optimized evacuation routes. These generated evacuation routes are then sent to the user's device.

[0206] User terminal behavior

[0207] Users input their personal information using a dedicated application on their device. After this information is sent to the server, they can receive the optimal evacuation route in the event of a disaster. The device visually displays the received evacuation route on a map application and guides the user along that route. Audio guidance is also provided, making it possible to accommodate users who prefer to evacuate without relying on visual cues.

[0208] Specific example

[0209] For example, consider a scenario where an earthquake occurs in the area where user B (60 years old, female, with knee pain) lives, and an evacuation order is issued. The server takes into account B's physical condition, such as her knee pain, and analyzes evacuation routes that allow the use of elevators and avoid stairs. This evacuation route is transmitted to B's terminal, and she is supported in evacuating safely through maps and voice guidance. In this way, the present invention enables flexible disaster response that meets individual needs.

[0210] The following describes the processing flow.

[0211] Step 1:

[0212] Users launch a dedicated terminal application and enter their personal information (age, gender, physical condition, address, etc.). This information is immediately sent to the server and stored in the database.

[0213] Step 2:

[0214] The server periodically uses an external disaster information API to retrieve the latest disaster-related data. This includes detailed information on earthquakes, tsunamis, floods, and other disasters. The server analyzes the retrieved information and generates a map that identifies dangerous and safe areas.

[0215] Step 3:

[0216] When a disaster occurs or is updated, the server integrates each user's personal characteristics information with the latest disaster-related data to generate the optimal evacuation route using AI. This route selection takes into account the user's physical limitations and living environment.

[0217] Step 4:

[0218] The server sends the evacuation route generated for each user to the user's terminal in real time.

[0219] Step 5:

[0220] The device presents the received evacuation route to the user using both map display and voice guidance, helping the user evacuate via the optimal route. Based on this information, the user begins the actual evacuation.

[0221] Step 6:

[0222] While the user is evacuating, the terminal requests the latest disaster information from the server at regular intervals. If the server detects a change in the situation, it sends the newly generated optimal route back to the user's terminal, enabling a flexible response.

[0223] (Example 1)

[0224] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0225] Providing optimal evacuation routes for users with diverse individual characteristics during a disaster is not easy. In particular, it is crucial to respond quickly and flexibly according to the type and progression of the disaster. To achieve efficient evacuation, real-time information provision and route selection tailored to each user's situation are required. Solving this challenge lies in utilizing external information sources and integrating individual characteristic information.

[0226] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0227] In this invention, the server includes means for storing individual characteristic information obtained from users, means for obtaining and analyzing disaster-related information from external information sources, means for generating evacuation routes tailored to users using a generation AI based on the individual characteristic information and the disaster-related information, and means for transferring the generated evacuation route information to user equipment. This makes it possible to provide safe evacuation routes tailored to individual users in real time.

[0228] "Individual characteristic information" refers to information unique to each user, such as age, gender, physical condition, and place of residence, and is data used to optimize evacuation routes.

[0229] "External information sources" refer to APIs and other information supply services that provide disaster-related information, and are means of obtaining the latest data on the type and progress of disasters.

[0230] "Generative AI" refers to a model that uses artificial intelligence technology to generate the optimal evacuation route for a user based on input data.

[0231] An "evacuation route" is information that indicates the optimal route that a user should follow to evacuate safely during a disaster.

[0232] "User equipment" refers to mobile devices and computers that receive evacuation route information and present it visually and audibly.

[0233] Regarding embodiments for carrying out the invention, the present invention is a system that utilizes individual user characteristic information and disaster-related information from external sources during a disaster to provide an optimized evacuation route for the user. The system mainly consists of a server and a user terminal, and its operation details are described below.

[0234] The server receives individual characteristic information sent by users and stores it in its internal database. This information includes the user's age, gender, physical condition, and place of residence, and is data necessary for disaster response. The server then retrieves disaster-related information provided by external sources. These sources are APIs that provide the latest disaster information, such as earthquakes and floods.

[0235] The server uses a generative AI to generate an optimized evacuation route for each user, based on accumulated individual characteristic information and disaster-related information. The generative AI model has the ability to process large amounts of data and quickly derive routes suitable for the user's characteristics. An example of a prompt used in this process is one in the form of "Specify user ID and generate the optimal evacuation route for a specific physical condition."

[0236] The generated evacuation route is transferred to the user's device. The user's device displays the received route and provides visual guidance through a map application. In addition, voice guidance is also provided to complement the visual information and support safe evacuation. For example, if the user has a knee problem, the generated evacuation route will be designed to prioritize elevators and avoid stairs. In this way, the system provides flexible evacuation support that is tailored to individual needs and disaster situations.

[0237] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0238] Step 1:

[0239] The server receives individual characteristic information sent from the user's terminal and stores it in a database. It receives user age, gender, physical condition, and place of residence information as input, organizes and constructs this data, and stores it in the database. Specifically, it analyzes the transmitted data and stores it in a disaster prevention database, associated with the user ID.

[0240] Step 2:

[0241] The server accesses disaster information APIs from external sources to retrieve current and predicted disaster-related data. As input, it identifies disaster types such as earthquakes and floods and collects the latest progress data. It analyzes the retrieved data to determine dangerous and safe areas. This allows for the development of new disaster response measures based on information obtained from external sources.

[0242] Step 3:

[0243] The server uses a generative AI to optimize evacuation routes by combining stored individual characteristic information with collected disaster-related data. The inputs used are the individual characteristic information obtained in Step 1 and the disaster data analyzed in Step 2. The generative AI model is used to calculate the optimal route tailored to each user's characteristics and define a route suitable for evacuation. Specifically, prompts such as "Generate the shortest and safest route for users with disabilities" are used.

[0244] Step 4:

[0245] The server sends the generated evacuation route to the user terminal. It receives the optimized route information generated in step 3 as input and seamlessly transfers it to the user terminal as output. This process includes sending the data in a format optimized for each individual user terminal.

[0246] Step 5:

[0247] The terminal visually displays the received evacuation route on a map application and provides voice guidance. It receives evacuation route information transmitted from a server as input and guides the user through it both visually and audibly. Specifically, it draws the route on a map and uses speech synthesis technology to provide instructions that the user should follow during evacuation.

[0248] Step 6:

[0249] The terminal requests real-time updates of disaster information from the server and receives the changed evacuation routes. It requests new disaster information or modification instructions from the server as input and receives updated evacuation routes as output. This ensures that users are provided with the most effective evacuation route information even as the situation changes.

[0250] (Application Example 1)

[0251] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0252] This invention solves the problem of enhancing user safety and security not only by providing evacuation routes tailored to individual users during disasters, but also by suggesting safe travel routes in real time during daily life. Specifically, it aims to enable rapid response during disasters and provide travel routes that are manageable according to the user's health condition.

[0253] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0254] In this invention, the server includes means for storing personal characteristic information obtained from the user, means for obtaining and analyzing disaster-related data from external information sources, and means for generating an evacuation route optimized for the user based on the personal characteristic information and the disaster-related data. This enables the user to receive appropriate travel route guidance not only during disasters but also in daily life.

[0255] "Personal characteristics information" refers to information that indicates characteristics unique to the user, such as the user's age, gender, physical condition, and place of residence.

[0256] "External information sources" refer to external means of providing information that offer data related to disasters such as earthquakes and floods.

[0257] "Disaster-related data" refers to data that includes information related to a disaster, such as the type of disaster, the location of the disaster, and its progress.

[0258] An "evacuation route" is route information that shows the path a user should take to evacuate safely.

[0259] "User terminal" refers to information processing devices used by users, such as smartphones and smart glasses.

[0260] "Means of acquiring location information in real time" refers to technical means for instantly determining the user's current location.

[0261] "Means of suggesting travel routes" refers to means of instructing users on a safe and efficient path for travel.

[0262] "Voice guide" is a function that provides information and instructions to users through voice.

[0263] This invention is a system that supports safe movement during disasters and in daily life. To realize this system, a server and a user's terminal work together.

[0264] The server first stores personal information submitted by the user in a database. This personal information includes the user's age, gender, physical condition, and place of residence. Next, the server collects disaster-related data from external sources. This data includes information about disasters such as earthquakes and floods, and is analyzed to identify high-risk areas.

[0265] Subsequently, the server uses a generation AI model to combine the user's personal characteristics information with disaster-related data to generate optimal evacuation and travel routes. The generated route information is then sent to the user's terminal.

[0266] The user terminal visually displays the received evacuation route on a map application. The terminal also features voice guidance, providing directions even in situations where visual confirmation is not possible. The terminal acquires location information in real time and uses this to provide the latest route guidance. This allows for rapid adaptation to changing circumstances.

[0267] For example, if a user receives a disaster warning while cycling, the system will immediately suggest an alternative route to support safe travel. An example of a prompt message could be: "Develop a program that suggests a safe commute route based on the user's location, health status, and real-time disaster information."

[0268] Thus, the present invention provides multi-layered support for user safety and can be widely used, from evacuation during disasters to daily travel.

[0269] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0270] Step 1:

[0271] The user uses a terminal to enter personal information, including age, gender, physical condition, and place of residence. The entered information is immediately sent to the server and stored in a database along with the user's identification information.

[0272] Step 2:

[0273] The server acquires disaster-related data in real time from external sources. This includes information on the location and progression of disasters such as earthquakes and floods. The acquired data is analyzed to identify hazardous areas. The output provides data on hazardous and safe areas.

[0274] Step 3:

[0275] The server combines stored user personal characteristics information with disaster-related data obtained in step 2. Using a generative AI model, it generates personalized and optimal evacuation and travel routes. The input is user characteristics information and disaster data, and the output is optimized route information.

[0276] Step 4:

[0277] The generated route information is sent from the server to the user's terminal. The terminal receives this information and displays it visually using a map application. Voice guidance is also utilized to provide the user with auditory guidance along their travel route.

[0278] Step 5:

[0279] The user terminal uses GPS to obtain the user's location information in real time. The location information is sent to the server and used to update the evacuation route as needed. The updated route is then guided to the user, similar to step 4.

[0280] Step 6:

[0281] Users move safely based on the route information they receive. By utilizing visual information and audio guidance, flexible evacuation is possible depending on the situation.

[0282] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion specific model 59 and perform specific processing using the user's emotions.

[0283] The present invention is a system that provides an optimized evacuation route based on the user's personal characteristic information and emotional state during a disaster. In this embodiment, it is composed of three main components: a server, the user's terminal, and an emotion engine.

[0284] Operation of the server

[0285] The server first stores the personal characteristic information obtained from the user's terminal in the database. This information includes the user's age, gender, physical condition, place of residence, etc. Also, the server uses an external disaster information API to obtain the latest disaster-related data and determines safe areas and dangerous areas. Based on this data and the personal characteristic information, the generation AI formulates an optimal evacuation route for each user. Furthermore, considering the data of the emotion engine, the evacuation route and its presentation method are adjusted and provided in a form most acceptable to the user. The server transmits the generated evacuation route to the user terminal.

[0286] Operation of the user's terminal and emotion engine

[0287] The user's terminal provides the evacuation route transmitted from the server to the user using a map and voice guidance. At that time, the terminal analyzes the user's emotional state using the emotion engine and adjusts the voice guidance and display messages according to the result. For example, when the user is anxious, the tone of the voice guidance is made gentle and an encouraging message is displayed.

[0288] Specific example >

[0289] Let's say user C (30 years old, male, constantly in a high-stress work environment) is affected by an earthquake. The server uses C's residential information and personal characteristics to determine the optimal evacuation route. Meanwhile, an emotion engine installed in C's device analyzes his emotional state in real time and recognizes that his stress levels are high. As a result, the device provides C with route guidance in a calming, relaxing voice tone and displays reassuring text messages. In this way, providing appropriate evacuation support tailored to emotions and circumstances can improve the user experience.

[0290] The following describes the processing flow.

[0291] Step 1:

[0292] Users enter personal information (age, gender, physical condition, place of residence) into the app using their device. The entered information is immediately sent to the server.

[0293] Step 2:

[0294] The server periodically retrieves the latest disaster-related data from an external disaster information API. This data includes information on earthquakes, floods, and fires. The retrieved data is analyzed within the server to identify dangerous and safe areas.

[0295] Step 3:

[0296] The server combines stored personal characteristics information with acquired disaster-related data and uses a generating AI to create the optimal evacuation route for each user. In this process, the generating AI optimizes the evacuation route to take into account the user's physical limitations.

[0297] Step 4:

[0298] Evacuation route information generated from the server is sent to the user's device. The device receives this information and visually displays the route on a map application.

[0299] Step 5:

[0300] The emotion engine installed on the terminal analyzes the user's emotional state in real time. This includes technologies for recognizing changes in facial expressions and voices using cameras and microphones.

[0301] Step 6:

[0302] Based on the analysis results of the emotion engine, the terminal adjusts the voice tone and message content for evacuation route guidance. For example, when the user shows anxiety, the guiding voice is changed to a calm tone, and a message such as "Please be at ease. I will guide you to a safe route" is displayed on the screen.

[0303] Step 7:

[0304] While the user is proceeding with evacuation, the terminal continuously sends update requests to the server. The server re-analyzes the evacuation route based on the new disaster information and resends the latest route if a change is necessary. Through this loop, the user can always receive the latest and optimal evacuation information.

[0305] (Example 2)

[0306] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0307] When evacuating during a disaster, there are problems that it is difficult to provide an optimal evacuation route based on the attribute information of individual users, and that guidance according to the user's emotional state is not sufficiently carried out. Therefore, it is required to balance the safety of evacuation and the reduction of the user's stress.

[0308] The specific processing by the specific processing unit 290 of the data processing device in Example 2 is realized by the following means.

[0309] In this invention, the server includes means for storing attribute information obtained from the user, means for obtaining disaster-related data from an external information source and analyzing its contents, means for using a generation model that generates an evacuation route optimized for the user based on the attribute information and the disaster-related data, means for emotion recognition that analyzes the user's state, and means for transmitting the generated evacuation route information to the user device and adjusting the presented content based on the results of the emotion recognition means. This makes it possible to provide each user with a safe and acceptable evacuation route and to optimize guidance according to their emotional state.

[0310] "Attribute information" refers to information that indicates individual characteristics of a user, such as their age, gender, physical condition, and place of residence.

[0311] "External information sources" refer to external databases and APIs that provide disaster-related data.

[0312] A "generative model" refers to an algorithm or AI model that generates the optimal evacuation route for a user from acquired information.

[0313] "Emotion recognition means" refers to technologies and devices for analyzing a user's emotional state, effectively utilizing facial expressions, voice tone, and input data.

[0314] "User device" refers to a terminal or device owned by a user for receiving and displaying evacuation route information.

[0315] This invention is a system that provides each user with the most suitable evacuation route during a disaster. The system mainly consists of three main components: a server, a user terminal, and an emotion engine. Each component works together to provide personalized support to the user.

[0316] The server stores and manages attribute information obtained from the user's terminal in a database. This enables the provision of services tailored to the user's characteristics. The server also obtains disaster-related data from external sources and analyzes its contents in detail. This analysis includes diverse disaster data such as earthquakes, typhoons, and floods. The server uses a generative model to design the optimal evacuation route based on the user's attribute information and disaster data. The generative model utilizes AI technology and operates based on appropriate prompt statements. For example, a prompt statement such as "Generate the optimal evacuation route during an earthquake for a 30-year-old male user in good physical condition" will generate route instructions tailored to each user.

[0317] The user's device receives evacuation route information provided by the server and visualizes it for the user. Information is presented in an intuitively understandable format using maps and voice guidance. The device also analyzes the user's emotional state using emotion recognition technology. This analysis is used to adjust the tone and message content when the device provides evacuation routes. For example, if the system detects that the user is stressed, it will display a gentler voice tone and a reassuring message.

[0318] For example, if a user is affected by an earthquake, the server uses the user's attribute information and the latest disaster information to design a safe and efficient evacuation route. The user's terminal then provides guidance that takes their emotional state into account based on the received information, supporting the user's sense of security. Through such coordinated activities, users receive optimal support, minimizing confusion during disasters.

[0319] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0320] Step 1:

[0321] The server receives attribute information from the user's terminal. This input includes attribute information such as the user's age, gender, physical condition, and place of residence. By storing this data in a database, individual user profiles are created to prepare for future evacuation route generation.

[0322] Step 2:

[0323] The server retrieves disaster-related data from external sources. Inputs include information such as the type of disaster, location, and affected area, obtained via an API. The server analyzes this information and processes it to identify safe and dangerous areas. The analysis results are used to generate evacuation routes.

[0324] Step 3:

[0325] The server generates evacuation routes using a generative AI model. The inputs are attribute information saved in Step 1 and disaster analysis data obtained in Step 2. Based on these inputs, the generative AI model designs the optimal evacuation route using prompt messages. The output is customized evacuation route data for each user.

[0326] Step 4:

[0327] The server sends the generated evacuation route to the user's terminal. The input is the evacuation route data generated in step 3. This data is presented to the user's terminal visually and audibly.

[0328] Step 5:

[0329] The device analyzes the user's emotional state using emotion recognition technology. Inputs include the user's facial expressions, voice, and touch information. Based on this input, the device performs emotion analysis to determine the user's emotional state. The output is the emotional state information resulting from the analysis.

[0330] Step 6:

[0331] The device adjusts how it presents evacuation routes based on the user's emotional state. The input consists of the evacuation route data obtained in step 4 and the emotional state information obtained in step 5. The device provides reassuring evacuation routes by adding gentle voice guidance and encouraging messages. The output is presented to the user as optimized guidance information.

[0332] (Application Example 2)

[0333] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0334] In recent years, with the increasing frequency of natural disasters, the need for evacuation support optimized for individual users has grown. However, conventional evacuation route guidance systems have the drawback of only providing uniform guidance, without considering the individual characteristics or real-time emotional state of users. Therefore, there is a need to provide a way for users to evacuate safely and without panic during disasters.

[0335] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0336] In this invention, the server includes means for storing personal characteristic information obtained from the user, means for obtaining and analyzing disaster-related data from external sources, means for generating an evacuation route optimized for the user based on the personal characteristic information and the disaster-related data, and means for analyzing the emotional state and adjusting the tone and message of the generated evacuation route guidance. This enables safe and effective evacuation guidance tailored to the individual circumstances of the user.

[0337] "Personal characteristic information obtained from users" refers to individual attribute information necessary for optimizing evacuation routes, such as the user's age, gender, physical condition, and place of residence.

[0338] "Means for acquiring and analyzing disaster-related data from external sources" refers to information processing functions that allow a server to acquire the latest disaster occurrence information using external APIs, etc., and to determine safe and dangerous areas.

[0339] "Methods for generating optimized evacuation routes" refers to algorithms that use generation AI to formulate the optimal evacuation route for each user, based on the user's personal characteristics information and disaster-related data.

[0340] "Means for analyzing emotional states and adjusting the tone and messages of generated evacuation route guidance" refers to a process that uses an emotion engine to evaluate the user's emotions in real time and adjust the voice and display content of the guidance accordingly.

[0341] A "user terminal" refers to a device that receives evacuation route information and provides users with audio and visual guidance, such as a smartphone.

[0342] This invention realizes a system that provides users with an optimized evacuation route during a disaster. The system consists of three main components: a server, a user terminal, and an emotion engine.

[0343] The server manages a database that holds personal characteristics information obtained from users. This information includes the user's age, gender, physical condition, and place of residence. The server obtains the latest disaster-related data from an external disaster information API and analyzes it to identify safe and dangerous areas. Furthermore, it uses a generative AI model to calculate the optimal evacuation route for each user based on their personal characteristics information and disaster-related data.

[0344] The user terminal receives evacuation routes transmitted from the server, displays them visually, and presents them to the user through voice guidance. The terminal is equipped with an emotion engine that has the ability to analyze the user's emotional state in real time. This allows the system to adjust the tone of the guidance and the content of the messages according to the user's emotions, striving to reduce the user's stress.

[0345] For example, if a 30-year-old user experiences an earthquake while under high stress, the server will suggest the optimal evacuation route based on the user's location and personal characteristics. Meanwhile, the device's emotion engine analyzes the user's emotional state, and if it determines that stress levels are high, it can provide guidance in a calming tone and display reassuring messages.

[0346] An example of a prompt to be input into the generating AI model is: "Based on data to provide the optimal evacuation route for a 30-year-old male with high stress levels during a disaster, please design an appropriate evacuation route."

[0347] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0348] Step 1:

[0349] The server retrieves personal information from the user. Input includes data such as the user's age, gender, physical condition, and place of residence. The server stores this information in a database, using it as the basis for user-optimized processing. Output is the storage of this information in the database.

[0350] Step 2:

[0351] The server retrieves the latest disaster-related data from an external disaster information API. This input includes information on the current disaster type, location, safe zones, and hazardous zones. The server analyzes this data and assesses the level of risk. Based on this assessment, it generates a list of areas deemed safe. The output is the analyzed disaster data.

[0352] Step 3:

[0353] The server uses a generative AI model to formulate the optimal evacuation route, taking personal characteristics information and analyzed disaster data as input. This generative AI model calculates the optimal route based on the prompt message: "Design an appropriate evacuation route based on data to provide the optimal evacuation route for a 30-year-old male with high stress levels during a disaster." The output is evacuation route information optimized for each user.

[0354] Step 4:

[0355] The server sends the generated evacuation route information to the user terminal. The user terminal receives the evacuation route information and uses it as input. Based on this information, the terminal generates map data and displays it visually to the user. The output is a visual route display on the user screen.

[0356] Step 5:

[0357] The device uses an emotion engine to analyze the user's emotional state in real time. Input consists of voice tone and facial expression data obtained from the user. Based on this, the device analyzes the user's emotional state and adjusts the guidance tone as needed. Based on these results, it may soften the tone of voice guidance directed at the user or display encouraging messages. Output consists of adjusted voice and text messages.

[0358] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0359] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0360] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0361] [Third Embodiment]

[0362] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0363] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0364] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0365] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0366] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0367] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0368] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0369] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0370] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0371] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0372] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0373] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0374] This invention is a system that provides users with the optimal evacuation route during a disaster. The system mainly consists of a server and user terminals and operates as follows:

[0375] Server operation

[0376] The server first receives personal information entered by the user from their device and stores it in a database. This personal information includes age, gender, physical condition, and place of residence. Next, the server collects the latest data on disasters such as earthquakes and floods through an external disaster information API. Based on this information, the server determines dangerous and safe areas. Furthermore, the server uses a generative AI to combine the user's stored personal information with disaster-related data to generate individually optimized evacuation routes. These generated evacuation routes are then sent to the user's device.

[0377] User terminal behavior

[0378] Users input their personal information using a dedicated application on their device. After this information is sent to the server, they can receive the optimal evacuation route in the event of a disaster. The device visually displays the received evacuation route on a map application and guides the user along that route. Audio guidance is also provided, making it possible to accommodate users who prefer to evacuate without relying on visual cues.

[0379] Specific example

[0380] For example, consider a scenario where an earthquake occurs in the area where user B (60 years old, female, with knee pain) lives, and an evacuation order is issued. The server takes into account B's physical condition, such as her knee pain, and analyzes evacuation routes that allow the use of elevators and avoid stairs. This evacuation route is transmitted to B's terminal, and she is supported in evacuating safely through maps and voice guidance. In this way, the present invention enables flexible disaster response that meets individual needs.

[0381] The following describes the processing flow.

[0382] Step 1:

[0383] Users launch a dedicated terminal application and enter their personal information (age, gender, physical condition, address, etc.). This information is immediately sent to the server and stored in the database.

[0384] Step 2:

[0385] The server periodically uses an external disaster information API to retrieve the latest disaster-related data. This includes detailed information on earthquakes, tsunamis, floods, and other disasters. The server analyzes the retrieved information and generates a map that identifies dangerous and safe areas.

[0386] Step 3:

[0387] When a disaster occurs or is updated, the server integrates each user's personal characteristics information with the latest disaster-related data to generate the optimal evacuation route using AI. This route selection takes into account the user's physical limitations and living environment.

[0388] Step 4:

[0389] The server sends the evacuation route generated for each user to the user's terminal in real time.

[0390] Step 5:

[0391] The device presents the received evacuation route to the user using both map display and voice guidance, helping the user evacuate via the optimal route. Based on this information, the user begins the actual evacuation.

[0392] Step 6:

[0393] While the user is evacuating, the terminal requests the latest disaster information from the server at regular intervals. If the server detects a change in the situation, it sends the newly generated optimal route back to the user's terminal, enabling a flexible response.

[0394] (Example 1)

[0395] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0396] Providing optimal evacuation routes for users with diverse individual characteristics during a disaster is not easy. In particular, it is crucial to respond quickly and flexibly according to the type and progression of the disaster. To achieve efficient evacuation, real-time information provision and route selection tailored to each user's situation are required. Solving this challenge lies in utilizing external information sources and integrating individual characteristic information.

[0397] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0398] In this invention, the server includes means for storing individual characteristic information obtained from users, means for obtaining and analyzing disaster-related information from external information sources, means for generating evacuation routes tailored to users using a generation AI based on the individual characteristic information and the disaster-related information, and means for transferring the generated evacuation route information to user equipment. This makes it possible to provide safe evacuation routes tailored to individual users in real time.

[0399] "Individual characteristic information" refers to information unique to each user, such as age, gender, physical condition, and place of residence, and is data used to optimize evacuation routes.

[0400] "External information sources" refer to APIs and other information supply services that provide disaster-related information, and are means of obtaining the latest data on the type and progress of disasters.

[0401] "Generative AI" refers to a model that uses artificial intelligence technology to generate the optimal evacuation route for a user based on input data.

[0402] An "evacuation route" is information that indicates the optimal route that a user should follow to evacuate safely during a disaster.

[0403] "User equipment" refers to mobile devices and computers that receive evacuation route information and present it visually and audibly.

[0404] Regarding embodiments for carrying out the invention, the present invention is a system that utilizes individual user characteristic information and disaster-related information from external sources during a disaster to provide an optimized evacuation route for the user. The system mainly consists of a server and a user terminal, and its operation details are described below.

[0405] The server receives individual characteristic information sent by users and stores it in its internal database. This information includes the user's age, gender, physical condition, and place of residence, and is data necessary for disaster response. The server then retrieves disaster-related information provided by external sources. These sources are APIs that provide the latest disaster information, such as earthquakes and floods.

[0406] The server uses a generative AI to generate an optimized evacuation route for each user, based on accumulated individual characteristic information and disaster-related information. The generative AI model has the ability to process large amounts of data and quickly derive routes suitable for the user's characteristics. An example of a prompt used in this process is one in the form of "Specify user ID and generate the optimal evacuation route for a specific physical condition."

[0407] The generated evacuation route is transferred to the user's device. The user's device displays the received route and provides visual guidance through a map application. In addition, voice guidance is also provided to complement the visual information and support safe evacuation. For example, if the user has a knee problem, the generated evacuation route will be designed to prioritize elevators and avoid stairs. In this way, the system provides flexible evacuation support that is tailored to individual needs and disaster situations.

[0408] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0409] Step 1:

[0410] The server receives individual characteristic information sent from the user's terminal and stores it in a database. It receives user age, gender, physical condition, and place of residence information as input, organizes and structures this data, and stores it in the database. Specifically, it analyzes the transmitted data and stores it in a disaster prevention database, associated with the user ID.

[0411] Step 2:

[0412] The server accesses disaster information APIs from external sources to retrieve current and predicted disaster-related data. As input, it identifies disaster types such as earthquakes and floods and collects the latest progress data. It analyzes the retrieved data to determine dangerous and safe areas. This allows for the development of new disaster response measures based on information obtained from external sources.

[0413] Step 3:

[0414] The server uses a generative AI to optimize evacuation routes by combining stored individual characteristic information with collected disaster-related data. The inputs used are the individual characteristic information obtained in Step 1 and the disaster data analyzed in Step 2. The generative AI model is used to calculate the optimal route tailored to each user's characteristics and define a route suitable for evacuation. Specifically, prompts such as "Generate the shortest and safest route for users with disabilities" are used.

[0415] Step 4:

[0416] The server sends the generated evacuation route to the user terminal. It receives the optimized route information generated in step 3 as input and seamlessly transfers it to the user terminal as output. This process includes sending the data in a format optimized for each individual user terminal.

[0417] Step 5:

[0418] The terminal visually displays the received evacuation route on a map application and provides voice guidance. It receives evacuation route information transmitted from a server as input and guides the user through it both visually and audibly. Specifically, it draws the route on a map and uses speech synthesis technology to provide instructions that the user should follow during evacuation.

[0419] Step 6:

[0420] The terminal requests real-time updates of disaster information from the server and receives the changed evacuation routes. It requests new disaster information or modification instructions from the server as input and receives updated evacuation routes as output. This ensures that users are provided with the most effective evacuation route information even as the situation changes.

[0421] (Application Example 1)

[0422] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0423] This invention solves the problem of enhancing user safety and security not only by providing evacuation routes tailored to individual users during disasters, but also by suggesting safe travel routes in real time during daily life. Specifically, it aims to enable rapid response during disasters and provide travel routes that are manageable according to the user's health condition.

[0424] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0425] In this invention, the server includes means for storing personal characteristic information obtained from the user, means for obtaining and analyzing disaster-related data from external information sources, and means for generating an evacuation route optimized for the user based on the personal characteristic information and the disaster-related data. This enables the user to receive appropriate travel route guidance not only during disasters but also in daily life.

[0426] "Personal characteristics information" refers to information that indicates characteristics unique to the user, such as the user's age, gender, physical condition, and place of residence.

[0427] "External information sources" refer to external means of providing information that offer data related to disasters such as earthquakes and floods.

[0428] "Disaster-related data" refers to data that includes information related to a disaster, such as the type of disaster, the location of the disaster, and its progress.

[0429] An "evacuation route" is route information that shows the path a user should take to evacuate safely.

[0430] "User terminal" refers to information processing devices used by users, such as smartphones and smart glasses.

[0431] "Means of acquiring location information in real time" refers to technical means for instantly determining the user's current location.

[0432] "Means of suggesting travel routes" refers to means of instructing users on a safe and efficient path for travel.

[0433] "Voice guide" is a function that provides information and instructions to users through voice.

[0434] This invention is a system that supports safe movement during disasters and in daily life. To realize this system, a server and a user's terminal work together.

[0435] The server first stores personal information submitted by the user in a database. This personal information includes the user's age, gender, physical condition, and place of residence. Next, the server collects disaster-related data from external sources. This data includes information about disasters such as earthquakes and floods, and is analyzed to identify high-risk areas.

[0436] Subsequently, the server uses a generation AI model to combine the user's personal characteristics information with disaster-related data to generate optimal evacuation and travel routes. The generated route information is then sent to the user's terminal.

[0437] The user terminal visually displays the received evacuation route on a map application. The terminal also features voice guidance, providing directions even in situations where visual confirmation is not possible. The terminal acquires location information in real time and uses this to provide the latest route guidance. This allows for rapid adaptation to changing circumstances.

[0438] For example, if a user receives a disaster warning while cycling, the system will immediately suggest an alternative route to support safe travel. An example of a prompt message could be: "Develop a program that suggests a safe commute route based on the user's location, health status, and real-time disaster information."

[0439] Thus, the present invention provides multi-layered support for user safety and can be widely used, from evacuation during disasters to daily travel.

[0440] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0441] Step 1:

[0442] The user uses a terminal to enter personal information, including age, gender, physical condition, and place of residence. The entered information is immediately sent to the server and stored in a database along with the user's identification information.

[0443] Step 2:

[0444] The server acquires disaster-related data in real time from external sources. This includes information on the location and progression of disasters such as earthquakes and floods. The acquired data is analyzed to identify hazardous areas. The output provides data on hazardous and safe areas.

[0445] Step 3:

[0446] The server combines stored user personal characteristics information with disaster-related data obtained in step 2. Using a generative AI model, it generates personalized and optimal evacuation and travel routes. The input is user characteristics information and disaster data, and the output is optimized route information.

[0447] Step 4:

[0448] The generated route information is sent from the server to the user's terminal. The terminal receives this information and displays it visually using a map application. Voice guidance is also utilized to provide the user with auditory guidance along their travel route.

[0449] Step 5:

[0450] The user terminal uses GPS to obtain the user's location information in real time. The location information is sent to the server and used to update the evacuation route as needed. The updated route is then guided to the user, similar to step 4.

[0451] Step 6:

[0452] Users move safely based on the route information they receive. By utilizing visual information and audio guidance, flexible evacuation is possible depending on the situation.

[0453] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0454] This invention provides a system that offers an optimized evacuation route based on a user's personal characteristics and emotional state during a disaster. In this embodiment, the system consists of three main components: a server, a user terminal, and an emotion engine.

[0455] Server operation

[0456] The server first stores personal characteristics information obtained from the user's device in a database. This information includes the user's age, gender, physical condition, and place of residence. The server also uses an external disaster information API to obtain the latest disaster-related data and determine safe and dangerous areas. Based on this data and personal characteristics information, the generating AI formulates the optimal evacuation route for each user. Furthermore, it adjusts the evacuation route and its presentation method, taking into account data from the emotion engine, and provides it in the most acceptable form for the user. The server then sends the generated evacuation route to the user's device.

[0457] User's device and the operation of the emotion engine

[0458] The user's device provides evacuation routes transmitted from the server using maps and voice guidance. During this process, the device uses an emotion engine to analyze the user's emotional state and adjusts the voice guidance and displayed messages accordingly. For example, if the user is anxious, the voice guidance tone becomes gentler and encouraging messages are displayed.

[0459] Specific example

[0460] Let's say user C (30 years old, male, constantly in a high-stress work environment) is affected by an earthquake. The server uses C's residential information and personal characteristics to determine the optimal evacuation route. Meanwhile, an emotion engine installed in C's device analyzes his emotional state in real time and recognizes that his stress levels are high. As a result, the device provides C with route guidance in a calming, relaxing voice tone and displays reassuring text messages. In this way, providing appropriate evacuation support tailored to emotions and circumstances can improve the user experience.

[0461] The following describes the processing flow.

[0462] Step 1:

[0463] Users enter personal information (age, gender, physical condition, place of residence) into the app using their device. The entered information is immediately sent to the server.

[0464] Step 2:

[0465] The server periodically retrieves the latest disaster-related data from an external disaster information API. This data includes information on earthquakes, floods, and fires. The retrieved data is analyzed within the server to identify dangerous and safe areas.

[0466] Step 3:

[0467] The server combines stored personal characteristics information with acquired disaster-related data and uses a generating AI to create the optimal evacuation route for each user. In this process, the generating AI optimizes the evacuation route to take into account the user's physical limitations.

[0468] Step 4:

[0469] Evacuation route information generated from the server is sent to the user's device. The device receives this information and visually displays the route on a map application.

[0470] Step 5:

[0471] The device's built-in emotion engine analyzes the user's emotional state in real time. This includes technology that uses the camera and microphone to recognize changes in facial expressions and voice.

[0472] Step 6:

[0473] Based on the analysis results of the emotion engine, the device adjusts the voice tone and message content of the evacuation route guidance. For example, if the user shows signs of anxiety, the guidance voice will be changed to a calmer tone, and a message such as "Don't worry, we will guide you to a safe route" will be displayed on the screen.

[0474] Step 7:

[0475] As users proceed with their evacuation, their devices continuously send update requests to the server. The server re-analyzes the evacuation route based on the new disaster information and resends the latest route if necessary. This loop ensures that users always receive the most up-to-date and optimal evacuation information.

[0476] (Example 2)

[0477] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0478] During disaster evacuations, there are challenges in providing optimal evacuation routes based on individual user attribute information and insufficient guidance tailored to users' emotional states. Therefore, it is necessary to balance evacuation safety with reducing user stress.

[0479] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0480] In this invention, the server includes means for storing attribute information obtained from the user, means for obtaining disaster-related data from an external information source and analyzing its contents, means for using a generation model that generates an evacuation route optimized for the user based on the attribute information and the disaster-related data, means for emotion recognition that analyzes the user's state, and means for transmitting the generated evacuation route information to the user device and adjusting the presented content based on the results of the emotion recognition means. This makes it possible to provide each user with a safe and acceptable evacuation route and to optimize guidance according to their emotional state.

[0481] "Attribute information" refers to information that indicates individual characteristics of a user, such as their age, gender, physical condition, and place of residence.

[0482] "External information sources" refer to external databases and APIs that provide disaster-related data.

[0483] A "generative model" refers to an algorithm or AI model that generates the optimal evacuation route for a user from acquired information.

[0484] "Emotion recognition means" refers to technologies and devices for analyzing a user's emotional state, effectively utilizing facial expressions, voice tone, and input data.

[0485] "User device" refers to a terminal or device owned by a user for receiving and displaying evacuation route information.

[0486] This invention is a system that provides each user with the most suitable evacuation route during a disaster. The system mainly consists of three main components: a server, a user terminal, and an emotion engine. Each component works together to provide personalized support to the user.

[0487] The server stores and manages attribute information obtained from the user's terminal in a database. This enables the provision of services tailored to the user's characteristics. The server also obtains disaster-related data from external sources and analyzes its contents in detail. This analysis includes diverse disaster data such as earthquakes, typhoons, and floods. The server uses a generative model to design the optimal evacuation route based on the user's attribute information and disaster data. The generative model utilizes AI technology and operates based on appropriate prompt statements. For example, a prompt statement such as "Generate the optimal evacuation route during an earthquake for a 30-year-old male user in good physical condition" will generate route instructions tailored to each user.

[0488] The user's device receives evacuation route information provided by the server and visualizes it for the user. Information is presented in an intuitively understandable format using maps and voice guidance. The device also analyzes the user's emotional state using emotion recognition technology. This analysis is used to adjust the tone and message content when the device provides evacuation routes. For example, if the system detects that the user is stressed, it will display a gentler voice tone and a reassuring message.

[0489] For example, if a user is affected by an earthquake, the server uses the user's attribute information and the latest disaster information to design a safe and efficient evacuation route. The user's terminal then provides guidance that takes their emotional state into account based on the received information, supporting the user's sense of security. Through such coordinated activities, users receive optimal support, minimizing confusion during disasters.

[0490] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0491] Step 1:

[0492] The server receives attribute information from the user's terminal. This input includes attribute information such as the user's age, gender, physical condition, and place of residence. By storing this data in a database, individual user profiles are created to prepare for future evacuation route generation.

[0493] Step 2:

[0494] The server retrieves disaster-related data from external sources. Inputs include information such as the type of disaster, location, and affected area, obtained via an API. The server analyzes this information and processes it to identify safe and dangerous areas. The analysis results are used to generate evacuation routes.

[0495] Step 3:

[0496] The server generates evacuation routes using a generative AI model. The inputs are attribute information saved in Step 1 and disaster analysis data obtained in Step 2. Based on these inputs, the generative AI model designs the optimal evacuation route using prompt messages. The output is customized evacuation route data for each user.

[0497] Step 4:

[0498] The server sends the generated evacuation route to the user's terminal. The input is the evacuation route data generated in step 3. This data is presented to the user's terminal visually and audibly.

[0499] Step 5:

[0500] The device analyzes the user's emotional state using emotion recognition technology. Inputs include the user's facial expressions, voice, and touch information. Based on this input, the device performs emotion analysis to determine the user's emotional state. The output is the emotional state information resulting from the analysis.

[0501] Step 6:

[0502] The device adjusts how it presents evacuation routes based on the user's emotional state. The input consists of the evacuation route data obtained in step 4 and the emotional state information obtained in step 5. The device provides reassuring evacuation routes by adding gentle voice guidance and encouraging messages. The output is presented to the user as optimized guidance information.

[0503] (Application Example 2)

[0504] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0505] In recent years, with the increasing frequency of natural disasters, the need for evacuation support optimized for individual users has grown. However, conventional evacuation route guidance systems have the drawback of only providing uniform guidance, without considering the individual characteristics or real-time emotional state of users. Therefore, there is a need to provide a way for users to evacuate safely and without panic during disasters.

[0506] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0507] In this invention, the server includes means for storing personal characteristic information obtained from the user, means for obtaining and analyzing disaster-related data from external sources, means for generating an evacuation route optimized for the user based on the personal characteristic information and the disaster-related data, and means for analyzing the emotional state and adjusting the tone and message of the generated evacuation route guidance. This enables safe and effective evacuation guidance tailored to the individual circumstances of the user.

[0508] "Personal characteristic information obtained from users" refers to individual attribute information necessary for optimizing evacuation routes, such as the user's age, gender, physical condition, and place of residence.

[0509] "Means for acquiring and analyzing disaster-related data from external sources" refers to information processing functions that allow a server to acquire the latest disaster occurrence information using external APIs, etc., and to determine safe and dangerous areas.

[0510] "Methods for generating optimized evacuation routes" refers to algorithms that use generation AI to formulate the optimal evacuation route for each user, based on the user's personal characteristics information and disaster-related data.

[0511] "Means for analyzing emotional states and adjusting the tone and messages of generated evacuation route guidance" refers to a process that uses an emotion engine to evaluate the user's emotions in real time and adjust the voice and display content of the guidance accordingly.

[0512] A "user terminal" refers to a device that receives evacuation route information and provides users with audio and visual guidance, such as a smartphone.

[0513] This invention realizes a system that provides users with an optimized evacuation route during a disaster. The system consists of three main components: a server, a user terminal, and an emotion engine.

[0514] The server manages a database that holds personal characteristics information obtained from users. This information includes the user's age, gender, physical condition, and place of residence. The server obtains the latest disaster-related data from an external disaster information API and analyzes it to identify safe and dangerous areas. Furthermore, it uses a generative AI model to calculate the optimal evacuation route for each user based on their personal characteristics information and disaster-related data.

[0515] The user terminal receives evacuation routes transmitted from the server, displays them visually, and presents them to the user through voice guidance. The terminal is equipped with an emotion engine that has the ability to analyze the user's emotional state in real time. This allows the system to adjust the tone of the guidance and the content of the messages according to the user's emotions, striving to reduce the user's stress.

[0516] For example, if a 30-year-old user experiences an earthquake while under high stress, the server will suggest the optimal evacuation route based on the user's location and personal characteristics. Meanwhile, the device's emotion engine analyzes the user's emotional state, and if it determines that stress levels are high, it can provide guidance in a calming tone and display reassuring messages.

[0517] An example of a prompt to be input into the generating AI model is: "Based on data to provide the optimal evacuation route for a 30-year-old male with high stress levels during a disaster, please design an appropriate evacuation route."

[0518] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0519] Step 1:

[0520] The server retrieves personal information from the user. Input includes data such as the user's age, gender, physical condition, and place of residence. The server stores this information in a database, using it as the basis for user-optimized processing. Output is the storage of this information in the database.

[0521] Step 2:

[0522] The server retrieves the latest disaster-related data from an external disaster information API. This input includes information on the current disaster type, location, safe zones, and hazardous zones. The server analyzes this data and assesses the level of risk. Based on this assessment, it generates a list of areas deemed safe. The output is the analyzed disaster data.

[0523] Step 3:

[0524] The server uses a generative AI model to formulate the optimal evacuation route, taking personal characteristics information and analyzed disaster data as input. This generative AI model calculates the optimal route based on the prompt message: "Design an appropriate evacuation route based on data to provide the optimal evacuation route for a 30-year-old male with high stress levels during a disaster." The output is evacuation route information optimized for each user.

[0525] Step 4:

[0526] The server sends the generated evacuation route information to the user terminal. The user terminal receives the evacuation route information and uses it as input. Based on this information, the terminal generates map data and displays it visually to the user. The output is a visual route display on the user screen.

[0527] Step 5:

[0528] The device uses an emotion engine to analyze the user's emotional state in real time. Input consists of voice tone and facial expression data obtained from the user. Based on this, the device analyzes the user's emotional state and adjusts the guidance tone as needed. Based on these results, it may soften the tone of voice guidance directed at the user or display encouraging messages. Output consists of adjusted voice and text messages.

[0529] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0530] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0531] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0532] [Fourth Embodiment]

[0533] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0534] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0535] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0536] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0537] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0538] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0539] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0540] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0541] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0542] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0543] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0544] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0545] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0546] This invention is a system that provides users with the optimal evacuation route during a disaster. The system mainly consists of a server and user terminals and operates as follows:

[0547] Server operation

[0548] The server first receives personal information entered by the user from their device and stores it in a database. This personal information includes age, gender, physical condition, and place of residence. Next, the server collects the latest data on disasters such as earthquakes and floods through an external disaster information API. Based on this information, the server determines dangerous and safe areas. Furthermore, the server uses a generative AI to combine the user's stored personal information with disaster-related data to generate individually optimized evacuation routes. These generated evacuation routes are then sent to the user's device.

[0549] User terminal behavior

[0550] Users input their personal information using a dedicated application on their device. After this information is sent to the server, they can receive the optimal evacuation route in the event of a disaster. The device visually displays the received evacuation route on a map application and guides the user along that route. Audio guidance is also provided, making it possible to accommodate users who prefer to evacuate without relying on visual cues.

[0551] Specific example

[0552] For example, consider a scenario where an earthquake occurs in the area where user B (60 years old, female, with knee pain) lives, and an evacuation order is issued. The server takes into account B's physical condition, such as her knee pain, and analyzes evacuation routes that allow the use of elevators and avoid stairs. This evacuation route is transmitted to B's terminal, and she is supported in evacuating safely through maps and voice guidance. In this way, the present invention enables flexible disaster response that meets individual needs.

[0553] The following describes the processing flow.

[0554] Step 1:

[0555] Users launch a dedicated terminal application and enter their personal information (age, gender, physical condition, address, etc.). This information is immediately sent to the server and stored in the database.

[0556] Step 2:

[0557] The server periodically uses an external disaster information API to retrieve the latest disaster-related data. This includes detailed information on earthquakes, tsunamis, floods, and other disasters. The server analyzes the retrieved information and generates a map that identifies dangerous and safe areas.

[0558] Step 3:

[0559] When a disaster occurs or is updated, the server integrates each user's personal characteristics information with the latest disaster-related data to generate the optimal evacuation route using AI. This route selection takes into account the user's physical limitations and living environment.

[0560] Step 4:

[0561] The server sends the evacuation route generated for each user to the user's terminal in real time.

[0562] Step 5:

[0563] The device presents the received evacuation route to the user using both map display and voice guidance, helping the user evacuate via the optimal route. Based on this information, the user begins the actual evacuation.

[0564] Step 6:

[0565] While the user is evacuating, the terminal requests the latest disaster information from the server at regular intervals. If the server detects a change in the situation, it sends the newly generated optimal route back to the user's terminal, enabling a flexible response.

[0566] (Example 1)

[0567] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0568] Providing optimal evacuation routes for users with diverse individual characteristics during a disaster is not easy. In particular, it is crucial to respond quickly and flexibly according to the type and progression of the disaster. To achieve efficient evacuation, real-time information provision and route selection tailored to each user's situation are required. Solving this challenge lies in utilizing external information sources and integrating individual characteristic information.

[0569] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0570] In this invention, the server includes means for storing individual characteristic information obtained from users, means for obtaining and analyzing disaster-related information from external information sources, means for generating evacuation routes tailored to users using a generation AI based on the individual characteristic information and the disaster-related information, and means for transferring the generated evacuation route information to user equipment. This makes it possible to provide safe evacuation routes tailored to individual users in real time.

[0571] "Individual characteristic information" refers to information unique to each user, such as age, gender, physical condition, and place of residence, and is data used to optimize evacuation routes.

[0572] "External information sources" refer to APIs and other information supply services that provide disaster-related information, and are means of obtaining the latest data on the type and progress of disasters.

[0573] "Generative AI" refers to a model that uses artificial intelligence technology to generate the optimal evacuation route for a user based on input data.

[0574] An "evacuation route" is information that indicates the optimal route that a user should follow to evacuate safely during a disaster.

[0575] "User equipment" refers to mobile devices and computers that receive evacuation route information and present it visually and audibly.

[0576] Regarding embodiments for carrying out the invention, the present invention is a system that utilizes individual user characteristic information and disaster-related information from external sources during a disaster to provide an optimized evacuation route for the user. The system mainly consists of a server and a user terminal, and its operation details are described below.

[0577] The server receives individual characteristic information sent by users and stores it in its internal database. This information includes the user's age, gender, physical condition, and place of residence, and is data necessary for disaster response. The server then retrieves disaster-related information provided by external sources. These sources are APIs that provide the latest disaster information, such as earthquakes and floods.

[0578] The server uses a generative AI to generate an optimized evacuation route for each user, based on accumulated individual characteristic information and disaster-related information. The generative AI model has the ability to process large amounts of data and quickly derive routes suitable for the user's characteristics. An example of a prompt used in this process is one in the form of "Specify user ID and generate the optimal evacuation route for a specific physical condition."

[0579] The generated evacuation route is transferred to the user's device. The user's device displays the received route and provides visual guidance through a map application. In addition, voice guidance is also provided to complement the visual information and support safe evacuation. For example, if the user has a knee problem, the generated evacuation route will be designed to prioritize elevators and avoid stairs. In this way, the system provides flexible evacuation support that is tailored to individual needs and disaster situations.

[0580] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0581] Step 1:

[0582] The server receives individual characteristic information sent from the user's terminal and stores it in a database. It receives user age, gender, physical condition, and place of residence information as input, organizes and structures this data, and stores it in the database. Specifically, it analyzes the transmitted data and stores it in a disaster prevention database, associated with the user ID.

[0583] Step 2:

[0584] The server accesses disaster information APIs from external sources to retrieve current and predicted disaster-related data. As input, it identifies disaster types such as earthquakes and floods and collects the latest progress data. It analyzes the retrieved data to determine dangerous and safe areas. This allows for the development of new disaster response measures based on information obtained from external sources.

[0585] Step 3:

[0586] The server uses a generative AI to optimize evacuation routes by combining stored individual characteristic information with collected disaster-related data. The inputs used are the individual characteristic information obtained in Step 1 and the disaster data analyzed in Step 2. The generative AI model is used to calculate the optimal route tailored to each user's characteristics and define a route suitable for evacuation. Specifically, prompts such as "Generate the shortest and safest route for users with disabilities" are used.

[0587] Step 4:

[0588] The server sends the generated evacuation route to the user terminal. It receives the optimized route information generated in step 3 as input and seamlessly transfers it to the user terminal as output. This process includes sending the data in a format optimized for each individual user terminal.

[0589] Step 5:

[0590] The terminal visually displays the received evacuation route on a map application and provides voice guidance. It receives evacuation route information transmitted from a server as input and guides the user through it both visually and audibly. Specifically, it draws the route on a map and uses speech synthesis technology to provide instructions that the user should follow during evacuation.

[0591] Step 6:

[0592] The terminal requests real-time updates of disaster information from the server and receives the changed evacuation routes. It requests new disaster information or modification instructions from the server as input and receives updated evacuation routes as output. This ensures that users are provided with the most effective evacuation route information even as the situation changes.

[0593] (Application Example 1)

[0594] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0595] This invention solves the problem of enhancing user safety and security not only by providing evacuation routes tailored to individual users during disasters, but also by suggesting safe travel routes in real time during daily life. Specifically, it aims to enable rapid response during disasters and provide travel routes that are manageable according to the user's health condition.

[0596] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0597] In this invention, the server includes means for storing personal characteristic information obtained from the user, means for obtaining and analyzing disaster-related data from external information sources, and means for generating an evacuation route optimized for the user based on the personal characteristic information and the disaster-related data. This enables the user to receive appropriate travel route guidance not only during disasters but also in daily life.

[0598] "Personal characteristics information" refers to information that indicates characteristics unique to the user, such as the user's age, gender, physical condition, and place of residence.

[0599] "External information sources" refer to external means of providing information that offer data related to disasters such as earthquakes and floods.

[0600] "Disaster-related data" refers to data that includes information related to a disaster, such as the type of disaster, the location of the disaster, and its progress.

[0601] An "evacuation route" is route information that shows the path a user should take to evacuate safely.

[0602] "User terminal" refers to information processing devices used by users, such as smartphones and smart glasses.

[0603] "Means of acquiring location information in real time" refers to technical means for instantly determining the user's current location.

[0604] "Means of suggesting travel routes" refers to means of instructing users on a safe and efficient path for travel.

[0605] "Voice guide" is a function that provides information and instructions to users through voice.

[0606] This invention is a system that supports safe movement during disasters and in daily life. To realize this system, a server and a user's terminal work together.

[0607] The server first stores personal information submitted by the user in a database. This personal information includes the user's age, gender, physical condition, and place of residence. Next, the server collects disaster-related data from external sources. This data includes information about disasters such as earthquakes and floods, and is analyzed to identify high-risk areas.

[0608] Subsequently, the server uses a generation AI model to combine the user's personal characteristics information with disaster-related data to generate optimal evacuation and travel routes. The generated route information is then sent to the user's terminal.

[0609] The user terminal visually displays the received evacuation route on a map application. The terminal also features voice guidance, providing directions even in situations where visual confirmation is not possible. The terminal acquires location information in real time and uses this to provide the latest route guidance. This allows for rapid adaptation to changing circumstances.

[0610] For example, if a user receives a disaster warning while cycling, the system will immediately suggest an alternative route to support safe travel. An example of a prompt message could be: "Develop a program that suggests a safe commute route based on the user's location, health status, and real-time disaster information."

[0611] Thus, the present invention provides multi-layered support for user safety and can be widely used, from evacuation during disasters to daily travel.

[0612] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0613] Step 1:

[0614] The user uses a terminal to enter personal information, including age, gender, physical condition, and place of residence. The entered information is immediately sent to the server and stored in a database along with the user's identification information.

[0615] Step 2:

[0616] The server acquires disaster-related data in real time from external sources. This includes information on the location and progression of disasters such as earthquakes and floods. The acquired data is analyzed to identify hazardous areas. The output provides data on hazardous and safe areas.

[0617] Step 3:

[0618] The server combines stored user personal characteristics information with disaster-related data obtained in step 2. Using a generative AI model, it generates personalized and optimal evacuation and travel routes. The input is user characteristics information and disaster data, and the output is optimized route information.

[0619] Step 4:

[0620] The generated route information is sent from the server to the user's terminal. The terminal receives this information and displays it visually using a map application. Voice guidance is also utilized to provide the user with auditory guidance along their travel route.

[0621] Step 5:

[0622] The user terminal uses GPS to obtain the user's location information in real time. The location information is sent to the server and used to update the evacuation route as needed. The updated route is then guided to the user, similar to step 4.

[0623] Step 6:

[0624] Users move safely based on the route information they receive. By utilizing visual information and audio guidance, flexible evacuation is possible depending on the situation.

[0625] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0626] This invention provides a system that offers an optimized evacuation route based on a user's personal characteristics and emotional state during a disaster. In this embodiment, the system consists of three main components: a server, a user terminal, and an emotion engine.

[0627] Server operation

[0628] The server first stores personal characteristics information obtained from the user's device in a database. This information includes the user's age, gender, physical condition, and place of residence. The server also uses an external disaster information API to obtain the latest disaster-related data and determine safe and dangerous areas. Based on this data and personal characteristics information, the generating AI formulates the optimal evacuation route for each user. Furthermore, it adjusts the evacuation route and its presentation method, taking into account data from the emotion engine, and provides it in the most acceptable form for the user. The server then sends the generated evacuation route to the user's device.

[0629] User's device and the operation of the emotion engine

[0630] The user's device provides evacuation routes transmitted from the server using maps and voice guidance. During this process, the device uses an emotion engine to analyze the user's emotional state and adjusts the voice guidance and displayed messages accordingly. For example, if the user is anxious, the voice guidance tone becomes gentler and encouraging messages are displayed.

[0631] Specific example

[0632] Let's say user C (30 years old, male, constantly in a high-stress work environment) is affected by an earthquake. The server uses C's residential information and personal characteristics to determine the optimal evacuation route. Meanwhile, an emotion engine installed in C's device analyzes his emotional state in real time and recognizes that his stress levels are high. As a result, the device provides C with route guidance in a calming, relaxing voice tone and displays reassuring text messages. In this way, providing appropriate evacuation support tailored to emotions and circumstances can improve the user experience.

[0633] The following describes the processing flow.

[0634] Step 1:

[0635] Users enter personal information (age, gender, physical condition, place of residence) into the app using their device. The entered information is immediately sent to the server.

[0636] Step 2:

[0637] The server periodically retrieves the latest disaster-related data from an external disaster information API. This data includes information on earthquakes, floods, and fires. The retrieved data is analyzed within the server to identify dangerous and safe areas.

[0638] Step 3:

[0639] The server combines stored personal characteristics information with acquired disaster-related data and uses a generating AI to create the optimal evacuation route for each user. In this process, the generating AI optimizes the evacuation route to take into account the user's physical limitations.

[0640] Step 4:

[0641] Evacuation route information generated from the server is sent to the user's device. The device receives this information and visually displays the route on a map application.

[0642] Step 5:

[0643] The device's built-in emotion engine analyzes the user's emotional state in real time. This includes technology that uses the camera and microphone to recognize changes in facial expressions and voice.

[0644] Step 6:

[0645] Based on the analysis results of the emotion engine, the device adjusts the voice tone and message content of the evacuation route guidance. For example, if the user shows signs of anxiety, the guidance voice will be changed to a calmer tone, and a message such as "Don't worry, we will guide you to a safe route" will be displayed on the screen.

[0646] Step 7:

[0647] As users proceed with their evacuation, their devices continuously send update requests to the server. The server re-analyzes the evacuation route based on the new disaster information and resends the latest route if necessary. This loop ensures that users always receive the most up-to-date and optimal evacuation information.

[0648] (Example 2)

[0649] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0650] During disaster evacuations, there are challenges in providing optimal evacuation routes based on individual user attribute information and insufficient guidance tailored to users' emotional states. Therefore, it is necessary to balance evacuation safety with reducing user stress.

[0651] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0652] In this invention, the server includes means for storing attribute information obtained from the user, means for obtaining disaster-related data from an external information source and analyzing its contents, means for using a generation model that generates an evacuation route optimized for the user based on the attribute information and the disaster-related data, means for emotion recognition that analyzes the user's state, and means for transmitting the generated evacuation route information to the user device and adjusting the presented content based on the results of the emotion recognition means. This makes it possible to provide each user with a safe and acceptable evacuation route and to optimize guidance according to their emotional state.

[0653] "Attribute information" refers to information that indicates individual characteristics of a user, such as their age, gender, physical condition, and place of residence.

[0654] "External information sources" refer to external databases and APIs that provide disaster-related data.

[0655] A "generative model" refers to an algorithm or AI model that generates the optimal evacuation route for a user from acquired information.

[0656] "Emotion recognition means" refers to technologies and devices for analyzing a user's emotional state, effectively utilizing facial expressions, voice tone, and input data.

[0657] "User device" refers to a terminal or device owned by a user for receiving and displaying evacuation route information.

[0658] This invention is a system that provides each user with the most suitable evacuation route during a disaster. The system mainly consists of three main components: a server, a user terminal, and an emotion engine. Each component works together to provide personalized support to the user.

[0659] The server stores and manages attribute information obtained from the user's terminal in a database. This enables the provision of services tailored to the user's characteristics. The server also obtains disaster-related data from external sources and analyzes its contents in detail. This analysis includes diverse disaster data such as earthquakes, typhoons, and floods. The server uses a generative model to design the optimal evacuation route based on the user's attribute information and disaster data. The generative model utilizes AI technology and operates based on appropriate prompt statements. For example, a prompt statement such as "Generate the optimal evacuation route during an earthquake for a 30-year-old male user in good physical condition" will generate route instructions tailored to each user.

[0660] The user's device receives evacuation route information provided by the server and visualizes it for the user. Information is presented in an intuitively understandable format using maps and voice guidance. The device also analyzes the user's emotional state using emotion recognition technology. This analysis is used to adjust the tone and message content when the device provides evacuation routes. For example, if the system detects that the user is stressed, it will display a gentler voice tone and a reassuring message.

[0661] For example, if a user is affected by an earthquake, the server uses the user's attribute information and the latest disaster information to design a safe and efficient evacuation route. The user's terminal then provides guidance that takes their emotional state into account based on the received information, supporting the user's sense of security. Through such coordinated activities, users receive optimal support, minimizing confusion during disasters.

[0662] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0663] Step 1:

[0664] The server receives attribute information from the user's terminal. This input includes attribute information such as the user's age, gender, physical condition, and place of residence. By storing this data in a database, individual user profiles are created to prepare for future evacuation route generation.

[0665] Step 2:

[0666] The server retrieves disaster-related data from external sources. Inputs include information such as the type of disaster, location, and affected area, obtained via an API. The server analyzes this information and processes it to identify safe and dangerous areas. The analysis results are used to generate evacuation routes.

[0667] Step 3:

[0668] The server generates evacuation routes using a generative AI model. The inputs are attribute information saved in Step 1 and disaster analysis data obtained in Step 2. Based on these inputs, the generative AI model designs the optimal evacuation route using prompt messages. The output is customized evacuation route data for each user.

[0669] Step 4:

[0670] The server sends the generated evacuation route to the user's terminal. The input is the evacuation route data generated in step 3. This data is presented to the user's terminal visually and audibly.

[0671] Step 5:

[0672] The device analyzes the user's emotional state using emotion recognition technology. Inputs include the user's facial expressions, voice, and touch information. Based on this input, the device performs emotion analysis to determine the user's emotional state. The output is the emotional state information resulting from the analysis.

[0673] Step 6:

[0674] The device adjusts how it presents evacuation routes based on the user's emotional state. The input consists of the evacuation route data obtained in step 4 and the emotional state information obtained in step 5. The device provides reassuring evacuation routes by adding gentle voice guidance and encouraging messages. The output is presented to the user as optimized guidance information.

[0675] (Application Example 2)

[0676] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0677] In recent years, with the increasing frequency of natural disasters, the need for evacuation support optimized for individual users has grown. However, conventional evacuation route guidance systems have the drawback of only providing uniform guidance, without considering the individual characteristics or real-time emotional state of users. Therefore, there is a need to provide a way for users to evacuate safely and without panic during disasters.

[0678] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0679] In this invention, the server includes means for storing personal characteristic information obtained from the user, means for obtaining and analyzing disaster-related data from external sources, means for generating an evacuation route optimized for the user based on the personal characteristic information and the disaster-related data, and means for analyzing the emotional state and adjusting the tone and message of the generated evacuation route guidance. This enables safe and effective evacuation guidance tailored to the individual circumstances of the user.

[0680] "Personal characteristic information obtained from users" refers to individual attribute information necessary for optimizing evacuation routes, such as the user's age, gender, physical condition, and place of residence.

[0681] "Means for acquiring and analyzing disaster-related data from external sources" refers to information processing functions that allow a server to acquire the latest disaster occurrence information using external APIs, etc., and to determine safe and dangerous areas.

[0682] "Methods for generating optimized evacuation routes" refers to algorithms that use generation AI to formulate the optimal evacuation route for each user, based on the user's personal characteristics information and disaster-related data.

[0683] "Means for analyzing emotional states and adjusting the tone and messages of generated evacuation route guidance" refers to a process that uses an emotion engine to evaluate the user's emotions in real time and adjust the voice and display content of the guidance accordingly.

[0684] A "user terminal" refers to a device that receives evacuation route information and provides users with audio and visual guidance, such as a smartphone.

[0685] This invention realizes a system that provides users with an optimized evacuation route during a disaster. The system consists of three main components: a server, a user terminal, and an emotion engine.

[0686] The server manages a database that holds personal characteristics information obtained from users. This information includes the user's age, gender, physical condition, and place of residence. The server obtains the latest disaster-related data from an external disaster information API and analyzes it to identify safe and dangerous areas. Furthermore, it uses a generative AI model to calculate the optimal evacuation route for each user based on their personal characteristics information and disaster-related data.

[0687] The user terminal receives evacuation routes transmitted from the server, displays them visually, and presents them to the user through voice guidance. The terminal is equipped with an emotion engine that has the ability to analyze the user's emotional state in real time. This allows the system to adjust the tone of the guidance and the content of the messages according to the user's emotions, striving to reduce the user's stress.

[0688] For example, if a 30-year-old user experiences an earthquake while under high stress, the server will suggest the optimal evacuation route based on the user's location and personal characteristics. Meanwhile, the device's emotion engine analyzes the user's emotional state, and if it determines that stress levels are high, it can provide guidance in a calming tone and display reassuring messages.

[0689] An example of a prompt to be input into the generating AI model is: "Based on data to provide the optimal evacuation route for a 30-year-old male with high stress levels during a disaster, please design an appropriate evacuation route."

[0690] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0691] Step 1:

[0692] The server retrieves personal information from the user. Input includes data such as the user's age, gender, physical condition, and place of residence. The server stores this information in a database, using it as the basis for user-optimized processing. Output is the storage of this information in the database.

[0693] Step 2:

[0694] The server retrieves the latest disaster-related data from an external disaster information API. This input includes information on the current disaster type, location, safe zones, and hazardous zones. The server analyzes this data and assesses the level of risk. Based on this assessment, it generates a list of areas deemed safe. The output is the analyzed disaster data.

[0695] Step 3:

[0696] The server uses a generative AI model to formulate the optimal evacuation route, taking personal characteristics information and analyzed disaster data as input. This generative AI model calculates the optimal route based on the prompt message: "Design an appropriate evacuation route based on data to provide the optimal evacuation route for a 30-year-old male with high stress levels during a disaster." The output is evacuation route information optimized for each user.

[0697] Step 4:

[0698] The server sends the generated evacuation route information to the user terminal. The user terminal receives the evacuation route information and uses it as input. Based on this information, the terminal generates map data and displays it visually to the user. The output is a visual route display on the user screen.

[0699] Step 5:

[0700] The device uses an emotion engine to analyze the user's emotional state in real time. Input consists of voice tone and facial expression data obtained from the user. Based on this, the device analyzes the user's emotional state and adjusts the guidance tone as needed. Based on these results, it may soften the tone of voice guidance directed at the user or display encouraging messages. Output consists of adjusted voice and text messages.

[0701] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0702] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0703] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0704] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0705] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0706] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0707] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0708] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0709] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0710] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0711] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0712] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0713] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0714] 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.

[0715] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0716] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0717] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0718] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0719] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0720] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0721] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0722] The following is further disclosed regarding the embodiments described above.

[0723] (Claim 1)

[0724] A means of storing personal characteristic information obtained from users,

[0725] Means for obtaining and analyzing disaster-related data from external sources,

[0726] A means for generating an evacuation route optimized for the user based on the aforementioned personal characteristics information and the aforementioned disaster-related data,

[0727] Means for transmitting the generated evacuation route information to a user terminal,

[0728] A system that includes this.

[0729] (Claim 2)

[0730] The system according to claim 1, further comprising means for visually displaying the received evacuation route on a user terminal.

[0731] (Claim 3)

[0732] The system according to claim 1, comprising means for a user terminal to request a server to update disaster information in real time and to receive the changed evacuation route.

[0733] "Example 1"

[0734] (Claim 1)

[0735] A means of accumulating individual characteristic information obtained from users,

[0736] A means of obtaining and analyzing disaster-related information from external sources,

[0737] A means for generating an evacuation route suitable for the user using a generated AI based on the aforementioned individual characteristic information and the aforementioned disaster-related information,

[0738] A means for transferring the generated evacuation route information to a user device,

[0739] A system that includes this.

[0740] (Claim 2)

[0741] The system according to claim 1, wherein the user device is equipped with means for visually displaying the received evacuation route and providing voice guidance.

[0742] (Claim 3)

[0743] The system according to claim 1, wherein the user's device includes means for requesting real-time updates of disaster information from a server and receiving changed evacuation routes.

[0744] "Application Example 1"

[0745] (Claim 1)

[0746] A means of storing personal characteristic information obtained from users,

[0747] Means for obtaining and analyzing disaster-related data from external sources,

[0748] A means for generating an evacuation route optimized for the user based on the aforementioned personal characteristics information and the aforementioned disaster-related data,

[0749] Means for transmitting the generated evacuation route information to a user terminal,

[0750] A means of obtaining location information in real time,

[0751] A means for proposing a safe travel route based on the acquired location information and personal characteristics information,

[0752] A system that includes this.

[0753] (Claim 2)

[0754] The system according to claim 1, further comprising means for visually displaying the received evacuation route on a user terminal.

[0755] (Claim 3)

[0756] The system according to claim 1, wherein the user terminal is equipped with means for requesting updates to disaster information from a server in real time and receiving the changed evacuation route, and also equipped with means for guiding the user along the evacuation route using voice guidance.

[0757] "Example 2 of combining an emotion engine"

[0758] (Claim 1)

[0759] A means of storing attribute information obtained from the user,

[0760] A means of obtaining disaster-related data from external sources and analyzing its contents,

[0761] A means of using a generative model that generates an evacuation route optimized for the user based on the attribute information and the disaster-related data,

[0762] An emotion recognition means for analyzing the user's state,

[0763] The generated evacuation route information is transmitted to the user device, and the presentation content is adjusted based on the result of the emotion recognition means,

[0764] A system that includes this.

[0765] (Claim 2)

[0766] The system according to claim 1, wherein the user device includes means for visually and audibly presenting the received evacuation route.

[0767] (Claim 3)

[0768] The system according to claim 1, wherein the user device includes means for requesting an information processing device to update disaster information in real time and for receiving changed evacuation routes.

[0769] "Application example 2 when combining with an emotional engine"

[0770] (Claim 1)

[0771] A means of storing personal characteristic information obtained from users,

[0772] Means for obtaining and analyzing disaster-related data from external sources,

[0773] A means for generating an evacuation route optimized for the user based on the aforementioned personal characteristics information and the aforementioned disaster-related data,

[0774] Means for transmitting the generated evacuation route information to a user terminal,

[0775] A means for analyzing emotional states and adjusting the tone and message of the generated evacuation route guidance,

[0776] A system that includes this.

[0777] (Claim 2)

[0778] The system according to claim 1, further comprising means for visually displaying the received evacuation route on the user terminal and adjusting voice guidance according to the user's emotional state.

[0779] (Claim 3)

[0780] The system according to claim 1, comprising means for a user terminal to request real-time updates of disaster information from a server, receive changed evacuation routes, and provide guidance based on emotional state. [Explanation of Symbols]

[0781] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of storing personal characteristic information obtained from users, Means for obtaining and analyzing disaster-related data from external sources, A means for generating an evacuation route optimized for the user based on the aforementioned personal characteristics information and the aforementioned disaster-related data, Means for transmitting the generated evacuation route information to a user terminal, A system that includes this.

2. The system according to claim 1, further comprising means for visually displaying the received evacuation route on a user terminal.

3. The system according to claim 1, further comprising means for a user terminal to request a server to update disaster information in real time and to receive the changed evacuation route.

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