system

Abstract

We provide the system. [Solution] A device for inputting and storing users' personal information, A device that periodically acquires and transmits the user's current location information, A device for obtaining the latest disaster-related information from external sources, A device that analyzes acquired personal information, current location information, and disaster-related information to generate the optimal evacuation route, A device that provides the user with a generated evacuation route through visual display and audio output, 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 persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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] Recently, due to the frequent occurrence of natural disasters, rapid and safe evacuation has been demanded. However, when all people use the same evacuation route during a disaster, congestion and delays in response time occur, and it is difficult to provide an optimal evacuation method according to individual characteristics. In particular, for the elderly and people with specific physical conditions, an evacuation route considering their own conditions is necessary. However, there is a problem that the current evacuation support system has not fully realized grasping the situation of each individual in real time and providing appropriate information.

Means for Solving the Problems

[0005] This invention provides a means for users to first input their age, gender, and physical information and store it in a database. Next, the terminal periodically acquires the user's current location information and transmits it to a central server. The server obtains the latest disaster information from an external disaster information database and analyzes it together with the user's personal information and current location information. This analysis uses an algorithm that generates the safest and fastest evacuation route, taking into account the user's physical characteristics. Finally, the generated evacuation route is provided to the user's terminal and further output as voice guidance, realizing evacuation support in a form that is easy for the user to understand and can be immediately implemented. As a result, appropriate evacuation routes tailored to individual characteristics are quickly provided, enabling safe evacuation.

[0006] "User personal information" refers to individually identifiable information such as age, gender, and physical information that users register.

[0007] "Current location information" refers to real-time geographical location data obtained through the user's device.

[0008] "Disaster information" refers to the latest disaster-related data concerning earthquakes, typhoons, fires, etc., obtained from databases of the Japan Meteorological Agency and local governments.

[0009] An "evacuation route" is a route recommended for users to evacuate safely and quickly in the event of a disaster.

[0010] "Means of generation" refers to algorithms and programs that analyze users' personal information, current location information, and disaster information to create evacuation routes.

[0011] "Means of providing" refers to an interface for communicating the generated evacuation route to the user, particularly a visual or audio method of information transmission. [Brief explanation of the drawing]

[0012] [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]

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, the labeled 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.

[0016] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0018] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0019] 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."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] This invention is a system that provides the optimal evacuation route in real time according to the individual needs of the user, and is configured as follows: In the initial stage, the user inputs personal information (age, gender, physical information, etc.) through an interface on the terminal. The server then stores the base information of each user and forms the foundation for individualized responses.

[0034] In the event of a disaster, the device acquires the user's current location information in real time and sends it to the server. The server retrieves the latest disaster information from an external disaster information database and analyzes it in combination with the user's current location and personal information. This analysis utilizes a generative AI algorithm to generate safe and rapid evacuation routes. For example, in the case of elderly people, whose movement speed is expected to be relatively slow, routes with fewer slopes and stairs are prioritized.

[0035] The generated evacuation route is transmitted to the terminal and displayed visually to the user, as well as outputted as voice guidance. This allows the user to intuitively understand safe evacuation procedures and begin taking action quickly. For example, if a user is in the city center during an earthquake, the safest walking route is guided, taking into account the surrounding road conditions and the location of evacuation shelters. As a result, the user can evacuate without confusion and quickly secure their safety.

[0036] This system can flexibly respond to different types of disasters and regional characteristics, providing evacuation support with the user's safety as its top priority.

[0037] The following describes the processing flow.

[0038] Step 1:

[0039] The user enters personal information on the device, including age, gender, and physical information. The device prepares to send this information to the server and encrypts the data. The server stores the received data in a database and notifies the device of success.

[0040] Step 2:

[0041] The device uses a GPS sensor to obtain the user's current location. The obtained location information is sent to the server at a specified frequency (e.g., every 5 minutes). The server receives this data and updates the user's profile by linking it to the user's location.

[0042] Step 3:

[0043] The server collects the latest disaster information from external disaster information databases. This includes information on earthquakes, typhoons, and fires. The server analyzes this information to determine the level of risk and the scope of impact.

[0044] Step 4:

[0045] The server combines the user's personal information, current location, and disaster information, and generates evacuation routes using a generation AI algorithm. This algorithm is designed to minimize the risks and travel time of the route according to individual circumstances.

[0046] Step 5:

[0047] The server sends the generated evacuation route to the user's terminal. The terminal displays the received route and starts voice guidance. The user can follow the on-screen instructions to evacuate safely.

[0048] (Example 1)

[0049] 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."

[0050] To quickly provide appropriate evacuation routes and maximize user safety during disasters, dynamic route setting that takes individual attribute information into account is necessary. However, existing systems have difficulty simultaneously achieving real-time data analysis and adjustments based on individual characteristics. Furthermore, if evacuation routes are not presented both visually and aurally, it may hinder users from taking quick and accurate action.

[0051] 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.

[0052] In this invention, the server includes means for acquiring and storing user attribute information, means for periodically acquiring and transmitting user location data, and means for acquiring the latest disaster-related data from external sources. This enables the generation of optimal evacuation routes tailored to the individual characteristics of the user and effective guidance through visual and auditory means.

[0053] A "user" is an individual who inputs information and receives suggestions for evacuation routes.

[0054] "Attribute information" refers to data that indicates individual user characteristics such as age, gender, and physical abilities.

[0055] "Location data" refers to geographical information that indicates the user's current location.

[0056] "Disaster-related data" refers to the latest information, including the type of disaster, location, and scale.

[0057] "Analysis means" refers to the process or algorithm used to calculate the optimal evacuation route based on the acquired information.

[0058] An "evacuation route" is a path established to reach a destination safely and quickly.

[0059] "Visual and auditory instructions" refers to methods of showing users routes using maps or audio guidance.

[0060] This invention relates to a system that provides users with the optimal route for safe evacuation during a disaster. The main components of this system are a server, a terminal, and a user.

[0061] The device has an interface for inputting user attribute information, where the user enters their age, gender, physical abilities, etc. The device uses its built-in GPS function to acquire location data in real time and transmit it to the server.

[0062] The server passively receives user attribute information and location data, and obtains the latest disaster-related data from external sources. The server then uses a generative AI model to calculate the safest and fastest evacuation route based on all the acquired data. This process involves personalized analysis that takes into account individual characteristics such as mobility.

[0063] The generated evacuation route is provided to the user via a terminal. The terminal conveys information to the user intuitively and clearly by combining visual displays and voice guidance. For example, if a user experiences an earthquake in the city center, the terminal can guide them to the optimal walking route, taking into account surrounding traffic conditions and information about evacuation shelters. An example of a prompt used in this case would be: "The user's current location is around Tokyo Station, age 75. The disaster is an earthquake. Please generate the optimal evacuation route, taking into account the condition of surrounding roads and the nearest evacuation shelter."

[0064] This system is designed to support swift and safe evacuation and can flexibly respond to a variety of disaster situations.

[0065] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0066] Step 1:

[0067] The user inputs attribute information (age, gender, physical ability, etc.) using the terminal's interface. This input information is sent from the terminal to the server. The server receives this input information and stores it as the user's individual profile. The data processing performed here involves verifying the user information and registering it in the database.

[0068] Step 2:

[0069] The device uses its built-in GPS function to obtain the user's current location in real time. This location data is transmitted from the device to the server. The server receives this location data to determine the user's current location. As part of the data processing, the location data is formatted and coordinates are normalized.

[0070] Step 3:

[0071] The server accesses external sources to obtain the latest disaster information. This includes obtaining disaster data and converting its format via APIs. The server uses the obtained disaster information to analyze all the data, combining it with the user's current location and attribute information. It then uses a generative AI model to derive the optimal evacuation route. This process includes weighting the route, taking into account the user's mobility.

[0072] Step 4:

[0073] The server sends the evacuation route, generated through analysis and calculation, to the terminal. The terminal receives this evacuation route information and displays it visually to the user. Using a map application or a dedicated UI, the route is visualized and voice guidance is turned on. Specifically, the terminal outputs instructions to the user via voice, such as "Turn left 50 meters ahead."

[0074] Step 5:

[0075] Users initiate safe evacuation actions by following visual and audio instructions provided by their device. This allows users to avoid confusion and reach their intended shelter quickly and accurately. Users act based on the presented route information and evaluate the actual evacuation route.

[0076] (Application Example 1)

[0077] 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."

[0078] In urban areas, when a disaster strikes, it is difficult to provide safe and rapid evacuation services tailored to the diverse characteristics of individual users. Furthermore, updating evacuation routes in real time requires considering the physical characteristics of users and the overall urban situation, but current systems do not adequately address these requirements. Therefore, there is a need for an advanced evacuation support system that is compatible with modern smart device environments and features an intuitively understandable interface.

[0079] 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.

[0080] This invention includes a server that includes a device for inputting and storing the user's personal information, a device for periodically acquiring and transmitting the user's current location information, a device for acquiring the latest disaster-related information from external sources, a technology for analyzing the acquired personal information, current location information, and disaster-related information to generate an optimal evacuation route, and a technology for providing the generated evacuation route to the user through visual display and audio output. This makes it possible to provide evacuation routes in real time that take into account the user's physical characteristics and are adjusted to support evacuation throughout the city.

[0081] "User personal information" refers to individual data such as age, gender, and physical information collected to provide the optimal evacuation route.

[0082] "Current location information" refers to geographical data indicating the physical location of a user at a specific point in time.

[0083] "Disaster-related information" refers to the latest data on natural disasters such as earthquakes and floods, obtained from external sources.

[0084] "Analysis technology" refers to data processing and analysis methods used to generate safe and rapid evacuation routes based on acquired data.

[0085] "Visual display and audio output" refers to the means of screen display and audio guidance used to allow users to intuitively understand the generated evacuation routes.

[0086] "City-wide evacuation support" refers to comprehensive evacuation support provided to diverse users in a specific area, taking their individual characteristics into consideration.

[0087] An embodiment of this invention is an advanced evacuation route guidance system designed to assist users in their safe evacuation. This system mainly consists of a server, terminals, and associated software.

[0088] The server has the functionality to securely store personal information entered by users through their devices. This information includes unique user data such as age, gender, and physical characteristics. Additionally, devices equipped with GPS functionality periodically acquire the user's current location information and transmit it to the server. This allows the server to determine the user's precise location.

[0089] Furthermore, the server acquires the latest disaster-related information from external sources in real time. To this end, it uses a disaster information API to collect information according to the type and scale of the natural disaster. Based on this information, the server uses a generative AI model to analyze the acquired personal information, current location information, and disaster-related information to generate safe and rapid evacuation routes.

[0090] The terminal supports intuitive operation by visually displaying the generated evacuation route to the user and providing voice guidance. This visual and voice guidance helps users avoid confusion and enables rapid evacuation.

[0091] The specific hardware used includes smartphones and smart glasses with GPS capabilities (e.g., typical mobile devices). The software incorporates programs for real-time information processing and route generation using AI models (e.g., custom algorithms using TENSORFLOW®).

[0092] As a concrete example, if an earthquake occurs in the city center, the server will immediately update disaster information and suggest evacuation routes suitable for specific users. For instance, for elderly people, routes with fewer steps will be prioritized. An example of the prompt statements used in this process is shown below.

[0093] Example of a prompt:

[0094] Disaster: Earthquake

[0095] User information: 60 years old, male, has a knee problem.

[0096] Current location: Shinjuku Ward, Tokyo

[0097] Route conditions: Route with minimal elevation changes, shortest route to evacuation shelter.

[0098] This system allows users to quickly find the optimal evacuation procedure tailored to their physical characteristics and circumstances, enabling them to evacuate safely.

[0099] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0100] Step 1:

[0101] The terminal receives personal information from the user. This information includes age, gender, and physical characteristics. This information is stored in a database and prepared for analysis.

[0102] Step 2:

[0103] The device acquires the user's current location information and sends it to the server at regular intervals. The input is geographic coordinate data obtained using GPS functionality, and the server records the user's current location as output. This data forms the basis for generating evacuation routes in real time.

[0104] Step 3:

[0105] The server retrieves the latest disaster-related information from external sources. Input is data obtained from a disaster information API, and output is aggregated information such as the type, scale, and scope of the disaster. This enables faster and more appropriate route generation.

[0106] Step 4:

[0107] The server uses a generated AI model to analyze personal information, current location information, and disaster-related information. It generates prompt messages, and based on these, the AI ​​model generates the optimal evacuation route for the user. Through this process, the input data is integrated and a route is output that provides the user with a safe and rapid means of transportation.

[0108] Step 5:

[0109] The server generates an evacuation route and sends it to the terminal. The terminal receives this and begins guiding the user visually and audibly. The input is the generated evacuation route information, and the output is a signal that the user receives, allowing them to adjust their actions accordingly.

[0110] Step 6:

[0111] The user follows instructions from the device and takes the designated route. This enables safe and efficient movement to shelters or safe locations. The user's actual actions are the system's final output.

[0112] 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.

[0113] This invention is a system that recognizes the user's emotional state and optimizes evacuation route guidance during disasters. First, the user inputs personal information using a terminal, which is then transmitted to a server. Based on this personal information, the terminal prepares to provide evacuation route guidance tailored to the user.

[0114] This system incorporates an emotion engine that infers emotions through the user's camera and microphone. Specifically, it has a function that determines stress levels and emotional distress from the user's facial expressions and tone of voice. This emotional information is sent to a server and integrated with other data to become part of the analysis.

[0115] When a disaster occurs, the device acquires the user's current location information in real time, and this data is sent to the server. The server retrieves the latest information from an external disaster information database and combines the user's personal information, emotional state, and current location to generate a highly customized evacuation route. If the emotional engine determines that the user is under high stress, it adjusts the content and tone of the guidance to provide anxiety-relieving voice guidance.

[0116] The generated evacuation route is sent to the terminal, which visually displays the route and guides the user safely through voice guidance. For example, if a user is feeling anxious during a disaster, the emotion engine detects that emotion and provides a reassuring message such as, "Please stay calm. We will guide you to a safe route." In this way, using the emotion engine enables flexible responses tailored to the user's psychological state, supporting safer and more effective evacuations.

[0117] The algorithm of this system allows for flexible responses tailored to individual situations, enabling personalized responses based on the type of disaster occurring, regional characteristics, and the user's emotional state.

[0118] The following describes the processing flow.

[0119] Step 1:

[0120] The user enters personal information on the device. This personal information includes age, gender, and physical characteristics. The device encrypts this information and sends it to the server. The server stores the information in a database and notifies the device when it is ready.

[0121] Step 2:

[0122] The device obtains the user's current location information. This operation is performed using GPS, and the location information is periodically sent to the server. The server records the received location information and updates the user's status.

[0123] Step 3:

[0124] The emotion engine uses the device's built-in camera and microphone to analyze the user's emotions. This includes steps to detect changes in facial expressions and tone of voice, and to determine the stress level. The emotional information is then sent to a server.

[0125] Step 4:

[0126] The server retrieves the latest disaster information from an external disaster information database. The data includes the progress of earthquakes, typhoons, and fires, and the server uses this information to assess the level of risk.

[0127] Step 5:

[0128] The server generates evacuation routes using an AI algorithm based on the user's personal information, current location, emotional state, and the latest disaster information. In particular, if a high-stress state is detected, it selects a safe route and approach that takes psychological burden into consideration.

[0129] Step 6:

[0130] The terminal receives an evacuation route generated from the server. The route is displayed on the screen, and voice guidance begins. Messages to reassure the user may also be included. The user can follow the guidance and evacuate safely along the designated route.

[0131] (Example 2)

[0132] 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".

[0133] Providing safe and rapid evacuation guidance while reducing the psychological stress of evacuees during natural disasters is a challenging task. Conventional evacuation route guidance systems provide information without considering the user's emotional state, which can actually increase evacuees' anxiety. There is a need for a system that can solve this problem.

[0134] 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.

[0135] In this invention, the server includes means for capturing and analyzing the user's emotional state, means for analyzing the acquired personal information, current location information, emotional state, and disaster information to generate an optimal evacuation route, and means for adjusting voice guidance according to the user's emotional state using a generated AI model. This makes it possible to provide an optimal evacuation route tailored to the individual emotional state of each evacuee.

[0136] "Personal information" refers to identifiable information such as a user's name and address, and is data used to identify users and provide appropriate services.

[0137] "Emotional state" refers to information that indicates the user's psychological and emotional condition, including stress levels and emotional distress.

[0138] "Current location information" refers to data that indicates the user's actual geographical location, and is usually obtained using GPS.

[0139] A "disaster information database" is an external information source that stores the latest data on disaster situations, warnings, and other information.

[0140] "Evacuation routes" refer to route information designed to enable users to evacuate safely and quickly.

[0141] A "generative AI model" refers to an artificial intelligence algorithm that generates appropriate output based on user input, and is particularly used to adjust voice guidance according to the user's emotional state.

[0142] "Voice guidance" refers to a system or message that provides information to the user through audio in addition to visual information.

[0143] As a form for implementing the invention, this system has the function of supporting evacuation during disasters. The system mainly consists of a terminal owned by the user and a server that processes data.

[0144] Users enter personal information using devices such as smartphones and tablets. These devices have the capability to encrypt this information and securely transmit it to the server. Furthermore, the devices are equipped with cameras and microphones, which are used to capture the user's facial expressions and voice. This data is analyzed by an emotion engine to infer the user's emotional state.

[0145] The server generates the optimal evacuation route using received personal information, emotional state, and real-time current location information transmitted from the terminal. During this process, it references an external disaster information database and incorporates the latest disaster information to construct real-time evacuation route information. Using a generation AI model, it also adjusts voice guidance according to the user's emotional state. For example, if high stress is detected, it generates a message encouraging calmness.

[0146] The generated evacuation route information is delivered to the terminal. The terminal visually displays the route and guides the user through voice guidance. For example, if the user feels stressed during an earthquake, it can provide a message such as, "Please stay calm. We will guide you to a safe route." In this way, it is possible to support safe and rapid evacuation while taking the user's emotional state into consideration.

[0147] An example of a prompt for the generating AI model would be: "Generate an appropriate voice guidance message for when a user experiences stress during an earthquake."

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

[0149] Step 1:

[0150] The user enters personal information via the device. After receiving this information, the device sends it to the server using an encryption protocol. The entered data includes name and address, and the output is encrypted.

[0151] Step 2:

[0152] The device activates its built-in camera and microphone to capture the user's facial expressions and voice. This data is sent as input to the emotion engine, where it is analyzed using a neural network. The emotion engine evaluates the user's stress level and emotional state and outputs it as emotional state information.

[0153] Step 3:

[0154] The device uses GPS functionality to obtain the user's current location. The acquired geographical information is sent to the server as input, and the output is the user's real-time location information.

[0155] Step 4:

[0156] The server combines emotional state, personal information, and current location information with an external disaster information database. The server applies an optimization algorithm to analyze this input data and generate the optimal evacuation route. The output is customized evacuation route information.

[0157] Step 5:

[0158] The server uses a generative AI model to create voice guidance tailored to the user's emotional state. If a high-stress state is detected, the generative AI generates a message to encourage calmness based on the prompt text. The input is emotional state information, and the output is a tailored voice guidance message.

[0159] Step 6:

[0160] The generated evacuation route and voice guidance data are transmitted from the server to the terminal. The terminal receives this information, visually displays the route on a map through the user interface, and activates the voice guidance system. The output consists of the visually displayed route and voice guidance.

[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] During disasters, it has been difficult to provide flexible evacuation guidance that takes into account the emotional state of users. Therefore, there is a need for a system that provides personalized evacuation guidance according to the user's psychological state, supporting safe evacuation while reducing anxiety.

[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 inputting and storing the user's personal information, means for periodically acquiring and transmitting the user's current location information and emotional state, means for acquiring the latest disaster information from an external database, means for analyzing the acquired personal information, current location information, emotional state, and disaster information to generate an optimal evacuation route, and means for providing the generated evacuation route to the user visually and audibly. This enables appropriate and reassuring evacuation guidance tailored to the user's psychological state.

[0166] "User personal information" refers to data that includes identifiable information related to the user and is used to customize evacuation instructions.

[0167] "Current location information" is data that indicates the user's geographical location, is acquired in real time, and is used to generate evacuation routes.

[0168] "Emotional state" refers to the user's psychological and emotional state, and is information inferred from facial expressions, tone of voice, and other factors.

[0169] "Disaster information" refers to the latest information regarding the occurrence of natural disasters, etc., obtained from external databases.

[0170] "Analysis" refers to the process of calculation and decision-making performed to derive the optimal evacuation route based on various acquired data.

[0171] An "evacuation route" refers to the optimal route that a user should take to evacuate safely, and it is generated through analysis.

[0172] "Providing information visually and aurally" refers to conveying information to the user through screen displays and audio guidance.

[0173] This invention describes a disaster-response evacuation route guidance system using a server and a user's terminal. The server comprehensively analyzes the user's personal information, current location information, emotional state, and disaster information obtained from an external database.

[0174] The user's device is a smartphone or similar mobile device, and its camera and microphone are used to capture the user's facial expressions and voice in real time. The data obtained is used to estimate the user's emotional state using sentiment analysis software such as Google® Cloud Vision API or IBM Watson® Tone Analyzer. This sentiment information is sent to a server and analyzed along with other information.

[0175] The server uses the Google Maps API to obtain the user's current location in real time. It also uses national and regional public disaster information APIs to obtain the latest disaster information. Based on this information, it generates an evacuation route suitable for each individual user. The generated route is displayed visually on the device screen and also output as voice guidance. The voice guidance is adjusted to take into account the user's emotional state and includes messages that provide reassurance.

[0176] For example, if a user is caught in an earthquake and feeling anxious, this system will assist them with voice guidance such as, "Please stay calm. We will guide you to a safe route."

[0177] An example of a prompt for a generative AI model would be: "When a user is instructed to evacuate due to an earthquake, please design an algorithm that analyzes the user's emotions in real time and proposes the optimal evacuation route and mental support messages."

[0178] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0179] Step 1:

[0180] The device captures the user's facial expressions with its camera and acquires their voice with its microphone. This input data is sent to emotion analysis software. The software analyzes the facial recognition information obtained through the camera and the features of the voice to infer the user's emotional state.

[0181] Step 2:

[0182] The terminal sends the analyzed emotional state to the server. The input data is the result of the emotion analysis, which the server receives and prepares to integrate with other data necessary for generating evacuation routes.

[0183] Step 3:

[0184] The device obtains its current location information via GPS and sends it to the server. The location information is obtained in real time using the Google Maps API and is input to the server as location data for generating evacuation routes.

[0185] Step 4:

[0186] The server retrieves the latest disaster information using an external database. Using data from the disaster information API as input, the server analyzes the type, intensity, and extent of the disaster, and aggregates the information necessary for evacuation planning.

[0187] Step 5:

[0188] The server integrates personal information, current location information, emotional state, and disaster information, and uses a generative AI model to generate the optimal evacuation route. It analyzes each piece of information as input and outputs an efficient and safe evacuation route.

[0189] Step 6:

[0190] The server generates an evacuation route and sends it to the terminal. The output provided to the user is a visual map display and audio guidance.

[0191] Step 7:

[0192] The device visually displays evacuation routes on its screen and plays voice guidance according to the user's emotional state. Specifically, it provides voice guidance that includes mental support messages to promote a sense of security and guide the user.

[0193] 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.

[0194] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. 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 indicated 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.

[0195] 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.

[0196] [Second Embodiment]

[0197] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0198] 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.

[0199] 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).

[0200] 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.

[0201] 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.

[0202] 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).

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] 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".

[0209] This invention is a system that provides the optimal evacuation route in real time according to the individual needs of the user, and is configured as follows: In the initial stage, the user inputs personal information (age, gender, physical information, etc.) through an interface on the terminal. The server then stores the base information of each user and forms the foundation for individualized responses.

[0210] In the event of a disaster, the device acquires the user's current location information in real time and sends it to the server. The server retrieves the latest disaster information from an external disaster information database and analyzes it in combination with the user's current location and personal information. This analysis utilizes a generative AI algorithm to generate safe and rapid evacuation routes. For example, in the case of elderly people, whose movement speed is expected to be relatively slow, routes with fewer slopes and stairs are prioritized.

[0211] The generated evacuation route is transmitted to the terminal and displayed visually to the user, as well as outputted as voice guidance. This allows the user to intuitively understand safe evacuation procedures and begin taking action quickly. For example, if a user is in the city center during an earthquake, the safest walking route is guided, taking into account the surrounding road conditions and the location of evacuation shelters. As a result, the user can evacuate without confusion and quickly secure their safety.

[0212] This system can flexibly respond to different types of disasters and regional characteristics, providing evacuation support with the user's safety as its top priority.

[0213] The following describes the processing flow.

[0214] Step 1:

[0215] The user enters personal information on the device, including age, gender, and physical information. The device prepares to send this information to the server and encrypts the data. The server stores the received data in a database and notifies the device of success.

[0216] Step 2:

[0217] The device uses a GPS sensor to obtain the user's current location. The obtained location information is sent to the server at a specified frequency (e.g., every 5 minutes). The server receives this data and updates the user's profile by linking it to the user's location.

[0218] Step 3:

[0219] The server collects the latest disaster information from external disaster information databases. This includes information on earthquakes, typhoons, and fires. The server analyzes this information to determine the level of risk and the scope of impact.

[0220] Step 4:

[0221] The server combines the user's personal information, current location, and disaster information, and generates evacuation routes using a generation AI algorithm. This algorithm is designed to minimize the risks and travel time of the route according to individual circumstances.

[0222] Step 5:

[0223] The server sends the generated evacuation route to the user's terminal. The terminal displays the received route and starts voice guidance. The user can follow the on-screen instructions to evacuate safely.

[0224] (Example 1)

[0225] 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".

[0226] To quickly provide appropriate evacuation routes and maximize user safety during disasters, dynamic route setting that takes individual attribute information into account is necessary. However, existing systems have difficulty simultaneously achieving real-time data analysis and adjustments based on individual characteristics. Furthermore, if evacuation routes are not presented both visually and aurally, it may hinder users from taking quick and accurate action.

[0227] 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.

[0228] In this invention, the server includes means for acquiring and storing user attribute information, means for periodically acquiring and transmitting user location data, and means for acquiring the latest disaster-related data from external sources. This enables the generation of optimal evacuation routes tailored to the individual characteristics of the user and effective guidance through visual and auditory means.

[0229] A "user" is an individual who inputs information and receives suggestions for evacuation routes.

[0230] "Attribute information" refers to data that indicates individual user characteristics such as age, gender, and physical abilities.

[0231] "Location data" refers to geographical information that indicates the user's current location.

[0232] "Disaster-related data" refers to the latest information, including the type of disaster, location, and scale.

[0233] "Analysis means" refers to the process or algorithm used to calculate the optimal evacuation route based on the acquired information.

[0234] An "evacuation route" is a path established to reach a destination safely and quickly.

[0235] "Visual and auditory instructions" refers to methods of showing users routes using maps or audio guidance.

[0236] This invention relates to a system that provides users with the optimal route for safe evacuation during a disaster. The main components of this system are a server, a terminal, and a user.

[0237] The device has an interface for inputting user attribute information, where the user enters their age, gender, physical abilities, etc. The device uses its built-in GPS function to acquire location data in real time and transmit it to the server.

[0238] The server passively receives user attribute information and location data, and obtains the latest disaster-related data from external sources. The server then uses a generative AI model to calculate the safest and fastest evacuation route based on all the acquired data. This process involves personalized analysis that takes into account individual characteristics such as mobility.

[0239] The generated evacuation route is provided to the user via a terminal. The terminal conveys information to the user intuitively and clearly by combining visual displays and voice guidance. For example, if a user experiences an earthquake in the city center, the terminal can guide them to the optimal walking route, taking into account surrounding traffic conditions and information about evacuation shelters. An example of a prompt used in this case would be: "The user's current location is around Tokyo Station, age 75. The disaster is an earthquake. Please generate the optimal evacuation route, taking into account the condition of surrounding roads and the nearest evacuation shelter."

[0240] This system is designed to support swift and safe evacuation and can flexibly respond to a variety of disaster situations.

[0241] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0242] Step 1:

[0243] The user inputs attribute information (age, gender, physical ability, etc.) using the terminal's interface. This input information is sent from the terminal to the server. The server receives this input information and stores it as the user's individual profile. The data processing performed here involves verifying the user information and registering it in the database.

[0244] Step 2:

[0245] The device uses its built-in GPS function to obtain the user's current location in real time. This location data is transmitted from the device to the server. The server receives this location data to determine the user's current location. As part of the data processing, the location data is formatted and coordinates are normalized.

[0246] Step 3:

[0247] The server accesses external sources to obtain the latest disaster information. This includes obtaining disaster data and converting its format via APIs. The server uses the obtained disaster information to analyze all the data, combining it with the user's current location and attribute information. It then uses a generative AI model to derive the optimal evacuation route. This process includes weighting the route, taking into account the user's mobility.

[0248] Step 4:

[0249] The server sends the evacuation route, generated through analysis and calculation, to the terminal. The terminal receives this evacuation route information and displays it visually to the user. Using a map application or a dedicated UI, the route is visualized and voice guidance is turned on. Specifically, the terminal outputs instructions to the user via voice, such as "Turn left 50 meters ahead."

[0250] Step 5:

[0251] Users initiate safe evacuation actions by following visual and audio instructions provided by their device. This allows users to avoid confusion and reach their intended shelter quickly and accurately. Users act based on the presented route information and evaluate the actual evacuation route.

[0252] (Application Example 1)

[0253] 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."

[0254] In urban areas, when a disaster strikes, it is difficult to provide safe and rapid evacuation services tailored to the diverse characteristics of individual users. Furthermore, updating evacuation routes in real time requires considering the physical characteristics of users and the overall urban situation, but current systems do not adequately address these requirements. Therefore, there is a need for an advanced evacuation support system that is compatible with modern smart device environments and features an intuitively understandable interface.

[0255] 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.

[0256] This invention includes a server that includes a device for inputting and storing the user's personal information, a device for periodically acquiring and transmitting the user's current location information, a device for acquiring the latest disaster-related information from external sources, a technology for analyzing the acquired personal information, current location information, and disaster-related information to generate an optimal evacuation route, and a technology for providing the generated evacuation route to the user through visual display and audio output. This makes it possible to provide evacuation routes in real time that take into account the user's physical characteristics and are adjusted to support evacuation throughout the city.

[0257] "User personal information" refers to individual data such as age, gender, and physical information collected to provide the optimal evacuation route.

[0258] "Current location information" refers to geographical data indicating the physical location of a user at a specific point in time.

[0259] "Disaster-related information" refers to the latest data on natural disasters such as earthquakes and floods, obtained from external sources.

[0260] "Analysis technology" refers to data processing and analysis methods used to generate safe and rapid evacuation routes based on acquired data.

[0261] "Visual display and audio output" refers to the means of screen display and audio guidance used to allow users to intuitively understand the generated evacuation routes.

[0262] "City-wide evacuation support" refers to comprehensive evacuation support provided to diverse users in a specific area, taking their individual characteristics into consideration.

[0263] An embodiment of this invention is an advanced evacuation route guidance system designed to assist users in their safe evacuation. This system mainly consists of a server, terminals, and associated software.

[0264] The server has the functionality to securely store personal information entered by users through their devices. This information includes unique user data such as age, gender, and physical characteristics. Additionally, devices equipped with GPS functionality periodically acquire the user's current location information and transmit it to the server. This allows the server to determine the user's precise location.

[0265] Furthermore, the server acquires the latest disaster-related information from external sources in real time. To this end, it uses a disaster information API to collect information according to the type and scale of the natural disaster. Based on this information, the server uses a generative AI model to analyze the acquired personal information, current location information, and disaster-related information to generate safe and rapid evacuation routes.

[0266] The terminal supports intuitive operation by visually displaying the generated evacuation route to the user and providing voice guidance. This visual and voice guidance helps users avoid confusion and enables rapid evacuation.

[0267] The specific hardware used includes smartphones and smart glasses with GPS capabilities (e.g., typical mobile devices). The software incorporates programs for real-time information processing and route generation using AI models (e.g., custom algorithms using TensorFlow).

[0268] As a concrete example, if an earthquake occurs in the city center, the server will immediately update disaster information and suggest evacuation routes suitable for specific users. For instance, for elderly people, routes with fewer steps will be prioritized. An example of the prompt statements used in this process is shown below.

[0269] Example of a prompt:

[0270] Disaster: Earthquake

[0271] User information: 60 years old, male, has a knee problem.

[0272] Current location: Shinjuku Ward, Tokyo

[0273] Route conditions: Route with minimal elevation changes, shortest route to evacuation shelter.

[0274] This system allows users to quickly find the optimal evacuation procedure tailored to their physical characteristics and circumstances, enabling them to evacuate safely.

[0275] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0276] Step 1:

[0277] The terminal receives personal information from the user. This information includes age, gender, and physical characteristics. This information is stored in a database and prepared for analysis.

[0278] Step 2:

[0279] The terminal acquires the user's current location information and transmits it to the server at regular intervals. The input is geographical coordinate data obtained by the GPS function, and as output, the server records the user's current location. This data serves as the basis for real-time evacuation route generation.

[0280] Step 3:

[0281] The server acquires the latest disaster-related information from an external information source. The input is data obtained from the disaster information API, and as output, the server aggregates information such as the type, scale, and affected area of the disaster. This enables more rapid and appropriate route generation.

[0282] Step 4:

[0283] The server analyzes personal information, current location information, and disaster-related information using a generative AI model. A prompt sentence is generated, and based on it, the AI model generates the optimal evacuation route for the user. This process integrates the input data and outputs a route for providing the user with a safe and rapid means of movement.

[0284] Step 5:

[0285] The server transmits the generated evacuation route to the terminal. The terminal receives this and starts guiding the user visually and audibly. The input is the generated evacuation route information, and as output, the user can receive a signal and adjust their actions.

[0286] Step 6:

[0287] The user follows the guidance from the terminal and follows the specified route. This enables safe and efficient movement to a shelter or a safe place. The user's actual actions are the final output of the system.

[0288] 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.

[0289] This invention is a system that recognizes the user's emotional state and optimizes evacuation route guidance during disasters. First, the user inputs personal information using a terminal, which is then transmitted to a server. Based on this personal information, the terminal prepares to provide evacuation route guidance tailored to the user.

[0290] This system incorporates an emotion engine that infers emotions through the user's camera and microphone. Specifically, it has a function that determines stress levels and emotional distress from the user's facial expressions and tone of voice. This emotional information is sent to a server and integrated with other data to become part of the analysis.

[0291] When a disaster occurs, the device acquires the user's current location information in real time, and this data is sent to the server. The server retrieves the latest information from an external disaster information database and combines the user's personal information, emotional state, and current location to generate a highly customized evacuation route. If the emotional engine determines that the user is under high stress, it adjusts the content and tone of the guidance to provide anxiety-relieving voice guidance.

[0292] The generated evacuation route is sent to the terminal, which visually displays the route and guides the user safely through voice guidance. For example, if a user is feeling anxious during a disaster, the emotion engine detects that emotion and provides a reassuring message such as, "Please stay calm. We will guide you to a safe route." In this way, using the emotion engine enables flexible responses tailored to the user's psychological state, supporting safer and more effective evacuations.

[0293] The algorithm of this system allows for flexible responses tailored to individual situations, enabling personalized responses based on the type of disaster occurring, regional characteristics, and the user's emotional state.

[0294] The following describes the processing flow.

[0295] Step 1:

[0296] The user enters personal information on the device. This personal information includes age, gender, and physical characteristics. The device encrypts this information and sends it to the server. The server stores the information in a database and notifies the device when it is ready.

[0297] Step 2:

[0298] The device obtains the user's current location information. This operation is performed using GPS, and the location information is periodically sent to the server. The server records the received location information and updates the user's status.

[0299] Step 3:

[0300] The emotion engine uses the device's built-in camera and microphone to analyze the user's emotions. This includes steps to detect changes in facial expressions and tone of voice, and to determine the stress level. The emotional information is then sent to a server.

[0301] Step 4:

[0302] The server retrieves the latest disaster information from an external disaster information database. The data includes the progress of earthquakes, typhoons, and fires, and the server uses this information to assess the level of risk.

[0303] Step 5:

[0304] Based on the user's personal information, current location, emotional state, and the latest disaster information, the server generates an evacuation route using a generative AI algorithm. When a high-stress state is particularly recognized, a safe route and approach considering the psychological burden are selected.

[0305] Step 6:

[0306] The terminal receives the evacuation route generated by the server. The route is displayed on the screen and voice guidance is started. There may also be a message included to give the user a sense of security. The user can follow the guidance and safely evacuate along the designated route.

[0307] (Example 2)

[0308] 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".

[0309] When a natural disaster occurs, it is a difficult task to provide route guidance that enables safe and rapid evacuation while reducing the mental stress of evacuees. Conventional evacuation route guidance systems provide information without considering the user's emotional state, which may instead increase the anxiety of evacuees. There is a need for a system to solve this problem.

[0310] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0311] In this invention, the server includes means for capturing and analyzing the user's emotional state, means for analyzing the acquired personal information, current location information, emotional state, and disaster information to generate an optimal evacuation route, and means for adjusting voice guidance according to the user's emotional state using a generative AI model. This enables the provision of an optimal evacuation route according to the individual emotional state of the evacuee.

[0312] "Personal information" refers to identifiable information such as a user's name and address, and is data used to identify users and provide appropriate services.

[0313] "Emotional state" refers to information that indicates the user's psychological and emotional condition, including stress levels and emotional distress.

[0314] "Current location information" refers to data that indicates the user's actual geographical location, and is usually obtained using GPS.

[0315] A "disaster information database" is an external information source that stores the latest data on disaster situations, warnings, and other information.

[0316] "Evacuation routes" refer to route information designed to enable users to evacuate safely and quickly.

[0317] A "generative AI model" refers to an artificial intelligence algorithm that generates appropriate output based on user input, and is particularly used to adjust voice guidance according to the user's emotional state.

[0318] "Voice guidance" refers to a system or message that provides information to the user through audio in addition to visual information.

[0319] As a form for implementing the invention, this system has the function of supporting evacuation during disasters. The system mainly consists of a terminal owned by the user and a server that processes data.

[0320] Users enter personal information using devices such as smartphones and tablets. These devices have the capability to encrypt this information and securely transmit it to the server. Furthermore, the devices are equipped with cameras and microphones, which are used to capture the user's facial expressions and voice. This data is analyzed by an emotion engine to infer the user's emotional state.

[0321] The server generates the optimal evacuation route using received personal information, emotional state, and real-time current location information transmitted from the terminal. During this process, it references an external disaster information database and incorporates the latest disaster information to construct real-time evacuation route information. Using a generation AI model, it also adjusts voice guidance according to the user's emotional state. For example, if high stress is detected, it generates a message encouraging calmness.

[0322] The generated evacuation route information is delivered to the terminal. The terminal visually displays the route and guides the user through voice guidance. For example, if the user feels stressed during an earthquake, it can provide a message such as, "Please stay calm. We will guide you to a safe route." In this way, it is possible to support safe and rapid evacuation while taking the user's emotional state into consideration.

[0323] An example of a prompt for the generating AI model would be: "Generate an appropriate voice guidance message for when a user experiences stress during an earthquake."

[0324] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0325] Step 1:

[0326] The user enters personal information via the device. After receiving this information, the device sends it to the server using an encryption protocol. The entered data includes name and address, and the output is encrypted.

[0327] Step 2:

[0328] The device activates its built-in camera and microphone to capture the user's facial expressions and voice. This data is sent as input to the emotion engine, where it is analyzed using a neural network. The emotion engine evaluates the user's stress level and emotional state and outputs it as emotional state information.

[0329] Step 3:

[0330] The device uses GPS functionality to obtain the user's current location. The acquired geographical information is sent to the server as input, and the output is the user's real-time location information.

[0331] Step 4:

[0332] The server combines emotional state, personal information, and current location information with an external disaster information database. The server applies an optimization algorithm to analyze this input data and generate the optimal evacuation route. The output is customized evacuation route information.

[0333] Step 5:

[0334] The server uses a generative AI model to create voice guidance tailored to the user's emotional state. If a high-stress state is detected, the generative AI generates a message to encourage calmness based on the prompt text. The input is emotional state information, and the output is a tailored voice guidance message.

[0335] Step 6:

[0336] The generated evacuation route and voice guidance data are transmitted from the server to the terminal. The terminal receives this information, visually displays the route on a map through the user interface, and activates the voice guidance system. The output consists of the visually displayed route and voice guidance.

[0337] (Application Example 2)

[0338] 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 as the "terminal".

[0339] During disasters, it has been difficult to provide flexible evacuation guidance that takes into account the emotional state of users. Therefore, there is a need for a system that provides personalized evacuation guidance according to the user's psychological state, supporting safe evacuation while reducing anxiety.

[0340] 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.

[0341] In this invention, the server includes means for inputting and storing the user's personal information, means for periodically acquiring and transmitting the user's current location information and emotional state, means for acquiring the latest disaster information from an external database, means for analyzing the acquired personal information, current location information, emotional state, and disaster information to generate an optimal evacuation route, and means for providing the generated evacuation route to the user visually and audibly. This enables appropriate and reassuring evacuation guidance tailored to the user's psychological state.

[0342] "User personal information" refers to data that includes identifiable information related to the user and is used to customize evacuation instructions.

[0343] "Current location information" is data that indicates the user's geographical location, is acquired in real time, and is used to generate evacuation routes.

[0344] "Emotional state" refers to the user's psychological and emotional state, and is information inferred from facial expressions, tone of voice, and other factors.

[0345] "Disaster information" refers to the latest information regarding the occurrence of natural disasters, etc., obtained from external databases.

[0346] "Analysis" refers to the process of calculation and decision-making performed to derive the optimal evacuation route based on various acquired data.

[0347] An "evacuation route" refers to the optimal route that a user should take to evacuate safely, and it is generated through analysis.

[0348] "Providing information visually and aurally" refers to conveying information to the user through screen displays and audio guidance.

[0349] This invention describes a disaster-response evacuation route guidance system using a server and a user's terminal. The server comprehensively analyzes the user's personal information, current location information, emotional state, and disaster information obtained from an external database.

[0350] The user's device is a smartphone or similar mobile device, and its camera and microphone are used to capture the user's facial expressions and voice in real time. The data obtained is then used to estimate the user's emotional state using sentiment analysis software such as the Google Cloud Vision API or IBM Watson Tone Analyzer. This emotional information is sent to a server and analyzed along with other information.

[0351] The server uses the Google Maps API to obtain the user's current location in real time. It also uses national and regional public disaster information APIs to obtain the latest disaster information. Based on this information, it generates an evacuation route suitable for each individual user. The generated route is displayed visually on the device screen and also output as voice guidance. The voice guidance is adjusted to take into account the user's emotional state and includes messages that provide reassurance.

[0352] For example, if a user is caught in an earthquake and feeling anxious, this system will assist them with voice guidance such as, "Please stay calm. We will guide you to a safe route."

[0353] An example of a prompt for a generative AI model would be: "When a user is instructed to evacuate due to an earthquake, please design an algorithm that analyzes the user's emotions in real time and proposes the optimal evacuation route and mental support messages."

[0354] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0355] Step 1:

[0356] The device captures the user's facial expressions with its camera and acquires their voice with its microphone. This input data is sent to emotion analysis software. The software analyzes the facial recognition information obtained through the camera and the features of the voice to infer the user's emotional state.

[0357] Step 2:

[0358] The terminal sends the analyzed emotional state to the server. The input data is the result of the emotion analysis, which the server receives and prepares to integrate with other data necessary for generating evacuation routes.

[0359] Step 3:

[0360] The device obtains its current location information via GPS and sends it to the server. The location information is obtained in real time using the Google Maps API and is input to the server as location data for generating evacuation routes.

[0361] Step 4:

[0362] The server retrieves the latest disaster information using an external database. Using data from the disaster information API as input, the server analyzes the type, intensity, and extent of the disaster, and aggregates the information necessary for evacuation planning.

[0363] Step 5:

[0364] The server integrates personal information, current location information, emotional state, and disaster information, and uses a generative AI model to generate the optimal evacuation route. It analyzes each piece of information as input and outputs an efficient and safe evacuation route.

[0365] Step 6:

[0366] The server generates an evacuation route and sends it to the terminal. The output provided to the user is a visual map display and audio guidance.

[0367] Step 7:

[0368] The device visually displays evacuation routes on its screen and plays voice guidance according to the user's emotional state. Specifically, it provides voice guidance that includes mental support messages to promote a sense of security and guide the user.

[0369] 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.

[0370] 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 the following. 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 indicated 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.

[0371] 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.

[0372] [Third Embodiment]

[0373] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0374] 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.

[0375] 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).

[0376] 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.

[0377] 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.

[0378] 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).

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] 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.

[0384] 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".

[0385] This invention is a system that provides the optimal evacuation route in real time according to the individual needs of the user, and is configured as follows: In the initial stage, the user inputs personal information (age, gender, physical information, etc.) through an interface on the terminal. The server then stores the base information of each user and forms the foundation for individualized responses.

[0386] In the event of a disaster, the device acquires the user's current location information in real time and sends it to the server. The server retrieves the latest disaster information from an external disaster information database and analyzes it in combination with the user's current location and personal information. This analysis utilizes a generative AI algorithm to generate safe and rapid evacuation routes. For example, in the case of elderly people, whose movement speed is expected to be relatively slow, routes with fewer slopes and stairs are prioritized.

[0387] The generated evacuation route is transmitted to the terminal and displayed visually to the user, as well as outputted as voice guidance. This allows the user to intuitively understand safe evacuation procedures and begin taking action quickly. For example, if a user is in the city center during an earthquake, the safest walking route is guided, taking into account the surrounding road conditions and the location of evacuation shelters. As a result, the user can evacuate without confusion and quickly secure their safety.

[0388] This system can flexibly respond to different types of disasters and regional characteristics, providing evacuation support with the user's safety as its top priority.

[0389] The following describes the processing flow.

[0390] Step 1:

[0391] The user enters personal information on the device, including age, gender, and physical information. The device prepares to send this information to the server and encrypts the data. The server stores the received data in a database and notifies the device of success.

[0392] Step 2:

[0393] The device uses a GPS sensor to obtain the user's current location. The obtained location information is sent to the server at a specified frequency (e.g., every 5 minutes). The server receives this data and updates the user's profile by linking it to the user's location.

[0394] Step 3:

[0395] The server collects the latest disaster information from external disaster information databases. This includes information on earthquakes, typhoons, and fires. The server analyzes this information to determine the level of risk and the scope of impact.

[0396] Step 4:

[0397] The server combines the user's personal information, current location, and disaster information, and generates evacuation routes using a generation AI algorithm. This algorithm is designed to minimize the risks and travel time of the route according to individual circumstances.

[0398] Step 5:

[0399] The server sends the generated evacuation route to the user's terminal. The terminal displays the received route and starts voice guidance. The user can follow the on-screen instructions to evacuate safely.

[0400] (Example 1)

[0401] 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."

[0402] To quickly provide appropriate evacuation routes and maximize user safety during disasters, dynamic route setting that takes individual attribute information into account is necessary. However, existing systems have difficulty simultaneously achieving real-time data analysis and adjustments based on individual characteristics. Furthermore, if evacuation routes are not presented both visually and aurally, it may hinder users from taking quick and accurate action.

[0403] 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.

[0404] In this invention, the server includes means for acquiring and storing user attribute information, means for periodically acquiring and transmitting user location data, and means for acquiring the latest disaster-related data from external sources. This enables the generation of optimal evacuation routes tailored to the individual characteristics of the user and effective guidance through visual and auditory means.

[0405] A "user" is an individual who inputs information and receives suggestions for evacuation routes.

[0406] "Attribute information" refers to data that indicates individual user characteristics such as age, gender, and physical abilities.

[0407] "Location data" refers to geographical information that indicates the user's current location.

[0408] "Disaster-related data" refers to the latest information, including the type of disaster, location, and scale.

[0409] "Analysis means" refers to the process or algorithm used to calculate the optimal evacuation route based on the acquired information.

[0410] An "evacuation route" is a path established to reach a destination safely and quickly.

[0411] "Visual and auditory instructions" refers to methods of showing users routes using maps or audio guidance.

[0412] This invention relates to a system that provides users with the optimal route for safe evacuation during a disaster. The main components of this system are a server, a terminal, and a user.

[0413] The device has an interface for inputting user attribute information, where the user enters their age, gender, physical abilities, etc. The device uses its built-in GPS function to acquire location data in real time and transmit it to the server.

[0414] The server passively receives user attribute information and location data, and obtains the latest disaster-related data from external sources. The server then uses a generative AI model to calculate the safest and fastest evacuation route based on all the acquired data. This process involves personalized analysis that takes into account individual characteristics such as mobility.

[0415] The generated evacuation route is provided to the user via a terminal. The terminal conveys information to the user intuitively and clearly by combining visual displays and voice guidance. For example, if a user experiences an earthquake in the city center, the terminal can guide them to the optimal walking route, taking into account surrounding traffic conditions and information about evacuation shelters. An example of a prompt used in this case would be: "The user's current location is around Tokyo Station, age 75. The disaster is an earthquake. Please generate the optimal evacuation route, taking into account the condition of surrounding roads and the nearest evacuation shelter."

[0416] This system is designed to support swift and safe evacuation and can flexibly respond to a variety of disaster situations.

[0417] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0418] Step 1:

[0419] The user inputs attribute information (age, gender, physical ability, etc.) using the terminal's interface. This input information is sent from the terminal to the server. The server receives this input information and stores it as the user's individual profile. The data processing performed here involves verifying the user information and registering it in the database.

[0420] Step 2:

[0421] The device uses its built-in GPS function to obtain the user's current location in real time. This location data is transmitted from the device to the server. The server receives this location data to determine the user's current location. As part of the data processing, the location data is formatted and coordinates are normalized.

[0422] Step 3:

[0423] The server accesses external sources to obtain the latest disaster information. This includes obtaining disaster data and converting its format via APIs. The server uses the obtained disaster information to analyze all the data, combining it with the user's current location and attribute information. It then uses a generative AI model to derive the optimal evacuation route. This process includes weighting the route, taking into account the user's mobility.

[0424] Step 4:

[0425] The server sends the evacuation route, generated through analysis and calculation, to the terminal. The terminal receives this evacuation route information and displays it visually to the user. Using a map application or a dedicated UI, the route is visualized and voice guidance is turned on. Specifically, the terminal outputs instructions to the user via voice, such as "Turn left 50 meters ahead."

[0426] Step 5:

[0427] Users initiate safe evacuation actions by following visual and audio instructions provided by their device. This allows users to avoid confusion and reach their intended shelter quickly and accurately. Users act based on the presented route information and evaluate the actual evacuation route.

[0428] (Application Example 1)

[0429] 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."

[0430] In urban areas, when a disaster strikes, it is difficult to provide safe and rapid evacuation services tailored to the diverse characteristics of individual users. Furthermore, updating evacuation routes in real time requires considering the physical characteristics of users and the overall urban situation, but current systems do not adequately address these requirements. Therefore, there is a need for an advanced evacuation support system that is compatible with modern smart device environments and features an intuitively understandable interface.

[0431] 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.

[0432] This invention includes a server that includes a device for inputting and storing the user's personal information, a device for periodically acquiring and transmitting the user's current location information, a device for acquiring the latest disaster-related information from external sources, a technology for analyzing the acquired personal information, current location information, and disaster-related information to generate an optimal evacuation route, and a technology for providing the generated evacuation route to the user through visual display and audio output. This makes it possible to provide evacuation routes in real time that take into account the user's physical characteristics and are adjusted to support evacuation throughout the city.

[0433] "User personal information" refers to individual data such as age, gender, and physical information collected to provide the optimal evacuation route.

[0434] "Current location information" refers to geographical data indicating the physical location of a user at a specific point in time.

[0435] "Disaster-related information" refers to the latest data on natural disasters such as earthquakes and floods, obtained from external sources.

[0436] "Analysis technology" refers to data processing and analysis methods used to generate safe and rapid evacuation routes based on acquired data.

[0437] "Visual display and audio output" refers to the means of screen display and audio guidance used to allow users to intuitively understand the generated evacuation routes.

[0438] "City-wide evacuation support" refers to comprehensive evacuation support provided to diverse users in a specific area, taking their individual characteristics into consideration.

[0439] An embodiment of this invention is an advanced evacuation route guidance system designed to assist users in their safe evacuation. This system mainly consists of a server, terminals, and associated software.

[0440] The server has the functionality to securely store personal information entered by users through their devices. This information includes unique user data such as age, gender, and physical characteristics. Additionally, devices equipped with GPS functionality periodically acquire the user's current location information and transmit it to the server. This allows the server to determine the user's precise location.

[0441] Furthermore, the server acquires the latest disaster-related information from external sources in real time. To this end, it uses a disaster information API to collect information according to the type and scale of the natural disaster. Based on this information, the server uses a generative AI model to analyze the acquired personal information, current location information, and disaster-related information to generate safe and rapid evacuation routes.

[0442] The terminal supports intuitive operation by visually displaying the generated evacuation route to the user and providing voice guidance. This visual and voice guidance helps users avoid confusion and enables rapid evacuation.

[0443] The specific hardware used includes smartphones and smart glasses with GPS capabilities (e.g., typical mobile devices). The software incorporates programs for real-time information processing and route generation using AI models (e.g., custom algorithms using TensorFlow).

[0444] As a concrete example, if an earthquake occurs in the city center, the server will immediately update disaster information and suggest evacuation routes suitable for specific users. For instance, for elderly people, routes with fewer steps will be prioritized. An example of the prompt statements used in this process is shown below.

[0445] Example of a prompt:

[0446] Disaster: Earthquake

[0447] User information: 60 years old, male, has a knee problem.

[0448] Current location: Shinjuku Ward, Tokyo

[0449] Route conditions: Route with minimal elevation changes, shortest route to evacuation shelter.

[0450] This system allows users to quickly find the optimal evacuation procedure tailored to their physical characteristics and circumstances, enabling them to evacuate safely.

[0451] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0452] Step 1:

[0453] The terminal receives personal information from the user. This information includes age, gender, and physical characteristics. This information is stored in a database and prepared for analysis.

[0454] Step 2:

[0455] The device acquires the user's current location information and sends it to the server at regular intervals. The input is geographical coordinate data obtained using GPS functionality, and the server records the user's current location as output. This data forms the basis for generating evacuation routes in real time.

[0456] Step 3:

[0457] The server retrieves the latest disaster-related information from external sources. Input is data obtained from a disaster information API, and output is aggregated information such as the type, scale, and scope of the disaster. This enables faster and more appropriate route generation.

[0458] Step 4:

[0459] The server uses a generated AI model to analyze personal information, current location information, and disaster-related information. It generates prompt messages, and based on these, the AI ​​model generates the optimal evacuation route for the user. Through this process, the input data is integrated and a route is output that provides the user with a safe and rapid means of transportation.

[0460] Step 5:

[0461] The server generates an evacuation route and sends it to the terminal. The terminal receives this and begins guiding the user visually and audibly. The input is the generated evacuation route information, and the output is a signal that the user receives, allowing them to adjust their actions accordingly.

[0462] Step 6:

[0463] The user follows instructions from the device and takes the designated route. This enables safe and efficient movement to shelters or safe locations. The user's actual actions are the system's final output.

[0464] 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.

[0465] This invention is a system that recognizes the user's emotional state and optimizes evacuation route guidance during disasters. First, the user inputs personal information using a terminal, which is then transmitted to a server. Based on this personal information, the terminal prepares to provide evacuation route guidance tailored to the user.

[0466] This system incorporates an emotion engine that infers emotions through the user's camera and microphone. Specifically, it has a function that determines stress levels and emotional distress from the user's facial expressions and tone of voice. This emotional information is sent to a server and integrated with other data to become part of the analysis.

[0467] When a disaster occurs, the device acquires the user's current location information in real time, and this data is sent to the server. The server retrieves the latest information from an external disaster information database and combines the user's personal information, emotional state, and current location to generate a highly customized evacuation route. If the emotional engine determines that the user is under high stress, it adjusts the content and tone of the guidance to provide anxiety-relieving voice guidance.

[0468] The generated evacuation route is sent to the terminal, which visually displays the route and guides the user safely through voice guidance. For example, if a user is feeling anxious during a disaster, the emotion engine detects that emotion and provides a reassuring message such as, "Please stay calm. We will guide you to a safe route." In this way, using the emotion engine enables flexible responses tailored to the user's psychological state, supporting safer and more effective evacuations.

[0469] The algorithm of this system allows for flexible responses tailored to individual situations, enabling personalized responses based on the type of disaster occurring, regional characteristics, and the user's emotional state.

[0470] The following describes the processing flow.

[0471] Step 1:

[0472] The user enters personal information on the device. This personal information includes age, gender, and physical characteristics. The device encrypts this information and sends it to the server. The server stores the information in a database and notifies the device when it is ready.

[0473] Step 2:

[0474] The device obtains the user's current location information. This operation is performed using GPS, and the location information is periodically sent to the server. The server records the received location information and updates the user's status.

[0475] Step 3:

[0476] The emotion engine uses the device's built-in camera and microphone to analyze the user's emotions. This includes steps to detect changes in facial expressions and tone of voice, and to determine the stress level. The emotional information is then sent to a server.

[0477] Step 4:

[0478] The server retrieves the latest disaster information from an external disaster information database. The data includes the progress of earthquakes, typhoons, and fires, and the server uses this information to assess the level of risk.

[0479] Step 5:

[0480] The server generates evacuation routes using an AI algorithm based on the user's personal information, current location, emotional state, and the latest disaster information. In particular, if a high-stress state is detected, it selects a safe route and approach that takes psychological burden into consideration.

[0481] Step 6:

[0482] The terminal receives an evacuation route generated from the server. The route is displayed on the screen, and voice guidance begins. Messages to reassure the user may also be included. The user can follow the guidance and evacuate safely along the designated route.

[0483] (Example 2)

[0484] 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."

[0485] Providing safe and rapid evacuation guidance while reducing the psychological stress of evacuees during natural disasters is a challenging task. Conventional evacuation route guidance systems provide information without considering the user's emotional state, which can actually increase evacuees' anxiety. There is a need for a system that can solve this problem.

[0486] 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.

[0487] In this invention, the server includes means for capturing and analyzing the user's emotional state, means for analyzing the acquired personal information, current location information, emotional state, and disaster information to generate an optimal evacuation route, and means for adjusting voice guidance according to the user's emotional state using a generated AI model. This makes it possible to provide an optimal evacuation route tailored to the individual emotional state of each evacuee.

[0488] "Personal information" refers to identifiable information such as a user's name and address, and is data used to identify users and provide appropriate services.

[0489] "Emotional state" refers to information that indicates the user's psychological and emotional condition, including stress levels and emotional distress.

[0490] "Current location information" refers to data that indicates the user's actual geographical location, and is usually obtained using GPS.

[0491] A "disaster information database" is an external information source that stores the latest data on disaster situations, warnings, and other information.

[0492] "Evacuation routes" refer to route information designed to enable users to evacuate safely and quickly.

[0493] A "generative AI model" refers to an artificial intelligence algorithm that generates appropriate output based on user input, and is particularly used to adjust voice guidance according to the user's emotional state.

[0494] "Voice guidance" refers to a system or message that provides information to the user through audio in addition to visual information.

[0495] As a form for implementing the invention, this system has the function of supporting evacuation during disasters. The system mainly consists of a terminal owned by the user and a server that processes data.

[0496] Users enter personal information using devices such as smartphones and tablets. These devices have the capability to encrypt this information and securely transmit it to the server. Furthermore, the devices are equipped with cameras and microphones, which are used to capture the user's facial expressions and voice. This data is analyzed by an emotion engine to infer the user's emotional state.

[0497] The server generates the optimal evacuation route using received personal information, emotional state, and real-time current location information transmitted from the terminal. During this process, it references an external disaster information database and incorporates the latest disaster information to construct real-time evacuation route information. Using a generation AI model, it also adjusts voice guidance according to the user's emotional state. For example, if high stress is detected, it generates a message encouraging calmness.

[0498] The generated evacuation route information is delivered to the terminal. The terminal visually displays the route and guides the user through voice guidance. For example, if the user feels stressed during an earthquake, it can provide a message such as, "Please stay calm. We will guide you to a safe route." In this way, it is possible to support safe and rapid evacuation while taking the user's emotional state into consideration.

[0499] An example of a prompt for the generating AI model would be: "Generate an appropriate voice guidance message for when a user experiences stress during an earthquake."

[0500] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0501] Step 1:

[0502] The user enters personal information via the device. After receiving this information, the device sends it to the server using an encryption protocol. The entered data includes name and address, and the output is encrypted.

[0503] Step 2:

[0504] The device activates its built-in camera and microphone to capture the user's facial expressions and voice. This data is sent as input to the emotion engine, where it is analyzed using a neural network. The emotion engine evaluates the user's stress level and emotional state and outputs it as emotional state information.

[0505] Step 3:

[0506] The device uses GPS functionality to obtain the user's current location. The acquired geographical information is sent to the server as input, and the output is the user's real-time location information.

[0507] Step 4:

[0508] The server combines emotional state, personal information, and current location information with an external disaster information database. The server applies an optimization algorithm to analyze this input data and generate the optimal evacuation route. The output is customized evacuation route information.

[0509] Step 5:

[0510] The server uses a generative AI model to create voice guidance tailored to the user's emotional state. If a high-stress state is detected, the generative AI generates a message to encourage calmness based on the prompt text. The input is emotional state information, and the output is a tailored voice guidance message.

[0511] Step 6:

[0512] The generated evacuation route and voice guidance data are transmitted from the server to the terminal. The terminal receives this information, visually displays the route on a map through the user interface, and activates the voice guidance system. The output consists of the visually displayed route and voice guidance.

[0513] (Application Example 2)

[0514] 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."

[0515] During disasters, it has been difficult to provide flexible evacuation guidance that takes into account the emotional state of users. Therefore, there is a need for a system that provides personalized evacuation guidance according to the user's psychological state, supporting safe evacuation while reducing anxiety.

[0516] 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.

[0517] In this invention, the server includes means for inputting and storing the user's personal information, means for periodically acquiring and transmitting the user's current location information and emotional state, means for acquiring the latest disaster information from an external database, means for analyzing the acquired personal information, current location information, emotional state, and disaster information to generate an optimal evacuation route, and means for providing the generated evacuation route to the user visually and audibly. This enables appropriate and reassuring evacuation guidance tailored to the user's psychological state.

[0518] "User personal information" refers to data that includes identifiable information related to the user and is used to customize evacuation instructions.

[0519] "Current location information" is data that indicates the user's geographical location, is acquired in real time, and is used to generate evacuation routes.

[0520] "Emotional state" refers to the user's psychological and emotional state, and is information inferred from facial expressions, tone of voice, and other factors.

[0521] "Disaster information" refers to the latest information regarding the occurrence of natural disasters, etc., obtained from external databases.

[0522] "Analysis" refers to the process of calculation and decision-making performed to derive the optimal evacuation route based on various acquired data.

[0523] An "evacuation route" refers to the optimal route that a user should take to evacuate safely, and it is generated through analysis.

[0524] "Providing information visually and aurally" refers to conveying information to the user through screen displays and audio guidance.

[0525] This invention describes a disaster-response evacuation route guidance system using a server and a user's terminal. The server comprehensively analyzes the user's personal information, current location information, emotional state, and disaster information obtained from an external database.

[0526] The user's device is a smartphone or similar mobile device, and its camera and microphone are used to capture the user's facial expressions and voice in real time. The data obtained is then used to estimate the user's emotional state using sentiment analysis software such as the Google Cloud Vision API or IBM Watson Tone Analyzer. This emotional information is sent to a server and analyzed along with other information.

[0527] The server uses the Google Maps API to obtain the user's current location in real time. It also uses national and regional public disaster information APIs to obtain the latest disaster information. Based on this information, it generates an evacuation route suitable for each individual user. The generated route is displayed visually on the device screen and also output as voice guidance. The voice guidance is adjusted to take into account the user's emotional state and includes messages that provide reassurance.

[0528] For example, if a user is caught in an earthquake and feeling anxious, this system will assist them with voice guidance such as, "Please stay calm. We will guide you to a safe route."

[0529] An example of a prompt for a generative AI model would be: "When a user is instructed to evacuate due to an earthquake, please design an algorithm that analyzes the user's emotions in real time and proposes the optimal evacuation route and mental support messages."

[0530] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0531] Step 1:

[0532] The device captures the user's facial expressions with its camera and acquires their voice with its microphone. This input data is sent to emotion analysis software. The software analyzes the facial recognition information obtained through the camera and the features of the voice to infer the user's emotional state.

[0533] Step 2:

[0534] The terminal sends the analyzed emotional state to the server. The input data is the result of the emotion analysis, which the server receives and prepares to integrate with other data necessary for generating evacuation routes.

[0535] Step 3:

[0536] The device obtains its current location information via GPS and sends it to the server. The location information is obtained in real time using the Google Maps API and is input to the server as location data for generating evacuation routes.

[0537] Step 4:

[0538] The server retrieves the latest disaster information using an external database. Using data from the disaster information API as input, the server analyzes the type, intensity, and extent of the disaster, and aggregates the information necessary for evacuation planning.

[0539] Step 5:

[0540] The server integrates personal information, current location information, emotional state, and disaster information, and uses a generative AI model to generate the optimal evacuation route. It analyzes each piece of information as input and outputs an efficient and safe evacuation route.

[0541] Step 6:

[0542] The server generates an evacuation route and sends it to the terminal. The output provided to the user is a visual map display and audio guidance.

[0543] Step 7:

[0544] The device visually displays evacuation routes on its screen and plays voice guidance according to the user's emotional state. Specifically, it provides voice guidance that includes mental support messages to promote a sense of security and guide the user.

[0545] 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.

[0546] 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 the following. 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 indicated 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.

[0547] 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.

[0548] [Fourth Embodiment]

[0549] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0550] 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.

[0551] 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).

[0552] 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.

[0553] 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.

[0554] 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).

[0555] 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.

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] 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".

[0562] This invention is a system that provides the optimal evacuation route in real time according to the individual needs of the user, and is configured as follows: In the initial stage, the user inputs personal information (age, gender, physical information, etc.) through an interface on the terminal. The server then stores the base information of each user and forms the foundation for individualized responses.

[0563] In the event of a disaster, the device acquires the user's current location information in real time and sends it to the server. The server retrieves the latest disaster information from an external disaster information database and analyzes it in combination with the user's current location and personal information. This analysis utilizes a generative AI algorithm to generate safe and rapid evacuation routes. For example, in the case of elderly people, whose movement speed is expected to be relatively slow, routes with fewer slopes and stairs are prioritized.

[0564] The generated evacuation route is transmitted to the terminal and displayed visually to the user, as well as outputted as voice guidance. This allows the user to intuitively understand safe evacuation procedures and begin taking action quickly. For example, if a user is in the city center during an earthquake, the safest walking route is guided, taking into account the surrounding road conditions and the location of evacuation shelters. As a result, the user can evacuate without confusion and quickly secure their safety.

[0565] This system can flexibly respond to different types of disasters and regional characteristics, providing evacuation support with the user's safety as its top priority.

[0566] The following describes the processing flow.

[0567] Step 1:

[0568] The user enters personal information on the device, including age, gender, and physical information. The device prepares to send this information to the server and encrypts the data. The server stores the received data in a database and notifies the device of success.

[0569] Step 2:

[0570] The device uses a GPS sensor to obtain the user's current location. The obtained location information is sent to the server at a specified frequency (e.g., every 5 minutes). The server receives this data and updates the user's profile by linking it to the user's location.

[0571] Step 3:

[0572] The server collects the latest disaster information from external disaster information databases. This includes information on earthquakes, typhoons, and fires. The server analyzes this information to determine the level of risk and the scope of impact.

[0573] Step 4:

[0574] The server combines the user's personal information, current location, and disaster information, and generates evacuation routes using a generation AI algorithm. This algorithm is designed to minimize the risks and travel time of the route according to individual circumstances.

[0575] Step 5:

[0576] The server sends the generated evacuation route to the user's terminal. The terminal displays the received route and starts voice guidance. The user can follow the on-screen instructions to evacuate safely.

[0577] (Example 1)

[0578] 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".

[0579] To quickly provide appropriate evacuation routes and maximize user safety during disasters, dynamic route setting that takes individual attribute information into account is necessary. However, existing systems have difficulty simultaneously achieving real-time data analysis and adjustments based on individual characteristics. Furthermore, if evacuation routes are not presented both visually and aurally, it may hinder users from taking quick and accurate action.

[0580] 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.

[0581] In this invention, the server includes means for acquiring and storing user attribute information, means for periodically acquiring and transmitting user location data, and means for acquiring the latest disaster-related data from external sources. This enables the generation of optimal evacuation routes tailored to the individual characteristics of the user and effective guidance through visual and auditory means.

[0582] A "user" is an individual who inputs information and receives suggestions for evacuation routes.

[0583] "Attribute information" refers to data that indicates individual user characteristics such as age, gender, and physical abilities.

[0584] "Location data" refers to geographical information that indicates the user's current location.

[0585] "Disaster-related data" refers to the latest information, including the type of disaster, location, and scale.

[0586] "Analysis means" refers to the process or algorithm used to calculate the optimal evacuation route based on the acquired information.

[0587] An "evacuation route" is a path established to reach a destination safely and quickly.

[0588] "Visual and auditory instructions" refers to methods of showing users routes using maps or audio guidance.

[0589] This invention relates to a system that provides users with the optimal route for safe evacuation during a disaster. The main components of this system are a server, a terminal, and a user.

[0590] The device has an interface for inputting user attribute information, where the user enters their age, gender, physical abilities, etc. The device uses its built-in GPS function to acquire location data in real time and transmit it to the server.

[0591] The server passively receives user attribute information and location data, and obtains the latest disaster-related data from external sources. The server then uses a generative AI model to calculate the safest and fastest evacuation route based on all the acquired data. This process involves personalized analysis that takes into account individual characteristics such as mobility.

[0592] The generated evacuation route is provided to the user via a terminal. The terminal conveys information to the user intuitively and clearly by combining visual displays and voice guidance. For example, if a user experiences an earthquake in the city center, the terminal can guide them to the optimal walking route, taking into account surrounding traffic conditions and information about evacuation shelters. An example of a prompt used in this case would be: "The user's current location is around Tokyo Station, age 75. The disaster is an earthquake. Please generate the optimal evacuation route, taking into account the condition of surrounding roads and the nearest evacuation shelter."

[0593] This system is designed to support swift and safe evacuation and can flexibly respond to a variety of disaster situations.

[0594] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0595] Step 1:

[0596] The user inputs attribute information (age, gender, physical ability, etc.) using the terminal's interface. This input information is sent from the terminal to the server. The server receives this input information and stores it as the user's individual profile. The data processing performed here involves verifying the user information and registering it in the database.

[0597] Step 2:

[0598] The device uses its built-in GPS function to obtain the user's current location in real time. This location data is transmitted from the device to the server. The server receives this location data to determine the user's current location. As part of the data processing, the location data is formatted and coordinates are normalized.

[0599] Step 3:

[0600] The server accesses external sources to obtain the latest disaster information. This includes obtaining disaster data and converting its format via APIs. The server uses the obtained disaster information to analyze all the data, combining it with the user's current location and attribute information. It then uses a generative AI model to derive the optimal evacuation route. This process includes weighting the route, taking into account the user's mobility.

[0601] Step 4:

[0602] The server sends the evacuation route, generated through analysis and calculation, to the terminal. The terminal receives this evacuation route information and displays it visually to the user. Using a map application or a dedicated UI, the route is visualized and voice guidance is turned on. Specifically, the terminal outputs instructions to the user via voice, such as "Turn left 50 meters ahead."

[0603] Step 5:

[0604] Users initiate safe evacuation actions by following visual and audio instructions provided by their device. This allows users to avoid confusion and reach their intended shelter quickly and accurately. Users act based on the presented route information and evaluate the actual evacuation route.

[0605] (Application Example 1)

[0606] 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".

[0607] In urban areas, when a disaster strikes, it is difficult to provide safe and rapid evacuation services tailored to the diverse characteristics of individual users. Furthermore, updating evacuation routes in real time requires considering the physical characteristics of users and the overall urban situation, but current systems do not adequately address these requirements. Therefore, there is a need for an advanced evacuation support system that is compatible with modern smart device environments and features an intuitively understandable interface.

[0608] 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.

[0609] This invention includes a server that includes a device for inputting and storing the user's personal information, a device for periodically acquiring and transmitting the user's current location information, a device for acquiring the latest disaster-related information from external sources, a technology for analyzing the acquired personal information, current location information, and disaster-related information to generate an optimal evacuation route, and a technology for providing the generated evacuation route to the user through visual display and audio output. This makes it possible to provide evacuation routes in real time that take into account the user's physical characteristics and are adjusted to support evacuation throughout the city.

[0610] "User personal information" refers to individual data such as age, gender, and physical information collected to provide the optimal evacuation route.

[0611] "Current location information" refers to geographical data indicating the physical location of a user at a specific point in time.

[0612] "Disaster-related information" refers to the latest data on natural disasters such as earthquakes and floods, obtained from external sources.

[0613] "Analysis technology" refers to data processing and analysis methods used to generate safe and rapid evacuation routes based on acquired data.

[0614] "Visual display and audio output" refers to the means of screen display and audio guidance used to allow users to intuitively understand the generated evacuation routes.

[0615] "City-wide evacuation support" refers to comprehensive evacuation support provided to diverse users in a specific area, taking their individual characteristics into consideration.

[0616] An embodiment of this invention is an advanced evacuation route guidance system designed to assist users in their safe evacuation. This system mainly consists of a server, terminals, and associated software.

[0617] The server has the functionality to securely store personal information entered by users through their devices. This information includes unique user data such as age, gender, and physical characteristics. Additionally, devices equipped with GPS functionality periodically acquire the user's current location information and transmit it to the server. This allows the server to determine the user's precise location.

[0618] Furthermore, the server acquires the latest disaster-related information from external sources in real time. To this end, it uses a disaster information API to collect information according to the type and scale of the natural disaster. Based on this information, the server uses a generative AI model to analyze the acquired personal information, current location information, and disaster-related information to generate safe and rapid evacuation routes.

[0619] The terminal supports intuitive operation by visually displaying the generated evacuation route to the user and providing voice guidance. This visual and voice guidance helps users avoid confusion and enables rapid evacuation.

[0620] The specific hardware used includes smartphones and smart glasses with GPS capabilities (e.g., typical mobile devices). The software incorporates programs for real-time information processing and route generation using AI models (e.g., custom algorithms using TensorFlow).

[0621] As a concrete example, if an earthquake occurs in the city center, the server will immediately update disaster information and suggest evacuation routes suitable for specific users. For instance, for elderly people, routes with fewer steps will be prioritized. An example of the prompt statements used in this process is shown below.

[0622] Example of a prompt:

[0623] Disaster: Earthquake

[0624] User information: 60 years old, male, has a knee problem.

[0625] Current location: Shinjuku Ward, Tokyo

[0626] Route conditions: Route with minimal elevation changes, shortest route to evacuation shelter.

[0627] This system allows users to quickly find the optimal evacuation procedure tailored to their physical characteristics and circumstances, enabling them to evacuate safely.

[0628] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0629] Step 1:

[0630] The terminal receives personal information from the user. This information includes age, gender, and physical characteristics. This information is stored in a database and prepared for analysis.

[0631] Step 2:

[0632] The device acquires the user's current location information and sends it to the server at regular intervals. The input is geographical coordinate data obtained using GPS functionality, and the server records the user's current location as output. This data forms the basis for generating evacuation routes in real time.

[0633] Step 3:

[0634] The server retrieves the latest disaster-related information from external sources. Input is data obtained from a disaster information API, and output is aggregated information such as the type, scale, and scope of the disaster. This enables faster and more appropriate route generation.

[0635] Step 4:

[0636] The server uses a generated AI model to analyze personal information, current location information, and disaster-related information. It generates prompt messages, and based on these, the AI ​​model generates the optimal evacuation route for the user. Through this process, the input data is integrated and a route is output that provides the user with a safe and rapid means of transportation.

[0637] Step 5:

[0638] The server generates an evacuation route and sends it to the terminal. The terminal receives this and begins guiding the user visually and audibly. The input is the generated evacuation route information, and the output is a signal that the user receives, allowing them to adjust their actions accordingly.

[0639] Step 6:

[0640] The user follows instructions from the device and takes the designated route. This enables safe and efficient movement to shelters or safe locations. The user's actual actions are the system's final output.

[0641] 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.

[0642] This invention is a system that recognizes the user's emotional state and optimizes evacuation route guidance during disasters. First, the user inputs personal information using a terminal, which is then transmitted to a server. Based on this personal information, the terminal prepares to provide evacuation route guidance tailored to the user.

[0643] This system incorporates an emotion engine that infers emotions through the user's camera and microphone. Specifically, it has a function that determines stress levels and emotional distress from the user's facial expressions and tone of voice. This emotional information is sent to a server and integrated with other data to become part of the analysis.

[0644] When a disaster occurs, the device acquires the user's current location information in real time, and this data is sent to the server. The server retrieves the latest information from an external disaster information database and combines the user's personal information, emotional state, and current location to generate a highly customized evacuation route. If the emotional engine determines that the user is under high stress, it adjusts the content and tone of the guidance to provide anxiety-relieving voice guidance.

[0645] The generated evacuation route is sent to the terminal, which visually displays the route and guides the user safely through voice guidance. For example, if a user is feeling anxious during a disaster, the emotion engine detects that emotion and provides a reassuring message such as, "Please stay calm. We will guide you to a safe route." In this way, using the emotion engine enables flexible responses tailored to the user's psychological state, supporting safer and more effective evacuations.

[0646] The algorithm of this system allows for flexible responses tailored to individual situations, enabling personalized responses based on the type of disaster occurring, regional characteristics, and the user's emotional state.

[0647] The following describes the processing flow.

[0648] Step 1:

[0649] The user enters personal information on the device. This personal information includes age, gender, and physical characteristics. The device encrypts this information and sends it to the server. The server stores the information in a database and notifies the device when it is ready.

[0650] Step 2:

[0651] The device obtains the user's current location information. This operation is performed using GPS, and the location information is periodically sent to the server. The server records the received location information and updates the user's status.

[0652] Step 3:

[0653] The emotion engine uses the device's built-in camera and microphone to analyze the user's emotions. This includes steps to detect changes in facial expressions and tone of voice, and to determine the stress level. The emotional information is then sent to a server.

[0654] Step 4:

[0655] The server retrieves the latest disaster information from an external disaster information database. The data includes the progress of earthquakes, typhoons, and fires, and the server uses this information to assess the level of risk.

[0656] Step 5:

[0657] The server generates evacuation routes using an AI algorithm based on the user's personal information, current location, emotional state, and the latest disaster information. In particular, if a high-stress state is detected, it selects a safe route and approach that takes psychological burden into consideration.

[0658] Step 6:

[0659] The terminal receives an evacuation route generated from the server. The route is displayed on the screen, and voice guidance begins. Messages to reassure the user may also be included. The user can follow the guidance and evacuate safely along the designated route.

[0660] (Example 2)

[0661] 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".

[0662] Providing safe and rapid evacuation guidance while reducing the psychological stress of evacuees during natural disasters is a challenging task. Conventional evacuation route guidance systems provide information without considering the user's emotional state, which can actually increase evacuees' anxiety. There is a need for a system that can solve this problem.

[0663] 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.

[0664] In this invention, the server includes means for capturing and analyzing the user's emotional state, means for analyzing the acquired personal information, current location information, emotional state, and disaster information to generate an optimal evacuation route, and means for adjusting voice guidance according to the user's emotional state using a generated AI model. This makes it possible to provide an optimal evacuation route tailored to the individual emotional state of each evacuee.

[0665] "Personal information" refers to identifiable information such as a user's name and address, and is data used to identify users and provide appropriate services.

[0666] "Emotional state" refers to information that indicates the user's psychological and emotional condition, including stress levels and emotional distress.

[0667] "Current location information" refers to data that indicates the user's actual geographical location, and is usually obtained using GPS.

[0668] A "disaster information database" is an external information source that stores the latest data on disaster situations, warnings, and other information.

[0669] "Evacuation routes" refer to route information designed to enable users to evacuate safely and quickly.

[0670] A "generative AI model" refers to an artificial intelligence algorithm that generates appropriate output based on user input, and is particularly used to adjust voice guidance according to the user's emotional state.

[0671] "Voice guidance" refers to a system or message that provides information to the user through audio in addition to visual information.

[0672] As a form for implementing the invention, this system has the function of supporting evacuation during disasters. The system mainly consists of a terminal owned by the user and a server that processes data.

[0673] Users enter personal information using devices such as smartphones and tablets. These devices have the capability to encrypt this information and securely transmit it to the server. Furthermore, the devices are equipped with cameras and microphones, which are used to capture the user's facial expressions and voice. This data is analyzed by an emotion engine to infer the user's emotional state.

[0674] The server generates the optimal evacuation route using received personal information, emotional state, and real-time current location information transmitted from the terminal. During this process, it references an external disaster information database and incorporates the latest disaster information to construct real-time evacuation route information. Using a generation AI model, it also adjusts voice guidance according to the user's emotional state. For example, if high stress is detected, it generates a message encouraging calmness.

[0675] The generated evacuation route information is delivered to the terminal. The terminal visually displays the route and guides the user through voice guidance. For example, if the user feels stressed during an earthquake, it can provide a message such as, "Please stay calm. We will guide you to a safe route." In this way, it is possible to support safe and rapid evacuation while taking the user's emotional state into consideration.

[0676] An example of a prompt for the generating AI model would be: "Generate an appropriate voice guidance message for when a user experiences stress during an earthquake."

[0677] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0678] Step 1:

[0679] The user enters personal information via the device. After receiving this information, the device sends it to the server using an encryption protocol. The entered data includes name and address, and the output is encrypted.

[0680] Step 2:

[0681] The device activates its built-in camera and microphone to capture the user's facial expressions and voice. This data is sent as input to the emotion engine, where it is analyzed using a neural network. The emotion engine evaluates the user's stress level and emotional state and outputs it as emotional state information.

[0682] Step 3:

[0683] The device uses GPS functionality to obtain the user's current location. The acquired geographical information is sent to the server as input, and the output is the user's real-time location information.

[0684] Step 4:

[0685] The server combines emotional state, personal information, and current location information with an external disaster information database. The server applies an optimization algorithm to analyze this input data and generate the optimal evacuation route. The output is customized evacuation route information.

[0686] Step 5:

[0687] The server uses a generative AI model to create voice guidance tailored to the user's emotional state. If a high-stress state is detected, the generative AI generates a message to encourage calmness based on the prompt text. The input is emotional state information, and the output is a tailored voice guidance message.

[0688] Step 6:

[0689] The generated evacuation route and voice guidance data are transmitted from the server to the terminal. The terminal receives this information, visually displays the route on a map through the user interface, and activates the voice guidance system. The output consists of the visually displayed route and voice guidance.

[0690] (Application Example 2)

[0691] 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".

[0692] During disasters, it has been difficult to provide flexible evacuation guidance that takes into account the emotional state of users. Therefore, there is a need for a system that provides personalized evacuation guidance according to the user's psychological state, supporting safe evacuation while reducing anxiety.

[0693] 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.

[0694] In this invention, the server includes means for inputting and storing the user's personal information, means for periodically acquiring and transmitting the user's current location information and emotional state, means for acquiring the latest disaster information from an external database, means for analyzing the acquired personal information, current location information, emotional state, and disaster information to generate an optimal evacuation route, and means for providing the generated evacuation route to the user visually and audibly. This enables appropriate and reassuring evacuation guidance tailored to the user's psychological state.

[0695] "User personal information" refers to data that includes identifiable information related to the user and is used to customize evacuation instructions.

[0696] "Current location information" is data that indicates the user's geographical location, is acquired in real time, and is used to generate evacuation routes.

[0697] "Emotional state" refers to the user's psychological and emotional state, and is information inferred from facial expressions, tone of voice, and other factors.

[0698] "Disaster information" refers to the latest information regarding the occurrence of natural disasters, etc., obtained from external databases.

[0699] "Analysis" refers to the process of calculation and decision-making performed to derive the optimal evacuation route based on various acquired data.

[0700] An "evacuation route" refers to the optimal route that a user should take to evacuate safely, and it is generated through analysis.

[0701] "Providing information visually and aurally" refers to conveying information to the user through screen displays and audio guidance.

[0702] This invention describes a disaster-response evacuation route guidance system using a server and a user's terminal. The server comprehensively analyzes the user's personal information, current location information, emotional state, and disaster information obtained from an external database.

[0703] The user's device is a smartphone or similar mobile device, and its camera and microphone are used to capture the user's facial expressions and voice in real time. The data obtained is then used to estimate the user's emotional state using sentiment analysis software such as the Google Cloud Vision API or IBM Watson Tone Analyzer. This emotional information is sent to a server and analyzed along with other information.

[0704] The server uses the Google Maps API to obtain the user's current location in real time. It also uses national and regional public disaster information APIs to obtain the latest disaster information. Based on this information, it generates an evacuation route suitable for each individual user. The generated route is displayed visually on the device screen and also output as voice guidance. The voice guidance is adjusted to take into account the user's emotional state and includes messages that provide reassurance.

[0705] For example, if a user is caught in an earthquake and feeling anxious, this system will assist them with voice guidance such as, "Please stay calm. We will guide you to a safe route."

[0706] An example of a prompt for a generative AI model would be: "When a user is instructed to evacuate due to an earthquake, please design an algorithm that analyzes the user's emotions in real time and proposes the optimal evacuation route and mental support messages."

[0707] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0708] Step 1:

[0709] The device captures the user's facial expressions with its camera and acquires their voice with its microphone. This input data is sent to emotion analysis software. The software analyzes the facial recognition information obtained through the camera and the features of the voice to infer the user's emotional state.

[0710] Step 2:

[0711] The terminal sends the analyzed emotional state to the server. The input data is the result of the emotion analysis, which the server receives and prepares to integrate with other data necessary for generating evacuation routes.

[0712] Step 3:

[0713] The device obtains its current location information via GPS and sends it to the server. The location information is obtained in real time using the Google Maps API and is input to the server as location data for generating evacuation routes.

[0714] Step 4:

[0715] The server retrieves the latest disaster information using an external database. Using data from the disaster information API as input, the server analyzes the type, intensity, and extent of the disaster, and aggregates the information necessary for evacuation planning.

[0716] Step 5:

[0717] The server integrates personal information, current location information, emotional state, and disaster information, and uses a generative AI model to generate the optimal evacuation route. It analyzes each piece of information as input and outputs an efficient and safe evacuation route.

[0718] Step 6:

[0719] The server generates an evacuation route and sends it to the terminal. The output provided to the user is a visual map display and audio guidance.

[0720] Step 7:

[0721] The device visually displays evacuation routes on its screen and plays voice guidance according to the user's emotional state. Specifically, it provides voice guidance that includes mental support messages to promote a sense of security and guide the user.

[0722] 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.

[0723] 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 the following. 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 indicated 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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.

[0728] 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.

[0729] 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.

[0730] 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."

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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.

[0735] 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.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0743] The following is further disclosed regarding the embodiments described above.

[0744] (Claim 1)

[0745] A means for entering and storing users' personal information,

[0746] A means of periodically acquiring and transmitting the user's current location information,

[0747] A means of obtaining the latest disaster information from an external database,

[0748] A means of analyzing acquired personal information, current location information, and disaster information to generate the optimal evacuation route,

[0749] A means of providing the generated evacuation route to the user,

[0750] A system that includes this.

[0751] (Claim 2)

[0752] The system according to claim 1, wherein the analysis means takes into account the user's physical characteristics and adjusts the optimal evacuation route.

[0753] (Claim 3)

[0754] The system according to claim 1, wherein the generated evacuation route is output as voice guidance.

[0755] "Example 1"

[0756] (Claim 1)

[0757] A means of acquiring and storing user attribute information,

[0758] A means of periodically acquiring and transmitting user location data,

[0759] A means of obtaining the latest disaster-related data from external sources,

[0760] A means for analyzing acquired attribute information, location data, and disaster-related data, and generating the optimal evacuation route using an algorithm,

[0761] A means of displaying and guiding users using the generated evacuation route,

[0762] A system that includes this.

[0763] (Claim 2)

[0764] The system according to claim 1, wherein the analysis means takes into account the user's mobility and individually adjusts the optimal evacuation route.

[0765] (Claim 3)

[0766] The system according to claim 1, wherein the generated evacuation route is indicated through visual and auditory means.

[0767] "Application Example 1"

[0768] (Claim 1)

[0769] A device for inputting and storing users' personal information,

[0770] A device that periodically acquires and transmits the user's current location information,

[0771] A device for obtaining the latest disaster-related information from external sources,

[0772] Technology that analyzes acquired personal information, current location information, and disaster-related information to generate the optimal evacuation route,

[0773] A technology that provides users with generated evacuation routes through visual display and audio output,

[0774] A system that includes this.

[0775] (Claim 2)

[0776] The system according to claim 1, wherein the analysis technology takes into account the user's physical characteristics and adjusts evacuation routes in order to provide evacuation support for the entire city.

[0777] (Claim 3)

[0778] The system according to claim 1, wherein the generated evacuation route is provided through voice guidance and a visual interface.

[0779] "Example 2 of combining an emotion engine"

[0780] (Claim 1)

[0781] A means of inputting and storing users' personal information,

[0782] A means of capturing and analyzing the emotional state of users,

[0783] A means of periodically acquiring and transmitting the user's current location information,

[0784] A means of obtaining the latest disaster information from an external database,

[0785] A means of analyzing acquired personal information, current location information, emotional state, and disaster information to generate the optimal evacuation route,

[0786] A means of adjusting voice guidance according to the user's emotional state using a generative AI model,

[0787] A means of providing the generated evacuation route to the user visually and audibly,

[0788] A system that includes this.

[0789] (Claim 2)

[0790] The system according to claim 1, wherein the analysis means takes into account the user's emotional state and physical characteristics and adjusts the optimal evacuation route.

[0791] (Claim 3)

[0792] The system according to claim 1, wherein the generated evacuation route is output as voice guidance adjusted based on the emotional state.

[0793] "Application example 2 when combining with an emotional engine"

[0794] (Claim 1)

[0795] A means of inputting and storing users' personal information,

[0796] A means of periodically acquiring and transmitting the user's current location information and emotional state,

[0797] A means of obtaining the latest disaster information from an external database,

[0798] A means of analyzing acquired personal information, current location information, emotional state, and disaster information to generate the optimal evacuation route,

[0799] Means for providing the generated evacuation route to the user visually and audibly,

[0800] A system that includes this.

[0801] (Claim 2)

[0802] The system according to claim 1, wherein the analysis means takes into account the user's emotional characteristics and adjusts the content and tone of the evacuation guidance.

[0803] (Claim 3)

[0804] The system according to claim 1, wherein the generated evacuation route is output as voice guidance that takes into account the user's psychological state and provides a sense of security. [Explanation of Symbols]

[0805] 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 device for inputting and storing users' personal information, A device that periodically acquires and transmits the user's current location information, A device for obtaining the latest disaster-related information from external sources, A device that analyzes acquired personal information, current location information, and disaster-related information to generate the optimal evacuation route, A device that provides the user with a generated evacuation route through visual display and audio output, A system that includes this.

2. The system according to claim 1, wherein the analysis technology takes into account the physical characteristics of the user and adjusts evacuation routes in order to provide evacuation support for the entire city.

3. The system according to claim 1, wherein the generated evacuation route is provided through voice guidance and a visual interface.

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