System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving an emergency alert mail; means for obtaining location information; means for searching for shelter information; means for summarizing and translating information using generative artificial intelligence; and means for interacting with a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] When a disaster occurs, depending on the situation, it can be difficult to access evacuation sites and disaster information, causing anxiety in many cases. For example, when traveling or on a business trip, it can be difficult to find an appropriate evacuation site when you are unfamiliar with your current location. International students and tourists can also be at a loss because they cannot understand the content of the warnings. Furthermore, disaster information is often confusing, making it difficult to find the information you need. Solving these problems and providing prompt and appropriate information during disasters is essential. [Means for solving the problem]

[0005] The present invention provides a system including a means for receiving emergency alert emails, a means for acquiring location information, a means for searching for evacuation site information, a means for summarizing and translating the information using a generative artificial intelligence, and a means for interactively exchanging information with a user. This allows a user to link with the emergency alert email and quickly find the nearest evacuation site based on the location information. By utilizing the generative artificial intelligence, disaster information and news can be summarized and provided in multiple languages, making it possible to accommodate users who speak different languages. Furthermore, providing information interactively allows for detailed guidance based on individual user questions. In this way, users can reduce their anxiety and take evacuation action with peace of mind.

[0006] An "emergency alert email" is an email sent to quickly convey information about disasters and emergencies to users.

[0007] "Location information" refers to the latitude and longitude of the user's current location obtained using GPS or other location measurement means.

[0008] "Evacuation site information" is data such as the name, address, contact information, and access route of a designated location for safe evacuation in the event of a disaster.

[0009] "Generative AI" is an AI technology that can generate text using natural language processing and machine learning techniques.

[0010] "Means for summarizing information" refers to techniques for concisely summarizing long pieces of information and extracting only the key points that are important to the user.

[0011] "Means for translating information" refers to techniques for converting information written in one language into another language.

[0012] "User" means an individual or organization that uses the system.

[0013] "Means for interactively exchanging information" refers to a mechanism that allows users to communicate with the system two-way through text or voice. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. This system combines functions for receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using AI generation, and exchanging information interactively with users.

[0036] Program processing explanation

[0037] 1. Information gathering stage

[0038] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The device also obtains the language information set by the user from the device's settings. The device then receives an emergency alert email via the mobile network and analyzes its contents.

[0039] 2. Identifying evacuation sites

[0040] The device sends the acquired location information to a server, which then uses this information to search for the nearest evacuation shelter in the local government's database. The search results include details such as the shelter's name, address, contact information, and a map link.

[0041] 3. Disaster Information Summary and Translation

[0042] The server collects the latest disaster news and social media information. This information is obtained from news APIs and social media feeds. It then uses generative AI to summarize this information and translate it into the user's language of choice. The translated information is then presented in a format that is easy for the user to understand.

[0043] 4. Interactive Response

[0044] The device displays a chat box-style interface to the user, allowing the user to ask questions about evacuation sites and disaster information. For example, if the user types "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server.

[0045] The server uses a generation AI to instantly respond to the user's questions, providing specific information such as, "The nearest evacuation site from your current location is Hibiya Park, 100 meters away." The generation AI also flexibly responds to the user's additional questions, providing a sense of security.

[0046] Specific examples

[0047] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0048] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0049] 2. The device sends its location information around Tokyo Station to the server.

[0050] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0051] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0052] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0053] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0054] Example 2: When the overseas trainee does not understand the content of the warning

[0055] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[0056] 2. The device sends the contents of the received emergency alert email to the server.

[0057] 3. The server uses the generation AI to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[0058] 4. The generating AI returns the translation results to the device and notifies the user of the alert content.

[0059] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[0060] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using generation AI.

[0061] In this way, the system of the present invention enables users to quickly and accurately receive necessary disaster information and evacuation instructions in an emergency. Specific information is provided according to the user's current location and language, reducing anxiety during a disaster and enabling safe evacuation.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] The device acquires the user's current location using the GPS function. Specifically, it collects latitude and longitude information through the built-in GPS module of the smartphone or tablet.

[0065] Step 2:

[0066] The device acquires the user's language setting information. Specifically, it checks the display language selected by the user (e.g., Japanese, English, Spanish, etc.) from the device's system settings.

[0067] Step 3:

[0068] The device receives emergency alert emails via the mobile network and analyzes the content of the email to determine the type of disaster and its urgency.

[0069] Step 4:

[0070] The device sends the acquired location information and emergency alert email information to the server. The sent data includes latitude, longitude, language setting, and the content of the emergency alert.

[0071] Step 5:

[0072] The server uses the received location information to search for the nearest evacuation site in the local government's database, which contains information such as the name, address, contact information, and capacity of each evacuation site.

[0073] Step 6:

[0074] The server passes the evacuation site information to the AI ​​generator and has it translate it into a language the user can understand. For example, Japanese evacuation site information can be translated into English, Spanish, etc.

[0075] Step 7:

[0076] The server collects the latest disaster news and social media information from the internet, summarizes the collected information using generative AI, and translates it into the language specified by the user.

[0077] Step 8:

[0078] The server sends evacuation site information and summarized / translated disaster information to the terminal.

[0079] Step 9:

[0080] The device displays a chat interface to the user, providing information on evacuation sites and disasters in an interactive format and answering any additional questions.

[0081] Step 10:

[0082] Users input questions about evacuation shelters and disaster information through the chat interface, such as "Where is the nearest evacuation shelter?" and "What items should I bring to the evacuation shelter?"

[0083] Step 11:

[0084] The terminal analyzes the user's question and sends an appropriate request to the server.

[0085] Step 12:

[0086] The server uses generative AI to instantly respond to user questions, providing specific information such as, "The nearest evacuation site is Hibiya Park, 100 meters away."

[0087] Step 13:

[0088] The terminal displays the response received from the server to the user, who can then take appropriate action based on the information provided.

[0089] The above is the specific processing flow of the "AI-Disaster Guide" system, which enables users to quickly and accurately receive the disaster information and evacuation instructions they need in an emergency.

[0090] Example 1

[0091] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0092] In recent years, natural disasters have become more frequent, creating a need for rapid and accurate information provision in the event of a disaster. However, issues remain, such as a lack of multilingual support and difficulty in identifying evacuation sites based on the user's current location. Furthermore, there are cases where the content of emergency alert emails is difficult to understand, and appropriate evacuation sites are unknown. A system is needed to resolve these issues and streamline the provision of disaster information.

[0093] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0094] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using a generative AI model, means for interactively exchanging information with a user, means for analyzing the content of the emergency alert emails, means for searching for the nearest evacuation site from a local government database, means for collecting news and SNS information, and means for providing a user interface. This allows users to quickly and accurately receive the information they need in the event of a disaster, improving the efficiency of emergency responses.

[0095] The "means for receiving emergency alert emails" is a function that enables a terminal to receive emergency alert emails that are sent when a disaster occurs.

[0096] "Means for acquiring location information" refers to a function for acquiring the latitude and longitude of the user's current location using a GPS function or the like.

[0097] The "means for searching for evacuation site information" is a function for searching for the nearest evacuation site based on the acquired location information.

[0098] "Means for summarizing and translating information using generative AI models" refers to the function of summarizing and translating collected disaster information into multiple languages ​​using generative AI technology.

[0099] The "means for exchanging information interactively with the user" is a function that allows the user to ask questions and respond using a chat box-style interface.

[0100] The "means for analyzing the contents of the emergency alert email" is a function for analyzing the contents of the received emergency alert email and extracting information necessary for the user.

[0101] "Means to search for the nearest evacuation site from the local government's database" is a function that searches for the nearest evacuation site based on location information from a database managed by the local government.

[0102] "Means of collecting news and social media information" refers to a function for collecting information from the latest disaster news and social media.

[0103] The "means for providing a user interface" is a function that provides an interface for users to check disaster information and ask and answer questions.

[0104] This invention is a system for providing users with fast and accurate information in the event of a disaster. This system combines functions for receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using a generative AI model, and exchanging information interactively with users.

[0105] Hardware and Software Configuration

[0106] Terminal

[0107] The devices are mobile communication devices such as smartphones and tablets. These devices have the following features:

[0108] GPS function: Obtain the user's current location

[0109] Mobile network: Receive emergency alert emails

[0110] User interface: Interact with the user in a chat box format

[0111] server

[0112] The server has the following features:

[0113] News API and SNS feed aggregation tool: Obtain the latest disaster news and SNS information

[0114] Database: Manages and provides information on evacuation sites for local governments

[0115] Generative AI models: Summarize collected information and translate it into a language the user can understand

[0116] What the program does

[0117] 1. Information gathering

[0118] The device first obtains the user's location information using its GPS function. For example, it obtains latitude and longitude information using the Google® Maps API. It also reads the language information set by the user from the device's settings menu. Next, it receives an emergency alert email via the mobile network and analyzes its contents using a text analysis tool.

[0119] 2. Identifying evacuation sites

[0120] The device sends the acquired location information to the server via an HTTP request. The server searches the database for the nearest evacuation site based on the location information and returns the results to the device, allowing the device to show the nearest evacuation site to the user.

[0121] 3. Disaster Information Summary and Translation

[0122] The server collects the latest disaster news from news APIs (e.g., Google News API) and social media feeds. This information is summarized and translated using a generative AI model (e.g., OpenAI's GPT-3 or GPT-4). The translated information is then sent to the device and provided to the user.

[0123] 4. Interactive Response

[0124] The device provides the user with a chat box-style interface, implemented, for example, using React Native. The user enters a question through the chat box, which the device analyzes and sends to the server. The server uses a generative AI model to instantly respond to the user's question, which is then returned to the device and displayed to the user.

[0125] Specific examples

[0126] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0127] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0128] 2. The device sends its location information around Tokyo Station to the server.

[0129] 3. The server uses the generative AI model to search for information about the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0130] 4. The generative AI model translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0131] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0132] 6. The generative AI model responds, "Shelters need drinking water, emergency food, phone chargers, medicine, etc."

[0133] Example 2: When the overseas trainee does not understand the content of the warning

[0134] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[0135] 2. The device sends the contents of the received emergency alert email to the server.

[0136] 3. The server uses the generative AI model to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[0137] 4. The generative AI model returns the translation results to the device and notifies the user of the alert content.

[0138] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[0139] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using a generative AI model.

[0140] In this way, the system of the present invention provides necessary information quickly and accurately in the event of a disaster, thereby ensuring the safety of users.

[0141] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0142] Step 1:

[0143] The device first obtains the user's current location using its GPS function. It uses data from the GPS sensor as input and outputs location information in the form of latitude and longitude. Specific examples include obtaining location information using the Google Maps API.

[0144] Step 2:

[0145] The device reads the language information set by the user from the device's settings menu. It uses the device's locale setting data as input and outputs the set language information. This obtains the user's language setting (e.g., Japanese, English, etc.).

[0146] Step 3:

[0147] The device receives emergency alert emails via the mobile network. It analyzes the received email data as input and outputs important disaster information (e.g., type of disaster, location, response methods, etc.). Specifically, it uses natural language processing (NLP) technology to perform text analysis.

[0148] Step 4:

[0149] The device sends its location information (latitude and longitude) to the server through an HTTP request. The server uses the location data obtained as input and provides the location information as output. This request is sent to identify the required evacuation location.

[0150] Step 5:

[0151] The server searches for the nearest evacuation site from the local government's database based on the location information. Using the location information data received as input, it outputs detailed information such as the name, address, contact information, and map link of the evacuation site. Specific operations use a database management system such as PostgreSQL.

[0152] Step 6:

[0153] The server sends the search results in JSON format to the device. It uses the organized evacuation location information as input and provides detailed information of evacuation locations to the device as output. This information can be used by the user to quickly find the nearest evacuation location.

[0154] Step 7:

[0155] The server collects the latest disaster news and social media information from news APIs and social media feeds. It uses information obtained from various APIs as input and outputs the collected disaster information. Specific operations include using the Google News API and Twitter API.

[0156] Step 8:

[0157] The server uses a generative AI model to summarize the collected disaster information and translate it into the language set by the user. It uses collected news and social media information and the user's language setting as input, and outputs the summarized and translated information. Specific examples use OpenAI's GPT-3 and GPT-4 and the Google Translate API.

[0158] Step 9:

[0159] The server sends the translated summary information to the terminal in JSON format. It uses the translated information data as input and provides the information to the terminal as output. This information is displayed in a format that is easy for the user to understand.

[0160] Step 10:

[0161] The terminal displays a chat box-style interface to the user. It uses user interface configuration information as input and provides the interface as output. Specifically, the interface is constructed using React Native.

[0162] Step 11:

[0163] The user inputs questions about evacuation sites and disaster information through the chat box. The user's text input data is used as input, and this is sent to the terminal. A specific example includes the action of inputting "Where is the nearest evacuation site?"

[0164] Step 12:

[0165] The device analyzes the user's question and sends it to the server. It uses the user's text data as input and analyzes it using natural language processing (NLP). It provides the analysis results to the server as output.

[0166] Step 13:

[0167] The server uses a generative AI model to instantly respond to user questions. It uses the analyzed question data as input and outputs a specific response. For example, if a user asks about the nearest evacuation site, it provides that information.

[0168] Step 14:

[0169] The server uses the generative AI model to generate a response and sends it to the terminal in JSON format. The generated response data is used as input and provided to the terminal as output. This information is displayed in a user-friendly format.

[0170] Step 15:

[0171] The terminal displays the response result in a chat box and provides it to the user. The received response data is used as input and displayed on the user's interface as output. A specific example includes the action of displaying "The nearest evacuation site from your current location is 100 meters away."

[0172] (Application example 1)

[0173] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0174] In the event of a disaster, it is extremely important to obtain accurate information quickly and respond appropriately. However, if information is not provided in multiple languages, it becomes difficult to provide effective information to users who have language barriers, such as foreigners. Furthermore, when there is a huge amount of information, it is difficult to quickly summarize and translate each piece of information and provide it in a form that users can understand. Furthermore, when users ask specific questions on the spot, it is difficult to obtain accurate answers in real time. A new system is needed to solve these issues.

[0175] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0176] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with a user in an interactive format, means for summarizing emergency alerts using a generative model, and means for providing real-time responses to user questions in multiple languages. This enables the rapid and accurate provision of information in the event of a disaster, particularly by enhancing multilingual support and responses to real-time user questions, thereby enabling support for users to take appropriate action.

[0177] "Means for receiving emergency emails" refers to a communication system for notifying user terminals of information about disasters and emergencies.

[0178] "Means for obtaining location information" refers to a system that uses GPS or other location-determining technology to obtain a user's current location in the form of latitude and longitude.

[0179] "Means for searching for evacuation site information" refers to a system that identifies the nearest evacuation site based on the user's current location information and provides that information.

[0180] "Means for summarizing and translating information using generative artificial intelligence" refers to a system that uses a generative AI model to concisely summarize collected disaster information and translate it into language that users can understand.

[0181] "Means for interactively exchanging information with the user" refers to a system that uses an interface such as a chat box or voice recognition to respond to questions from the user in an interactive manner.

[0182] "Means for summarizing emergency alerts using a generative model" refers to a system that uses a generative AI model to concisely summarize the contents of emergency alert emails.

[0183] "Means for providing real-time responses to user questions in multiple languages" refers to a system that uses generative AI models and natural language processing technology to provide real-time answers to questions asked by users in multiple languages.

[0184] This invention was developed to implement a "Disaster Countermeasure Security Guide" system that provides prompt and accurate information in the event of a disaster. This system is implemented on devices such as smartphones and smart glasses, and provides the following specific functions:

[0185] 1. Receiving emergency alert emails

[0186] The terminal receives emergency alert emails about disasters and emergencies via the communication network, allowing users to obtain important information in real time.

[0187] 2. Obtaining location information

[0188] The device uses the GPS function to obtain the user's current location. The current location information is obtained in the form of latitude and longitude and sent to the server. This allows the user to know exactly where they are.

[0189] 3. Search for evacuation shelter information

[0190] The server searches the local government's database for the nearest evacuation site based on the user's location information. The search results include the name, address, and map link of the evacuation site, and this information is provided to the user.

[0191] 4. Summary and Translation of Information

[0192] The server collects emergency alerts and the latest disaster information and summarizes the information using a generative AI model. Furthermore, to support multiple languages, the summarized information is translated into the language selected by the user. This allows users, such as foreigners, who face language barriers, to understand accurate information.

[0193] 5. Interactive information provision

[0194] The device provides a chat box-style interface and responds to user questions in real time. The server uses a generative AI model to generate appropriate answers to the user's questions and provides them in multiple languages. For example, in response to the question, "Where is the nearest evacuation site?", it provides specific information such as, "The nearest evacuation site is a park 100 meters away."

[0195] Hardware and software used

[0196] Hardware: Smartphones, smart glasses

[0197] software:

[0198] Geopy: a location processing library

[0199] Transformers: A natural language processing library

[0200] OpenAI GPT-3: Generative AI model

[0201] Specific examples

[0202] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0203] 1. The user starts up the device and obtains the current location information (latitude: 35.6895, longitude: 139.6917).

[0204] 2. The device sends the location information to the server.

[0205] 3. The server uses the generation AI to search for information on the nearest evacuation site and provide it to the user.

[0206] 4. The generating AI translates the information into the language set by the user (English) and shows the route to the evacuation site.

[0207] 5. The user asks in the chat box, "What do you need for evacuation shelters?"

[0208] 6. The generated AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0209] Prompt Sentence Examples

[0210] "Please summarize: Emergency alert: Earthquake has occurred. Evacuate immediately."

[0211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0212] Step 1:

[0213] The terminal receives an emergency alert email. The input is the emergency alert email sent over a communication network, and the terminal receives the email content as a message. The output is the text information of the received emergency alert email. This text information is used in the next step.

[0214] Step 2:

[0215] The device obtains location information. The input is a process that obtains the current latitude and longitude through the GPS function. The output is the numerical data of the latitude and longitude corresponding to the user's current location. This numerical data is used in the next step.

[0216] Step 3:

[0217] The server searches for evacuation shelters based on location information. The input is the latitude and longitude of the current location obtained in step 2, and references the evacuation shelter database. The output is information about the evacuation shelter closest to the current location (name, address, contact information, map link, etc.). This information is used in the next step.

[0218] Step 4:

[0219] The server uses a generative AI model to summarize the content of the emergency alert email. The input is the text information of the emergency alert email received in step 1, which is provided to the generative AI model as a prompt. The output is the summary text of the emergency alert email. This summary text is used in the next step.

[0220] Step 5:

[0221] The server uses a generative AI model to translate the summarized disaster information. The input is the summary text obtained in step 4 and the language information set by the user. The output is the text translated from the summary text into the specified language. This translated text is used in the next step.

[0222] Step 6:

[0223] The terminal exchanges information with the user in a dialogue format. The input is a question text from the user (e.g., "Where is the nearest evacuation site?"). The output is a response text from the server, which is displayed in a format that the user can view in a chat box.

[0224] Step 7:

[0225] The server uses a generative AI model to respond to user questions. The input is the question text sent by the user via the terminal, and the generative AI model analyzes the question. The output is a specific and accurate response text to the question. This response text is sent to the terminal and provided to the user.

[0226] Specific actions

[0227] 1. Obtaining location information: The GPS module is used to obtain latitude and longitude, and this is sent to the server along with the contents of the emergency alert email.

[0228] 2. Search for evacuation shelters: The server accesses the local government database to identify the nearest evacuation shelter from the user's current location. It also translates the information into the user's language.

[0229] 3. Information Summarization: Using a generative AI model (e.g., OpenAI GPT-3), a concise summary of the received emergency alert email is created. This summary is sent as a prompt to the generative AI model in the next step.

[0230] 4. Multilingual translation: Using a translation model (e.g., MarianMT model), summarizes information and outputs it in multiple languages.

[0231] 5. Conversational information provision: Users can ask questions via a chat box, and the generative AI will provide an appropriate response based on the question.

[0232] Prompt Sentence Examples

[0233] "Please summarize: Emergency alert: Earthquake has occurred. Evacuate immediately."

[0234] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0235] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. This system combines functions such as receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using generative AI, exchanging information with users in a dialogue format, and an emotion engine that recognizes the user's emotions.

[0236] Program processing explanation

[0237] 1. Information gathering stage

[0238] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The device also obtains the language information set by the user from the device's settings. The device then receives an emergency alert email via the mobile network and analyzes its contents.

[0239] 2. Identifying evacuation sites

[0240] The device sends the acquired location information and emergency alert email information to the server. The sent data includes latitude, longitude, language setting, and the content of the emergency alert.

[0241] The server uses the received location information to search the local government's database for the nearest evacuation shelter, and the search results include details such as the shelter's name, address, contact information, and a map link.

[0242] 3. Disaster Information Summary and Translation

[0243] The server collects the latest disaster news and social media information. This information is obtained from news APIs and social media feeds. It then uses generative AI to summarize this information and translate it into the user's language of choice. The translated information is then presented in a format that is easy for the user to understand.

[0244] 4. Introducing the Emotion Engine

[0245] The device runs an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotional state (e.g., anxiety, relief, confusion, etc.) from their voice and text.

[0246] 5. Interactive Response

[0247] The device displays a chat box-style interface to the user, allowing the user to ask questions about evacuation sites and disaster information. For example, if the user types "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server.

[0248] The server uses a generation AI to instantly respond to the user's questions. For example, it provides specific information such as, "The nearest evacuation site from your current location is Hibiya Park, 100 meters away." The generation AI also adjusts the response based on the user's emotional state. For example, if the user is feeling anxious, it adds a reassuring comment.

[0249] Specific examples

[0250] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0251] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0252] 2. The device sends its location information around Tokyo Station to the server.

[0253] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0254] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0255] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0256] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0257] 7. The emotion engine detects the user's anxiety and adds comments such as, "Don't worry, there is a shelter near your current location."

[0258] Example 2: When the overseas trainee does not understand the content of the warning

[0259] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[0260] 2. The device sends the contents of the received emergency alert email to the server.

[0261] 3. The server uses the generation AI to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[0262] 4. The generating AI returns the translation results to the device and notifies the user of the alert content.

[0263] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[0264] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using generation AI.

[0265] 7. The emotion engine detects the user's confusion and adds a comment such as, "Don't worry, we'll give you detailed directions to the evacuation shelter."

[0266] In this way, the system of the present invention allows users to quickly and accurately receive necessary disaster information and evacuation instructions in an emergency. Furthermore, by recognizing the user's emotions in real time and responding appropriately according to their emotional state, anxiety and confusion during a disaster can be reduced. Specific information is provided according to the user's current location and language, allowing them to take safe evacuation action.

[0267] The processing flow will be explained below.

[0268] Step 1:

[0269] The device acquires the user's current location using the GPS function. Specifically, it collects latitude and longitude information using the built-in GPS module of the smartphone or tablet.

[0270] Step 2:

[0271] The terminal acquires the user's language setting information. Specifically, the terminal checks the display language selected by the user (e.g., Japanese, English, Spanish, etc.) from the terminal's system settings.

[0272] Step 3:

[0273] The device receives emergency alert emails via the mobile network, analyzes the content of the emails, and determines the type of disaster and its urgency.

[0274] Step 4:

[0275] The device sends the acquired location information and emergency alert email information to the server. The transmitted data includes latitude, longitude, language setting, and the content of the emergency alert email.

[0276] Step 5:

[0277] The server uses the received location information to search for the nearest evacuation site in the local government's database, which contains information such as the name, address, contact information, and capacity of each evacuation site.

[0278] Step 6:

[0279] The server passes the evacuation site information to the AI ​​generator and has it translate it into a language the user can understand. For example, Japanese evacuation site information can be translated into English, Spanish, etc.

[0280] Step 7:

[0281] The server collects the latest disaster news and social media information from the internet, summarizes the collected information using generative AI, and translates it into the language specified by the user.

[0282] Step 8:

[0283] The server sends summarized and translated disaster information and evacuation shelter information to the terminal, including evacuation shelter routes and important disaster news.

[0284] Step 9:

[0285] The device displays a chat interface to the user, through which the user can ask questions about evacuation sites and disaster information.

[0286] Step 10:

[0287] The device runs an emotion engine to recognize emotions from the user's voice and text. The emotion engine analyzes the tone of the voice and keywords in the text to identify the user's emotional state (e.g., anxiety, relief, confusion, etc.).

[0288] Step 11:

[0289] Users can input questions about evacuation shelters and disaster information through the chat interface, such as "Where is the nearest evacuation shelter?" and "What items should I bring to the evacuation shelter?"

[0290] Step 12:

[0291] The device analyzes the input question and sends an appropriate request to the server. The transmitted data includes the user's question and the emotion analysis results of the emotion engine.

[0292] Step 13:

[0293] The server uses generative AI to instantly respond to the user's questions, generating information such as "The nearest evacuation site from your current location is Hibiya Park, 100 meters away," and adding additional comments based on the user's emotional state.

[0294] Step 14:

[0295] The device displays the response received from the server to the user. To reassure the user, a comment such as "Don't worry, this is a nearby evacuation site." may be added.

[0296] This is the specific processing flow of the "AI-Disaster Guide" system, which combines an emotion engine that recognizes the user's emotions. The system aims to provide fast and accurate information in the event of a disaster, reducing user anxiety and confusion.

[0297] Example 2

[0298] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0299] During a disaster, it is difficult for users to obtain the information they need quickly and accurately, and confusion and anxiety increase, especially in unfamiliar areas or places where different languages ​​are spoken. Providing disaster information in multiple languages ​​and recognizing the user's emotional state and responding appropriately are also challenges.

[0300] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0301] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with a user in an interactive format, means for analyzing the user's emotional state, and means for adjusting response content based on the user's emotional state. This allows the server to provide disaster information quickly and accurately, enabling users to take evacuation action with peace of mind.

[0302] "Means for receiving emergency emails" refers to a function for receiving alerts and notifications sent via a communication network in the event of a disaster or serious emergency.

[0303] "Means for obtaining location information" refers to a function for obtaining the user's current location in the form of latitude and longitude using technologies such as GPS and Wi-Fi.

[0304] The "means for searching for evacuation site information" is a function for identifying the nearest evacuation site based on the user's current location. This identification includes referencing databases of local governments and administrative agencies.

[0305] "Means for summarizing and translating information using generative AI" is a function that uses a generative AI model to concisely summarize collected disaster information and translate it into a language that the user can understand.

[0306] "Means for interactively exchanging information with the user" refers to a function that allows the user to input questions or instructions through an interface such as a chat box or voice assistant, and the system then responds to them.

[0307] "Means for analyzing the user's emotional state" is a function for analyzing emotions such as anxiety, relief, and confusion from the user's voice and text in real time.

[0308] The "means for adjusting the response content based on the user's emotional state" is a function for appropriately changing the system's response content depending on the user's emotional state. For example, if a user is feeling anxious, a comment that gives a sense of security may be added.

[0309] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. The system combines functions such as receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using generative AI, exchanging information with users in a dialogue format, and an emotion engine that recognizes the user's emotions.

[0310] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The specific hardware used is a smartphone or tablet. The device also obtains the language information set by the user from the device's settings. The device receives an emergency alert email via the mobile network and analyzes its contents. The software used is a location information service or email client.

[0311] The device sends the acquired location information and emergency alert email information to the server. The transmitted data includes latitude, longitude, language setting, and the content of the emergency alert. The server uses the received location information to search for the nearest evacuation site from the local government's database. This is done using a Web API.

[0312] The server collects the latest disaster news and information from news APIs and social media feeds. It then uses a generative AI to summarize this information and translate it into the user's language. The generative AI uses models such as GPT-3. The translated information is then presented in a format that is easy for the user to understand.

[0313] The device runs an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotional state from their voice and text using voice recognition software and natural language processing tools.

[0314] The device displays a chat box-style interface to the user. Through this interface, the user can ask questions about evacuation sites and disaster information. For example, if the user types, "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server. The server uses a generative AI to instantly respond to the user's question. The generative AI also adjusts the response based on the user's emotional state.

[0315] Specific examples

[0316] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0317] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0318] 2. The device sends its location information around Tokyo Station to the server.

[0319] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0320] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0321] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0322] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0323] 7. The emotion engine detects the user's anxiety and adds comments such as, "Don't worry, there is a shelter near your current location."

[0324] Prompt Sentence Examples

[0325] "Please tell me the nearest evacuation site from my current location."

[0326] "Please summarize the latest earthquake information and translate it into English."

[0327] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0328] Step 1:

[0329] The device uses its GPS function to obtain the user's current location. The input is location information obtained from the user's device, and the output is current location information expressed in latitude and longitude format. Specifically, the device collects GPS signals while displaying a progress bar such as "obtaining current location."

[0330] Step 2:

[0331] The device receives an emergency alert email. The input is the emergency alert email sent over the mobile network, and the output is the parsed content of the email. Specifically, the device displays a notification in the notification bar, such as "Earthquake alert. The epicenter is Higashi Ward."

[0332] Step 3:

[0333] The device sends the acquired location information and the contents of the emergency alert email to the server. The input is the latitude and longitude location information and the contents of the emergency alert email, and the output is a data packet containing this information. Specifically, the device displays "Sending data..." in the status bar.

[0334] Step 4:

[0335] The server searches the local government's database for the nearest evacuation site based on the received location information. The input is the user's location information, and the output is detailed information such as the name, address, contact information, and map link of the evacuation site. Specifically, the server records "Searching for evacuation site..." in the log and calls the API of the local government's database to perform the search.

[0336] Step 5:

[0337] The server collects the latest disaster news and information from news APIs and social media feeds. The input is raw data obtained from news APIs and social media feeds, and the output is a collection of collected disaster news. Specifically, the server records "Collecting disaster news..." in the log.

[0338] Step 6:

[0339] The server uses a generative AI to summarize the collected disaster news and translate it into the language set by the user. The input is a collection of collected disaster news and the user's language setting, and the output is a translated summary in a format that is easy for the user to understand. Specifically, the server inputs a prompt to the generative AI model saying, "Please summarize the latest earthquake information and translate it into English."

[0340] Step 7:

[0341] The device runs an emotion engine to recognize the user's emotional state in real time. The input is the user's voice or text, and the output is the analyzed emotional state (e.g., anxious, relieved, confused, etc.). Specifically, the device displays "Analyzing emotions..." in the status bar.

[0342] Step 8:

[0343] The terminal displays a chat box-style interface to the user and sends the user's question to the server. The input is the user's question, and the output is a data packet sent to the server. Specifically, when the user types "Where is the nearest evacuation site?", the terminal analyzes the question and sends it to the server.

[0344] Step 9:

[0345] The server uses the generation AI to respond to the user's question and send it back to the device. The input is the user's question and a prompt to the generation AI, and the output is the generated answer. Specifically, the generation AI model receives a prompt saying, "Please tell me the nearest evacuation site from my current location," and generates a response saying, "The nearest evacuation site is Hibiya Park, 100 meters away."

[0346] Step 10:

[0347] The device displays the response from the server based on the user's emotional state. The input is the information returned from the server and the analysis results of the emotion engine, and the output is the adjusted response. Specifically, if the emotion engine detects the user's anxiety, it adds a comment such as "Don't worry, this is a shelter near your current location" and displays it.

[0348] (Application example 2)

[0349] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0350] The purpose of this invention is to provide rapid and accurate information in the event of a disaster. In particular, it aims to provide a system that can receive emergency alerts and acquire location information, search for evacuation shelter information, summarize and translate information using artificial intelligence, provide information in a dialogue format with the user, and analyze the user's emotions to enable appropriate responses according to the user's situation.

[0351] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving emergency alerts, means for acquiring location information, means for searching for evacuation shelter information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with the user in an interactive format, means for analyzing the user's emotions, and means for adjusting the response content based on the emotions. This allows the user to quickly and accurately obtain the information they need in the event of a disaster, reduce anxiety and confusion, and enable them to take safe evacuation action.

[0352] Definition of Terms

[0353] The "means for receiving emergency alerts" refers to communication devices and software for receiving alerts sent in the event of a disaster or emergency.

[0354] "Means for obtaining location information" refers to technology that obtains location data using a geographic information system (GIS) or a global positioning system (GPS) to identify the user's current location.

[0355] The "means for searching for evacuation shelter information" is a function that searches a database for the nearest evacuation shelter for the user based on the acquired location information.

[0356] "Means for summarizing and translating information using generative artificial intelligence" is a technology that uses generative AI to concisely summarize large amounts of disaster information and translate it into a form that is easy for users to understand.

[0357] "Means for exchanging information interactively with a user" refers to an interface and processing technology in which a user inputs questions or instructions and the system responds interactively to them.

[0358] "Means for analyzing user emotions" refers to technology that analyzes text and voice data entered by a user and determines their emotional state (e.g., anxiety, relief, confusion, etc.).

[0359] "Means for adjusting response content based on emotions" refers to a technology that adjusts the response content so that the generating AI provides an appropriate response according to the analyzed emotional state of the user.

[0360] MODE FOR CARRYING OUT THE INVENTION

[0361] System Overview

[0362] This invention provides an "AI-Disaster Guide" system for providing fast and accurate information during disasters. This system combines functions such as receiving emergency alerts, acquiring location information, searching for evacuation shelter information, summarizing and translating information using generative artificial intelligence (AI), exchanging information interactively with the user, and analyzing the user's emotions to adjust responses.

[0363] Hardware and Software Description

[0364] This system is realized mainly by the following hardware and software:

[0365] Smartphone: Used as a user interface and a computing resource.

[0366] GPS function: Used to obtain the user's location information.

[0367] Mobile network: Used to receive emergency alerts and communicate with the server.

[0368] Server: Processes disaster information, searches for evacuation shelter information, summarizes and translates information, and performs sentiment analysis.

[0369] Generative AI models: Used to summarize and translate text data.

[0370] Emotion engine: Used to analyze emotions from user voice and text.

[0371] Chat box format: An interface for interacting with the user.

[0372] System Operation

[0373] Initial Setup

[0374] When a user starts up a smartphone with the application installed, the current location information is obtained using the GPS function. When an emergency alert is received via the mobile network, the content is analyzed and disaster information is sent to the server.

[0375] Information search and provision

[0376] The server searches the local government's database for information on the nearest evacuation shelter based on the location information and emergency alerts received from the user. The obtained evacuation shelter information (shelter name, address, contact information, map link, etc.) is sent to the user's smartphone and displayed on a chat box-style interface.

[0377] Summary and translation of information

[0378] The server collects the latest disaster information from news APIs and social media feeds, summarizes and translates this information using a generative AI model, and provides the translation results in a format that is easy for users to understand.

[0379] Sentiment analysis and conversational responses

[0380] Sentiment analysis is performed on the user's input (voice or text), and responses are tailored based on the user's emotional state. For example, if the user is feeling anxious, a reassuring comment is added to the response.

[0381] Specific examples

[0382] Here are some examples and prompts:

[0383] Example 1: A traveler experiences an earthquake

[0384] 1. The user starts up the smartphone and their current location information (e.g., near the station) is obtained.

[0385] 2. The server searches for evacuation shelter information and provides the user with the nearest evacuation shelter.

[0386] 3. Using a generative AI model, the disaster information is translated into the user's language (e.g., English) and the route to the evacuation shelter is displayed.

[0387] Recommended prompts

[0388] "Summarize and translate the following text to Japanese: Earthquake warning in Tokyo. Seek immediate shelter."

[0389] In this way, we can realize a system that allows users to quickly and accurately obtain the information they need in the event of a disaster. Furthermore, the emotion analysis and response adjustment functions can reduce users' anxiety and confusion and support safe evacuation behavior.

[0390] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0391] Program processing flow

[0392] Step 1:

[0393] The device is started up and the user's current location is obtained using the GPS function. The input is the device's GPS data, and the output is the latitude and longitude location information. This location information is used for subsequent processing.

[0394] Step 2:

[0395] The device receives emergency alerts via mobile communications. The input is an emergency alert email received via the mobile network, and the output is the content of the received emergency alert. The device analyzes this content and identifies the type of disaster and its urgency.

[0396] Step 3:

[0397] The device transmits the acquired current location information and the contents of the emergency alert to the server. The transmitted data includes the user's latitude and longitude, language settings, and the contents of the emergency alert. The input is the data obtained in steps 1 and 2, and the output is the data transmitted to the server.

[0398] Step 4:

[0399] Based on the location information received by the server, the server searches for the nearest evacuation shelter from the local government database. The input is the location information and emergency alert content sent to the server, and the output is information about the nearest evacuation shelter (shelter name, address, contact information, map link, etc.).

[0400] Step 5:

[0401] The server collects the latest disaster information from news APIs and SNS feeds. The input is feed data from each news API or SNS feed, and the output is the collected latest disaster information.

[0402] Step 6:

[0403] The server uses the generative AI model to summarize the collected disaster information and translate it into the user's preferred language. The input is the disaster information collected in step 5 and the user's preferred language, and the output is the summarized and translated disaster information.

[0404] Step 7:

[0405] The device receives the user's voice or text input and analyzes the emotional state using an emotion engine. The input is the user's voice or text data, and the output is the analyzed emotional state (e.g., anxiety, relief, confusion, etc.).

[0406] Step 8:

[0407] The server uses a generative AI model to generate an answer based on the user's question and further adjusts the response according to the user's emotional state. The input is the analyzed emotional state and the user's question, and the output is the adjusted response. As a specific example, in response to the user's question, "Where are the evacuation shelters?", information about the nearest evacuation shelters is provided, and a reassuring response such as "Don't worry, you can evacuate safely" is added.

[0408] Step 9:

[0409] The terminal displays the evacuation shelter information and responses received from the server to the user through a chat box-style interface. The input is the data sent from the server in step 8, and the output is the information displayed on the terminal's display. The user can take safe evacuation actions based on this information.

[0410] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0411] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0412] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0413] [Second embodiment]

[0414] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0415] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0416] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0417] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0418] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0419] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0420] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0421] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0422] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0423] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0424] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0425] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0426] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. This system combines functions for receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using AI generation, and exchanging information interactively with users.

[0427] Program processing explanation

[0428] 1. Information gathering stage

[0429] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The device also obtains the language information set by the user from the device's settings. The device then receives an emergency alert email via the mobile network and analyzes its contents.

[0430] 2. Identifying evacuation sites

[0431] The device sends the acquired location information to a server, which then uses this information to search for the nearest evacuation shelter in the local government's database. The search results include details such as the shelter's name, address, contact information, and a map link.

[0432] 3. Disaster Information Summary and Translation

[0433] The server collects the latest disaster news and social media information. This information is obtained from news APIs and social media feeds. It then uses generative AI to summarize this information and translate it into the user's language of choice. The translated information is then presented in a format that is easy for the user to understand.

[0434] 4. Interactive Response

[0435] The device displays a chat box-style interface to the user, allowing the user to ask questions about evacuation sites and disaster information. For example, if the user types "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server.

[0436] The server uses a generation AI to instantly respond to the user's questions, providing specific information such as, "The nearest evacuation site from your current location is Hibiya Park, 100 meters away." The generation AI also flexibly responds to the user's additional questions, providing a sense of security.

[0437] Specific examples

[0438] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0439] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0440] 2. The device sends its location information around Tokyo Station to the server.

[0441] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0442] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0443] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0444] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0445] Example 2: When the overseas trainee does not understand the content of the warning

[0446] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[0447] 2. The device sends the contents of the received emergency alert email to the server.

[0448] 3. The server uses the generation AI to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[0449] 4. The generating AI returns the translation results to the device and notifies the user of the alert content.

[0450] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[0451] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using generation AI.

[0452] In this way, the system of the present invention enables users to quickly and accurately receive necessary disaster information and evacuation instructions in an emergency. Specific information is provided according to the user's current location and language, reducing anxiety during a disaster and enabling safe evacuation.

[0453] The processing flow will be explained below.

[0454] Step 1:

[0455] The device acquires the user's current location using the GPS function. Specifically, it collects latitude and longitude information through the built-in GPS module of the smartphone or tablet.

[0456] Step 2:

[0457] The device acquires the user's language setting information. Specifically, it checks the display language selected by the user (e.g., Japanese, English, Spanish, etc.) from the device's system settings.

[0458] Step 3:

[0459] The device receives emergency alert emails via the mobile network and analyzes the content of the email to determine the type of disaster and its urgency.

[0460] Step 4:

[0461] The device sends the acquired location information and emergency alert email information to the server. The sent data includes latitude, longitude, language setting, and the content of the emergency alert.

[0462] Step 5:

[0463] The server uses the received location information to search for the nearest evacuation site in the local government's database, which contains information such as the name, address, contact information, and capacity of each evacuation site.

[0464] Step 6:

[0465] The server passes the evacuation site information to the AI ​​generator and has it translate it into a language the user can understand. For example, Japanese evacuation site information can be translated into English, Spanish, etc.

[0466] Step 7:

[0467] The server collects the latest disaster news and social media information from the internet, summarizes the collected information using generative AI, and translates it into the language specified by the user.

[0468] Step 8:

[0469] The server sends evacuation site information and summarized / translated disaster information to the terminal.

[0470] Step 9:

[0471] The device displays a chat interface to the user, providing information on evacuation sites and disasters in an interactive format and answering any additional questions.

[0472] Step 10:

[0473] Users input questions about evacuation shelters and disaster information through the chat interface, such as "Where is the nearest evacuation shelter?" and "What items should I bring to the evacuation shelter?"

[0474] Step 11:

[0475] The terminal analyzes the user's question and sends an appropriate request to the server.

[0476] Step 12:

[0477] The server uses generative AI to instantly respond to user questions, providing specific information such as, "The nearest evacuation site is Hibiya Park, 100 meters away."

[0478] Step 13:

[0479] The terminal displays the response received from the server to the user, who can then take appropriate action based on the information provided.

[0480] The above is the specific processing flow of the "AI-Disaster Guide" system, which enables users to quickly and accurately receive the disaster information and evacuation instructions they need in an emergency.

[0481] Example 1

[0482] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0483] In recent years, natural disasters have become more frequent, creating a need for rapid and accurate information provision in the event of a disaster. However, issues remain, such as a lack of multilingual support and difficulty in identifying evacuation sites based on the user's current location. Furthermore, there are cases where the content of emergency alert emails is difficult to understand, and appropriate evacuation sites are unknown. A system is needed to resolve these issues and streamline the provision of disaster information.

[0484] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0485] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using a generative AI model, means for interactively exchanging information with a user, means for analyzing the content of the emergency alert emails, means for searching for the nearest evacuation site from a local government database, means for collecting news and SNS information, and means for providing a user interface. This allows users to quickly and accurately receive the information they need in the event of a disaster, improving the efficiency of emergency responses.

[0486] The "means for receiving emergency alert emails" is a function that enables a terminal to receive emergency alert emails that are sent when a disaster occurs.

[0487] "Means for acquiring location information" refers to a function for acquiring the latitude and longitude of the user's current location using a GPS function or the like.

[0488] The "means for searching for evacuation site information" is a function for searching for the nearest evacuation site based on the acquired location information.

[0489] "Means for summarizing and translating information using generative AI models" refers to the function of summarizing and translating collected disaster information into multiple languages ​​using generative AI technology.

[0490] The "means for exchanging information interactively with the user" is a function that allows the user to ask questions and respond using a chat box-style interface.

[0491] The "means for analyzing the contents of the emergency alert email" is a function for analyzing the contents of the received emergency alert email and extracting information necessary for the user.

[0492] "Means to search for the nearest evacuation site from the local government's database" is a function that searches for the nearest evacuation site based on location information from a database managed by the local government.

[0493] "Means of collecting news and social media information" refers to a function for collecting information from the latest disaster news and social media.

[0494] The "means for providing a user interface" is a function that provides an interface for users to check disaster information and ask and answer questions.

[0495] This invention is a system for providing users with fast and accurate information in the event of a disaster. This system combines functions for receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using a generative AI model, and exchanging information interactively with users.

[0496] Hardware and Software Configuration

[0497] Terminal

[0498] The devices are mobile communication devices such as smartphones and tablets. These devices have the following features:

[0499] GPS function: Obtain the user's current location

[0500] Mobile network: Receive emergency alert emails

[0501] User interface: Interact with the user in a chat box format

[0502] server

[0503] The server has the following features:

[0504] News API and SNS feed aggregation tool: Obtain the latest disaster news and SNS information

[0505] Database: Manages and provides information on evacuation sites for local governments

[0506] Generative AI models: Summarize collected information and translate it into a language the user can understand

[0507] What the program does

[0508] 1. Information gathering

[0509] The device first obtains the user's location information using its GPS function. For example, it obtains latitude and longitude information using the Google Maps API. It also reads the language information set by the user from the device's settings menu. Next, it receives an emergency alert email via the mobile network and analyzes its contents using a text analysis tool.

[0510] 2. Identifying evacuation sites

[0511] The device sends the acquired location information to the server via an HTTP request. The server searches the database for the nearest evacuation site based on the location information and returns the results to the device, allowing the device to show the nearest evacuation site to the user.

[0512] 3. Disaster Information Summary and Translation

[0513] The server collects the latest disaster news from news APIs (e.g., Google News API) and social media feeds. This information is summarized and translated using a generative AI model (e.g., OpenAI's GPT-3 or GPT-4). The translated information is then sent to the device and provided to the user.

[0514] 4. Interactive Response

[0515] The device provides the user with a chat box-style interface, implemented, for example, using React Native. The user enters a question through the chat box, which the device analyzes and sends to the server. The server uses a generative AI model to instantly respond to the user's question, which is then returned to the device and displayed to the user.

[0516] Specific examples

[0517] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0518] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0519] 2. The device sends its location information around Tokyo Station to the server.

[0520] 3. The server uses the generative AI model to search for information about the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0521] 4. The generative AI model translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0522] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0523] 6. The generative AI model responds, "Shelters need drinking water, emergency food, phone chargers, medicine, etc."

[0524] Example 2: When the overseas trainee does not understand the content of the warning

[0525] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[0526] 2. The device sends the contents of the received emergency alert email to the server.

[0527] 3. The server uses the generative AI model to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[0528] 4. The generative AI model returns the translation results to the device and notifies the user of the alert content.

[0529] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[0530] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using a generative AI model.

[0531] In this way, the system of the present invention provides necessary information quickly and accurately in the event of a disaster, thereby ensuring the safety of users.

[0532] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0533] Step 1:

[0534] The device first obtains the user's current location using its GPS function. It uses data from the GPS sensor as input and outputs location information in the form of latitude and longitude. Specific examples include obtaining location information using the Google Maps API.

[0535] Step 2:

[0536] The device reads the language information set by the user from the device's settings menu. It uses the device's locale setting data as input and outputs the set language information. This obtains the user's language setting (e.g., Japanese, English, etc.).

[0537] Step 3:

[0538] The device receives emergency alert emails via the mobile network. It analyzes the received email data as input and outputs important disaster information (e.g., type of disaster, location, response methods, etc.). Specifically, it uses natural language processing (NLP) technology to perform text analysis.

[0539] Step 4:

[0540] The device sends its location information (latitude and longitude) to the server through an HTTP request. The server uses the location data obtained as input and provides the location information as output. This request is sent to identify the required evacuation location.

[0541] Step 5:

[0542] The server searches for the nearest evacuation site from the local government's database based on the location information. Using the location information data received as input, it outputs detailed information such as the name, address, contact information, and map link of the evacuation site. Specific operations use a database management system such as PostgreSQL.

[0543] Step 6:

[0544] The server sends the search results in JSON format to the device. It uses the organized evacuation location information as input and provides detailed information of evacuation locations to the device as output. This information can be used by the user to quickly find the nearest evacuation location.

[0545] Step 7:

[0546] The server collects the latest disaster news and social media information from news APIs and social media feeds. It uses information obtained from various APIs as input and outputs the collected disaster information. Specific operations include using the Google News API and Twitter API.

[0547] Step 8:

[0548] The server uses a generative AI model to summarize the collected disaster information and translate it into the language set by the user. It uses collected news and social media information and the user's language setting as input, and outputs the summarized and translated information. Specific examples use OpenAI's GPT-3 and GPT-4 and the Google Translate API.

[0549] Step 9:

[0550] The server sends the translated summary information to the terminal in JSON format. It uses the translated information data as input and provides the information to the terminal as output. This information is displayed in a format that is easy for the user to understand.

[0551] Step 10:

[0552] The terminal displays a chat box-style interface to the user. It uses user interface configuration information as input and provides the interface as output. Specifically, the interface is constructed using React Native.

[0553] Step 11:

[0554] The user inputs questions about evacuation sites and disaster information through the chat box. The user's text input data is used as input, and this is sent to the terminal. A specific example includes the action of inputting "Where is the nearest evacuation site?"

[0555] Step 12:

[0556] The device analyzes the user's question and sends it to the server. It uses the user's text data as input and analyzes it using natural language processing (NLP). It provides the analysis results to the server as output.

[0557] Step 13:

[0558] The server uses a generative AI model to instantly respond to user questions. It uses the analyzed question data as input and outputs a specific response. For example, if a user asks about the nearest evacuation site, it provides that information.

[0559] Step 14:

[0560] The server uses the generative AI model to generate a response and sends it to the terminal in JSON format. The generated response data is used as input and provided to the terminal as output. This information is displayed in a user-friendly format.

[0561] Step 15:

[0562] The terminal displays the response result in a chat box and provides it to the user. The received response data is used as input and displayed on the user's interface as output. A specific example includes the action of displaying "The nearest evacuation site from your current location is 100 meters away."

[0563] (Application example 1)

[0564] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0565] In the event of a disaster, it is extremely important to obtain accurate information quickly and respond appropriately. However, if information is not provided in multiple languages, it becomes difficult to provide effective information to users who have language barriers, such as foreigners. Furthermore, when there is a huge amount of information, it is difficult to quickly summarize and translate each piece of information and provide it in a form that users can understand. Furthermore, when users ask specific questions on the spot, it is difficult to obtain accurate answers in real time. A new system is needed to solve these issues.

[0566] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0567] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with a user in an interactive format, means for summarizing emergency alerts using a generative model, and means for providing real-time responses to user questions in multiple languages. This enables the rapid and accurate provision of information in the event of a disaster, particularly by enhancing multilingual support and responses to real-time user questions, thereby enabling support for users to take appropriate action.

[0568] "Means for receiving emergency emails" refers to a communication system for notifying user terminals of information about disasters and emergencies.

[0569] "Means for obtaining location information" refers to a system that uses GPS or other location-determining technology to obtain a user's current location in the form of latitude and longitude.

[0570] "Means for searching for evacuation site information" refers to a system that identifies the nearest evacuation site based on the user's current location information and provides that information.

[0571] "Means for summarizing and translating information using generative artificial intelligence" refers to a system that uses a generative AI model to concisely summarize collected disaster information and translate it into language that users can understand.

[0572] "Means for interactively exchanging information with the user" refers to a system that uses an interface such as a chat box or voice recognition to respond to questions from the user in an interactive manner.

[0573] "Means for summarizing emergency alerts using a generative model" refers to a system that uses a generative AI model to concisely summarize the contents of emergency alert emails.

[0574] "Means for providing real-time responses to user questions in multiple languages" refers to a system that uses generative AI models and natural language processing technology to provide real-time answers to questions asked by users in multiple languages.

[0575] This invention was developed to implement a "Disaster Countermeasure Security Guide" system that provides prompt and accurate information in the event of a disaster. This system is implemented on devices such as smartphones and smart glasses, and provides the following specific functions:

[0576] 1. Receiving emergency alert emails

[0577] The terminal receives emergency alert emails about disasters and emergencies via the communication network, allowing users to obtain important information in real time.

[0578] 2. Obtaining location information

[0579] The device uses the GPS function to obtain the user's current location. The current location information is obtained in the form of latitude and longitude and sent to the server. This allows the user to know exactly where they are.

[0580] 3. Search for evacuation shelter information

[0581] The server searches the local government's database for the nearest evacuation site based on the user's location information. The search results include the name, address, and map link of the evacuation site, and this information is provided to the user.

[0582] 4. Summary and Translation of Information

[0583] The server collects emergency alerts and the latest disaster information and summarizes the information using a generative AI model. Furthermore, to support multiple languages, the summarized information is translated into the language selected by the user. This allows users, such as foreigners, who face language barriers, to understand accurate information.

[0584] 5. Interactive information provision

[0585] The device provides a chat box-style interface and responds to user questions in real time. The server uses a generative AI model to generate appropriate answers to the user's questions and provides them in multiple languages. For example, in response to the question, "Where is the nearest evacuation site?", it provides specific information such as, "The nearest evacuation site is a park 100 meters away."

[0586] Hardware and software used

[0587] Hardware: Smartphones, smart glasses

[0588] software:

[0589] Geopy: a location processing library

[0590] Transformers: A natural language processing library

[0591] OpenAI GPT-3: Generative AI model

[0592] Specific examples

[0593] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0594] 1. The user starts up the device and obtains the current location information (latitude: 35.6895, longitude: 139.6917).

[0595] 2. The device sends the location information to the server.

[0596] 3. The server uses the generation AI to search for information on the nearest evacuation site and provide it to the user.

[0597] 4. The generating AI translates the information into the language set by the user (English) and shows the route to the evacuation site.

[0598] 5. The user asks in the chat box, "What do you need for evacuation shelters?"

[0599] 6. The generated AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0600] Prompt Sentence Examples

[0601] "Please summarize: Emergency alert: Earthquake has occurred. Evacuate immediately."

[0602] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0603] Step 1:

[0604] The terminal receives an emergency alert email. The input is the emergency alert email sent over a communication network, and the terminal receives the email content as a message. The output is the text information of the received emergency alert email. This text information is used in the next step.

[0605] Step 2:

[0606] The device obtains location information. The input is a process that obtains the current latitude and longitude through the GPS function. The output is the numerical data of the latitude and longitude corresponding to the user's current location. This numerical data is used in the next step.

[0607] Step 3:

[0608] The server searches for evacuation shelters based on location information. The input is the latitude and longitude of the current location obtained in step 2, and references the evacuation shelter database. The output is information about the evacuation shelter closest to the current location (name, address, contact information, map link, etc.). This information is used in the next step.

[0609] Step 4:

[0610] The server uses a generative AI model to summarize the content of the emergency alert email. The input is the text information of the emergency alert email received in step 1, which is provided to the generative AI model as a prompt. The output is the summary text of the emergency alert email. This summary text is used in the next step.

[0611] Step 5:

[0612] The server uses a generative AI model to translate the summarized disaster information. The input is the summary text obtained in step 4 and the language information set by the user. The output is the text translated from the summary text into the specified language. This translated text is used in the next step.

[0613] Step 6:

[0614] The terminal exchanges information with the user in a dialogue format. The input is a question text from the user (e.g., "Where is the nearest evacuation site?"). The output is a response text from the server, which is displayed in a format that the user can view in a chat box.

[0615] Step 7:

[0616] The server uses a generative AI model to respond to user questions. The input is the question text sent by the user via the terminal, and the generative AI model analyzes the question. The output is a specific and accurate response text to the question. This response text is sent to the terminal and provided to the user.

[0617] Specific actions

[0618] 1. Obtaining location information: The GPS module is used to obtain latitude and longitude, and this is sent to the server along with the contents of the emergency alert email.

[0619] 2. Search for evacuation shelters: The server accesses the local government database to identify the nearest evacuation shelter from the user's current location. It also translates the information into the user's language.

[0620] 3. Information Summarization: Using a generative AI model (e.g., OpenAI GPT-3), a concise summary of the received emergency alert email is created. This summary is sent as a prompt to the generative AI model in the next step.

[0621] 4. Multilingual translation: Using a translation model (e.g., MarianMT model), summarizes information and outputs it in multiple languages.

[0622] 5. Conversational information provision: Users can ask questions via a chat box, and the generative AI will provide an appropriate response based on the question.

[0623] Prompt Sentence Examples

[0624] "Please summarize: Emergency alert: Earthquake has occurred. Evacuate immediately."

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

[0626] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. This system combines functions such as receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using generative AI, exchanging information with users in a dialogue format, and an emotion engine that recognizes the user's emotions.

[0627] Program processing explanation

[0628] 1. Information gathering stage

[0629] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The device also obtains the language information set by the user from the device's settings. The device then receives an emergency alert email via the mobile network and analyzes its contents.

[0630] 2. Identifying evacuation sites

[0631] The device sends the acquired location information and emergency alert email information to the server. The sent data includes latitude, longitude, language setting, and the content of the emergency alert.

[0632] The server uses the received location information to search the local government's database for the nearest evacuation shelter, and the search results include details such as the shelter's name, address, contact information, and a map link.

[0633] 3. Disaster Information Summary and Translation

[0634] The server collects the latest disaster news and social media information. This information is obtained from news APIs and social media feeds. It then uses generative AI to summarize this information and translate it into the user's language of choice. The translated information is then presented in a format that is easy for the user to understand.

[0635] 4. Introducing the Emotion Engine

[0636] The device runs an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotional state (e.g., anxiety, relief, confusion, etc.) from their voice and text.

[0637] 5. Interactive Response

[0638] The device displays a chat box-style interface to the user, allowing the user to ask questions about evacuation sites and disaster information. For example, if the user types "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server.

[0639] The server uses a generation AI to instantly respond to the user's questions. For example, it provides specific information such as, "The nearest evacuation site from your current location is Hibiya Park, 100 meters away." The generation AI also adjusts the response based on the user's emotional state. For example, if the user is feeling anxious, it adds a reassuring comment.

[0640] Specific examples

[0641] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0642] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0643] 2. The device sends its location information around Tokyo Station to the server.

[0644] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0645] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0646] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0647] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0648] 7. The emotion engine detects the user's anxiety and adds comments such as, "Don't worry, there is a shelter near your current location."

[0649] Example 2: When the overseas trainee does not understand the content of the warning

[0650] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[0651] 2. The device sends the contents of the received emergency alert email to the server.

[0652] 3. The server uses the generation AI to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[0653] 4. The generating AI returns the translation results to the device and notifies the user of the alert content.

[0654] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[0655] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using generation AI.

[0656] 7. The emotion engine detects the user's confusion and adds a comment such as, "Don't worry, we'll give you detailed directions to the evacuation shelter."

[0657] In this way, the system of the present invention allows users to quickly and accurately receive necessary disaster information and evacuation instructions in an emergency. Furthermore, by recognizing the user's emotions in real time and responding appropriately according to their emotional state, anxiety and confusion during a disaster can be reduced. Specific information is provided according to the user's current location and language, allowing them to take safe evacuation action.

[0658] The processing flow will be explained below.

[0659] Step 1:

[0660] The device acquires the user's current location using the GPS function. Specifically, it collects latitude and longitude information using the built-in GPS module of the smartphone or tablet.

[0661] Step 2:

[0662] The terminal acquires the user's language setting information. Specifically, the terminal checks the display language selected by the user (e.g., Japanese, English, Spanish, etc.) from the terminal's system settings.

[0663] Step 3:

[0664] The device receives emergency alert emails via the mobile network, analyzes the content of the emails, and determines the type of disaster and its urgency.

[0665] Step 4:

[0666] The device sends the acquired location information and emergency alert email information to the server. The transmitted data includes latitude, longitude, language setting, and the content of the emergency alert email.

[0667] Step 5:

[0668] The server uses the received location information to search for the nearest evacuation site in the local government's database, which contains information such as the name, address, contact information, and capacity of each evacuation site.

[0669] Step 6:

[0670] The server passes the evacuation site information to the AI ​​generator and has it translate it into a language the user can understand. For example, Japanese evacuation site information can be translated into English, Spanish, etc.

[0671] Step 7:

[0672] The server collects the latest disaster news and social media information from the internet, summarizes the collected information using generative AI, and translates it into the language specified by the user.

[0673] Step 8:

[0674] The server sends summarized and translated disaster information and evacuation shelter information to the terminal, including evacuation shelter routes and important disaster news.

[0675] Step 9:

[0676] The device displays a chat interface to the user, through which the user can ask questions about evacuation sites and disaster information.

[0677] Step 10:

[0678] The device runs an emotion engine to recognize emotions from the user's voice and text. The emotion engine analyzes the tone of the voice and keywords in the text to identify the user's emotional state (e.g., anxiety, relief, confusion, etc.).

[0679] Step 11:

[0680] Users can input questions about evacuation shelters and disaster information through the chat interface, such as "Where is the nearest evacuation shelter?" and "What items should I bring to the evacuation shelter?"

[0681] Step 12:

[0682] The device analyzes the input question and sends an appropriate request to the server. The transmitted data includes the user's question and the emotion analysis results of the emotion engine.

[0683] Step 13:

[0684] The server uses generative AI to instantly respond to the user's questions, generating information such as "The nearest evacuation site from your current location is Hibiya Park, 100 meters away," and adding additional comments based on the user's emotional state.

[0685] Step 14:

[0686] The device displays the response received from the server to the user. To reassure the user, a comment such as "Don't worry, this is a nearby evacuation site." may be added.

[0687] This is the specific processing flow of the "AI-Disaster Guide" system, which combines an emotion engine that recognizes the user's emotions. The system aims to provide fast and accurate information in the event of a disaster, reducing user anxiety and confusion.

[0688] Example 2

[0689] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0690] During a disaster, it is difficult for users to obtain the information they need quickly and accurately, and confusion and anxiety increase, especially in unfamiliar areas or places where different languages ​​are spoken. Providing disaster information in multiple languages ​​and recognizing the user's emotional state and responding appropriately are also challenges.

[0691] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0692] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with a user in an interactive format, means for analyzing the user's emotional state, and means for adjusting response content based on the user's emotional state. This allows the server to provide disaster information quickly and accurately, enabling users to take evacuation action with peace of mind.

[0693] "Means for receiving emergency emails" refers to a function for receiving alerts and notifications sent via a communication network in the event of a disaster or serious emergency.

[0694] "Means for obtaining location information" refers to a function for obtaining the user's current location in the form of latitude and longitude using technologies such as GPS and Wi-Fi.

[0695] The "means for searching for evacuation site information" is a function for identifying the nearest evacuation site based on the user's current location. This identification includes referencing databases of local governments and administrative agencies.

[0696] "Means for summarizing and translating information using generative AI" is a function that uses a generative AI model to concisely summarize collected disaster information and translate it into a language that the user can understand.

[0697] "Means for interactively exchanging information with the user" refers to a function that allows the user to input questions or instructions through an interface such as a chat box or voice assistant, and the system then responds to them.

[0698] "Means for analyzing the user's emotional state" is a function for analyzing emotions such as anxiety, relief, and confusion from the user's voice and text in real time.

[0699] The "means for adjusting the response content based on the user's emotional state" is a function for appropriately changing the system's response content depending on the user's emotional state. For example, if a user is feeling anxious, a comment that gives a sense of security may be added.

[0700] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. The system combines functions such as receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using generative AI, exchanging information with users in a dialogue format, and an emotion engine that recognizes the user's emotions.

[0701] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The specific hardware used is a smartphone or tablet. The device also obtains the language information set by the user from the device's settings. The device receives an emergency alert email via the mobile network and analyzes its contents. The software used is a location information service or email client.

[0702] The device sends the acquired location information and emergency alert email information to the server. The transmitted data includes latitude, longitude, language setting, and the content of the emergency alert. The server uses the received location information to search for the nearest evacuation site from the local government's database. This is done using a Web API.

[0703] The server collects the latest disaster news and information from news APIs and social media feeds. It then uses a generative AI to summarize this information and translate it into the user's language. The generative AI uses models such as GPT-3. The translated information is then presented in a format that is easy for the user to understand.

[0704] The device runs an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotional state from their voice and text using voice recognition software and natural language processing tools.

[0705] The device displays a chat box-style interface to the user. Through this interface, the user can ask questions about evacuation sites and disaster information. For example, if the user types, "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server. The server uses a generative AI to instantly respond to the user's question. The generative AI also adjusts the response based on the user's emotional state.

[0706] Specific examples

[0707] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0708] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0709] 2. The device sends its location information around Tokyo Station to the server.

[0710] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0711] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0712] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0713] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0714] 7. The emotion engine detects the user's anxiety and adds comments such as, "Don't worry, there is a shelter near your current location."

[0715] Prompt Sentence Examples

[0716] "Please tell me the nearest evacuation site from my current location."

[0717] "Please summarize the latest earthquake information and translate it into English."

[0718] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0719] Step 1:

[0720] The device uses its GPS function to obtain the user's current location. The input is location information obtained from the user's device, and the output is current location information expressed in latitude and longitude format. Specifically, the device collects GPS signals while displaying a progress bar such as "obtaining current location."

[0721] Step 2:

[0722] The device receives an emergency alert email. The input is the emergency alert email sent over the mobile network, and the output is the parsed content of the email. Specifically, the device displays a notification in the notification bar, such as "Earthquake alert. The epicenter is Higashi Ward."

[0723] Step 3:

[0724] The device sends the acquired location information and the contents of the emergency alert email to the server. The input is the latitude and longitude location information and the contents of the emergency alert email, and the output is a data packet containing this information. Specifically, the device displays "Sending data..." in the status bar.

[0725] Step 4:

[0726] The server searches the local government's database for the nearest evacuation site based on the received location information. The input is the user's location information, and the output is detailed information such as the name, address, contact information, and map link of the evacuation site. Specifically, the server records "Searching for evacuation site..." in the log and calls the API of the local government's database to perform the search.

[0727] Step 5:

[0728] The server collects the latest disaster news and information from news APIs and social media feeds. The input is raw data obtained from news APIs and social media feeds, and the output is a collection of collected disaster news. Specifically, the server records "Collecting disaster news..." in the log.

[0729] Step 6:

[0730] The server uses a generative AI to summarize the collected disaster news and translate it into the language set by the user. The input is a collection of collected disaster news and the user's language setting, and the output is a translated summary in a format that is easy for the user to understand. Specifically, the server inputs a prompt to the generative AI model saying, "Please summarize the latest earthquake information and translate it into English."

[0731] Step 7:

[0732] The device runs an emotion engine to recognize the user's emotional state in real time. The input is the user's voice or text, and the output is the analyzed emotional state (e.g., anxious, relieved, confused, etc.). Specifically, the device displays "Analyzing emotions..." in the status bar.

[0733] Step 8:

[0734] The terminal displays a chat box-style interface to the user and sends the user's question to the server. The input is the user's question, and the output is a data packet sent to the server. Specifically, when the user types "Where is the nearest evacuation site?", the terminal analyzes the question and sends it to the server.

[0735] Step 9:

[0736] The server uses the generation AI to respond to the user's question and send it back to the device. The input is the user's question and a prompt to the generation AI, and the output is the generated answer. Specifically, the generation AI model receives a prompt saying, "Please tell me the nearest evacuation site from my current location," and generates a response saying, "The nearest evacuation site is Hibiya Park, 100 meters away."

[0737] Step 10:

[0738] The device displays the response from the server based on the user's emotional state. The input is the information returned from the server and the analysis results of the emotion engine, and the output is the adjusted response. Specifically, if the emotion engine detects the user's anxiety, it adds a comment such as "Don't worry, this is a shelter near your current location" and displays it.

[0739] (Application example 2)

[0740] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0741] The purpose of this invention is to provide rapid and accurate information in the event of a disaster. In particular, it aims to provide a system that can receive emergency alerts and acquire location information, search for evacuation shelter information, summarize and translate information using artificial intelligence, provide information in a dialogue format with the user, and analyze the user's emotions to enable appropriate responses according to the user's situation.

[0742] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving emergency alerts, means for acquiring location information, means for searching for evacuation shelter information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with the user in an interactive format, means for analyzing the user's emotions, and means for adjusting the response content based on the emotions. This allows the user to quickly and accurately obtain the information they need in the event of a disaster, reduce anxiety and confusion, and enable them to take safe evacuation action.

[0743] Definition of Terms

[0744] The "means for receiving emergency alerts" refers to communication devices and software for receiving alerts sent in the event of a disaster or emergency.

[0745] "Means for obtaining location information" refers to technology that obtains location data using a geographic information system (GIS) or a global positioning system (GPS) to identify the user's current location.

[0746] The "means for searching for evacuation shelter information" is a function that searches a database for the nearest evacuation shelter for the user based on the acquired location information.

[0747] "Means for summarizing and translating information using generative artificial intelligence" is a technology that uses generative AI to concisely summarize large amounts of disaster information and translate it into a form that is easy for users to understand.

[0748] "Means for exchanging information interactively with a user" refers to an interface and processing technology in which a user inputs questions or instructions and the system responds interactively to them.

[0749] "Means for analyzing user emotions" refers to technology that analyzes text and voice data entered by a user and determines their emotional state (e.g., anxiety, relief, confusion, etc.).

[0750] "Means for adjusting response content based on emotions" refers to a technology that adjusts the response content so that the generating AI provides an appropriate response according to the analyzed emotional state of the user.

[0751] MODE FOR CARRYING OUT THE INVENTION

[0752] System Overview

[0753] This invention provides an "AI-Disaster Guide" system for providing fast and accurate information during disasters. This system combines functions such as receiving emergency alerts, acquiring location information, searching for evacuation shelter information, summarizing and translating information using generative artificial intelligence (AI), exchanging information interactively with the user, and analyzing the user's emotions to adjust responses.

[0754] Hardware and Software Description

[0755] This system is realized mainly by the following hardware and software:

[0756] Smartphone: Used as a user interface and a computing resource.

[0757] GPS function: Used to obtain the user's location information.

[0758] Mobile network: Used to receive emergency alerts and communicate with the server.

[0759] Server: Processes disaster information, searches for evacuation shelter information, summarizes and translates information, and performs sentiment analysis.

[0760] Generative AI models: Used to summarize and translate text data.

[0761] Emotion engine: Used to analyze emotions from user voice and text.

[0762] Chat box format: An interface for interacting with the user.

[0763] System Operation

[0764] Initial Setup

[0765] When a user starts up a smartphone with the application installed, the current location information is obtained using the GPS function. When an emergency alert is received via the mobile network, the content is analyzed and disaster information is sent to the server.

[0766] Information search and provision

[0767] The server searches the local government's database for information on the nearest evacuation shelter based on the location information and emergency alerts received from the user. The obtained evacuation shelter information (shelter name, address, contact information, map link, etc.) is sent to the user's smartphone and displayed on a chat box-style interface.

[0768] Summary and translation of information

[0769] The server collects the latest disaster information from news APIs and social media feeds, summarizes and translates this information using a generative AI model, and provides the translation results in a format that is easy for users to understand.

[0770] Sentiment analysis and conversational responses

[0771] Sentiment analysis is performed on the user's input (voice or text), and responses are tailored based on the user's emotional state. For example, if the user is feeling anxious, a reassuring comment is added to the response.

[0772] Specific examples

[0773] Here are some examples and prompts:

[0774] Example 1: A traveler experiences an earthquake

[0775] 1. The user starts up the smartphone and their current location information (e.g., near the station) is obtained.

[0776] 2. The server searches for evacuation shelter information and provides the user with the nearest evacuation shelter.

[0777] 3. Using a generative AI model, the disaster information is translated into the user's language (e.g., English) and the route to the evacuation shelter is displayed.

[0778] Recommended prompts

[0779] "Summarize and translate the following text to Japanese: Earthquake warning in Tokyo. Seek immediate shelter."

[0780] In this way, we can realize a system that allows users to quickly and accurately obtain the information they need in the event of a disaster. Furthermore, the emotion analysis and response adjustment functions can reduce users' anxiety and confusion and support safe evacuation behavior.

[0781] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0782] Program processing flow

[0783] Step 1:

[0784] The device is started up and the user's current location is obtained using the GPS function. The input is the device's GPS data, and the output is the latitude and longitude location information. This location information is used for subsequent processing.

[0785] Step 2:

[0786] The device receives emergency alerts via mobile communications. The input is an emergency alert email received via the mobile network, and the output is the content of the received emergency alert. The device analyzes this content and identifies the type of disaster and its urgency.

[0787] Step 3:

[0788] The device transmits the acquired current location information and the contents of the emergency alert to the server. The transmitted data includes the user's latitude and longitude, language settings, and the contents of the emergency alert. The input is the data obtained in steps 1 and 2, and the output is the data transmitted to the server.

[0789] Step 4:

[0790] Based on the location information received by the server, the server searches for the nearest evacuation shelter from the local government database. The input is the location information and emergency alert content sent to the server, and the output is information about the nearest evacuation shelter (shelter name, address, contact information, map link, etc.).

[0791] Step 5:

[0792] The server collects the latest disaster information from news APIs and SNS feeds. The input is feed data from each news API or SNS feed, and the output is the collected latest disaster information.

[0793] Step 6:

[0794] The server uses the generative AI model to summarize the collected disaster information and translate it into the user's preferred language. The input is the disaster information collected in step 5 and the user's preferred language, and the output is the summarized and translated disaster information.

[0795] Step 7:

[0796] The device receives the user's voice or text input and analyzes the emotional state using an emotion engine. The input is the user's voice or text data, and the output is the analyzed emotional state (e.g., anxiety, relief, confusion, etc.).

[0797] Step 8:

[0798] The server uses a generative AI model to generate an answer based on the user's question and further adjusts the response according to the user's emotional state. The input is the analyzed emotional state and the user's question, and the output is the adjusted response. As a specific example, in response to the user's question, "Where are the evacuation shelters?", information about the nearest evacuation shelters is provided, and a reassuring response such as "Don't worry, you can evacuate safely" is added.

[0799] Step 9:

[0800] The terminal displays the evacuation shelter information and responses received from the server to the user through a chat box-style interface. The input is the data sent from the server in step 8, and the output is the information displayed on the terminal's display. The user can take safe evacuation actions based on this information.

[0801] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0802] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0803] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0804] [Third embodiment]

[0805] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0806] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0807] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0808] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0809] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0810] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0811] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0812] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0813] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0814] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0815] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0816] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0817] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. This system combines functions for receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using AI generation, and exchanging information interactively with users.

[0818] Program processing explanation

[0819] 1. Information gathering stage

[0820] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The device also obtains the language information set by the user from the device's settings. The device then receives an emergency alert email via the mobile network and analyzes its contents.

[0821] 2. Identifying evacuation sites

[0822] The device sends the acquired location information to a server, which then uses this information to search for the nearest evacuation shelter in the local government's database. The search results include details such as the shelter's name, address, contact information, and a map link.

[0823] 3. Disaster Information Summary and Translation

[0824] The server collects the latest disaster news and social media information. This information is obtained from news APIs and social media feeds. It then uses generative AI to summarize this information and translate it into the user's language of choice. The translated information is then presented in a format that is easy for the user to understand.

[0825] 4. Interactive Response

[0826] The device displays a chat box-style interface to the user, allowing the user to ask questions about evacuation sites and disaster information. For example, if the user types "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server.

[0827] The server uses a generation AI to instantly respond to the user's questions, providing specific information such as, "The nearest evacuation site from your current location is Hibiya Park, 100 meters away." The generation AI also flexibly responds to the user's additional questions, providing a sense of security.

[0828] Specific examples

[0829] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0830] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0831] 2. The device sends its location information around Tokyo Station to the server.

[0832] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0833] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0834] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0835] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0836] Example 2: When the overseas trainee does not understand the content of the warning

[0837] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[0838] 2. The device sends the contents of the received emergency alert email to the server.

[0839] 3. The server uses the generation AI to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[0840] 4. The generating AI returns the translation results to the device and notifies the user of the alert content.

[0841] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[0842] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using generation AI.

[0843] In this way, the system of the present invention enables users to quickly and accurately receive necessary disaster information and evacuation instructions in an emergency. Specific information is provided according to the user's current location and language, reducing anxiety during a disaster and enabling safe evacuation.

[0844] The processing flow will be explained below.

[0845] Step 1:

[0846] The device acquires the user's current location using the GPS function. Specifically, it collects latitude and longitude information through the built-in GPS module of the smartphone or tablet.

[0847] Step 2:

[0848] The device acquires the user's language setting information. Specifically, it checks the display language selected by the user (e.g., Japanese, English, Spanish, etc.) from the device's system settings.

[0849] Step 3:

[0850] The device receives emergency alert emails via the mobile network and analyzes the content of the email to determine the type of disaster and its urgency.

[0851] Step 4:

[0852] The device sends the acquired location information and emergency alert email information to the server. The sent data includes latitude, longitude, language setting, and the content of the emergency alert.

[0853] Step 5:

[0854] The server uses the received location information to search for the nearest evacuation site in the local government's database, which contains information such as the name, address, contact information, and capacity of each evacuation site.

[0855] Step 6:

[0856] The server passes the evacuation site information to the AI ​​generator and has it translate it into a language the user can understand. For example, Japanese evacuation site information can be translated into English, Spanish, etc.

[0857] Step 7:

[0858] The server collects the latest disaster news and social media information from the internet, summarizes the collected information using generative AI, and translates it into the language specified by the user.

[0859] Step 8:

[0860] The server sends evacuation site information and summarized / translated disaster information to the terminal.

[0861] Step 9:

[0862] The device displays a chat interface to the user, providing information on evacuation sites and disasters in an interactive format and answering any additional questions.

[0863] Step 10:

[0864] Users input questions about evacuation shelters and disaster information through the chat interface, such as "Where is the nearest evacuation shelter?" and "What items should I bring to the evacuation shelter?"

[0865] Step 11:

[0866] The terminal analyzes the user's question and sends an appropriate request to the server.

[0867] Step 12:

[0868] The server uses generative AI to instantly respond to user questions, providing specific information such as, "The nearest evacuation site is Hibiya Park, 100 meters away."

[0869] Step 13:

[0870] The terminal displays the response received from the server to the user, who can then take appropriate action based on the information provided.

[0871] The above is the specific processing flow of the "AI-Disaster Guide" system, which enables users to quickly and accurately receive the disaster information and evacuation instructions they need in an emergency.

[0872] Example 1

[0873] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0874] In recent years, natural disasters have become more frequent, creating a need for rapid and accurate information provision in the event of a disaster. However, issues remain, such as a lack of multilingual support and difficulty in identifying evacuation sites based on the user's current location. Furthermore, there are cases where the content of emergency alert emails is difficult to understand, and appropriate evacuation sites are unknown. A system is needed to resolve these issues and streamline the provision of disaster information.

[0875] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0876] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using a generative AI model, means for interactively exchanging information with a user, means for analyzing the content of the emergency alert emails, means for searching for the nearest evacuation site from a local government database, means for collecting news and SNS information, and means for providing a user interface. This allows users to quickly and accurately receive the information they need in the event of a disaster, improving the efficiency of emergency responses.

[0877] The "means for receiving emergency alert emails" is a function that enables a terminal to receive emergency alert emails that are sent when a disaster occurs.

[0878] "Means for acquiring location information" refers to a function for acquiring the latitude and longitude of the user's current location using a GPS function or the like.

[0879] The "means for searching for evacuation site information" is a function for searching for the nearest evacuation site based on the acquired location information.

[0880] "Means for summarizing and translating information using generative AI models" refers to the function of summarizing and translating collected disaster information into multiple languages ​​using generative AI technology.

[0881] The "means for exchanging information interactively with the user" is a function that allows the user to ask questions and respond using a chat box-style interface.

[0882] The "means for analyzing the contents of the emergency alert email" is a function for analyzing the contents of the received emergency alert email and extracting information necessary for the user.

[0883] "Means to search for the nearest evacuation site from the local government's database" is a function that searches for the nearest evacuation site based on location information from a database managed by the local government.

[0884] "Means of collecting news and social media information" refers to a function for collecting information from the latest disaster news and social media.

[0885] The "means for providing a user interface" is a function that provides an interface for users to check disaster information and ask and answer questions.

[0886] This invention is a system for providing users with fast and accurate information in the event of a disaster. This system combines functions for receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using a generative AI model, and exchanging information interactively with users.

[0887] Hardware and Software Configuration

[0888] Terminal

[0889] The devices are mobile communication devices such as smartphones and tablets. These devices have the following features:

[0890] GPS function: Obtain the user's current location

[0891] Mobile network: Receive emergency alert emails

[0892] User interface: Interact with the user in a chat box format

[0893] server

[0894] The server has the following features:

[0895] News API and SNS feed aggregation tool: Obtain the latest disaster news and SNS information

[0896] Database: Manages and provides information on evacuation sites for local governments

[0897] Generative AI models: Summarize collected information and translate it into a language the user can understand

[0898] What the program does

[0899] 1. Information gathering

[0900] The device first obtains the user's location information using its GPS function. For example, it obtains latitude and longitude information using the Google Maps API. It also reads the language information set by the user from the device's settings menu. Next, it receives an emergency alert email via the mobile network and analyzes its contents using a text analysis tool.

[0901] 2. Identifying evacuation sites

[0902] The device sends the acquired location information to the server via an HTTP request. The server searches the database for the nearest evacuation site based on the location information and returns the results to the device, allowing the device to show the nearest evacuation site to the user.

[0903] 3. Disaster Information Summary and Translation

[0904] The server collects the latest disaster news from news APIs (e.g., Google News API) and social media feeds. This information is summarized and translated using a generative AI model (e.g., OpenAI's GPT-3 or GPT-4). The translated information is then sent to the device and provided to the user.

[0905] 4. Interactive Response

[0906] The device provides the user with a chat box-style interface, implemented, for example, using React Native. The user enters a question through the chat box, which the device analyzes and sends to the server. The server uses a generative AI model to instantly respond to the user's question, which is then returned to the device and displayed to the user.

[0907] Specific examples

[0908] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0909] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[0910] 2. The device sends its location information around Tokyo Station to the server.

[0911] 3. The server uses the generative AI model to search for information about the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[0912] 4. The generative AI model translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[0913] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[0914] 6. The generative AI model responds, "Shelters need drinking water, emergency food, phone chargers, medicine, etc."

[0915] Example 2: When the overseas trainee does not understand the content of the warning

[0916] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[0917] 2. The device sends the contents of the received emergency alert email to the server.

[0918] 3. The server uses the generative AI model to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[0919] 4. The generative AI model returns the translation results to the device and notifies the user of the alert content.

[0920] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[0921] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using a generative AI model.

[0922] In this way, the system of the present invention provides necessary information quickly and accurately in the event of a disaster, thereby ensuring the safety of users.

[0923] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0924] Step 1:

[0925] The device first obtains the user's current location using its GPS function. It uses data from the GPS sensor as input and outputs location information in the form of latitude and longitude. Specific examples include obtaining location information using the Google Maps API.

[0926] Step 2:

[0927] The device reads the language information set by the user from the device's settings menu. It uses the device's locale setting data as input and outputs the set language information. This obtains the user's language setting (e.g., Japanese, English, etc.).

[0928] Step 3:

[0929] The device receives emergency alert emails via the mobile network. It analyzes the received email data as input and outputs important disaster information (e.g., type of disaster, location, response methods, etc.). Specifically, it uses natural language processing (NLP) technology to perform text analysis.

[0930] Step 4:

[0931] The device sends its location information (latitude and longitude) to the server through an HTTP request. The server uses the location data obtained as input and provides the location information as output. This request is sent to identify the required evacuation location.

[0932] Step 5:

[0933] The server searches for the nearest evacuation site from the local government's database based on the location information. Using the location information data received as input, it outputs detailed information such as the name, address, contact information, and map link of the evacuation site. Specific operations use a database management system such as PostgreSQL.

[0934] Step 6:

[0935] The server sends the search results in JSON format to the device. It uses the organized evacuation location information as input and provides detailed information of evacuation locations to the device as output. This information can be used by the user to quickly find the nearest evacuation location.

[0936] Step 7:

[0937] The server collects the latest disaster news and social media information from news APIs and social media feeds. It uses information obtained from various APIs as input and outputs the collected disaster information. Specific operations include using the Google News API and Twitter API.

[0938] Step 8:

[0939] The server uses a generative AI model to summarize the collected disaster information and translate it into the language set by the user. It uses collected news and social media information and the user's language setting as input, and outputs the summarized and translated information. Specific examples use OpenAI's GPT-3 and GPT-4 and the Google Translate API.

[0940] Step 9:

[0941] The server sends the translated summary information to the terminal in JSON format. It uses the translated information data as input and provides the information to the terminal as output. This information is displayed in a format that is easy for the user to understand.

[0942] Step 10:

[0943] The terminal displays a chat box-style interface to the user. It uses user interface configuration information as input and provides the interface as output. Specifically, the interface is constructed using React Native.

[0944] Step 11:

[0945] The user inputs questions about evacuation sites and disaster information through the chat box. The user's text input data is used as input, and this is sent to the terminal. A specific example includes the action of inputting "Where is the nearest evacuation site?"

[0946] Step 12:

[0947] The device analyzes the user's question and sends it to the server. It uses the user's text data as input and analyzes it using natural language processing (NLP). It provides the analysis results to the server as output.

[0948] Step 13:

[0949] The server uses a generative AI model to instantly respond to user questions. It uses the analyzed question data as input and outputs a specific response. For example, if a user asks about the nearest evacuation site, it provides that information.

[0950] Step 14:

[0951] The server uses the generative AI model to generate a response and sends it to the terminal in JSON format. The generated response data is used as input and provided to the terminal as output. This information is displayed in a user-friendly format.

[0952] Step 15:

[0953] The terminal displays the response result in a chat box and provides it to the user. The received response data is used as input and displayed on the user's interface as output. A specific example includes the action of displaying "The nearest evacuation site from your current location is 100 meters away."

[0954] (Application example 1)

[0955] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0956] In the event of a disaster, it is extremely important to obtain accurate information quickly and respond appropriately. However, if information is not provided in multiple languages, it becomes difficult to provide effective information to users who have language barriers, such as foreigners. Furthermore, when there is a huge amount of information, it is difficult to quickly summarize and translate each piece of information and provide it in a form that users can understand. Furthermore, when users ask specific questions on the spot, it is difficult to obtain accurate answers in real time. A new system is needed to solve these issues.

[0957] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0958] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with a user in an interactive format, means for summarizing emergency alerts using a generative model, and means for providing real-time responses to user questions in multiple languages. This enables the rapid and accurate provision of information in the event of a disaster, particularly by enhancing multilingual support and responses to real-time user questions, thereby enabling support for users to take appropriate action.

[0959] "Means for receiving emergency emails" refers to a communication system for notifying user terminals of information about disasters and emergencies.

[0960] "Means for obtaining location information" refers to a system that uses GPS or other location-determining technology to obtain a user's current location in the form of latitude and longitude.

[0961] "Means for searching for evacuation site information" refers to a system that identifies the nearest evacuation site based on the user's current location information and provides that information.

[0962] "Means for summarizing and translating information using generative artificial intelligence" refers to a system that uses a generative AI model to concisely summarize collected disaster information and translate it into language that users can understand.

[0963] "Means for interactively exchanging information with the user" refers to a system that uses an interface such as a chat box or voice recognition to respond to questions from the user in an interactive manner.

[0964] "Means for summarizing emergency alerts using a generative model" refers to a system that uses a generative AI model to concisely summarize the contents of emergency alert emails.

[0965] "Means for providing real-time responses to user questions in multiple languages" refers to a system that uses generative AI models and natural language processing technology to provide real-time answers to questions asked by users in multiple languages.

[0966] This invention was developed to implement a "Disaster Countermeasure Security Guide" system that provides prompt and accurate information in the event of a disaster. This system is implemented on devices such as smartphones and smart glasses, and provides the following specific functions:

[0967] 1. Receiving emergency alert emails

[0968] The terminal receives emergency alert emails about disasters and emergencies via the communication network, allowing users to obtain important information in real time.

[0969] 2. Obtaining location information

[0970] The device uses the GPS function to obtain the user's current location. The current location information is obtained in the form of latitude and longitude and sent to the server. This allows the user to know exactly where they are.

[0971] 3. Search for evacuation shelter information

[0972] The server searches the local government's database for the nearest evacuation site based on the user's location information. The search results include the name, address, and map link of the evacuation site, and this information is provided to the user.

[0973] 4. Summary and Translation of Information

[0974] The server collects emergency alerts and the latest disaster information and summarizes the information using a generative AI model. Furthermore, to support multiple languages, the summarized information is translated into the language selected by the user. This allows users, such as foreigners, who face language barriers, to understand accurate information.

[0975] 5. Interactive information provision

[0976] The device provides a chat box-style interface and responds to user questions in real time. The server uses a generative AI model to generate appropriate answers to the user's questions and provides them in multiple languages. For example, in response to the question, "Where is the nearest evacuation site?", it provides specific information such as, "The nearest evacuation site is a park 100 meters away."

[0977] Hardware and software used

[0978] Hardware: Smartphones, smart glasses

[0979] software:

[0980] Geopy: a location processing library

[0981] Transformers: A natural language processing library

[0982] OpenAI GPT-3: Generative AI model

[0983] Specific examples

[0984] Example 1: A traveler experiences an earthquake in an unfamiliar area

[0985] 1. The user starts up the device and obtains the current location information (latitude: 35.6895, longitude: 139.6917).

[0986] 2. The device sends the location information to the server.

[0987] 3. The server uses the generation AI to search for information on the nearest evacuation site and provide it to the user.

[0988] 4. The generating AI translates the information into the language set by the user (English) and shows the route to the evacuation site.

[0989] 5. The user asks in the chat box, "What do you need for evacuation shelters?"

[0990] 6. The generated AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[0991] Prompt Sentence Examples

[0992] "Please summarize: Emergency alert: Earthquake has occurred. Evacuate immediately."

[0993] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0994] Step 1:

[0995] The terminal receives an emergency alert email. The input is the emergency alert email sent over a communication network, and the terminal receives the email content as a message. The output is the text information of the received emergency alert email. This text information is used in the next step.

[0996] Step 2:

[0997] The device obtains location information. The input is a process that obtains the current latitude and longitude through the GPS function. The output is the numerical data of the latitude and longitude corresponding to the user's current location. This numerical data is used in the next step.

[0998] Step 3:

[0999] The server searches for evacuation shelters based on location information. The input is the latitude and longitude of the current location obtained in step 2, and references the evacuation shelter database. The output is information about the evacuation shelter closest to the current location (name, address, contact information, map link, etc.). This information is used in the next step.

[1000] Step 4:

[1001] The server uses a generative AI model to summarize the content of the emergency alert email. The input is the text information of the emergency alert email received in step 1, which is provided to the generative AI model as a prompt. The output is the summary text of the emergency alert email. This summary text is used in the next step.

[1002] Step 5:

[1003] The server uses a generative AI model to translate the summarized disaster information. The input is the summary text obtained in step 4 and the language information set by the user. The output is the text translated from the summary text into the specified language. This translated text is used in the next step.

[1004] Step 6:

[1005] The terminal exchanges information with the user in a dialogue format. The input is a question text from the user (e.g., "Where is the nearest evacuation site?"). The output is a response text from the server, which is displayed in a format that the user can view in a chat box.

[1006] Step 7:

[1007] The server uses a generative AI model to respond to user questions. The input is the question text sent by the user via the terminal, and the generative AI model analyzes the question. The output is a specific and accurate response text to the question. This response text is sent to the terminal and provided to the user.

[1008] Specific actions

[1009] 1. Obtaining location information: The GPS module is used to obtain latitude and longitude, and this is sent to the server along with the contents of the emergency alert email.

[1010] 2. Search for evacuation shelters: The server accesses the local government database to identify the nearest evacuation shelter from the user's current location. It also translates the information into the user's language.

[1011] 3. Information Summarization: Using a generative AI model (e.g., OpenAI GPT-3), a concise summary of the received emergency alert email is created. This summary is sent as a prompt to the generative AI model in the next step.

[1012] 4. Multilingual translation: Using a translation model (e.g., MarianMT model), summarizes information and outputs it in multiple languages.

[1013] 5. Conversational information provision: Users can ask questions via a chat box, and the generative AI will provide an appropriate response based on the question.

[1014] Prompt Sentence Examples

[1015] "Please summarize: Emergency alert: Earthquake has occurred. Evacuate immediately."

[1016] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1017] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. This system combines functions such as receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using generative AI, exchanging information with users in a dialogue format, and an emotion engine that recognizes the user's emotions.

[1018] Program processing explanation

[1019] 1. Information gathering stage

[1020] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The device also obtains the language information set by the user from the device's settings. The device then receives an emergency alert email via the mobile network and analyzes its contents.

[1021] 2. Identifying evacuation sites

[1022] The device sends the acquired location information and emergency alert email information to the server. The sent data includes latitude, longitude, language setting, and the content of the emergency alert.

[1023] The server uses the received location information to search the local government's database for the nearest evacuation shelter, and the search results include details such as the shelter's name, address, contact information, and a map link.

[1024] 3. Disaster Information Summary and Translation

[1025] The server collects the latest disaster news and social media information. This information is obtained from news APIs and social media feeds. It then uses generative AI to summarize this information and translate it into the user's language of choice. The translated information is then presented in a format that is easy for the user to understand.

[1026] 4. Introducing the Emotion Engine

[1027] The device runs an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotional state (e.g., anxiety, relief, confusion, etc.) from their voice and text.

[1028] 5. Interactive Response

[1029] The device displays a chat box-style interface to the user, allowing the user to ask questions about evacuation sites and disaster information. For example, if the user types "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server.

[1030] The server uses a generation AI to instantly respond to the user's questions. For example, it provides specific information such as, "The nearest evacuation site from your current location is Hibiya Park, 100 meters away." The generation AI also adjusts the response based on the user's emotional state. For example, if the user is feeling anxious, it adds a reassuring comment.

[1031] Specific examples

[1032] Example 1: A traveler experiences an earthquake in an unfamiliar area

[1033] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[1034] 2. The device sends its location information around Tokyo Station to the server.

[1035] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[1036] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[1037] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[1038] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[1039] 7. The emotion engine detects the user's anxiety and adds comments such as, "Don't worry, there is a shelter near your current location."

[1040] Example 2: When the overseas trainee does not understand the content of the warning

[1041] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[1042] 2. The device sends the contents of the received emergency alert email to the server.

[1043] 3. The server uses the generation AI to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[1044] 4. The generating AI returns the translation results to the device and notifies the user of the alert content.

[1045] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[1046] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using generation AI.

[1047] 7. The emotion engine detects the user's confusion and adds a comment such as, "Don't worry, we'll give you detailed directions to the evacuation shelter."

[1048] In this way, the system of the present invention allows users to quickly and accurately receive necessary disaster information and evacuation instructions in an emergency. Furthermore, by recognizing the user's emotions in real time and responding appropriately according to their emotional state, anxiety and confusion during a disaster can be reduced. Specific information is provided according to the user's current location and language, allowing them to take safe evacuation action.

[1049] The processing flow will be explained below.

[1050] Step 1:

[1051] The device acquires the user's current location using the GPS function. Specifically, it collects latitude and longitude information using the built-in GPS module of the smartphone or tablet.

[1052] Step 2:

[1053] The terminal acquires the user's language setting information. Specifically, the terminal checks the display language selected by the user (e.g., Japanese, English, Spanish, etc.) from the terminal's system settings.

[1054] Step 3:

[1055] The device receives emergency alert emails via the mobile network, analyzes the content of the emails, and determines the type of disaster and its urgency.

[1056] Step 4:

[1057] The device sends the acquired location information and emergency alert email information to the server. The transmitted data includes latitude, longitude, language setting, and the content of the emergency alert email.

[1058] Step 5:

[1059] The server uses the received location information to search for the nearest evacuation site in the local government's database, which contains information such as the name, address, contact information, and capacity of each evacuation site.

[1060] Step 6:

[1061] The server passes the evacuation site information to the AI ​​generator and has it translate it into a language the user can understand. For example, Japanese evacuation site information can be translated into English, Spanish, etc.

[1062] Step 7:

[1063] The server collects the latest disaster news and social media information from the internet, summarizes the collected information using generative AI, and translates it into the language specified by the user.

[1064] Step 8:

[1065] The server sends summarized and translated disaster information and evacuation shelter information to the terminal, including evacuation shelter routes and important disaster news.

[1066] Step 9:

[1067] The device displays a chat interface to the user, through which the user can ask questions about evacuation sites and disaster information.

[1068] Step 10:

[1069] The device runs an emotion engine to recognize emotions from the user's voice and text. The emotion engine analyzes the tone of the voice and keywords in the text to identify the user's emotional state (e.g., anxiety, relief, confusion, etc.).

[1070] Step 11:

[1071] Users can input questions about evacuation shelters and disaster information through the chat interface, such as "Where is the nearest evacuation shelter?" and "What items should I bring to the evacuation shelter?"

[1072] Step 12:

[1073] The device analyzes the input question and sends an appropriate request to the server. The transmitted data includes the user's question and the emotion analysis results of the emotion engine.

[1074] Step 13:

[1075] The server uses generative AI to instantly respond to the user's questions, generating information such as "The nearest evacuation site from your current location is Hibiya Park, 100 meters away," and adding additional comments based on the user's emotional state.

[1076] Step 14:

[1077] The device displays the response received from the server to the user. To reassure the user, a comment such as "Don't worry, this is a nearby evacuation site." may be added.

[1078] This is the specific processing flow of the "AI-Disaster Guide" system, which combines an emotion engine that recognizes the user's emotions. The system aims to provide fast and accurate information in the event of a disaster, reducing user anxiety and confusion.

[1079] Example 2

[1080] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1081] During a disaster, it is difficult for users to obtain the information they need quickly and accurately, and confusion and anxiety increase, especially in unfamiliar areas or places where different languages ​​are spoken. Providing disaster information in multiple languages ​​and recognizing the user's emotional state and responding appropriately are also challenges.

[1082] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1083] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with a user in an interactive format, means for analyzing the user's emotional state, and means for adjusting response content based on the user's emotional state. This allows the server to provide disaster information quickly and accurately, enabling users to take evacuation action with peace of mind.

[1084] "Means for receiving emergency emails" refers to a function for receiving alerts and notifications sent via a communication network in the event of a disaster or serious emergency.

[1085] "Means for obtaining location information" refers to a function for obtaining the user's current location in the form of latitude and longitude using technologies such as GPS and Wi-Fi.

[1086] The "means for searching for evacuation site information" is a function for identifying the nearest evacuation site based on the user's current location. This identification includes referencing databases of local governments and administrative agencies.

[1087] "Means for summarizing and translating information using generative AI" is a function that uses a generative AI model to concisely summarize collected disaster information and translate it into a language that the user can understand.

[1088] "Means for interactively exchanging information with the user" refers to a function that allows the user to input questions or instructions through an interface such as a chat box or voice assistant, and the system then responds to them.

[1089] "Means for analyzing the user's emotional state" is a function for analyzing emotions such as anxiety, relief, and confusion from the user's voice and text in real time.

[1090] The "means for adjusting the response content based on the user's emotional state" is a function for appropriately changing the system's response content depending on the user's emotional state. For example, if a user is feeling anxious, a comment that gives a sense of security may be added.

[1091] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. The system combines functions such as receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using generative AI, exchanging information with users in a dialogue format, and an emotion engine that recognizes the user's emotions.

[1092] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The specific hardware used is a smartphone or tablet. The device also obtains the language information set by the user from the device's settings. The device receives an emergency alert email via the mobile network and analyzes its contents. The software used is a location information service or email client.

[1093] The device sends the acquired location information and emergency alert email information to the server. The transmitted data includes latitude, longitude, language setting, and the content of the emergency alert. The server uses the received location information to search for the nearest evacuation site from the local government's database. This is done using a Web API.

[1094] The server collects the latest disaster news and information from news APIs and social media feeds. It then uses a generative AI to summarize this information and translate it into the user's language. The generative AI uses models such as GPT-3. The translated information is then presented in a format that is easy for the user to understand.

[1095] The device runs an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotional state from their voice and text using voice recognition software and natural language processing tools.

[1096] The device displays a chat box-style interface to the user. Through this interface, the user can ask questions about evacuation sites and disaster information. For example, if the user types, "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server. The server uses a generative AI to instantly respond to the user's question. The generative AI also adjusts the response based on the user's emotional state.

[1097] Specific examples

[1098] Example 1: A traveler experiences an earthquake in an unfamiliar area

[1099] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[1100] 2. The device sends its location information around Tokyo Station to the server.

[1101] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[1102] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[1103] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[1104] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[1105] 7. The emotion engine detects the user's anxiety and adds comments such as, "Don't worry, there is a shelter near your current location."

[1106] Prompt Sentence Examples

[1107] "Please tell me the nearest evacuation site from my current location."

[1108] "Please summarize the latest earthquake information and translate it into English."

[1109] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1110] Step 1:

[1111] The device uses its GPS function to obtain the user's current location. The input is location information obtained from the user's device, and the output is current location information expressed in latitude and longitude format. Specifically, the device collects GPS signals while displaying a progress bar such as "obtaining current location."

[1112] Step 2:

[1113] The device receives an emergency alert email. The input is the emergency alert email sent over the mobile network, and the output is the parsed content of the email. Specifically, the device displays a notification in the notification bar, such as "Earthquake alert. The epicenter is Higashi Ward."

[1114] Step 3:

[1115] The device sends the acquired location information and the contents of the emergency alert email to the server. The input is the latitude and longitude location information and the contents of the emergency alert email, and the output is a data packet containing this information. Specifically, the device displays "Sending data..." in the status bar.

[1116] Step 4:

[1117] The server searches the local government's database for the nearest evacuation site based on the received location information. The input is the user's location information, and the output is detailed information such as the name, address, contact information, and map link of the evacuation site. Specifically, the server records "Searching for evacuation site..." in the log and calls the API of the local government's database to perform the search.

[1118] Step 5:

[1119] The server collects the latest disaster news and information from news APIs and social media feeds. The input is raw data obtained from news APIs and social media feeds, and the output is a collection of collected disaster news. Specifically, the server records "Collecting disaster news..." in the log.

[1120] Step 6:

[1121] The server uses a generative AI to summarize the collected disaster news and translate it into the language set by the user. The input is a collection of collected disaster news and the user's language setting, and the output is a translated summary in a format that is easy for the user to understand. Specifically, the server inputs a prompt to the generative AI model saying, "Please summarize the latest earthquake information and translate it into English."

[1122] Step 7:

[1123] The device runs an emotion engine to recognize the user's emotional state in real time. The input is the user's voice or text, and the output is the analyzed emotional state (e.g., anxious, relieved, confused, etc.). Specifically, the device displays "Analyzing emotions..." in the status bar.

[1124] Step 8:

[1125] The terminal displays a chat box-style interface to the user and sends the user's question to the server. The input is the user's question, and the output is a data packet sent to the server. Specifically, when the user types "Where is the nearest evacuation site?", the terminal analyzes the question and sends it to the server.

[1126] Step 9:

[1127] The server uses the generation AI to respond to the user's question and send it back to the device. The input is the user's question and a prompt to the generation AI, and the output is the generated answer. Specifically, the generation AI model receives a prompt saying, "Please tell me the nearest evacuation site from my current location," and generates a response saying, "The nearest evacuation site is Hibiya Park, 100 meters away."

[1128] Step 10:

[1129] The device displays the response from the server based on the user's emotional state. The input is the information returned from the server and the analysis results of the emotion engine, and the output is the adjusted response. Specifically, if the emotion engine detects the user's anxiety, it adds a comment such as "Don't worry, this is a shelter near your current location" and displays it.

[1130] (Application example 2)

[1131] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1132] The purpose of this invention is to provide rapid and accurate information in the event of a disaster. In particular, it aims to provide a system that can receive emergency alerts and acquire location information, search for evacuation shelter information, summarize and translate information using artificial intelligence, provide information in a dialogue format with the user, and analyze the user's emotions to enable appropriate responses according to the user's situation.

[1133] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving emergency alerts, means for acquiring location information, means for searching for evacuation shelter information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with the user in an interactive format, means for analyzing the user's emotions, and means for adjusting the response content based on the emotions. This allows the user to quickly and accurately obtain the information they need in the event of a disaster, reduce anxiety and confusion, and enable them to take safe evacuation action.

[1134] Definition of Terms

[1135] The "means for receiving emergency alerts" refers to communication devices and software for receiving alerts sent in the event of a disaster or emergency.

[1136] "Means for obtaining location information" refers to technology that obtains location data using a geographic information system (GIS) or a global positioning system (GPS) to identify the user's current location.

[1137] The "means for searching for evacuation shelter information" is a function that searches a database for the nearest evacuation shelter for the user based on the acquired location information.

[1138] "Means for summarizing and translating information using generative artificial intelligence" is a technology that uses generative AI to concisely summarize large amounts of disaster information and translate it into a form that is easy for users to understand.

[1139] "Means for exchanging information interactively with a user" refers to an interface and processing technology in which a user inputs questions or instructions and the system responds interactively to them.

[1140] "Means for analyzing user emotions" refers to technology that analyzes text and voice data entered by a user and determines their emotional state (e.g., anxiety, relief, confusion, etc.).

[1141] "Means for adjusting response content based on emotions" refers to a technology that adjusts the response content so that the generating AI provides an appropriate response according to the analyzed emotional state of the user.

[1142] MODE FOR CARRYING OUT THE INVENTION

[1143] System Overview

[1144] This invention provides an "AI-Disaster Guide" system for providing fast and accurate information during disasters. This system combines functions such as receiving emergency alerts, acquiring location information, searching for evacuation shelter information, summarizing and translating information using generative artificial intelligence (AI), exchanging information interactively with the user, and analyzing the user's emotions to adjust responses.

[1145] Hardware and Software Description

[1146] This system is realized mainly by the following hardware and software:

[1147] Smartphone: Used as a user interface and a computing resource.

[1148] GPS function: Used to obtain the user's location information.

[1149] Mobile network: Used to receive emergency alerts and communicate with the server.

[1150] Server: Processes disaster information, searches for evacuation shelter information, summarizes and translates information, and performs sentiment analysis.

[1151] Generative AI models: Used to summarize and translate text data.

[1152] Emotion engine: Used to analyze emotions from user voice and text.

[1153] Chat box format: An interface for interacting with the user.

[1154] System Operation

[1155] Initial Setup

[1156] When a user starts up a smartphone with the application installed, the current location information is obtained using the GPS function. When an emergency alert is received via the mobile network, the content is analyzed and disaster information is sent to the server.

[1157] Information search and provision

[1158] The server searches the local government's database for information on the nearest evacuation shelter based on the location information and emergency alerts received from the user. The obtained evacuation shelter information (shelter name, address, contact information, map link, etc.) is sent to the user's smartphone and displayed on a chat box-style interface.

[1159] Summary and translation of information

[1160] The server collects the latest disaster information from news APIs and social media feeds, summarizes and translates this information using a generative AI model, and provides the translation results in a format that is easy for users to understand.

[1161] Sentiment analysis and conversational responses

[1162] Sentiment analysis is performed on the user's input (voice or text), and responses are tailored based on the user's emotional state. For example, if the user is feeling anxious, a reassuring comment is added to the response.

[1163] Specific examples

[1164] Here are some examples and prompts:

[1165] Example 1: A traveler experiences an earthquake

[1166] 1. The user starts up the smartphone and their current location information (e.g., near the station) is obtained.

[1167] 2. The server searches for evacuation shelter information and provides the user with the nearest evacuation shelter.

[1168] 3. Using a generative AI model, the disaster information is translated into the user's language (e.g., English) and the route to the evacuation shelter is displayed.

[1169] Recommended prompts

[1170] "Summarize and translate the following text to Japanese: Earthquake warning in Tokyo. Seek immediate shelter."

[1171] In this way, we can realize a system that allows users to quickly and accurately obtain the information they need in the event of a disaster. Furthermore, the emotion analysis and response adjustment functions can reduce users' anxiety and confusion and support safe evacuation behavior.

[1172] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1173] Program processing flow

[1174] Step 1:

[1175] The device is started up and the user's current location is obtained using the GPS function. The input is the device's GPS data, and the output is the latitude and longitude location information. This location information is used for subsequent processing.

[1176] Step 2:

[1177] The device receives emergency alerts via mobile communications. The input is an emergency alert email received via the mobile network, and the output is the content of the received emergency alert. The device analyzes this content and identifies the type of disaster and its urgency.

[1178] Step 3:

[1179] The device transmits the acquired current location information and the contents of the emergency alert to the server. The transmitted data includes the user's latitude and longitude, language settings, and the contents of the emergency alert. The input is the data obtained in steps 1 and 2, and the output is the data transmitted to the server.

[1180] Step 4:

[1181] Based on the location information received by the server, the server searches for the nearest evacuation shelter from the local government database. The input is the location information and emergency alert content sent to the server, and the output is information about the nearest evacuation shelter (shelter name, address, contact information, map link, etc.).

[1182] Step 5:

[1183] The server collects the latest disaster information from news APIs and SNS feeds. The input is feed data from each news API or SNS feed, and the output is the collected latest disaster information.

[1184] Step 6:

[1185] The server uses the generative AI model to summarize the collected disaster information and translate it into the user's preferred language. The input is the disaster information collected in step 5 and the user's preferred language, and the output is the summarized and translated disaster information.

[1186] Step 7:

[1187] The device receives the user's voice or text input and analyzes the emotional state using an emotion engine. The input is the user's voice or text data, and the output is the analyzed emotional state (e.g., anxiety, relief, confusion, etc.).

[1188] Step 8:

[1189] The server uses a generative AI model to generate an answer based on the user's question and further adjusts the response according to the user's emotional state. The input is the analyzed emotional state and the user's question, and the output is the adjusted response. As a specific example, in response to the user's question, "Where are the evacuation shelters?", information about the nearest evacuation shelters is provided, and a reassuring response such as "Don't worry, you can evacuate safely" is added.

[1190] Step 9:

[1191] The terminal displays the evacuation shelter information and responses received from the server to the user through a chat box-style interface. The input is the data sent from the server in step 8, and the output is the information displayed on the terminal's display. The user can take safe evacuation actions based on this information.

[1192] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1193] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1194] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1195] [Fourth embodiment]

[1196] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1197] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1198] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1199] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1200] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1201] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1202] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1203] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1204] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1205] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1206] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1207] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1208] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1209] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. This system combines functions for receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using AI generation, and exchanging information interactively with users.

[1210] Program processing explanation

[1211] 1. Information gathering stage

[1212] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The device also obtains the language information set by the user from the device's settings. The device then receives an emergency alert email via the mobile network and analyzes its contents.

[1213] 2. Identifying evacuation sites

[1214] The device sends the acquired location information to a server, which then uses this information to search for the nearest evacuation shelter in the local government's database. The search results include details such as the shelter's name, address, contact information, and a map link.

[1215] 3. Disaster Information Summary and Translation

[1216] The server collects the latest disaster news and social media information. This information is obtained from news APIs and social media feeds. It then uses generative AI to summarize this information and translate it into the user's language of choice. The translated information is then presented in a format that is easy for the user to understand.

[1217] 4. Interactive Response

[1218] The device displays a chat box-style interface to the user, allowing the user to ask questions about evacuation sites and disaster information. For example, if the user types "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server.

[1219] The server uses a generation AI to instantly respond to the user's questions, providing specific information such as, "The nearest evacuation site from your current location is Hibiya Park, 100 meters away." The generation AI also flexibly responds to the user's additional questions, providing a sense of security.

[1220] Specific examples

[1221] Example 1: A traveler experiences an earthquake in an unfamiliar area

[1222] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[1223] 2. The device sends its location information around Tokyo Station to the server.

[1224] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[1225] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[1226] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[1227] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[1228] Example 2: When the overseas trainee does not understand the content of the warning

[1229] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[1230] 2. The device sends the contents of the received emergency alert email to the server.

[1231] 3. The server uses the generation AI to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[1232] 4. The generating AI returns the translation results to the device and notifies the user of the alert content.

[1233] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[1234] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using generation AI.

[1235] In this way, the system of the present invention enables users to quickly and accurately receive necessary disaster information and evacuation instructions in an emergency. Specific information is provided according to the user's current location and language, reducing anxiety during a disaster and enabling safe evacuation.

[1236] The processing flow will be explained below.

[1237] Step 1:

[1238] The device acquires the user's current location using the GPS function. Specifically, it collects latitude and longitude information through the built-in GPS module of the smartphone or tablet.

[1239] Step 2:

[1240] The device acquires the user's language setting information. Specifically, it checks the display language selected by the user (e.g., Japanese, English, Spanish, etc.) from the device's system settings.

[1241] Step 3:

[1242] The device receives emergency alert emails via the mobile network and analyzes the content of the email to determine the type of disaster and its urgency.

[1243] Step 4:

[1244] The device sends the acquired location information and emergency alert email information to the server. The sent data includes latitude, longitude, language setting, and the content of the emergency alert.

[1245] Step 5:

[1246] The server uses the received location information to search for the nearest evacuation site in the local government's database, which contains information such as the name, address, contact information, and capacity of each evacuation site.

[1247] Step 6:

[1248] The server passes the evacuation site information to the AI ​​generator and has it translate it into a language the user can understand. For example, Japanese evacuation site information can be translated into English, Spanish, etc.

[1249] Step 7:

[1250] The server collects the latest disaster news and social media information from the internet, summarizes the collected information using generative AI, and translates it into the language specified by the user.

[1251] Step 8:

[1252] The server sends evacuation site information and summarized / translated disaster information to the terminal.

[1253] Step 9:

[1254] The device displays a chat interface to the user, providing information on evacuation sites and disasters in an interactive format and answering any additional questions.

[1255] Step 10:

[1256] Users input questions about evacuation shelters and disaster information through the chat interface, such as "Where is the nearest evacuation shelter?" and "What items should I bring to the evacuation shelter?"

[1257] Step 11:

[1258] The terminal analyzes the user's question and sends an appropriate request to the server.

[1259] Step 12:

[1260] The server uses generative AI to instantly respond to user questions, providing specific information such as, "The nearest evacuation site is Hibiya Park, 100 meters away."

[1261] Step 13:

[1262] The terminal displays the response received from the server to the user, who can then take appropriate action based on the information provided.

[1263] The above is the specific processing flow of the "AI-Disaster Guide" system, which enables users to quickly and accurately receive the disaster information and evacuation instructions they need in an emergency.

[1264] Example 1

[1265] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1266] In recent years, natural disasters have become more frequent, creating a need for rapid and accurate information provision in the event of a disaster. However, issues remain, such as a lack of multilingual support and difficulty in identifying evacuation sites based on the user's current location. Furthermore, there are cases where the content of emergency alert emails is difficult to understand, and appropriate evacuation sites are unknown. A system is needed to resolve these issues and streamline the provision of disaster information.

[1267] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1268] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using a generative AI model, means for interactively exchanging information with a user, means for analyzing the content of the emergency alert emails, means for searching for the nearest evacuation site from a local government database, means for collecting news and SNS information, and means for providing a user interface. This allows users to quickly and accurately receive the information they need in the event of a disaster, improving the efficiency of emergency responses.

[1269] The "means for receiving emergency alert emails" is a function that enables a terminal to receive emergency alert emails that are sent when a disaster occurs.

[1270] "Means for acquiring location information" refers to a function for acquiring the latitude and longitude of the user's current location using a GPS function or the like.

[1271] The "means for searching for evacuation site information" is a function for searching for the nearest evacuation site based on the acquired location information.

[1272] "Means for summarizing and translating information using generative AI models" refers to the function of summarizing and translating collected disaster information into multiple languages ​​using generative AI technology.

[1273] The "means for exchanging information interactively with the user" is a function that allows the user to ask questions and respond using a chat box-style interface.

[1274] The "means for analyzing the contents of the emergency alert email" is a function for analyzing the contents of the received emergency alert email and extracting information necessary for the user.

[1275] "Means to search for the nearest evacuation site from the local government's database" is a function that searches for the nearest evacuation site based on location information from a database managed by the local government.

[1276] "Means of collecting news and social media information" refers to a function for collecting information from the latest disaster news and social media.

[1277] The "means for providing a user interface" is a function that provides an interface for users to check disaster information and ask and answer questions.

[1278] This invention is a system for providing users with fast and accurate information in the event of a disaster. This system combines functions for receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using a generative AI model, and exchanging information interactively with users.

[1279] Hardware and Software Configuration

[1280] Terminal

[1281] The devices are mobile communication devices such as smartphones and tablets. These devices have the following features:

[1282] GPS function: Obtain the user's current location

[1283] Mobile network: Receive emergency alert emails

[1284] User interface: Interact with the user in a chat box format

[1285] server

[1286] The server has the following features:

[1287] News API and SNS feed aggregation tool: Obtain the latest disaster news and SNS information

[1288] Database: Manages and provides information on evacuation sites for local governments

[1289] Generative AI models: Summarize collected information and translate it into a language the user can understand

[1290] What the program does

[1291] 1. Information gathering

[1292] The device first obtains the user's location information using its GPS function. For example, it obtains latitude and longitude information using the Google Maps API. It also reads the language information set by the user from the device's settings menu. Next, it receives an emergency alert email via the mobile network and analyzes its contents using a text analysis tool.

[1293] 2. Identifying evacuation sites

[1294] The device sends the acquired location information to the server via an HTTP request. The server searches the database for the nearest evacuation site based on the location information and returns the results to the device, allowing the device to show the nearest evacuation site to the user.

[1295] 3. Disaster Information Summary and Translation

[1296] The server collects the latest disaster news from news APIs (e.g., Google News API) and social media feeds. This information is summarized and translated using a generative AI model (e.g., OpenAI's GPT-3 or GPT-4). The translated information is then sent to the device and provided to the user.

[1297] 4. Interactive Response

[1298] The device provides the user with a chat box-style interface, implemented, for example, using React Native. The user enters a question through the chat box, which the device analyzes and sends to the server. The server uses a generative AI model to instantly respond to the user's question, which is then returned to the device and displayed to the user.

[1299] Specific examples

[1300] Example 1: A traveler experiences an earthquake in an unfamiliar area

[1301] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[1302] 2. The device sends its location information around Tokyo Station to the server.

[1303] 3. The server uses the generative AI model to search for information about the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[1304] 4. The generative AI model translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[1305] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[1306] 6. The generative AI model responds, "Shelters need drinking water, emergency food, phone chargers, medicine, etc."

[1307] Example 2: When the overseas trainee does not understand the content of the warning

[1308] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[1309] 2. The device sends the contents of the received emergency alert email to the server.

[1310] 3. The server uses the generative AI model to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[1311] 4. The generative AI model returns the translation results to the device and notifies the user of the alert content.

[1312] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[1313] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using a generative AI model.

[1314] In this way, the system of the present invention provides necessary information quickly and accurately in the event of a disaster, thereby ensuring the safety of users.

[1315] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1316] Step 1:

[1317] The device first obtains the user's current location using its GPS function. It uses data from the GPS sensor as input and outputs location information in the form of latitude and longitude. Specific examples include obtaining location information using the Google Maps API.

[1318] Step 2:

[1319] The device reads the language information set by the user from the device's settings menu. It uses the device's locale setting data as input and outputs the set language information. This obtains the user's language setting (e.g., Japanese, English, etc.).

[1320] Step 3:

[1321] The device receives emergency alert emails via the mobile network. It analyzes the received email data as input and outputs important disaster information (e.g., type of disaster, location, response methods, etc.). Specifically, it uses natural language processing (NLP) technology to perform text analysis.

[1322] Step 4:

[1323] The device sends its location information (latitude and longitude) to the server through an HTTP request. The server uses the location data obtained as input and provides the location information as output. This request is sent to identify the required evacuation location.

[1324] Step 5:

[1325] The server searches for the nearest evacuation site from the local government's database based on the location information. Using the location information data received as input, it outputs detailed information such as the name, address, contact information, and map link of the evacuation site. Specific operations use a database management system such as PostgreSQL.

[1326] Step 6:

[1327] The server sends the search results in JSON format to the device. It uses the organized evacuation location information as input and provides detailed information of evacuation locations to the device as output. This information can be used by the user to quickly find the nearest evacuation location.

[1328] Step 7:

[1329] The server collects the latest disaster news and social media information from news APIs and social media feeds. It uses information obtained from various APIs as input and outputs the collected disaster information. Specific operations include using the Google News API and Twitter API.

[1330] Step 8:

[1331] The server uses a generative AI model to summarize the collected disaster information and translate it into the language set by the user. It uses collected news and social media information and the user's language setting as input, and outputs the summarized and translated information. Specific examples use OpenAI's GPT-3 and GPT-4 and the Google Translate API.

[1332] Step 9:

[1333] The server sends the translated summary information to the terminal in JSON format. It uses the translated information data as input and provides the information to the terminal as output. This information is displayed in a format that is easy for the user to understand.

[1334] Step 10:

[1335] The terminal displays a chat box-style interface to the user. It uses user interface configuration information as input and provides the interface as output. Specifically, the interface is constructed using React Native.

[1336] Step 11:

[1337] The user inputs questions about evacuation sites and disaster information through the chat box. The user's text input data is used as input, and this is sent to the terminal. A specific example includes the action of inputting "Where is the nearest evacuation site?"

[1338] Step 12:

[1339] The device analyzes the user's question and sends it to the server. It uses the user's text data as input and analyzes it using natural language processing (NLP). It provides the analysis results to the server as output.

[1340] Step 13:

[1341] The server uses a generative AI model to instantly respond to user questions. It uses the analyzed question data as input and outputs a specific response. For example, if a user asks about the nearest evacuation site, it provides that information.

[1342] Step 14:

[1343] The server uses the generative AI model to generate a response and sends it to the terminal in JSON format. The generated response data is used as input and provided to the terminal as output. This information is displayed in a user-friendly format.

[1344] Step 15:

[1345] The terminal displays the response result in a chat box and provides it to the user. The received response data is used as input and displayed on the user's interface as output. A specific example includes the action of displaying "The nearest evacuation site from your current location is 100 meters away."

[1346] (Application example 1)

[1347] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1348] In the event of a disaster, it is extremely important to obtain accurate information quickly and respond appropriately. However, if information is not provided in multiple languages, it becomes difficult to provide effective information to users who have language barriers, such as foreigners. Furthermore, when there is a huge amount of information, it is difficult to quickly summarize and translate each piece of information and provide it in a form that users can understand. Furthermore, when users ask specific questions on the spot, it is difficult to obtain accurate answers in real time. A new system is needed to solve these issues.

[1349] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1350] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with a user in an interactive format, means for summarizing emergency alerts using a generative model, and means for providing real-time responses to user questions in multiple languages. This enables the rapid and accurate provision of information in the event of a disaster, particularly by enhancing multilingual support and responses to real-time user questions, thereby enabling support for users to take appropriate action.

[1351] "Means for receiving emergency emails" refers to a communication system for notifying user terminals of information about disasters and emergencies.

[1352] "Means for obtaining location information" refers to a system that uses GPS or other location-determining technology to obtain a user's current location in the form of latitude and longitude.

[1353] "Means for searching for evacuation site information" refers to a system that identifies the nearest evacuation site based on the user's current location information and provides that information.

[1354] "Means for summarizing and translating information using generative artificial intelligence" refers to a system that uses a generative AI model to concisely summarize collected disaster information and translate it into language that users can understand.

[1355] "Means for interactively exchanging information with the user" refers to a system that uses an interface such as a chat box or voice recognition to respond to questions from the user in an interactive manner.

[1356] "Means for summarizing emergency alerts using a generative model" refers to a system that uses a generative AI model to concisely summarize the contents of emergency alert emails.

[1357] "Means for providing real-time responses to user questions in multiple languages" refers to a system that uses generative AI models and natural language processing technology to provide real-time answers to questions asked by users in multiple languages.

[1358] This invention was developed to implement a "Disaster Countermeasure Security Guide" system that provides prompt and accurate information in the event of a disaster. This system is implemented on devices such as smartphones and smart glasses, and provides the following specific functions:

[1359] 1. Receiving emergency alert emails

[1360] The terminal receives emergency alert emails about disasters and emergencies via the communication network, allowing users to obtain important information in real time.

[1361] 2. Obtaining location information

[1362] The device uses the GPS function to obtain the user's current location. The current location information is obtained in the form of latitude and longitude and sent to the server. This allows the user to know exactly where they are.

[1363] 3. Search for evacuation shelter information

[1364] The server searches the local government's database for the nearest evacuation site based on the user's location information. The search results include the name, address, and map link of the evacuation site, and this information is provided to the user.

[1365] 4. Summary and Translation of Information

[1366] The server collects emergency alerts and the latest disaster information and summarizes the information using a generative AI model. Furthermore, to support multiple languages, the summarized information is translated into the language selected by the user. This allows users, such as foreigners, who face language barriers, to understand accurate information.

[1367] 5. Interactive information provision

[1368] The device provides a chat box-style interface and responds to user questions in real time. The server uses a generative AI model to generate appropriate answers to the user's questions and provides them in multiple languages. For example, in response to the question, "Where is the nearest evacuation site?", it provides specific information such as, "The nearest evacuation site is a park 100 meters away."

[1369] Hardware and software used

[1370] Hardware: Smartphones, smart glasses

[1371] software:

[1372] Geopy: a location processing library

[1373] Transformers: A natural language processing library

[1374] OpenAI GPT-3: Generative AI model

[1375] Specific examples

[1376] Example 1: A traveler experiences an earthquake in an unfamiliar area

[1377] 1. The user starts up the device and obtains the current location information (latitude: 35.6895, longitude: 139.6917).

[1378] 2. The device sends the location information to the server.

[1379] 3. The server uses the generation AI to search for information on the nearest evacuation site and provide it to the user.

[1380] 4. The generating AI translates the information into the language set by the user (English) and shows the route to the evacuation site.

[1381] 5. The user asks in the chat box, "What do you need for evacuation shelters?"

[1382] 6. The generated AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[1383] Prompt Sentence Examples

[1384] "Please summarize: Emergency alert: Earthquake has occurred. Evacuate immediately."

[1385] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1386] Step 1:

[1387] The terminal receives an emergency alert email. The input is the emergency alert email sent over a communication network, and the terminal receives the email content as a message. The output is the text information of the received emergency alert email. This text information is used in the next step.

[1388] Step 2:

[1389] The device obtains location information. The input is a process that obtains the current latitude and longitude through the GPS function. The output is the numerical data of the latitude and longitude corresponding to the user's current location. This numerical data is used in the next step.

[1390] Step 3:

[1391] The server searches for evacuation shelters based on location information. The input is the latitude and longitude of the current location obtained in step 2, and references the evacuation shelter database. The output is information about the evacuation shelter closest to the current location (name, address, contact information, map link, etc.). This information is used in the next step.

[1392] Step 4:

[1393] The server uses a generative AI model to summarize the content of the emergency alert email. The input is the text information of the emergency alert email received in step 1, which is provided to the generative AI model as a prompt. The output is the summary text of the emergency alert email. This summary text is used in the next step.

[1394] Step 5:

[1395] The server uses a generative AI model to translate the summarized disaster information. The input is the summary text obtained in step 4 and the language information set by the user. The output is the text translated from the summary text into the specified language. This translated text is used in the next step.

[1396] Step 6:

[1397] The terminal exchanges information with the user in a dialogue format. The input is a question text from the user (e.g., "Where is the nearest evacuation site?"). The output is a response text from the server, which is displayed in a format that the user can view in a chat box.

[1398] Step 7:

[1399] The server uses a generative AI model to respond to user questions. The input is the question text sent by the user via the terminal, and the generative AI model analyzes the question. The output is a specific and accurate response text to the question. This response text is sent to the terminal and provided to the user.

[1400] Specific actions

[1401] 1. Obtaining location information: The GPS module is used to obtain latitude and longitude, and this is sent to the server along with the contents of the emergency alert email.

[1402] 2. Search for evacuation shelters: The server accesses the local government database to identify the nearest evacuation shelter from the user's current location. It also translates the information into the user's language.

[1403] 3. Information Summarization: Using a generative AI model (e.g., OpenAI GPT-3), a concise summary of the received emergency alert email is created. This summary is sent as a prompt to the generative AI model in the next step.

[1404] 4. Multilingual translation: Using a translation model (e.g., MarianMT model), summarizes information and outputs it in multiple languages.

[1405] 5. Conversational information provision: Users can ask questions via a chat box, and the generative AI will provide an appropriate response based on the question.

[1406] Prompt Sentence Examples

[1407] "Please summarize: Emergency alert: Earthquake has occurred. Evacuate immediately."

[1408] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1409] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. This system combines functions such as receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using generative AI, exchanging information with users in a dialogue format, and an emotion engine that recognizes the user's emotions.

[1410] Program processing explanation

[1411] 1. Information gathering stage

[1412] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The device also obtains the language information set by the user from the device's settings. The device then receives an emergency alert email via the mobile network and analyzes its contents.

[1413] 2. Identifying evacuation sites

[1414] The device sends the acquired location information and emergency alert email information to the server. The sent data includes latitude, longitude, language setting, and the content of the emergency alert.

[1415] The server uses the received location information to search the local government's database for the nearest evacuation shelter, and the search results include details such as the shelter's name, address, contact information, and a map link.

[1416] 3. Disaster Information Summary and Translation

[1417] The server collects the latest disaster news and social media information. This information is obtained from news APIs and social media feeds. It then uses generative AI to summarize this information and translate it into the user's language of choice. The translated information is then presented in a format that is easy for the user to understand.

[1418] 4. Introducing the Emotion Engine

[1419] The device runs an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotional state (e.g., anxiety, relief, confusion, etc.) from their voice and text.

[1420] 5. Interactive Response

[1421] The device displays a chat box-style interface to the user, allowing the user to ask questions about evacuation sites and disaster information. For example, if the user types "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server.

[1422] The server uses a generation AI to instantly respond to the user's questions. For example, it provides specific information such as, "The nearest evacuation site from your current location is Hibiya Park, 100 meters away." The generation AI also adjusts the response based on the user's emotional state. For example, if the user is feeling anxious, it adds a reassuring comment.

[1423] Specific examples

[1424] Example 1: A traveler experiences an earthquake in an unfamiliar area

[1425] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[1426] 2. The device sends its location information around Tokyo Station to the server.

[1427] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[1428] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[1429] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[1430] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[1431] 7. The emotion engine detects the user's anxiety and adds comments such as, "Don't worry, there is a shelter near your current location."

[1432] Example 2: When the overseas trainee does not understand the content of the warning

[1433] 1. The user (overseas trainee) starts up the terminal and types, "I don't understand the meaning of the alarm."

[1434] 2. The device sends the contents of the received emergency alert email to the server.

[1435] 3. The server uses the generation AI to analyze the content of the emergency alert email and translate it into a language the user can understand (e.g., Chinese).

[1436] 4. The generating AI returns the translation results to the device and notifies the user of the alert content.

[1437] 5. The user then asks the additional question, "Where should I evacuate in this case?"

[1438] 6. The server searches for the nearest evacuation site based on the user's current location information and provides the necessary information using generation AI.

[1439] 7. The emotion engine detects the user's confusion and adds a comment such as, "Don't worry, we'll give you detailed directions to the evacuation shelter."

[1440] In this way, the system of the present invention allows users to quickly and accurately receive necessary disaster information and evacuation instructions in an emergency. Furthermore, by recognizing the user's emotions in real time and responding appropriately according to their emotional state, anxiety and confusion during a disaster can be reduced. Specific information is provided according to the user's current location and language, allowing them to take safe evacuation action.

[1441] The processing flow will be explained below.

[1442] Step 1:

[1443] The device acquires the user's current location using the GPS function. Specifically, it collects latitude and longitude information using the built-in GPS module of the smartphone or tablet.

[1444] Step 2:

[1445] The terminal acquires the user's language setting information. Specifically, the terminal checks the display language selected by the user (e.g., Japanese, English, Spanish, etc.) from the terminal's system settings.

[1446] Step 3:

[1447] The device receives emergency alert emails via the mobile network, analyzes the content of the emails, and determines the type of disaster and its urgency.

[1448] Step 4:

[1449] The device sends the acquired location information and emergency alert email information to the server. The transmitted data includes latitude, longitude, language setting, and the content of the emergency alert email.

[1450] Step 5:

[1451] The server uses the received location information to search for the nearest evacuation site in the local government's database, which contains information such as the name, address, contact information, and capacity of each evacuation site.

[1452] Step 6:

[1453] The server passes the evacuation site information to the AI ​​generator and has it translate it into a language the user can understand. For example, Japanese evacuation site information can be translated into English, Spanish, etc.

[1454] Step 7:

[1455] The server collects the latest disaster news and social media information from the internet, summarizes the collected information using generative AI, and translates it into the language specified by the user.

[1456] Step 8:

[1457] The server sends summarized and translated disaster information and evacuation shelter information to the terminal, including evacuation shelter routes and important disaster news.

[1458] Step 9:

[1459] The device displays a chat interface to the user, through which the user can ask questions about evacuation sites and disaster information.

[1460] Step 10:

[1461] The device runs an emotion engine to recognize emotions from the user's voice and text. The emotion engine analyzes the tone of the voice and keywords in the text to identify the user's emotional state (e.g., anxiety, relief, confusion, etc.).

[1462] Step 11:

[1463] Users can input questions about evacuation shelters and disaster information through the chat interface, such as "Where is the nearest evacuation shelter?" and "What items should I bring to the evacuation shelter?"

[1464] Step 12:

[1465] The device analyzes the input question and sends an appropriate request to the server. The transmitted data includes the user's question and the emotion analysis results of the emotion engine.

[1466] Step 13:

[1467] The server uses generative AI to instantly respond to the user's questions, generating information such as "The nearest evacuation site from your current location is Hibiya Park, 100 meters away," and adding additional comments based on the user's emotional state.

[1468] Step 14:

[1469] The device displays the response received from the server to the user. To reassure the user, a comment such as "Don't worry, this is a nearby evacuation site." may be added.

[1470] This is the specific processing flow of the "AI-Disaster Guide" system, which combines an emotion engine that recognizes the user's emotions. The system aims to provide fast and accurate information in the event of a disaster, reducing user anxiety and confusion.

[1471] Example 2

[1472] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1473] During a disaster, it is difficult for users to obtain the information they need quickly and accurately, and confusion and anxiety increase, especially in unfamiliar areas or places where different languages ​​are spoken. Providing disaster information in multiple languages ​​and recognizing the user's emotional state and responding appropriately are also challenges.

[1474] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1475] In this invention, the server includes means for receiving emergency alert emails, means for acquiring location information, means for searching for evacuation site information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with a user in an interactive format, means for analyzing the user's emotional state, and means for adjusting response content based on the user's emotional state. This allows the server to provide disaster information quickly and accurately, enabling users to take evacuation action with peace of mind.

[1476] "Means for receiving emergency emails" refers to a function for receiving alerts and notifications sent via a communication network in the event of a disaster or serious emergency.

[1477] "Means for obtaining location information" refers to a function for obtaining the user's current location in the form of latitude and longitude using technologies such as GPS and Wi-Fi.

[1478] The "means for searching for evacuation site information" is a function for identifying the nearest evacuation site based on the user's current location. This identification includes referencing databases of local governments and administrative agencies.

[1479] "Means for summarizing and translating information using generative AI" is a function that uses a generative AI model to concisely summarize collected disaster information and translate it into a language that the user can understand.

[1480] "Means for interactively exchanging information with the user" refers to a function that allows the user to input questions or instructions through an interface such as a chat box or voice assistant, and the system then responds to them.

[1481] "Means for analyzing the user's emotional state" is a function for analyzing emotions such as anxiety, relief, and confusion from the user's voice and text in real time.

[1482] The "means for adjusting the response content based on the user's emotional state" is a function for appropriately changing the system's response content depending on the user's emotional state. For example, if a user is feeling anxious, a comment that gives a sense of security may be added.

[1483] This invention is implemented as an "AI-Disaster Guide" that provides users with fast and accurate information during disasters. The system combines functions such as receiving emergency alert emails, acquiring location information, searching for evacuation site information, summarizing and translating information using generative AI, exchanging information with users in a dialogue format, and an emotion engine that recognizes the user's emotions.

[1484] The device first obtains the user's current location using its GPS function. The location information is obtained in the form of latitude and longitude. The specific hardware used is a smartphone or tablet. The device also obtains the language information set by the user from the device's settings. The device receives an emergency alert email via the mobile network and analyzes its contents. The software used is a location information service or email client.

[1485] The device sends the acquired location information and emergency alert email information to the server. The transmitted data includes latitude, longitude, language setting, and the content of the emergency alert. The server uses the received location information to search for the nearest evacuation site from the local government's database. This is done using a Web API.

[1486] The server collects the latest disaster news and information from news APIs and social media feeds. It then uses a generative AI to summarize this information and translate it into the user's language. The generative AI uses models such as GPT-3. The translated information is then presented in a format that is easy for the user to understand.

[1487] The device runs an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotional state from their voice and text using voice recognition software and natural language processing tools.

[1488] The device displays a chat box-style interface to the user. Through this interface, the user can ask questions about evacuation sites and disaster information. For example, if the user types, "Where is the nearest evacuation site?", the device analyzes the question and sends it to the server. The server uses a generative AI to instantly respond to the user's question. The generative AI also adjusts the response based on the user's emotional state.

[1489] Specific examples

[1490] Example 1: A traveler experiences an earthquake in an unfamiliar area

[1491] 1. The user starts up the device and obtains current location information (e.g., near Tokyo Station).

[1492] 2. The device sends its location information around Tokyo Station to the server.

[1493] 3. The server uses the generation AI to search for information on the nearest evacuation site (e.g., Hibiya Park) and sends it to the device.

[1494] 4. The generating AI translates the information into the language set by the user (e.g., English) and displays the route to the evacuation site on the device.

[1495] 5. The user asks the question in the chat box, "What do you need for an evacuation shelter?"

[1496] 6. The generating AI responds, "Shelters need drinking water, emergency food, cell phone chargers, medicine, etc."

[1497] 7. The emotion engine detects the user's anxiety and adds comments such as, "Don't worry, there is a shelter near your current location."

[1498] Prompt Sentence Examples

[1499] "Please tell me the nearest evacuation site from my current location."

[1500] "Please summarize the latest earthquake information and translate it into English."

[1501] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1502] Step 1:

[1503] The device uses its GPS function to obtain the user's current location. The input is location information obtained from the user's device, and the output is current location information expressed in latitude and longitude format. Specifically, the device collects GPS signals while displaying a progress bar such as "obtaining current location."

[1504] Step 2:

[1505] The device receives an emergency alert email. The input is the emergency alert email sent over the mobile network, and the output is the parsed content of the email. Specifically, the device displays a notification in the notification bar, such as "Earthquake alert. The epicenter is Higashi Ward."

[1506] Step 3:

[1507] The device sends the acquired location information and the contents of the emergency alert email to the server. The input is the latitude and longitude location information and the contents of the emergency alert email, and the output is a data packet containing this information. Specifically, the device displays "Sending data..." in the status bar.

[1508] Step 4:

[1509] The server searches the local government's database for the nearest evacuation site based on the received location information. The input is the user's location information, and the output is detailed information such as the name, address, contact information, and map link of the evacuation site. Specifically, the server records "Searching for evacuation site..." in the log and calls the API of the local government's database to perform the search.

[1510] Step 5:

[1511] The server collects the latest disaster news and information from news APIs and social media feeds. The input is raw data obtained from news APIs and social media feeds, and the output is a collection of collected disaster news. Specifically, the server records "Collecting disaster news..." in the log.

[1512] Step 6:

[1513] The server uses a generative AI to summarize the collected disaster news and translate it into the language set by the user. The input is a collection of collected disaster news and the user's language setting, and the output is a translated summary in a format that is easy for the user to understand. Specifically, the server inputs a prompt to the generative AI model saying, "Please summarize the latest earthquake information and translate it into English."

[1514] Step 7:

[1515] The device runs an emotion engine to recognize the user's emotional state in real time. The input is the user's voice or text, and the output is the analyzed emotional state (e.g., anxious, relieved, confused, etc.). Specifically, the device displays "Analyzing emotions..." in the status bar.

[1516] Step 8:

[1517] The terminal displays a chat box-style interface to the user and sends the user's question to the server. The input is the user's question, and the output is a data packet sent to the server. Specifically, when the user types "Where is the nearest evacuation site?", the terminal analyzes the question and sends it to the server.

[1518] Step 9:

[1519] The server uses the generation AI to respond to the user's question and send it back to the device. The input is the user's question and a prompt to the generation AI, and the output is the generated answer. Specifically, the generation AI model receives a prompt saying, "Please tell me the nearest evacuation site from my current location," and generates a response saying, "The nearest evacuation site is Hibiya Park, 100 meters away."

[1520] Step 10:

[1521] The device displays the response from the server based on the user's emotional state. The input is the information returned from the server and the analysis results of the emotion engine, and the output is the adjusted response. Specifically, if the emotion engine detects the user's anxiety, it adds a comment such as "Don't worry, this is a shelter near your current location" and displays it.

[1522] (Application example 2)

[1523] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1524] The purpose of this invention is to provide rapid and accurate information in the event of a disaster. In particular, it aims to provide a system that can receive emergency alerts and acquire location information, search for evacuation shelter information, summarize and translate information using artificial intelligence, provide information in a dialogue format with the user, and analyze the user's emotions to enable appropriate responses according to the user's situation.

[1525] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving emergency alerts, means for acquiring location information, means for searching for evacuation shelter information, means for summarizing and translating information using generative artificial intelligence, means for exchanging information with the user in an interactive format, means for analyzing the user's emotions, and means for adjusting the response content based on the emotions. This allows the user to quickly and accurately obtain the information they need in the event of a disaster, reduce anxiety and confusion, and enable them to take safe evacuation action.

[1526] Definition of Terms

[1527] The "means for receiving emergency alerts" refers to communication devices and software for receiving alerts sent in the event of a disaster or emergency.

[1528] "Means for obtaining location information" refers to technology that obtains location data using a geographic information system (GIS) or a global positioning system (GPS) to identify the user's current location.

[1529] The "means for searching for evacuation shelter information" is a function that searches a database for the nearest evacuation shelter for the user based on the acquired location information.

[1530] "Means for summarizing and translating information using generative artificial intelligence" is a technology that uses generative AI to concisely summarize large amounts of disaster information and translate it into a form that is easy for users to understand.

[1531] "Means for exchanging information interactively with a user" refers to an interface and processing technology in which a user inputs questions or instructions and the system responds interactively to them.

[1532] "Means for analyzing user emotions" refers to technology that analyzes text and voice data entered by a user and determines their emotional state (e.g., anxiety, relief, confusion, etc.).

[1533] "Means for adjusting response content based on emotions" refers to a technology that adjusts the response content so that the generating AI provides an appropriate response according to the analyzed emotional state of the user.

[1534] MODE FOR CARRYING OUT THE INVENTION

[1535] System Overview

[1536] This invention provides an "AI-Disaster Guide" system for providing fast and accurate information during disasters. This system combines functions such as receiving emergency alerts, acquiring location information, searching for evacuation shelter information, summarizing and translating information using generative artificial intelligence (AI), exchanging information interactively with the user, and analyzing the user's emotions to adjust responses.

[1537] Hardware and Software Description

[1538] This system is realized mainly by the following hardware and software:

[1539] Smartphone: Used as a user interface and a computing resource.

[1540] GPS function: Used to obtain the user's location information.

[1541] Mobile network: Used to receive emergency alerts and communicate with the server.

[1542] Server: Processes disaster information, searches for evacuation shelter information, summarizes and translates information, and performs sentiment analysis.

[1543] Generative AI models: Used to summarize and translate text data.

[1544] Emotion engine: Used to analyze emotions from user voice and text.

[1545] Chat box format: An interface for interacting with the user.

[1546] System Operation

[1547] Initial Setup

[1548] When a user starts up a smartphone with the application installed, the current location information is obtained using the GPS function. When an emergency alert is received via the mobile network, the content is analyzed and disaster information is sent to the server.

[1549] Information search and provision

[1550] The server searches the local government's database for information on the nearest evacuation shelter based on the location information and emergency alerts received from the user. The obtained evacuation shelter information (shelter name, address, contact information, map link, etc.) is sent to the user's smartphone and displayed on a chat box-style interface.

[1551] Summary and translation of information

[1552] The server collects the latest disaster information from news APIs and social media feeds, summarizes and translates this information using a generative AI model, and provides the translation results in a format that is easy for users to understand.

[1553] Sentiment analysis and conversational responses

[1554] Sentiment analysis is performed on the user's input (voice or text), and responses are tailored based on the user's emotional state. For example, if the user is feeling anxious, a reassuring comment is added to the response.

[1555] Specific examples

[1556] Here are some examples and prompts:

[1557] Example 1: A traveler experiences an earthquake

[1558] 1. The user starts up the smartphone and their current location information (e.g., near the station) is obtained.

[1559] 2. The server searches for evacuation shelter information and provides the user with the nearest evacuation shelter.

[1560] 3. Using a generative AI model, the disaster information is translated into the user's language (e.g., English) and the route to the evacuation shelter is displayed.

[1561] Recommended prompts

[1562] "Summarize and translate the following text to Japanese: Earthquake warning in Tokyo. Seek immediate shelter."

[1563] In this way, we can realize a system that allows users to quickly and accurately obtain the information they need in the event of a disaster. Furthermore, the emotion analysis and response adjustment functions can reduce users' anxiety and confusion and support safe evacuation behavior.

[1564] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1565] Program processing flow

[1566] Step 1:

[1567] The device is started up and the user's current location is obtained using the GPS function. The input is the device's GPS data, and the output is the latitude and longitude location information. This location information is used for subsequent processing.

[1568] Step 2:

[1569] The device receives emergency alerts via mobile communications. The input is an emergency alert email received via the mobile network, and the output is the content of the received emergency alert. The device analyzes this content and identifies the type of disaster and its urgency.

[1570] Step 3:

[1571] The device transmits the acquired current location information and the contents of the emergency alert to the server. The transmitted data includes the user's latitude and longitude, language settings, and the contents of the emergency alert. The input is the data obtained in steps 1 and 2, and the output is the data transmitted to the server.

[1572] Step 4:

[1573] Based on the location information received by the server, the server searches for the nearest evacuation shelter from the local government database. The input is the location information and emergency alert content sent to the server, and the output is information about the nearest evacuation shelter (shelter name, address, contact information, map link, etc.).

[1574] Step 5:

[1575] The server collects the latest disaster information from news APIs and SNS feeds. The input is feed data from each news API or SNS feed, and the output is the collected latest disaster information.

[1576] Step 6:

[1577] The server uses the generative AI model to summarize the collected disaster information and translate it into the user's preferred language. The input is the disaster information collected in step 5 and the user's preferred language, and the output is the summarized and translated disaster information.

[1578] Step 7:

[1579] The device receives the user's voice or text input and analyzes the emotional state using an emotion engine. The input is the user's voice or text data, and the output is the analyzed emotional state (e.g., anxiety, relief, confusion, etc.).

[1580] Step 8:

[1581] The server uses a generative AI model to generate an answer based on the user's question and further adjusts the response according to the user's emotional state. The input is the analyzed emotional state and the user's question, and the output is the adjusted response. As a specific example, in response to the user's question, "Where are the evacuation shelters?", information about the nearest evacuation shelters is provided, and a reassuring response such as "Don't worry, you can evacuate safely" is added.

[1582] Step 9:

[1583] The terminal displays the evacuation shelter information and responses received from the server to the user through a chat box-style interface. The input is the data sent from the server in step 8, and the output is the information displayed on the terminal's display. The user can take safe evacuation actions based on this information.

[1584] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1585] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1586] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1587] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1588] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1589] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1590] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1591] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1592] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1593] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1594] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1595] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1596] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1597] 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.

[1598] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1599] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1600] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1601] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1602] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1603] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1604] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1605] The following is further disclosed regarding the above embodiment.

[1606] (Claim 1)

[1607] A means for receiving emergency alert emails;

[1608] A means for acquiring location information;

[1609] A means for searching evacuation site information;

[1610] means for summarizing and translating information using generative artificial intelligence;

[1611] a means for interactively communicating with a user;

[1612] A system including:

[1613] (Claim 2)

[1614] 10. The system of claim 1, further comprising: means for providing disaster information in multiple languages.

[1615] (Claim 3)

[1616] 10. The system of claim 1, further comprising: means for obtaining evacuation site information from a municipal database.

[1617] "Example 1"

[1618] (Claim 1)

[1619] A means for receiving emergency alert emails;

[1620] A means for acquiring location information;

[1621] A means for searching evacuation site information;

[1622] means for summarizing and translating information using generative artificial intelligence;

[1623] a means for interactively communicating with a user;

[1624] A means for analyzing the contents of the emergency alert email;

[1625] A way to search for the nearest evacuation site from the local government database,

[1626] Means of collecting news and social media information;

[1627] means for providing a user interface;

[1628] A system including:

[1629] (Claim 2)

[1630] 10. The system of claim 1, further comprising: means for providing disaster information in multiple languages.

[1631] (Claim 3)

[1632] 10. The system of claim 1, further comprising: means for obtaining evacuation site information from a municipal database.

[1633] "Application Example 1"

[1634] (Claim 1)

[1635] A means for receiving emergency alert emails;

[1636] A means for acquiring location information;

[1637] A means for searching evacuation site information;

[1638] means for summarizing and translating information using generative artificial intelligence;

[1639] a means for interactively communicating with a user;

[1640] A means for summarizing emergency news using a generative model;

[1641] a means for providing real-time responses to user questions in multiple languages;

[1642] A system including:

[1643] (Claim 2)

[1644] 10. The system of claim 1, further comprising: means for providing disaster information in multiple languages.

[1645] (Claim 3)

[1646] 10. The system of claim 1, further comprising: means for obtaining evacuation site information from a municipal database.

[1647] "Example 2: Combining Emotion Engines"

[1648] (Claim 1)

[1649] A means for receiving emergency alert emails;

[1650] A means for acquiring location information;

[1651] A means for searching evacuation site information;

[1652] means for summarizing and translating information using generative artificial intelligence;

[1653] a means for interactively communicating with a user;

[1654] means for analyzing the emotional state of a user;

[1655] a means for adjusting response content based on emotional state;

[1656] A system including:

[1657] (Claim 2)

[1658] 10. The system of claim 1, further comprising: means for providing disaster information in multiple languages.

[1659] (Claim 3)

[1660] 10. The system of claim 1, further comprising means for obtaining evacuation site information from a government database.

[1661] "Application example 2 when combining emotion engines"

[1662] (Claim 1)

[1663] a means for receiving emergency alerts;

[1664] A means for acquiring location information;

[1665] A means of searching for evacuation shelter information;

[1666] means for summarizing and translating information using generative artificial intelligence;

[1667] a means for interactively communicating with a user;

[1668] means for analyzing user emotions;

[1669] a means for adjusting response content based on emotion;

[1670] A system including:

[1671] (Claim 2)

[1672] 10. The system of claim 1, further comprising: means for providing disaster information in multiple languages.

[1673] (Claim 3)

[1674] 10. The system of claim 1, further comprising means for obtaining evacuation shelter information from a municipal database. [Explanation of symbols]

[1675] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving emergency alert emails; A means for acquiring location information; A means for searching evacuation site information; means for summarizing and translating information using generative artificial intelligence; a means for interactively communicating with a user; A system including:

2. The system of claim 1 further comprising means for providing disaster information in multiple languages.

3. The system of claim 1 , further comprising means for obtaining evacuation site information from a municipal database.

Images