system

Abstract

Provide a system. A means for collecting disaster information in real time; means for processing and filtering the collected information; means for publishing the processed and filtered information; and means for using generative artificial intelligence to provide information interactively to a user; A means for visually displaying information in an understandable manner; and A system including:

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, a large amount of information is scattered, making it difficult for victims to efficiently obtain the information necessary to take prompt and appropriate action. Current information provision methods tend to fragment information and may lack accuracy and timeliness. As a result, it is difficult to quickly and accurately grasp important information such as information on evacuation centers, the status of supplies, and emergency alerts. The purpose of this invention is to solve these problems and ensure the safety of victims and enable rapid reconstruction support by providing necessary information in a unified manner when a disaster occurs. [Means for solving the problem]

[0005] The system of the present invention includes means for collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information interactively to users, and means for visually displaying the information in an easy-to-understand format. The system also includes means for providing guidelines for action based on the published disaster information, and means for using generative artificial intelligence to analyze user input and provide optimal disaster response actions. In this way, a system can be provided that centrally manages information needed during a disaster and supports disaster victims in responding quickly and appropriately.

[0006] "Disaster information" refers to a series of information necessary for victims to take prompt and appropriate action in the event of a natural or man-made disaster, such as information on evacuation shelters, emergency alerts, and the status of supplies.

[0007] "Real-time" refers to information being transmitted, processed, and displayed immediately at the moment it occurs.

[0008] "Collection" is the process of consolidating scattered information and integrating it into a specific system or database.

[0009] "Processing" refers to the process of analyzing, categorizing, and filtering collected information, and the steps taken to verify the validity and accuracy of the information.

[0010] "Filtering" is the process of selecting only necessary information from collected information and removing unnecessary information.

[0011] "Publication" means making the processed and filtered information publicly accessible, including through a website or application.

[0012] "Dialogue" refers to a format in which a user and a system exchange information interactively via text or voice.

[0013] "Generative AI" is AI that has the ability to generate natural-sounding sentences and answers like humans, based on specific algorithms and data.

[0014] "Visual display" means presenting information in a form that is easy for users to understand by using visual elements such as text, graphs, and illustrations.

[0015] "Guidelines for action" are information that indicates the specific actions and countermeasures that disaster victims should take in the event of a disaster. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention relates to a system that collects and processes disaster information in an integrated manner and provides users with appropriate action guidelines. This system is composed of three main elements: a server, a terminal, and a user.

[0038] First, the server collects disaster information in real time from various API endpoints, such as evacuation shelter information, emergency alerts, and the status of supplies. The server retrieves data from these sources using HTTP requests and integrates the collected information into a single database.

[0039] The server then processes and filters the collected information, including verifying data accuracy, removing duplicate information, and categorizing necessary information. The processed and filtered information is then published in real time by the server and made available to users via their devices or web applications.

[0040] The device visually displays the published information to the user. The display includes text, graphs, illustrations, etc., allowing the user to intuitively understand the information they need. The device also has the ability to provide information interactively with the user using generative artificial intelligence. When the user inputs a question into the device, the generative artificial intelligence generates the most appropriate answer and presents it to the user. For example, in response to a question such as "Where is the nearest evacuation shelter?" the device will provide updated evacuation shelter information in real time.

[0041] The server also analyzes user input and suggests optimal disaster response actions. For example, if a user provides their current location, the server will recommend the optimal evacuation route and evacuation shelter based on that location.

[0042] As a concrete example, when an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes this information, filters out the necessary information, and makes it public. The device visually displays this information to the user and provides the optimal course of action based on the user's situation. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0043] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0044] The processing flow will be explained below.

[0045] Step 1:

[0046] The server collects disaster information from various API endpoints. Specifically, it uses HTTP GET requests to retrieve data from multiple sources, such as evacuation shelter information, emergency alerts, and supply status. This allows the necessary information to be integrated into a single database.

[0047] Step 2:

[0048] The server processes and filters the collected information, checking the accuracy of the data obtained and removing duplicate or unnecessary information. It also categorizes the information and prioritizes it as needed, ensuring that the most important information is readily available.

[0049] Step 3:

[0050] The server publishes the processed and filtered information in real time, and the collected information is made available to users through web applications and terminals.

[0051] Step 4:

[0052] The terminal visually displays the published information to the user, and the visual display can include various formats such as text information, graphs, illustrations, etc. This allows the user to intuitively understand the required information.

[0053] Step 5:

[0054] The user can obtain necessary information or input specific questions through the terminal. For example, the user can input a question such as "Where is the nearest evacuation shelter?"

[0055] Step 6:

[0056] The device sends the user's question to a generative artificial intelligence that generates an optimal answer based on the user's input and real-time data.

[0057] Step 7:

[0058] The device displays the answer generated by the generative AI to the user, providing specific information such as, "The nearest evacuation shelter is XX. The current capacity is XX."

[0059] Step 8:

[0060] The server analyzes the information entered by the user and provides the optimal evacuation route and action guidelines. If the user provides location information, the server calculates the optimal evacuation route based on that information and presents it to the user via their device.

[0061] In this way, this system centrally manages the information needed in the event of a disaster, helping users to respond quickly and appropriately.

[0062] Example 1

[0063] 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."

[0064] When a disaster occurs, there is a need for an efficient method to collect necessary information in real time from multiple sources, process and filter it appropriately, and provide it to users quickly and accurately. There is also a need for a method to display information in a format that is intuitively easy for users to understand, and to respond appropriately to user inquiries using generative artificial intelligence. Conventional technologies have difficulty meeting these requirements, and the problem is that it takes a long time to collect and provide information.

[0065] 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.

[0066] In this invention, the server includes means for collecting disaster information in real time using communication technology, means for importing the collected information into an integrated database and analyzing it, communication means for providing aggregated and filtered data to user devices, means for responding to user inquiries using generative artificial intelligence, and means for visually displaying information so that users can intuitively understand it. This makes it possible to collect and process information necessary in the event of a disaster in real time and provide it to users quickly and accurately.

[0067] "Disaster information" refers to data such as evacuation shelter information, emergency alerts, and the status of supplies related to natural disasters such as earthquakes, floods, and typhoons.

[0068] "Communication technology" refers to technology for sending and receiving data using HTTP requests, WebSockets, API endpoints, etc.

[0069] An "integrated database" refers to a database system that centrally manages and stores data collected from multiple sources.

[0070] "Analysis" refers to the process of verifying the accuracy of collected data, removing duplicate information, and classifying the necessary information.

[0071] "User device" refers to a terminal device, such as a PC, smartphone, or tablet, that a user uses to receive and operate information.

[0072] "Generative AI" refers to AI technology that generates responses in natural language to user inquiries.

[0073] "Visually displaying" refers to presenting information to users in a way that they can intuitively understand, using text information, graphs, illustrations, maps, etc.

[0074] This invention relates to a system that collects disaster information in real time and provides users with prompt and accurate action guidelines. This system consists of three main elements: a server, a terminal, and a user.

[0075] First, the server collects disaster information from multiple sources. Specifically, it uses HTTP requests to obtain information on evacuation shelters, emergency alerts, and the status of supplies from government and private API endpoints (e.g., "https: / / api.disasterinfo.gov / shelters" and "https: / / api.weatheragency.jp / alerts"). The collected information is then stored in an integrated database such as MySQL (registered trademark) or PostgreSQL.

[0076] The server then analyzes the information stored in the database, which includes verifying the accuracy of the data, removing duplicate information, and categorizing the necessary information. For example, the server may run SQL queries to remove duplicate data and categorize the information by importance.

[0077] The analyzed and filtered data is provided to the user device in real time. The server uses WebSocket or HTTP API to deliver the latest information to the front end. The user device visually displays the received information using HTML, CSS, and JavaScript (registered trademark). For example, it can mark the location of evacuation shelters on a map or display emergency alerts as a notification pop-up.

[0078] Furthermore, the device uses generative artificial intelligence to generate responses to user questions. For example, if a user asks, "Where is the nearest evacuation shelter?", the device uses a generative AI model (e.g., ChatGPT®) to generate an answer and present it to the user.

[0079] The server also analyzes input information (e.g., location information) provided by the user to determine the optimal disaster response action. The server analyzes the latitude and longitude information of the current location, calculates the shortest route using Google (registered trademark) Maps API, etc., and presents the results to the user.

[0080] For example, when an earthquake occurs, the server quickly collects emergency alerts and evacuation shelter information from multiple sources, filters the necessary information, and provides it to the user's device. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0081] An example of a prompt would be, "In the event of a large-scale earthquake, collect emergency alerts and evacuation shelter information from government APIs and the Japan Meteorological Agency APIs. Then, integrate the collected information into a database, remove duplicate information, and verify its accuracy before providing it to users. Also, when users ask about the nearest evacuation shelter or evacuation route, use generative artificial intelligence to generate an appropriate answer."

[0082] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0083] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0084] Step 1:

[0085] The server collects disaster information.

[0086] Input: Multiple API endpoints (e.g., "https: / / api.disasterinfo.gov / shelters", "https: / / api.weatheragency.jp / alerts")

[0087] Specific operation: The server sends an HTTP GET request to each endpoint and receives JSON formatted data as a response.

[0088] Output: Raw collected data (JSON format)

[0089] Step 2:

[0090] The server consolidates the collected data into a database.

[0091] Input: Output data from Step 1 (JSON format)

[0092] Specific operation: The server parses the received JSON data and inserts the data into the MySQL database by executing a query such as "INSERT INTO shelters (name, address, capacity) VALUES (...)".

[0093] Output: Merged database entries

[0094] Step 3:

[0095] The server processes and filters the data.

[0096] Input: Integrated database entries

[0097] What happens: The server runs SQL queries such as "SELECT DISTINCT FROM disaster_info" to remove duplicates, check for accuracy, and categorize important information.

[0098] Output: Processed and filtered data

[0099] Step 4:

[0100] The server publishes the processed data.

[0101] Input: Output data from step 3

[0102] Specific operation: The server uses WebSocket or HTTP API to deliver the latest information to the user device in real time. It maintains a connection at "ws: / / example.com / disaster-updates" and notifies the user when the data is updated.

[0103] Output: The latest data sent to the user device

[0104] Step 5:

[0105] The terminal visually displays the information to the user.

[0106] Input: Output data from step 4

[0107] Specific operation: The device uses HTML, CSS, and JavaScript to display the received information in the form of a map or graph. For example, " uses the Google Maps API to display evacuation shelter information.

[0108] Output: Information displayed visually on the user's screen

[0109] Step 6:

[0110] The device uses the generative AI model to answer the user's questions.

[0111] Input: User-entered question, generative AI model (e.g., ChatGPT)

[0112] How it works: When a user asks, "Where is the nearest evacuation shelter?", the device passes this question as a prompt to the generative AI model, which generates the best answer, and then presents the generated answer to the user.

[0113] Output: Answer from the generative AI model

[0114] Step 7:

[0115] The server analyzes the input information from the user.

[0116] Input: User-provided location information (latitude and longitude)

[0117] Specific operation: The server executes the query "SELECT FROM shelters ORDER BY distance FROM user's location LIMIT 1" to determine the best evacuation location.

[0118] Output: Analysis results (optimal evacuation location)

[0119] Step 8:

[0120] The server proposes optimal disaster response actions.

[0121] Input: Analysis results from step 7

[0122] Specific operation: The server uses the Google Maps API to calculate the shortest route from the current location to the nearest evacuation shelter and sends the result to the user in JSON format.

[0123] Output: Suggestion to the user (optimal evacuation route)

[0124] (Application example 1)

[0125] 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."

[0126] In recent years, with the increasing frequency of disasters, there is a demand for providing prompt and appropriate guidelines for action in the event of a disaster. However, current systems do not centralize the collection, processing, and provision of disaster information, making it particularly difficult to present specific guidelines for action to individual users. In addition, conventional methods for providing information interactively with users are limited and lack real-time capabilities. Furthermore, there is a lack of individualized responses based on the user's location information, making it difficult for users to take appropriate action quickly.

[0127] 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.

[0128] In this invention, the server includes means for collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information to a user in an interactive format, means for visually displaying the information in an easy-to-understand format, means for acquiring user location information, means for suggesting appropriate actions to the user based on the acquired location information and disaster information, and means for generating optimal answers to user queries using generative artificial intelligence. This makes it possible to centrally manage disaster information and support users in responding quickly and appropriately.

[0129] "Disaster information" refers to real-time data needed in the event of a disaster, such as the status of the disaster, evacuation shelter information, emergency alerts, and the status of supplies.

[0130] "Means for collection" refers to the interfaces and processes for obtaining disaster information in real time from various API endpoints and other sources.

[0131] "Processing and filtering measures" refers to the process of verifying the accuracy of collected disaster information, removing duplicate information, and classifying necessary information.

[0132] "Means for publishing" refers to the interface or medium by which the processed and filtered information is made accessible to users in real time.

[0133] "Means using generative artificial intelligence" refers to artificial intelligence technology that generates optimal answers to questions in order to provide information to users in an interactive format.

[0134] "Means for visual display" refers to technology that displays information in the form of text, graphs, illustrations, etc., making it easy for users to understand intuitively.

[0135] "Means for obtaining location information" refers to processes or devices that use GPS or other technologies to determine a user's current location.

[0136] "Means for suggesting actions" refers to the process of presenting users with guidelines for action, such as optimal evacuation routes and evacuation shelters, based on the acquired location information and collected disaster information.

[0137] "Means for generating optimal answers to queries" refers to generative artificial intelligence technology that generates the most appropriate answers to user questions based on real-time data.

[0138] This invention relates to a system that collects and processes disaster information in an integrated manner and provides users with appropriate action guidelines. This system consists of three main elements: a server, a terminal, and a user.

[0139] Server Features

[0140] 1. Collection of information

[0141] The server retrieves disaster information in real time from various API endpoints. This information includes evacuation shelter information, emergency alerts, and the status of supplies. This is done using HTTP requests.

[0142] 2. Processing and filtering of information

[0143] The server checks the accuracy of the collected information, removes duplicates, and classifies necessary information, allowing reliable disaster information to be integrated into the database.

[0144] 3. Disclosure of Information

[0145] The processed and filtered information is published in real time and made available to users via terminals and web applications.

[0146] 4. Utilizing location information

[0147] The server provides information on optimal evacuation routes and evacuation locations based on the location information sent by the user.

[0148] Device Features

[0149] 1. Visual information display

[0150] The terminal visually displays the information provided by the server in the form of text, graphs, illustrations, etc. This allows the user to intuitively understand the information they need.

[0151] 2. Interaction with generative AI

[0152] The device uses generative AI to provide information interactively with the user. When the user inputs a question into the device, the generative AI generates the optimal answer in real time and presents it to the user.

[0153] For example, if a user asks, "Where is the nearest evacuation shelter?", the device will provide the most suitable evacuation shelter based on real-time updated evacuation shelter information. An example of a prompt sentence is as follows:

[0154] Prompt statement:

[0155] Your current location is latitude 35.6895, longitude 139.6917. Where is the nearest evacuation shelter? Please provide the best information. Disaster information: [{'type': 'shelter', 'name': 'XX Elementary School', 'location': [35.6890, 139.6920], 'status': 'open', 'capacity': 200},...]

[0156] User Interaction

[0157] 1. Providing location information

[0158] Users can send their location information to the device, which is acquired using GPS.

[0159] 2. Enter your query

[0160] Users can input questions or queries into the device, which then uses generative artificial intelligence to generate optimal answers and present them to the user.

[0161] Hardware and software used

[0162] Hardware

[0163] Server: High-performance cloud servers and data centers are suitable.

[0164] Devices: Smartphones, tablets, computers, etc.

[0165] software

[0166] The requests library (Python) for processing HTTP requests

[0167] Geopy library (Python) for location information acquisition

[0168] Database management requires the use of database systems such as PostgreSQL and MySQL.

[0169] Uses OpenAI (registered trademark) API for generative artificial intelligence

[0170] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0171] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0172] Step 1:

[0173] The server obtains disaster information. Specifically, it sends HTTP requests to various API endpoints to collect data such as evacuation shelter information, emergency alerts, and supply status in real time. It receives the API endpoint URL as input and obtains various disaster information data as output.

[0174] Step 2:

[0175] The server processes and filters the collected information. Specifically, it checks the accuracy of the collected data, removes duplicate information, and classifies the necessary information. The input is the disaster information data obtained in step 1, and the output is the processed and filtered disaster information with high reliability.

[0176] Step 3:

[0177] The server stores the filtered information in a database, and simultaneously publishes this information in real time, making it accessible to devices and web applications. It receives processed disaster information data as input and stores it in a public database as output.

[0178] Step 4:

[0179] The cross-platform terminal obtains public disaster information from the server. Specifically, it uses the server's public API to obtain data in real time. It receives the server's public API endpoint as input and stores the disaster information locally as output.

[0180] Step 5:

[0181] The device visually displays the acquired information. Specifically, it displays disaster information in the form of text, graphs, illustrations, etc., allowing users to intuitively understand it. It receives the acquired disaster information as input and displays it on the UI as output.

[0182] Step 6:

[0183] A user inputs a question or query into the device, for example, "Where is the nearest evacuation shelter?" The input is the user's query text, and the device receives the query as output.

[0184] Step 7:

[0185] The device obtains the user's location information. Specifically, it uses the GPS function to determine the user's current location. It receives the user's permission and GPS function as input, and obtains the latitude and longitude location information as output.

[0186] Step 8:

[0187] The device sends a query to the generative AI to generate the optimal answer. Specifically, a prompt is generated based on the user query and location information, and the generative AI obtains the optimal answer. The input is the user query, location information, and the model settings of the generative AI, and the output is the generated answer text.

[0188] Example prompt sentence:

[0189] Your current location is latitude 35.6895, longitude 139.6917. Where is the nearest evacuation shelter? Please provide the best information. Disaster information: [{'type': 'shelter', 'name': 'XX Elementary School', 'location': [35.6890, 139.6920], 'status': 'open', 'capacity': 200},...]

[0190] Step 9:

[0191] The terminal provides the generated answer to the user. Specifically, the answer obtained from the generative AI is displayed on the screen. The input is the generated answer text, and the output is the display on the screen.

[0192] Step 10:

[0193] The user takes appropriate action based on the information provided. Specifically, they begin taking action based on the information received from the device, such as heading to an evacuation site or preparing necessary supplies. The input is the action guidelines provided by the device, and the output is the user's specific actions.

[0194] 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.

[0195] The present invention provides a system that collects disaster information in real time, processes and filters the information, and provides it to users in an appropriate format. This system also incorporates an emotion engine that recognizes the user's emotions, and provides information according to the user's emotions.

[0196] First, the server collects disaster information in real time from various API endpoints, including evacuation shelter information, emergency alerts, and the status of supplies. The server retrieves this information using HTTP requests and integrates it into a single database.

[0197] The server then processes and filters the collected information. First, it checks the accuracy of the information obtained and removes duplicate or unnecessary information. It also categorizes the information and prioritizes it as needed. This processed and filtered information is then made public in real time and made available to users via their devices or web applications.

[0198] The device visually displays the published information to the user. The visual display can include text information, graphs, illustrations, etc. This allows the user to intuitively understand the information they need. The device also has the ability to provide information interactively with the user using generative artificial intelligence. When the user inputs a question into the device, the generative artificial intelligence generates the most appropriate answer and presents it to the user. For example, in response to a question such as "Where is the nearest evacuation shelter?" the device will provide evacuation shelter information updated in real time.

[0199] Furthermore, the server analyzes the user's input information and suggests optimal disaster response actions. For example, if the user provides their current location information, the server can recommend the optimal evacuation route and evacuation site based on that information.

[0200] The present invention further combines an emotion engine to recognize a user's emotions and provide information according to the emotions. The emotion engine reads the emotions from the text or voice input by the user and adjusts the information provided based on the user's emotional state. For example, if the user is in a high stress state, the emotion engine provides information to reassure the user or advice on stress reduction.

[0201] As a concrete example, when an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes this information, filters out the necessary information, and makes it public. The device visually displays this information to the user, and the emotion engine recognizes the user's emotional state. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0202] If the emotion engine recognizes from the user's input that the user is feeling stressed, it will simultaneously provide information and advice to reduce the user's stress. In this way, the present invention centrally manages information needed in the event of a disaster, not only helping users respond quickly and appropriately, but also enabling flexible responses according to the user's emotional state.

[0203] The processing flow will be explained below.

[0204] Step 1:

[0205] The server collects disaster information such as evacuation shelter information, emergency alerts, and supply status in real time from various API endpoints. Specifically, it retrieves data from these sources using HTTP GET requests and integrates it into a single database.

[0206] Step 2:

[0207] The server processes and filters the collected information, first verifying the accuracy of the data obtained and removing duplicate or unnecessary information, then categorizing the information and prioritizing it as needed.

[0208] Step 3:

[0209] The server publishes the processed and filtered information in real time, and the collected information is made available to users through web applications and terminals.

[0210] Step 4:

[0211] The terminal visually displays the published information to the user, including text information, graphs, illustrations, etc. This allows the user to intuitively understand the required information.

[0212] Step 5:

[0213] Users can obtain the necessary information directly through their devices or enter specific questions, such as "Where is the nearest evacuation shelter?"

[0214] Step 6:

[0215] The device sends the user's question to a generative artificial intelligence that generates an optimal answer based on the user's input and real-time data.

[0216] Step 7:

[0217] The device displays the answer generated by the generative AI to the user, providing specific information such as, "The nearest evacuation shelter is XX. The current capacity is XX."

[0218] Step 8:

[0219] The server analyzes the information entered by the user and provides the optimal evacuation route and action guidelines. If the user provides location information, the server calculates the optimal evacuation route based on that information and presents it to the user via their device.

[0220] Step 9:

[0221] The device uses an emotion engine to recognize the user's emotions. The emotion engine reads emotions from the user's input text and voice.

[0222] Step 10:

[0223] The device adjusts the information provided based on the emotional state recognized by the emotion engine. For example, if the user is in a state of high stress, the device will provide information and advice to help reduce stress.

[0224] Step 11:

[0225] The emotion engine allows users to take the information presented to them and act safely and effectively, for example, providing evacuation route instructions in a calming tone and providing additional reassurance information as needed.

[0226] In this way, this system centrally manages the information needed in the event of a disaster, not only helping users respond quickly and appropriately, but also enabling flexible responses according to the user's emotional state.

[0227] Example 2

[0228] 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."

[0229] In modern society, there is a growing need to quickly and accurately collect disaster information and provide it to users in an appropriate format. However, conventional systems take time to collect and process information, and are unable to provide information that reflects the user's emotions, making it difficult to respond appropriately in the event of a disaster. The present invention aims to solve these problems by providing a system that can provide accurate disaster information in real time while flexibly responding to the user's emotions.

[0230] 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.

[0231] In this invention, the server includes means for collecting disaster information in real time, means for processing and filtering the collected information, and means for publishing the processed and filtered information, thereby enabling prompt and accurate collection of disaster information to be provided to users and enabling flexible response.

[0232] Furthermore, the system includes means for using generative artificial intelligence to provide information to users in an interactive format, means for visually displaying information in an easy-to-understand format, and means for recognizing the user's emotions and adjusting the information according to the emotions. This allows users to obtain optimal disaster information in real time and respond according to their emotions, thereby minimizing confusion during a disaster.

[0233] "Disaster information" refers to information about natural disasters and man-made disasters, including emergency alerts, evacuation shelter information, and the status of supplies.

[0234] "Means of collecting information in real time" refers to a method for instantly obtaining disaster information from various API endpoints, and refers to the use of protocols such as HTTP requests.

[0235] "Processing and filtering measures" refers to methods for reviewing and organizing collected information by accuracy, redundancy, and necessity, and removing unnecessary information.

[0236] "Means of publication" refers to the method by which the processed and filtered information is made available on the Internet in a form accessible to users.

[0237] "Generative artificial intelligence" refers to algorithms and models used to generate appropriate answers to user questions.

[0238] "Visual display means" refers to methods of displaying information in a way that is easy for users to understand, such as by using graphs, maps, text, etc.

[0239] "Means for recognizing emotions" refers to technology that analyzes the emotional state of a user at that time from the text or voice input provided by the user.

[0240] The term "means for adjusting information according to emotions" refers to a method for changing the content or format of information provided based on the recognized emotional state of the user.

[0241] "Means for providing guidelines for action" refers to methods for helping users take appropriate actions based on publicly available disaster information.

[0242] The present invention is a system that collects disaster information in real time and provides users with processed and filtered information. This system is designed to recognize the user's emotions and provide information according to the emotions. Specific embodiments for implementing the present invention will be described below.

[0243] First, the server collects disaster information in real time from various API endpoints. The server uses a high-performance server machine as its hardware and executes a script that sends HTTP requests as its software. For example, an API request from the Japan Meteorological Agency or a local government might be sent as follows:

[0244] GET / api / disaster / latest HTTP / 1.1

[0245] Host: weatherapi.com

[0246] The server then processes and integrates the acquired disaster information into a database, which can be in SQL or NoSQL format, for example. After the data is collected, the server runs algorithms to verify the accuracy of the information and filter out duplicate or incorrect information. This is also where the information is categorized and prioritized.

[0247] The collected and processed information is made available in real time and visually displayed to users via devices such as smartphones, tablets, and PCs. The software on the devices visualizes the information in an easy-to-understand way using text, pinpoints on maps, graphs, and more.

[0248] Users can check disaster information updated in real time on their devices. Furthermore, they can ask questions in an interactive format using generative AI to obtain optimal answers. For example, if a user types a question like, "Where is the nearest evacuation shelter?", the generative AI will generate an answer based on real-time data and provide it to the user.

[0249] The server proposes optimal disaster response actions based on the information entered by the user. If the user provides their current location information, the server recommends optimal evacuation routes and evacuation locations based on that information. Furthermore, it uses an emotion engine to recognize the user's emotions and provide information appropriate to their emotions. For example, if the server recognizes that the user is in a state of high stress, it will provide messages and advice to reassure the user.

[0250] Specific examples

[0251] When an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes the information, filters out the necessary information, and makes it public. The device visually displays the information to the user, and the emotion engine recognizes the user's emotional state. For example, if a user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0252] Below are some example prompts to be input to the generative AI model:

[0253] Input: I'm feeling very anxious about the current situation. Do you have any advice to help me feel more at ease?

[0254] Generated AI prompt: This user is in a state of high stress. Please provide information and advice to help them feel more at ease.

[0255] Output: First, take a deep breath and stay calm. Also, you will be safe if you evacuate to the XX Community Center.

[0256] In this way, the present invention is a system that not only manages disaster information in an integrated manner and supports users in responding quickly and appropriately, but also enables flexible responses according to the user's emotional state.

[0257] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0258] Program processing flow

[0259] Step 1:

[0260] The server collects disaster information in real time from various API endpoints.

[0261] Specifically, it sends HTTP requests to retrieve data. For example, it retrieves earthquake alerts from the Japan Meteorological Agency's API, and collects information on evacuation centers and the status of supplies from local government APIs.

[0262] Input: Each API endpoint

[0263] Data processing: Sending HTTP requests and receiving responses from each API

[0264] Output: Acquired disaster information

[0265] GET / api / disaster / latest HTTP / 1.1

[0266] Host: weatherapi.com

[0267] Step 2:

[0268] The server integrates the collected disaster information into a database.

[0269] Specifically, the information is stored in a SQL or NoSQL database, and the collected data is de-duplicated and checked for accuracy.

[0270] Input: Collected disaster information

[0271] Data processing: Deleting duplicates, checking accuracy

[0272] Output: Integrated disaster information database

[0273] Disaster information database: evacuation shelter information, earthquake alerts, supply status

[0274] Step 3:

[0275] The server publishes the processed and filtered information.

[0276] Specifically, it provides information to web applications and mobile devices in real time.

[0277] Input: Integrated disaster information database

[0278] Data processing: filtering information and dividing it into categories (shelters, emergency alerts, supply status)

[0279] Output: Disaster information released

[0280] HTML

[0281]

[0282] <h2> Latest evacuation shelter information< / h2>

[0283]

[0284] Shelter 1: Address XYZ, Capacity 100, Spaces 50

[0285] Shelter 2: Address ABC, Capacity 200, Vacant seats 150

[0286]

[0287]

[0288] Step 4:

[0289] The terminal visually displays the published information to the user.

[0290] Specifically, it performs operations such as displaying text information and pinpointing the location of evacuation shelters on a map.

[0291] Input: Disaster information released

[0292] Data processing: Map generation, text information display

[0293] Output: Visually displayed disaster information

[0294] Pin on map: Shelter 1: Address XYZ, Capacity 100, Space 50

[0295] Step 5:

[0296] The terminal uses generative artificial intelligence to provide information to the user in an interactive format.

[0297] When a user enters a question, the generative artificial intelligence generates the best answer based on that question and presents it to the user.

[0298] Input: User question (e.g., "Where is the nearest evacuation shelter?")

[0299] Data processing: Answer generation using generative AI

[0300] Output: Best answer (e.g. "The nearest evacuation shelter is XX Community Center.")

[0301] User: "Where is the nearest evacuation shelter?"

[0302] AI: "The nearest evacuation shelter is the XX Community Center. The address is XYZ, and there are currently 50 spaces available."

[0303] Step 6:

[0304] The server uses an emotion engine to recognize the user's emotion.

[0305] Specifically, the system analyzes the emotional state of the user from the text and voice input and provides the necessary information.

[0306] Input: User text and voice input

[0307] Data processing: Emotion analysis using an emotion engine

[0308] Output: Information or advice based on the perceived emotional state

[0309] Input: I'm feeling very anxious about the current situation. Do you have any advice to help me feel more at ease?

[0310] Generated AI prompt: This user is in a state of high stress. Please provide information and advice to help them feel more at ease.

[0311] Output: First, take a deep breath and stay calm. Also, you will be safe if you evacuate to the XX Community Center.

[0312] Through this series of steps, the system is able to quickly and accurately collect disaster information, provide it in a format that is easy for users to understand, and even assist users in taking appropriate action based on their emotions.

[0313] (Application example 2)

[0314] 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."

[0315] In order for autonomous vehicles to respond appropriately in the event of a disaster, they need to collect accurate disaster information in real time and respond appropriately based on that information. However, typical disaster information systems take time to integrate information and do not provide information that takes users' emotions into consideration. As a result, users are not provided with enough information to make the right decisions, which can cause stress and confusion.

[0316] The identification processing 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 collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information to the user in an interactive format, means including an emotion engine for recognizing the user's emotions and providing information according to the emotions, means for using a navigation system to provide an optimal route based on vehicle position information, and means for visually displaying information in an easy-to-understand format. This enables an autonomous vehicle to obtain accurate disaster information in real time, provide appropriate information according to the user's emotional state, and suggest an optimal evacuation route.

[0317] "Disaster information" refers to information about natural disasters and man-made disasters such as earthquakes, tsunamis, floods, and fires.

[0318] "Real-time" refers to information being processed and provided immediately at the moment it occurs or shortly thereafter.

[0319] "Collection" refers to obtaining data from various sources and integrating it into one system.

[0320] "Processing and filtering" refers to the process of analyzing collected information, extracting useful information, and removing unnecessary information.

[0321] "Publishing" refers to making the processed and filtered information widely available.

[0322] "Generative AI" refers to AI technology that can generate and provide optimal answers to questions and requests from users.

[0323] An "emotion engine" refers to technology that reads emotions from user input and adjusts the information provided accordingly.

[0324] A "navigation system" is a system that calculates and provides the optimal route based on the current location.

[0325] "Visually displaying" refers to presenting information to a user in the form of text, graphics, images, etc.

[0326] In this invention, a disaster information system is installed in an autonomous vehicle, and disaster information is collected in real time, filtered, and processed to provide appropriate instructions to the user in the vehicle. The system utilizes generative artificial intelligence and an emotion engine to provide information according to the user's emotions. Specific embodiments are described below.

[0327] The server collects disaster information in real time from multiple API endpoints, including evacuation shelter information, emergency alerts, and supply status. The server retrieves this information using HTTP requests and consolidates it into a single database. The collected information is then sent to the autonomous vehicle in real time.

[0328] The device processes and filters the acquired information. First, it checks the accuracy of the collected information and removes duplicate or unnecessary information. Next, it categorizes the information and prioritizes it as needed. The processed and filtered information is then visually displayed to the user in real time. This display can include text information, graphs, and figures.

[0329] Generative AI generates optimal answers based on user questions. For example, in response to the question, "Where is the nearest evacuation shelter?", it provides information on the nearest evacuation shelter based on real-time data. In addition, if a user inputs the question, "Please tell me the evacuation route," the navigation system of an autonomous vehicle will calculate and display the optimal evacuation route based on the vehicle's current location information.

[0330] Furthermore, the emotion engine recognizes emotions from the text and voice input of the user. If it detects that the user is in a state of high stress, the emotion engine will provide information to calm the user and advice on how to reduce stress. For example, in response to a statement such as "I don't know what to do," it will provide a message of kindness and reassurance.

[0331] For example, when an earthquake occurs, the server rapidly collects emergency alerts and evacuation shelter information from multiple sources. The device then processes and filters this information and visually displays it to the user in the vehicle. When the user asks the device, "What is the best evacuation route?", the navigation system calculates the optimal evacuation route and presents it based on real-time data. If the emotion engine detects high stress levels in the user's input, it provides the information along with a reassuring message.

[0332] Prompt Sentence Examples

[0333] 1. Obtain disaster information:

[0334] Please collect the latest disaster information from the API endpoint.

[0335] 2. Emotion recognition:

[0336] Identify the sentiment based on the text entered by the user.

[0337] 3. Providing optimal evacuation routes:

[0338] Provide the best evacuation route based on your current location.

[0339] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0340] Step 1:

[0341] The server collects disaster information from various API endpoints. It uses HTTP requests to obtain data such as evacuation shelter information, emergency alerts, and supply status. The obtained data is integrated into a single database. The input is the various API endpoints, and the output is the integrated database.

[0342] Step 2:

[0343] The server processes and filters the collected information. It removes duplicate and unnecessary information and checks for accuracy. Information is categorized and prioritized as needed. The input is the consolidated database and the output is the filtered information.

[0344] Step 3:

[0345] The processed and filtered information is published in real time. The server sends the processed data to the autonomous vehicle's terminal. The input is the filtered information, and the output is the information sent to the terminal.

[0346] Step 4:

[0347] The terminal visually displays the information sent from the server. It uses text information, graphs, figures, etc. to present the necessary information to the user in an easy-to-understand format. The input is the information sent from the server, and the output is the information displayed on the visual display.

[0348] Step 5:

[0349] A user inputs a question to a terminal. For example, the user inputs a question such as "Where is the nearest evacuation shelter?" The input is the user's question, and the output is the question passed to the terminal via the user interface.

[0350] Step 6:

[0351] The device's generative artificial intelligence generates the best answer based on the user's question. Depending on the content of the question, it searches a real-time database and generates an answer. The input is the user's question and real-time data, and the output is the generated answer.

[0352] Step 7:

[0353] The device's emotion engine recognizes emotions from user input information. It analyzes the text and voice entered by the user and determines their emotional state. The input is the user's input information, and the output is the emotion recognition result.

[0354] Step 8:

[0355] Based on the emotion recognition results, generative AI provides information according to the emotional state. If a high stress state is recognized, a message or advice to reassure the user is added. The input is the emotion recognition result and the generated answer, and the output is an information message that takes emotion into consideration.

[0356] Step 9:

[0357] The navigation system provides the optimal evacuation route based on the vehicle's current location information. It combines the current location and information on nearby evacuation shelters to calculate the optimal route and present it to the user. The input is the current location information and information on nearby evacuation shelters, and the output is the optimal evacuation route.

[0358] 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.

[0359] 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 (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.

[0360] 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.

[0361] [Second embodiment]

[0362] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0363] 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.

[0364] 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).

[0365] 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.

[0366] 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.

[0367] 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).

[0368] 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. 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.

[0369] 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.

[0370] 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.

[0371] 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.

[0372] In the smart glasses 214, 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.

[0373] 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."

[0374] This invention relates to a system that collects and processes disaster information in an integrated manner and provides users with appropriate action guidelines. This system is composed of three main elements: a server, a terminal, and a user.

[0375] First, the server collects disaster information in real time from various API endpoints, such as evacuation shelter information, emergency alerts, and the status of supplies. The server retrieves data from these sources using HTTP requests and integrates the collected information into a single database.

[0376] The server then processes and filters the collected information, including verifying data accuracy, removing duplicate information, and categorizing necessary information. The processed and filtered information is then published in real time by the server and made available to users via their devices or web applications.

[0377] The device visually displays the published information to the user. The display includes text, graphs, illustrations, etc., allowing the user to intuitively understand the information they need. The device also has the ability to provide information interactively with the user using generative artificial intelligence. When the user inputs a question into the device, the generative artificial intelligence generates the most appropriate answer and presents it to the user. For example, in response to a question such as "Where is the nearest evacuation shelter?" the device will provide updated evacuation shelter information in real time.

[0378] The server also analyzes user input and suggests optimal disaster response actions. For example, if a user provides their current location, the server will recommend the optimal evacuation route and evacuation shelter based on that location.

[0379] As a concrete example, when an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes this information, filters out the necessary information, and makes it public. The device visually displays this information to the user and provides the optimal course of action based on the user's situation. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0380] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0381] The processing flow will be explained below.

[0382] Step 1:

[0383] The server collects disaster information from various API endpoints. Specifically, it uses HTTP GET requests to retrieve data from multiple sources, such as evacuation shelter information, emergency alerts, and supply status. This allows the necessary information to be integrated into a single database.

[0384] Step 2:

[0385] The server processes and filters the collected information, checking the accuracy of the data obtained and removing duplicate or unnecessary information. It also categorizes the information and prioritizes it as needed, ensuring that the most important information is readily available.

[0386] Step 3:

[0387] The server publishes the processed and filtered information in real time, and the collected information is made available to users through web applications and terminals.

[0388] Step 4:

[0389] The terminal visually displays the published information to the user, and the visual display can include various formats such as text information, graphs, illustrations, etc. This allows the user to intuitively understand the required information.

[0390] Step 5:

[0391] The user can obtain necessary information or input specific questions through the terminal. For example, the user can input a question such as "Where is the nearest evacuation shelter?"

[0392] Step 6:

[0393] The device sends the user's question to a generative artificial intelligence that generates an optimal answer based on the user's input and real-time data.

[0394] Step 7:

[0395] The device displays the answer generated by the generative AI to the user, providing specific information such as, "The nearest evacuation shelter is XX. The current capacity is XX."

[0396] Step 8:

[0397] The server analyzes the information entered by the user and provides the optimal evacuation route and action guidelines. If the user provides location information, the server calculates the optimal evacuation route based on that information and presents it to the user via their device.

[0398] In this way, this system centrally manages the information needed in the event of a disaster, helping users to respond quickly and appropriately.

[0399] Example 1

[0400] 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."

[0401] When a disaster occurs, there is a need for an efficient method to collect necessary information in real time from multiple sources, process and filter it appropriately, and provide it to users quickly and accurately. There is also a need for a method to display information in a format that is intuitively easy for users to understand, and to respond appropriately to user inquiries using generative artificial intelligence. Conventional technologies have difficulty meeting these requirements, and the problem is that it takes a long time to collect and provide information.

[0402] 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.

[0403] In this invention, the server includes means for collecting disaster information in real time using communication technology, means for importing the collected information into an integrated database and analyzing it, communication means for providing aggregated and filtered data to user devices, means for responding to user inquiries using generative artificial intelligence, and means for visually displaying information so that users can intuitively understand it. This makes it possible to collect and process information necessary in the event of a disaster in real time and provide it to users quickly and accurately.

[0404] "Disaster information" refers to data such as evacuation shelter information, emergency alerts, and the status of supplies related to natural disasters such as earthquakes, floods, and typhoons.

[0405] "Communication technology" refers to technology for sending and receiving data using HTTP requests, WebSockets, API endpoints, etc.

[0406] An "integrated database" refers to a database system that centrally manages and stores data collected from multiple sources.

[0407] "Analysis" refers to the process of verifying the accuracy of collected data, removing duplicate information, and classifying the necessary information.

[0408] "User device" refers to a terminal device, such as a PC, smartphone, or tablet, that a user uses to receive and operate information.

[0409] "Generative AI" refers to AI technology that generates responses in natural language to user inquiries.

[0410] "Visually displaying" refers to presenting information to users in a way that they can intuitively understand, using text information, graphs, illustrations, maps, etc.

[0411] This invention relates to a system that collects disaster information in real time and provides users with prompt and accurate action guidelines. This system consists of three main elements: a server, a terminal, and a user.

[0412] First, the server collects disaster information from multiple sources. Specifically, it uses HTTP requests to obtain information on evacuation shelters, emergency alerts, and the status of supplies from government and private API endpoints (e.g., "https: / / api.disasterinfo.gov / shelters" and "https: / / api.weatheragency.jp / alerts"). The collected information is then stored in an integrated database such as MySQL or PostgreSQL.

[0413] The server then analyzes the information stored in the database, which includes verifying the accuracy of the data, removing duplicate information, and categorizing the necessary information. For example, the server may run SQL queries to remove duplicate data and categorize the information by importance.

[0414] The analyzed and filtered data is provided to the user device in real time. The server uses WebSocket or HTTP API to deliver the latest information to the front end. The user device visually displays the received information using HTML, CSS, and JavaScript. For example, it can mark the locations of evacuation shelters on a map or display emergency alerts as notification popups.

[0415] Furthermore, the device uses generative artificial intelligence to generate responses to user questions. For example, if a user asks, "Where is the nearest evacuation shelter?", the device uses a generative AI model (e.g., ChatGPT) to generate an answer and present it to the user.

[0416] The server also analyzes input information (e.g., location information) provided by the user to determine the optimal disaster response action. The server analyzes the latitude and longitude information of the current location, calculates the shortest route using Google Maps API, etc., and presents the results to the user.

[0417] For example, when an earthquake occurs, the server quickly collects emergency alerts and evacuation shelter information from multiple sources, filters the necessary information, and provides it to the user's device. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0418] An example of a prompt would be, "In the event of a large-scale earthquake, collect emergency alerts and evacuation shelter information from government APIs and the Japan Meteorological Agency APIs. Then, integrate the collected information into a database, remove duplicate information, and verify its accuracy before providing it to users. Also, when users ask about the nearest evacuation shelter or evacuation route, use generative artificial intelligence to generate an appropriate answer."

[0419] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0420] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0421] Step 1:

[0422] The server collects disaster information.

[0423] Input: Multiple API endpoints (e.g., "https: / / api.disasterinfo.gov / shelters", "https: / / api.weatheragency.jp / alerts")

[0424] Specific operation: The server sends an HTTP GET request to each endpoint and receives JSON formatted data as a response.

[0425] Output: Raw collected data (JSON format)

[0426] Step 2:

[0427] The server consolidates the collected data into a database.

[0428] Input: Output data from Step 1 (JSON format)

[0429] Specific operation: The server parses the received JSON data and inserts the data into the MySQL database by executing a query such as "INSERT INTO shelters (name, address, capacity) VALUES (...)".

[0430] Output: Merged database entries

[0431] Step 3:

[0432] The server processes and filters the data.

[0433] Input: Integrated database entries

[0434] What happens: The server runs SQL queries such as "SELECT DISTINCT FROM disaster_info" to remove duplicates, check for accuracy, and categorize important information.

[0435] Output: Processed and filtered data

[0436] Step 4:

[0437] The server publishes the processed data.

[0438] Input: Output data from step 3

[0439] Specific operation: The server uses WebSocket or HTTP API to deliver the latest information to the user device in real time. It maintains a connection at "ws: / / example.com / disaster-updates" and notifies the user when the data is updated.

[0440] Output: The latest data sent to the user device

[0441] Step 5:

[0442] The terminal visually displays the information to the user.

[0443] Input: Output data from step 4

[0444] Specific operation: The device uses HTML, CSS, and JavaScript to display the received information in the form of a map or graph. For example, " uses the Google Maps API to display evacuation shelter information.

[0445] Output: Information displayed visually on the user's screen

[0446] Step 6:

[0447] The device uses the generative AI model to answer the user's questions.

[0448] Input: User-entered question, generative AI model (e.g., ChatGPT)

[0449] How it works: When a user asks, "Where is the nearest evacuation shelter?", the device passes this question as a prompt to the generative AI model, which generates the best answer, and then presents the generated answer to the user.

[0450] Output: Answer from the generative AI model

[0451] Step 7:

[0452] The server analyzes the input information from the user.

[0453] Input: User-provided location information (latitude and longitude)

[0454] Specific operation: The server executes the query "SELECT FROM shelters ORDER BY distance FROM user's location LIMIT 1" to determine the best evacuation location.

[0455] Output: Analysis results (optimal evacuation location)

[0456] Step 8:

[0457] The server proposes optimal disaster response actions.

[0458] Input: Analysis results from step 7

[0459] Specific operation: The server uses the Google Maps API to calculate the shortest route from the current location to the nearest evacuation shelter and sends the result to the user in JSON format.

[0460] Output: Suggestion to the user (optimal evacuation route)

[0461] (Application example 1)

[0462] 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."

[0463] In recent years, with the increasing frequency of disasters, there is a demand for providing prompt and appropriate guidelines for action in the event of a disaster. However, current systems do not centralize the collection, processing, and provision of disaster information, making it particularly difficult to present specific guidelines for action to individual users. In addition, conventional methods for providing information interactively with users are limited and lack real-time capabilities. Furthermore, there is a lack of individualized responses based on the user's location information, making it difficult for users to take appropriate action quickly.

[0464] 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.

[0465] In this invention, the server includes means for collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information to a user in an interactive format, means for visually displaying the information in an easy-to-understand format, means for acquiring user location information, means for suggesting appropriate actions to the user based on the acquired location information and disaster information, and means for generating optimal answers to user queries using generative artificial intelligence. This makes it possible to centrally manage disaster information and support users in responding quickly and appropriately.

[0466] "Disaster information" refers to real-time data needed in the event of a disaster, such as the status of the disaster, evacuation shelter information, emergency alerts, and the status of supplies.

[0467] "Means for collection" refers to the interfaces and processes for obtaining disaster information in real time from various API endpoints and other sources.

[0468] "Processing and filtering measures" refers to the process of verifying the accuracy of collected disaster information, removing duplicate information, and classifying necessary information.

[0469] "Means for publishing" refers to the interface or medium by which the processed and filtered information is made accessible to users in real time.

[0470] "Means using generative artificial intelligence" refers to artificial intelligence technology that generates optimal answers to questions in order to provide information to users in an interactive format.

[0471] "Means for visual display" refers to technology that displays information in the form of text, graphs, illustrations, etc., making it easy for users to understand intuitively.

[0472] "Means for obtaining location information" refers to processes or devices that use GPS or other technologies to determine a user's current location.

[0473] "Means for suggesting actions" refers to the process of presenting users with guidelines for action, such as optimal evacuation routes and evacuation shelters, based on the acquired location information and collected disaster information.

[0474] "Means for generating optimal answers to queries" refers to generative artificial intelligence technology that generates the most appropriate answers to user questions based on real-time data.

[0475] This invention relates to a system that collects and processes disaster information in an integrated manner and provides users with appropriate action guidelines. This system consists of three main elements: a server, a terminal, and a user.

[0476] Server Features

[0477] 1. Collection of information

[0478] The server retrieves disaster information in real time from various API endpoints. This information includes evacuation shelter information, emergency alerts, and the status of supplies. This is done using HTTP requests.

[0479] 2. Processing and filtering of information

[0480] The server checks the accuracy of the collected information, removes duplicates, and classifies necessary information, allowing reliable disaster information to be integrated into the database.

[0481] 3. Disclosure of Information

[0482] The processed and filtered information is published in real time and made available to users via terminals and web applications.

[0483] 4. Utilizing location information

[0484] The server provides information on optimal evacuation routes and evacuation locations based on the location information sent by the user.

[0485] Device Features

[0486] 1. Visual information display

[0487] The terminal visually displays the information provided by the server in the form of text, graphs, illustrations, etc. This allows the user to intuitively understand the information they need.

[0488] 2. Interaction with generative AI

[0489] The device uses generative AI to provide information interactively with the user. When the user inputs a question into the device, the generative AI generates the optimal answer in real time and presents it to the user.

[0490] For example, if a user asks, "Where is the nearest evacuation shelter?", the device will provide the most suitable evacuation shelter based on real-time updated evacuation shelter information. An example of a prompt sentence is as follows:

[0491] Prompt statement:

[0492] Your current location is latitude 35.6895, longitude 139.6917. Where is the nearest evacuation shelter? Please provide the best information. Disaster information: [{'type': 'shelter', 'name': 'XX Elementary School', 'location': [35.6890, 139.6920], 'status': 'open', 'capacity': 200},...]

[0493] User Interaction

[0494] 1. Providing location information

[0495] Users can send their location information to the device, which is acquired using GPS.

[0496] 2. Enter your query

[0497] Users can input questions or queries into the device, which then uses generative artificial intelligence to generate optimal answers and present them to the user.

[0498] Hardware and software used

[0499] Hardware

[0500] Server: High-performance cloud servers and data centers are suitable.

[0501] Devices: Smartphones, tablets, computers, etc.

[0502] software

[0503] The requests library (Python) for processing HTTP requests

[0504] Geopy library (Python) for location information acquisition

[0505] Database management requires the use of database systems such as PostgreSQL and MySQL.

[0506] Uses OpenAI API for generative artificial intelligence

[0507] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0508] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0509] Step 1:

[0510] The server obtains disaster information. Specifically, it sends HTTP requests to various API endpoints to collect data such as evacuation shelter information, emergency alerts, and supply status in real time. It receives the API endpoint URL as input and obtains various disaster information data as output.

[0511] Step 2:

[0512] The server processes and filters the collected information. Specifically, it checks the accuracy of the collected data, removes duplicate information, and classifies the necessary information. The input is the disaster information data obtained in step 1, and the output is the processed and filtered disaster information with high reliability.

[0513] Step 3:

[0514] The server stores the filtered information in a database, and simultaneously publishes this information in real time, making it accessible to devices and web applications. It receives processed disaster information data as input and stores it in a public database as output.

[0515] Step 4:

[0516] The cross-platform terminal obtains public disaster information from the server. Specifically, it uses the server's public API to obtain data in real time. It receives the server's public API endpoint as input and stores the disaster information locally as output.

[0517] Step 5:

[0518] The device visually displays the acquired information. Specifically, it displays disaster information in the form of text, graphs, illustrations, etc., allowing users to intuitively understand it. It receives the acquired disaster information as input and displays it on the UI as output.

[0519] Step 6:

[0520] A user inputs a question or query into the device, for example, "Where is the nearest evacuation shelter?" The input is the user's query text, and the device receives the query as output.

[0521] Step 7:

[0522] The device obtains the user's location information. Specifically, it uses the GPS function to determine the user's current location. It receives the user's permission and GPS function as input, and obtains the latitude and longitude location information as output.

[0523] Step 8:

[0524] The device sends a query to the generative AI to generate the optimal answer. Specifically, a prompt is generated based on the user query and location information, and the generative AI obtains the optimal answer. The input is the user query, location information, and the model settings of the generative AI, and the output is the generated answer text.

[0525] Example prompt sentence:

[0526] Your current location is latitude 35.6895, longitude 139.6917. Where is the nearest evacuation shelter? Please provide the best information. Disaster information: [{'type': 'shelter', 'name': 'XX Elementary School', 'location': [35.6890, 139.6920], 'status': 'open', 'capacity': 200},...]

[0527] Step 9:

[0528] The terminal provides the generated answer to the user. Specifically, the answer obtained from the generative AI is displayed on the screen. The input is the generated answer text, and the output is the display on the screen.

[0529] Step 10:

[0530] The user takes appropriate action based on the information provided. Specifically, they begin taking action based on the information received from the device, such as heading to an evacuation site or preparing necessary supplies. The input is the action guidelines provided by the device, and the output is the user's specific actions.

[0531] 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.

[0532] The present invention provides a system that collects disaster information in real time, processes and filters the information, and provides it to users in an appropriate format. This system also incorporates an emotion engine that recognizes the user's emotions, and provides information according to the user's emotions.

[0533] First, the server collects disaster information in real time from various API endpoints, including evacuation shelter information, emergency alerts, and the status of supplies. The server retrieves this information using HTTP requests and integrates it into a single database.

[0534] The server then processes and filters the collected information. First, it checks the accuracy of the information obtained and removes duplicate or unnecessary information. It also categorizes the information and prioritizes it as needed. This processed and filtered information is then made public in real time and made available to users via their devices or web applications.

[0535] The device visually displays the published information to the user. The visual display can include text information, graphs, illustrations, etc. This allows the user to intuitively understand the information they need. The device also has the ability to provide information interactively with the user using generative artificial intelligence. When the user inputs a question into the device, the generative artificial intelligence generates the most appropriate answer and presents it to the user. For example, in response to a question such as "Where is the nearest evacuation shelter?" the device will provide evacuation shelter information updated in real time.

[0536] Furthermore, the server analyzes the user's input information and suggests optimal disaster response actions. For example, if the user provides their current location information, the server can recommend the optimal evacuation route and evacuation site based on that information.

[0537] The present invention further combines an emotion engine to recognize a user's emotions and provide information according to the emotions. The emotion engine reads the emotions from the text or voice input by the user and adjusts the information provided based on the user's emotional state. For example, if the user is in a high stress state, the emotion engine provides information to reassure the user or advice on stress reduction.

[0538] As a concrete example, when an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes this information, filters out the necessary information, and makes it public. The device visually displays this information to the user, and the emotion engine recognizes the user's emotional state. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0539] If the emotion engine recognizes from the user's input that the user is feeling stressed, it will simultaneously provide information and advice to reduce the user's stress. In this way, the present invention centrally manages information needed in the event of a disaster, not only helping users respond quickly and appropriately, but also enabling flexible responses according to the user's emotional state.

[0540] The processing flow will be explained below.

[0541] Step 1:

[0542] The server collects disaster information such as evacuation shelter information, emergency alerts, and supply status in real time from various API endpoints. Specifically, it retrieves data from these sources using HTTP GET requests and integrates it into a single database.

[0543] Step 2:

[0544] The server processes and filters the collected information, first verifying the accuracy of the data obtained and removing duplicate or unnecessary information, then categorizing the information and prioritizing it as needed.

[0545] Step 3:

[0546] The server publishes the processed and filtered information in real time, and the collected information is made available to users through web applications and terminals.

[0547] Step 4:

[0548] The terminal visually displays the published information to the user, including text information, graphs, illustrations, etc. This allows the user to intuitively understand the required information.

[0549] Step 5:

[0550] Users can obtain the necessary information directly through their devices or enter specific questions, such as "Where is the nearest evacuation shelter?"

[0551] Step 6:

[0552] The device sends the user's question to a generative artificial intelligence that generates an optimal answer based on the user's input and real-time data.

[0553] Step 7:

[0554] The device displays the answer generated by the generative AI to the user, providing specific information such as, "The nearest evacuation shelter is XX. The current capacity is XX."

[0555] Step 8:

[0556] The server analyzes the information entered by the user and provides the optimal evacuation route and action guidelines. If the user provides location information, the server calculates the optimal evacuation route based on that information and presents it to the user via their device.

[0557] Step 9:

[0558] The device uses an emotion engine to recognize the user's emotions. The emotion engine reads emotions from the user's input text and voice.

[0559] Step 10:

[0560] The device adjusts the information provided based on the emotional state recognized by the emotion engine. For example, if the user is in a state of high stress, the device will provide information and advice to help reduce stress.

[0561] Step 11:

[0562] The emotion engine allows users to take the information presented to them and act safely and effectively, for example, providing evacuation route instructions in a calming tone and providing additional reassurance information as needed.

[0563] In this way, this system centrally manages the information needed in the event of a disaster, not only helping users respond quickly and appropriately, but also enabling flexible responses according to the user's emotional state.

[0564] Example 2

[0565] 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."

[0566] In modern society, there is a growing need to quickly and accurately collect disaster information and provide it to users in an appropriate format. However, conventional systems take time to collect and process information, and are unable to provide information that reflects the user's emotions, making it difficult to respond appropriately in the event of a disaster. The present invention aims to solve these problems by providing a system that can provide accurate disaster information in real time while flexibly responding to the user's emotions.

[0567] 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.

[0568] In this invention, the server includes means for collecting disaster information in real time, means for processing and filtering the collected information, and means for publishing the processed and filtered information, thereby enabling prompt and accurate collection of disaster information to be provided to users and enabling flexible response.

[0569] Furthermore, the system includes means for using generative artificial intelligence to provide information to users in an interactive format, means for visually displaying information in an easy-to-understand format, and means for recognizing the user's emotions and adjusting the information according to the emotions. This allows users to obtain optimal disaster information in real time and respond according to their emotions, thereby minimizing confusion during a disaster.

[0570] "Disaster information" refers to information about natural disasters and man-made disasters, including emergency alerts, evacuation shelter information, and the status of supplies.

[0571] "Means of collecting information in real time" refers to a method for instantly obtaining disaster information from various API endpoints, and refers to the use of protocols such as HTTP requests.

[0572] "Processing and filtering measures" refers to methods for reviewing and organizing collected information by accuracy, redundancy, and necessity, and removing unnecessary information.

[0573] "Means of publication" refers to the method by which the processed and filtered information is made available on the Internet in a form accessible to users.

[0574] "Generative artificial intelligence" refers to algorithms and models used to generate appropriate answers to user questions.

[0575] "Visual display means" refers to methods of displaying information in a way that is easy for users to understand, such as by using graphs, maps, text, etc.

[0576] "Means for recognizing emotions" refers to technology that analyzes the emotional state of a user at that time from the text or voice input provided by the user.

[0577] The term "means for adjusting information according to emotions" refers to a method for changing the content or format of information provided based on the recognized emotional state of the user.

[0578] "Means for providing guidelines for action" refers to methods for helping users take appropriate actions based on publicly available disaster information.

[0579] The present invention is a system that collects disaster information in real time and provides users with processed and filtered information. This system is designed to recognize the user's emotions and provide information according to the emotions. Specific embodiments for implementing the present invention will be described below.

[0580] First, the server collects disaster information in real time from various API endpoints. The server uses a high-performance server machine as its hardware and executes a script that sends HTTP requests as its software. For example, an API request from the Japan Meteorological Agency or a local government might be sent as follows:

[0581] GET / api / disaster / latest HTTP / 1.1

[0582] Host: weatherapi.com

[0583] The server then processes and integrates the acquired disaster information into a database, which can be in SQL or NoSQL format, for example. After the data is collected, the server runs algorithms to verify the accuracy of the information and filter out duplicate or incorrect information. This is also where the information is categorized and prioritized.

[0584] The collected and processed information is made available in real time and visually displayed to users via devices such as smartphones, tablets, and PCs. The software on the devices visualizes the information in an easy-to-understand way using text, pinpoints on maps, graphs, and more.

[0585] Users can check disaster information updated in real time on their devices. Furthermore, they can ask questions in an interactive format using generative AI to obtain optimal answers. For example, if a user types a question like, "Where is the nearest evacuation shelter?", the generative AI will generate an answer based on real-time data and provide it to the user.

[0586] The server proposes optimal disaster response actions based on the information entered by the user. If the user provides their current location information, the server recommends optimal evacuation routes and evacuation locations based on that information. Furthermore, it uses an emotion engine to recognize the user's emotions and provide information appropriate to their emotions. For example, if the server recognizes that the user is in a state of high stress, it will provide messages and advice to reassure the user.

[0587] Specific examples

[0588] When an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes the information, filters out the necessary information, and makes it public. The device visually displays the information to the user, and the emotion engine recognizes the user's emotional state. For example, if a user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0589] Below are some example prompts to be input to the generative AI model:

[0590] Input: I'm feeling very anxious about the current situation. Do you have any advice to help me feel more at ease?

[0591] Generated AI prompt: This user is in a state of high stress. Please provide information and advice to help them feel more at ease.

[0592] Output: First, take a deep breath and stay calm. Also, you will be safe if you evacuate to the XX Community Center.

[0593] In this way, the present invention is a system that not only manages disaster information in an integrated manner and supports users in responding quickly and appropriately, but also enables flexible responses according to the user's emotional state.

[0594] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0595] Program processing flow

[0596] Step 1:

[0597] The server collects disaster information in real time from various API endpoints.

[0598] Specifically, it sends HTTP requests to retrieve data. For example, it retrieves earthquake alerts from the Japan Meteorological Agency's API, and collects information on evacuation centers and the status of supplies from local government APIs.

[0599] Input: Each API endpoint

[0600] Data processing: Sending HTTP requests and receiving responses from each API

[0601] Output: Acquired disaster information

[0602] GET / api / disaster / latest HTTP / 1.1

[0603] Host: weatherapi.com

[0604] Step 2:

[0605] The server integrates the collected disaster information into a database.

[0606] Specifically, the information is stored in a SQL or NoSQL database, and the collected data is de-duplicated and checked for accuracy.

[0607] Input: Collected disaster information

[0608] Data processing: Deleting duplicates, checking accuracy

[0609] Output: Integrated disaster information database

[0610] Disaster information database: evacuation shelter information, earthquake alerts, supply status

[0611] Step 3:

[0612] The server publishes the processed and filtered information.

[0613] Specifically, it provides information to web applications and mobile devices in real time.

[0614] Input: Integrated disaster information database

[0615] Data processing: filtering information and dividing it into categories (shelters, emergency alerts, supply status)

[0616] Output: Disaster information released

[0617] HTML

[0618]

[0619] <h2> Latest evacuation shelter information< / h2>

[0620]

[0621] Shelter 1: Address XYZ, Capacity 100, Spaces 50

[0622] Shelter 2: Address ABC, Capacity 200, Vacant seats 150

[0623]

[0624]

[0625] Step 4:

[0626] The terminal visually displays the published information to the user.

[0627] Specifically, it performs operations such as displaying text information and pinpointing the location of evacuation shelters on a map.

[0628] Input: Disaster information released

[0629] Data processing: Map generation, text information display

[0630] Output: Visually displayed disaster information

[0631] Pin on map: Shelter 1: Address XYZ, Capacity 100, Space 50

[0632] Step 5:

[0633] The terminal uses generative artificial intelligence to provide information to the user in an interactive format.

[0634] When a user enters a question, the generative artificial intelligence generates the best answer based on that question and presents it to the user.

[0635] Input: User question (e.g., "Where is the nearest evacuation shelter?")

[0636] Data processing: Answer generation using generative AI

[0637] Output: Best answer (e.g. "The nearest evacuation shelter is XX Community Center.")

[0638] User: "Where is the nearest evacuation shelter?"

[0639] AI: "The nearest evacuation shelter is the XX Community Center. The address is XYZ, and there are currently 50 spaces available."

[0640] Step 6:

[0641] The server uses an emotion engine to recognize the user's emotion.

[0642] Specifically, the system analyzes the emotional state of the user from the text and voice input and provides the necessary information.

[0643] Input: User text and voice input

[0644] Data processing: Emotion analysis using an emotion engine

[0645] Output: Information or advice based on the perceived emotional state

[0646] Input: I'm feeling very anxious about the current situation. Do you have any advice to help me feel more at ease?

[0647] Generated AI prompt: This user is in a state of high stress. Please provide information and advice to help them feel more at ease.

[0648] Output: First, take a deep breath and stay calm. Also, you will be safe if you evacuate to the XX Community Center.

[0649] Through this series of steps, the system is able to quickly and accurately collect disaster information, provide it in a format that is easy for users to understand, and even assist users in taking appropriate action based on their emotions.

[0650] (Application example 2)

[0651] 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."

[0652] In order for autonomous vehicles to respond appropriately in the event of a disaster, they need to collect accurate disaster information in real time and respond appropriately based on that information. However, typical disaster information systems take time to integrate information and do not provide information that takes users' emotions into consideration. As a result, users are not provided with enough information to make the right decisions, which can cause stress and confusion.

[0653] The identification processing 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 collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information to the user in an interactive format, means including an emotion engine for recognizing the user's emotions and providing information according to the emotions, means for using a navigation system to provide an optimal route based on vehicle position information, and means for visually displaying information in an easy-to-understand format. This enables an autonomous vehicle to obtain accurate disaster information in real time, provide appropriate information according to the user's emotional state, and suggest an optimal evacuation route.

[0654] "Disaster information" refers to information about natural disasters and man-made disasters such as earthquakes, tsunamis, floods, and fires.

[0655] "Real-time" refers to information being processed and provided immediately at the moment it occurs or shortly thereafter.

[0656] "Collection" refers to obtaining data from various sources and integrating it into one system.

[0657] "Processing and filtering" refers to the process of analyzing collected information, extracting useful information, and removing unnecessary information.

[0658] "Publishing" refers to making the processed and filtered information widely available.

[0659] "Generative AI" refers to AI technology that can generate and provide optimal answers to questions and requests from users.

[0660] An "emotion engine" refers to technology that reads emotions from user input and adjusts the information provided accordingly.

[0661] A "navigation system" is a system that calculates and provides the optimal route based on the current location.

[0662] "Visually displaying" refers to presenting information to a user in the form of text, graphics, images, etc.

[0663] In this invention, a disaster information system is installed in an autonomous vehicle, and disaster information is collected in real time, filtered, and processed to provide appropriate instructions to the user in the vehicle. The system utilizes generative artificial intelligence and an emotion engine to provide information according to the user's emotions. Specific embodiments are described below.

[0664] The server collects disaster information in real time from multiple API endpoints, including evacuation shelter information, emergency alerts, and supply status. The server retrieves this information using HTTP requests and consolidates it into a single database. The collected information is then sent to the autonomous vehicle in real time.

[0665] The device processes and filters the acquired information. First, it checks the accuracy of the collected information and removes duplicate or unnecessary information. Next, it categorizes the information and prioritizes it as needed. The processed and filtered information is then visually displayed to the user in real time. This display can include text information, graphs, and figures.

[0666] Generative AI generates optimal answers based on user questions. For example, in response to the question, "Where is the nearest evacuation shelter?", it provides information on the nearest evacuation shelter based on real-time data. In addition, if a user inputs the question, "Please tell me the evacuation route," the navigation system of an autonomous vehicle will calculate and display the optimal evacuation route based on the vehicle's current location information.

[0667] Furthermore, the emotion engine recognizes emotions from the text and voice input of the user. If it detects that the user is in a state of high stress, the emotion engine will provide information to calm the user and advice on how to reduce stress. For example, in response to a statement such as "I don't know what to do," it will provide a message of kindness and reassurance.

[0668] For example, when an earthquake occurs, the server rapidly collects emergency alerts and evacuation shelter information from multiple sources. The device then processes and filters this information and visually displays it to the user in the vehicle. When the user asks the device, "What is the best evacuation route?", the navigation system calculates the optimal evacuation route and presents it based on real-time data. If the emotion engine detects high stress levels in the user's input, it provides the information along with a reassuring message.

[0669] Prompt Sentence Examples

[0670] 1. Obtain disaster information:

[0671] Please collect the latest disaster information from the API endpoint.

[0672] 2. Emotion recognition:

[0673] Identify the sentiment based on the text entered by the user.

[0674] 3. Providing optimal evacuation routes:

[0675] Provide the best evacuation route based on your current location.

[0676] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0677] Step 1:

[0678] The server collects disaster information from various API endpoints. It uses HTTP requests to obtain data such as evacuation shelter information, emergency alerts, and supply status. The obtained data is integrated into a single database. The input is the various API endpoints, and the output is the integrated database.

[0679] Step 2:

[0680] The server processes and filters the collected information. It removes duplicate and unnecessary information and checks for accuracy. Information is categorized and prioritized as needed. The input is the consolidated database and the output is the filtered information.

[0681] Step 3:

[0682] The processed and filtered information is published in real time. The server sends the processed data to the autonomous vehicle's terminal. The input is the filtered information, and the output is the information sent to the terminal.

[0683] Step 4:

[0684] The terminal visually displays the information sent from the server. It uses text information, graphs, figures, etc. to present the necessary information to the user in an easy-to-understand format. The input is the information sent from the server, and the output is the information displayed on the visual display.

[0685] Step 5:

[0686] A user inputs a question to a terminal. For example, the user inputs a question such as "Where is the nearest evacuation shelter?" The input is the user's question, and the output is the question passed to the terminal via the user interface.

[0687] Step 6:

[0688] The device's generative artificial intelligence generates the best answer based on the user's question. Depending on the content of the question, it searches a real-time database and generates an answer. The input is the user's question and real-time data, and the output is the generated answer.

[0689] Step 7:

[0690] The device's emotion engine recognizes emotions from user input information. It analyzes the text and voice entered by the user and determines their emotional state. The input is the user's input information, and the output is the emotion recognition result.

[0691] Step 8:

[0692] Based on the emotion recognition results, generative AI provides information according to the emotional state. If a high stress state is recognized, a message or advice to reassure the user is added. The input is the emotion recognition result and the generated answer, and the output is an information message that takes emotion into consideration.

[0693] Step 9:

[0694] The navigation system provides the optimal evacuation route based on the vehicle's current location information. It combines the current location and information on nearby evacuation shelters to calculate the optimal route and present it to the user. The input is the current location information and information on nearby evacuation shelters, and the output is the optimal evacuation route.

[0695] 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.

[0696] 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.

[0697] 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.

[0698] [Third embodiment]

[0699] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0700] 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.

[0701] 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).

[0702] 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.

[0703] 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.

[0704] 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).

[0705] 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. 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.

[0706] 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.

[0707] 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.

[0708] 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.

[0709] 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.

[0710] 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."

[0711] This invention relates to a system that collects and processes disaster information in an integrated manner and provides users with appropriate action guidelines. This system is composed of three main elements: a server, a terminal, and a user.

[0712] First, the server collects disaster information in real time from various API endpoints, such as evacuation shelter information, emergency alerts, and the status of supplies. The server retrieves data from these sources using HTTP requests and integrates the collected information into a single database.

[0713] The server then processes and filters the collected information, including verifying data accuracy, removing duplicate information, and categorizing necessary information. The processed and filtered information is then published in real time by the server and made available to users via their devices or web applications.

[0714] The device visually displays the published information to the user. The display includes text, graphs, illustrations, etc., allowing the user to intuitively understand the information they need. The device also has the ability to provide information interactively with the user using generative artificial intelligence. When the user inputs a question into the device, the generative artificial intelligence generates the most appropriate answer and presents it to the user. For example, in response to a question such as "Where is the nearest evacuation shelter?" the device will provide updated evacuation shelter information in real time.

[0715] The server also analyzes user input and suggests optimal disaster response actions. For example, if a user provides their current location, the server will recommend the optimal evacuation route and evacuation shelter based on that location.

[0716] As a concrete example, when an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes this information, filters out the necessary information, and makes it public. The device visually displays this information to the user and provides the optimal course of action based on the user's situation. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0717] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0718] The processing flow will be explained below.

[0719] Step 1:

[0720] The server collects disaster information from various API endpoints. Specifically, it uses HTTP GET requests to retrieve data from multiple sources, such as evacuation shelter information, emergency alerts, and supply status. This allows the necessary information to be integrated into a single database.

[0721] Step 2:

[0722] The server processes and filters the collected information, checking the accuracy of the data obtained and removing duplicate or unnecessary information. It also categorizes the information and prioritizes it as needed, ensuring that the most important information is readily available.

[0723] Step 3:

[0724] The server publishes the processed and filtered information in real time, and the collected information is made available to users through web applications and terminals.

[0725] Step 4:

[0726] The terminal visually displays the published information to the user, and the visual display can include various formats such as text information, graphs, illustrations, etc. This allows the user to intuitively understand the required information.

[0727] Step 5:

[0728] The user can obtain necessary information or input specific questions through the terminal. For example, the user can input a question such as "Where is the nearest evacuation shelter?"

[0729] Step 6:

[0730] The device sends the user's question to a generative artificial intelligence that generates an optimal answer based on the user's input and real-time data.

[0731] Step 7:

[0732] The device displays the answer generated by the generative AI to the user, providing specific information such as, "The nearest evacuation shelter is XX. The current capacity is XX."

[0733] Step 8:

[0734] The server analyzes the information entered by the user and provides the optimal evacuation route and action guidelines. If the user provides location information, the server calculates the optimal evacuation route based on that information and presents it to the user via their device.

[0735] In this way, this system centrally manages the information needed in the event of a disaster, helping users to respond quickly and appropriately.

[0736] Example 1

[0737] 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."

[0738] When a disaster occurs, there is a need for an efficient method to collect necessary information in real time from multiple sources, process and filter it appropriately, and provide it to users quickly and accurately. There is also a need for a method to display information in a format that is intuitively easy for users to understand, and to respond appropriately to user inquiries using generative artificial intelligence. Conventional technologies have difficulty meeting these requirements, and the problem is that it takes a long time to collect and provide information.

[0739] 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.

[0740] In this invention, the server includes means for collecting disaster information in real time using communication technology, means for importing the collected information into an integrated database and analyzing it, communication means for providing aggregated and filtered data to user devices, means for responding to user inquiries using generative artificial intelligence, and means for visually displaying information so that users can intuitively understand it. This makes it possible to collect and process information necessary in the event of a disaster in real time and provide it to users quickly and accurately.

[0741] "Disaster information" refers to data such as evacuation shelter information, emergency alerts, and the status of supplies related to natural disasters such as earthquakes, floods, and typhoons.

[0742] "Communication technology" refers to technology for sending and receiving data using HTTP requests, WebSockets, API endpoints, etc.

[0743] An "integrated database" refers to a database system that centrally manages and stores data collected from multiple sources.

[0744] "Analysis" refers to the process of verifying the accuracy of collected data, removing duplicate information, and classifying the necessary information.

[0745] "User device" refers to a terminal device, such as a PC, smartphone, or tablet, that a user uses to receive and operate information.

[0746] "Generative AI" refers to AI technology that generates responses in natural language to user inquiries.

[0747] "Visually displaying" refers to presenting information to users in a way that they can intuitively understand, using text information, graphs, illustrations, maps, etc.

[0748] This invention relates to a system that collects disaster information in real time and provides users with prompt and accurate action guidelines. This system consists of three main elements: a server, a terminal, and a user.

[0749] First, the server collects disaster information from multiple sources. Specifically, it uses HTTP requests to obtain information on evacuation shelters, emergency alerts, and the status of supplies from government and private API endpoints (e.g., "https: / / api.disasterinfo.gov / shelters" and "https: / / api.weatheragency.jp / alerts"). The collected information is then stored in an integrated database such as MySQL or PostgreSQL.

[0750] The server then analyzes the information stored in the database, which includes verifying the accuracy of the data, removing duplicate information, and categorizing the necessary information. For example, the server may run SQL queries to remove duplicate data and categorize the information by importance.

[0751] The analyzed and filtered data is provided to the user device in real time. The server uses WebSocket or HTTP API to deliver the latest information to the front end. The user device visually displays the received information using HTML, CSS, and JavaScript. For example, it can mark the locations of evacuation shelters on a map or display emergency alerts as notification popups.

[0752] Furthermore, the device uses generative artificial intelligence to generate responses to user questions. For example, if a user asks, "Where is the nearest evacuation shelter?", the device uses a generative AI model (e.g., ChatGPT) to generate an answer and present it to the user.

[0753] The server also analyzes input information (e.g., location information) provided by the user to determine the optimal disaster response action. The server analyzes the latitude and longitude information of the current location, calculates the shortest route using Google Maps API, etc., and presents the results to the user.

[0754] For example, when an earthquake occurs, the server quickly collects emergency alerts and evacuation shelter information from multiple sources, filters the necessary information, and provides it to the user's device. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0755] An example of a prompt would be, "In the event of a large-scale earthquake, collect emergency alerts and evacuation shelter information from government APIs and the Japan Meteorological Agency APIs. Then, integrate the collected information into a database, remove duplicate information, and verify its accuracy before providing it to users. Also, when users ask about the nearest evacuation shelter or evacuation route, use generative artificial intelligence to generate an appropriate answer."

[0756] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0757] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0758] Step 1:

[0759] The server collects disaster information.

[0760] Input: Multiple API endpoints (e.g., "https: / / api.disasterinfo.gov / shelters", "https: / / api.weatheragency.jp / alerts")

[0761] Specific operation: The server sends an HTTP GET request to each endpoint and receives JSON formatted data as a response.

[0762] Output: Raw collected data (JSON format)

[0763] Step 2:

[0764] The server consolidates the collected data into a database.

[0765] Input: Output data from Step 1 (JSON format)

[0766] Specific operation: The server parses the received JSON data and inserts the data into the MySQL database by executing a query such as "INSERT INTO shelters (name, address, capacity) VALUES (...)".

[0767] Output: Merged database entries

[0768] Step 3:

[0769] The server processes and filters the data.

[0770] Input: Integrated database entries

[0771] What happens: The server runs SQL queries such as "SELECT DISTINCT FROM disaster_info" to remove duplicates, check for accuracy, and categorize important information.

[0772] Output: Processed and filtered data

[0773] Step 4:

[0774] The server publishes the processed data.

[0775] Input: Output data from step 3

[0776] Specific operation: The server uses WebSocket or HTTP API to deliver the latest information to the user device in real time. It maintains a connection at "ws: / / example.com / disaster-updates" and notifies the user when the data is updated.

[0777] Output: The latest data sent to the user device

[0778] Step 5:

[0779] The terminal visually displays the information to the user.

[0780] Input: Output data from step 4

[0781] Specific operation: The device uses HTML, CSS, and JavaScript to display the received information in the form of a map or graph. For example, " uses the Google Maps API to display evacuation shelter information.

[0782] Output: Information displayed visually on the user's screen

[0783] Step 6:

[0784] The device uses the generative AI model to answer the user's questions.

[0785] Input: User-entered question, generative AI model (e.g., ChatGPT)

[0786] How it works: When a user asks, "Where is the nearest evacuation shelter?", the device passes this question as a prompt to the generative AI model, which generates the best answer, and then presents the generated answer to the user.

[0787] Output: Answer from the generative AI model

[0788] Step 7:

[0789] The server analyzes the input information from the user.

[0790] Input: User-provided location information (latitude and longitude)

[0791] Specific operation: The server executes the query "SELECT FROM shelters ORDER BY distance FROM user's location LIMIT 1" to determine the best evacuation location.

[0792] Output: Analysis results (optimal evacuation location)

[0793] Step 8:

[0794] The server proposes optimal disaster response actions.

[0795] Input: Analysis results from step 7

[0796] Specific operation: The server uses the Google Maps API to calculate the shortest route from the current location to the nearest evacuation shelter and sends the result to the user in JSON format.

[0797] Output: Suggestion to the user (optimal evacuation route)

[0798] (Application example 1)

[0799] 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."

[0800] In recent years, with the increasing frequency of disasters, there is a demand for providing prompt and appropriate guidelines for action in the event of a disaster. However, current systems do not centralize the collection, processing, and provision of disaster information, making it particularly difficult to present specific guidelines for action to individual users. In addition, conventional methods for providing information interactively with users are limited and lack real-time capabilities. Furthermore, there is a lack of individualized responses based on the user's location information, making it difficult for users to take appropriate action quickly.

[0801] 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.

[0802] In this invention, the server includes means for collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information to a user in an interactive format, means for visually displaying the information in an easy-to-understand format, means for acquiring user location information, means for suggesting appropriate actions to the user based on the acquired location information and disaster information, and means for generating optimal answers to user queries using generative artificial intelligence. This makes it possible to centrally manage disaster information and support users in responding quickly and appropriately.

[0803] "Disaster information" refers to real-time data needed in the event of a disaster, such as the status of the disaster, evacuation shelter information, emergency alerts, and the status of supplies.

[0804] "Means for collection" refers to the interfaces and processes for obtaining disaster information in real time from various API endpoints and other sources.

[0805] "Processing and filtering measures" refers to the process of verifying the accuracy of collected disaster information, removing duplicate information, and classifying necessary information.

[0806] "Means for publishing" refers to the interface or medium by which the processed and filtered information is made accessible to users in real time.

[0807] "Means using generative artificial intelligence" refers to artificial intelligence technology that generates optimal answers to questions in order to provide information to users in an interactive format.

[0808] "Means for visual display" refers to technology that displays information in the form of text, graphs, illustrations, etc., making it easy for users to understand intuitively.

[0809] "Means for obtaining location information" refers to processes or devices that use GPS or other technologies to determine a user's current location.

[0810] "Means for suggesting actions" refers to the process of presenting users with guidelines for action, such as optimal evacuation routes and evacuation shelters, based on the acquired location information and collected disaster information.

[0811] "Means for generating optimal answers to queries" refers to generative artificial intelligence technology that generates the most appropriate answers to user questions based on real-time data.

[0812] This invention relates to a system that collects and processes disaster information in an integrated manner and provides users with appropriate action guidelines. This system consists of three main elements: a server, a terminal, and a user.

[0813] Server Features

[0814] 1. Collection of information

[0815] The server retrieves disaster information in real time from various API endpoints. This information includes evacuation shelter information, emergency alerts, and the status of supplies. This is done using HTTP requests.

[0816] 2. Processing and filtering of information

[0817] The server checks the accuracy of the collected information, removes duplicates, and classifies necessary information, allowing reliable disaster information to be integrated into the database.

[0818] 3. Disclosure of Information

[0819] The processed and filtered information is published in real time and made available to users via terminals and web applications.

[0820] 4. Utilizing location information

[0821] The server provides information on optimal evacuation routes and evacuation locations based on the location information sent by the user.

[0822] Device Features

[0823] 1. Visual information display

[0824] The terminal visually displays the information provided by the server in the form of text, graphs, illustrations, etc. This allows the user to intuitively understand the information they need.

[0825] 2. Interaction with generative AI

[0826] The device uses generative AI to provide information interactively with the user. When the user inputs a question into the device, the generative AI generates the optimal answer in real time and presents it to the user.

[0827] For example, if a user asks, "Where is the nearest evacuation shelter?", the device will provide the most suitable evacuation shelter based on real-time updated evacuation shelter information. An example of a prompt sentence is as follows:

[0828] Prompt statement:

[0829] Your current location is latitude 35.6895, longitude 139.6917. Where is the nearest evacuation shelter? Please provide the best information. Disaster information: [{'type': 'shelter', 'name': 'XX Elementary School', 'location': [35.6890, 139.6920], 'status': 'open', 'capacity': 200},...]

[0830] User Interaction

[0831] 1. Providing location information

[0832] Users can send their location information to the device, which is acquired using GPS.

[0833] 2. Enter your query

[0834] Users can input questions or queries into the device, which then uses generative artificial intelligence to generate optimal answers and present them to the user.

[0835] Hardware and software used

[0836] Hardware

[0837] Server: High-performance cloud servers and data centers are suitable.

[0838] Devices: Smartphones, tablets, computers, etc.

[0839] software

[0840] The requests library (Python) for processing HTTP requests

[0841] Geopy library (Python) for location information acquisition

[0842] Database management requires the use of database systems such as PostgreSQL and MySQL.

[0843] Uses OpenAI API for generative artificial intelligence

[0844] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[0845] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0846] Step 1:

[0847] The server obtains disaster information. Specifically, it sends HTTP requests to various API endpoints to collect data such as evacuation shelter information, emergency alerts, and supply status in real time. It receives the API endpoint URL as input and obtains various disaster information data as output.

[0848] Step 2:

[0849] The server processes and filters the collected information. Specifically, it checks the accuracy of the collected data, removes duplicate information, and classifies the necessary information. The input is the disaster information data obtained in step 1, and the output is the processed and filtered disaster information with high reliability.

[0850] Step 3:

[0851] The server stores the filtered information in a database, and simultaneously publishes this information in real time, making it accessible to devices and web applications. It receives processed disaster information data as input and stores it in a public database as output.

[0852] Step 4:

[0853] The cross-platform terminal obtains public disaster information from the server. Specifically, it uses the server's public API to obtain data in real time. It receives the server's public API endpoint as input and stores the disaster information locally as output.

[0854] Step 5:

[0855] The device visually displays the acquired information. Specifically, it displays disaster information in the form of text, graphs, illustrations, etc., allowing users to intuitively understand it. It receives the acquired disaster information as input and displays it on the UI as output.

[0856] Step 6:

[0857] A user inputs a question or query into the device, for example, "Where is the nearest evacuation shelter?" The input is the user's query text, and the device receives the query as output.

[0858] Step 7:

[0859] The device obtains the user's location information. Specifically, it uses the GPS function to determine the user's current location. It receives the user's permission and GPS function as input, and obtains the latitude and longitude location information as output.

[0860] Step 8:

[0861] The device sends a query to the generative AI to generate the optimal answer. Specifically, a prompt is generated based on the user query and location information, and the generative AI obtains the optimal answer. The input is the user query, location information, and the model settings of the generative AI, and the output is the generated answer text.

[0862] Example prompt sentence:

[0863] Your current location is latitude 35.6895, longitude 139.6917. Where is the nearest evacuation shelter? Please provide the best information. Disaster information: [{'type': 'shelter', 'name': 'XX Elementary School', 'location': [35.6890, 139.6920], 'status': 'open', 'capacity': 200},...]

[0864] Step 9:

[0865] The terminal provides the generated answer to the user. Specifically, the answer obtained from the generative AI is displayed on the screen. The input is the generated answer text, and the output is the display on the screen.

[0866] Step 10:

[0867] The user takes appropriate action based on the information provided. Specifically, they begin taking action based on the information received from the device, such as heading to an evacuation site or preparing necessary supplies. The input is the action guidelines provided by the device, and the output is the user's specific actions.

[0868] 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.

[0869] The present invention provides a system that collects disaster information in real time, processes and filters the information, and provides it to users in an appropriate format. This system also incorporates an emotion engine that recognizes the user's emotions, and provides information according to the user's emotions.

[0870] First, the server collects disaster information in real time from various API endpoints, including evacuation shelter information, emergency alerts, and the status of supplies. The server retrieves this information using HTTP requests and integrates it into a single database.

[0871] The server then processes and filters the collected information. First, it checks the accuracy of the information obtained and removes duplicate or unnecessary information. It also categorizes the information and prioritizes it as needed. This processed and filtered information is then made public in real time and made available to users via their devices or web applications.

[0872] The device visually displays the published information to the user. The visual display can include text information, graphs, illustrations, etc. This allows the user to intuitively understand the information they need. The device also has the ability to provide information interactively with the user using generative artificial intelligence. When the user inputs a question into the device, the generative artificial intelligence generates the most appropriate answer and presents it to the user. For example, in response to a question such as "Where is the nearest evacuation shelter?" the device will provide evacuation shelter information updated in real time.

[0873] Furthermore, the server analyzes the user's input information and suggests optimal disaster response actions. For example, if the user provides their current location information, the server can recommend the optimal evacuation route and evacuation site based on that information.

[0874] The present invention further combines an emotion engine to recognize a user's emotions and provide information according to the emotions. The emotion engine reads the emotions from the text or voice input by the user and adjusts the information provided based on the user's emotional state. For example, if the user is in a high stress state, the emotion engine provides information to reassure the user or advice on stress reduction.

[0875] As a concrete example, when an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes this information, filters out the necessary information, and makes it public. The device visually displays this information to the user, and the emotion engine recognizes the user's emotional state. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0876] If the emotion engine recognizes from the user's input that the user is feeling stressed, it will simultaneously provide information and advice to reduce the user's stress. In this way, the present invention centrally manages information needed in the event of a disaster, not only helping users respond quickly and appropriately, but also enabling flexible responses according to the user's emotional state.

[0877] The processing flow will be explained below.

[0878] Step 1:

[0879] The server collects disaster information such as evacuation shelter information, emergency alerts, and supply status in real time from various API endpoints. Specifically, it retrieves data from these sources using HTTP GET requests and integrates it into a single database.

[0880] Step 2:

[0881] The server processes and filters the collected information, first verifying the accuracy of the data obtained and removing duplicate or unnecessary information, then categorizing the information and prioritizing it as needed.

[0882] Step 3:

[0883] The server publishes the processed and filtered information in real time, and the collected information is made available to users through web applications and terminals.

[0884] Step 4:

[0885] The terminal visually displays the published information to the user, including text information, graphs, illustrations, etc. This allows the user to intuitively understand the required information.

[0886] Step 5:

[0887] Users can obtain the necessary information directly through their devices or enter specific questions, such as "Where is the nearest evacuation shelter?"

[0888] Step 6:

[0889] The device sends the user's question to a generative artificial intelligence that generates an optimal answer based on the user's input and real-time data.

[0890] Step 7:

[0891] The device displays the answer generated by the generative AI to the user, providing specific information such as, "The nearest evacuation shelter is XX. The current capacity is XX."

[0892] Step 8:

[0893] The server analyzes the information entered by the user and provides the optimal evacuation route and action guidelines. If the user provides location information, the server calculates the optimal evacuation route based on that information and presents it to the user via their device.

[0894] Step 9:

[0895] The device uses an emotion engine to recognize the user's emotions. The emotion engine reads emotions from the user's input text and voice.

[0896] Step 10:

[0897] The device adjusts the information provided based on the emotional state recognized by the emotion engine. For example, if the user is in a state of high stress, the device will provide information and advice to help reduce stress.

[0898] Step 11:

[0899] The emotion engine allows users to take the information presented to them and act safely and effectively, for example, providing evacuation route instructions in a calming tone and providing additional reassurance information as needed.

[0900] In this way, this system centrally manages the information needed in the event of a disaster, not only helping users respond quickly and appropriately, but also enabling flexible responses according to the user's emotional state.

[0901] Example 2

[0902] 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."

[0903] In modern society, there is a growing need to quickly and accurately collect disaster information and provide it to users in an appropriate format. However, conventional systems take time to collect and process information, and are unable to provide information that reflects the user's emotions, making it difficult to respond appropriately in the event of a disaster. The present invention aims to solve these problems by providing a system that can provide accurate disaster information in real time while flexibly responding to the user's emotions.

[0904] 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.

[0905] In this invention, the server includes means for collecting disaster information in real time, means for processing and filtering the collected information, and means for publishing the processed and filtered information, thereby enabling prompt and accurate collection of disaster information to be provided to users and enabling flexible response.

[0906] Furthermore, the system includes means for using generative artificial intelligence to provide information to users in an interactive format, means for visually displaying information in an easy-to-understand format, and means for recognizing the user's emotions and adjusting the information according to the emotions. This allows users to obtain optimal disaster information in real time and respond according to their emotions, thereby minimizing confusion during a disaster.

[0907] "Disaster information" refers to information about natural disasters and man-made disasters, including emergency alerts, evacuation shelter information, and the status of supplies.

[0908] "Means of collecting information in real time" refers to a method for instantly obtaining disaster information from various API endpoints, and refers to the use of protocols such as HTTP requests.

[0909] "Processing and filtering measures" refers to methods for reviewing and organizing collected information by accuracy, redundancy, and necessity, and removing unnecessary information.

[0910] "Means of publication" refers to the method by which the processed and filtered information is made available on the Internet in a form accessible to users.

[0911] "Generative artificial intelligence" refers to algorithms and models used to generate appropriate answers to user questions.

[0912] "Visual display means" refers to methods of displaying information in a way that is easy for users to understand, such as by using graphs, maps, text, etc.

[0913] "Means for recognizing emotions" refers to technology that analyzes the emotional state of a user at that time from the text or voice input provided by the user.

[0914] The term "means for adjusting information according to emotions" refers to a method for changing the content or format of information provided based on the recognized emotional state of the user.

[0915] "Means for providing guidelines for action" refers to methods for helping users take appropriate actions based on publicly available disaster information.

[0916] The present invention is a system that collects disaster information in real time and provides users with processed and filtered information. This system is designed to recognize the user's emotions and provide information according to the emotions. Specific embodiments for implementing the present invention will be described below.

[0917] First, the server collects disaster information in real time from various API endpoints. The server uses a high-performance server machine as its hardware and executes a script that sends HTTP requests as its software. For example, an API request from the Japan Meteorological Agency or a local government might be sent as follows:

[0918] GET / api / disaster / latest HTTP / 1.1

[0919] Host: weatherapi.com

[0920] The server then processes and integrates the acquired disaster information into a database, which can be in SQL or NoSQL format, for example. After the data is collected, the server runs algorithms to verify the accuracy of the information and filter out duplicate or incorrect information. This is also where the information is categorized and prioritized.

[0921] The collected and processed information is made available in real time and visually displayed to users via devices such as smartphones, tablets, and PCs. The software on the devices visualizes the information in an easy-to-understand way using text, pinpoints on maps, graphs, and more.

[0922] Users can check disaster information updated in real time on their devices. Furthermore, they can ask questions in an interactive format using generative AI to obtain optimal answers. For example, if a user types a question like, "Where is the nearest evacuation shelter?", the generative AI will generate an answer based on real-time data and provide it to the user.

[0923] The server proposes optimal disaster response actions based on the information entered by the user. If the user provides their current location information, the server recommends optimal evacuation routes and evacuation locations based on that information. Furthermore, it uses an emotion engine to recognize the user's emotions and provide information appropriate to their emotions. For example, if the server recognizes that the user is in a state of high stress, it will provide messages and advice to reassure the user.

[0924] Specific examples

[0925] When an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes the information, filters out the necessary information, and makes it public. The device visually displays the information to the user, and the emotion engine recognizes the user's emotional state. For example, if a user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[0926] Below are some example prompts to be input to the generative AI model:

[0927] Input: I'm feeling very anxious about the current situation. Do you have any advice to help me feel more at ease?

[0928] Generated AI prompt: This user is in a state of high stress. Please provide information and advice to help them feel more at ease.

[0929] Output: First, take a deep breath and stay calm. Also, you will be safe if you evacuate to the XX Community Center.

[0930] In this way, the present invention is a system that not only manages disaster information in an integrated manner and supports users in responding quickly and appropriately, but also enables flexible responses according to the user's emotional state.

[0931] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0932] Program processing flow

[0933] Step 1:

[0934] The server collects disaster information in real time from various API endpoints.

[0935] Specifically, it sends HTTP requests to retrieve data. For example, it retrieves earthquake alerts from the Japan Meteorological Agency's API, and collects information on evacuation centers and the status of supplies from local government APIs.

[0936] Input: Each API endpoint

[0937] Data processing: Sending HTTP requests and receiving responses from each API

[0938] Output: Acquired disaster information

[0939] GET / api / disaster / latest HTTP / 1.1

[0940] Host: weatherapi.com

[0941] Step 2:

[0942] The server integrates the collected disaster information into a database.

[0943] Specifically, the information is stored in a SQL or NoSQL database, and the collected data is de-duplicated and checked for accuracy.

[0944] Input: Collected disaster information

[0945] Data processing: Deleting duplicates, checking accuracy

[0946] Output: Integrated disaster information database

[0947] Disaster information database: evacuation shelter information, earthquake alerts, supply status

[0948] Step 3:

[0949] The server publishes the processed and filtered information.

[0950] Specifically, it provides information to web applications and mobile devices in real time.

[0951] Input: Integrated disaster information database

[0952] Data processing: filtering information and dividing it into categories (shelters, emergency alerts, supply status)

[0953] Output: Disaster information released

[0954] HTML

[0955]

[0956] <h2> Latest evacuation shelter information< / h2>

[0957]

[0958] Shelter 1: Address XYZ, Capacity 100, Spaces 50

[0959] Shelter 2: Address ABC, Capacity 200, Vacant seats 150

[0960]

[0961]

[0962] Step 4:

[0963] The terminal visually displays the published information to the user.

[0964] Specifically, it performs operations such as displaying text information and pinpointing the location of evacuation shelters on a map.

[0965] Input: Disaster information released

[0966] Data processing: Map generation, text information display

[0967] Output: Visually displayed disaster information

[0968] Pin on map: Shelter 1: Address XYZ, Capacity 100, Space 50

[0969] Step 5:

[0970] The terminal uses generative artificial intelligence to provide information to the user in an interactive format.

[0971] When a user enters a question, the generative artificial intelligence generates the best answer based on that question and presents it to the user.

[0972] Input: User question (e.g., "Where is the nearest evacuation shelter?")

[0973] Data processing: Answer generation using generative AI

[0974] Output: Best answer (e.g. "The nearest evacuation shelter is XX Community Center.")

[0975] User: "Where is the nearest evacuation shelter?"

[0976] AI: "The nearest evacuation shelter is the XX Community Center. The address is XYZ, and there are currently 50 spaces available."

[0977] Step 6:

[0978] The server uses an emotion engine to recognize the user's emotion.

[0979] Specifically, the system analyzes the emotional state of the user from the text and voice input and provides the necessary information.

[0980] Input: User text and voice input

[0981] Data processing: Emotion analysis using an emotion engine

[0982] Output: Information or advice based on the perceived emotional state

[0983] Input: I'm feeling very anxious about the current situation. Do you have any advice to help me feel more at ease?

[0984] Generated AI prompt: This user is in a state of high stress. Please provide information and advice to help them feel more at ease.

[0985] Output: First, take a deep breath and stay calm. Also, you will be safe if you evacuate to the XX Community Center.

[0986] Through this series of steps, the system is able to quickly and accurately collect disaster information, provide it in a format that is easy for users to understand, and even assist users in taking appropriate action based on their emotions.

[0987] (Application example 2)

[0988] 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."

[0989] In order for autonomous vehicles to respond appropriately in the event of a disaster, they need to collect accurate disaster information in real time and respond appropriately based on that information. However, typical disaster information systems take time to integrate information and do not provide information that takes users' emotions into consideration. As a result, users are not provided with enough information to make the right decisions, which can cause stress and confusion.

[0990] The identification processing 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 collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information to the user in an interactive format, means including an emotion engine for recognizing the user's emotions and providing information according to the emotions, means for using a navigation system to provide an optimal route based on vehicle position information, and means for visually displaying information in an easy-to-understand format. This enables an autonomous vehicle to obtain accurate disaster information in real time, provide appropriate information according to the user's emotional state, and suggest an optimal evacuation route.

[0991] "Disaster information" refers to information about natural disasters and man-made disasters such as earthquakes, tsunamis, floods, and fires.

[0992] "Real-time" refers to information being processed and provided immediately at the moment it occurs or shortly thereafter.

[0993] "Collection" refers to obtaining data from various sources and integrating it into one system.

[0994] "Processing and filtering" refers to the process of analyzing collected information, extracting useful information, and removing unnecessary information.

[0995] "Publishing" refers to making the processed and filtered information widely available.

[0996] "Generative AI" refers to AI technology that can generate and provide optimal answers to questions and requests from users.

[0997] An "emotion engine" refers to technology that reads emotions from user input and adjusts the information provided accordingly.

[0998] A "navigation system" is a system that calculates and provides the optimal route based on the current location.

[0999] "Visually displaying" refers to presenting information to a user in the form of text, graphics, images, etc.

[1000] In this invention, a disaster information system is installed in an autonomous vehicle, and disaster information is collected in real time, filtered, and processed to provide appropriate instructions to the user in the vehicle. The system utilizes generative artificial intelligence and an emotion engine to provide information according to the user's emotions. Specific embodiments are described below.

[1001] The server collects disaster information in real time from multiple API endpoints, including evacuation shelter information, emergency alerts, and supply status. The server retrieves this information using HTTP requests and consolidates it into a single database. The collected information is then sent to the autonomous vehicle in real time.

[1002] The device processes and filters the acquired information. First, it checks the accuracy of the collected information and removes duplicate or unnecessary information. Next, it categorizes the information and prioritizes it as needed. The processed and filtered information is then visually displayed to the user in real time. This display can include text information, graphs, and figures.

[1003] Generative AI generates optimal answers based on user questions. For example, in response to the question, "Where is the nearest evacuation shelter?", it provides information on the nearest evacuation shelter based on real-time data. In addition, if a user inputs the question, "Please tell me the evacuation route," the navigation system of an autonomous vehicle will calculate and display the optimal evacuation route based on the vehicle's current location information.

[1004] Furthermore, the emotion engine recognizes emotions from the text and voice input of the user. If it detects that the user is in a state of high stress, the emotion engine will provide information to calm the user and advice on how to reduce stress. For example, in response to a statement such as "I don't know what to do," it will provide a message of kindness and reassurance.

[1005] For example, when an earthquake occurs, the server rapidly collects emergency alerts and evacuation shelter information from multiple sources. The device then processes and filters this information and visually displays it to the user in the vehicle. When the user asks the device, "What is the best evacuation route?", the navigation system calculates the optimal evacuation route and presents it based on real-time data. If the emotion engine detects high stress levels in the user's input, it provides the information along with a reassuring message.

[1006] Prompt Sentence Examples

[1007] 1. Obtain disaster information:

[1008] Please collect the latest disaster information from the API endpoint.

[1009] 2. Emotion recognition:

[1010] Identify the sentiment based on the text entered by the user.

[1011] 3. Providing optimal evacuation routes:

[1012] Provide the best evacuation route based on your current location.

[1013] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1014] Step 1:

[1015] The server collects disaster information from various API endpoints. It uses HTTP requests to obtain data such as evacuation shelter information, emergency alerts, and supply status. The obtained data is integrated into a single database. The input is the various API endpoints, and the output is the integrated database.

[1016] Step 2:

[1017] The server processes and filters the collected information. It removes duplicate and unnecessary information and checks for accuracy. Information is categorized and prioritized as needed. The input is the consolidated database and the output is the filtered information.

[1018] Step 3:

[1019] The processed and filtered information is published in real time. The server sends the processed data to the autonomous vehicle's terminal. The input is the filtered information, and the output is the information sent to the terminal.

[1020] Step 4:

[1021] The terminal visually displays the information sent from the server. It uses text information, graphs, figures, etc. to present the necessary information to the user in an easy-to-understand format. The input is the information sent from the server, and the output is the information displayed on the visual display.

[1022] Step 5:

[1023] A user inputs a question to a terminal. For example, the user inputs a question such as "Where is the nearest evacuation shelter?" The input is the user's question, and the output is the question passed to the terminal via the user interface.

[1024] Step 6:

[1025] The device's generative artificial intelligence generates the best answer based on the user's question. Depending on the content of the question, it searches a real-time database and generates an answer. The input is the user's question and real-time data, and the output is the generated answer.

[1026] Step 7:

[1027] The device's emotion engine recognizes emotions from user input information. It analyzes the text and voice entered by the user and determines their emotional state. The input is the user's input information, and the output is the emotion recognition result.

[1028] Step 8:

[1029] Based on the emotion recognition results, generative AI provides information according to the emotional state. If a high stress state is recognized, a message or advice to reassure the user is added. The input is the emotion recognition result and the generated answer, and the output is an information message that takes emotion into consideration.

[1030] Step 9:

[1031] The navigation system provides the optimal evacuation route based on the vehicle's current location information. It combines the current location and information on nearby evacuation shelters to calculate the optimal route and present it to the user. The input is the current location information and information on nearby evacuation shelters, and the output is the optimal evacuation route.

[1032] 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.

[1033] 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.

[1034] 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.

[1035] [Fourth embodiment]

[1036] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1037] 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.

[1038] 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).

[1039] 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.

[1040] 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.

[1041] 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).

[1042] 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. 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.

[1043] 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.

[1044] 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.

[1045] 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.

[1046] 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.

[1047] 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.

[1048] 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."

[1049] This invention relates to a system that collects and processes disaster information in an integrated manner and provides users with appropriate action guidelines. This system is composed of three main elements: a server, a terminal, and a user.

[1050] First, the server collects disaster information in real time from various API endpoints, such as evacuation shelter information, emergency alerts, and the status of supplies. The server retrieves data from these sources using HTTP requests and integrates the collected information into a single database.

[1051] The server then processes and filters the collected information, including verifying data accuracy, removing duplicate information, and categorizing necessary information. The processed and filtered information is then published in real time by the server and made available to users via their devices or web applications.

[1052] The device visually displays the published information to the user. The display includes text, graphs, illustrations, etc., allowing the user to intuitively understand the information they need. The device also has the ability to provide information interactively with the user using generative artificial intelligence. When the user inputs a question into the device, the generative artificial intelligence generates the most appropriate answer and presents it to the user. For example, in response to a question such as "Where is the nearest evacuation shelter?" the device will provide updated evacuation shelter information in real time.

[1053] The server also analyzes user input and suggests optimal disaster response actions. For example, if a user provides their current location, the server will recommend the optimal evacuation route and evacuation shelter based on that location.

[1054] As a concrete example, when an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes this information, filters out the necessary information, and makes it public. The device visually displays this information to the user and provides the optimal course of action based on the user's situation. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[1055] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[1056] The processing flow will be explained below.

[1057] Step 1:

[1058] The server collects disaster information from various API endpoints. Specifically, it uses HTTP GET requests to retrieve data from multiple sources, such as evacuation shelter information, emergency alerts, and supply status. This allows the necessary information to be integrated into a single database.

[1059] Step 2:

[1060] The server processes and filters the collected information, checking the accuracy of the data obtained and removing duplicate or unnecessary information. It also categorizes the information and prioritizes it as needed, ensuring that the most important information is readily available.

[1061] Step 3:

[1062] The server publishes the processed and filtered information in real time, and the collected information is made available to users through web applications and terminals.

[1063] Step 4:

[1064] The terminal visually displays the published information to the user, and the visual display can include various formats such as text information, graphs, illustrations, etc. This allows the user to intuitively understand the required information.

[1065] Step 5:

[1066] The user can obtain necessary information or input specific questions through the terminal. For example, the user can input a question such as "Where is the nearest evacuation shelter?"

[1067] Step 6:

[1068] The device sends the user's question to a generative artificial intelligence that generates an optimal answer based on the user's input and real-time data.

[1069] Step 7:

[1070] The device displays the answer generated by the generative AI to the user, providing specific information such as, "The nearest evacuation shelter is XX. The current capacity is XX."

[1071] Step 8:

[1072] The server analyzes the information entered by the user and provides the optimal evacuation route and action guidelines. If the user provides location information, the server calculates the optimal evacuation route based on that information and presents it to the user via their device.

[1073] In this way, this system centrally manages the information needed in the event of a disaster, helping users to respond quickly and appropriately.

[1074] Example 1

[1075] 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."

[1076] When a disaster occurs, there is a need for an efficient method to collect necessary information in real time from multiple sources, process and filter it appropriately, and provide it to users quickly and accurately. There is also a need for a method to display information in a format that is intuitively easy for users to understand, and to respond appropriately to user inquiries using generative artificial intelligence. Conventional technologies have difficulty meeting these requirements, and the problem is that it takes a long time to collect and provide information.

[1077] 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.

[1078] In this invention, the server includes means for collecting disaster information in real time using communication technology, means for importing the collected information into an integrated database and analyzing it, communication means for providing aggregated and filtered data to user devices, means for responding to user inquiries using generative artificial intelligence, and means for visually displaying information so that users can intuitively understand it. This makes it possible to collect and process information necessary in the event of a disaster in real time and provide it to users quickly and accurately.

[1079] "Disaster information" refers to data such as evacuation shelter information, emergency alerts, and the status of supplies related to natural disasters such as earthquakes, floods, and typhoons.

[1080] "Communication technology" refers to technology for sending and receiving data using HTTP requests, WebSockets, API endpoints, etc.

[1081] An "integrated database" refers to a database system that centrally manages and stores data collected from multiple sources.

[1082] "Analysis" refers to the process of verifying the accuracy of collected data, removing duplicate information, and classifying the necessary information.

[1083] "User device" refers to a terminal device, such as a PC, smartphone, or tablet, that a user uses to receive and operate information.

[1084] "Generative AI" refers to AI technology that generates responses in natural language to user inquiries.

[1085] "Visually displaying" refers to presenting information to users in a way that they can intuitively understand, using text information, graphs, illustrations, maps, etc.

[1086] This invention relates to a system that collects disaster information in real time and provides users with prompt and accurate action guidelines. This system consists of three main elements: a server, a terminal, and a user.

[1087] First, the server collects disaster information from multiple sources. Specifically, it uses HTTP requests to obtain information on evacuation shelters, emergency alerts, and the status of supplies from government and private API endpoints (e.g., "https: / / api.disasterinfo.gov / shelters" and "https: / / api.weatheragency.jp / alerts"). The collected information is then stored in an integrated database such as MySQL or PostgreSQL.

[1088] The server then analyzes the information stored in the database, which includes verifying the accuracy of the data, removing duplicate information, and categorizing the necessary information. For example, the server may run SQL queries to remove duplicate data and categorize the information by importance.

[1089] The analyzed and filtered data is provided to the user device in real time. The server uses WebSocket or HTTP API to deliver the latest information to the front end. The user device visually displays the received information using HTML, CSS, and JavaScript. For example, it can mark the locations of evacuation shelters on a map or display emergency alerts as notification popups.

[1090] Furthermore, the device uses generative artificial intelligence to generate responses to user questions. For example, if a user asks, "Where is the nearest evacuation shelter?", the device uses a generative AI model (e.g., ChatGPT) to generate an answer and present it to the user.

[1091] The server also analyzes input information (e.g., location information) provided by the user to determine the optimal disaster response action. The server analyzes the latitude and longitude information of the current location, calculates the shortest route using Google Maps API, etc., and presents the results to the user.

[1092] For example, when an earthquake occurs, the server quickly collects emergency alerts and evacuation shelter information from multiple sources, filters the necessary information, and provides it to the user's device. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[1093] An example of a prompt would be, "In the event of a large-scale earthquake, collect emergency alerts and evacuation shelter information from government APIs and the Japan Meteorological Agency APIs. Then, integrate the collected information into a database, remove duplicate information, and verify its accuracy before providing it to users. Also, when users ask about the nearest evacuation shelter or evacuation route, use generative artificial intelligence to generate an appropriate answer."

[1094] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[1095] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1096] Step 1:

[1097] The server collects disaster information.

[1098] Input: Multiple API endpoints (e.g., "https: / / api.disasterinfo.gov / shelters", "https: / / api.weatheragency.jp / alerts")

[1099] Specific operation: The server sends an HTTP GET request to each endpoint and receives JSON formatted data as a response.

[1100] Output: Raw collected data (JSON format)

[1101] Step 2:

[1102] The server consolidates the collected data into a database.

[1103] Input: Output data from Step 1 (JSON format)

[1104] Specific operation: The server parses the received JSON data and inserts the data into the MySQL database by executing a query such as "INSERT INTO shelters (name, address, capacity) VALUES (...)".

[1105] Output: Merged database entries

[1106] Step 3:

[1107] The server processes and filters the data.

[1108] Input: Integrated database entries

[1109] What happens: The server runs SQL queries such as "SELECT DISTINCT FROM disaster_info" to remove duplicates, check for accuracy, and categorize important information.

[1110] Output: Processed and filtered data

[1111] Step 4:

[1112] The server publishes the processed data.

[1113] Input: Output data from step 3

[1114] Specific operation: The server uses WebSocket or HTTP API to deliver the latest information to the user device in real time. It maintains a connection at "ws: / / example.com / disaster-updates" and notifies the user when the data is updated.

[1115] Output: The latest data sent to the user device

[1116] Step 5:

[1117] The terminal visually displays the information to the user.

[1118] Input: Output data from step 4

[1119] Specific operation: The device uses HTML, CSS, and JavaScript to display the received information in the form of a map or graph. For example, " uses the Google Maps API to display evacuation shelter information.

[1120] Output: Information displayed visually on the user's screen

[1121] Step 6:

[1122] The device uses the generative AI model to answer the user's questions.

[1123] Input: User-entered question, generative AI model (e.g., ChatGPT)

[1124] How it works: When a user asks, "Where is the nearest evacuation shelter?", the device passes this question as a prompt to the generative AI model, which generates the best answer, and then presents the generated answer to the user.

[1125] Output: Answer from the generative AI model

[1126] Step 7:

[1127] The server analyzes the input information from the user.

[1128] Input: User-provided location information (latitude and longitude)

[1129] Specific operation: The server executes the query "SELECT FROM shelters ORDER BY distance FROM user's location LIMIT 1" to determine the best evacuation location.

[1130] Output: Analysis results (optimal evacuation location)

[1131] Step 8:

[1132] The server proposes optimal disaster response actions.

[1133] Input: Analysis results from step 7

[1134] Specific operation: The server uses the Google Maps API to calculate the shortest route from the current location to the nearest evacuation shelter and sends the result to the user in JSON format.

[1135] Output: Suggestion to the user (optimal evacuation route)

[1136] (Application example 1)

[1137] 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."

[1138] In recent years, with the increasing frequency of disasters, there is a demand for providing prompt and appropriate guidelines for action in the event of a disaster. However, current systems do not centralize the collection, processing, and provision of disaster information, making it particularly difficult to present specific guidelines for action to individual users. In addition, conventional methods for providing information interactively with users are limited and lack real-time capabilities. Furthermore, there is a lack of individualized responses based on the user's location information, making it difficult for users to take appropriate action quickly.

[1139] 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.

[1140] In this invention, the server includes means for collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information to a user in an interactive format, means for visually displaying the information in an easy-to-understand format, means for acquiring user location information, means for suggesting appropriate actions to the user based on the acquired location information and disaster information, and means for generating optimal answers to user queries using generative artificial intelligence. This makes it possible to centrally manage disaster information and support users in responding quickly and appropriately.

[1141] "Disaster information" refers to real-time data needed in the event of a disaster, such as the status of the disaster, evacuation shelter information, emergency alerts, and the status of supplies.

[1142] "Means for collection" refers to the interfaces and processes for obtaining disaster information in real time from various API endpoints and other sources.

[1143] "Processing and filtering measures" refers to the process of verifying the accuracy of collected disaster information, removing duplicate information, and classifying necessary information.

[1144] "Means for publishing" refers to the interface or medium by which the processed and filtered information is made accessible to users in real time.

[1145] "Means using generative artificial intelligence" refers to artificial intelligence technology that generates optimal answers to questions in order to provide information to users in an interactive format.

[1146] "Means for visual display" refers to technology that displays information in the form of text, graphs, illustrations, etc., making it easy for users to understand intuitively.

[1147] "Means for obtaining location information" refers to processes or devices that use GPS or other technologies to determine a user's current location.

[1148] "Means for suggesting actions" refers to the process of presenting users with guidelines for action, such as optimal evacuation routes and evacuation shelters, based on the acquired location information and collected disaster information.

[1149] "Means for generating optimal answers to queries" refers to generative artificial intelligence technology that generates the most appropriate answers to user questions based on real-time data.

[1150] This invention relates to a system that collects and processes disaster information in an integrated manner and provides users with appropriate action guidelines. This system consists of three main elements: a server, a terminal, and a user.

[1151] Server Features

[1152] 1. Collection of information

[1153] The server retrieves disaster information in real time from various API endpoints. This information includes evacuation shelter information, emergency alerts, and the status of supplies. This is done using HTTP requests.

[1154] 2. Processing and filtering of information

[1155] The server checks the accuracy of the collected information, removes duplicates, and classifies necessary information, allowing reliable disaster information to be integrated into the database.

[1156] 3. Disclosure of Information

[1157] The processed and filtered information is published in real time and made available to users via terminals and web applications.

[1158] 4. Utilizing location information

[1159] The server provides information on optimal evacuation routes and evacuation locations based on the location information sent by the user.

[1160] Device Features

[1161] 1. Visual information display

[1162] The terminal visually displays the information provided by the server in the form of text, graphs, illustrations, etc. This allows the user to intuitively understand the information they need.

[1163] 2. Interaction with generative AI

[1164] The device uses generative AI to provide information interactively with the user. When the user inputs a question into the device, the generative AI generates the optimal answer in real time and presents it to the user.

[1165] For example, if a user asks, "Where is the nearest evacuation shelter?", the device will provide the most suitable evacuation shelter based on real-time updated evacuation shelter information. An example of a prompt sentence is as follows:

[1166] Prompt statement:

[1167] Your current location is latitude 35.6895, longitude 139.6917. Where is the nearest evacuation shelter? Please provide the best information. Disaster information: [{'type': 'shelter', 'name': 'XX Elementary School', 'location': [35.6890, 139.6920], 'status': 'open', 'capacity': 200},...]

[1168] User Interaction

[1169] 1. Providing location information

[1170] Users can send their location information to the device, which is acquired using GPS.

[1171] 2. Enter your query

[1172] Users can input questions or queries into the device, which then uses generative artificial intelligence to generate optimal answers and present them to the user.

[1173] Hardware and software used

[1174] Hardware

[1175] Server: High-performance cloud servers and data centers are suitable.

[1176] Devices: Smartphones, tablets, computers, etc.

[1177] software

[1178] The requests library (Python) for processing HTTP requests

[1179] Geopy library (Python) for location information acquisition

[1180] Database management requires the use of database systems such as PostgreSQL and MySQL.

[1181] Uses OpenAI API for generative artificial intelligence

[1182] In this way, the present invention centrally manages information necessary in the event of a disaster, and supports users in responding quickly and appropriately.

[1183] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1184] Step 1:

[1185] The server obtains disaster information. Specifically, it sends HTTP requests to various API endpoints to collect data such as evacuation shelter information, emergency alerts, and supply status in real time. It receives the API endpoint URL as input and obtains various disaster information data as output.

[1186] Step 2:

[1187] The server processes and filters the collected information. Specifically, it checks the accuracy of the collected data, removes duplicate information, and classifies the necessary information. The input is the disaster information data obtained in step 1, and the output is the processed and filtered disaster information with high reliability.

[1188] Step 3:

[1189] The server stores the filtered information in a database, and simultaneously publishes this information in real time, making it accessible to devices and web applications. It receives processed disaster information data as input and stores it in a public database as output.

[1190] Step 4:

[1191] The cross-platform terminal obtains public disaster information from the server. Specifically, it uses the server's public API to obtain data in real time. It receives the server's public API endpoint as input and stores the disaster information locally as output.

[1192] Step 5:

[1193] The device visually displays the acquired information. Specifically, it displays disaster information in the form of text, graphs, illustrations, etc., allowing users to intuitively understand it. It receives the acquired disaster information as input and displays it on the UI as output.

[1194] Step 6:

[1195] A user inputs a question or query into the device, for example, "Where is the nearest evacuation shelter?" The input is the user's query text, and the device receives the query as output.

[1196] Step 7:

[1197] The device obtains the user's location information. Specifically, it uses the GPS function to determine the user's current location. It receives the user's permission and GPS function as input, and obtains the latitude and longitude location information as output.

[1198] Step 8:

[1199] The device sends a query to the generative AI to generate the optimal answer. Specifically, a prompt is generated based on the user query and location information, and the generative AI obtains the optimal answer. The input is the user query, location information, and the model settings of the generative AI, and the output is the generated answer text.

[1200] Example prompt sentence:

[1201] Your current location is latitude 35.6895, longitude 139.6917. Where is the nearest evacuation shelter? Please provide the best information. Disaster information: [{'type': 'shelter', 'name': 'XX Elementary School', 'location': [35.6890, 139.6920], 'status': 'open', 'capacity': 200},...]

[1202] Step 9:

[1203] The terminal provides the generated answer to the user. Specifically, the answer obtained from the generative AI is displayed on the screen. The input is the generated answer text, and the output is the display on the screen.

[1204] Step 10:

[1205] The user takes appropriate action based on the information provided. Specifically, they begin taking action based on the information received from the device, such as heading to an evacuation site or preparing necessary supplies. The input is the action guidelines provided by the device, and the output is the user's specific actions.

[1206] 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.

[1207] The present invention provides a system that collects disaster information in real time, processes and filters the information, and provides it to users in an appropriate format. This system also incorporates an emotion engine that recognizes the user's emotions, and provides information according to the user's emotions.

[1208] First, the server collects disaster information in real time from various API endpoints, including evacuation shelter information, emergency alerts, and the status of supplies. The server retrieves this information using HTTP requests and integrates it into a single database.

[1209] The server then processes and filters the collected information. First, it checks the accuracy of the information obtained and removes duplicate or unnecessary information. It also categorizes the information and prioritizes it as needed. This processed and filtered information is then made public in real time and made available to users via their devices or web applications.

[1210] The device visually displays the published information to the user. The visual display can include text information, graphs, illustrations, etc. This allows the user to intuitively understand the information they need. The device also has the ability to provide information interactively with the user using generative artificial intelligence. When the user inputs a question into the device, the generative artificial intelligence generates the most appropriate answer and presents it to the user. For example, in response to a question such as "Where is the nearest evacuation shelter?" the device will provide evacuation shelter information updated in real time.

[1211] Furthermore, the server analyzes the user's input information and suggests optimal disaster response actions. For example, if the user provides their current location information, the server can recommend the optimal evacuation route and evacuation site based on that information.

[1212] The present invention further combines an emotion engine to recognize a user's emotions and provide information according to the emotions. The emotion engine reads the emotions from the text or voice input by the user and adjusts the information provided based on the user's emotional state. For example, if the user is in a high stress state, the emotion engine provides information to reassure the user or advice on stress reduction.

[1213] As a concrete example, when an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes this information, filters out the necessary information, and makes it public. The device visually displays this information to the user, and the emotion engine recognizes the user's emotional state. When the user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[1214] If the emotion engine recognizes from the user's input that the user is feeling stressed, it will simultaneously provide information and advice to reduce the user's stress. In this way, the present invention centrally manages information needed in the event of a disaster, not only helping users respond quickly and appropriately, but also enabling flexible responses according to the user's emotional state.

[1215] The processing flow will be explained below.

[1216] Step 1:

[1217] The server collects disaster information such as evacuation shelter information, emergency alerts, and supply status in real time from various API endpoints. Specifically, it retrieves data from these sources using HTTP GET requests and integrates it into a single database.

[1218] Step 2:

[1219] The server processes and filters the collected information, first verifying the accuracy of the data obtained and removing duplicate or unnecessary information, then categorizing the information and prioritizing it as needed.

[1220] Step 3:

[1221] The server publishes the processed and filtered information in real time, and the collected information is made available to users through web applications and terminals.

[1222] Step 4:

[1223] The terminal visually displays the published information to the user, including text information, graphs, illustrations, etc. This allows the user to intuitively understand the required information.

[1224] Step 5:

[1225] Users can obtain the necessary information directly through their devices or enter specific questions, such as "Where is the nearest evacuation shelter?"

[1226] Step 6:

[1227] The device sends the user's question to a generative artificial intelligence that generates an optimal answer based on the user's input and real-time data.

[1228] Step 7:

[1229] The device displays the answer generated by the generative AI to the user, providing specific information such as, "The nearest evacuation shelter is XX. The current capacity is XX."

[1230] Step 8:

[1231] The server analyzes the information entered by the user and provides the optimal evacuation route and action guidelines. If the user provides location information, the server calculates the optimal evacuation route based on that information and presents it to the user via their device.

[1232] Step 9:

[1233] The device uses an emotion engine to recognize the user's emotions. The emotion engine reads emotions from the user's input text and voice.

[1234] Step 10:

[1235] The device adjusts the information provided based on the emotional state recognized by the emotion engine. For example, if the user is in a state of high stress, the device will provide information and advice to help reduce stress.

[1236] Step 11:

[1237] The emotion engine allows users to take the information presented to them and act safely and effectively, for example, providing evacuation route instructions in a calming tone and providing additional reassurance information as needed.

[1238] In this way, this system centrally manages the information needed in the event of a disaster, not only helping users respond quickly and appropriately, but also enabling flexible responses according to the user's emotional state.

[1239] Example 2

[1240] 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."

[1241] In modern society, there is a growing need to quickly and accurately collect disaster information and provide it to users in an appropriate format. However, conventional systems take time to collect and process information, and are unable to provide information that reflects the user's emotions, making it difficult to respond appropriately in the event of a disaster. The present invention aims to solve these problems by providing a system that can provide accurate disaster information in real time while flexibly responding to the user's emotions.

[1242] 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.

[1243] In this invention, the server includes means for collecting disaster information in real time, means for processing and filtering the collected information, and means for publishing the processed and filtered information, thereby enabling prompt and accurate collection of disaster information to be provided to users and enabling flexible response.

[1244] Furthermore, the system includes means for using generative artificial intelligence to provide information to users in an interactive format, means for visually displaying information in an easy-to-understand format, and means for recognizing the user's emotions and adjusting the information according to the emotions. This allows users to obtain optimal disaster information in real time and respond according to their emotions, thereby minimizing confusion during a disaster.

[1245] "Disaster information" refers to information about natural disasters and man-made disasters, including emergency alerts, evacuation shelter information, and the status of supplies.

[1246] "Means of collecting information in real time" refers to a method for instantly obtaining disaster information from various API endpoints, and refers to the use of protocols such as HTTP requests.

[1247] "Processing and filtering measures" refers to methods for reviewing and organizing collected information by accuracy, redundancy, and necessity, and removing unnecessary information.

[1248] "Means of publication" refers to the method by which the processed and filtered information is made available on the Internet in a form accessible to users.

[1249] "Generative artificial intelligence" refers to algorithms and models used to generate appropriate answers to user questions.

[1250] "Visual display means" refers to methods of displaying information in a way that is easy for users to understand, such as by using graphs, maps, text, etc.

[1251] "Means for recognizing emotions" refers to technology that analyzes the emotional state of a user at that time from the text or voice input provided by the user.

[1252] The term "means for adjusting information according to emotions" refers to a method for changing the content or format of information provided based on the recognized emotional state of the user.

[1253] "Means for providing guidelines for action" refers to methods for helping users take appropriate actions based on publicly available disaster information.

[1254] The present invention is a system that collects disaster information in real time and provides users with processed and filtered information. This system is designed to recognize the user's emotions and provide information according to the emotions. Specific embodiments for implementing the present invention will be described below.

[1255] First, the server collects disaster information in real time from various API endpoints. The server uses a high-performance server machine as its hardware and executes a script that sends HTTP requests as its software. For example, an API request from the Japan Meteorological Agency or a local government might be sent as follows:

[1256] GET / api / disaster / latest HTTP / 1.1

[1257] Host: weatherapi.com

[1258] The server then processes and integrates the acquired disaster information into a database, which can be in SQL or NoSQL format, for example. After the data is collected, the server runs algorithms to verify the accuracy of the information and filter out duplicate or incorrect information. This is also where the information is categorized and prioritized.

[1259] The collected and processed information is made available in real time and visually displayed to users via devices such as smartphones, tablets, and PCs. The software on the devices visualizes the information in an easy-to-understand way using text, pinpoints on maps, graphs, and more.

[1260] Users can check disaster information updated in real time on their devices. Furthermore, they can ask questions in an interactive format using generative AI to obtain optimal answers. For example, if a user types a question like, "Where is the nearest evacuation shelter?", the generative AI will generate an answer based on real-time data and provide it to the user.

[1261] The server proposes optimal disaster response actions based on the information entered by the user. If the user provides their current location information, the server recommends optimal evacuation routes and evacuation locations based on that information. Furthermore, it uses an emotion engine to recognize the user's emotions and provide information appropriate to their emotions. For example, if the server recognizes that the user is in a state of high stress, it will provide messages and advice to reassure the user.

[1262] Specific examples

[1263] When an earthquake occurs in a certain area, the server quickly collects emergency alerts and evacuation shelter information from multiple sources. The server then processes the information, filters out the necessary information, and makes it public. The device visually displays the information to the user, and the emotion engine recognizes the user's emotional state. For example, if a user asks the device, "Please tell me the evacuation route," the device uses generative artificial intelligence to suggest the optimal route based on real-time data.

[1264] Below are some example prompts to be input to the generative AI model:

[1265] Input: I'm feeling very anxious about the current situation. Do you have any advice to help me feel more at ease?

[1266] Generated AI prompt: This user is in a state of high stress. Please provide information and advice to help them feel more at ease.

[1267] Output: First, take a deep breath and stay calm. Also, you will be safe if you evacuate to the XX Community Center.

[1268] In this way, the present invention is a system that not only manages disaster information in an integrated manner and supports users in responding quickly and appropriately, but also enables flexible responses according to the user's emotional state.

[1269] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1270] Program processing flow

[1271] Step 1:

[1272] The server collects disaster information in real time from various API endpoints.

[1273] Specifically, it sends HTTP requests to retrieve data. For example, it retrieves earthquake alerts from the Japan Meteorological Agency's API, and collects information on evacuation centers and the status of supplies from local government APIs.

[1274] Input: Each API endpoint

[1275] Data processing: Sending HTTP requests and receiving responses from each API

[1276] Output: Acquired disaster information

[1277] GET / api / disaster / latest HTTP / 1.1

[1278] Host: weatherapi.com

[1279] Step 2:

[1280] The server integrates the collected disaster information into a database.

[1281] Specifically, the information is stored in a SQL or NoSQL database, and the collected data is de-duplicated and checked for accuracy.

[1282] Input: Collected disaster information

[1283] Data processing: Deleting duplicates, checking accuracy

[1284] Output: Integrated disaster information database

[1285] Disaster information database: evacuation shelter information, earthquake alerts, supply status

[1286] Step 3:

[1287] The server publishes the processed and filtered information.

[1288] Specifically, it provides information to web applications and mobile devices in real time.

[1289] Input: Integrated disaster information database

[1290] Data processing: filtering information and dividing it into categories (shelters, emergency alerts, supply status)

[1291] Output: Disaster information released

[1292] HTML

[1293]

[1294] <h2> Latest evacuation shelter information< / h2>

[1295]

[1296] Shelter 1: Address XYZ, Capacity 100, Spaces 50

[1297] Shelter 2: Address ABC, Capacity 200, Vacant seats 150

[1298]

[1299]

[1300] Step 4:

[1301] The terminal visually displays the published information to the user.

[1302] Specifically, it performs operations such as displaying text information and pinpointing the location of evacuation shelters on a map.

[1303] Input: Disaster information released

[1304] Data processing: Map generation, text information display

[1305] Output: Visually displayed disaster information

[1306] Pin on map: Shelter 1: Address XYZ, Capacity 100, Space 50

[1307] Step 5:

[1308] The terminal uses generative artificial intelligence to provide information to the user in an interactive format.

[1309] When a user enters a question, the generative artificial intelligence generates the best answer based on that question and presents it to the user.

[1310] Input: User question (e.g., "Where is the nearest evacuation shelter?")

[1311] Data processing: Answer generation using generative AI

[1312] Output: Best answer (e.g. "The nearest evacuation shelter is XX Community Center.")

[1313] User: "Where is the nearest evacuation shelter?"

[1314] AI: "The nearest evacuation shelter is the XX Community Center. The address is XYZ, and there are currently 50 spaces available."

[1315] Step 6:

[1316] The server uses an emotion engine to recognize the user's emotion.

[1317] Specifically, the system analyzes the emotional state of the user from the text and voice input and provides the necessary information.

[1318] Input: User text and voice input

[1319] Data processing: Emotion analysis using an emotion engine

[1320] Output: Information or advice based on the perceived emotional state

[1321] Input: I'm feeling very anxious about the current situation. Do you have any advice to help me feel more at ease?

[1322] Generated AI prompt: This user is in a state of high stress. Please provide information and advice to help them feel more at ease.

[1323] Output: First, take a deep breath and stay calm. Also, you will be safe if you evacuate to the XX Community Center.

[1324] Through this series of steps, the system is able to quickly and accurately collect disaster information, provide it in a format that is easy for users to understand, and even assist users in taking appropriate action based on their emotions.

[1325] (Application example 2)

[1326] 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."

[1327] In order for autonomous vehicles to respond appropriately in the event of a disaster, they need to collect accurate disaster information in real time and respond appropriately based on that information. However, typical disaster information systems take time to integrate information and do not provide information that takes users' emotions into consideration. As a result, users are not provided with enough information to make the right decisions, which can cause stress and confusion.

[1328] The identification processing 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 collecting disaster information in real time, means for processing and filtering the collected information, means for publishing the processed and filtered information, means for using generative artificial intelligence to provide information to the user in an interactive format, means including an emotion engine for recognizing the user's emotions and providing information according to the emotions, means for using a navigation system to provide an optimal route based on vehicle position information, and means for visually displaying information in an easy-to-understand format. This enables an autonomous vehicle to obtain accurate disaster information in real time, provide appropriate information according to the user's emotional state, and suggest an optimal evacuation route.

[1329] "Disaster information" refers to information about natural disasters and man-made disasters such as earthquakes, tsunamis, floods, and fires.

[1330] "Real-time" refers to information being processed and provided immediately at the moment it occurs or shortly thereafter.

[1331] "Collection" refers to obtaining data from various sources and integrating it into one system.

[1332] "Processing and filtering" refers to the process of analyzing collected information, extracting useful information, and removing unnecessary information.

[1333] "Publishing" refers to making the processed and filtered information widely available.

[1334] "Generative AI" refers to AI technology that can generate and provide optimal answers to questions and requests from users.

[1335] An "emotion engine" refers to technology that reads emotions from user input and adjusts the information provided accordingly.

[1336] A "navigation system" is a system that calculates and provides the optimal route based on the current location.

[1337] "Visually displaying" refers to presenting information to a user in the form of text, graphics, images, etc.

[1338] In this invention, a disaster information system is installed in an autonomous vehicle, and disaster information is collected in real time, filtered, and processed to provide appropriate instructions to the user in the vehicle. The system utilizes generative artificial intelligence and an emotion engine to provide information according to the user's emotions. Specific embodiments are described below.

[1339] The server collects disaster information in real time from multiple API endpoints, including evacuation shelter information, emergency alerts, and supply status. The server retrieves this information using HTTP requests and consolidates it into a single database. The collected information is then sent to the autonomous vehicle in real time.

[1340] The device processes and filters the acquired information. First, it checks the accuracy of the collected information and removes duplicate or unnecessary information. Next, it categorizes the information and prioritizes it as needed. The processed and filtered information is then visually displayed to the user in real time. This display can include text information, graphs, and figures.

[1341] Generative AI generates optimal answers based on user questions. For example, in response to the question, "Where is the nearest evacuation shelter?", it provides information on the nearest evacuation shelter based on real-time data. In addition, if a user inputs the question, "Please tell me the evacuation route," the navigation system of an autonomous vehicle will calculate and display the optimal evacuation route based on the vehicle's current location information.

[1342] Furthermore, the emotion engine recognizes emotions from the text and voice input of the user. If it detects that the user is in a state of high stress, the emotion engine will provide information to calm the user and advice on how to reduce stress. For example, in response to a statement such as "I don't know what to do," it will provide a message of kindness and reassurance.

[1343] For example, when an earthquake occurs, the server rapidly collects emergency alerts and evacuation shelter information from multiple sources. The device then processes and filters this information and visually displays it to the user in the vehicle. When the user asks the device, "What is the best evacuation route?", the navigation system calculates the optimal evacuation route and presents it based on real-time data. If the emotion engine detects high stress levels in the user's input, it provides the information along with a reassuring message.

[1344] Prompt Sentence Examples

[1345] 1. Obtain disaster information:

[1346] Please collect the latest disaster information from the API endpoint.

[1347] 2. Emotion recognition:

[1348] Identify the sentiment based on the text entered by the user.

[1349] 3. Providing optimal evacuation routes:

[1350] Provide the best evacuation route based on your current location.

[1351] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1352] Step 1:

[1353] The server collects disaster information from various API endpoints. It uses HTTP requests to obtain data such as evacuation shelter information, emergency alerts, and supply status. The obtained data is integrated into a single database. The input is the various API endpoints, and the output is the integrated database.

[1354] Step 2:

[1355] The server processes and filters the collected information. It removes duplicate and unnecessary information and checks for accuracy. Information is categorized and prioritized as needed. The input is the consolidated database and the output is the filtered information.

[1356] Step 3:

[1357] The processed and filtered information is published in real time. The server sends the processed data to the autonomous vehicle's terminal. The input is the filtered information, and the output is the information sent to the terminal.

[1358] Step 4:

[1359] The terminal visually displays the information sent from the server. It uses text information, graphs, figures, etc. to present the necessary information to the user in an easy-to-understand format. The input is the information sent from the server, and the output is the information displayed on the visual display.

[1360] Step 5:

[1361] A user inputs a question to a terminal. For example, the user inputs a question such as "Where is the nearest evacuation shelter?" The input is the user's question, and the output is the question passed to the terminal via the user interface.

[1362] Step 6:

[1363] The device's generative artificial intelligence generates the best answer based on the user's question. Depending on the content of the question, it searches a real-time database and generates an answer. The input is the user's question and real-time data, and the output is the generated answer.

[1364] Step 7:

[1365] The device's emotion engine recognizes emotions from user input information. It analyzes the text and voice entered by the user and determines their emotional state. The input is the user's input information, and the output is the emotion recognition result.

[1366] Step 8:

[1367] Based on the emotion recognition results, generative AI provides information according to the emotional state. If a high stress state is recognized, a message or advice to reassure the user is added. The input is the emotion recognition result and the generated answer, and the output is an information message that takes emotion into consideration.

[1368] Step 9:

[1369] The navigation system provides the optimal evacuation route based on the vehicle's current location information. It combines the current location and information on nearby evacuation shelters to calculate the optimal route and present it to the user. The input is the current location information and information on nearby evacuation shelters, and the output is the optimal evacuation route.

[1370] 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.

[1371] 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.

[1372] 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.

[1373] 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.

[1374] FIG. 9 is a diagram illustrating 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 actions 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.

[1375] 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.

[1376] 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).

[1377] 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.

[1378] 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."

[1379] 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.

[1380] 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).

[1381] 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.

[1382] 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.

[1383] 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.

[1384] 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.

[1385] 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.

[1386] 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.

[1387] 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.

[1388] 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.

[1389] 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.

[1390] 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.

[1391] The following is further disclosed regarding the above embodiment.

[1392] (Claim 1)

[1393] A means for collecting disaster information in real time;

[1394] means for processing and filtering the collected information;

[1395] means for publishing the processed and filtered information; and

[1396] means for using generative artificial intelligence to provide information interactively to a user;

[1397] A means for visually displaying information in an understandable manner; and

[1398] A system including:

[1399] (Claim 2)

[1400] 2. The system according to claim 1, further comprising means for providing a course of action based on publicly available disaster information.

[1401] (Claim 3)

[1402] 10. The system of claim 1, further comprising means for using generative artificial intelligence to analyze user input information and prescribe optimal disaster response actions.

[1403] "Example 1"

[1404] (Claim 1)

[1405] A means for collecting disaster information in real time using communication technology;

[1406] A means for incorporating and analyzing the collected information into an integrated database;

[1407] communication means for providing the aggregated and filtered data to a user device;

[1408] means for responding to user inquiries using generative artificial intelligence;

[1409] means for visually displaying information in a manner that is intuitively understandable to a user;

[1410] A system including:

[1411] (Claim 2)

[1412] 2. The system according to claim 1, further comprising means for proposing an optimal course of action based on the publicly available disaster information.

[1413] (Claim 3)

[1414] 10. The system of claim 1, further comprising means for using generative artificial intelligence to analyze input data, such as a user's location information, and to utilize statistical algorithms to recommend optimal evacuation routes and shelters.

[1415] "Application Example 1"

[1416] (Claim 1)

[1417] A means for collecting disaster information in real time;

[1418] means for processing and filtering the collected information;

[1419] means for publishing the processed and filtered information; and

[1420] means for using generative artificial intelligence to provide information interactively to a user;

[1421] A means for visually displaying information in an understandable manner; and

[1422] means for obtaining location information of a user;

[1423] A means for suggesting appropriate actions to users based on the acquired location information and disaster information;

[1424] means for generating optimal answers to user queries using generative artificial intelligence;

[1425] A system including:

[1426] (Claim 2)

[1427] 2. The system according to claim 1, further comprising means for providing a course of action based on publicly available disaster information.

[1428] (Claim 3)

[1429] 10. The system of claim 1, further comprising means for using generative artificial intelligence to analyze user input information and prescribe optimal disaster response actions.

[1430] "Example 2: Combining Emotion Engines"

[1431] (Claim 1)

[1432] A means for collecting disaster information in real time;

[1433] means for processing and filtering the collected information;

[1434] means for publishing the processed and filtered information; and

[1435] means for using generative artificial intelligence to provide information interactively to a user;

[1436] A means for visually displaying information in an understandable manner; and

[1437] means for recognizing a user's emotion and adjusting information according to the emotion;

[1438] A system including:

[1439] (Claim 2)

[1440] 2. The system according to claim 1, further comprising means for providing a course of action based on publicly available disaster information.

[1441] (Claim 3)

[1442] 10. The system of claim 1, further comprising means for using generative artificial intelligence to analyze user input information and prescribe optimal disaster response actions.

[1443] "Application example 2 when combining emotion engines"

[1444] (Claim 1)

[1445] A means for collecting disaster information in real time;

[1446] means for processing and filtering the collected information;

[1447] means for publishing the processed and filtered information; and

[1448] means for using generative artificial intelligence to provide information interactively to a user;

[1449] means including an emotion engine for recognizing a user's emotion and providing information according to the emotion;

[1450] a means for using a navigation system to provide an optimal route based on the vehicle's location information;

[1451] A means for visually displaying information in an understandable manner; and

[1452] A system including:

[1453] (Claim 2)

[1454] 10. The system according to claim 1, further comprising means for providing a course of action based on the publicly available disaster information.

[1455] (Claim 3)

[1456] 10. The system of claim 1, further comprising means for using generative artificial intelligence to analyze user input information and prescribe optimal disaster response actions. [Explanation of symbols]

[1457] 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 collecting disaster information in real time; means for processing and filtering the collected information; means for publishing the processed and filtered information; and means for using generative artificial intelligence to provide information interactively to a user; A means for visually displaying information in an understandable manner; and A system including:

2. The system according to claim 1 , further comprising means for providing a course of action based on publicly available disaster information.

3. 10. The system of claim 1, further comprising means for using generative artificial intelligence to analyze user input information and prescribe optimal disaster response actions.

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