System

Abstract

A system is provided.SOLUTION: A system for collecting and sharing information when a disaster occurs, the system comprising means for acquiring position information of a user, means for collecting disaster information of a corresponding area on the basis of the position information, means for displaying the disaster information on a map, chatbot means using a generation model that receives a question of the user, means for displaying an answer generated by the chatbot means, and means for inputting and sharing a situation of a relief supply or a public service.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When a disaster occurs, it is necessary to collect a large amount of information efficiently and quickly to make decisions, but this is not easy, especially when power sources and communication infrastructure are limited. In addition, there is a lack of means to grasp the local aid situation in real time, making it difficult to grasp the necessary and excess aid supplies and to distribute them appropriately. Therefore, the challenge is to efficiently and accurately collect and share the information needed during a disaster. [Means for solving the problem]

[0005] To solve this problem, we provide a system for collecting and sharing information when a disaster occurs. This system includes a means for acquiring user location information and a means for collecting disaster information for the relevant area based on the location information. It also includes a means for displaying the collected disaster information on a map and a chatbot means that uses a generative model to accept questions from users. Furthermore, by including a means for displaying answers generated by the chatbot means and a means for inputting and sharing the status of relief supplies and public services, real-time information sharing between users is realized.

[0006] "User location information" means information about your current location obtained from your device, primarily provided by GPS data.

[0007] "Disaster information" means information about natural disasters such as earthquakes, tsunamis, floods, and fires, and information about the status of related infrastructure and services.

[0008] "Means for displaying on a map" refers to a function that uses a geographic information system (GIS) on a terminal to visually display disaster information and support information.

[0009] "Chatbot means using generative models" is a function that uses a generative AI model that performs natural language processing to generate and provide appropriate answers to questions entered by users.

[0010] "Means for inputting and sharing the status of relief supplies and public services" is a function that allows users to input the current status of relief supplies and the availability of public services and share that information with other users.

[0011] A "database" is a system for systematically storing and managing collected data such as disaster information, support information, and user questions and answers.

[0012] "Means of real-time updates" refers to the function that enables the system to instantly obtain the latest information and provide it to users.

[0013] "Notifications" are messages or alerts that inform relevant users when new information is added to the database. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0022] [First embodiment]

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

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

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

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

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

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

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

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

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

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

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0035] This invention relates to a system for collecting and sharing necessary information when a disaster occurs, and has the function of providing disaster information based on the user's location information and generating appropriate answers to user questions using a generative AI model.

[0036] Program processing overview

[0037] System Configuration

[0038] The system of the present invention is composed of a "server," a "terminal," and a "user."

[0039] 1. Processing when the app starts

[0040] Device: When a user launches the app, the app first prepares to display a map on the initial screen, then uses the GPS function to obtain the user's location information and sends this location information to the server.

[0041] 2. Displaying information on the map

[0042] Server: Receives location information sent from the device and retrieves disaster information for the relevant area from a database based on that information. Combines the retrieved disaster information with map data to generate visually displayable map data and send it to the device.

[0043] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to view.

[0044] 3. Question and answering by chatbot

[0045] User: Enters a question into the chatbot's input field and submits it.

[0046] Terminal: Sends user questions to the server.

[0047] Server: Receives the question and analyzes it using a generative AI model. It then retrieves the necessary information from a database or external API to generate an appropriate answer. It then sends the generated answer to the device.

[0048] Terminal: Display the received response on the chatbot screen.

[0049] 4. Sharing support status

[0050] User: Enter the current status of relief supplies and public service usage.

[0051] Terminal: Sends the entered information to the server.

[0052] Server: Stores the received information in a database and sends notifications to other users in the same area.

[0053] On your device: Display the assistance you receive on a map and share it with other users.

[0054] Specific examples

[0055] Example 1: Displaying disaster information

[0056] User: Launch the app and allow location information to be sent.

[0057] Device: Sends location information to the server, receives map data, and displays it.

[0058] Server: Receives location information from users in Sapporo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Sapporo, and generates map data.

[0059] Terminal: Analyzes the received map data and displays disaster information on the map.

[0060] Example 2: Asking a Chatbot

[0061] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[0062] Terminal: Sends the entered question to the server.

[0063] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as, "The nearest evacuation shelter is XX Park."

[0064] Terminal: Display the received response on the chatbot screen.

[0065] Example 3: Sharing relief supplies

[0066] User: Enters the information "Water is running low" and submits.

[0067] Terminal: Sends the entered assistance information to the server.

[0068] Server: Receives the information, stores it in a database, and sends notifications to users in the same area.

[0069] Device: Receive a notification and see a "Water Shortage" icon on the map.

[0070] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs.

[0071] The processing flow will be explained below.

[0072] 1. Processing when the app starts

[0073] Step 1:

[0074] Device: The user launches the app.

[0075] Step 2:

[0076] Terminal: Prepares the layout to display the map on the initial screen.

[0077] Step 3:

[0078] Device: Uses GPS to obtain the user's location.

[0079] Step 4:

[0080] Device: Sends the acquired location information to the server.

[0081] 2. Displaying information on the map

[0082] Step 1:

[0083] Server: Receives location information sent from the device.

[0084] Step 2:

[0085] Server: Based on the location information, search for disaster information for the relevant area from the disaster information database.

[0086] Step 3:

[0087] Server: Incorporates disaster information for the relevant area into map data.

[0088] Step 4:

[0089] Server: Sends the generated map data to the device.

[0090] Step 5:

[0091] Terminal: Analyzes the received map data and displays it on the screen.

[0092] Step 6:

[0093] Terminal: Place disaster information icons and text on the map.

[0094] 3. Question and answering by chatbot

[0095] Step 1:

[0096] User: Enter a question into the chatbot's input field.

[0097] Step 2:

[0098] User: Presses the submit button to send the question to the server.

[0099] Step 3:

[0100] Terminal: Transfers the entered question to the server.

[0101] Step 4:

[0102] Server: Receives the question and analyzes the sentence using a generative AI model.

[0103] Step 5:

[0104] Server: Based on the query, retrieves the necessary information from a database or external API.

[0105] Step 6:

[0106] Server: Generates the appropriate answer.

[0107] Step 7:

[0108] Server: Sends the generated answer to the device.

[0109] Step 8:

[0110] Terminal: Display the received response on the chatbot screen.

[0111] 4. Sharing support status

[0112] Step 1:

[0113] User: Enter the status of use of relief supplies and public services.

[0114] Step 2:

[0115] User: Presses the submit button to send the information to the server.

[0116] Step 3:

[0117] Terminal: Transfers the input assistance information to the server.

[0118] Step 4:

[0119] Server: Receives assistance information and stores it in a database.

[0120] Step 5:

[0121] Server: Sends notifications to other users in the same area.

[0122] Step 6:

[0123] Terminal: Receives notification of support information received from the server.

[0124] Step 7:

[0125] Terminal: Displays aid status icons such as "water shortage" and "food surplus" on the map.

[0126] Example 1

[0127] 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."

[0128] In modern society, rapid and accurate information gathering and sharing is required when a disaster occurs. However, many current systems do not adequately provide real-time information based on the user's location information, and there are insufficient means to efficiently share disaster information and the status of relief supplies. As a result, users may not be able to obtain the necessary information quickly, which can delay appropriate responses.

[0129] 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.

[0130] In this invention, the server includes means for displaying a map on an initial screen when a user launches an application, means for acquiring user location information using GPS and transmitting the location information to the server, means for collecting disaster information for a corresponding area from a database based on the location information, means for combining the collected disaster information with map data to generate visually displayable map data and transmitting the data to the terminal, chatbot means for analyzing user questions using a generative model and generating appropriate answers, means for displaying the answers generated by the chatbot means, means for inputting the status of relief supplies and public services, saving the information in a database, and notifying other users, and means for displaying the relief information on a map. This enables users to quickly acquire and efficiently share disaster information based on their location information in real time.

[0131] "User" refers to any individual or entity that uses the System.

[0132] "Information collection means" refers to a combination of hard and soft data for obtaining specified information.

[0133] "Location Information" means data indicating a user's current geographic location obtained using technology such as GPS.

[0134] "Initial screen display means" refers to a function for providing the user with the initial screen that is displayed when the application is launched.

[0135] "Map Data" refers to data that includes visual representations of geographically based maps.

[0136] "Disaster information" refers to data related to disasters such as earthquakes, tsunamis, floods, and fires.

[0137] A "chatbot" is software that uses natural language processing to automatically respond to user questions.

[0138] A "generative AI model" refers to an algorithm or model that uses AI technology to automatically generate answers or explanations.

[0139] "Relief supplies" refers to relief supplies such as water, food, and medical supplies needed in the event of a disaster.

[0140] "Public services" refers to public services that can be used during a disaster, such as information on evacuation shelters and the operation status of public transportation.

[0141] "Notification means" refers to a function for notifying users of new or updated information.

[0142] "Real-time" refers to near-instantaneous processing or information updates.

[0143] "Database" refers to a system that stores data in a structured format.

[0144] "Map display means" refers to a function for displaying information on a map in a format that is easy for users to understand.

[0145] This invention is a system for collecting and sharing necessary information in the event of a disaster. The system of this invention is composed of a server, terminals, and users, and efficiently manages and provides information through their respective roles.

[0146] The system uses the Google Maps API to provide a means to display a map on the initial screen. When a user launches the application, the device first prepares to display the map on the initial screen. Next, the device uses the GPS function to obtain the user's location information and sends this location information to the server. This location information is sent securely using HTTPS.

[0147] The server receives the location information sent from the device and collects disaster information for the relevant area from a database (e.g., PostgreSQL) based on that location information. The collected disaster information is combined with map data (e.g., OpenStreetMap) to generate visually displayable map data and send it to the device.

[0148] The device analyzes the received map data and displays disaster information on the map in a user-friendly format. Specifically, various disaster icons (e.g., earthquake, flood, fire) are displayed on the map.

[0149] The system of the present invention also provides a chatbot function that uses a generative AI model. The user enters a question into the chatbot's input field and sends it. For example, "Where is the nearest evacuation shelter?" The device sends the entered question to a server, which receives the question and analyzes it using a generative AI model (e.g., OpenAI's GPT-3). Based on the analysis results, the system obtains the necessary information from a database or external API and generates an appropriate answer. The generated answer is sent to the device and displayed on the chatbot screen.

[0150] The system also includes a function for inputting and sharing the status of relief supplies and public services. Users can input the current status of relief supplies and the use of public services and send a message saying, "There is a shortage of water." The device sends this information to a server, which stores the received information in a database. Notifications are then sent to other users in the same area, and the device displays the received support information on a map. This allows for efficient and accurate information collection and sharing among users when a disaster occurs.

[0151] As a specific example, when a user launches the app and allows location information to be sent, the device sends the location information to a server, which receives and displays map data. The server receives the user's location information in Sapporo, collects disaster information such as earthquakes, tsunamis, floods, and fires in the Sapporo area, and generates map data. The device analyzes the received map data and displays the disaster information on a map.

[0152] When a user types a question into the chatbot, such as "Where is the nearest evacuation shelter?", the device sends the question to the server, which analyzes the question, searches for information about evacuation shelters in the area, and generates a response such as "The nearest evacuation shelter is XX Park." The device then displays the received response on the chatbot screen.

[0153] In this way, the system of the present invention makes it possible to quickly collect necessary information based on the user's location information when a disaster occurs, display it visually, generate appropriate answers to the user's questions, and share the status of relief supplies.

[0154] Examples of prompts:

[0155] "Where is the nearest evacuation shelter?"

[0156] Please tell me the current fire information.

[0157] "There's a water shortage."

[0158] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0159] Step 1:

[0160] Device: When the user launches the app, it begins preparations to display a map on the initial screen. Specifically, it loads the initial map data using the Google Maps API. The input triggers the application launch, and the output is that the map is ready to be displayed on the initial screen.

[0161] Step 2:

[0162] Device: Uses GPS to obtain the user's location information. This location information includes latitude and longitude. The obtained location information is sent to the server using HTTPS. The input is the latitude and longitude data obtained from the GPS, and the output is the completion of transmission to the server.

[0163] Step 3:

[0164] Server: Receives location information sent from the device. The input is the location data from the device, and the output is the completion of location information reception.

[0165] Step 4:

[0166] Server: Based on the received location information, retrieves disaster information for the corresponding area from the database. For example, if the location information is Sapporo city, collects disaster information such as earthquakes, tsunamis, floods, and fires around Sapporo city. The input is the received location information, and the output is disaster information data for the corresponding area.

[0167] Step 5:

[0168] Server: Combines collected disaster information with map data to generate visually displayable map data. The map data is obtained from map services such as OpenStreetMap. The input is disaster information data and map data, and the output is visually displayable map data.

[0169] Step 6:

[0170] Server: Sends visually displayable map data to the device. The input is the generated map data, and the output is the completion of transmission to the device.

[0171] Step 7:

[0172] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to see. Specifically, various disaster icons (e.g., earthquake, flood, fire) are displayed on the map. The input is the received map data, and the output is the map displayed to the user.

[0173] Step 8:

[0174] User: Enters a question into the chatbot's input field and submits it. For example, "Where is the nearest evacuation shelter?" The input is the user's question, and the output is submission.

[0175] Step 9:

[0176] Terminal: Sends the user's question to the server. The input is the user's question, and the output is the completion of transmission to the server.

[0177] Step 10:

[0178] Server: Receives the question and analyzes it using a generative AI model. The input is the received question, and the output is the analysis result.

[0179] Step 11:

[0180] Server: Based on the analysis results, obtains the necessary information from a database or external API and generates an appropriate answer. For example, search for information on the nearest evacuation shelter and generate an answer such as "The nearest evacuation shelter is XX Park." The input is the analysis results and information from the database or external API, and the output is the generated answer.

[0181] Step 12:

[0182] Server: Sends the generated answer to the terminal. The input is the generated answer, and the output is the completion of sending it to the terminal.

[0183] Step 13:

[0184] Terminal: Displays the received answer on the chatbot screen. The input is the received answer, and the output is the answer displayed to the user.

[0185] Step 14:

[0186] User: Enters the current status of relief supplies and the status of public service use. For example, enters "There is a water shortage." The input is the relief information entered by the user, and the output is transmission completion.

[0187] Step 15:

[0188] Terminal: Sends the input assistance information to the server. The input is the user's assistance information, and the output is the completion of transmission to the server.

[0189] Step 16:

[0190] Server: Saves the received information in the database. Here, the relief supplies information is updated. The input is the received relief information, and the output is the completion of saving it to the database.

[0191] Step 17:

[0192] Server: Sends notifications of received support information to other users in the same area. Uses push notification service. Input is support information stored in the database, and output is notification sending completion.

[0193] Step 18:

[0194] Terminal: Receives notifications and displays a "water shortage" icon on the map. The input is the received notification information, and the output is the map update shown to the user.

[0195] (Application example 1)

[0196] 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."

[0197] When a disaster or crime occurs, it is necessary to quickly and accurately grasp local danger information and support situations and provide users with appropriate countermeasures. However, current systems have limited real-time information updates and question-and-answer functions using generative models, making it difficult for users to quickly obtain the information they need. Furthermore, support information is often not shared effectively with other users. This poses a challenge in ensuring user safety in emergency situations where a rapid response is required.

[0198] 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.

[0199] In this invention, the server includes means for acquiring user location information, means for collecting disaster information and danger information for the relevant area based on the location information, means for displaying the disaster information and danger information on a map, and means for notifying other users of the danger information. This enables users to acquire information and share support information in real time even when a disaster or crime occurs, enabling them to respond quickly and appropriately.

[0200] "Disaster information" refers to information that includes specific damage situations and warnings regarding natural disasters and man-made disasters.

[0201] "Danger information" is information that includes specific situations and warnings regarding man-made dangers such as crimes and accidents.

[0202] A "generative model" refers to an artificial intelligence model that generates appropriate responses from large amounts of data, and includes natural language processing technology.

[0203] A "chatbot" is a system that automatically generates and provides appropriate answers to user questions using a generative model.

[0204] "Location Information" means your current geographic coordinates obtained using GPS or other positioning technology.

[0205] "Notification means" refers to systems and functions for communicating dangerous or important information to other users in real time.

[0206] "Support information" refers to information about the status of relief supplies and the use of public services, and is primarily shared during disasters and emergencies.

[0207] A "database" refers to a collection of data that is organized to store information and make it easy to search and update.

[0208] "User" refers to an individual or organization that uses this system and provides location information and inputs questions.

[0209] The present invention is a system for quickly and accurately collecting and sharing information in the event of a disaster or crime. Specific embodiments of the present invention will be described below.

[0210] System Configuration

[0211] The system of the present invention consists of a "server," a "terminal," and a "user." This system collects disaster and danger information based on the user's location information and provides that information to the user. It also uses a generative AI model to generate appropriate answers to the user's questions and shares the status of relief supplies and public services with other users in real time.

[0212] Hardware and software used

[0213] Hardware: Smartphone (iOS / Android compatible), smart glasses, GPS module

[0214] Software: GPS API, generative AI models (e.g. OpenAI GPT-4), RESTful API, database (MySQL)

[0215] Processing when the app starts

[0216] When a user launches the app, the device first prepares to display a map on the initial screen, then uses GPS to obtain the user's location information and sends it to the server, which uses this location information to collect disaster and danger information.

[0217] Displaying information on a map

[0218] The server retrieves disaster and danger information for the area based on the user's location information from a database, combines it with map data, and generates visually displayable map data. This map data is then sent to the device, which analyzes the received data and displays the information on the map in a format that is easy for the user to view.

[0219] Chatbot Q&A

[0220] The user enters a question into the chatbot's input field and sends it. The device sends the user's question to the server, which analyzes the received question using a generative AI model. The server then retrieves the necessary information from a database or external API, generates an appropriate answer, and sends it back to the device. The device then displays the received answer on the chatbot screen.

[0221] Prompt Sentence Examples

[0222] "Where is the nearest evacuation shelter?"

[0223] Please tell me about recent crimes.

[0224] "Please tell me the current weather conditions."

[0225] Sharing support status

[0226] Users input the current status of relief supplies and the use of public services, and send it to the server via their device. The server stores the received information in a database and sends notifications to other users in the same area. The device then displays the received relief information on a map and shares it with other users.

[0227] Example 1: Displaying disaster information

[0228] When a user launches the app and allows the transmission of location information, the device sends the location information to the server. For example, when the server receives the location information of a user in a certain city, it collects disaster information such as earthquakes, tsunamis, floods, and fires around that city and generates map data. The device analyzes the received map data and displays the disaster information on a map.

[0229] Example 2: Asking a Chatbot

[0230] When a user types the question "Where is the nearest evacuation shelter?" into the chatbot and sends it, the device sends the question to the server. The server analyzes the question, searches for information on evacuation shelters in the area, and generates an appropriate answer, such as "The nearest evacuation shelter is XX Park." The device then displays the received answer on the chatbot screen.

[0231] Example 3: Sharing relief supplies

[0232] When a user inputs and submits the information "Water shortage," the device sends the input assistance information to the server. The server receives the information, stores it in a database, and sends a notification to users in the same area. The device receives the notification and displays a "Water shortage" icon on the map.

[0233] In this way, the system of the present invention can efficiently and accurately collect and share information during disasters and crimes.

[0234] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0235] Step 1:

[0236] When a user launches the app, the device first prepares to display a map on the initial screen and obtains the user's location information using the GPS function. The input is the user's current location information, and the output is the obtained location information. This location information is then processed (for example, converted into JSON format) to be sent to the server.

[0237] Step 2:

[0238] The server receives the location information sent from the device and retrieves disaster and danger information for the relevant area from the database based on the location information. This information collection is performed using a database search query, with location information as input and disaster and danger information as output.

[0239] Step 3:

[0240] The server combines the acquired disaster and danger information with map data to generate visually displayable map data. Here, the map data is generated using a GIS (geographic information system) API, with the input being information about the relevant area and the output being displayable map data. The generated map data is sent to the device.

[0241] Step 4:

[0242] The terminal analyzes the received map data and displays disaster and danger information on the map in a format that is easy for the user to view. The input is the received map data, and the output is a display in a format that the user can view.

[0243] Step 5:

[0244] The user enters a question into the chatbot's input field and submits it. The input is the user's question, and the output is the question data to be sent to the server. The question data is sent to the server in text format.

[0245] Step 6:

[0246] The server receives a question from the user and analyzes the question using a generative AI model. The input is the user's question, and the output is the analyzed question. The AI ​​model collects information from appropriate databases and external APIs.

[0247] Step 7:

[0248] The server obtains the necessary information based on the analyzed question and generates an appropriate answer. The input is the analyzed question, and the output is the generated answer. The generated answer is sent to the terminal.

[0249] Step 8:

[0250] The terminal displays the received answer on the chatbot screen. The input is the received answer, and the output is a display in a format that can be viewed by the user.

[0251] Step 9:

[0252] Users input the current status of relief supplies and the status of public service usage, and send it to the server via their terminal. The input is relief information, and the output is data to be sent to the server. This data is sent to the server in text format.

[0253] Step 10:

[0254] The server stores the received assistance information in a database and sends notifications to other users in the same area. The input is assistance information, and the output is a notification message. Notifications are sent using a push notification API.

[0255] Step 11:

[0256] The device receives the notification and displays the support information on the map. The input is the received notification message, and the output is the support information displayed on the map. This allows other users to share support information in real time.

[0257] The above are the specific processing steps of the system that realizes the application example.

[0258] 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.

[0259] This invention combines a system for collecting and sharing necessary information in the event of a disaster with an emotion engine that recognizes the user's emotions, thereby providing appropriate information according to the user's psychological state.

[0260] Program processing overview

[0261] System Configuration

[0262] The system of the present invention is composed of a "server," a "terminal," and a "user." It also incorporates an emotion engine for recognizing the user's emotions.

[0263] 1. Processing when the app starts

[0264] On the device: When a user launches the app, the app prepares a layout to display a map on the initial screen, and uses the GPS function to obtain the user's location information. This location information is then sent to the server.

[0265] 2. Displaying information on the map

[0266] Server: Receives location information sent from the device, searches for disaster information for the relevant area in the disaster information database based on the location information, incorporates the disaster information for the relevant area into map data, and sends the generated map data to the device.

[0267] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to view.

[0268] 3. Question and answering by chatbot

[0269] User: Enters a question into the chatbot's input field and submits it.

[0270] Terminal: Sends user questions to the server.

[0271] Server: Receives the question and analyzes it using the generative AI model. Retrieves necessary information from databases and external APIs to generate an appropriate answer. Sends the generated answer to the device.

[0272] Terminal: Display the received response on the chatbot screen.

[0273] 4. Sharing support status

[0274] User: Enter and submit information on the status of relief supplies and the use of public services.

[0275] Terminal: Sends the entered information to the server.

[0276] Server: Saves the entered assistance information in a database and sends notifications to other users.

[0277] On your device: Display the assistance you receive on a map and share it with other users.

[0278] 5. Use of Emotion Engine

[0279] Users: Express their emotions (e.g., text, facial expressions) while interacting with the app or asking questions.

[0280] On-device: Recognizes user emotions using an emotion engine.

[0281] Server: Receives the user's emotional data recognized by the emotion engine and adjusts the tone of the response and provides appropriate information. For example, if the server detects that the user is feeling anxious, it provides information in a reassuring manner.

[0282] Specific examples

[0283] Example 1: Displaying disaster information

[0284] User: Launch the app and allow location information to be sent.

[0285] Device: Sends location information to the server, receives map data, and displays it.

[0286] Server: Receives location information from users in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Tokyo, and generates map data.

[0287] Terminal: Analyzes the received map data and displays disaster information on the map.

[0288] Example 2: Asking a Chatbot

[0289] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[0290] Terminal: Sends the entered question to the server.

[0291] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as "The nearest evacuation shelter is XX Park."

[0292] Terminal: Display the received response on the chatbot screen.

[0293] Example 3: Sharing relief supplies

[0294] User: Enters the information "Water is running low" and submits.

[0295] Terminal: Sends the entered assistance information to the server.

[0296] Server: Receives the information, stores it in a database, and notifies users in the same area.

[0297] Device: Receive a notification and see a "Water Shortage" icon on the map.

[0298] Example 4: Using an Emotion Engine

[0299] User: Type, "I'm really worried. Is there anything I can reassure you about?"

[0300] Device: The emotion engine recognizes the user's emotion of "anxiety."

[0301] Server: Generates a reassuring response based on the perceived emotion (e.g., "Nearby evacuation centers have sufficient supplies").

[0302] Device: Display responses based on emotions.

[0303] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs, and also provides appropriate information based on the user's emotions.

[0304] The processing flow will be explained below.

[0305] Program processing flow (including emotion engine)

[0306] 1. Processing when the app starts

[0307] Step 1:

[0308] Device: The user launches the app.

[0309] Step 2:

[0310] Terminal: Prepares the layout to display the map on the initial screen.

[0311] Step 3:

[0312] Device: Uses GPS to obtain the user's location.

[0313] Step 4:

[0314] Device: Sends the acquired location information to the server.

[0315] 2. Displaying information on the map

[0316] Step 1:

[0317] Server: Receives location information sent from the device.

[0318] Step 2:

[0319] Server: Based on the location information, search for disaster information for the relevant area from the disaster information database.

[0320] Step 3:

[0321] Server: Incorporates disaster information for the relevant area into map data.

[0322] Step 4:

[0323] Server: Sends the generated map data to the device.

[0324] Step 5:

[0325] Terminal: Analyzes the received map data and displays it on the screen.

[0326] Step 6:

[0327] Terminal: Place disaster information icons and text on the map.

[0328] 3. Question and answering by chatbot

[0329] Step 1:

[0330] User: Enter a question into the chatbot's input field.

[0331] Step 2:

[0332] User: Presses the submit button to send the question to the server.

[0333] Step 3:

[0334] Terminal: Transfers the entered question to the server.

[0335] Step 4:

[0336] Server: Receives the question and analyzes the sentence using a generative AI model.

[0337] Step 5:

[0338] Server: Based on the query, retrieves the necessary information from a database or external API.

[0339] Step 6:

[0340] Server: Generates the appropriate answer.

[0341] Step 7:

[0342] Server: Sends the generated answer to the device.

[0343] Step 8:

[0344] Terminal: Display the received response on the chatbot screen.

[0345] 4. Sharing support status

[0346] Step 1:

[0347] User: Enter the status of use of relief supplies and public services.

[0348] Step 2:

[0349] User: Presses the submit button to send the information to the server.

[0350] Step 3:

[0351] Terminal: Transfers the input assistance information to the server.

[0352] Step 4:

[0353] Server: Receives assistance information and stores it in a database.

[0354] Step 5:

[0355] Server: Sends notifications to other users in the same area.

[0356] Step 6:

[0357] Terminal: Receives notification of support information received from the server.

[0358] Step 7:

[0359] Terminal: Displays aid status icons such as "water shortage" and "food surplus" on the map.

[0360] 5. Use of Emotion Engine

[0361] Step 1:

[0362] Users: Input or express their emotions (e.g., text, facial expressions) while interacting with or asking questions within the app.

[0363] Step 2:

[0364] On-device: Recognizes user emotions using an emotion engine.

[0365] Step 3:

[0366] Device: Sends the recognized emotion data to the server.

[0367] Step 4:

[0368] Server: Receives emotion data and stores it in a database.

[0369] Step 5:

[0370] Server: Provides appropriate information and adjusts the tone of responses based on the user's emotions recognized by the emotion engine.

[0371] Step 6:

[0372] Server: Generates responses that correspond to the perceived emotion, for example, providing reassuring information if the user is feeling anxious.

[0373] Step 7:

[0374] Server: Sends the generated answer to the device.

[0375] Step 8:

[0376] Terminal: Display the received response on the chatbot screen.

[0377] Specific examples

[0378] Example 1: Displaying disaster information

[0379] Step 1:

[0380] User: Launch the app and allow location information to be sent.

[0381] Step 2:

[0382] Device: Sends location information to the server.

[0383] Step 3:

[0384] Server: Receives location information from users in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Tokyo, and generates map data.

[0385] Step 4:

[0386] Terminal: Analyzes the received map data and displays disaster information on the map.

[0387] Example 2: Asking a Chatbot

[0388] Step 1:

[0389] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[0390] Step 2:

[0391] Terminal: Sends the entered question to the server.

[0392] Step 3:

[0393] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as "The nearest evacuation shelter is XX Park."

[0394] Step 4:

[0395] Terminal: Display the received response on the chatbot screen.

[0396] Example 3: Sharing relief supplies

[0397] Step 1:

[0398] User: Enters the information "Water is running low" and submits.

[0399] Step 2:

[0400] Terminal: Sends the entered assistance information to the server.

[0401] Step 3:

[0402] Server: Receives the information, stores it in a database, and notifies users in the same area.

[0403] Step 4:

[0404] Device: Receive a notification and see a "Water Shortage" icon on the map.

[0405] Example 4: Using an Emotion Engine

[0406] Step 1:

[0407] User: Type, "I'm really worried. Is there anything I can reassure you about?"

[0408] Step 2:

[0409] Device: The emotion engine recognizes the user's emotion of "anxiety."

[0410] Step 3:

[0411] Device: Sends the recognized emotion data to the server.

[0412] Step 4:

[0413] Server: Generates a reassuring response based on the perceived emotion (e.g., "Nearby evacuation centers have sufficient supplies").

[0414] Step 5:

[0415] Device: Display responses based on emotions.

[0416] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs, and also provides appropriate information based on the user's emotions.

[0417] Example 2

[0418] 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."

[0419] When a disaster occurs, rapid and accurate information gathering and sharing is required, but the current system lacks the ability to provide information that takes into account the psychological state of the user.Furthermore, it is difficult to effectively update disaster information in real time and share the status of relief supplies.

[0420] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring user location information, means for collecting disaster information for a relevant area, means for displaying the disaster information on a map, chatbot means using a generative model to accept user questions, means for displaying generated answers, means for inputting and sharing the status of relief supplies and public services, emotion engine means for recognizing the user's emotions, and means for adjusting the content of answers and the provision of information based on the recognized emotions. This enables rapid and accurate information collection and sharing in the event of a disaster, and further enables the provision of appropriate information according to the user's psychological state.

[0421] "Means for obtaining user location information" means a method of using the device's GPS function or other location information obtaining technology to obtain the user's current location in the form of latitude and longitude.

[0422] The "means for collecting disaster information for the relevant area" is a method for searching and collecting disaster information such as earthquakes, tsunamis, floods, and fires in a specified area from a database based on the location information.

[0423] "Means for displaying disaster information on a map" refers to a method of incorporating collected disaster information into map data using a geographic information system (GIS) and presenting it visually to users.

[0424] A "chatbot method using a generative model" is a method that uses artificial intelligence (AI) to accept questions from users, analyzes the content of the question using natural language processing technology, and generates appropriate answers.

[0425] The "means for displaying the generated answer" is a method for displaying the answer generated by the chatbot means on the screen of the terminal.

[0426] "Means for inputting and sharing the status of relief supplies and public services" refers to a method by which users can input the status of relief supplies and the status of use of public services, send that information to a server, and share it with other users.

[0427] The "emotion engine means for recognizing user emotions" is a technology that determines the user's emotional state through text input and facial expression analysis, and acquires that emotional data.

[0428] "Means for adjusting response content and information provision based on recognized emotions" refers to a method for changing the tone of the information provided and responses based on the user's emotional data obtained by the emotion engine, thereby achieving a more appropriate and empathetic response.

[0429] This invention relates to a system for collecting and sharing information when a disaster occurs, and in particular to a system for recognizing the emotions of users and providing appropriate information.

[0430] System Configuration

[0431] The system of the present invention is composed of a server, a terminal, and a user. Each component and its function will be described in detail below.

[0432] server

[0433] The server is a central information processing unit that includes multiple functional modules. This central information processing unit has the following main functions:

[0434] 1. Location information receiving module:

[0435] This module receives user location information from the device and generates basic data for accessing the disaster information database. This module receives data using HTTPS communication.

[0436] 2. Disaster Information Collection Module:

[0437] Based on the location information, the system searches and collects the latest disaster information for the relevant area from a disaster information database. This disaster information includes various types such as earthquakes, tsunamis, floods, and fires.

[0438] 3. Map data generation module:

[0439] The collected disaster information is incorporated into map data and processed so that it can be displayed in a format that is intuitively easy for users to understand. This processing is done using a geographic information system (GIS).

[0440] 4. Chatbot module:

[0441] It uses generative AI models to respond to user questions, using natural language processing technologies such as OpenAI's GPT-3 to analyze the question and retrieve the necessary information from databases or external APIs to generate an answer.

[0442] 5. Support status management module:

[0443] Information about relief supplies and public services provided by users is stored in a database and notified to other users.

[0444] 6. Emotion Engine Module:

[0445] Recognize and capture user emotions. This emotional data is used to tailor question responses and information provision.

[0446] Terminal

[0447] A terminal is a device, including a smartphone or tablet, that acts as an interface between the user and the server. A terminal has the following functions:

[0448] 1. Acquisition of location information:

[0449] The GPS function is used to obtain the user's current location, which is saved as latitude and longitude and sent to the server.

[0450] 2. Map display:

[0451] The map data sent from the server is analyzed and disaster information is displayed intuitively, with icons and colors used to indicate the type of disaster.

[0452] 3. Chatbot screen:

[0453] It is an interface with a question input field and a text area, which sends questions from users to the server and displays the answers received.

[0454] 4. Emotion recognition:

[0455] It uses an emotion engine that analyzes text input and facial expressions to recognize the user's emotional state, and the recognized emotion data is sent to the server.

[0456] user

[0457] The user is the entity that uses the system and performs the following operations:

[0458] 1. Location Sharing:

[0459] Launch the app and allow it to send location information.

[0460] 2. Enter your question:

[0461] Enter your question in the chatbot's input field and submit.

[0462] 3. Enter supporting information:

[0463] Enter the status of relief supplies and the usage of public services and submit.

[0464] 4. Expressing emotions:

[0465] Express your emotions while interacting with the app or asking questions (e.g., through text, facial expressions).

[0466] Specific examples

[0467] Example 1: Displaying disaster information

[0468] When a user launches the app and allows location information to be sent, the device sends the location information to the server. The server receives the user's location information in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires in the Tokyo area, and generates map data. The device analyzes the received map data and displays the disaster information on the map. The server notifies the user that "the latest disaster information has been obtained."

[0469] Example 2: Asking a Chatbot

[0470] When a user inputs the question "Where is the nearest evacuation shelter?" into the chatbot and sends it, the device sends the question to the server. The server analyzes the question, searches for evacuation shelter information in the relevant area, and generates the answer "The nearest evacuation shelter is XX Park." The device displays the received answer on the chatbot screen. It also temporarily displays the message "Analyzing question..."

[0471] Example 3: Sharing relief supplies

[0472] When a user inputs and sends the information "There is a water shortage," the device sends the support information to the server. The server receives the information and stores it in a database. It also notifies other users in the same area. The device receives the notification and displays a "Water Shortage" icon on the map. It also displays the message "Support information has been added."

[0473] Example 4: Using an Emotion Engine

[0474] When the user inputs "I'm very anxious. Is there any information that can reassure me?", the device uses an emotion engine to recognize the user's emotion of "anxiety." Depending on the recognized emotion, the server generates a reassuring response such as "Nearby evacuation centers have sufficient supplies." The device displays the response according to the emotion and temporarily displays the message "Analyzing user's emotions..."

[0475] Prompt Sentence Examples

[0476] "Please tell me the latest disaster information for the Tokyo area."

[0477] "Please tell me where the evacuation shelter is."

[0478] "What should I do if there is a water shortage?"

[0479] "Please give me some information to ease my anxiety."

[0480] In this way, the system of the present invention not only efficiently and accurately collects and shares information when a disaster occurs, but also provides appropriate information based on the user's emotions.

[0481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0482] Step 1: What to do when the app starts

[0483] Device: When a user launches the app, the layout to be displayed on the initial screen is prepared and the GPS function is used to obtain the user's location. This location information is recorded as latitude and longitude. The recorded location information is sent to the server using HTTPS communication. Specifically, the device notifies the user by saying "Obtaining location information..."

[0484] Input: App launch, GPS location information

[0485] Data processing: location information acquisition, data recording (latitude and longitude)

[0486] Output: Location information transmission

[0487] Step 2: Displaying information on the map

[0488] server:

[0489] 1. The location information sent from the device is received. The received data is analyzed and the corresponding area is identified.

[0490] 2. Access the disaster information database and collect disaster information (earthquake, tsunami, flood, fire, etc.) for the identified area.

[0491] 3. The collected disaster information is incorporated into map data, which is generated using GIS.

[0492] 4. The generated map data is sent to the device.

[0493] Device:

[0494] 1. Analyze the received map data and display disaster information in a user-friendly format (e.g., using different colors and icons).

[0495] Specifically, it notifies the user that "the latest disaster information has been obtained."

[0496] Input: Location

[0497] Data processing: disaster information acquisition, map data generation

[0498] Output: Send map data, display disaster information on the map

[0499] Step 3: Answer questions with a chatbot

[0500] User:

[0501] 1. Enter your question in the chatbot's input field and submit.

[0502] Device:

[0503] 1. The question entered by the user is sent to the server.

[0504] server:

[0505] 1. Analyze the received question. A generative AI model (e.g., OpenAI's GPT-3) is used to analyze the content of the question using natural language processing techniques.

[0506] 2. Depending on the content of the question, access databases or external APIs to obtain the necessary information.

[0507] 3. Generate appropriate answers based on the information obtained.

[0508] 4. Send the generated answer to the device.

[0509] Device:

[0510] 1. Display the received answer on the chatbot screen. Specifically, it displays "Analyzing question..."

[0511] Input: Question

[0512] Data processing: Question analysis, information acquisition, answer generation

[0513] Output: Display answer

[0514] Step 4: Sharing support status

[0515] User:

[0516] 1. Enter and submit information about the status of relief supplies and the use of public services.

[0517] Device:

[0518] 1. The entered support information is sent to the server.

[0519] server:

[0520] 1. The received assistance information is stored in a database.

[0521] 2. Send notifications to other users in the same area based on the saved information.

[0522] Device:

[0523] 1. Receive a notification and display support information on the map. Specifically, the message "Support information has been added" will be displayed.

[0524] Input: Support information

[0525] Data processing: Support information storage, notification generation

[0526] Output: Support information display, notification

[0527] Step 5: Use the Emotion Engine

[0528] User:

[0529] 1. Express your emotions (through text, facial expressions, etc.) while operating or asking questions within the app.

[0530] Device:

[0531] 1. The emotion engine recognizes the user's emotions, using emotion recognition software and facial expression analysis using a camera.

[0532] 2. The recognized emotion data is sent to the server.

[0533] server:

[0534] 1. Receive emotion data obtained by the emotion engine.

[0535] 2. Adjust the content and tone of your responses based on the user's emotions. For example, if the user is feeling anxious, generate reassuring information.

[0536] Device:

[0537] 1. Display tailored answers or information to the user. Specifically, the action is to display "Analyzing user sentiment..."

[0538] Input: Emotion

[0539] Data processing: emotion recognition, data transmission, response adjustment

[0540] Output: Adjusted answer, information display

[0541] (Application example 2)

[0542] 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."

[0543] Conventional disaster information systems generally provide information based on location information and share relief supplies, but they have the problem of not being able to provide information that takes into account the user's psychological state. During disasters, users often feel anxiety and fear, and providing information that ignores these emotions does not provide sufficient support to the user. The present invention aims to improve the user's sense of security by recognizing the user's emotions and providing appropriate information according to those emotions.

[0544] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0545] In this invention, the server includes a means for acquiring user location information, a means for recognizing emotions, a chatbot means using a generative model, and a means for adjusting information provision based on emotion recognition, thereby enabling appropriate information provision that takes into account the user's psychological state.

[0546] "Disaster occurrence" refers to the time when a natural or man-made disaster occurs, and a rapid response is required to ensure the safety of the affected areas and people.

[0547] "Information collection and sharing" refers to the act of gathering data and knowledge needed in the event of a disaster and exchanging it with relevant people and organizations through communication means.

[0548] "User Location Information" refers to the geographic location of a User, obtained using location-finding technology such as GPS.

[0549] "Disaster information for the relevant area" refers to information about disasters related to the user's current location or the specified area, including data on the types and occurrence status of earthquakes, floods, fires, etc.

[0550] "Displaying on a map" means providing collected disaster information visually to users using digital maps and geographic information systems (GIS).

[0551] A "chatbot means using generative models" is a program that uses technology in the field of natural language processing to automatically generate answers to users' questions.

[0552] The "means for displaying the answer" is an interface that displays the answer generated by the generative model on the user's terminal.

[0553] "Status of relief supplies and public services" refers to information such as food, water, medical supplies, and other supplies provided during disasters, as well as the availability of evacuation shelters and the operation status of public transportation.

[0554] "Emotion recognition" refers to technology that determines a user's current emotional state by analyzing text, facial expressions, tone of voice, etc.

[0555] "Means for adjusting information provision" refers to a function that changes the content and presentation of information in an appropriate form according to the user's recognized emotions.

[0556] "Means for updating disaster information in real time" refers to technology that keeps collected disaster information up to date and provides it to users quickly.

[0557] The present invention is an information collection and sharing system for use in the event of a disaster. It can recognize the user's emotions and provide appropriate information accordingly. This system is realized by the following configuration and procedures.

[0558] 1. Obtaining user location information

[0559] When a user launches the app, the device uses its GPS to obtain the user's location information. This location information is then sent to a server, which then collects disaster information for the relevant area.

[0560] 2. Collecting and displaying disaster information for the relevant area

[0561] The server searches a database for disaster information for the relevant area based on the location information sent from the device. It then incorporates the disaster information into map data and sends the generated map data to the device. The device then analyzes this map data and displays the disaster information on a map in a format that is easy for the user to view.

[0562] 3. User Emotion Recognition

[0563] When a user enters an operation or question within the app, the device uses an emotion engine to recognize the emotion. This emotion engine determines the user's emotion by analyzing text, facial expressions, tone of voice, etc. The obtained emotion data is sent to the server.

[0564] 4. Question and Answering Using Chatbots

[0565] When a user types a question through the chatbot, it is sent to the server via the device. The server uses a generative AI model to analyze the question, retrieves necessary information from a database or external APIs, and generates an appropriate answer. This answer is adjusted based on the user's emotional state. For example, if the user is feeling anxious, a reassuring statement will be added to the answer. Finally, the answer is displayed on the device.

[0566] 5. Sharing the status of relief supplies and public services

[0567] When users input information about the status of relief supplies and the use of public services, the information is sent to the server via the device. The server stores the information in a database and sends notifications to other users. The device that receives the notification displays the information on a map and shares it with other users.

[0568] Specific examples

[0569] When a user opens the app, enters their location as "Tokyo," and then enters text expressing their feelings as "I'm anxious," this information is sent to the server and processed in the following steps:

[0570] Example prompt sentence:

[0571] "A user in Tokyo said, 'I'm worried.'"

[0572] Based on this information, the server collects disaster information for the area and generates a response that includes supplementary information to reassure the user. For example, the device might display something like, "Current disaster information: A flood warning has been issued. Please do not worry. The nearest evacuation shelter is safe."

[0573] This allows users to instantly obtain appropriate information according to their emotions, allowing them to respond to disasters with peace of mind.

[0574] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0575] Step 1:

[0576] When a user launches the app, the device uses its GPS function to obtain the user's location information. This location information is then sent to the server. The input is the user's current location, and the output is the transmission of location information to the server. Specifically, the app uses the smartphone's GPS function to send the obtained latitude and longitude data to the server.

[0577] Step 2:

[0578] The server collects disaster information for the relevant area based on the location information sent from the device. The input is the user's location information, and the output is map data that collects the disaster information. The server obtains the latest disaster information for the relevant area from the database and integrates it into the map data.

[0579] Step 3:

[0580] The server sends the generated map data to the device. The input is map data including disaster information, and the output is sending the map data to the device. Specifically, the map data is encoded in JSON format or similar and sent to the device via an API.

[0581] Step 4:

[0582] The terminal analyzes the map data received from the server and displays disaster information on the map in a format that is easy for the user to view. The input is the map data from the server, and the output is the user's display screen. The terminal analyzes the map data and overlays disaster information on the map with appropriate icons and text.

[0583] Step 5:

[0584] Users input operations or questions within the app, and the device uses an emotion engine to recognize the emotion. The input is the user's text and facial expression data, and the output is the recognized emotion data. Natural language processing and facial recognition technologies are used to analyze text and image data to determine emotions.

[0585] Step 6:

[0586] The device sends the recognized emotion data to the server. The input is emotion data, and the output is sending the emotion data to the server. Specifically, the emotion data is sent to the server via an API.

[0587] Step 7:

[0588] When a user enters a question through the chatbot, the device sends the question to the server. The input is the user's question text, and the output is the transmission of the question data to the server. The question entered in the text box is sent to the server via API.

[0589] Step 8:

[0590] The server analyzes the question content using a generative AI model based on the received question and emotion data. The input is question data and emotion data, and the output is analyzed answer data. The generative AI model analyzes the meaning of the question and generates an appropriate answer.

[0591] Step 9:

[0592] The server retrieves the necessary information from a database or external API and adjusts the information provided based on the recognized sentiment. The input is the analyzed response data and additional information from outside, and the output is the adjusted response. Specifically, if the user expresses anxiety, reassuring words are added to the response.

[0593] Step 10:

[0594] The server sends the generated adjusted answer to the device. The input is the adjusted answer, and the output is the answer sent to the device. The answer data is encoded in JSON format or similar and sent to the device.

[0595] Step 11:

[0596] The terminal displays the adjusted response on the chatbot screen. The input is the response data from the server, and the output is the user's display screen. The response is displayed in the chatbot interface in an appropriate format.

[0597] Step 12:

[0598] When users input information about the status of relief supplies and the use of public services, that information is sent to the server via their device. The input is relief information, and the output is the transmission of that information to the server. The relief information is sent to the server as text data via an API.

[0599] Step 13:

[0600] The server saves the input assistance information in a database and sends notifications to other users. The input is assistance information and the output is notification data. The server saves the information in a database, generates notifications, and sends them to users in the relevant area.

[0601] Step 14:

[0602] The device displays notifications received from the server on a map and shares them with other users. The input is notification data from the server, and the output is the user's display screen. The notification data is analyzed and displayed on the map with appropriate icons and text.

[0603] 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.

[0604] 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.

[0605] 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.

[0606] [Second embodiment]

[0607] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0608] 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.

[0609] 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).

[0610] 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.

[0611] 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.

[0612] 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).

[0613] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0618] 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."

[0619] This invention relates to a system for collecting and sharing necessary information when a disaster occurs, and has the function of providing disaster information based on the user's location information and generating appropriate answers to user questions using a generative AI model.

[0620] Program processing overview

[0621] System Configuration

[0622] The system of the present invention is composed of a "server," a "terminal," and a "user."

[0623] 1. Processing when the app starts

[0624] Device: When a user launches the app, the app first prepares to display a map on the initial screen, then uses the GPS function to obtain the user's location information and sends this location information to the server.

[0625] 2. Displaying information on the map

[0626] Server: Receives location information sent from the device and retrieves disaster information for the relevant area from a database based on that information. Combines the retrieved disaster information with map data to generate visually displayable map data and send it to the device.

[0627] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to view.

[0628] 3. Question and answering by chatbot

[0629] User: Enters a question into the chatbot's input field and submits it.

[0630] Terminal: Sends user questions to the server.

[0631] Server: Receives the question and analyzes it using a generative AI model. It then retrieves the necessary information from a database or external API to generate an appropriate answer. It then sends the generated answer to the device.

[0632] Terminal: Display the received response on the chatbot screen.

[0633] 4. Sharing support status

[0634] User: Enter the current status of relief supplies and public service usage.

[0635] Terminal: Sends the entered information to the server.

[0636] Server: Stores the received information in a database and sends notifications to other users in the same area.

[0637] On your device: Display the assistance you receive on a map and share it with other users.

[0638] Specific examples

[0639] Example 1: Displaying disaster information

[0640] User: Launch the app and allow location information to be sent.

[0641] Device: Sends location information to the server, receives map data, and displays it.

[0642] Server: Receives location information from users in Sapporo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Sapporo, and generates map data.

[0643] Terminal: Analyzes the received map data and displays disaster information on the map.

[0644] Example 2: Asking a Chatbot

[0645] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[0646] Terminal: Sends the entered question to the server.

[0647] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as, "The nearest evacuation shelter is XX Park."

[0648] Terminal: Display the received response on the chatbot screen.

[0649] Example 3: Sharing relief supplies

[0650] User: Enters the information "Water is running low" and submits.

[0651] Terminal: Sends the entered assistance information to the server.

[0652] Server: Receives the information, stores it in a database, and sends notifications to users in the same area.

[0653] Device: Receive a notification and see a "Water Shortage" icon on the map.

[0654] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs.

[0655] The processing flow will be explained below.

[0656] 1. Processing when the app starts

[0657] Step 1:

[0658] Device: The user launches the app.

[0659] Step 2:

[0660] Terminal: Prepares the layout to display the map on the initial screen.

[0661] Step 3:

[0662] Device: Uses GPS to obtain the user's location.

[0663] Step 4:

[0664] Device: Sends the acquired location information to the server.

[0665] 2. Displaying information on the map

[0666] Step 1:

[0667] Server: Receives location information sent from the device.

[0668] Step 2:

[0669] Server: Based on the location information, search for disaster information for the relevant area from the disaster information database.

[0670] Step 3:

[0671] Server: Incorporates disaster information for the relevant area into map data.

[0672] Step 4:

[0673] Server: Sends the generated map data to the device.

[0674] Step 5:

[0675] Terminal: Analyzes the received map data and displays it on the screen.

[0676] Step 6:

[0677] Terminal: Place disaster information icons and text on the map.

[0678] 3. Question and answering by chatbot

[0679] Step 1:

[0680] User: Enter a question into the chatbot's input field.

[0681] Step 2:

[0682] User: Presses the submit button to send the question to the server.

[0683] Step 3:

[0684] Terminal: Transfers the entered question to the server.

[0685] Step 4:

[0686] Server: Receives the question and analyzes the sentence using a generative AI model.

[0687] Step 5:

[0688] Server: Based on the query, retrieves the necessary information from a database or external API.

[0689] Step 6:

[0690] Server: Generates the appropriate answer.

[0691] Step 7:

[0692] Server: Sends the generated answer to the device.

[0693] Step 8:

[0694] Terminal: Display the received response on the chatbot screen.

[0695] 4. Sharing support status

[0696] Step 1:

[0697] User: Enter the status of use of relief supplies and public services.

[0698] Step 2:

[0699] User: Presses the submit button to send the information to the server.

[0700] Step 3:

[0701] Terminal: Transfers the input assistance information to the server.

[0702] Step 4:

[0703] Server: Receives assistance information and stores it in a database.

[0704] Step 5:

[0705] Server: Sends notifications to other users in the same area.

[0706] Step 6:

[0707] Terminal: Receives notification of support information received from the server.

[0708] Step 7:

[0709] Terminal: Displays aid status icons such as "water shortage" and "food surplus" on the map.

[0710] Example 1

[0711] 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."

[0712] In modern society, rapid and accurate information gathering and sharing is required when a disaster occurs. However, many current systems do not adequately provide real-time information based on the user's location information, and there are insufficient means to efficiently share disaster information and the status of relief supplies. As a result, users may not be able to obtain the necessary information quickly, which can delay appropriate responses.

[0713] 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.

[0714] In this invention, the server includes means for displaying a map on an initial screen when a user launches an application, means for acquiring user location information using GPS and transmitting the location information to the server, means for collecting disaster information for a corresponding area from a database based on the location information, means for combining the collected disaster information with map data to generate visually displayable map data and transmitting the data to the terminal, chatbot means for analyzing user questions using a generative model and generating appropriate answers, means for displaying the answers generated by the chatbot means, means for inputting the status of relief supplies and public services, saving the information in a database, and notifying other users, and means for displaying the relief information on a map. This enables users to quickly acquire and efficiently share disaster information based on their location information in real time.

[0715] "User" refers to any individual or entity that uses the System.

[0716] "Information collection means" refers to a combination of hard and soft data for obtaining specified information.

[0717] "Location Information" means data indicating a user's current geographic location obtained using technology such as GPS.

[0718] "Initial screen display means" refers to a function for providing the user with the initial screen that is displayed when the application is launched.

[0719] "Map Data" refers to data that includes visual representations of geographically based maps.

[0720] "Disaster information" refers to data related to disasters such as earthquakes, tsunamis, floods, and fires.

[0721] A "chatbot" is software that uses natural language processing to automatically respond to user questions.

[0722] A "generative AI model" refers to an algorithm or model that uses AI technology to automatically generate answers or explanations.

[0723] "Relief supplies" refers to relief supplies such as water, food, and medical supplies needed in the event of a disaster.

[0724] "Public services" refers to public services that can be used during a disaster, such as information on evacuation shelters and the operation status of public transportation.

[0725] "Notification means" refers to a function for notifying users of new or updated information.

[0726] "Real-time" refers to near-instantaneous processing or information updates.

[0727] "Database" refers to a system that stores data in a structured format.

[0728] "Map display means" refers to a function for displaying information on a map in a format that is easy for users to understand.

[0729] This invention is a system for collecting and sharing necessary information in the event of a disaster. The system of this invention is composed of a server, terminals, and users, and efficiently manages and provides information through their respective roles.

[0730] The system uses the Google Maps API to provide a means to display a map on the initial screen. When a user launches the application, the device first prepares to display the map on the initial screen. Next, the device uses the GPS function to obtain the user's location information and sends this location information to the server. This location information is sent securely using HTTPS.

[0731] The server receives the location information sent from the device and collects disaster information for the relevant area from a database (e.g., PostgreSQL) based on that location information. The collected disaster information is combined with map data (e.g., OpenStreetMap) to generate visually displayable map data and send it to the device.

[0732] The device analyzes the received map data and displays disaster information on the map in a user-friendly format. Specifically, various disaster icons (e.g., earthquake, flood, fire) are displayed on the map.

[0733] The system of the present invention also provides a chatbot function that uses a generative AI model. The user enters a question into the chatbot's input field and sends it. For example, "Where is the nearest evacuation shelter?" The device sends the entered question to a server, which receives the question and analyzes it using a generative AI model (e.g., OpenAI's GPT-3). Based on the analysis results, the system obtains the necessary information from a database or external API and generates an appropriate answer. The generated answer is sent to the device and displayed on the chatbot screen.

[0734] The system also includes a function for inputting and sharing the status of relief supplies and public services. Users can input the current status of relief supplies and the use of public services and send a message saying, "There is a shortage of water." The device sends this information to a server, which stores the received information in a database. Notifications are then sent to other users in the same area, and the device displays the received support information on a map. This allows for efficient and accurate information collection and sharing among users when a disaster occurs.

[0735] As a specific example, when a user launches the app and allows location information to be sent, the device sends the location information to a server, which receives and displays map data. The server receives the user's location information in Sapporo, collects disaster information such as earthquakes, tsunamis, floods, and fires in the Sapporo area, and generates map data. The device analyzes the received map data and displays the disaster information on a map.

[0736] When a user types a question into the chatbot, such as "Where is the nearest evacuation shelter?", the device sends the question to the server, which analyzes the question, searches for information about evacuation shelters in the area, and generates a response such as "The nearest evacuation shelter is XX Park." The device then displays the received response on the chatbot screen.

[0737] In this way, the system of the present invention makes it possible to quickly collect necessary information based on the user's location information when a disaster occurs, display it visually, generate appropriate answers to the user's questions, and share the status of relief supplies.

[0738] Examples of prompts:

[0739] "Where is the nearest evacuation shelter?"

[0740] Please tell me the current fire information.

[0741] "There's a water shortage."

[0742] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0743] Step 1:

[0744] Device: When the user launches the app, it begins preparations to display a map on the initial screen. Specifically, it loads the initial map data using the Google Maps API. The input triggers the application launch, and the output is that the map is ready to be displayed on the initial screen.

[0745] Step 2:

[0746] Device: Uses GPS to obtain the user's location information. This location information includes latitude and longitude. The obtained location information is sent to the server using HTTPS. The input is the latitude and longitude data obtained from the GPS, and the output is the completion of transmission to the server.

[0747] Step 3:

[0748] Server: Receives location information sent from the device. The input is the location data from the device, and the output is the completion of location information reception.

[0749] Step 4:

[0750] Server: Based on the received location information, retrieves disaster information for the corresponding area from the database. For example, if the location information is Sapporo city, collects disaster information such as earthquakes, tsunamis, floods, and fires around Sapporo city. The input is the received location information, and the output is disaster information data for the corresponding area.

[0751] Step 5:

[0752] Server: Combines collected disaster information with map data to generate visually displayable map data. The map data is obtained from map services such as OpenStreetMap. The input is disaster information data and map data, and the output is visually displayable map data.

[0753] Step 6:

[0754] Server: Sends visually displayable map data to the device. The input is the generated map data, and the output is the completion of transmission to the device.

[0755] Step 7:

[0756] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to see. Specifically, various disaster icons (e.g., earthquake, flood, fire) are displayed on the map. The input is the received map data, and the output is the map displayed to the user.

[0757] Step 8:

[0758] User: Enters a question into the chatbot's input field and submits it. For example, "Where is the nearest evacuation shelter?" The input is the user's question, and the output is submission.

[0759] Step 9:

[0760] Terminal: Sends the user's question to the server. The input is the user's question, and the output is the completion of transmission to the server.

[0761] Step 10:

[0762] Server: Receives the question and analyzes it using a generative AI model. The input is the received question, and the output is the analysis result.

[0763] Step 11:

[0764] Server: Based on the analysis results, obtains the necessary information from a database or external API and generates an appropriate answer. For example, search for information on the nearest evacuation shelter and generate an answer such as "The nearest evacuation shelter is XX Park." The input is the analysis results and information from the database or external API, and the output is the generated answer.

[0765] Step 12:

[0766] Server: Sends the generated answer to the terminal. The input is the generated answer, and the output is the completion of sending it to the terminal.

[0767] Step 13:

[0768] Terminal: Displays the received answer on the chatbot screen. The input is the received answer, and the output is the answer displayed to the user.

[0769] Step 14:

[0770] User: Enters the current status of relief supplies and the status of public service use. For example, enters "There is a water shortage." The input is the relief information entered by the user, and the output is transmission completion.

[0771] Step 15:

[0772] Terminal: Sends the input assistance information to the server. The input is the user's assistance information, and the output is the completion of transmission to the server.

[0773] Step 16:

[0774] Server: Saves the received information in the database. Here, the relief supplies information is updated. The input is the received relief information, and the output is the completion of saving it to the database.

[0775] Step 17:

[0776] Server: Sends notifications of received support information to other users in the same area. Uses push notification service. Input is support information stored in the database, and output is notification sending completion.

[0777] Step 18:

[0778] Terminal: Receives notifications and displays a "water shortage" icon on the map. The input is the received notification information, and the output is the map update shown to the user.

[0779] (Application example 1)

[0780] 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."

[0781] When a disaster or crime occurs, it is necessary to quickly and accurately grasp local danger information and support situations and provide users with appropriate countermeasures. However, current systems have limited real-time information updates and question-and-answer functions using generative models, making it difficult for users to quickly obtain the information they need. Furthermore, support information is often not shared effectively with other users. This poses a challenge in ensuring user safety in emergency situations where a rapid response is required.

[0782] 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.

[0783] In this invention, the server includes means for acquiring user location information, means for collecting disaster information and danger information for the relevant area based on the location information, means for displaying the disaster information and danger information on a map, and means for notifying other users of the danger information. This enables users to acquire information and share support information in real time even when a disaster or crime occurs, enabling them to respond quickly and appropriately.

[0784] "Disaster information" refers to information that includes specific damage situations and warnings regarding natural disasters and man-made disasters.

[0785] "Danger information" is information that includes specific situations and warnings regarding man-made dangers such as crimes and accidents.

[0786] A "generative model" refers to an artificial intelligence model that generates appropriate responses from large amounts of data, and includes natural language processing technology.

[0787] A "chatbot" is a system that automatically generates and provides appropriate answers to user questions using a generative model.

[0788] "Location Information" means your current geographic coordinates obtained using GPS or other positioning technology.

[0789] "Notification means" refers to systems and functions for communicating dangerous or important information to other users in real time.

[0790] "Support information" refers to information about the status of relief supplies and the use of public services, and is primarily shared during disasters and emergencies.

[0791] A "database" refers to a collection of data that is organized to store information and make it easy to search and update.

[0792] "User" refers to an individual or organization that uses this system and provides location information and inputs questions.

[0793] The present invention is a system for quickly and accurately collecting and sharing information in the event of a disaster or crime. Specific embodiments of the present invention will be described below.

[0794] System Configuration

[0795] The system of the present invention consists of a "server," a "terminal," and a "user." This system collects disaster and danger information based on the user's location information and provides that information to the user. It also uses a generative AI model to generate appropriate answers to the user's questions and shares the status of relief supplies and public services with other users in real time.

[0796] Hardware and software used

[0797] Hardware: Smartphone (iOS / Android compatible), smart glasses, GPS module

[0798] Software: GPS API, generative AI models (e.g. OpenAI GPT-4), RESTful API, database (MySQL)

[0799] Processing when the app starts

[0800] When a user launches the app, the device first prepares to display a map on the initial screen, then uses GPS to obtain the user's location information and sends it to the server, which uses this location information to collect disaster and danger information.

[0801] Displaying information on a map

[0802] The server retrieves disaster and danger information for the area based on the user's location information from a database, combines it with map data, and generates visually displayable map data. This map data is then sent to the device, which analyzes the received data and displays the information on the map in a format that is easy for the user to view.

[0803] Chatbot Q&A

[0804] The user enters a question into the chatbot's input field and sends it. The device sends the user's question to the server, which analyzes the received question using a generative AI model. The server then retrieves the necessary information from a database or external API, generates an appropriate answer, and sends it back to the device. The device then displays the received answer on the chatbot screen.

[0805] Prompt Sentence Examples

[0806] "Where is the nearest evacuation shelter?"

[0807] Please tell me about recent crimes.

[0808] "Please tell me the current weather conditions."

[0809] Sharing support status

[0810] Users input the current status of relief supplies and the use of public services, and send it to the server via their device. The server stores the received information in a database and sends notifications to other users in the same area. The device then displays the received relief information on a map and shares it with other users.

[0811] Example 1: Displaying disaster information

[0812] When a user launches the app and allows the transmission of location information, the device sends the location information to the server. For example, when the server receives the location information of a user in a certain city, it collects disaster information such as earthquakes, tsunamis, floods, and fires around that city and generates map data. The device analyzes the received map data and displays the disaster information on a map.

[0813] Example 2: Asking a Chatbot

[0814] When a user types the question "Where is the nearest evacuation shelter?" into the chatbot and sends it, the device sends the question to the server. The server analyzes the question, searches for information on evacuation shelters in the area, and generates an appropriate answer, such as "The nearest evacuation shelter is XX Park." The device then displays the received answer on the chatbot screen.

[0815] Example 3: Sharing relief supplies

[0816] When a user inputs and submits the information "Water shortage," the device sends the input assistance information to the server. The server receives the information, stores it in a database, and sends a notification to users in the same area. The device receives the notification and displays a "Water shortage" icon on the map.

[0817] In this way, the system of the present invention can efficiently and accurately collect and share information during disasters and crimes.

[0818] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0819] Step 1:

[0820] When a user launches the app, the device first prepares to display a map on the initial screen and obtains the user's location information using the GPS function. The input is the user's current location information, and the output is the obtained location information. This location information is then processed (for example, converted into JSON format) to be sent to the server.

[0821] Step 2:

[0822] The server receives the location information sent from the device and retrieves disaster and danger information for the relevant area from the database based on the location information. This information collection is performed using a database search query, with location information as input and disaster and danger information as output.

[0823] Step 3:

[0824] The server combines the acquired disaster and danger information with map data to generate visually displayable map data. Here, the map data is generated using a GIS (geographic information system) API, with the input being information about the relevant area and the output being displayable map data. The generated map data is sent to the device.

[0825] Step 4:

[0826] The terminal analyzes the received map data and displays disaster and danger information on the map in a format that is easy for the user to view. The input is the received map data, and the output is a display in a format that the user can view.

[0827] Step 5:

[0828] The user enters a question into the chatbot's input field and submits it. The input is the user's question, and the output is the question data to be sent to the server. The question data is sent to the server in text format.

[0829] Step 6:

[0830] The server receives a question from the user and analyzes the question using a generative AI model. The input is the user's question, and the output is the analyzed question. The AI ​​model collects information from appropriate databases and external APIs.

[0831] Step 7:

[0832] The server obtains the necessary information based on the analyzed question and generates an appropriate answer. The input is the analyzed question, and the output is the generated answer. The generated answer is sent to the terminal.

[0833] Step 8:

[0834] The terminal displays the received answer on the chatbot screen. The input is the received answer, and the output is a display in a format that can be viewed by the user.

[0835] Step 9:

[0836] Users input the current status of relief supplies and the status of public service usage, and send it to the server via their terminal. The input is relief information, and the output is data to be sent to the server. This data is sent to the server in text format.

[0837] Step 10:

[0838] The server stores the received assistance information in a database and sends notifications to other users in the same area. The input is assistance information, and the output is a notification message. Notifications are sent using a push notification API.

[0839] Step 11:

[0840] The device receives the notification and displays the support information on the map. The input is the received notification message, and the output is the support information displayed on the map. This allows other users to share support information in real time.

[0841] The above are the specific processing steps of the system that realizes the application example.

[0842] 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.

[0843] This invention combines a system for collecting and sharing necessary information in the event of a disaster with an emotion engine that recognizes the user's emotions, thereby providing appropriate information according to the user's psychological state.

[0844] Program processing overview

[0845] System Configuration

[0846] The system of the present invention is composed of a "server," a "terminal," and a "user." It also incorporates an emotion engine for recognizing the user's emotions.

[0847] 1. Processing when the app starts

[0848] On the device: When a user launches the app, the app prepares a layout to display a map on the initial screen, and uses the GPS function to obtain the user's location information. This location information is then sent to the server.

[0849] 2. Displaying information on the map

[0850] Server: Receives location information sent from the device, searches for disaster information for the relevant area in the disaster information database based on the location information, incorporates the disaster information for the relevant area into map data, and sends the generated map data to the device.

[0851] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to view.

[0852] 3. Question and answering by chatbot

[0853] User: Enters a question into the chatbot's input field and submits it.

[0854] Terminal: Sends user questions to the server.

[0855] Server: Receives the question and analyzes it using the generative AI model. Retrieves necessary information from databases and external APIs to generate an appropriate answer. Sends the generated answer to the device.

[0856] Terminal: Display the received response on the chatbot screen.

[0857] 4. Sharing support status

[0858] User: Enter and submit information on the status of relief supplies and the use of public services.

[0859] Terminal: Sends the entered information to the server.

[0860] Server: Saves the entered assistance information in a database and sends notifications to other users.

[0861] On your device: Display the assistance you receive on a map and share it with other users.

[0862] 5. Use of Emotion Engine

[0863] Users: Express their emotions (e.g., text, facial expressions) while interacting with the app or asking questions.

[0864] On-device: Recognizes user emotions using an emotion engine.

[0865] Server: Receives the user's emotional data recognized by the emotion engine and adjusts the tone of the response and provides appropriate information. For example, if the server detects that the user is feeling anxious, it provides information in a reassuring manner.

[0866] Specific examples

[0867] Example 1: Displaying disaster information

[0868] User: Launch the app and allow location information to be sent.

[0869] Device: Sends location information to the server, receives map data, and displays it.

[0870] Server: Receives location information from users in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Tokyo, and generates map data.

[0871] Terminal: Analyzes the received map data and displays disaster information on the map.

[0872] Example 2: Asking a Chatbot

[0873] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[0874] Terminal: Sends the entered question to the server.

[0875] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as "The nearest evacuation shelter is XX Park."

[0876] Terminal: Display the received response on the chatbot screen.

[0877] Example 3: Sharing relief supplies

[0878] User: Enters the information "Water is running low" and submits.

[0879] Terminal: Sends the entered assistance information to the server.

[0880] Server: Receives the information, stores it in a database, and notifies users in the same area.

[0881] Device: Receive a notification and see a "Water Shortage" icon on the map.

[0882] Example 4: Using an Emotion Engine

[0883] User: Type, "I'm really worried. Is there anything I can reassure you about?"

[0884] Device: The emotion engine recognizes the user's emotion of "anxiety."

[0885] Server: Generates a reassuring response based on the perceived emotion (e.g., "Nearby evacuation centers have sufficient supplies").

[0886] Device: Display responses based on emotions.

[0887] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs, and also provides appropriate information based on the user's emotions.

[0888] The processing flow will be explained below.

[0889] Program processing flow (including emotion engine)

[0890] 1. Processing when the app starts

[0891] Step 1:

[0892] Device: The user launches the app.

[0893] Step 2:

[0894] Terminal: Prepares the layout to display the map on the initial screen.

[0895] Step 3:

[0896] Device: Uses GPS to obtain the user's location.

[0897] Step 4:

[0898] Device: Sends the acquired location information to the server.

[0899] 2. Displaying information on the map

[0900] Step 1:

[0901] Server: Receives location information sent from the device.

[0902] Step 2:

[0903] Server: Based on the location information, search for disaster information for the relevant area from the disaster information database.

[0904] Step 3:

[0905] Server: Incorporates disaster information for the relevant area into map data.

[0906] Step 4:

[0907] Server: Sends the generated map data to the device.

[0908] Step 5:

[0909] Terminal: Analyzes the received map data and displays it on the screen.

[0910] Step 6:

[0911] Terminal: Place disaster information icons and text on the map.

[0912] 3. Question and answering by chatbot

[0913] Step 1:

[0914] User: Enter a question into the chatbot's input field.

[0915] Step 2:

[0916] User: Presses the submit button to send the question to the server.

[0917] Step 3:

[0918] Terminal: Transfers the entered question to the server.

[0919] Step 4:

[0920] Server: Receives the question and analyzes the sentence using a generative AI model.

[0921] Step 5:

[0922] Server: Based on the query, retrieves the necessary information from a database or external API.

[0923] Step 6:

[0924] Server: Generates the appropriate answer.

[0925] Step 7:

[0926] Server: Sends the generated answer to the device.

[0927] Step 8:

[0928] Terminal: Display the received response on the chatbot screen.

[0929] 4. Sharing support status

[0930] Step 1:

[0931] User: Enter the status of use of relief supplies and public services.

[0932] Step 2:

[0933] User: Presses the submit button to send the information to the server.

[0934] Step 3:

[0935] Terminal: Transfers the input assistance information to the server.

[0936] Step 4:

[0937] Server: Receives assistance information and stores it in a database.

[0938] Step 5:

[0939] Server: Sends notifications to other users in the same area.

[0940] Step 6:

[0941] Terminal: Receives notification of support information received from the server.

[0942] Step 7:

[0943] Terminal: Displays aid status icons such as "water shortage" and "food surplus" on the map.

[0944] 5. Use of Emotion Engine

[0945] Step 1:

[0946] Users: Input or express their emotions (e.g., text, facial expressions) while interacting with or asking questions within the app.

[0947] Step 2:

[0948] On-device: Recognizes user emotions using an emotion engine.

[0949] Step 3:

[0950] Device: Sends the recognized emotion data to the server.

[0951] Step 4:

[0952] Server: Receives emotion data and stores it in a database.

[0953] Step 5:

[0954] Server: Provides appropriate information and adjusts the tone of responses based on the user's emotions recognized by the emotion engine.

[0955] Step 6:

[0956] Server: Generates responses that correspond to the perceived emotion, for example, providing reassuring information if the user is feeling anxious.

[0957] Step 7:

[0958] Server: Sends the generated answer to the device.

[0959] Step 8:

[0960] Terminal: Display the received response on the chatbot screen.

[0961] Specific examples

[0962] Example 1: Displaying disaster information

[0963] Step 1:

[0964] User: Launch the app and allow location information to be sent.

[0965] Step 2:

[0966] Device: Sends location information to the server.

[0967] Step 3:

[0968] Server: Receives location information from users in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Tokyo, and generates map data.

[0969] Step 4:

[0970] Terminal: Analyzes the received map data and displays disaster information on the map.

[0971] Example 2: Asking a Chatbot

[0972] Step 1:

[0973] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[0974] Step 2:

[0975] Terminal: Sends the entered question to the server.

[0976] Step 3:

[0977] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as "The nearest evacuation shelter is XX Park."

[0978] Step 4:

[0979] Terminal: Display the received response on the chatbot screen.

[0980] Example 3: Sharing relief supplies

[0981] Step 1:

[0982] User: Enters the information "Water is running low" and submits.

[0983] Step 2:

[0984] Terminal: Sends the entered assistance information to the server.

[0985] Step 3:

[0986] Server: Receives the information, stores it in a database, and notifies users in the same area.

[0987] Step 4:

[0988] Device: Receive a notification and see a "Water Shortage" icon on the map.

[0989] Example 4: Using an Emotion Engine

[0990] Step 1:

[0991] User: Type, "I'm really worried. Is there anything I can reassure you about?"

[0992] Step 2:

[0993] Device: The emotion engine recognizes the user's emotion of "anxiety."

[0994] Step 3:

[0995] Device: Sends the recognized emotion data to the server.

[0996] Step 4:

[0997] Server: Generates a reassuring response based on the perceived emotion (e.g., "Nearby evacuation centers have sufficient supplies").

[0998] Step 5:

[0999] Device: Display responses based on emotions.

[1000] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs, and also provides appropriate information based on the user's emotions.

[1001] Example 2

[1002] 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."

[1003] When a disaster occurs, rapid and accurate information gathering and sharing is required, but the current system lacks the ability to provide information that takes into account the psychological state of the user.Furthermore, it is difficult to effectively update disaster information in real time and share the status of relief supplies.

[1004] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring user location information, means for collecting disaster information for a relevant area, means for displaying the disaster information on a map, chatbot means using a generative model to accept user questions, means for displaying generated answers, means for inputting and sharing the status of relief supplies and public services, emotion engine means for recognizing the user's emotions, and means for adjusting the content of answers and the provision of information based on the recognized emotions. This enables rapid and accurate information collection and sharing in the event of a disaster, and further enables the provision of appropriate information according to the user's psychological state.

[1005] "Means for obtaining user location information" means a method of using the device's GPS function or other location information obtaining technology to obtain the user's current location in the form of latitude and longitude.

[1006] The "means for collecting disaster information for the relevant area" is a method for searching and collecting disaster information such as earthquakes, tsunamis, floods, and fires in a specified area from a database based on the location information.

[1007] "Means for displaying disaster information on a map" refers to a method of incorporating collected disaster information into map data using a geographic information system (GIS) and presenting it visually to users.

[1008] A "chatbot method using a generative model" is a method that uses artificial intelligence (AI) to accept questions from users, analyzes the content of the question using natural language processing technology, and generates appropriate answers.

[1009] The "means for displaying the generated answer" is a method for displaying the answer generated by the chatbot means on the screen of the terminal.

[1010] "Means for inputting and sharing the status of relief supplies and public services" refers to a method by which users can input the status of relief supplies and the status of use of public services, send that information to a server, and share it with other users.

[1011] The "emotion engine means for recognizing user emotions" is a technology that determines the user's emotional state through text input and facial expression analysis, and acquires that emotional data.

[1012] "Means for adjusting response content and information provision based on recognized emotions" refers to a method for changing the tone of the information provided and responses based on the user's emotional data obtained by the emotion engine, thereby achieving a more appropriate and empathetic response.

[1013] This invention relates to a system for collecting and sharing information when a disaster occurs, and in particular to a system for recognizing the emotions of users and providing appropriate information.

[1014] System Configuration

[1015] The system of the present invention is composed of a server, a terminal, and a user. Each component and its function will be described in detail below.

[1016] server

[1017] The server is a central information processing unit that includes multiple functional modules. This central information processing unit has the following main functions:

[1018] 1. Location information receiving module:

[1019] This module receives user location information from the device and generates basic data for accessing the disaster information database. This module receives data using HTTPS communication.

[1020] 2. Disaster Information Collection Module:

[1021] Based on the location information, the system searches and collects the latest disaster information for the relevant area from a disaster information database. This disaster information includes various types such as earthquakes, tsunamis, floods, and fires.

[1022] 3. Map data generation module:

[1023] The collected disaster information is incorporated into map data and processed so that it can be displayed in a format that is intuitively easy for users to understand. This processing is done using a geographic information system (GIS).

[1024] 4. Chatbot module:

[1025] It uses generative AI models to respond to user questions, using natural language processing technologies such as OpenAI's GPT-3 to analyze the question and retrieve the necessary information from databases or external APIs to generate an answer.

[1026] 5. Support status management module:

[1027] Information about relief supplies and public services provided by users is stored in a database and notified to other users.

[1028] 6. Emotion Engine Module:

[1029] Recognize and capture user emotions. This emotional data is used to tailor question responses and information provision.

[1030] Terminal

[1031] A terminal is a device, including a smartphone or tablet, that acts as an interface between the user and the server. A terminal has the following functions:

[1032] 1. Acquisition of location information:

[1033] The GPS function is used to obtain the user's current location, which is saved as latitude and longitude and sent to the server.

[1034] 2. Map display:

[1035] The map data sent from the server is analyzed and disaster information is displayed intuitively, with icons and colors used to indicate the type of disaster.

[1036] 3. Chatbot screen:

[1037] It is an interface with a question input field and a text area, which sends questions from users to the server and displays the answers received.

[1038] 4. Emotion recognition:

[1039] It uses an emotion engine that analyzes text input and facial expressions to recognize the user's emotional state, and the recognized emotion data is sent to the server.

[1040] user

[1041] The user is the entity that uses the system and performs the following operations:

[1042] 1. Location Sharing:

[1043] Launch the app and allow it to send location information.

[1044] 2. Enter your question:

[1045] Enter your question in the chatbot's input field and submit.

[1046] 3. Enter supporting information:

[1047] Enter the status of relief supplies and the usage of public services and submit.

[1048] 4. Expressing emotions:

[1049] Express your emotions while interacting with the app or asking questions (e.g., through text, facial expressions).

[1050] Specific examples

[1051] Example 1: Displaying disaster information

[1052] When a user launches the app and allows location information to be sent, the device sends the location information to the server. The server receives the user's location information in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires in the Tokyo area, and generates map data. The device analyzes the received map data and displays the disaster information on the map. The server notifies the user that "the latest disaster information has been obtained."

[1053] Example 2: Asking a Chatbot

[1054] When a user inputs the question "Where is the nearest evacuation shelter?" into the chatbot and sends it, the device sends the question to the server. The server analyzes the question, searches for evacuation shelter information in the relevant area, and generates the answer "The nearest evacuation shelter is XX Park." The device displays the received answer on the chatbot screen. It also temporarily displays the message "Analyzing question..."

[1055] Example 3: Sharing relief supplies

[1056] When a user inputs and sends the information "There is a water shortage," the device sends the support information to the server. The server receives the information and stores it in a database. It also notifies other users in the same area. The device receives the notification and displays a "Water Shortage" icon on the map. It also displays the message "Support information has been added."

[1057] Example 4: Using an Emotion Engine

[1058] When the user inputs "I'm very anxious. Is there any information that can reassure me?", the device uses an emotion engine to recognize the user's emotion of "anxiety." Depending on the recognized emotion, the server generates a reassuring response such as "Nearby evacuation centers have sufficient supplies." The device displays the response according to the emotion and temporarily displays the message "Analyzing user's emotions..."

[1059] Prompt Sentence Examples

[1060] "Please tell me the latest disaster information for the Tokyo area."

[1061] "Please tell me where the evacuation shelter is."

[1062] "What should I do if there is a water shortage?"

[1063] "Please give me some information to ease my anxiety."

[1064] In this way, the system of the present invention not only efficiently and accurately collects and shares information when a disaster occurs, but also provides appropriate information based on the user's emotions.

[1065] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1066] Step 1: What to do when the app starts

[1067] Device: When a user launches the app, the layout to be displayed on the initial screen is prepared and the GPS function is used to obtain the user's location. This location information is recorded as latitude and longitude. The recorded location information is sent to the server using HTTPS communication. Specifically, the device notifies the user by saying "Obtaining location information..."

[1068] Input: App launch, GPS location information

[1069] Data processing: location information acquisition, data recording (latitude and longitude)

[1070] Output: Location information transmission

[1071] Step 2: Displaying information on the map

[1072] server:

[1073] 1. The location information sent from the device is received. The received data is analyzed and the corresponding area is identified.

[1074] 2. Access the disaster information database and collect disaster information (earthquake, tsunami, flood, fire, etc.) for the identified area.

[1075] 3. The collected disaster information is incorporated into map data, which is generated using GIS.

[1076] 4. The generated map data is sent to the device.

[1077] Device:

[1078] 1. Analyze the received map data and display disaster information in a user-friendly format (e.g., using different colors and icons).

[1079] Specifically, it notifies the user that "the latest disaster information has been obtained."

[1080] Input: Location

[1081] Data processing: disaster information acquisition, map data generation

[1082] Output: Send map data, display disaster information on the map

[1083] Step 3: Answer questions with a chatbot

[1084] User:

[1085] 1. Enter your question in the chatbot's input field and submit.

[1086] Device:

[1087] 1. The question entered by the user is sent to the server.

[1088] server:

[1089] 1. Analyze the received question. A generative AI model (e.g., OpenAI's GPT-3) is used to analyze the content of the question using natural language processing techniques.

[1090] 2. Depending on the content of the question, access databases or external APIs to obtain the necessary information.

[1091] 3. Generate appropriate answers based on the information obtained.

[1092] 4. Send the generated answer to the device.

[1093] Device:

[1094] 1. Display the received answer on the chatbot screen. Specifically, it displays "Analyzing question..."

[1095] Input: Question

[1096] Data processing: Question analysis, information acquisition, answer generation

[1097] Output: Display answer

[1098] Step 4: Sharing support status

[1099] User:

[1100] 1. Enter and submit information about the status of relief supplies and the use of public services.

[1101] Device:

[1102] 1. The entered support information is sent to the server.

[1103] server:

[1104] 1. The received assistance information is stored in a database.

[1105] 2. Send notifications to other users in the same area based on the saved information.

[1106] Device:

[1107] 1. Receive a notification and display support information on the map. Specifically, the message "Support information has been added" will be displayed.

[1108] Input: Support information

[1109] Data processing: Support information storage, notification generation

[1110] Output: Support information display, notification

[1111] Step 5: Use the Emotion Engine

[1112] User:

[1113] 1. Express your emotions (through text, facial expressions, etc.) while operating or asking questions within the app.

[1114] Device:

[1115] 1. The emotion engine recognizes the user's emotions, using emotion recognition software and facial expression analysis using a camera.

[1116] 2. The recognized emotion data is sent to the server.

[1117] server:

[1118] 1. Receive emotion data obtained by the emotion engine.

[1119] 2. Adjust the content and tone of your responses based on the user's emotions. For example, if the user is feeling anxious, generate reassuring information.

[1120] Device:

[1121] 1. Display tailored answers or information to the user. Specifically, the action is to display "Analyzing user sentiment..."

[1122] Input: Emotion

[1123] Data processing: emotion recognition, data transmission, response adjustment

[1124] Output: Adjusted answer, information display

[1125] (Application example 2)

[1126] 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."

[1127] Conventional disaster information systems generally provide information based on location information and share relief supplies, but they have the problem of not being able to provide information that takes into account the user's psychological state. During disasters, users often feel anxiety and fear, and providing information that ignores these emotions does not provide sufficient support to the user. The present invention aims to improve the user's sense of security by recognizing the user's emotions and providing appropriate information according to those emotions.

[1128] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1129] In this invention, the server includes a means for acquiring user location information, a means for recognizing emotions, a chatbot means using a generative model, and a means for adjusting information provision based on emotion recognition, thereby enabling appropriate information provision that takes into account the user's psychological state.

[1130] "Disaster occurrence" refers to the time when a natural or man-made disaster occurs, and a rapid response is required to ensure the safety of the affected areas and people.

[1131] "Information collection and sharing" refers to the act of gathering data and knowledge needed in the event of a disaster and exchanging it with relevant people and organizations through communication means.

[1132] "User Location Information" refers to the geographic location of a User, obtained using location-finding technology such as GPS.

[1133] "Disaster information for the relevant area" refers to information about disasters related to the user's current location or the specified area, including data on the types and occurrence status of earthquakes, floods, fires, etc.

[1134] "Displaying on a map" means providing collected disaster information visually to users using digital maps and geographic information systems (GIS).

[1135] A "chatbot means using generative models" is a program that uses technology in the field of natural language processing to automatically generate answers to users' questions.

[1136] The "means for displaying the answer" is an interface that displays the answer generated by the generative model on the user's terminal.

[1137] "Status of relief supplies and public services" refers to information such as food, water, medical supplies, and other supplies provided during disasters, as well as the availability of evacuation shelters and the operation status of public transportation.

[1138] "Emotion recognition" refers to technology that determines a user's current emotional state by analyzing text, facial expressions, tone of voice, etc.

[1139] "Means for adjusting information provision" refers to a function that changes the content and presentation of information in an appropriate form according to the user's recognized emotions.

[1140] "Means for updating disaster information in real time" refers to technology that keeps collected disaster information up to date and provides it to users quickly.

[1141] The present invention is an information collection and sharing system for use in the event of a disaster. It can recognize the user's emotions and provide appropriate information accordingly. This system is realized by the following configuration and procedures.

[1142] 1. Obtaining user location information

[1143] When a user launches the app, the device uses its GPS to obtain the user's location information. This location information is then sent to a server, which then collects disaster information for the relevant area.

[1144] 2. Collecting and displaying disaster information for the relevant area

[1145] The server searches a database for disaster information for the relevant area based on the location information sent from the device. It then incorporates the disaster information into map data and sends the generated map data to the device. The device then analyzes this map data and displays the disaster information on a map in a format that is easy for the user to view.

[1146] 3. User Emotion Recognition

[1147] When a user enters an operation or question within the app, the device uses an emotion engine to recognize the emotion. This emotion engine determines the user's emotion by analyzing text, facial expressions, tone of voice, etc. The obtained emotion data is sent to the server.

[1148] 4. Question and Answering Using Chatbots

[1149] When a user types a question through the chatbot, it is sent to the server via the device. The server uses a generative AI model to analyze the question, retrieves necessary information from a database or external APIs, and generates an appropriate answer. This answer is adjusted based on the user's emotional state. For example, if the user is feeling anxious, a reassuring statement will be added to the answer. Finally, the answer is displayed on the device.

[1150] 5. Sharing the status of relief supplies and public services

[1151] When users input information about the status of relief supplies and the use of public services, the information is sent to the server via the device. The server stores the information in a database and sends notifications to other users. The device that receives the notification displays the information on a map and shares it with other users.

[1152] Specific examples

[1153] When a user opens the app, enters their location as "Tokyo," and then enters text expressing their feelings as "I'm anxious," this information is sent to the server and processed in the following steps:

[1154] Example prompt sentence:

[1155] "A user in Tokyo said, 'I'm worried.'"

[1156] Based on this information, the server collects disaster information for the area and generates a response that includes supplementary information to reassure the user. For example, the device might display something like, "Current disaster information: A flood warning has been issued. Please do not worry. The nearest evacuation shelter is safe."

[1157] This allows users to instantly obtain appropriate information according to their emotions, allowing them to respond to disasters with peace of mind.

[1158] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1159] Step 1:

[1160] When a user launches the app, the device uses its GPS function to obtain the user's location information. This location information is then sent to the server. The input is the user's current location, and the output is the transmission of location information to the server. Specifically, the app uses the smartphone's GPS function to send the obtained latitude and longitude data to the server.

[1161] Step 2:

[1162] The server collects disaster information for the relevant area based on the location information sent from the device. The input is the user's location information, and the output is map data that collects the disaster information. The server obtains the latest disaster information for the relevant area from the database and integrates it into the map data.

[1163] Step 3:

[1164] The server sends the generated map data to the device. The input is map data including disaster information, and the output is sending the map data to the device. Specifically, the map data is encoded in JSON format or similar and sent to the device via an API.

[1165] Step 4:

[1166] The terminal analyzes the map data received from the server and displays disaster information on the map in a format that is easy for the user to view. The input is the map data from the server, and the output is the user's display screen. The terminal analyzes the map data and overlays disaster information on the map with appropriate icons and text.

[1167] Step 5:

[1168] Users input operations or questions within the app, and the device uses an emotion engine to recognize the emotion. The input is the user's text and facial expression data, and the output is the recognized emotion data. Natural language processing and facial recognition technologies are used to analyze text and image data to determine emotions.

[1169] Step 6:

[1170] The device sends the recognized emotion data to the server. The input is emotion data, and the output is sending the emotion data to the server. Specifically, the emotion data is sent to the server via an API.

[1171] Step 7:

[1172] When a user enters a question through the chatbot, the device sends the question to the server. The input is the user's question text, and the output is the transmission of the question data to the server. The question entered in the text box is sent to the server via API.

[1173] Step 8:

[1174] The server analyzes the question content using a generative AI model based on the received question and emotion data. The input is question data and emotion data, and the output is analyzed answer data. The generative AI model analyzes the meaning of the question and generates an appropriate answer.

[1175] Step 9:

[1176] The server retrieves the necessary information from a database or external API and adjusts the information provided based on the recognized sentiment. The input is the analyzed response data and additional information from outside, and the output is the adjusted response. Specifically, if the user expresses anxiety, reassuring words are added to the response.

[1177] Step 10:

[1178] The server sends the generated adjusted answer to the device. The input is the adjusted answer, and the output is the answer sent to the device. The answer data is encoded in JSON format or similar and sent to the device.

[1179] Step 11:

[1180] The terminal displays the adjusted response on the chatbot screen. The input is the response data from the server, and the output is the user's display screen. The response is displayed in the chatbot interface in an appropriate format.

[1181] Step 12:

[1182] When users input information about the status of relief supplies and the use of public services, that information is sent to the server via their device. The input is relief information, and the output is the transmission of that information to the server. The relief information is sent to the server as text data via an API.

[1183] Step 13:

[1184] The server saves the input assistance information in a database and sends notifications to other users. The input is assistance information and the output is notification data. The server saves the information in a database, generates notifications, and sends them to users in the relevant area.

[1185] Step 14:

[1186] The device displays notifications received from the server on a map and shares them with other users. The input is notification data from the server, and the output is the user's display screen. The notification data is analyzed and displayed on the map with appropriate icons and text.

[1187] 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.

[1188] 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.

[1189] 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.

[1190] [Third embodiment]

[1191] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1192] 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.

[1193] 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).

[1194] 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.

[1195] 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.

[1196] 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).

[1197] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1198] 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.

[1199] 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.

[1200] 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.

[1201] 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.

[1202] 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."

[1203] This invention relates to a system for collecting and sharing necessary information when a disaster occurs, and has the function of providing disaster information based on the user's location information and generating appropriate answers to user questions using a generative AI model.

[1204] Program processing overview

[1205] System Configuration

[1206] The system of the present invention is composed of a "server," a "terminal," and a "user."

[1207] 1. Processing when the app starts

[1208] Device: When a user launches the app, the app first prepares to display a map on the initial screen, then uses the GPS function to obtain the user's location information and sends this location information to the server.

[1209] 2. Displaying information on the map

[1210] Server: Receives location information sent from the device and retrieves disaster information for the relevant area from a database based on that information. Combines the retrieved disaster information with map data to generate visually displayable map data and send it to the device.

[1211] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to view.

[1212] 3. Question and answering by chatbot

[1213] User: Enters a question into the chatbot's input field and submits it.

[1214] Terminal: Sends user questions to the server.

[1215] Server: Receives the question and analyzes it using a generative AI model. It then retrieves the necessary information from a database or external API to generate an appropriate answer. It then sends the generated answer to the device.

[1216] Terminal: Display the received response on the chatbot screen.

[1217] 4. Sharing support status

[1218] User: Enter the current status of relief supplies and public service usage.

[1219] Terminal: Sends the entered information to the server.

[1220] Server: Stores the received information in a database and sends notifications to other users in the same area.

[1221] On your device: Display the assistance you receive on a map and share it with other users.

[1222] Specific examples

[1223] Example 1: Displaying disaster information

[1224] User: Launch the app and allow location information to be sent.

[1225] Device: Sends location information to the server, receives map data, and displays it.

[1226] Server: Receives location information from users in Sapporo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Sapporo, and generates map data.

[1227] Terminal: Analyzes the received map data and displays disaster information on the map.

[1228] Example 2: Asking a Chatbot

[1229] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[1230] Terminal: Sends the entered question to the server.

[1231] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as, "The nearest evacuation shelter is XX Park."

[1232] Terminal: Display the received response on the chatbot screen.

[1233] Example 3: Sharing relief supplies

[1234] User: Enters the information "Water is running low" and submits.

[1235] Terminal: Sends the entered assistance information to the server.

[1236] Server: Receives the information, stores it in a database, and sends notifications to users in the same area.

[1237] Device: Receive a notification and see a "Water Shortage" icon on the map.

[1238] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs.

[1239] The processing flow will be explained below.

[1240] 1. Processing when the app starts

[1241] Step 1:

[1242] Device: The user launches the app.

[1243] Step 2:

[1244] Terminal: Prepares the layout to display the map on the initial screen.

[1245] Step 3:

[1246] Device: Uses GPS to obtain the user's location.

[1247] Step 4:

[1248] Device: Sends the acquired location information to the server.

[1249] 2. Displaying information on the map

[1250] Step 1:

[1251] Server: Receives location information sent from the device.

[1252] Step 2:

[1253] Server: Based on the location information, search for disaster information for the relevant area from the disaster information database.

[1254] Step 3:

[1255] Server: Incorporates disaster information for the relevant area into map data.

[1256] Step 4:

[1257] Server: Sends the generated map data to the device.

[1258] Step 5:

[1259] Terminal: Analyzes the received map data and displays it on the screen.

[1260] Step 6:

[1261] Terminal: Place disaster information icons and text on the map.

[1262] 3. Question and answering by chatbot

[1263] Step 1:

[1264] User: Enter a question into the chatbot's input field.

[1265] Step 2:

[1266] User: Presses the submit button to send the question to the server.

[1267] Step 3:

[1268] Terminal: Transfers the entered question to the server.

[1269] Step 4:

[1270] Server: Receives the question and analyzes the sentence using a generative AI model.

[1271] Step 5:

[1272] Server: Based on the query, retrieves the necessary information from a database or external API.

[1273] Step 6:

[1274] Server: Generates the appropriate answer.

[1275] Step 7:

[1276] Server: Sends the generated answer to the device.

[1277] Step 8:

[1278] Terminal: Display the received response on the chatbot screen.

[1279] 4. Sharing support status

[1280] Step 1:

[1281] User: Enter the status of use of relief supplies and public services.

[1282] Step 2:

[1283] User: Presses the submit button to send the information to the server.

[1284] Step 3:

[1285] Terminal: Transfers the input assistance information to the server.

[1286] Step 4:

[1287] Server: Receives assistance information and stores it in a database.

[1288] Step 5:

[1289] Server: Sends notifications to other users in the same area.

[1290] Step 6:

[1291] Terminal: Receives notification of support information received from the server.

[1292] Step 7:

[1293] Terminal: Displays aid status icons such as "water shortage" and "food surplus" on the map.

[1294] Example 1

[1295] 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."

[1296] In modern society, rapid and accurate information gathering and sharing is required when a disaster occurs. However, many current systems do not adequately provide real-time information based on the user's location information, and there are insufficient means to efficiently share disaster information and the status of relief supplies. As a result, users may not be able to obtain the necessary information quickly, which can delay appropriate responses.

[1297] 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.

[1298] In this invention, the server includes means for displaying a map on an initial screen when a user launches an application, means for acquiring user location information using GPS and transmitting the location information to the server, means for collecting disaster information for a corresponding area from a database based on the location information, means for combining the collected disaster information with map data to generate visually displayable map data and transmitting the data to the terminal, chatbot means for analyzing user questions using a generative model and generating appropriate answers, means for displaying the answers generated by the chatbot means, means for inputting the status of relief supplies and public services, saving the information in a database, and notifying other users, and means for displaying the relief information on a map. This enables users to quickly acquire and efficiently share disaster information based on their location information in real time.

[1299] "User" refers to any individual or entity that uses the System.

[1300] "Information collection means" refers to a combination of hard and soft data for obtaining specified information.

[1301] "Location Information" means data indicating a user's current geographic location obtained using technology such as GPS.

[1302] "Initial screen display means" refers to a function for providing the user with the initial screen that is displayed when the application is launched.

[1303] "Map Data" refers to data that includes visual representations of geographically based maps.

[1304] "Disaster information" refers to data related to disasters such as earthquakes, tsunamis, floods, and fires.

[1305] A "chatbot" is software that uses natural language processing to automatically respond to user questions.

[1306] A "generative AI model" refers to an algorithm or model that uses AI technology to automatically generate answers or explanations.

[1307] "Relief supplies" refers to relief supplies such as water, food, and medical supplies needed in the event of a disaster.

[1308] "Public services" refers to public services that can be used during a disaster, such as information on evacuation shelters and the operation status of public transportation.

[1309] "Notification means" refers to a function for notifying users of new or updated information.

[1310] "Real-time" refers to near-instantaneous processing or information updates.

[1311] "Database" refers to a system that stores data in a structured format.

[1312] "Map display means" refers to a function for displaying information on a map in a format that is easy for users to understand.

[1313] This invention is a system for collecting and sharing necessary information in the event of a disaster. The system of this invention is composed of a server, terminals, and users, and efficiently manages and provides information through their respective roles.

[1314] The system uses the Google Maps API to provide a means to display a map on the initial screen. When a user launches the application, the device first prepares to display the map on the initial screen. Next, the device uses the GPS function to obtain the user's location information and sends this location information to the server. This location information is sent securely using HTTPS.

[1315] The server receives the location information sent from the device and collects disaster information for the relevant area from a database (e.g., PostgreSQL) based on that location information. The collected disaster information is combined with map data (e.g., OpenStreetMap) to generate visually displayable map data and send it to the device.

[1316] The device analyzes the received map data and displays disaster information on the map in a user-friendly format. Specifically, various disaster icons (e.g., earthquake, flood, fire) are displayed on the map.

[1317] The system of the present invention also provides a chatbot function that uses a generative AI model. The user enters a question into the chatbot's input field and sends it. For example, "Where is the nearest evacuation shelter?" The device sends the entered question to a server, which receives the question and analyzes it using a generative AI model (e.g., OpenAI's GPT-3). Based on the analysis results, the system obtains the necessary information from a database or external API and generates an appropriate answer. The generated answer is sent to the device and displayed on the chatbot screen.

[1318] The system also includes a function for inputting and sharing the status of relief supplies and public services. Users can input the current status of relief supplies and the use of public services and send a message saying, "There is a shortage of water." The device sends this information to a server, which stores the received information in a database. Notifications are then sent to other users in the same area, and the device displays the received support information on a map. This allows for efficient and accurate information collection and sharing among users when a disaster occurs.

[1319] As a specific example, when a user launches the app and allows location information to be sent, the device sends the location information to a server, which receives and displays map data. The server receives the user's location information in Sapporo, collects disaster information such as earthquakes, tsunamis, floods, and fires in the Sapporo area, and generates map data. The device analyzes the received map data and displays the disaster information on a map.

[1320] When a user types a question into the chatbot, such as "Where is the nearest evacuation shelter?", the device sends the question to the server, which analyzes the question, searches for information about evacuation shelters in the area, and generates a response such as "The nearest evacuation shelter is XX Park." The device then displays the received response on the chatbot screen.

[1321] In this way, the system of the present invention makes it possible to quickly collect necessary information based on the user's location information when a disaster occurs, display it visually, generate appropriate answers to the user's questions, and share the status of relief supplies.

[1322] Examples of prompts:

[1323] "Where is the nearest evacuation shelter?"

[1324] Please tell me the current fire information.

[1325] "There's a water shortage."

[1326] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1327] Step 1:

[1328] Device: When the user launches the app, it begins preparations to display a map on the initial screen. Specifically, it loads the initial map data using the Google Maps API. The input triggers the application launch, and the output is that the map is ready to be displayed on the initial screen.

[1329] Step 2:

[1330] Device: Uses GPS to obtain the user's location information. This location information includes latitude and longitude. The obtained location information is sent to the server using HTTPS. The input is the latitude and longitude data obtained from the GPS, and the output is the completion of transmission to the server.

[1331] Step 3:

[1332] Server: Receives location information sent from the device. The input is the location data from the device, and the output is the completion of location information reception.

[1333] Step 4:

[1334] Server: Based on the received location information, retrieves disaster information for the corresponding area from the database. For example, if the location information is Sapporo city, collects disaster information such as earthquakes, tsunamis, floods, and fires around Sapporo city. The input is the received location information, and the output is disaster information data for the corresponding area.

[1335] Step 5:

[1336] Server: Combines collected disaster information with map data to generate visually displayable map data. The map data is obtained from map services such as OpenStreetMap. The input is disaster information data and map data, and the output is visually displayable map data.

[1337] Step 6:

[1338] Server: Sends visually displayable map data to the device. The input is the generated map data, and the output is the completion of transmission to the device.

[1339] Step 7:

[1340] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to see. Specifically, various disaster icons (e.g., earthquake, flood, fire) are displayed on the map. The input is the received map data, and the output is the map displayed to the user.

[1341] Step 8:

[1342] User: Enters a question into the chatbot's input field and submits it. For example, "Where is the nearest evacuation shelter?" The input is the user's question, and the output is submission.

[1343] Step 9:

[1344] Terminal: Sends the user's question to the server. The input is the user's question, and the output is the completion of transmission to the server.

[1345] Step 10:

[1346] Server: Receives the question and analyzes it using a generative AI model. The input is the received question, and the output is the analysis result.

[1347] Step 11:

[1348] Server: Based on the analysis results, obtains the necessary information from a database or external API and generates an appropriate answer. For example, search for information on the nearest evacuation shelter and generate an answer such as "The nearest evacuation shelter is XX Park." The input is the analysis results and information from the database or external API, and the output is the generated answer.

[1349] Step 12:

[1350] Server: Sends the generated answer to the terminal. The input is the generated answer, and the output is the completion of sending it to the terminal.

[1351] Step 13:

[1352] Terminal: Displays the received answer on the chatbot screen. The input is the received answer, and the output is the answer displayed to the user.

[1353] Step 14:

[1354] User: Enters the current status of relief supplies and the status of public service use. For example, enters "There is a water shortage." The input is the relief information entered by the user, and the output is transmission completion.

[1355] Step 15:

[1356] Terminal: Sends the input assistance information to the server. The input is the user's assistance information, and the output is the completion of transmission to the server.

[1357] Step 16:

[1358] Server: Saves the received information in the database. Here, the relief supplies information is updated. The input is the received relief information, and the output is the completion of saving it to the database.

[1359] Step 17:

[1360] Server: Sends notifications of received support information to other users in the same area. Uses push notification service. Input is support information stored in the database, and output is notification sending completion.

[1361] Step 18:

[1362] Terminal: Receives notifications and displays a "water shortage" icon on the map. The input is the received notification information, and the output is the map update shown to the user.

[1363] (Application example 1)

[1364] 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."

[1365] When a disaster or crime occurs, it is necessary to quickly and accurately grasp local danger information and support situations and provide users with appropriate countermeasures. However, current systems have limited real-time information updates and question-and-answer functions using generative models, making it difficult for users to quickly obtain the information they need. Furthermore, support information is often not shared effectively with other users. This poses a challenge in ensuring user safety in emergency situations where a rapid response is required.

[1366] 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.

[1367] In this invention, the server includes means for acquiring user location information, means for collecting disaster information and danger information for the relevant area based on the location information, means for displaying the disaster information and danger information on a map, and means for notifying other users of the danger information. This enables users to acquire information and share support information in real time even when a disaster or crime occurs, enabling them to respond quickly and appropriately.

[1368] "Disaster information" refers to information that includes specific damage situations and warnings regarding natural disasters and man-made disasters.

[1369] "Danger information" is information that includes specific situations and warnings regarding man-made dangers such as crimes and accidents.

[1370] A "generative model" refers to an artificial intelligence model that generates appropriate responses from large amounts of data, and includes natural language processing technology.

[1371] A "chatbot" is a system that automatically generates and provides appropriate answers to user questions using a generative model.

[1372] "Location Information" means your current geographic coordinates obtained using GPS or other positioning technology.

[1373] "Notification means" refers to systems and functions for communicating dangerous or important information to other users in real time.

[1374] "Support information" refers to information about the status of relief supplies and the use of public services, and is primarily shared during disasters and emergencies.

[1375] A "database" refers to a collection of data that is organized to store information and make it easy to search and update.

[1376] "User" refers to an individual or organization that uses this system and provides location information and inputs questions.

[1377] The present invention is a system for quickly and accurately collecting and sharing information in the event of a disaster or crime. Specific embodiments of the present invention will be described below.

[1378] System Configuration

[1379] The system of the present invention consists of a "server," a "terminal," and a "user." This system collects disaster and danger information based on the user's location information and provides that information to the user. It also uses a generative AI model to generate appropriate answers to the user's questions and shares the status of relief supplies and public services with other users in real time.

[1380] Hardware and software used

[1381] Hardware: Smartphone (iOS / Android compatible), smart glasses, GPS module

[1382] Software: GPS API, generative AI models (e.g. OpenAI GPT-4), RESTful API, database (MySQL)

[1383] Processing when the app starts

[1384] When a user launches the app, the device first prepares to display a map on the initial screen, then uses GPS to obtain the user's location information and sends it to the server, which uses this location information to collect disaster and danger information.

[1385] Displaying information on a map

[1386] The server retrieves disaster and danger information for the area based on the user's location information from a database, combines it with map data, and generates visually displayable map data. This map data is then sent to the device, which analyzes the received data and displays the information on the map in a format that is easy for the user to view.

[1387] Chatbot Q&A

[1388] The user enters a question into the chatbot's input field and sends it. The device sends the user's question to the server, which analyzes the received question using a generative AI model. The server then retrieves the necessary information from a database or external API, generates an appropriate answer, and sends it back to the device. The device then displays the received answer on the chatbot screen.

[1389] Prompt Sentence Examples

[1390] "Where is the nearest evacuation shelter?"

[1391] Please tell me about recent crimes.

[1392] "Please tell me the current weather conditions."

[1393] Sharing support status

[1394] Users input the current status of relief supplies and the use of public services, and send it to the server via their device. The server stores the received information in a database and sends notifications to other users in the same area. The device then displays the received relief information on a map and shares it with other users.

[1395] Example 1: Displaying disaster information

[1396] When a user launches the app and allows the transmission of location information, the device sends the location information to the server. For example, when the server receives the location information of a user in a certain city, it collects disaster information such as earthquakes, tsunamis, floods, and fires around that city and generates map data. The device analyzes the received map data and displays the disaster information on a map.

[1397] Example 2: Asking a Chatbot

[1398] When a user types the question "Where is the nearest evacuation shelter?" into the chatbot and sends it, the device sends the question to the server. The server analyzes the question, searches for information on evacuation shelters in the area, and generates an appropriate answer, such as "The nearest evacuation shelter is XX Park." The device then displays the received answer on the chatbot screen.

[1399] Example 3: Sharing relief supplies

[1400] When a user inputs and submits the information "Water shortage," the device sends the input assistance information to the server. The server receives the information, stores it in a database, and sends a notification to users in the same area. The device receives the notification and displays a "Water shortage" icon on the map.

[1401] In this way, the system of the present invention can efficiently and accurately collect and share information during disasters and crimes.

[1402] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1403] Step 1:

[1404] When a user launches the app, the device first prepares to display a map on the initial screen and obtains the user's location information using the GPS function. The input is the user's current location information, and the output is the obtained location information. This location information is then processed (for example, converted into JSON format) to be sent to the server.

[1405] Step 2:

[1406] The server receives the location information sent from the device and retrieves disaster and danger information for the relevant area from the database based on the location information. This information collection is performed using a database search query, with location information as input and disaster and danger information as output.

[1407] Step 3:

[1408] The server combines the acquired disaster and danger information with map data to generate visually displayable map data. Here, the map data is generated using a GIS (geographic information system) API, with the input being information about the relevant area and the output being displayable map data. The generated map data is sent to the device.

[1409] Step 4:

[1410] The terminal analyzes the received map data and displays disaster and danger information on the map in a format that is easy for the user to view. The input is the received map data, and the output is a display in a format that the user can view.

[1411] Step 5:

[1412] The user enters a question into the chatbot's input field and submits it. The input is the user's question, and the output is the question data to be sent to the server. The question data is sent to the server in text format.

[1413] Step 6:

[1414] The server receives a question from the user and analyzes the question using a generative AI model. The input is the user's question, and the output is the analyzed question. The AI ​​model collects information from appropriate databases and external APIs.

[1415] Step 7:

[1416] The server obtains the necessary information based on the analyzed question and generates an appropriate answer. The input is the analyzed question, and the output is the generated answer. The generated answer is sent to the terminal.

[1417] Step 8:

[1418] The terminal displays the received answer on the chatbot screen. The input is the received answer, and the output is a display in a format that can be viewed by the user.

[1419] Step 9:

[1420] Users input the current status of relief supplies and the status of public service usage, and send it to the server via their terminal. The input is relief information, and the output is data to be sent to the server. This data is sent to the server in text format.

[1421] Step 10:

[1422] The server stores the received assistance information in a database and sends notifications to other users in the same area. The input is assistance information, and the output is a notification message. Notifications are sent using a push notification API.

[1423] Step 11:

[1424] The device receives the notification and displays the support information on the map. The input is the received notification message, and the output is the support information displayed on the map. This allows other users to share support information in real time.

[1425] The above are the specific processing steps of the system that realizes the application example.

[1426] 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.

[1427] This invention combines a system for collecting and sharing necessary information in the event of a disaster with an emotion engine that recognizes the user's emotions, thereby providing appropriate information according to the user's psychological state.

[1428] Program processing overview

[1429] System Configuration

[1430] The system of the present invention is composed of a "server," a "terminal," and a "user." It also incorporates an emotion engine for recognizing the user's emotions.

[1431] 1. Processing when the app starts

[1432] On the device: When a user launches the app, the app prepares a layout to display a map on the initial screen, and uses the GPS function to obtain the user's location information. This location information is then sent to the server.

[1433] 2. Displaying information on the map

[1434] Server: Receives location information sent from the device, searches for disaster information for the relevant area in the disaster information database based on the location information, incorporates the disaster information for the relevant area into map data, and sends the generated map data to the device.

[1435] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to view.

[1436] 3. Question and answering by chatbot

[1437] User: Enters a question into the chatbot's input field and submits it.

[1438] Terminal: Sends user questions to the server.

[1439] Server: Receives the question and analyzes it using the generative AI model. Retrieves necessary information from databases and external APIs to generate an appropriate answer. Sends the generated answer to the device.

[1440] Terminal: Display the received response on the chatbot screen.

[1441] 4. Sharing support status

[1442] User: Enter and submit information on the status of relief supplies and the use of public services.

[1443] Terminal: Sends the entered information to the server.

[1444] Server: Saves the entered assistance information in a database and sends notifications to other users.

[1445] On your device: Display the assistance you receive on a map and share it with other users.

[1446] 5. Use of Emotion Engine

[1447] Users: Express their emotions (e.g., text, facial expressions) while interacting with the app or asking questions.

[1448] On-device: Recognizes user emotions using an emotion engine.

[1449] Server: Receives the user's emotional data recognized by the emotion engine and adjusts the tone of the response and provides appropriate information. For example, if the server detects that the user is feeling anxious, it provides information in a reassuring manner.

[1450] Specific examples

[1451] Example 1: Displaying disaster information

[1452] User: Launch the app and allow location information to be sent.

[1453] Device: Sends location information to the server, receives map data, and displays it.

[1454] Server: Receives location information from users in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Tokyo, and generates map data.

[1455] Terminal: Analyzes the received map data and displays disaster information on the map.

[1456] Example 2: Asking a Chatbot

[1457] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[1458] Terminal: Sends the entered question to the server.

[1459] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as "The nearest evacuation shelter is XX Park."

[1460] Terminal: Display the received response on the chatbot screen.

[1461] Example 3: Sharing relief supplies

[1462] User: Enters the information "Water is running low" and submits.

[1463] Terminal: Sends the entered assistance information to the server.

[1464] Server: Receives the information, stores it in a database, and notifies users in the same area.

[1465] Device: Receive a notification and see a "Water Shortage" icon on the map.

[1466] Example 4: Using an Emotion Engine

[1467] User: Type, "I'm really worried. Is there anything I can reassure you about?"

[1468] Device: The emotion engine recognizes the user's emotion of "anxiety."

[1469] Server: Generates a reassuring response based on the perceived emotion (e.g., "Nearby evacuation centers have sufficient supplies").

[1470] Device: Display responses based on emotions.

[1471] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs, and also provides appropriate information based on the user's emotions.

[1472] The processing flow will be explained below.

[1473] Program processing flow (including emotion engine)

[1474] 1. Processing when the app starts

[1475] Step 1:

[1476] Device: The user launches the app.

[1477] Step 2:

[1478] Terminal: Prepares the layout to display the map on the initial screen.

[1479] Step 3:

[1480] Device: Uses GPS to obtain the user's location.

[1481] Step 4:

[1482] Device: Sends the acquired location information to the server.

[1483] 2. Displaying information on the map

[1484] Step 1:

[1485] Server: Receives location information sent from the device.

[1486] Step 2:

[1487] Server: Based on the location information, search for disaster information for the relevant area from the disaster information database.

[1488] Step 3:

[1489] Server: Incorporates disaster information for the relevant area into map data.

[1490] Step 4:

[1491] Server: Sends the generated map data to the device.

[1492] Step 5:

[1493] Terminal: Analyzes the received map data and displays it on the screen.

[1494] Step 6:

[1495] Terminal: Place disaster information icons and text on the map.

[1496] 3. Question and answering by chatbot

[1497] Step 1:

[1498] User: Enter a question into the chatbot's input field.

[1499] Step 2:

[1500] User: Presses the submit button to send the question to the server.

[1501] Step 3:

[1502] Terminal: Transfers the entered question to the server.

[1503] Step 4:

[1504] Server: Receives the question and analyzes the sentence using a generative AI model.

[1505] Step 5:

[1506] Server: Based on the query, retrieves the necessary information from a database or external API.

[1507] Step 6:

[1508] Server: Generates the appropriate answer.

[1509] Step 7:

[1510] Server: Sends the generated answer to the device.

[1511] Step 8:

[1512] Terminal: Display the received response on the chatbot screen.

[1513] 4. Sharing support status

[1514] Step 1:

[1515] User: Enter the status of use of relief supplies and public services.

[1516] Step 2:

[1517] User: Presses the submit button to send the information to the server.

[1518] Step 3:

[1519] Terminal: Transfers the input assistance information to the server.

[1520] Step 4:

[1521] Server: Receives assistance information and stores it in a database.

[1522] Step 5:

[1523] Server: Sends notifications to other users in the same area.

[1524] Step 6:

[1525] Terminal: Receives notification of support information received from the server.

[1526] Step 7:

[1527] Terminal: Displays aid status icons such as "water shortage" and "food surplus" on the map.

[1528] 5. Use of Emotion Engine

[1529] Step 1:

[1530] Users: Input or express their emotions (e.g., text, facial expressions) while interacting with or asking questions within the app.

[1531] Step 2:

[1532] On-device: Recognizes user emotions using an emotion engine.

[1533] Step 3:

[1534] Device: Sends the recognized emotion data to the server.

[1535] Step 4:

[1536] Server: Receives emotion data and stores it in a database.

[1537] Step 5:

[1538] Server: Provides appropriate information and adjusts the tone of responses based on the user's emotions recognized by the emotion engine.

[1539] Step 6:

[1540] Server: Generates responses that correspond to the perceived emotion, for example, providing reassuring information if the user is feeling anxious.

[1541] Step 7:

[1542] Server: Sends the generated answer to the device.

[1543] Step 8:

[1544] Terminal: Display the received response on the chatbot screen.

[1545] Specific examples

[1546] Example 1: Displaying disaster information

[1547] Step 1:

[1548] User: Launch the app and allow location information to be sent.

[1549] Step 2:

[1550] Device: Sends location information to the server.

[1551] Step 3:

[1552] Server: Receives location information from users in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Tokyo, and generates map data.

[1553] Step 4:

[1554] Terminal: Analyzes the received map data and displays disaster information on the map.

[1555] Example 2: Asking a Chatbot

[1556] Step 1:

[1557] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[1558] Step 2:

[1559] Terminal: Sends the entered question to the server.

[1560] Step 3:

[1561] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as "The nearest evacuation shelter is XX Park."

[1562] Step 4:

[1563] Terminal: Display the received response on the chatbot screen.

[1564] Example 3: Sharing relief supplies

[1565] Step 1:

[1566] User: Enters the information "Water is running low" and submits.

[1567] Step 2:

[1568] Terminal: Sends the entered assistance information to the server.

[1569] Step 3:

[1570] Server: Receives the information, stores it in a database, and notifies users in the same area.

[1571] Step 4:

[1572] Device: Receive a notification and see a "Water Shortage" icon on the map.

[1573] Example 4: Using an Emotion Engine

[1574] Step 1:

[1575] User: Type, "I'm really worried. Is there anything I can reassure you about?"

[1576] Step 2:

[1577] Device: The emotion engine recognizes the user's emotion of "anxiety."

[1578] Step 3:

[1579] Device: Sends the recognized emotion data to the server.

[1580] Step 4:

[1581] Server: Generates a reassuring response based on the perceived emotion (e.g., "Nearby evacuation centers have sufficient supplies").

[1582] Step 5:

[1583] Device: Display responses based on emotions.

[1584] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs, and also provides appropriate information based on the user's emotions.

[1585] Example 2

[1586] 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."

[1587] When a disaster occurs, rapid and accurate information gathering and sharing is required, but the current system lacks the ability to provide information that takes into account the psychological state of the user.Furthermore, it is difficult to effectively update disaster information in real time and share the status of relief supplies.

[1588] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring user location information, means for collecting disaster information for a relevant area, means for displaying the disaster information on a map, chatbot means using a generative model to accept user questions, means for displaying generated answers, means for inputting and sharing the status of relief supplies and public services, emotion engine means for recognizing the user's emotions, and means for adjusting the content of answers and the provision of information based on the recognized emotions. This enables rapid and accurate information collection and sharing in the event of a disaster, and further enables the provision of appropriate information according to the user's psychological state.

[1589] "Means for obtaining user location information" means a method of using the device's GPS function or other location information obtaining technology to obtain the user's current location in the form of latitude and longitude.

[1590] The "means for collecting disaster information for the relevant area" is a method for searching and collecting disaster information such as earthquakes, tsunamis, floods, and fires in a specified area from a database based on the location information.

[1591] "Means for displaying disaster information on a map" refers to a method of incorporating collected disaster information into map data using a geographic information system (GIS) and presenting it visually to users.

[1592] A "chatbot method using a generative model" is a method that uses artificial intelligence (AI) to accept questions from users, analyzes the content of the question using natural language processing technology, and generates appropriate answers.

[1593] The "means for displaying the generated answer" is a method for displaying the answer generated by the chatbot means on the screen of the terminal.

[1594] "Means for inputting and sharing the status of relief supplies and public services" refers to a method by which users can input the status of relief supplies and the status of use of public services, send that information to a server, and share it with other users.

[1595] The "emotion engine means for recognizing user emotions" is a technology that determines the user's emotional state through text input and facial expression analysis, and acquires that emotional data.

[1596] "Means for adjusting response content and information provision based on recognized emotions" refers to a method for changing the tone of the information provided and responses based on the user's emotional data obtained by the emotion engine, thereby achieving a more appropriate and empathetic response.

[1597] This invention relates to a system for collecting and sharing information when a disaster occurs, and in particular to a system for recognizing the emotions of users and providing appropriate information.

[1598] System Configuration

[1599] The system of the present invention is composed of a server, a terminal, and a user. Each component and its function will be described in detail below.

[1600] server

[1601] The server is a central information processing unit that includes multiple functional modules. This central information processing unit has the following main functions:

[1602] 1. Location information receiving module:

[1603] This module receives user location information from the device and generates basic data for accessing the disaster information database. This module receives data using HTTPS communication.

[1604] 2. Disaster Information Collection Module:

[1605] Based on the location information, the system searches and collects the latest disaster information for the relevant area from a disaster information database. This disaster information includes various types such as earthquakes, tsunamis, floods, and fires.

[1606] 3. Map data generation module:

[1607] The collected disaster information is incorporated into map data and processed so that it can be displayed in a format that is intuitively easy for users to understand. This processing is done using a geographic information system (GIS).

[1608] 4. Chatbot module:

[1609] It uses generative AI models to respond to user questions, using natural language processing technologies such as OpenAI's GPT-3 to analyze the question and retrieve the necessary information from databases or external APIs to generate an answer.

[1610] 5. Support status management module:

[1611] Information about relief supplies and public services provided by users is stored in a database and notified to other users.

[1612] 6. Emotion Engine Module:

[1613] Recognize and capture user emotions. This emotional data is used to tailor question responses and information provision.

[1614] Terminal

[1615] A terminal is a device, including a smartphone or tablet, that acts as an interface between the user and the server. A terminal has the following functions:

[1616] 1. Acquisition of location information:

[1617] The GPS function is used to obtain the user's current location, which is saved as latitude and longitude and sent to the server.

[1618] 2. Map display:

[1619] The map data sent from the server is analyzed and disaster information is displayed intuitively, with icons and colors used to indicate the type of disaster.

[1620] 3. Chatbot screen:

[1621] It is an interface with a question input field and a text area, which sends questions from users to the server and displays the answers received.

[1622] 4. Emotion recognition:

[1623] It uses an emotion engine that analyzes text input and facial expressions to recognize the user's emotional state, and the recognized emotion data is sent to the server.

[1624] user

[1625] The user is the entity that uses the system and performs the following operations:

[1626] 1. Location Sharing:

[1627] Launch the app and allow it to send location information.

[1628] 2. Enter your question:

[1629] Enter your question in the chatbot's input field and submit.

[1630] 3. Enter supporting information:

[1631] Enter the status of relief supplies and the usage of public services and submit.

[1632] 4. Expressing emotions:

[1633] Express your emotions while interacting with the app or asking questions (e.g., through text, facial expressions).

[1634] Specific examples

[1635] Example 1: Displaying disaster information

[1636] When a user launches the app and allows location information to be sent, the device sends the location information to the server. The server receives the user's location information in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires in the Tokyo area, and generates map data. The device analyzes the received map data and displays the disaster information on the map. The server notifies the user that "the latest disaster information has been obtained."

[1637] Example 2: Asking a Chatbot

[1638] When a user inputs the question "Where is the nearest evacuation shelter?" into the chatbot and sends it, the device sends the question to the server. The server analyzes the question, searches for evacuation shelter information in the relevant area, and generates the answer "The nearest evacuation shelter is XX Park." The device displays the received answer on the chatbot screen. It also temporarily displays the message "Analyzing question..."

[1639] Example 3: Sharing relief supplies

[1640] When a user inputs and sends the information "There is a water shortage," the device sends the support information to the server. The server receives the information and stores it in a database. It also notifies other users in the same area. The device receives the notification and displays a "Water Shortage" icon on the map. It also displays the message "Support information has been added."

[1641] Example 4: Using an Emotion Engine

[1642] When the user inputs "I'm very anxious. Is there any information that can reassure me?", the device uses an emotion engine to recognize the user's emotion of "anxiety." Depending on the recognized emotion, the server generates a reassuring response such as "Nearby evacuation centers have sufficient supplies." The device displays the response according to the emotion and temporarily displays the message "Analyzing user's emotions..."

[1643] Prompt Sentence Examples

[1644] "Please tell me the latest disaster information for the Tokyo area."

[1645] "Please tell me where the evacuation shelter is."

[1646] "What should I do if there is a water shortage?"

[1647] "Please give me some information to ease my anxiety."

[1648] In this way, the system of the present invention not only efficiently and accurately collects and shares information when a disaster occurs, but also provides appropriate information based on the user's emotions.

[1649] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1650] Step 1: What to do when the app starts

[1651] Device: When a user launches the app, the layout to be displayed on the initial screen is prepared and the GPS function is used to obtain the user's location. This location information is recorded as latitude and longitude. The recorded location information is sent to the server using HTTPS communication. Specifically, the device notifies the user by saying "Obtaining location information..."

[1652] Input: App launch, GPS location information

[1653] Data processing: location information acquisition, data recording (latitude and longitude)

[1654] Output: Location information transmission

[1655] Step 2: Displaying information on the map

[1656] server:

[1657] 1. The location information sent from the device is received. The received data is analyzed and the corresponding area is identified.

[1658] 2. Access the disaster information database and collect disaster information (earthquake, tsunami, flood, fire, etc.) for the identified area.

[1659] 3. The collected disaster information is incorporated into map data, which is generated using GIS.

[1660] 4. The generated map data is sent to the device.

[1661] Device:

[1662] 1. Analyze the received map data and display disaster information in a user-friendly format (e.g., using different colors and icons).

[1663] Specifically, it notifies the user that "the latest disaster information has been obtained."

[1664] Input: Location

[1665] Data processing: disaster information acquisition, map data generation

[1666] Output: Send map data, display disaster information on the map

[1667] Step 3: Answer questions with a chatbot

[1668] User:

[1669] 1. Enter your question in the chatbot's input field and submit.

[1670] Device:

[1671] 1. The question entered by the user is sent to the server.

[1672] server:

[1673] 1. Analyze the received question. A generative AI model (e.g., OpenAI's GPT-3) is used to analyze the content of the question using natural language processing techniques.

[1674] 2. Depending on the content of the question, access databases or external APIs to obtain the necessary information.

[1675] 3. Generate appropriate answers based on the information obtained.

[1676] 4. Send the generated answer to the device.

[1677] Device:

[1678] 1. Display the received answer on the chatbot screen. Specifically, it displays "Analyzing question..."

[1679] Input: Question

[1680] Data processing: Question analysis, information acquisition, answer generation

[1681] Output: Display answer

[1682] Step 4: Sharing support status

[1683] User:

[1684] 1. Enter and submit information about the status of relief supplies and the use of public services.

[1685] Device:

[1686] 1. The entered support information is sent to the server.

[1687] server:

[1688] 1. The received assistance information is stored in a database.

[1689] 2. Send notifications to other users in the same area based on the saved information.

[1690] Device:

[1691] 1. Receive a notification and display support information on the map. Specifically, the message "Support information has been added" will be displayed.

[1692] Input: Support information

[1693] Data processing: Support information storage, notification generation

[1694] Output: Support information display, notification

[1695] Step 5: Use the Emotion Engine

[1696] User:

[1697] 1. Express your emotions (through text, facial expressions, etc.) while operating or asking questions within the app.

[1698] Device:

[1699] 1. The emotion engine recognizes the user's emotions, using emotion recognition software and facial expression analysis using a camera.

[1700] 2. The recognized emotion data is sent to the server.

[1701] server:

[1702] 1. Receive emotion data obtained by the emotion engine.

[1703] 2. Adjust the content and tone of your responses based on the user's emotions. For example, if the user is feeling anxious, generate reassuring information.

[1704] Device:

[1705] 1. Display tailored answers or information to the user. Specifically, the action is to display "Analyzing user sentiment..."

[1706] Input: Emotion

[1707] Data processing: emotion recognition, data transmission, response adjustment

[1708] Output: Adjusted answer, information display

[1709] (Application example 2)

[1710] 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."

[1711] Conventional disaster information systems generally provide information based on location information and share relief supplies, but they have the problem of not being able to provide information that takes into account the user's psychological state. During disasters, users often feel anxiety and fear, and providing information that ignores these emotions does not provide sufficient support to the user. The present invention aims to improve the user's sense of security by recognizing the user's emotions and providing appropriate information according to those emotions.

[1712] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1713] In this invention, the server includes a means for acquiring user location information, a means for recognizing emotions, a chatbot means using a generative model, and a means for adjusting information provision based on emotion recognition, thereby enabling appropriate information provision that takes into account the user's psychological state.

[1714] "Disaster occurrence" refers to the time when a natural or man-made disaster occurs, and a rapid response is required to ensure the safety of the affected areas and people.

[1715] "Information collection and sharing" refers to the act of gathering data and knowledge needed in the event of a disaster and exchanging it with relevant people and organizations through communication means.

[1716] "User Location Information" refers to the geographic location of a User, obtained using location-finding technology such as GPS.

[1717] "Disaster information for the relevant area" refers to information about disasters related to the user's current location or the specified area, including data on the types and occurrence status of earthquakes, floods, fires, etc.

[1718] "Displaying on a map" means providing collected disaster information visually to users using digital maps and geographic information systems (GIS).

[1719] A "chatbot means using generative models" is a program that uses technology in the field of natural language processing to automatically generate answers to users' questions.

[1720] The "means for displaying the answer" is an interface that displays the answer generated by the generative model on the user's terminal.

[1721] "Status of relief supplies and public services" refers to information such as food, water, medical supplies, and other supplies provided during disasters, as well as the availability of evacuation shelters and the operation status of public transportation.

[1722] "Emotion recognition" refers to technology that determines a user's current emotional state by analyzing text, facial expressions, tone of voice, etc.

[1723] "Means for adjusting information provision" refers to a function that changes the content and presentation of information in an appropriate form according to the user's recognized emotions.

[1724] "Means for updating disaster information in real time" refers to technology that keeps collected disaster information up to date and provides it to users quickly.

[1725] The present invention is an information collection and sharing system for use in the event of a disaster. It can recognize the user's emotions and provide appropriate information accordingly. This system is realized by the following configuration and procedures.

[1726] 1. Obtaining user location information

[1727] When a user launches the app, the device uses its GPS to obtain the user's location information. This location information is then sent to a server, which then collects disaster information for the relevant area.

[1728] 2. Collecting and displaying disaster information for the relevant area

[1729] The server searches a database for disaster information for the relevant area based on the location information sent from the device. It then incorporates the disaster information into map data and sends the generated map data to the device. The device then analyzes this map data and displays the disaster information on a map in a format that is easy for the user to view.

[1730] 3. User Emotion Recognition

[1731] When a user enters an operation or question within the app, the device uses an emotion engine to recognize the emotion. This emotion engine determines the user's emotion by analyzing text, facial expressions, tone of voice, etc. The obtained emotion data is sent to the server.

[1732] 4. Question and Answering Using Chatbots

[1733] When a user types a question through the chatbot, it is sent to the server via the device. The server uses a generative AI model to analyze the question, retrieves necessary information from a database or external APIs, and generates an appropriate answer. This answer is adjusted based on the user's emotional state. For example, if the user is feeling anxious, a reassuring statement will be added to the answer. Finally, the answer is displayed on the device.

[1734] 5. Sharing the status of relief supplies and public services

[1735] When users input information about the status of relief supplies and the use of public services, the information is sent to the server via the device. The server stores the information in a database and sends notifications to other users. The device that receives the notification displays the information on a map and shares it with other users.

[1736] Specific examples

[1737] When a user opens the app, enters their location as "Tokyo," and then enters text expressing their feelings as "I'm anxious," this information is sent to the server and processed in the following steps:

[1738] Example prompt sentence:

[1739] "A user in Tokyo said, 'I'm worried.'"

[1740] Based on this information, the server collects disaster information for the area and generates a response that includes supplementary information to reassure the user. For example, the device might display something like, "Current disaster information: A flood warning has been issued. Please do not worry. The nearest evacuation shelter is safe."

[1741] This allows users to instantly obtain appropriate information according to their emotions, allowing them to respond to disasters with peace of mind.

[1742] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1743] Step 1:

[1744] When a user launches the app, the device uses its GPS function to obtain the user's location information. This location information is then sent to the server. The input is the user's current location, and the output is the transmission of location information to the server. Specifically, the app uses the smartphone's GPS function to send the obtained latitude and longitude data to the server.

[1745] Step 2:

[1746] The server collects disaster information for the relevant area based on the location information sent from the device. The input is the user's location information, and the output is map data that collects the disaster information. The server obtains the latest disaster information for the relevant area from the database and integrates it into the map data.

[1747] Step 3:

[1748] The server sends the generated map data to the device. The input is map data including disaster information, and the output is sending the map data to the device. Specifically, the map data is encoded in JSON format or similar and sent to the device via an API.

[1749] Step 4:

[1750] The terminal analyzes the map data received from the server and displays disaster information on the map in a format that is easy for the user to view. The input is the map data from the server, and the output is the user's display screen. The terminal analyzes the map data and overlays disaster information on the map with appropriate icons and text.

[1751] Step 5:

[1752] Users input operations or questions within the app, and the device uses an emotion engine to recognize the emotion. The input is the user's text and facial expression data, and the output is the recognized emotion data. Natural language processing and facial recognition technologies are used to analyze text and image data to determine emotions.

[1753] Step 6:

[1754] The device sends the recognized emotion data to the server. The input is emotion data, and the output is sending the emotion data to the server. Specifically, the emotion data is sent to the server via an API.

[1755] Step 7:

[1756] When a user enters a question through the chatbot, the device sends the question to the server. The input is the user's question text, and the output is the transmission of the question data to the server. The question entered in the text box is sent to the server via API.

[1757] Step 8:

[1758] The server analyzes the question content using a generative AI model based on the received question and emotion data. The input is question data and emotion data, and the output is analyzed answer data. The generative AI model analyzes the meaning of the question and generates an appropriate answer.

[1759] Step 9:

[1760] The server retrieves the necessary information from a database or external API and adjusts the information provided based on the recognized sentiment. The input is the analyzed response data and additional information from outside, and the output is the adjusted response. Specifically, if the user expresses anxiety, reassuring words are added to the response.

[1761] Step 10:

[1762] The server sends the generated adjusted answer to the device. The input is the adjusted answer, and the output is the answer sent to the device. The answer data is encoded in JSON format or similar and sent to the device.

[1763] Step 11:

[1764] The terminal displays the adjusted response on the chatbot screen. The input is the response data from the server, and the output is the user's display screen. The response is displayed in the chatbot interface in an appropriate format.

[1765] Step 12:

[1766] When users input information about the status of relief supplies and the use of public services, that information is sent to the server via their device. The input is relief information, and the output is the transmission of that information to the server. The relief information is sent to the server as text data via an API.

[1767] Step 13:

[1768] The server saves the input assistance information in a database and sends notifications to other users. The input is assistance information and the output is notification data. The server saves the information in a database, generates notifications, and sends them to users in the relevant area.

[1769] Step 14:

[1770] The device displays notifications received from the server on a map and shares them with other users. The input is notification data from the server, and the output is the user's display screen. The notification data is analyzed and displayed on the map with appropriate icons and text.

[1771] 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.

[1772] 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.

[1773] 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.

[1774] [Fourth embodiment]

[1775] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1776] 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.

[1777] 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).

[1778] 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.

[1779] 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.

[1780] 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).

[1781] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1782] 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.

[1783] 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.

[1784] 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.

[1785] 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.

[1786] 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.

[1787] 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."

[1788] This invention relates to a system for collecting and sharing necessary information when a disaster occurs, and has the function of providing disaster information based on the user's location information and generating appropriate answers to user questions using a generative AI model.

[1789] Program processing overview

[1790] System Configuration

[1791] The system of the present invention is composed of a "server," a "terminal," and a "user."

[1792] 1. Processing when the app starts

[1793] Device: When a user launches the app, the app first prepares to display a map on the initial screen, then uses the GPS function to obtain the user's location information and sends this location information to the server.

[1794] 2. Displaying information on the map

[1795] Server: Receives location information sent from the device and retrieves disaster information for the relevant area from a database based on that information. Combines the retrieved disaster information with map data to generate visually displayable map data and send it to the device.

[1796] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to view.

[1797] 3. Question and answering by chatbot

[1798] User: Enters a question into the chatbot's input field and submits it.

[1799] Terminal: Sends user questions to the server.

[1800] Server: Receives the question and analyzes it using a generative AI model. It then retrieves the necessary information from a database or external API to generate an appropriate answer. It then sends the generated answer to the device.

[1801] Terminal: Display the received response on the chatbot screen.

[1802] 4. Sharing support status

[1803] User: Enter the current status of relief supplies and public service usage.

[1804] Terminal: Sends the entered information to the server.

[1805] Server: Stores the received information in a database and sends notifications to other users in the same area.

[1806] On your device: Display the assistance you receive on a map and share it with other users.

[1807] Specific examples

[1808] Example 1: Displaying disaster information

[1809] User: Launch the app and allow location information to be sent.

[1810] Device: Sends location information to the server, receives map data, and displays it.

[1811] Server: Receives location information from users in Sapporo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Sapporo, and generates map data.

[1812] Terminal: Analyzes the received map data and displays disaster information on the map.

[1813] Example 2: Asking a Chatbot

[1814] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[1815] Terminal: Sends the entered question to the server.

[1816] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as, "The nearest evacuation shelter is XX Park."

[1817] Terminal: Display the received response on the chatbot screen.

[1818] Example 3: Sharing relief supplies

[1819] User: Enters the information "Water is running low" and submits.

[1820] Terminal: Sends the entered assistance information to the server.

[1821] Server: Receives the information, stores it in a database, and sends notifications to users in the same area.

[1822] Device: Receive a notification and see a "Water Shortage" icon on the map.

[1823] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs.

[1824] The processing flow will be explained below.

[1825] 1. Processing when the app starts

[1826] Step 1:

[1827] Device: The user launches the app.

[1828] Step 2:

[1829] Terminal: Prepares the layout to display the map on the initial screen.

[1830] Step 3:

[1831] Device: Uses GPS to obtain the user's location.

[1832] Step 4:

[1833] Device: Sends the acquired location information to the server.

[1834] 2. Displaying information on the map

[1835] Step 1:

[1836] Server: Receives location information sent from the device.

[1837] Step 2:

[1838] Server: Based on the location information, search for disaster information for the relevant area from the disaster information database.

[1839] Step 3:

[1840] Server: Incorporates disaster information for the relevant area into map data.

[1841] Step 4:

[1842] Server: Sends the generated map data to the device.

[1843] Step 5:

[1844] Terminal: Analyzes the received map data and displays it on the screen.

[1845] Step 6:

[1846] Terminal: Place disaster information icons and text on the map.

[1847] 3. Question and answering by chatbot

[1848] Step 1:

[1849] User: Enter a question into the chatbot's input field.

[1850] Step 2:

[1851] User: Presses the submit button to send the question to the server.

[1852] Step 3:

[1853] Terminal: Transfers the entered question to the server.

[1854] Step 4:

[1855] Server: Receives the question and analyzes the sentence using a generative AI model.

[1856] Step 5:

[1857] Server: Based on the query, retrieves the necessary information from a database or external API.

[1858] Step 6:

[1859] Server: Generates the appropriate answer.

[1860] Step 7:

[1861] Server: Sends the generated answer to the device.

[1862] Step 8:

[1863] Terminal: Display the received response on the chatbot screen.

[1864] 4. Sharing support status

[1865] Step 1:

[1866] User: Enter the status of use of relief supplies and public services.

[1867] Step 2:

[1868] User: Presses the submit button to send the information to the server.

[1869] Step 3:

[1870] Terminal: Transfers the input assistance information to the server.

[1871] Step 4:

[1872] Server: Receives assistance information and stores it in a database.

[1873] Step 5:

[1874] Server: Sends notifications to other users in the same area.

[1875] Step 6:

[1876] Terminal: Receives notification of support information received from the server.

[1877] Step 7:

[1878] Terminal: Displays aid status icons such as "water shortage" and "food surplus" on the map.

[1879] Example 1

[1880] 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."

[1881] In modern society, rapid and accurate information gathering and sharing is required when a disaster occurs. However, many current systems do not adequately provide real-time information based on the user's location information, and there are insufficient means to efficiently share disaster information and the status of relief supplies. As a result, users may not be able to obtain the necessary information quickly, which can delay appropriate responses.

[1882] 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.

[1883] In this invention, the server includes means for displaying a map on an initial screen when a user launches an application, means for acquiring user location information using GPS and transmitting the location information to the server, means for collecting disaster information for a corresponding area from a database based on the location information, means for combining the collected disaster information with map data to generate visually displayable map data and transmitting the data to the terminal, chatbot means for analyzing user questions using a generative model and generating appropriate answers, means for displaying the answers generated by the chatbot means, means for inputting the status of relief supplies and public services, saving the information in a database, and notifying other users, and means for displaying the relief information on a map. This enables users to quickly acquire and efficiently share disaster information based on their location information in real time.

[1884] "User" refers to any individual or entity that uses the System.

[1885] "Information collection means" refers to a combination of hard and soft data for obtaining specified information.

[1886] "Location Information" means data indicating a user's current geographic location obtained using technology such as GPS.

[1887] "Initial screen display means" refers to a function for providing the user with the initial screen that is displayed when the application is launched.

[1888] "Map Data" refers to data that includes visual representations of geographically based maps.

[1889] "Disaster information" refers to data related to disasters such as earthquakes, tsunamis, floods, and fires.

[1890] A "chatbot" is software that uses natural language processing to automatically respond to user questions.

[1891] A "generative AI model" refers to an algorithm or model that uses AI technology to automatically generate answers or explanations.

[1892] "Relief supplies" refers to relief supplies such as water, food, and medical supplies needed in the event of a disaster.

[1893] "Public services" refers to public services that can be used during a disaster, such as information on evacuation shelters and the operation status of public transportation.

[1894] "Notification means" refers to a function for notifying users of new or updated information.

[1895] "Real-time" refers to near-instantaneous processing or information updates.

[1896] "Database" refers to a system that stores data in a structured format.

[1897] "Map display means" refers to a function for displaying information on a map in a format that is easy for users to understand.

[1898] This invention is a system for collecting and sharing necessary information in the event of a disaster. The system of this invention is composed of a server, terminals, and users, and efficiently manages and provides information through their respective roles.

[1899] The system uses the Google Maps API to provide a means to display a map on the initial screen. When a user launches the application, the device first prepares to display the map on the initial screen. Next, the device uses the GPS function to obtain the user's location information and sends this location information to the server. This location information is sent securely using HTTPS.

[1900] The server receives the location information sent from the device and collects disaster information for the relevant area from a database (e.g., PostgreSQL) based on that location information. The collected disaster information is combined with map data (e.g., OpenStreetMap) to generate visually displayable map data and send it to the device.

[1901] The device analyzes the received map data and displays disaster information on the map in a user-friendly format. Specifically, various disaster icons (e.g., earthquake, flood, fire) are displayed on the map.

[1902] The system of the present invention also provides a chatbot function that uses a generative AI model. The user enters a question into the chatbot's input field and sends it. For example, "Where is the nearest evacuation shelter?" The device sends the entered question to a server, which receives the question and analyzes it using a generative AI model (e.g., OpenAI's GPT-3). Based on the analysis results, the system obtains the necessary information from a database or external API and generates an appropriate answer. The generated answer is sent to the device and displayed on the chatbot screen.

[1903] The system also includes a function for inputting and sharing the status of relief supplies and public services. Users can input the current status of relief supplies and the use of public services and send a message saying, "There is a shortage of water." The device sends this information to a server, which stores the received information in a database. Notifications are then sent to other users in the same area, and the device displays the received support information on a map. This allows for efficient and accurate information collection and sharing among users when a disaster occurs.

[1904] As a specific example, when a user launches the app and allows location information to be sent, the device sends the location information to a server, which receives and displays map data. The server receives the user's location information in Sapporo, collects disaster information such as earthquakes, tsunamis, floods, and fires in the Sapporo area, and generates map data. The device analyzes the received map data and displays the disaster information on a map.

[1905] When a user types a question into the chatbot, such as "Where is the nearest evacuation shelter?", the device sends the question to the server, which analyzes the question, searches for information about evacuation shelters in the area, and generates a response such as "The nearest evacuation shelter is XX Park." The device then displays the received response on the chatbot screen.

[1906] In this way, the system of the present invention makes it possible to quickly collect necessary information based on the user's location information when a disaster occurs, display it visually, generate appropriate answers to the user's questions, and share the status of relief supplies.

[1907] Examples of prompts:

[1908] "Where is the nearest evacuation shelter?"

[1909] Please tell me the current fire information.

[1910] "There's a water shortage."

[1911] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1912] Step 1:

[1913] Device: When the user launches the app, it begins preparations to display a map on the initial screen. Specifically, it loads the initial map data using the Google Maps API. The input triggers the application launch, and the output is that the map is ready to be displayed on the initial screen.

[1914] Step 2:

[1915] Device: Uses GPS to obtain the user's location information. This location information includes latitude and longitude. The obtained location information is sent to the server using HTTPS. The input is the latitude and longitude data obtained from the GPS, and the output is the completion of transmission to the server.

[1916] Step 3:

[1917] Server: Receives location information sent from the device. The input is the location data from the device, and the output is the completion of location information reception.

[1918] Step 4:

[1919] Server: Based on the received location information, retrieves disaster information for the corresponding area from the database. For example, if the location information is Sapporo city, collects disaster information such as earthquakes, tsunamis, floods, and fires around Sapporo city. The input is the received location information, and the output is disaster information data for the corresponding area.

[1920] Step 5:

[1921] Server: Combines collected disaster information with map data to generate visually displayable map data. The map data is obtained from map services such as OpenStreetMap. The input is disaster information data and map data, and the output is visually displayable map data.

[1922] Step 6:

[1923] Server: Sends visually displayable map data to the device. The input is the generated map data, and the output is the completion of transmission to the device.

[1924] Step 7:

[1925] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to see. Specifically, various disaster icons (e.g., earthquake, flood, fire) are displayed on the map. The input is the received map data, and the output is the map displayed to the user.

[1926] Step 8:

[1927] User: Enters a question into the chatbot's input field and submits it. For example, "Where is the nearest evacuation shelter?" The input is the user's question, and the output is submission.

[1928] Step 9:

[1929] Terminal: Sends the user's question to the server. The input is the user's question, and the output is the completion of transmission to the server.

[1930] Step 10:

[1931] Server: Receives the question and analyzes it using a generative AI model. The input is the received question, and the output is the analysis result.

[1932] Step 11:

[1933] Server: Based on the analysis results, obtains the necessary information from a database or external API and generates an appropriate answer. For example, search for information on the nearest evacuation shelter and generate an answer such as "The nearest evacuation shelter is XX Park." The input is the analysis results and information from the database or external API, and the output is the generated answer.

[1934] Step 12:

[1935] Server: Sends the generated answer to the terminal. The input is the generated answer, and the output is the completion of sending it to the terminal.

[1936] Step 13:

[1937] Terminal: Displays the received answer on the chatbot screen. The input is the received answer, and the output is the answer displayed to the user.

[1938] Step 14:

[1939] User: Enters the current status of relief supplies and the status of public service use. For example, enters "There is a water shortage." The input is the relief information entered by the user, and the output is transmission completion.

[1940] Step 15:

[1941] Terminal: Sends the input assistance information to the server. The input is the user's assistance information, and the output is the completion of transmission to the server.

[1942] Step 16:

[1943] Server: Saves the received information in the database. Here, the relief supplies information is updated. The input is the received relief information, and the output is the completion of saving it to the database.

[1944] Step 17:

[1945] Server: Sends notifications of received support information to other users in the same area. Uses push notification service. Input is support information stored in the database, and output is notification sending completion.

[1946] Step 18:

[1947] Terminal: Receives notifications and displays a "water shortage" icon on the map. The input is the received notification information, and the output is the map update shown to the user.

[1948] (Application example 1)

[1949] 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."

[1950] When a disaster or crime occurs, it is necessary to quickly and accurately grasp local danger information and support situations and provide users with appropriate countermeasures. However, current systems have limited real-time information updates and question-and-answer functions using generative models, making it difficult for users to quickly obtain the information they need. Furthermore, support information is often not shared effectively with other users. This poses a challenge in ensuring user safety in emergency situations where a rapid response is required.

[1951] 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.

[1952] In this invention, the server includes means for acquiring user location information, means for collecting disaster information and danger information for the relevant area based on the location information, means for displaying the disaster information and danger information on a map, and means for notifying other users of the danger information. This enables users to acquire information and share support information in real time even when a disaster or crime occurs, enabling them to respond quickly and appropriately.

[1953] "Disaster information" refers to information that includes specific damage situations and warnings regarding natural disasters and man-made disasters.

[1954] "Danger information" is information that includes specific situations and warnings regarding man-made dangers such as crimes and accidents.

[1955] A "generative model" refers to an artificial intelligence model that generates appropriate responses from large amounts of data, and includes natural language processing technology.

[1956] A "chatbot" is a system that automatically generates and provides appropriate answers to user questions using a generative model.

[1957] "Location Information" means your current geographic coordinates obtained using GPS or other positioning technology.

[1958] "Notification means" refers to systems and functions for communicating dangerous or important information to other users in real time.

[1959] "Support information" refers to information about the status of relief supplies and the use of public services, and is primarily shared during disasters and emergencies.

[1960] A "database" refers to a collection of data that is organized to store information and make it easy to search and update.

[1961] "User" refers to an individual or organization that uses this system and provides location information and inputs questions.

[1962] The present invention is a system for quickly and accurately collecting and sharing information in the event of a disaster or crime. Specific embodiments of the present invention will be described below.

[1963] System Configuration

[1964] The system of the present invention consists of a "server," a "terminal," and a "user." This system collects disaster and danger information based on the user's location information and provides that information to the user. It also uses a generative AI model to generate appropriate answers to the user's questions and shares the status of relief supplies and public services with other users in real time.

[1965] Hardware and software used

[1966] Hardware: Smartphone (iOS / Android compatible), smart glasses, GPS module

[1967] Software: GPS API, generative AI models (e.g. OpenAI GPT-4), RESTful API, database (MySQL)

[1968] Processing when the app starts

[1969] When a user launches the app, the device first prepares to display a map on the initial screen, then uses GPS to obtain the user's location information and sends it to the server, which uses this location information to collect disaster and danger information.

[1970] Displaying information on a map

[1971] The server retrieves disaster and danger information for the area based on the user's location information from a database, combines it with map data, and generates visually displayable map data. This map data is then sent to the device, which analyzes the received data and displays the information on the map in a format that is easy for the user to view.

[1972] Chatbot Q&A

[1973] The user enters a question into the chatbot's input field and sends it. The device sends the user's question to the server, which analyzes the received question using a generative AI model. The server then retrieves the necessary information from a database or external API, generates an appropriate answer, and sends it back to the device. The device then displays the received answer on the chatbot screen.

[1974] Prompt Sentence Examples

[1975] "Where is the nearest evacuation shelter?"

[1976] Please tell me about recent crimes.

[1977] "Please tell me the current weather conditions."

[1978] Sharing support status

[1979] Users input the current status of relief supplies and the use of public services, and send it to the server via their device. The server stores the received information in a database and sends notifications to other users in the same area. The device then displays the received relief information on a map and shares it with other users.

[1980] Example 1: Displaying disaster information

[1981] When a user launches the app and allows the transmission of location information, the device sends the location information to the server. For example, when the server receives the location information of a user in a certain city, it collects disaster information such as earthquakes, tsunamis, floods, and fires around that city and generates map data. The device analyzes the received map data and displays the disaster information on a map.

[1982] Example 2: Asking a Chatbot

[1983] When a user types the question "Where is the nearest evacuation shelter?" into the chatbot and sends it, the device sends the question to the server. The server analyzes the question, searches for information on evacuation shelters in the area, and generates an appropriate answer, such as "The nearest evacuation shelter is XX Park." The device then displays the received answer on the chatbot screen.

[1984] Example 3: Sharing relief supplies

[1985] When a user inputs and submits the information "Water shortage," the device sends the input assistance information to the server. The server receives the information, stores it in a database, and sends a notification to users in the same area. The device receives the notification and displays a "Water shortage" icon on the map.

[1986] In this way, the system of the present invention can efficiently and accurately collect and share information during disasters and crimes.

[1987] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1988] Step 1:

[1989] When a user launches the app, the device first prepares to display a map on the initial screen and obtains the user's location information using the GPS function. The input is the user's current location information, and the output is the obtained location information. This location information is then processed (for example, converted into JSON format) to be sent to the server.

[1990] Step 2:

[1991] The server receives the location information sent from the device and retrieves disaster and danger information for the relevant area from the database based on the location information. This information collection is performed using a database search query, with location information as input and disaster and danger information as output.

[1992] Step 3:

[1993] The server combines the acquired disaster and danger information with map data to generate visually displayable map data. Here, the map data is generated using a GIS (geographic information system) API, with the input being information about the relevant area and the output being displayable map data. The generated map data is sent to the device.

[1994] Step 4:

[1995] The terminal analyzes the received map data and displays disaster and danger information on the map in a format that is easy for the user to view. The input is the received map data, and the output is a display in a format that the user can view.

[1996] Step 5:

[1997] The user enters a question into the chatbot's input field and submits it. The input is the user's question, and the output is the question data to be sent to the server. The question data is sent to the server in text format.

[1998] Step 6:

[1999] The server receives a question from the user and analyzes the question using a generative AI model. The input is the user's question, and the output is the analyzed question. The AI ​​model collects information from appropriate databases and external APIs.

[2000] Step 7:

[2001] The server obtains the necessary information based on the analyzed question and generates an appropriate answer. The input is the analyzed question, and the output is the generated answer. The generated answer is sent to the terminal.

[2002] Step 8:

[2003] The terminal displays the received answer on the chatbot screen. The input is the received answer, and the output is a display in a format that can be viewed by the user.

[2004] Step 9:

[2005] Users input the current status of relief supplies and the status of public service usage, and send it to the server via their terminal. The input is relief information, and the output is data to be sent to the server. This data is sent to the server in text format.

[2006] Step 10:

[2007] The server stores the received assistance information in a database and sends notifications to other users in the same area. The input is assistance information, and the output is a notification message. Notifications are sent using a push notification API.

[2008] Step 11:

[2009] The device receives the notification and displays the support information on the map. The input is the received notification message, and the output is the support information displayed on the map. This allows other users to share support information in real time.

[2010] The above are the specific processing steps of the system that realizes the application example.

[2011] 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.

[2012] This invention combines a system for collecting and sharing necessary information in the event of a disaster with an emotion engine that recognizes the user's emotions, thereby providing appropriate information according to the user's psychological state.

[2013] Program processing overview

[2014] System Configuration

[2015] The system of the present invention is composed of a "server," a "terminal," and a "user." It also incorporates an emotion engine for recognizing the user's emotions.

[2016] 1. Processing when the app starts

[2017] On the device: When a user launches the app, the app prepares a layout to display a map on the initial screen, and uses the GPS function to obtain the user's location information. This location information is then sent to the server.

[2018] 2. Displaying information on the map

[2019] Server: Receives location information sent from the device, searches for disaster information for the relevant area in the disaster information database based on the location information, incorporates the disaster information for the relevant area into map data, and sends the generated map data to the device.

[2020] Terminal: Analyzes the received map data and displays disaster information on the map in a format that is easy for the user to view.

[2021] 3. Question and answering by chatbot

[2022] User: Enters a question into the chatbot's input field and submits it.

[2023] Terminal: Sends user questions to the server.

[2024] Server: Receives the question and analyzes it using the generative AI model. Retrieves necessary information from databases and external APIs to generate an appropriate answer. Sends the generated answer to the device.

[2025] Terminal: Display the received response on the chatbot screen.

[2026] 4. Sharing support status

[2027] User: Enter and submit information on the status of relief supplies and the use of public services.

[2028] Terminal: Sends the entered information to the server.

[2029] Server: Saves the entered assistance information in a database and sends notifications to other users.

[2030] On your device: Display the assistance you receive on a map and share it with other users.

[2031] 5. Use of Emotion Engine

[2032] Users: Express their emotions (e.g., text, facial expressions) while interacting with the app or asking questions.

[2033] On-device: Recognizes user emotions using an emotion engine.

[2034] Server: Receives the user's emotional data recognized by the emotion engine and adjusts the tone of the response and provides appropriate information. For example, if the server detects that the user is feeling anxious, it provides information in a reassuring manner.

[2035] Specific examples

[2036] Example 1: Displaying disaster information

[2037] User: Launch the app and allow location information to be sent.

[2038] Device: Sends location information to the server, receives map data, and displays it.

[2039] Server: Receives location information from users in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Tokyo, and generates map data.

[2040] Terminal: Analyzes the received map data and displays disaster information on the map.

[2041] Example 2: Asking a Chatbot

[2042] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[2043] Terminal: Sends the entered question to the server.

[2044] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as "The nearest evacuation shelter is XX Park."

[2045] Terminal: Display the received response on the chatbot screen.

[2046] Example 3: Sharing relief supplies

[2047] User: Enters the information "Water is running low" and submits.

[2048] Terminal: Sends the entered assistance information to the server.

[2049] Server: Receives the information, stores it in a database, and notifies users in the same area.

[2050] Device: Receive a notification and see a "Water Shortage" icon on the map.

[2051] Example 4: Using an Emotion Engine

[2052] User: Type, "I'm really worried. Is there anything I can reassure you about?"

[2053] Device: The emotion engine recognizes the user's emotion of "anxiety."

[2054] Server: Generates a reassuring response based on the perceived emotion (e.g., "Nearby evacuation centers have sufficient supplies").

[2055] Device: Display responses based on emotions.

[2056] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs, and also provides appropriate information based on the user's emotions.

[2057] The processing flow will be explained below.

[2058] Program processing flow (including emotion engine)

[2059] 1. Processing when the app starts

[2060] Step 1:

[2061] Device: The user launches the app.

[2062] Step 2:

[2063] Terminal: Prepares the layout to display the map on the initial screen.

[2064] Step 3:

[2065] Device: Uses GPS to obtain the user's location.

[2066] Step 4:

[2067] Device: Sends the acquired location information to the server.

[2068] 2. Displaying information on the map

[2069] Step 1:

[2070] Server: Receives location information sent from the device.

[2071] Step 2:

[2072] Server: Based on the location information, search for disaster information for the relevant area from the disaster information database.

[2073] Step 3:

[2074] Server: Incorporates disaster information for the relevant area into map data.

[2075] Step 4:

[2076] Server: Sends the generated map data to the device.

[2077] Step 5:

[2078] Terminal: Analyzes the received map data and displays it on the screen.

[2079] Step 6:

[2080] Terminal: Place disaster information icons and text on the map.

[2081] 3. Question and answering by chatbot

[2082] Step 1:

[2083] User: Enter a question into the chatbot's input field.

[2084] Step 2:

[2085] User: Presses the submit button to send the question to the server.

[2086] Step 3:

[2087] Terminal: Transfers the entered question to the server.

[2088] Step 4:

[2089] Server: Receives the question and analyzes the sentence using a generative AI model.

[2090] Step 5:

[2091] Server: Based on the query, retrieves the necessary information from a database or external API.

[2092] Step 6:

[2093] Server: Generates the appropriate answer.

[2094] Step 7:

[2095] Server: Sends the generated answer to the device.

[2096] Step 8:

[2097] Terminal: Display the received response on the chatbot screen.

[2098] 4. Sharing support status

[2099] Step 1:

[2100] User: Enter the status of use of relief supplies and public services.

[2101] Step 2:

[2102] User: Presses the submit button to send the information to the server.

[2103] Step 3:

[2104] Terminal: Transfers the input assistance information to the server.

[2105] Step 4:

[2106] Server: Receives assistance information and stores it in a database.

[2107] Step 5:

[2108] Server: Sends notifications to other users in the same area.

[2109] Step 6:

[2110] Terminal: Receives notification of support information received from the server.

[2111] Step 7:

[2112] Terminal: Displays aid status icons such as "water shortage" and "food surplus" on the map.

[2113] 5. Use of Emotion Engine

[2114] Step 1:

[2115] Users: Input or express their emotions (e.g., text, facial expressions) while interacting with or asking questions within the app.

[2116] Step 2:

[2117] On-device: Recognizes user emotions using an emotion engine.

[2118] Step 3:

[2119] Device: Sends the recognized emotion data to the server.

[2120] Step 4:

[2121] Server: Receives emotion data and stores it in a database.

[2122] Step 5:

[2123] Server: Provides appropriate information and adjusts the tone of responses based on the user's emotions recognized by the emotion engine.

[2124] Step 6:

[2125] Server: Generates responses that correspond to the perceived emotion, for example, providing reassuring information if the user is feeling anxious.

[2126] Step 7:

[2127] Server: Sends the generated answer to the device.

[2128] Step 8:

[2129] Terminal: Display the received response on the chatbot screen.

[2130] Specific examples

[2131] Example 1: Displaying disaster information

[2132] Step 1:

[2133] User: Launch the app and allow location information to be sent.

[2134] Step 2:

[2135] Device: Sends location information to the server.

[2136] Step 3:

[2137] Server: Receives location information from users in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires around Tokyo, and generates map data.

[2138] Step 4:

[2139] Terminal: Analyzes the received map data and displays disaster information on the map.

[2140] Example 2: Asking a Chatbot

[2141] Step 1:

[2142] User: Type the question "Where is the nearest evacuation shelter?" into the chatbot and submit.

[2143] Step 2:

[2144] Terminal: Sends the entered question to the server.

[2145] Step 3:

[2146] Server: Analyzes the question, searches for information about evacuation shelters in the area, and generates an answer such as "The nearest evacuation shelter is XX Park."

[2147] Step 4:

[2148] Terminal: Display the received response on the chatbot screen.

[2149] Example 3: Sharing relief supplies

[2150] Step 1:

[2151] User: Enters the information "Water is running low" and submits.

[2152] Step 2:

[2153] Terminal: Sends the entered assistance information to the server.

[2154] Step 3:

[2155] Server: Receives the information, stores it in a database, and notifies users in the same area.

[2156] Step 4:

[2157] Device: Receive a notification and see a "Water Shortage" icon on the map.

[2158] Example 4: Using an Emotion Engine

[2159] Step 1:

[2160] User: Type, "I'm really worried. Is there anything I can reassure you about?"

[2161] Step 2:

[2162] Device: The emotion engine recognizes the user's emotion of "anxiety."

[2163] Step 3:

[2164] Device: Sends the recognized emotion data to the server.

[2165] Step 4:

[2166] Server: Generates a reassuring response based on the perceived emotion (e.g., "Nearby evacuation centers have sufficient supplies").

[2167] Step 5:

[2168] Device: Display responses based on emotions.

[2169] In this way, the system of the present invention can efficiently and accurately collect and share information when a disaster occurs, and also provides appropriate information based on the user's emotions.

[2170] Example 2

[2171] 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."

[2172] When a disaster occurs, rapid and accurate information gathering and sharing is required, but the current system lacks the ability to provide information that takes into account the psychological state of the user.Furthermore, it is difficult to effectively update disaster information in real time and share the status of relief supplies.

[2173] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring user location information, means for collecting disaster information for a relevant area, means for displaying the disaster information on a map, chatbot means using a generative model to accept user questions, means for displaying generated answers, means for inputting and sharing the status of relief supplies and public services, emotion engine means for recognizing the user's emotions, and means for adjusting the content of answers and the provision of information based on the recognized emotions. This enables rapid and accurate information collection and sharing in the event of a disaster, and further enables the provision of appropriate information according to the user's psychological state.

[2174] "Means for obtaining user location information" means a method of using the device's GPS function or other location information obtaining technology to obtain the user's current location in the form of latitude and longitude.

[2175] The "means for collecting disaster information for the relevant area" is a method for searching and collecting disaster information such as earthquakes, tsunamis, floods, and fires in a specified area from a database based on the location information.

[2176] "Means for displaying disaster information on a map" refers to a method of incorporating collected disaster information into map data using a geographic information system (GIS) and presenting it visually to users.

[2177] A "chatbot method using a generative model" is a method that uses artificial intelligence (AI) to accept questions from users, analyzes the content of the question using natural language processing technology, and generates appropriate answers.

[2178] The "means for displaying the generated answer" is a method for displaying the answer generated by the chatbot means on the screen of the terminal.

[2179] "Means for inputting and sharing the status of relief supplies and public services" refers to a method by which users can input the status of relief supplies and the status of use of public services, send that information to a server, and share it with other users.

[2180] The "emotion engine means for recognizing user emotions" is a technology that determines the user's emotional state through text input and facial expression analysis, and acquires that emotional data.

[2181] "Means for adjusting response content and information provision based on recognized emotions" refers to a method for changing the tone of the information provided and responses based on the user's emotional data obtained by the emotion engine, thereby achieving a more appropriate and empathetic response.

[2182] This invention relates to a system for collecting and sharing information when a disaster occurs, and in particular to a system for recognizing the emotions of users and providing appropriate information.

[2183] System Configuration

[2184] The system of the present invention is composed of a server, a terminal, and a user. Each component and its function will be described in detail below.

[2185] server

[2186] The server is a central information processing unit that includes multiple functional modules. This central information processing unit has the following main functions:

[2187] 1. Location information receiving module:

[2188] This module receives user location information from the device and generates basic data for accessing the disaster information database. This module receives data using HTTPS communication.

[2189] 2. Disaster Information Collection Module:

[2190] Based on the location information, the system searches and collects the latest disaster information for the relevant area from a disaster information database. This disaster information includes various types such as earthquakes, tsunamis, floods, and fires.

[2191] 3. Map data generation module:

[2192] The collected disaster information is incorporated into map data and processed so that it can be displayed in a format that is intuitively easy for users to understand. This processing is done using a geographic information system (GIS).

[2193] 4. Chatbot module:

[2194] It uses generative AI models to respond to user questions, using natural language processing technologies such as OpenAI's GPT-3 to analyze the question and retrieve the necessary information from databases or external APIs to generate an answer.

[2195] 5. Support status management module:

[2196] Information about relief supplies and public services provided by users is stored in a database and notified to other users.

[2197] 6. Emotion Engine Module:

[2198] Recognize and capture user emotions. This emotional data is used to tailor question responses and information provision.

[2199] Terminal

[2200] A terminal is a device, including a smartphone or tablet, that acts as an interface between the user and the server. A terminal has the following functions:

[2201] 1. Acquisition of location information:

[2202] The GPS function is used to obtain the user's current location, which is saved as latitude and longitude and sent to the server.

[2203] 2. Map display:

[2204] The map data sent from the server is analyzed and disaster information is displayed intuitively, with icons and colors used to indicate the type of disaster.

[2205] 3. Chatbot screen:

[2206] It is an interface with a question input field and a text area, which sends questions from users to the server and displays the answers received.

[2207] 4. Emotion recognition:

[2208] It uses an emotion engine that analyzes text input and facial expressions to recognize the user's emotional state, and the recognized emotion data is sent to the server.

[2209] user

[2210] The user is the entity that uses the system and performs the following operations:

[2211] 1. Location Sharing:

[2212] Launch the app and allow it to send location information.

[2213] 2. Enter your question:

[2214] Enter your question in the chatbot's input field and submit.

[2215] 3. Enter supporting information:

[2216] Enter the status of relief supplies and the usage of public services and submit.

[2217] 4. Expressing emotions:

[2218] Express your emotions while interacting with the app or asking questions (e.g., through text, facial expressions).

[2219] Specific examples

[2220] Example 1: Displaying disaster information

[2221] When a user launches the app and allows location information to be sent, the device sends the location information to the server. The server receives the user's location information in Tokyo, collects disaster information such as earthquakes, tsunamis, floods, and fires in the Tokyo area, and generates map data. The device analyzes the received map data and displays the disaster information on the map. The server notifies the user that "the latest disaster information has been obtained."

[2222] Example 2: Asking a Chatbot

[2223] When a user inputs the question "Where is the nearest evacuation shelter?" into the chatbot and sends it, the device sends the question to the server. The server analyzes the question, searches for evacuation shelter information in the relevant area, and generates the answer "The nearest evacuation shelter is XX Park." The device displays the received answer on the chatbot screen. It also temporarily displays the message "Analyzing question..."

[2224] Example 3: Sharing relief supplies

[2225] When a user inputs and sends the information "There is a water shortage," the device sends the support information to the server. The server receives the information and stores it in a database. It also notifies other users in the same area. The device receives the notification and displays a "Water Shortage" icon on the map. It also displays the message "Support information has been added."

[2226] Example 4: Using an Emotion Engine

[2227] When the user inputs "I'm very anxious. Is there any information that can reassure me?", the device uses an emotion engine to recognize the user's emotion of "anxiety." Depending on the recognized emotion, the server generates a reassuring response such as "Nearby evacuation centers have sufficient supplies." The device displays the response according to the emotion and temporarily displays the message "Analyzing user's emotions..."

[2228] Prompt Sentence Examples

[2229] "Please tell me the latest disaster information for the Tokyo area."

[2230] "Please tell me where the evacuation shelter is."

[2231] "What should I do if there is a water shortage?"

[2232] "Please give me some information to ease my anxiety."

[2233] In this way, the system of the present invention not only efficiently and accurately collects and shares information when a disaster occurs, but also provides appropriate information based on the user's emotions.

[2234] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2235] Step 1: What to do when the app starts

[2236] Device: When a user launches the app, the layout to be displayed on the initial screen is prepared and the GPS function is used to obtain the user's location. This location information is recorded as latitude and longitude. The recorded location information is sent to the server using HTTPS communication. Specifically, the device notifies the user by saying "Obtaining location information..."

[2237] Input: App launch, GPS location information

[2238] Data processing: location information acquisition, data recording (latitude and longitude)

[2239] Output: Location information transmission

[2240] Step 2: Displaying information on the map

[2241] server:

[2242] 1. The location information sent from the device is received. The received data is analyzed and the corresponding area is identified.

[2243] 2. Access the disaster information database and collect disaster information (earthquake, tsunami, flood, fire, etc.) for the identified area.

[2244] 3. The collected disaster information is incorporated into map data, which is generated using GIS.

[2245] 4. The generated map data is sent to the device.

[2246] Device:

[2247] 1. Analyze the received map data and display disaster information in a user-friendly format (e.g., using different colors and icons).

[2248] Specifically, it notifies the user that "the latest disaster information has been obtained."

[2249] Input: Location

[2250] Data processing: disaster information acquisition, map data generation

[2251] Output: Send map data, display disaster information on the map

[2252] Step 3: Answer questions with a chatbot

[2253] User:

[2254] 1. Enter your question in the chatbot's input field and submit.

[2255] Device:

[2256] 1. The question entered by the user is sent to the server.

[2257] server:

[2258] 1. Analyze the received question. A generative AI model (e.g., OpenAI's GPT-3) is used to analyze the content of the question using natural language processing techniques.

[2259] 2. Depending on the content of the question, access databases or external APIs to obtain the necessary information.

[2260] 3. Generate appropriate answers based on the information obtained.

[2261] 4. Send the generated answer to the device.

[2262] Device:

[2263] 1. Display the received answer on the chatbot screen. Specifically, it displays "Analyzing question..."

[2264] Input: Question

[2265] Data processing: Question analysis, information acquisition, answer generation

[2266] Output: Display answer

[2267] Step 4: Sharing support status

[2268] User:

[2269] 1. Enter and submit information about the status of relief supplies and the use of public services.

[2270] Device:

[2271] 1. The entered support information is sent to the server.

[2272] server:

[2273] 1. The received assistance information is stored in a database.

[2274] 2. Send notifications to other users in the same area based on the saved information.

[2275] Device:

[2276] 1. Receive a notification and display support information on the map. Specifically, the message "Support information has been added" will be displayed.

[2277] Input: Support information

[2278] Data processing: Support information storage, notification generation

[2279] Output: Support information display, notification

[2280] Step 5: Use the Emotion Engine

[2281] User:

[2282] 1. Express your emotions (through text, facial expressions, etc.) while operating or asking questions within the app.

[2283] Device:

[2284] 1. The emotion engine recognizes the user's emotions, using emotion recognition software and facial expression analysis using a camera.

[2285] 2. The recognized emotion data is sent to the server.

[2286] server:

[2287] 1. Receive emotion data obtained by the emotion engine.

[2288] 2. Adjust the content and tone of your responses based on the user's emotions. For example, if the user is feeling anxious, generate reassuring information.

[2289] Device:

[2290] 1. Display tailored answers or information to the user. Specifically, the action is to display "Analyzing user sentiment..."

[2291] Input: Emotion

[2292] Data processing: emotion recognition, data transmission, response adjustment

[2293] Output: Adjusted answer, information display

[2294] (Application example 2)

[2295] 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."

[2296] Conventional disaster information systems generally provide information based on location information and share relief supplies, but they have the problem of not being able to provide information that takes into account the user's psychological state. During disasters, users often feel anxiety and fear, and providing information that ignores these emotions does not provide sufficient support to the user. The present invention aims to improve the user's sense of security by recognizing the user's emotions and providing appropriate information according to those emotions.

[2297] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2298] In this invention, the server includes a means for acquiring user location information, a means for recognizing emotions, a chatbot means using a generative model, and a means for adjusting information provision based on emotion recognition, thereby enabling appropriate information provision that takes into account the user's psychological state.

[2299] "Disaster occurrence" refers to the time when a natural or man-made disaster occurs, and a rapid response is required to ensure the safety of the affected areas and people.

[2300] "Information collection and sharing" refers to the act of gathering data and knowledge needed in the event of a disaster and exchanging it with relevant people and organizations through communication means.

[2301] "User Location Information" refers to the geographic location of a User, obtained using location-finding technology such as GPS.

[2302] "Disaster information for the relevant area" refers to information about disasters related to the user's current location or the specified area, including data on the types and occurrence status of earthquakes, floods, fires, etc.

[2303] "Displaying on a map" means providing collected disaster information visually to users using digital maps and geographic information systems (GIS).

[2304] A "chatbot means using generative models" is a program that uses technology in the field of natural language processing to automatically generate answers to users' questions.

[2305] The "means for displaying the answer" is an interface that displays the answer generated by the generative model on the user's terminal.

[2306] "Status of relief supplies and public services" refers to information such as food, water, medical supplies, and other supplies provided during disasters, as well as the availability of evacuation shelters and the operation status of public transportation.

[2307] "Emotion recognition" refers to technology that determines a user's current emotional state by analyzing text, facial expressions, tone of voice, etc.

[2308] "Means for adjusting information provision" refers to a function that changes the content and presentation of information in an appropriate form according to the user's recognized emotions.

[2309] "Means for updating disaster information in real time" refers to technology that keeps collected disaster information up to date and provides it to users quickly.

[2310] The present invention is an information collection and sharing system for use in the event of a disaster. It can recognize the user's emotions and provide appropriate information accordingly. This system is realized by the following configuration and procedures.

[2311] 1. Obtaining user location information

[2312] When a user launches the app, the device uses its GPS to obtain the user's location information. This location information is then sent to a server, which then collects disaster information for the relevant area.

[2313] 2. Collecting and displaying disaster information for the relevant area

[2314] The server searches a database for disaster information for the relevant area based on the location information sent from the device. It then incorporates the disaster information into map data and sends the generated map data to the device. The device then analyzes this map data and displays the disaster information on a map in a format that is easy for the user to view.

[2315] 3. User Emotion Recognition

[2316] When a user enters an operation or question within the app, the device uses an emotion engine to recognize the emotion. This emotion engine determines the user's emotion by analyzing text, facial expressions, tone of voice, etc. The obtained emotion data is sent to the server.

[2317] 4. Question and Answering Using Chatbots

[2318] When a user types a question through the chatbot, it is sent to the server via the device. The server uses a generative AI model to analyze the question, retrieves necessary information from a database or external APIs, and generates an appropriate answer. This answer is adjusted based on the user's emotional state. For example, if the user is feeling anxious, a reassuring statement will be added to the answer. Finally, the answer is displayed on the device.

[2319] 5. Sharing the status of relief supplies and public services

[2320] When users input information about the status of relief supplies and the use of public services, the information is sent to the server via the device. The server stores the information in a database and sends notifications to other users. The device that receives the notification displays the information on a map and shares it with other users.

[2321] Specific examples

[2322] When a user opens the app, enters their location as "Tokyo," and then enters text expressing their feelings as "I'm anxious," this information is sent to the server and processed in the following steps:

[2323] Example prompt sentence:

[2324] "A user in Tokyo said, 'I'm worried.'"

[2325] Based on this information, the server collects disaster information for the area and generates a response that includes supplementary information to reassure the user. For example, the device might display something like, "Current disaster information: A flood warning has been issued. Please do not worry. The nearest evacuation shelter is safe."

[2326] This allows users to instantly obtain appropriate information according to their emotions, allowing them to respond to disasters with peace of mind.

[2327] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2328] Step 1:

[2329] When a user launches the app, the device uses its GPS function to obtain the user's location information. This location information is then sent to the server. The input is the user's current location, and the output is the transmission of location information to the server. Specifically, the app uses the smartphone's GPS function to send the obtained latitude and longitude data to the server.

[2330] Step 2:

[2331] The server collects disaster information for the relevant area based on the location information sent from the device. The input is the user's location information, and the output is map data that collects the disaster information. The server obtains the latest disaster information for the relevant area from the database and integrates it into the map data.

[2332] Step 3:

[2333] The server sends the generated map data to the device. The input is map data including disaster information, and the output is sending the map data to the device. Specifically, the map data is encoded in JSON format or similar and sent to the device via an API.

[2334] Step 4:

[2335] The terminal analyzes the map data received from the server and displays disaster information on the map in a format that is easy for the user to view. The input is the map data from the server, and the output is the user's display screen. The terminal analyzes the map data and overlays disaster information on the map with appropriate icons and text.

[2336] Step 5:

[2337] Users input operations or questions within the app, and the device uses an emotion engine to recognize the emotion. The input is the user's text and facial expression data, and the output is the recognized emotion data. Natural language processing and facial recognition technologies are used to analyze text and image data to determine emotions.

[2338] Step...

Claims

1. A system for collecting and sharing information in the event of a disaster, A means for obtaining user location information; means for collecting disaster information for the relevant area based on the location information; means for displaying the disaster information on a map; A chatbot means using a generative model to accept user questions, means for displaying a response generated by the chatbot means; A system that includes a means to input and share the status of relief supplies and public services.

2. The system of claim 1 further comprising means for updating disaster information in real time based on user location information.

3. 2. The system according to claim 1, further comprising means for storing support information from users in a database and notifying other users of the support information.

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