System

Abstract

To provide a system.SOLUTION: A system comprises: means for transmitting a message saying "Do you have any difficulties?" to a disaster victim by inputting a specific prompt sentence to a generative AI model; an emotion engine for recognizing the emotion of the disaster victim on the basis of a response to the message from the disaster victim; proposal means for providing the disaster victim with useful information during a disaster and suggesting actions taken by the disaster victim during a disaster on the basis of the recognized emotion using the generative AI model; means for adjusting the report content during a disaster to a municipality and the government on the basis of the emotion; and means for transmitting the report content to the municipality and the government via the Internet.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 a description and related instruction sentence regarding 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] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Victims of large-scale disasters may find it difficult to access appropriate support information because of the burden of actively seeking out information. There is also a need for a system that can grasp the specific problems and needs of victims and provide support based on those. [Means for solving the problem]

[0005] The system disclosed herein includes a means for sending a message to a disaster victim saying "Is there anything you are having trouble with?" by inputting a specific prompt sentence into a generative AI model; an emotion engine for recognizing the emotions of the disaster victim based on the disaster victim's response to the message; a suggestion means for providing the disaster victim with information that will be useful to the disaster victim and suggesting actions the disaster victim can take in the event of a disaster based on the recognized emotions using the generative AI model; a means for adjusting the content of reports to local governments and the government in the event of a disaster based on the emotions; and a means for transmitting the content of the reports to the local government and the government via the Internet. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 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. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 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. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 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. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. [Figure 19] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system according to the embodiment 2 of the second embodiment in the case where an emotion engine is combined. [Figure 20] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when combined with an emotion engine. [Figure 21] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the embodiment 3 of the form example 3 in the case where an emotion engine is combined. [Figure 22] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0011] 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.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] 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. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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 wide area network (WAN) and / or a local area network (LAN).

[0018] 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.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. 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.

[0020] 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 (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Fig. 2, 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. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process 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 process program 56 executed on the RAM 30.

[0024] 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.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention uses communication means such as a messenger app or an internet search tool as a means for sending a message to disaster victims asking, "Is there anything you need help with?" For example, a message can be sent to disaster victims from an official account of a messenger app.

[0029] "Example 2"

[0030] To receive responses from disaster victims, communication methods such as messenger apps and internet search tools are used. For example, messages from disaster victims can be received from official messenger app accounts.

[0031] "Example 3"

[0032] Natural language processing technology and machine learning technology are used as a means for the generative AI to provide consultation, guide users to useful information, and suggest actions based on the received answers. For example, keywords contained in messages from disaster victims are extracted and appropriate information is provided based on them. The server may be equipped with a suggestion means for providing information that will be useful to disaster victims and suggesting actions for disaster victims to take in the event of a disaster based on the emotions of the disaster victims recognized using the generative AI model.

[0033] "Example 4"

[0034] As a means of coordinating consultations with local governments and the government, data sharing methods via the Internet will be used. For example, messages from disaster victims will be collected and provided to local governments and the government to optimize support for disaster victims.

[0035] The process flow of each embodiment will be described below.

[0036] "Example 1"

[0037] Step 1: The system sends a message to the victim via the official account of the messenger app asking, "Is there anything you need help with?"

[0038] Step 2: Receive a response message from the victim, the message including information indicating the victim's problems and needs.

[0039] Step 3: Analyze the messages received and understand the information needed by the victims.

[0040] Step 4: Based on the information gathered, the generating AI provides appropriate consultation to victims, directs them to useful information, and suggests actions to take.

[0041] "Example 2"

[0042] Step 1: The system sends a message to victims via an Internet search tool asking, "Is there anything you need help with?"

[0043] Step 2: Receive a response message from the victim, the message including information indicating the victim's problems and needs.

[0044] Step 3: Analyze the messages received and understand the information needed by the victims.

[0045] Step 4: Based on the information gathered, the generating AI provides appropriate consultation to victims, directs them to useful information, and suggests actions to take.

[0046] "Example 3"

[0047] Step 1: The system aggregates messages from disaster victims.

[0048] Step 2: Provide aggregated messages to local governments and governments.

[0049] Step 3: Local governments and governments will optimize assistance to disaster victims based on the messages provided.

[0050] Example 1

[0051] Next, a description will be given of Example 1 of the embodiment 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".

[0052] There is a problem in that it is difficult for disaster victims to receive prompt and appropriate support. In particular, support is often delayed because disaster victims have limited means to properly communicate their problems. Another challenge is efficiently collecting information from disaster victims and providing optimal support in cooperation with local governments and the national government.

[0053] 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.

[0054] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for acquiring the contact information of the disaster victim from a database, a means for generating a message using the API of a messenger app, a means for sending the generated message to the disaster victim, a means for receiving a reply from the disaster victim and storing it in a database, a means for using a generation AI to provide advice based on the received reply, for directing the victim to useful information and for suggesting actions, and a means for coordinating the details of the consultation with the local government or the government. This enables the disaster victim to receive prompt and appropriate support.

[0055] "Disaster Victim" refers to an individual or group affected by a disaster.

[0056] "Means for sending messages" refers to a communication means for sending information such as text or images to disaster victims.

[0057] "Contact information" refers to information for contacting disaster victims, and includes, for example, phone numbers, email addresses, and messenger app IDs.

[0058] A "database" refers to a system that systematically stores information and allows it to be searched and updated as needed.

[0059] "Messenger App API" refers to the program interface provided by a messenger app, and means by which external systems can use the functions of a messenger app.

[0060] "Means for generating a message" refers to a program or algorithm used to create the content of the message to be sent.

[0061] "Means for receiving a reply" refers to a communication means for receiving a reply from the disaster victim.

[0062] "Generative AI" refers to a system that uses artificial intelligence technology to generate appropriate information and suggestions based on the responses of disaster victims.

[0063] "Means of providing consultation, directing people to useful information, and suggesting actions" refers to means of providing appropriate advice and information based on the situation of disaster victims and suggesting specific actions to take.

[0064] "Means of collaboration with local governments and the government" refers to means for sharing information with local governments and government agencies and working together to provide support to disaster victims.

[0065] This invention is a system for providing prompt and appropriate support to disaster victims. The system operates in cooperation with three parties: a server, a terminal, and a user.

[0066] The server runs a program to send a message to disaster victims asking, "Is there anything you need help with?" This program retrieves the contact information of the disaster victims from a database, and uses the API of a messenger app to generate and send a message. Specifically, the server connects to the database using AWS (registered trademark) RDS (Relational Database Service) to retrieve the contact information of the disaster victims. It then generates a message using the LINE Messaging API or Facebook Messenger API and sends it to the disaster victims.

[0067] The terminal is a device that disaster victims use to receive and reply to messages. The disaster victim opens a messenger app on their smartphone or tablet and receives messages sent from the server. The disaster victim replies to the message, and the reply is sent to the server.

[0068] The server receives replies from the victims and stores them in a database. The server receives replies from the victims using the LINE Messaging API Webhook, analyzes the content of the replies, and stores them in a database. The stored information is analyzed by a generation AI, which provides consultation to the victims, guides them to useful information, and suggests actions to take.

[0069] As a specific example, the server runs on an AWS EC2 instance and uses the LINE Messaging API to send messages to disaster victims. The server first obtains the LINE ID of the disaster victim from a database and calls the LINE Messaging API using that ID. It then sends the message "Is there anything you need help with?" via the API. The server may be equipped with a means to send the message "Is there anything you need help with?" to disaster victims by inputting a specific prompt sentence into the generative AI model.

[0070] Examples of prompts to be input to a generative AI model include:

[0071] "Please create a program to send a message to disaster victims asking, 'Is there anything you need help with?' Use the official account of the messenger app and send the message using the LINE Messaging API."

[0072] In this way, the server can send messages to provide assistance to disaster victims quickly and store the replies in the database, enabling disaster victims to receive prompt and appropriate assistance.

[0073] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0074] Step 1:

[0075] The server retrieves the victim's contact information from a database.

[0076] Input: Database connection information, victim status (e.g. active)

[0077] Specific operation: The server connects to AWS RDS and executes an SQL query to obtain contact information (e.g. LINE ID) of active victims.

[0078] Output: Contact information of victims (e.g. list of LINE IDs)

[0079] Step 2:

[0080] The server generates the message using the messenger app's API.

[0081] Input: Contact information of the victim, message content (e.g. "Is there anything you need help with?")

[0082] Specific behavior: The server uses the obtained contact information to send an HTTP POST request to the LINE Messaging API or Facebook Messenger API to generate a message.

[0083] Output: API request for the generated message

[0084] Step 3:

[0085] A server-generated message is sent to the victim.

[0086] Input: The API request for the generated message

[0087] Specific operation: The server sends an API request, checks the response from the API, and verifies that the status code is 200 to confirm that the message was sent successfully.

[0088] Output: API response (e.g., successful submission status)

[0089] Step 4:

[0090] The victim receives the message and replies.

[0091] Input: Message sent to victim's device

[0092] Specific operation: The victim opens a messenger app on their smartphone or tablet and receives the message sent from the server. The victim then replies to the message.

[0093] Output: Reply message from the victim

[0094] Step 5:

[0095] The server receives replies from victims and stores them in a database.

[0096] Input: Reply message from the victim

[0097] Specific operation: The server receives replies from disaster victims using the LINE Messaging API Webhook, analyzes the contents of the replies, and stores them in a database.

[0098] Output: Responses stored in the database

[0099] Step 6:

[0100] Based on the answers received by the server, the generative AI will provide consultation, guide the user to useful information, and suggest actions.

[0101] Input: Responses stored in the database

[0102] Specific operation: The server uses the generative AI model to analyze the content of the victim's replies and generate appropriate advice, guidance to useful information, and suggestions for action.

[0103] Output: Generated consultation content and action suggestions

[0104] Step 7:

[0105] The server will share the consultation information with local governments and the government.

[0106] Input: Generated consultation content and action suggestions

[0107] Specific operation: The server connects with local government and government systems to share the generated consultation content and action suggestions.

[0108] Output: Information shared with local governments and governments

[0109] In this way, the server, terminals, and users can work together to provide quick and appropriate support to disaster victims.

[0110] (Application example 1)

[0111] Next, a description will be given of Application Example 1 of Form 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."

[0112] In order for disaster victims to receive prompt and appropriate support, it is important to accurately understand the situation and needs of the victims. However, with conventional methods, there were many cases where the collection of information from the victims was delayed and appropriate support was not provided. In addition, there were cases where it was difficult for the victims to request support themselves, which resulted in delays in providing support.

[0113] 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.

[0114] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice or guide the victim to useful information and suggest actions based on the received response, a means for coordinating the consultation content with a local government or the government, a means for sending a message using an API of a messenger app, and a means for obtaining a reply using the user ID of the disaster victim. This makes it possible to quickly and accurately grasp the situation and needs of the disaster victim and provide appropriate support.

[0115] "Victims" refers to people affected by a disaster.

[0116] "Means for sending a message" refers to a communication means for sending a specific message to a disaster victim.

[0117] "Means of receiving a response" refers to the means of communication for receiving replies or responses from disaster victims.

[0118] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate information and suggested actions.

[0119] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to the means by which the generative AI provides necessary information and suggests appropriate actions based on the victims' responses.

[0120] "Means of collaboration with local governments and the government" refers to the means of sharing the consultation details and needs of disaster victims with local governments and government agencies, and of coordinating support activities.

[0121] "Messenger app API" refers to the program interface provided by a messenger application that can be used to send and receive messages.

[0122] "User ID" refers to a unique identifier used to identify a disaster victim.

[0123] "Means of obtaining a reply" refers to a communication means for obtaining a reply from the disaster victim.

[0124] The system for carrying out the present invention provides prompt and appropriate support to disaster victims by sending them a message asking, "Is there anything you need help with?" and receiving a reply from the disaster victim. A specific embodiment of this system will be described below.

[0125] System Configuration

[0126] The system consists of the following main components:

[0127] 1. Server: Sends messages, receives responses, analyzes using generative AI, and coordinates with local governments and the government.

[0128] 2. Victim's device: A device with a messenger app installed, such as a smartphone or tablet.

[0129] 3. Generative AI model: An artificial intelligence system that analyzes responses from disaster victims and provides appropriate information and suggests actions.

[0130] Program Processing

[0131] The server performs the process in the following procedure.

[0132] 1. Send a message:

[0133] The server uses the victim's user ID to send a message to the messenger app's API asking, "Is there anything you need help with?". To do this, the server uses the requests library to send an HTTP POST request.

[0134] 2. Receiving a response:

[0135] When the victim replies to the message, the reply is sent to the server, which uses the Messenger app's API to retrieve the reply based on the victim's user ID, again using the requests library to send an HTTP GET request.

[0136] 3. Generative AI Analysis:

[0137] The server inputs the received responses into a generative AI model to generate information and action suggestions needed by disaster victims. The generative AI model uses natural language processing technology to analyze the responses and provide appropriate information.

[0138] 4. Collaboration with local governments and governments:

[0139] The server will share the information and suggestions generated by the generative AI model with local governments and government agencies to optimize support for disaster victims.

[0140] Hardware and Software Used

[0141] Hardware: Servers, smartphones, tablets

[0142] Software: Messenger app, generative AI model, requests library

[0143] Examples

[0144] For example, for victims in a disaster-hit area, the following prompt sentences are input into the generative AI model:

[0145] Example prompt:

[0146] A disaster has occurred. Please create a system to send a message to the victims asking "Is there anything you need help with?" and receive a reply. Please use the following information.

[0147] Victim's user ID: "12345"

[0148] Message: "Is there anything I can help you with?"

[0149] Messenger app API endpoint: "https: / / api.messagingapp.com"

[0150] By inputting this prompt sentence into the generative AI model, it is possible to propose specific implementation methods for a disaster victim support system.

[0151] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0152] Step 1:

[0153] The server obtains the victim's user ID and uses the messenger app's API to send a message saying "Is there anything I can help you with?". The input requires the victim's user ID and the message content, and the output is the success or failure status of the message transmission. In this step, the specific operation of sending an HTTP POST request using the requests library is performed.

[0154] Step 2:

[0155] The victim's device receives the message sent from the server and displays it to the user. As input, the message sent from the server is required, and as output, the message displayed to the user is obtained. In this step, the specific operation of the messenger app to display the message is performed.

[0156] Step 3:

[0157] The user replies to the message. The input requires the reply content entered by the user, and the output requires the reply content to be sent to the server via the messenger app. In this step, the specific actions of the user operating the messenger app to enter and send the reply are performed.

[0158] Step 4:

[0159] The server uses the API of the messenger app to get the reply based on the victim's user ID. The input requires the victim's user ID, and the output is the reply from the victim. In this step, the concrete operation of sending an HTTP GET request using the requests library is performed.

[0160] Step 5:

[0161] The server inputs the retrieved reply content into the generative AI model for analysis. The input requires the reply content from the victim, and the output is appropriate information provision and action suggestions as the analysis result. In this step, the generative AI model performs the specific operation of analyzing the reply content using natural language processing technology.

[0162] Step 6:

[0163] The server shares the information and suggestions generated by the generative AI model with the local government or government agency. As input, the analysis results of the generative AI model are required, and as output, the information and suggestions are obtained to be sent to the local government or government agency. In this step, the specific operation of the server to communicate with the local government or government agency is performed.

[0164] Step 7:

[0165] Local governments and government agencies optimize support for disaster victims based on the information and proposals received from the server. The input requires the information and proposals sent from the server, and the output is specific support activities for disaster victims. In this step, local governments and government agencies take concrete actions to plan and execute support activities.

[0166] Example 2

[0167] Next, a second embodiment of the second embodiment will be described. 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."

[0168] It is necessary to quickly and accurately grasp the problems and difficulties that disaster victims face and provide appropriate support. However, in conventional systems, the collection and analysis of information from victims is often done manually, making it difficult to respond quickly. In addition, the provision of information and support according to the needs of victims is not adequately optimized. This can result in delays in providing the support that victims need.

[0169] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0170] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generative AI model to provide advice and guidance to useful information and suggest actions based on the received response, a means for linking the consultation content with a public institution, a means for using natural language processing technology to analyze the message, and a means for storing the analysis results and executing necessary actions. This makes it possible to quickly and accurately collect and analyze information from the disaster victim and provide appropriate support.

[0171] "Victims" refers to people affected by a disaster.

[0172] "Means for sending a message" refers to a communications means for sending a text message to a disaster victim.

[0173] "Means of receiving a response" refers to a means of communication for receiving messages sent by disaster victims.

[0174] A "generative AI model" refers to a model that uses artificial intelligence technology to analyze messages from disaster victims and generate appropriate information and suggestions.

[0175] "Means of providing consultation, guidance to useful information, and suggested actions" refers to the use of generative AI models to provide appropriate advice and information to disaster victims.

[0176] "Public institutions" refers to public institutions such as local governments and governments.

[0177] "Natural language processing technology" refers to technology for analyzing human language and understanding its meaning.

[0178] "Means for storing the analysis results" refers to means for storing the analyzed information in a database or the like.

[0179] "Means of taking necessary actions" refers to the means of carrying out appropriate responses and support based on the analysis results.

[0180] The present invention is a system for quickly and accurately collecting and analyzing information from disaster victims, and providing appropriate support. A specific embodiment of this system will be described below.

[0181] The server has a means to send a message to the disaster victims asking, "Is there anything you need help with?". This means uses the API of a messenger app (for example, the LINE Messaging API or the Facebook Graph API). The server sends messages to the disaster victims through these APIs and receives responses.

[0182] The server has a means of receiving responses from disaster victims. The received messages are stored in a database. The server uses natural language processing technology to analyze the received messages. Specifically, it uses Google (registered trademark) Cloud Natural Language API and IBM Watson (registered trademark) Natural Language Understanding. This allows the content of the messages to be analyzed and important information to be extracted.

[0183] The server uses the generative AI model to analyze messages from disaster victims and generate appropriate information and suggestions. The generative AI model provides information and suggests actions according to the needs of the disaster victim. For example, it extracts the information "Arrived at the evacuation shelter" from the message "Arrived at the evacuation shelter" and sends a notification to the evacuation shelter manager.

[0184] The server stores the analysis results in a database and has the means to take necessary actions, such as using an email sending API (e.g., the SendGrid API) or a notification system, to respond appropriately or provide assistance based on the analysis results.

[0185] The terminal is a device that disaster victims use to send messages. This can be a smartphone, tablet, or computer. Disaster victims can use a messenger app to send messages to the official account. For example, they can send messages such as "We have arrived at the evacuation shelter" or "Food is running low."

[0186] A user (disaster victim) sends a message to the official account using a messenger app. As a concrete example, consider a case where a disaster victim sends a message to the official LINE account saying "I have arrived at the evacuation shelter." The server receives this message, analyzes it using the Google Cloud Natural Language API, and extracts the information that "I have arrived at the evacuation shelter."

[0187] Examples of prompt sentences to be input to a generative AI model include the following:

[0188] Example prompt:

[0189] "Please analyze the messages from the disaster victims and extract the necessary information. The message content is 'I have arrived at the evacuation shelter.'"

[0190] By inputting this prompt sentence into a generative AI model, the model will provide an analysis of the message, for example extracting the information "arrived at the evacuation shelter."

[0191] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0192] Step 1:

[0193] A user sends a message using a messenger app.

[0194] Specifically, a user opens a messenger app on a smartphone, tablet, or other device, types a message to the official account such as "I've arrived at the evacuation shelter" or "There is a shortage of food," and presses the send button.

[0195] Input: The message entered by the user.

[0196] Output: Messages sent through the Messenger app

[0197] Step 2:

[0198] The server receives the message.

[0199] Specifically, the server receives messages sent by users using the API of the messenger app. For example, it uses the LINE Messaging API or the Facebook Graph API to obtain message data. The server then stores the received messages in a database.

[0200] Input: Message sent from Messenger app

[0201] Output: Message data stored in the database

[0202] Step 3:

[0203] The server parses the message.

[0204] Specifically, the server uses natural language processing technology to analyze the received messages. Specifically, it uses Google Cloud Natural Language API and IBM Watson Natural Language Understanding. The server analyzes the content of the messages and extracts important information.

[0205] Input: Message data stored in the database

[0206] Output: Analyzed information (e.g. "arrived at evacuation shelter")

[0207] Step 4:

[0208] The server stores the analysis results and performs the necessary actions.

[0209] Specifically, the server saves the analysis results in a database. It then executes actions as necessary. For example, it can send a notification to the shelter manager or arrange for relief supplies. To do this, it uses an email sending API or a notification system.

[0210] Input: Parsed information

[0211] Output: Actions taken (e.g. notifications sent to shelter administrators)

[0212] (Application example 2)

[0213] Next, a description will be given of Application Example 2 of Form 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."

[0214] In the event of a disaster, it is difficult for victims to receive prompt and appropriate support. In particular, delays in collecting information from victims and responding appropriately based on that information can threaten the safety and livelihood of victims. In addition, insufficient cooperation with local governments and the national government makes it difficult to optimize support.

[0215] 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. In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for consulting using a generative AI model, guiding the victim to useful information, and proposing actions based on the received response, a means for generating an appropriate response to the message from the disaster victim using the generative AI model, and a means for coordinating the consultation content with the local government or the government. This makes it possible to quickly collect information from the disaster victim and provide appropriate support. Furthermore, by strengthening cooperation with the local government or the government, optimization of support can be achieved.

[0216] "Victims" refers to people affected by a disaster.

[0217] "Means for sending a message" refers to a communication means for sending a specific message to a disaster victim.

[0218] "Means of receiving responses" refers to the means of communication for receiving messages and information from disaster victims.

[0219] A "generative AI model" refers to a model that uses artificial intelligence to generate appropriate responses and suggestions to messages from disaster victims.

[0220] "Means of providing consultation, directing people to useful information, and suggesting actions" refers to means of providing appropriate consultation and useful information based on information from disaster victims, and suggesting specific actions.

[0221] "Means of collaboration with local governments and the government" refers to the means of sharing information about disaster victims and the details of their concerns with local governments and government agencies, and working together to provide support.

[0222] "Means for generating an appropriate response" refers to means for automatically generating an appropriate response to a message from a disaster victim using a generative AI model.

[0223] A system for implementing this invention includes means for sending a message to disaster victims asking "Is there anything you need help with?", means for receiving responses from disaster victims, means for using a generative AI model to provide advice and guide users to useful information and suggest actions based on the received answers, means for generating appropriate responses to messages from disaster victims using the generative AI model, and means for coordinating the content of the consultation with local governments and the government.

[0224] Hardware and Software Used

[0225] Hardware: Smartphones, servers

[0226] Software: Messenger apps (e.g. LINE, WhatsApp), OpenAI (registered trademark) API

[0227] Data processing and calculation

[0228] 1. Sending a message: The server uses the messenger app's API to send a message to the victim asking, "Is there anything you need help with?"

[0229] 2. Receiving response: The server receives the response sent by the victim through the messenger app.

[0230] 3. Response generation using a generative AI model: The server inputs the received answer into a generative AI model (e.g., OpenAI GPT-3 (registered trademark)) to generate an appropriate response.

[0231] 4. Providing a response: The server provides the generated response to the victim.

[0232] 5. Collaboration with local governments and the government: The server will share information and inquiries from disaster victims with local governments and government agencies, and work together to provide support.

[0233] Examples

[0234] If the server receives a message from a victim saying, "Your house is flooded and you need to evacuate," it will use the generative AI model to generate a response such as, "Please evacuate to a nearby evacuation shelter. Please let us know if you need any assistance," and provide this to the victim.

[0235] Examples of prompt statements

[0236] Message from the victim: My house is flooded and I need to evacuate

[0237] Generate an appropriate response.

[0238] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0239] Step 1:

[0240] The server uses the messenger app's API to send a message to the victim asking, "Is there anything you need help with?"

[0241] Input: Victim's contact information

[0242] Output: Message sent to victim

[0243] Specific operation: The server sends an HTTP request to the API endpoint of the messenger app to send a message to the victim.

[0244] Step 2:

[0245] The user (victim) sends the response via a messenger app.

[0246] Input: Victim's response message

[0247] Output: Reply message sent to messenger app

[0248] What happens: A victim uses a messenger app to type a text message and presses send.

[0249] Step 3:

[0250] The server receives the responses from the victims.

[0251] Input: Message sent by victim

[0252] Output: Message data of victims stored on the server

[0253] Specific operation: The server stores messages received through the messenger app's API in a database.

[0254] Step 4:

[0255] The server inputs the received answers into a generative AI model to generate an appropriate response.

[0256] Input: Message data from victims

[0257] Output: The generated response message

[0258] Specific operation: The server sends an API request to a generative AI model (e.g., OpenAI GPT-3) and generates an appropriate response using the prompt sentence as input.

[0259] Step 5:

[0260] The server provides the generated response to the victim.

[0261] Input: The generated response message

[0262] Output: Response message sent to victim

[0263] Specific operation: The server generates a response message using the messenger app's API and sends it to the victim.

[0264] Step 6:

[0265] The server will share information and consultation details from disaster victims with local governments and government agencies.

[0266] Input: victim's message data and generated response message

[0267] Output: Information sent to local government or government agencies

[0268] Specific operation: The server sends an HTTP request to the API endpoint of a local government or government agency to share information about disaster victims.

[0269] Example 3

[0270] Next, a third embodiment of the third embodiment will be described. 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."

[0271] There is a problem in that it is difficult to provide disaster victims with the information they need quickly and accurately. It is also difficult to effectively communicate with local governments and the government on the content of inquiries from disaster victims and optimize support.

[0272] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for extracting keywords based on the received response using natural language processing technology, a means for generating appropriate information using a generative AI model based on the extracted keywords, a means for providing the generated information to the disaster victim, and a means for coordinating the consultation content with a local government or the government. This makes it possible to quickly and accurately provide the information required by the disaster victim and optimize support through cooperation with the local government or the government.

[0273] "Disaster Victim" refers to an individual or group affected by a disaster.

[0274] "Means for sending a message" refers to a communication means for sending information to disaster victims in the form of text, voice, or the like.

[0275] "Means of receiving a response" refers to the means of communication for receiving responses or feedback from affected people.

[0276] "Natural language processing technology" refers to technology that enables computers to understand, analyze, and generate human language.

[0277] "Keyword extraction means" refers to techniques for identifying and extracting important words and phrases from received text data.

[0278] A "generative AI model" refers to a model that uses artificial intelligence to generate appropriate responses or information based on input data.

[0279] "Means for generating information" refers to technology for using a generative AI model to create appropriate information based on extracted keywords.

[0280] "Means for providing information" refers to communication means for conveying the generated information to disaster victims.

[0281] "Means of collaboration with local governments and the government" refers to means for sharing information from disaster victims with local governments and government agencies and working together to carry out relief activities.

[0282] This invention is a system that quickly and accurately provides disaster victims with the information they need in the event of a disaster, and optimizes support through cooperation with local governments and the government. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0283] Hardware and Software Used

[0284] Server: Use a server with high-performance computing power. The server plays a central role in receiving, analyzing, generating, and transmitting data.

[0285] Terminal: A device used by a user, such as a smartphone, tablet, or computer. The terminal sends messages from the user and receives information from the server.

[0286] Natural language processing technology: Uses Python libraries NLTK and spaCy to extract keywords from messages.

[0287] Generative AI models: Generative AI models such as OpenAI's GPT-4 (registered trademark) are used to generate appropriate information based on the extracted keywords.

[0288] Program Processing

[0289] 1. Receiving a message from a user

[0290] A user uses a terminal to send a message. For example, the user types, "Please tell me where the evacuation shelter is" and presses the send button.

[0291] The terminal sends a message to the server.

[0292] 2. Extracting keywords from messages

[0293] The server analyzes the received messages using natural language processing techniques, specifically using Python's NLTK and spaCy to extract important keywords from the messages.

[0294] For example, from the message "Please tell me where the evacuation shelter is," the keywords "evacuation shelter" and "location" are extracted.

[0295] 3. Producing the right information

[0296] The server uses a generative AI model to generate appropriate information based on the extracted keywords. A prompt sentence is input to the generative AI model to generate a response.

[0297] For example, a prompt sentence such as "Please tell me where the evacuation shelter is" can be input into a generative AI model, and the model can generate the information, "The nearest evacuation shelter is next to City Hall. The address is XX."

[0298] 4. Provision of generated information

[0299] The server transmits the generated information to the terminal, which then displays the received information to the user.

[0300] For example, the user's screen might display, "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[0301] 5. Data aggregation and sharing

[0302] The server stores messages from users in a database. Periodically, the server aggregates the stored data and provides it to local governments and governments.

[0303] Use a secure internet connection (e.g., HTTPS) for data sharing.

[0304] Examples

[0305] User message: "Where are the evacuation shelters?"

[0306] Keyword extraction: "shelter", "place"

[0307] Prompt for generative AI model: "When asked where the evacuation shelters are located, please provide the appropriate evacuation shelter information."

[0308] Generated information: "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[0309] This system is a powerful tool for providing support to disaster victims quickly and accurately. By combining natural language processing technology and generative AI models, it is possible to provide information and optimize support according to the needs of users. The flow of the identification process in the third embodiment will be described with reference to FIG. 15.

[0310] Step 1:

[0311] Receiving messages from users

[0312] Input: A user uses a device to type a message and presses the send button. For example, "Please tell me where the evacuation shelters are."

[0313] Specific operation: The terminal sends the user's message to the server as an HTTP request.

[0314] Output: The server stores the received message in a database and passes it on to the next processing step.

[0315] Step 2:

[0316] Extracting keywords from messages

[0317] Input: The user's message received by the server. For example, "Please tell me where the evacuation shelter is."

[0318] What it does: The server uses natural language processing libraries such as Python's NLTK or spaCy to extract important keywords from messages.

[0319] Data processing: Tokenize messages, tag parts of speech, and extract key keywords.

[0320] Output: Extracted keywords, e.g. "shelter", "location".

[0321] Step 3:

[0322] Producing the right information

[0323] Input: Extracted keywords, e.g. "shelter", "location".

[0324] Specific operation: The server creates and inputs a prompt sentence to the generative AI model (e.g., GPT-4).

[0325] Data calculation: The generative AI model generates appropriate information based on the prompt.

[0326] Output: The generated information. For example, "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[0327] Step 4:

[0328] Providing generated information

[0329] Input: Generated information. For example, "The nearest evacuation shelter is next to ____ City Hall. The address is ____."

[0330] Specific operation: The server sends the generated information to the terminal as an HTTP response.

[0331] Output: The device displays the received information to the user. For example, the user's screen might display "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[0332] Step 5:

[0333] Data aggregation and sharing

[0334] Input: Message from user and generated information.

[0335] What happens: The server stores this data in a database and aggregates it periodically.

[0336] Data processing: Collecting and analyzing stored data.

[0337] Output: Provide aggregated data to local governments and / or governments using a secure internet connection (e.g. HTTPS) to share data.

[0338] (Application example 3)

[0339] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0340] There is a problem that it is difficult for disaster victims to quickly obtain appropriate information in an emergency. In addition, there is a problem that support for disaster victims is not optimized due to insufficient cooperation with local governments and the government. Furthermore, there is a lack of means to efficiently process messages from disaster victims and propose appropriate actions.

[0341] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0342] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice and guidance to useful information and suggest actions based on the received answer, a means for coordinating the consultation content with a local government or the government, a means for extracting keywords from the message from the disaster victim using natural language processing technology, a means for providing appropriate information based on the extracted keywords, and a means for sharing the message from the disaster victim with the local government or the government. This enables the disaster victim to quickly obtain appropriate information, strengthens cooperation with the local government or the government, and optimizes support for the disaster victim.

[0343] "Disaster Victim" refers to an individual or group of people affected by a disaster or emergency.

[0344] "Message" refers to text data sent to disaster victims to ask questions or provide information.

[0345] "Response" refers to a reply or response to a message sent by a disaster victim.

[0346] "Generative AI" refers to a system that uses artificial intelligence technology to provide information and suggest actions based on the data it receives.

[0347] "Consultation" refers to the act of providing advice and solutions to problems and questions that disaster victims have.

[0348] "Useful information" refers to information that is important and useful to disaster victims.

[0349] "Suggested actions" refers to advice that provides specific actions that survivors should take.

[0350] "Local government" refers to local public entities, specifically including cities, towns, villages, and prefectures.

[0351] "Government" refers to the administrative organs of a nation, including central and local governments.

[0352] "Collaboration" refers to different organizations and agencies working together to share information and respond jointly.

[0353] "Natural language processing technology" refers to technology that enables computers to understand and process human language.

[0354] "Keywords" refer to important words or phrases extracted from a message.

[0355] "Means of providing information" refers to the method of conveying appropriate information to disaster victims based on the extracted keywords.

[0356] "Means of sharing data" refers to the methods of conveying messages from disaster victims to local governments and the government.

[0357] The system for implementing this invention has the function of sending a message to disaster victims asking "Is there anything you are struggling with?" and receiving responses from them. Based on the responses received, a generative AI model is used to provide advice, guide users to useful information, and suggest actions. It also has the function of sharing the details of consultations with local governments and the national government.

[0358] Hardware and Software Used

[0359] Hardware: Smartphones, servers

[0360] Software: Python, spaCy, Transformers library

[0361] Data processing and calculation

[0362] 1. Message transmission: The server sends a message to the disaster victim asking, "Is there anything you need help with?" This message is sent as text data.

[0363] 2. Response reception: The server receives the responses from the victims. The received responses are stored as text data.

[0364] 3. Keyword extraction: The server uses natural language processing technology (spaCy) to extract keywords from messages from disaster victims. The extracted keywords are compiled into a list of important words and phrases.

[0365] 4. Information provision: Based on the extracted keywords, the server uses a generative AI model (Transformers library) to provide appropriate information, such as the location of evacuation shelters and emergency contact information.

[0366] 5. Data sharing: The server shares messages from disaster victims with local governments and the government. This sharing is done via the Internet.

[0367] Examples

[0368] For example, if a disaster victim sends a message saying, "My house is flooded and I need to evacuate. Where should I go?", the server receives this message and uses natural language processing technology to extract the keywords "flooded," "evacuation," and "where should I go." It then uses a generative AI model to provide the location of the evacuation shelter. This message is also shared with local governments and the government, enabling them to provide rapid assistance.

[0369] Examples of prompt statements

[0370] Please receive messages from disaster victims, extract keywords, and provide appropriate information. Also, please tell us how to share the messages with local governments and the government.

[0371] In this way, a specific embodiment for carrying out the invention has been shown, which enables disaster victims to quickly obtain appropriate information, strengthens cooperation with local governments and the government, and optimizes support for disaster victims.

[0372] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0373] Step 1:

[0374] The server sends a message to the victim asking, "Is there anything you need help with?"

[0375] Input: Victim's contact information

[0376] Output: The message sent.

[0377] Specific operation: The server retrieves the victim's contact information from a database and generates and sends a text message.

[0378] Step 2:

[0379] The user (victim) sends a reply to the message from the server.

[0380] Input: Message from the server

[0381] Output: Reply message from the victim

[0382] Specific operations: The victim enters a response via text message using a device such as a smartphone and sends it to the server.

[0383] Step 3:

[0384] The server receives the responses from the victims.

[0385] Input: Response message from the victim

[0386] Output: Received response message

[0387] Specific operation: The server receives messages from disaster victims via the network and stores them in a database.

[0388] Step 4:

[0389] The server uses natural language processing technology to extract keywords from messages from disaster victims.

[0390] Input: Received response message

[0391] Output: Extracted keywords

[0392] What it does: The server uses the spaCy library to parse the message and extract important words and phrases.

[0393] Step 5:

[0394] The server provides appropriate information based on the extracted keywords.

[0395] Input: Extracted keywords

[0396] Output: Information provided

[0397] Specific operation: The server runs a generative AI model using the Transformers library to generate information related to keywords and send it to the victim.

[0398] Step 6:

[0399] The server shares messages from disaster victims with local governments and the government.

[0400] Input: Received response message

[0401] Output: Message shared with local governments

[0402] Specific operation: The server sends messages via the Internet to local government and government systems for sharing.

[0403] In this manner, the specific operations performed at each processing step and their inputs and outputs have been described.

[0404] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0405] "Example 1"

[0406] In one embodiment of the present invention, the emotion engine recognizes emotions based on the response from the victim. Specifically, the emotion engine analyzes text information included in the response message from the victim and estimates the emotional state of the victim from the text information. For example, if the response message contains words such as "scary" or "anxiety," it is determined that the victim is feeling fear or anxiety.

[0407] "Example 2"

[0408] In another embodiment of the present invention, the emotion engine adjusts the consultation content and the method of providing useful information according to the emotion of the victim. Specifically, when it is determined that the victim is feeling fear or anxiety, the emotion engine adjusts the consultation content and the method of providing useful information to the victim based on the emotional state. For example, when it is determined that the victim is feeling anxiety, information that provides a sense of security is provided preferentially.

[0409] "Example 3"

[0410] In yet another embodiment of the present invention, the emotion engine adjusts the report content to the local government or government according to the emotions of the victims. Specifically, the emotion engine reports the information to the local government or government based on the emotional state of the victims. For example, if responses indicating fear or anxiety are obtained from many victims, the information is reported to the local government or government and used as reference information for optimizing support measures for the victims.

[0411] The process flow of each embodiment will be described below.

[0412] "Example 1"

[0413] Step 1: Receive a response message from the victim.

[0414] Step 2: Analyze the text information contained in the received message.

[0415] Step 3: Estimate the emotional state of the victim from the text information.

[0416] "Example 2"

[0417] Step 1: Determine the victim's emotional state.

[0418] Step 2: Adjust the content of your consultation and the way you provide useful information based on the person's emotional state.

[0419] Step 3: Provide the adjusted information to the victims.

[0420] "Example 3"

[0421] Step 1: Determine the victim's emotional state.

[0422] Step 2: Tailor your reporting based on your emotional state.

[0423] Step 3: Report the adjusted information to the local government or government.

[0424] Example 1

[0425] Next, a description will be given of Example 1 of the embodiment 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".

[0426] It is necessary to quickly grasp the anxiety and fear that disaster victims feel in the event of a disaster and provide appropriate support. However, conventional systems have difficulty accurately recognizing the emotional state of victims, making it difficult to provide appropriate support. In addition, there was a lack of means to effectively utilize information from disaster victims in cooperation with local governments and the national government.

[0427] 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.

[0428] In this invention, the server includes a means for sending a message to the disaster victim asking "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for performing emotion analysis based on the received response, a means for using a generative AI to provide advice or guide the victim to useful information and suggest actions based on the results of the emotion analysis, and a means for coordinating the consultation content with local governments and the government. This makes it possible to quickly and accurately grasp the emotional state of the disaster victim and provide appropriate support. In addition, the information from the disaster victim can be effectively utilized to strengthen cooperation with local governments and the government.

[0429] "Disaster Victim" refers to an individual or group affected by a disaster.

[0430] "Means for sending a message" refers to a communication means for sending a specific message to a disaster victim.

[0431] "Means of receiving a response" refers to the means of communication for receiving replies or responses from disaster victims.

[0432] "Means for performing emotion analysis" refers to technology for analyzing the text information contained in responses from disaster victims and inferring their emotional state.

[0433] "Generative AI" refers to a system that uses artificial intelligence technology to provide appropriate information and suggest actions based on the responses of disaster victims.

[0434] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to technology that provides appropriate consultation, information, and action suggestions to disaster victims based on the results of emotion analysis.

[0435] "Means of collaborating with local governments and the government" refers to technology for sharing information obtained from disaster victims with local governments and government agencies and working together to carry out relief activities.

[0436] This invention is a system that sends a message to a disaster victim asking "Is there anything that's troubling you?", analyzes the response, recognizes the emotion, and provides appropriate support. A specific embodiment of this system will be described below. The server may include an emotion engine that recognizes the emotion of the disaster victim based on the response from the disaster victim to the message asking "Is there anything that's troubling you?".

[0437] System Configuration

[0438] Sending a message

[0439] The server sends a message to the disaster victim through the official account of the messenger app, asking "Is there anything you need help with?". This message is sent using a messenger app such as LINE or Facebook Messenger. The server uses the API of these applications to send the message.

[0440] Response received

[0441] The user uses the messenger app to reply to the message from the server. For example, the user replies, "My house is broken into and I'm scared." The device transmits the user's reply to the server.

[0442] Emotion analysis

[0443] When the server receives the user's answer, it sends the answer to the emotion engine. The emotion engine uses natural language processing tools such as IBM Watson or Google Cloud Natural Language API. The emotion engine analyzes the text information included in the answer message and estimates the emotion, such as "fear" or "anxiety."

[0444] Save and notify results

[0445] The server stores the results of emotion analysis obtained from the emotion engine in a database. If necessary, the server notifies the relevant parties of the analysis results. For example, it sends an email using the SMTP protocol to notify the disaster relief team.

[0446] Examples

[0447] scenario:

[0448] The user receives a message from the official LINE account asking, "Is there anything you're struggling with?" The user replies, "My house is broken into and I'm scared."

[0449] Process flow:

[0450] 1. The server sends a message to the user via the LINE official account.

[0451] 2. The user responds, "My house is broken into and I'm scared."

[0452] 3. The server receives the user's answer and sends it to the emotion engine.

[0453] 4. The emotion engine analyzes the reply message and determines that the user is feeling scared based on the word "scary."

[0454] 5. The server stores the results of the emotion analysis in a database and notifies the victim support team via email.

[0455] Example prompts for generative AI models

[0456] "A user receives a message from the LINE official account asking, 'Is there anything troubling you?' and responds, 'My house is broken and I'm scared.' Please infer the user's emotions from this response."

[0457] In this way, a specific embodiment of the system will be described while clarifying the roles of the server, the terminal, and the user.

[0458] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0459] Step 1:

[0460] The server sends a message to the disaster victim asking "Is there anything you need help with?" through the official account of the messenger app. Specifically, the server uses the LINE API or Facebook Messenger API to send an HTTP request and deliver the message. The input is the contact information of the disaster victim, and the output is the message sent.

[0461] Step 2:

[0462] The user uses a messenger app to reply to the message from the server. For example, the user replies, "My house is broken into and I'm scared." The device sends the user's input to the server through the LINE API. The input is the user's reply message, and the output is the reply data sent to the server.

[0463] Step 3:

[0464] When the server receives the user's answer, it sends the answer to the emotion engine. Specifically, the server sends an HTTP request to the Google Cloud Natural Language API to request text analysis. The input is the user's answer message, and the output is the result of the emotion analysis.

[0465] Step 4:

[0466] The emotion engine analyzes the reply message and estimates emotions such as "fear" or "anxiety." Specifically, it uses natural language processing technology to extract emotional expressions in the text and estimate the emotional state. The input is the user's reply message, and the output is the estimated emotional state.

[0467] Step 5:

[0468] The server stores the emotion analysis results obtained from the emotion engine in a database. Specifically, the server uses a SQL query to insert the analysis results into the database. The input is the emotion analysis result, and the output is the data stored in the database.

[0469] Step 6:

[0470] The server notifies the relevant parties of the analysis results as necessary. For example, to notify the disaster victim support team, it sends an email using the SMTP protocol. The input is the result of the sentiment analysis and the notification destination information, and the output is the sent notification email.

[0471] (Application example 1)

[0472] Next, a description will be given of Application Example 1 of Form 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."

[0473] In the event of a disaster, it is necessary to quickly and accurately grasp the emotions such as fear and anxiety felt by disaster victims and provide appropriate support information. However, conventional systems have difficulty accurately recognizing the emotional state of disaster victims, which can lead to delays in providing appropriate support. In addition, there has been a lack of consultation and information provision by generative AI based on responses from disaster victims, which has led to issues with providing support that meets the needs of disaster victims.

[0474] 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.

[0475] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice or guide users to useful information and suggest actions based on the received response, a means for coordinating the consultation content with a local government or the government, a means for analyzing the response message from the disaster victim and recognizing the emotional state, and a means for providing appropriate support information based on the recognized emotional state. This makes it possible to quickly and accurately grasp the emotional state of the disaster victim and provide appropriate support information.

[0476] "Victims" refers to people affected by a disaster.

[0477] "Means for sending a message" refers to a communications means for sending a text message to a disaster victim.

[0478] "Means of receiving a response" refers to the means of communication for receiving a reply message from the disaster victim.

[0479] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate consultation and information.

[0480] "Means of consultation, guidance to useful information, and suggested actions" refers to means of providing appropriate advice and information based on the responses of disaster victims and suggesting actions.

[0481] "Means of collaboration with local governments and the government" refers to the means of sharing the consultation details of disaster victims with local governments and government agencies and working together to provide support.

[0482] "Means for recognizing emotional states" refers to means for analyzing response messages from disaster victims and recognizing the emotions contained therein.

[0483] The "means for providing appropriate support information" refers to a means for providing necessary support information to a disaster victim based on the recognized emotional state.

[0484] A system for carrying out this invention includes a communication means for sending a message to a disaster victim asking "Is there anything you need help with?" and receiving a response from the disaster victim. Specifically, a messenger app installed on a terminal such as a smartphone or tablet is used. A server receives the response message from the disaster victim and analyzes the response using a generative AI model.

[0485] The generative AI model analyzes the text information contained in the victim's response message and recognizes the emotions contained therein. For example, if the message contains words such as "scared" or "anxious," it determines that the victim is feeling fear or anxiety. TextBlob or other natural language processing libraries can be used as the emotion engine.

[0486] The server provides appropriate support information based on the recognized emotional state. For example, if a victim answers, "I'm scared. What should I do?", the server recognizes that the victim is "feeling scared and anxious" and provides appropriate support information. Support information is provided in cooperation with local governments and the national government.

[0487] As a concrete example, the following prompt sentence can be input to a generative AI model to perform sentiment analysis:

[0488] Analyze the response messages from the victims and recognize their emotional state. For example, if the messages contain words such as "scared" or "anxious," determine that the victim is feeling fear or anxiety.

[0489] Response message: "I'm scared. What should I do?"

[0490] This system makes it possible to quickly and accurately grasp the emotional state of disaster victims and provide appropriate support information. It is expected that this will lead to faster support that meets the needs of disaster victims and more effective support activities during disasters.

[0491] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0492] Step 1:

[0493] The server sends a message to the victim asking, "Is there anything you need help with?"

[0494] Input: Victim's contact information

[0495] Output: Message sent to victim's device

[0496] What it does: The server uses the messenger app's API to send messages based on the victim's contact information.

[0497] Step 2:

[0498] The victim inputs a response to the received message and sends it.

[0499] Input: Victim's response message

[0500] Output: The response message sent to the server.

[0501] Specific operations: Victims use a device such as a smartphone or tablet to enter and send responses via a messenger app.

[0502] Step 3:

[0503] The server receives the reply messages from the victims.

[0504] Input: Victim's response message

[0505] Output: The answer message stored on the server

[0506] Specific operation: The server uses the messenger app's API to receive response messages from victims and store them in a database.

[0507] Step 4:

[0508] The server uses a generative AI model to analyze the reply message and recognize the emotional state.

[0509] Input: Victim's response message

[0510] Output: Perceived emotional state

[0511] How it works: The server uses a natural language processing library such as TextBlob to analyze the reply message and recognize the emotional state of the message. For example, it detects keywords such as "scared" and "anxious."

[0512] Step 5:

[0513] The server generates appropriate assistance information based on the recognized emotional state.

[0514] Input: Perceived emotional state

[0515] Output: Appropriate supporting information

[0516] How it works: The server uses the generative AI model to generate support information appropriate for the victim based on their recognized emotional state. For example, if they are feeling scared or anxious, it provides reassuring information and action guidelines.

[0517] Step 6:

[0518] The server transmits the generated support information to the disaster victims.

[0519] Input: Generated support information

[0520] Output: Support information sent to the victim's device

[0521] Specific operation: The server uses the messenger app's API to send the generated support information to the victim's device.

[0522] Step 7:

[0523] The server will share the consultation details in order to collaborate with local governments and the government.

[0524] Input: victim's counseling content and perceived emotional state

[0525] Output: Information shared with local governments and governments

[0526] Specific operation: The server transmits the details of the victim's consultation and their recognized emotional state to local government and government systems to coordinate with them.

[0527] Example 2

[0528] Next, a second embodiment of the second embodiment will be described. 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."

[0529] There is a need to reduce the fear and anxiety that disaster victims feel during disasters and provide them with appropriate information quickly. However, conventional systems have difficulty providing information that takes into account the emotions of disaster victims, and there are cases where the information that disaster victims need cannot be provided appropriately. In addition, there is a problem that cooperation with local governments and the national government is insufficient, and support for disaster victims is not optimized.

[0530] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0531] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are struggling with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice or guide users to useful information and suggest actions based on the received answer, a means for coordinating the consultation content with a local government or the government, a means for sending a message from the disaster victim to an emotion analysis engine and identifying emotions, a means for selecting information to be provided according to the identified emotions, and a means for returning the selected information to the disaster victim. This makes it possible to provide appropriate information that takes into account the emotions of the disaster victim, and to optimize support for the disaster victim through collaboration with the local government or the government.

[0532] "Disaster Victim" refers to an individual or group affected by a disaster.

[0533] "Means for sending a message" refers to a communication means for sending a message, such as text or voice, to a disaster victim.

[0534] "Means of receiving a response" refers to the means of communication for receiving replies or responses from disaster victims.

[0535] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate consultation and information.

[0536] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to the means by which the generative AI provides appropriate consultation content and useful information based on the victims' responses, and suggests specific actions.

[0537] "Means of collaboration with local governments and the government" refers to the means of sharing information about disaster victims and the details of their concerns with local governments and government agencies, and working together to carry out support activities.

[0538] An "emotion analysis engine" refers to a system that analyzes messages from disaster victims and identifies their emotions from their content.

[0539] "Means for identifying emotions" refers to means for identifying emotions of a disaster victim using an emotion analysis engine.

[0540] "Means for selecting information to provide" refers to means for selecting appropriate information to provide to disaster victims according to the identified emotions.

[0541] "Means of returning information" refers to the means of communication for returning selected information to the disaster victims.

[0542] The present invention is a system that receives messages from disaster victims, analyzes their emotions, and provides appropriate information. A specific embodiment of this system is described below.

[0543] System Configuration

[0544] The server receives messages from disaster victims using communication means such as a messenger app, an internet search tool, etc. For example, messages from disaster victims can be received using an official account of a messenger app.

[0545] The server then sends the received messages to a sentiment analysis engine, which uses natural language processing technology to analyze the content of the messages and identify the emotions of the victims. For example, the Google Cloud Natural Language API can be used to detect emotions such as "fear" and "anxiety" from the messages of the victims.

[0546] After the emotion analysis engine identifies the emotion, the server selects the information to provide according to that emotion. For example, if it determines that the victim is feeling "anxiety," the server will prioritize information that provides a sense of security, such as "how to act safely in the event of an earthquake" and "information on evacuation sites." The server extracts appropriate information from a database of information prepared in advance.

[0547] Finally, the server sends the selected information back to the victim via the messenger app. For example, it sends specific advice such as, "If an earthquake occurs, first ensure your safety and move to a shelter. Information on evacuation shelters is available here." The server uses the API of the messenger app to send the reply message.

[0548] Examples

[0549] As a concrete example, consider the case where a disaster victim sends a message via a messenger app saying, "I'm scared of earthquakes. What should I do?" The server that receives this message sends it to an emotion analysis engine, which detects "fear." Based on the results, the server prioritizes sending information that provides a sense of security to the disaster victim, such as "how to act safely in the event of an earthquake" and "information on evacuation sites."

[0550] Examples of prompt statements

[0551] Examples of prompts to be input to a generative AI model include:

[0552] "Analyze messages from disaster victims and identify their emotions. Then suggest ways to provide appropriate information based on those emotions. For example, if a disaster victim sends a message saying, 'I'm scared of the earthquake. What should I do?', show them what information they should provide."

[0553] In this way, it will be possible to provide appropriate information that takes into account the feelings of disaster victims, and support for disaster victims can be optimized through collaboration with local governments and the national government.

[0554] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0555] Step 1:

[0556] The server uses the messenger app's API to receive messages from disaster victims in real time.

[0557] Input: Message from the victim (e.g. "I'm scared of the earthquake. What should I do?")

[0558] Output: Received message data

[0559] Specific operation: The server receives messages sent by disaster victims through the official account of the messenger app. The received messages are stored on the server in text format.

[0560] Step 2:

[0561] The server sends the received message to a sentiment analysis engine.

[0562] Input: Received message data

[0563] Output: Emotion identification by the emotion analysis engine (e.g. "fear")

[0564] How it works: The server uses a sentiment analysis engine, such as the Google Cloud Natural Language API, to analyze the content of the received message. The sentiment analysis engine uses natural language processing techniques to identify the sentiment of the message and returns the results to the server.

[0565] Step 3:

[0566] The server selects information to provide to disaster victims based on the emotional information obtained from the emotion analysis engine.

[0567] Input: Emotion identification result (e.g. "fear")

[0568] Output: Selected information (e.g. "How to act safely in the event of an earthquake")

[0569] Specific operation: The server extracts appropriate information from a pre-prepared information database based on the emotion identification results returned by the emotion analysis engine. For example, if the victim is feeling "fear," the server selects information that provides a sense of security, such as "how to act safely in the event of an earthquake" and "information on evacuation sites."

[0570] Step 4:

[0571] The server then sends the selected information back to the victim via a messenger app.

[0572] Input: Selected information (e.g. "How to act safely in the event of an earthquake")

[0573] Output: Reply message to the victim

[0574] Specific operation: The server uses the API of the messenger app to send the selected information back to the victim. For example, it sends specific advice such as, "If an earthquake occurs, first ensure your safety and move to a shelter. Information on evacuation shelters is available here."

[0575] (Application example 2)

[0576] Next, a description will be given of Application Example 2 of Form 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."

[0577] Conventional victim support systems provide uniform information without considering the emotional state of the victim, which means that the anxiety and fear felt by the victim cannot be fully alleviated. In addition, there is a lack of means to provide appropriate support information according to the victim's emotions, making it difficult to alleviate the psychological burden on the victim.

[0578] 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.

[0579] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are struggling with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice and guidance to useful information and suggest actions based on the received answer, a means for coordinating the consultation content with a local government or the government, a means for analyzing the emotional state of the disaster victim using an emotion engine and adjusting the method of providing information according to the emotion, and a means for preferentially providing information that provides a sense of security based on the emotional state of the disaster victim. This makes it possible to provide appropriate information according to the emotional state of the disaster victim, thereby reducing the anxiety and fear of the disaster victim and reducing the psychological burden. The server includes: a means for sending a message to the disaster victim saying "Is there anything that bothers you?" by inputting a specific prompt sentence into a generative AI model; an emotion engine for recognizing the emotion of the disaster victim based on the response from the disaster victim to the message; a suggestion means for providing the disaster victim with information that will be useful to the disaster victim and a suggestion of actions that the disaster victim should take based on the recognized emotion using the generative AI model; a means for adjusting the content of a report to the local government and the government based on the emotion; and a means for transmitting the report to the local government and the government via the Internet. When the suggestion means determines that the disaster victim feels anxious based on the recognized emotion, the suggestion means provides the disaster victim with a safe way to act in the event of an earthquake and information on evacuation sites as information that will be useful to the disaster victim. The suggestion means provides information that provides the disaster victim with a sense of security based on the recognized emotion.

[0580] "Disaster Victim" refers to an individual or group affected by a natural or man-made disaster.

[0581] "Means for sending a message" refers to a communication means for sending information to disaster victims in the form of text, voice, or the like.

[0582] "Means of receiving a response" refers to the means of communication for receiving responses or feedback from affected people.

[0583] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate consultation and information.

[0584] "Means of providing consultation, directing people to useful information, and suggesting actions" refers to means of providing appropriate advice and information based on the situation of disaster victims and suggesting specific actions to take.

[0585] "Means of cooperation with local governments and the government" refers to means for sharing information and cooperating with local governments and government agencies to provide support to disaster victims.

[0586] An "emotion engine" refers to technology that analyzes the emotional state of disaster victims and adjusts the way information is provided based on the results.

[0587] "Emotional state" refers to the psychological state, such as anxiety, fear, or relief, felt by the disaster victim.

[0588] "Measures to adjust the method of providing information" refers to measures for changing the content and format of the information provided depending on the emotional state of the disaster victims.

[0589] "Information that provides a sense of security" refers to information that reduces the anxiety and fear of disaster victims and gives them a sense of security.

[0590] The system for implementing this invention is realized by installing a disaster victim support application on a smartphone. This application receives messages from disaster victims, analyzes the messages using an emotion engine, and provides appropriate information according to the emotional state of the disaster victim.

[0591] The server has a means to send a message to the disaster victims asking "Is there anything you need help with?" This means uses a Messenger API to send a text message. The server also uses a Messenger API to receive responses from the disaster victims, and receives messages sent by the disaster victims.

[0592] Incoming messages are analyzed using an emotion engine, which uses the TextBlob library to analyze the emotional state of the message and classify it as positive, negative, or neutral. Based on this emotional state, a generative AI provides appropriate information.

[0593] For example, if a disaster victim sends a message saying, "I'm so scared. Please help me," the emotion engine will analyze this message as a negative emotion. Based on this negative emotion, the generative AI will prioritize providing information like, "Don't worry. Help is on the way soon."

[0594] This system will also work with local governments and the government to share information on the emotional state of disaster victims and the support they need, optimizing support for disaster victims. This will reduce the anxiety and fear of disaster victims and ease their psychological burden.

[0595] As an illustration, consider the following prompt:

[0596] Message from survivor: "I'm so scared. Please help."

[0597] Sentiment analysis result: Negative

[0598] Provide information: "Don't worry, help is on the way."

[0599] In this way, it is possible to provide appropriate information according to the emotional state of the victim, thereby reducing the victim's anxiety and fear.

[0600] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0601] Step 1:

[0602] The server sends a message to the victim asking, "Is there anything you need help with?" The victim's contact information is required as input, and the message is displayed on the victim's smartphone as output. The specific operation is to send a text message using a messenger API.

[0603] Step 2:

[0604] The user (victim) sends a response to the message sent from the server. The input is the victim's text message, and the output is the response being sent to the server. The specific operation is that the victim enters a text message using a messenger app on their smartphone and presses the send button.

[0605] Step 3:

[0606] The server receives responses from the victims. The input requires a text message sent by the victim, and the output is that the received message is stored on the server. Specifically, the server receives messages using a messenger API and stores them in a database.

[0607] Step 4:

[0608] The server analyzes the received messages with an emotion engine. As input, it requires the text messages of the victims, and as output, it obtains their emotional state (positive, negative, neutral). Specifically, it uses the TextBlob library to analyze the emotions of the messages and classify the emotional state.

[0609] Step 5:

[0610] The server uses a generative AI to generate appropriate information based on the emotional state. The inputs required are the emotional state and the victim's text message, and the output is information to be provided to the victim. The specific operation is to use a generative AI model to generate information according to the emotional state.

[0611] Step 6:

[0612] The server provides the generated information to the disaster victims. The generated information is required as input, and the information is displayed on the disaster victim's smartphone as output. The specific operation is to send the generated information as a text message using a messenger API.

[0613] Step 7:

[0614] The server shares the emotional state of the victims and the necessary support information with the local government or government. The inputs are the emotional state of the victims and the support information, and the output is to send the information to the local government or government. The specific operation is to send the information to the local government or government system using API.

[0615] Step 8:

[0616] Local governments and governments optimize support for disaster victims based on the received information. The inputs are the emotional state and support information sent from the server, and the output is the creation of an optimized support plan. The specific operation is to analyze the received information and create a support plan.

[0617] Example 3

[0618] Next, a third embodiment of the third embodiment will be described. 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."

[0619] There is a need to provide prompt and appropriate support for the problems that disaster victims face during disasters. However, conventional systems have the challenge of being unable to accurately grasp the specific needs and emotional state of disaster victims and provide appropriate information and support based on that. In addition, there is insufficient cooperation with local governments and the national government, making it difficult to optimize support.

[0620] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0621] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for analyzing the message based on the received response using natural language processing technology, a means for extracting keywords from the analysis result, a means for providing appropriate information based on the extracted keywords, a means for analyzing the emotional state of the disaster victim using emotion analysis technology, a means for reporting to the local government or the government based on the result of the emotion analysis, and a means for coordinating with the local government or the government regarding the consultation content. This makes it possible to accurately grasp the specific needs and emotional state of the disaster victim, and to provide prompt and appropriate information and support based on the grasp. It is also possible to strengthen cooperation with the local government or the government and optimize support.

[0622] "Disaster Victim" refers to an individual or group affected by a disaster.

[0623] "Message" refers to text information sent by a disaster victim to the system.

[0624] "Server" refers to a computer system for receiving messages from disaster victims, analyzing them, and providing appropriate information.

[0625] "Natural language processing technology" refers to technology that enables computers to understand, analyze, and generate human language.

[0626] "Keywords" refer to important words or phrases extracted from disaster victims' messages.

[0627] "Emotion analysis technology" refers to technology for analyzing the emotional state of disaster victims from their messages.

[0628] "Local government" refers to local government entities and organizations that provide support to disaster victims.

[0629] "Government" refers to the national administrative body and organizations that provide support to disaster victims.

[0630] "Information provision" refers to the act of providing data and advice that disaster victims need.

[0631] "Collaboration" refers to multiple organizations or systems working together.

[0632] "Optimizing assistance" refers to providing assistance to disaster victims in the most effective and efficient manner possible.

[0633] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0634] The present invention is a system for providing prompt and appropriate support to disaster victims for solving problems they face during a disaster. A specific embodiment of this system will be described below.

[0635] System Configuration

[0636] This system consists of three main elements: a server, a terminal, and a user. The server is a computer system that receives messages from disaster victims, analyzes them, and provides appropriate information. The terminal is a device (such as a smartphone or PC) that disaster victims use to send messages. The user is the disaster victim themselves.

[0637] Hardware and Software Used

[0638] The server is a computer system with a powerful processor and a large amount of memory. The following software is installed on the server:

[0639] Generative AI models for implementing natural language processing techniques (e.g., Google's BERT, OpenAI's GPT-3)

[0640] Software for implementing emotion analysis technology (e.g. IBM's Watson Tone Analyzer)

[0641] Database management system (e.g. MySQL (registered trademark), PostgreSQL)

[0642] Data processing and calculation

[0643] When the server receives a message from a disaster victim, it first analyzes the message using natural language processing technology. For this analysis, it uses generative AI models such as Google's BERT and OpenAI's GPT-3. It extracts keywords from the analysis results and provides appropriate information based on those keywords.

[0644] Specifically, if a disaster victim sends a message saying, "My house has been destroyed. What should I do?", the server will extract the keywords "house," "broken," and "what should I do." Based on this, the server will retrieve information about nearby evacuation shelters and contact information for repair companies from the database and provide this information to the user.

[0645] In addition, the server uses emotion analysis technology to analyze the emotional state of the victims. IBM's Watson Tone Analyzer is used for this emotion analysis. From the analysis results, it is determined whether the victims are feeling fear or anxiety. Based on the results of the emotion analysis, the server reports to local governments and the government to optimize assistance measures.

[0646] Examples and prompts

[0647] For example, if a user sends a message saying "My house is broken into, what should I do?" the server processes it as follows:

[0648] 1. The user sends a message.

[0649] 2. The server receives the message and analyzes it using Google's BERT model.

[0650] 3. The server extracts the keywords "house," "broken," and "what should I do."

[0651] 4. The server retrieves information about nearby evacuation shelters and contact information for repair companies from the database and provides it to the user.

[0652] 5. The server performs emotion analysis using IBM's Watson Tone Analyzer to detect whether the user is feeling fear or anxiety.

[0653] 6. The server reports the results of the sentiment analysis to local governments and the government in order to optimize support measures.

[0654] Examples of prompts to be input to a generative AI model include:

[0655] "Please analyze messages from disaster victims and provide them with appropriate information. Message content: 'My house has been destroyed. What should I do?'"

[0656] By using this prompt sentence, the generative AI model analyzes the message of the victim and performs processing to provide appropriate information. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0657] Step 1:

[0658] A user uses a terminal to send a response to the message "Is there anything I can help you with?". The input is the text message the user sends from the terminal. The output is the user's message received by the server.

[0659] Step 2:

[0660] The server analyzes the received message using natural language processing techniques. The input is the text message received from the user. The server analyzes the message's context and intent using a generative AI model (e.g., BERT or GPT-3). The output is the analyzed message's contextual information.

[0661] Step 3:

[0662] The server extracts keywords from the analysis results. The input is the context information of the message analyzed by natural language processing technology. The server extracts important keywords using text mining technology. The output is a list of extracted keywords.

[0663] Step 4:

[0664] The server provides appropriate information based on the extracted keywords. The input is a list of extracted keywords. The server retrieves related information from a database or external API. Specifically, the server retrieves information about nearby evacuation shelters and contact information for repair companies for the keywords "house," "broken," and "what should I do." The output is the retrieved information.

[0665] Step 5:

[0666] The server analyzes the emotional state of the victim using emotion analysis technology. The input is a text message received from a user. The server analyzes the emotional state from the message using emotion analysis software (e.g., Watson Tone Analyzer). The output is the analyzed emotional state information.

[0667] Step 6:

[0668] The server reports to the local government or government based on the results of the emotion analysis. The input is the analyzed emotional state information. The server reports to the local government or government using a data sharing means via the Internet. In concrete terms, if many victims show signs of fear or anxiety, the server provides that information to the local government or government. The output is the report information sent to the local government or government.

[0669] Step 7:

[0670] The server transmits the provided information to the user. The input is the acquired information and the analyzed emotional state information. The server transmits the appropriate information to the user's terminal. In concrete terms, the server provides the user with information on nearby evacuation shelters and contact information for repair businesses. The output is the information transmitted to the user's terminal.

[0671] (Application example 3)

[0672] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0673] In order for disaster victims to receive prompt and appropriate support during a disaster, it is necessary to accurately grasp the victim's situation and emotional state, and provide appropriate information and optimize support measures. However, conventional systems do not adequately take into account the emotional state of the victim when providing information or optimizing support measures, which can result in delays in providing the support that the victim needs.

[0674] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means. In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for consulting using a generation AI based on the received response, a means for directing the user to useful information and proposing actions, a means for coordinating the consultation content with the local government or the government, a means for analyzing the emotional state of the disaster victim, a means for adjusting the content of a report to the local government or the government based on the emotional state, and a means for transmitting data via the Internet. This makes it possible to provide information quickly and appropriately and optimize support measures taking into account the emotional state of the disaster victim.

[0675] "Victims" refers to people affected by a disaster.

[0676] "Means of sending a message" refers to a communication means for sending specific questions or information to disaster victims.

[0677] "Means of receiving a response" refers to the means of communication for receiving replies and information from disaster victims.

[0678] "Generative AI" refers to a system that uses artificial intelligence technology to generate appropriate information and suggestions based on the data it receives.

[0679] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to means of using generative AI to provide appropriate advice and information to disaster victims.

[0680] "Means of collaboration with local governments and the government" refers to means of sharing information obtained from disaster victims with local governments and government agencies and working together to carry out support activities.

[0681] "Means of analyzing emotional states" refers to technology for analyzing emotions from messages from disaster victims and understanding their state.

[0682] "Means for adjusting the content of reports" refers to means for appropriately changing the content of reports to local governments or governments based on the analyzed emotional state.

[0683] "Means for transmitting data via the Internet" refers to communication means for transmitting data using the Internet.

[0684] The system for carrying out this invention includes a means for sending a message to disaster victims asking "Is there anything you're struggling with?" and receiving a response from the disaster victim. It also includes a means for using a generation AI to provide advice, guide users to useful information, and suggest actions based on the received response. It also includes a means for coordinating the consultation content with local governments and the government, a means for analyzing the emotional state of the disaster victim, a means for adjusting the content of reports to local governments and the government based on the emotional state, and a means for transmitting data via the internet.

[0685] Hardware and software used

[0686] Hardware: Smartphones, servers

[0687] Software: Python, Transformers library, Requests library

[0688] Data processing and calculation

[0689] The server first sends a message to the victim asking, "Is there anything you need help with?" When it receives a response from the victim, it uses a generative AI model to analyze the response and provide appropriate advice, guide the victim to useful information, and suggest actions. The generative AI model uses the Transformers library to perform sentiment analysis and analyze the emotional state of the victim.

[0690] Based on the analyzed emotional state, the server adjusts the report to the local government or government. For example, if many of the victims show fear or anxiety, the server reports this information to the local government or government and uses it as reference information for taking prompt assistance measures. Data is sent over the Internet using the Requests library.

[0691] Examples

[0692] If a disaster victim sends a message saying, "My house has been destroyed. I'm very scared," the server receives the message and performs sentiment analysis using a generative AI model. If the result of the sentiment analysis is determined to be "NEGATIVE," the server reports the information to the local government or the government.

[0693] Examples of prompt statements

[0694] Please enter a message from the victim: My house is destroyed. I'm very scared.

[0695] In this way, the emotional state of the victim can be analyzed in real time and appropriate support information can be provided.

[0696] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0697] Step 1:

[0698] The server sends a message to the victim asking, "Is there anything you need help with?" The input is the victim's contact information, and the output is the sent message. This message is displayed on the victim's smartphone.

[0699] Step 2:

[0700] The victim inputs the answer using a smartphone and sends it to the server. The input is the text message entered by the victim, and the output is the answer sent to the server.

[0701] Step 3:

[0702] The server inputs the received answers into a generative AI model and performs sentiment analysis. The input is the text message from the disaster victim, and the output is the result of the sentiment analysis. Specifically, the Transformers library is used to analyze the emotional state of the message (e.g., positive, negative, neutral).

[0703] Step 4:

[0704] The server provides appropriate advice and guidance to useful information and suggests actions based on the results of the sentiment analysis. The input is the result of the sentiment analysis and the message from the victim, and the output is the generated advice and information. Using the generative AI model, appropriate advice and information is provided to the victim.

[0705] Step 5:

[0706] The server adjusts the report content to the local government or the government based on the emotional state of the victim. The input is the result of the emotion analysis and the message of the victim, and the output is the adjusted report content. If the emotional state is negative, the report content is emphasized to encourage a quick response.

[0707] Step 6:

[0708] The server sends the reconciled reports over the Internet to the local government or government. The input is the reconciled reports and the output is the submitted reports. The Requests library is used to submit the data.

[0709] Step 7:

[0710] Local governments and the government take measures to support disaster victims based on the reports they receive. The input is the report sent from the server, and the output is the support measures to be implemented. This allows disaster victims to receive prompt and appropriate support.

[0711] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0712] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0713] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0714] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0715] [Second embodiment]

[0716] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0717] 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.

[0718] 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 wide area network (WAN) and / or a local area network (LAN).

[0719] 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.

[0720] 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 the voice according to instructions from the processor 46.

[0721] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0722] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0723] Fig. 4 shows an example of 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0728] "Example 1"

[0729] The system of the present invention uses communication means such as a messenger app or an internet search tool as a means for sending a message to disaster victims asking, "Is there anything you need help with?" For example, a message can be sent to disaster victims from an official account of a messenger app.

[0730] "Example 2"

[0731] To receive responses from disaster victims, communication methods such as messenger apps and internet search tools are used. For example, messages from disaster victims can be received from official messenger app accounts.

[0732] "Example 3"

[0733] Based on the answers received, the AI ​​can provide advice, guide users to useful information, and suggest actions, using natural language processing and machine learning technologies. For example, it can extract keywords contained in messages from disaster victims and provide appropriate information based on them.

[0734] "Example 4"

[0735] As a means of coordinating consultations with local governments and the government, data sharing methods via the Internet will be used. For example, messages from disaster victims will be collected and provided to local governments and the government to optimize support for disaster victims.

[0736] The process flow of each embodiment will be described below.

[0737] "Example 1"

[0738] Step 1: The system sends a message to the victim via the official account of the messenger app asking, "Is there anything you need help with?"

[0739] Step 2: Receive a response message from the victim, the message including information indicating the victim's problems and needs.

[0740] Step 3: Analyze the messages received and understand the information needed by the victims.

[0741] Step 4: Based on the information gathered, the generating AI provides appropriate consultation to victims, directs them to useful information, and suggests actions to take.

[0742] "Example 2"

[0743] Step 1: The system sends a message to victims via an Internet search tool asking, "Is there anything you need help with?"

[0744] Step 2: Receive a response message from the victim, the message including information indicating the victim's problems and needs.

[0745] Step 3: Analyze the messages received and understand the information needed by the victims.

[0746] Step 4: Based on the information gathered, the generating AI provides appropriate consultation to victims, directs them to useful information, and suggests actions to take.

[0747] "Example 3"

[0748] Step 1: The system aggregates messages from disaster victims.

[0749] Step 2: Provide aggregated messages to local governments and governments.

[0750] Step 3: Local governments and governments will optimize assistance to disaster victims based on the messages provided.

[0751] Example 1

[0752] Next, a description will be given of Example 1 of Form 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".

[0753] There is a problem in that it is difficult for disaster victims to receive prompt and appropriate support. In particular, support is often delayed because disaster victims have limited means to properly communicate their problems. Another challenge is efficiently collecting information from disaster victims and providing optimal support in cooperation with local governments and the national government.

[0754] 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.

[0755] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for acquiring the contact information of the disaster victim from a database, a means for generating a message using the API of a messenger app, a means for sending the generated message to the disaster victim, a means for receiving a reply from the disaster victim and storing it in a database, a means for using a generation AI to provide advice based on the received reply, for directing the victim to useful information and for suggesting actions, and a means for coordinating the details of the consultation with the local government or the government. This enables the disaster victim to receive prompt and appropriate support.

[0756] "Disaster Victim" refers to an individual or group affected by a disaster.

[0757] "Means for sending messages" refers to a communication means for sending information such as text or images to disaster victims.

[0758] "Contact information" refers to information for contacting disaster victims, and includes, for example, phone numbers, email addresses, and messenger app IDs.

[0759] A "database" refers to a system that systematically stores information and allows it to be searched and updated as needed.

[0760] "Messenger App API" refers to the program interface provided by a messenger app, and means by which external systems can use the functions of a messenger app.

[0761] "Means for generating a message" refers to a program or algorithm used to create the content of the message to be sent.

[0762] "Means for receiving a reply" refers to a communication means for receiving a reply from the disaster victim.

[0763] "Generative AI" refers to a system that uses artificial intelligence technology to generate appropriate information and suggestions based on the responses of disaster victims.

[0764] "Means of providing consultation, directing people to useful information, and suggesting actions" refers to means of providing appropriate advice and information based on the situation of disaster victims and suggesting specific actions to take.

[0765] "Means of collaboration with local governments and the government" refers to means for sharing information with local governments and government agencies and working together to provide support to disaster victims.

[0766] This invention is a system for providing prompt and appropriate support to disaster victims. The system operates in cooperation with three parties: a server, a terminal, and a user.

[0767] The server runs a program to send a message to disaster victims asking, "Is there anything you need help with?" This program retrieves the contact information of the disaster victims from a database, and uses the messenger app's API to generate and send a message. Specifically, the server connects to the database using AWS's RDS (Relational Database Service) to retrieve the contact information of the disaster victims. It then uses the LINE Messaging API or Facebook Messenger API to generate a message and send it to the disaster victims.

[0768] The terminal is a device that disaster victims use to receive and reply to messages. The disaster victim opens a messenger app on their smartphone or tablet and receives messages sent from the server. The disaster victim replies to the message, and the reply is sent to the server.

[0769] The server receives replies from the victims and stores them in a database. The server receives replies from the victims using the LINE Messaging API Webhook, analyzes the content of the replies, and stores them in a database. The stored information is analyzed by a generation AI, which provides consultation to the victims, guides them to useful information, and suggests actions to take.

[0770] As a concrete example, the server runs on an AWS EC2 instance and uses the LINE Messaging API to send messages to disaster victims. The server first retrieves the LINE ID of the disaster victim from the database and calls the LINE Messaging API using that ID. It then sends a message via the API asking, "Is there anything you need help with?"

[0771] Examples of prompts to be input to a generative AI model include:

[0772] "Please create a program to send a message to disaster victims asking, 'Is there anything you need help with?' Use the official account of the messenger app and send the message using the LINE Messaging API."

[0773] In this way, the server can send messages to provide assistance to disaster victims quickly and store the replies in the database, enabling disaster victims to receive prompt and appropriate assistance.

[0774] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0775] Step 1:

[0776] The server retrieves the victim's contact information from a database.

[0777] Input: Database connection information, victim status (e.g. active)

[0778] Specific operation: The server connects to AWS RDS and executes an SQL query to obtain contact information (e.g. LINE ID) of active victims.

[0779] Output: Contact information of victims (e.g. list of LINE IDs)

[0780] Step 2:

[0781] The server generates the message using the messenger app's API.

[0782] Input: Contact information of the victim, message content (e.g. "Is there anything you need help with?")

[0783] Specific behavior: The server uses the obtained contact information to send an HTTP POST request to the LINE Messaging API or Facebook Messenger API to generate a message.

[0784] Output: API request for the generated message

[0785] Step 3:

[0786] A server-generated message is sent to the victim.

[0787] Input: The API request for the generated message

[0788] Specific operation: The server sends an API request, checks the response from the API, and verifies that the status code is 200 to confirm that the message was sent successfully.

[0789] Output: API response (e.g., successful submission status)

[0790] Step 4:

[0791] The victim receives the message and replies.

[0792] Input: Message sent to victim's device

[0793] Specific operation: The victim opens a messenger app on their smartphone or tablet and receives the message sent from the server. The victim then replies to the message.

[0794] Output: Reply message from the victim

[0795] Step 5:

[0796] The server receives replies from victims and stores them in a database.

[0797] Input: Reply message from the victim

[0798] Specific operation: The server receives replies from disaster victims using the LINE Messaging API Webhook, analyzes the contents of the replies, and stores them in a database.

[0799] Output: Responses stored in the database

[0800] Step 6:

[0801] Based on the answers received by the server, the generative AI will provide consultation, guide the user to useful information, and suggest actions.

[0802] Input: Responses stored in the database

[0803] Specific operation: The server uses the generative AI model to analyze the content of the victim's replies and generate appropriate advice, guidance to useful information, and suggestions for action.

[0804] Output: Generated consultation content and action suggestions

[0805] Step 7:

[0806] The server will share the consultation information with local governments and the government.

[0807] Input: Generated consultation content and action suggestions

[0808] Specific operation: The server connects with local government and government systems to share the generated consultation content and action suggestions.

[0809] Output: Information shared with local governments and governments

[0810] In this way, the server, terminals, and users can work together to provide quick and appropriate support to disaster victims.

[0811] (Application example 1)

[0812] Next, a description will be given of Application Example 1 of Form 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".

[0813] In order for disaster victims to receive prompt and appropriate support, it is important to accurately understand the situation and needs of the victims. However, with conventional methods, there were often delays in collecting information from victims and appropriate support was not provided. In addition, there were cases where it was difficult for victims to request support themselves, resulting in delays in providing support.

[0814] 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.

[0815] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice or guide the victim to useful information and suggest actions based on the received response, a means for coordinating the consultation content with a local government or the government, a means for sending a message using an API of a messenger app, and a means for obtaining a reply using the user ID of the disaster victim. This makes it possible to quickly and accurately grasp the situation and needs of the disaster victim and provide appropriate support.

[0816] "Victims" refers to people affected by a disaster.

[0817] "Means for sending a message" refers to a communication means for sending a specific message to a disaster victim.

[0818] "Means of receiving a response" refers to the means of communication for receiving replies or responses from disaster victims.

[0819] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate information and suggested actions.

[0820] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to the means by which the generative AI provides necessary information and suggests appropriate actions based on the victims' responses.

[0821] "Means of collaboration with local governments and the government" refers to the means of sharing the consultation details and needs of disaster victims with local governments and government agencies, and of coordinating support activities.

[0822] "Messenger app API" refers to the program interface provided by a messenger application that can be used to send and receive messages.

[0823] "User ID" refers to a unique identifier used to identify a disaster victim.

[0824] "Means of obtaining a reply" refers to a communication means for obtaining a reply from the disaster victim.

[0825] The system for carrying out the present invention provides prompt and appropriate support to disaster victims by sending them a message asking, "Is there anything you need help with?" and receiving a reply from the disaster victim. A specific embodiment of this system will be described below.

[0826] System Configuration

[0827] The system consists of the following main components:

[0828] 1. Server: Sends messages, receives responses, analyzes using generative AI, and coordinates with local governments and the government.

[0829] 2. Victim's device: A device with a messenger app installed, such as a smartphone or tablet.

[0830] 3. Generative AI model: An artificial intelligence system that analyzes responses from disaster victims and provides appropriate information and suggests actions.

[0831] Program Processing

[0832] The server performs the process in the following procedure.

[0833] 1. Send a message:

[0834] The server uses the victim's user ID to send a message to the messenger app's API asking, "Is there anything you need help with?". To do this, the server uses the requests library to send an HTTP POST request.

[0835] 2. Receiving a response:

[0836] When the victim replies to the message, the reply is sent to the server, which uses the Messenger app's API to retrieve the reply based on the victim's user ID, again using the requests library to send an HTTP GET request.

[0837] 3. Generative AI Analysis:

[0838] The server inputs the received responses into a generative AI model to generate information and action suggestions needed by disaster victims. The generative AI model uses natural language processing technology to analyze the responses and provide appropriate information.

[0839] 4. Collaboration with local governments and governments:

[0840] The server will share the information and suggestions generated by the generative AI model with local governments and government agencies to optimize support for disaster victims.

[0841] Hardware and Software Used

[0842] Hardware: Servers, smartphones, tablets

[0843] Software: Messenger app, generative AI model, requests library

[0844] Examples

[0845] For example, for victims in a disaster-hit area, the following prompt sentences are input into the generative AI model:

[0846] Example prompt:

[0847] A disaster has occurred. Please create a system to send a message to the victims asking "Is there anything you need help with?" and receive a reply. Please use the following information.

[0848] Victim's user ID: "12345"

[0849] Message: "Is there anything I can help you with?"

[0850] Messenger app API endpoint: "https: / / api.messagingapp.com"

[0851] By inputting this prompt sentence into the generative AI model, it is possible to propose specific implementation methods for a disaster victim support system.

[0852] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0853] Step 1:

[0854] The server obtains the victim's user ID and uses the messenger app's API to send a message saying "Is there anything I can help you with?". The input requires the victim's user ID and the message content, and the output is the success or failure status of the message transmission. In this step, the specific operation of sending an HTTP POST request using the requests library is performed.

[0855] Step 2:

[0856] The victim's device receives the message sent from the server and displays it to the user. As input, the message sent from the server is required, and as output, the message displayed to the user is obtained. In this step, the specific operation of the messenger app to display the message is performed.

[0857] Step 3:

[0858] The user replies to the message. The input requires the reply content entered by the user, and the output requires the reply content to be sent to the server via the messenger app. In this step, the specific actions of the user operating the messenger app to enter and send the reply are performed.

[0859] Step 4:

[0860] The server uses the API of the messenger app to get the reply based on the victim's user ID. The input requires the victim's user ID, and the output is the reply from the victim. In this step, the concrete operation of sending an HTTP GET request using the requests library is performed.

[0861] Step 5:

[0862] The server inputs the retrieved reply content into the generative AI model for analysis. The input requires the reply content from the victim, and the output is appropriate information provision and action suggestions as the analysis result. In this step, the generative AI model performs the specific operation of analyzing the reply content using natural language processing technology.

[0863] Step 6:

[0864] The server shares the information and suggestions generated by the generative AI model with the local government or government agency. As input, the analysis results of the generative AI model are required, and as output, the information and suggestions are obtained to be sent to the local government or government agency. In this step, the specific operation of the server to communicate with the local government or government agency is performed.

[0865] Step 7:

[0866] Local governments and government agencies optimize support for disaster victims based on the information and proposals received from the server. The input requires the information and proposals sent from the server, and the output is specific support activities for disaster victims. In this step, local governments and government agencies take concrete actions to plan and execute support activities.

[0867] Example 2

[0868] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0869] It is necessary to quickly and accurately grasp the problems and difficulties that disaster victims face and provide appropriate support. However, in conventional systems, the collection and analysis of information from victims is often done manually, making it difficult to respond quickly. In addition, the provision of information and support according to the needs of victims is not adequately optimized. This can result in delays in providing the support that victims need.

[0870] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0871] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generative AI model to provide advice and guidance to useful information and suggest actions based on the received response, a means for linking the consultation content with a public institution, a means for using natural language processing technology to analyze the message, and a means for storing the analysis results and executing necessary actions. This makes it possible to quickly and accurately collect and analyze information from the disaster victim and provide appropriate support.

[0872] "Victims" refers to people affected by a disaster.

[0873] "Means for sending a message" refers to a communications means for sending a text message to a disaster victim.

[0874] "Means of receiving a response" refers to a means of communication for receiving messages sent by disaster victims.

[0875] A "generative AI model" refers to a model that uses artificial intelligence technology to analyze messages from disaster victims and generate appropriate information and suggestions.

[0876] "Means of providing consultation, guidance to useful information, and suggested actions" refers to the use of generative AI models to provide appropriate advice and information to disaster victims.

[0877] "Public institutions" refers to public institutions such as local governments and governments.

[0878] "Natural language processing technology" refers to technology for analyzing human language and understanding its meaning.

[0879] "Means for storing the analysis results" refers to means for storing the analyzed information in a database or the like.

[0880] "Means of taking necessary actions" refers to the means of carrying out appropriate responses and support based on the analysis results.

[0881] The present invention is a system for quickly and accurately collecting and analyzing information from disaster victims, and providing appropriate support. A specific embodiment of this system will be described below.

[0882] The server has a means to send a message to the disaster victims asking, "Is there anything you need help with?". This means uses the API of a messenger app (for example, the LINE Messaging API or the Facebook Graph API). The server sends messages to the disaster victims through these APIs and receives responses.

[0883] The server has a means of receiving responses from disaster victims. The received messages are stored in a database. The server uses natural language processing technology to analyze the received messages. Specifically, it uses Google Cloud Natural Language API and IBM Watson Natural Language Understanding. This allows it to analyze the content of the messages and extract important information.

[0884] The server uses the generative AI model to analyze messages from disaster victims and generate appropriate information and suggestions. The generative AI model provides information and suggests actions according to the needs of the disaster victim. For example, it extracts the information "Arrived at the evacuation shelter" from the message "Arrived at the evacuation shelter" and sends a notification to the evacuation shelter manager.

[0885] The server stores the analysis results in a database and has the means to take necessary actions, such as using an email sending API (e.g., the SendGrid API) or a notification system, to respond appropriately or provide assistance based on the analysis results.

[0886] The terminal is a device that disaster victims use to send messages. This can be a smartphone, tablet, or computer. Disaster victims can use a messenger app to send messages to the official account. For example, they can send messages such as "We have arrived at the evacuation shelter" or "Food is running low."

[0887] A user (disaster victim) sends a message to the official account using a messenger app. As a concrete example, consider a case where a disaster victim sends a message to the official LINE account saying "I have arrived at the evacuation shelter." The server receives this message, analyzes it using the Google Cloud Natural Language API, and extracts the information that "I have arrived at the evacuation shelter."

[0888] Examples of prompt sentences to be input to a generative AI model include the following:

[0889] Example prompt:

[0890] "Please analyze the messages from the disaster victims and extract the necessary information. The message content is 'I have arrived at the evacuation shelter.'"

[0891] By inputting this prompt sentence into a generative AI model, the model will provide an analysis of the message, for example extracting the information "arrived at the evacuation shelter."

[0892] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0893] Step 1:

[0894] A user sends a message using a messenger app.

[0895] Specifically, a user opens a messenger app on a smartphone, tablet, or other device, types a message to the official account such as "I've arrived at the evacuation shelter" or "There is a shortage of food," and presses the send button.

[0896] Input: The message entered by the user.

[0897] Output: Messages sent through the Messenger app

[0898] Step 2:

[0899] The server receives the message.

[0900] Specifically, the server receives messages sent by users using the API of the messenger app. For example, it uses the LINE Messaging API or the Facebook Graph API to obtain message data. The server then stores the received messages in a database.

[0901] Input: Message sent from Messenger app

[0902] Output: Message data stored in the database

[0903] Step 3:

[0904] The server parses the message.

[0905] Specifically, the server uses natural language processing technology to analyze the received messages. Specifically, it uses Google Cloud Natural Language API and IBM Watson Natural Language Understanding. The server analyzes the content of the messages and extracts important information.

[0906] Input: Message data stored in the database

[0907] Output: Analyzed information (e.g. "arrived at evacuation shelter")

[0908] Step 4:

[0909] The server stores the analysis results and performs the necessary actions.

[0910] Specifically, the server saves the analysis results in a database. It then executes actions as necessary. For example, it can send a notification to the shelter manager or arrange for relief supplies. To do this, it uses an email sending API or a notification system.

[0911] Input: Parsed information

[0912] Output: Actions taken (e.g. notifications sent to shelter administrators)

[0913] (Application example 2)

[0914] Next, a description will be given of Application Example 2 of Form 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".

[0915] In the event of a disaster, it is difficult for victims to receive prompt and appropriate support. In particular, delays in collecting information from victims and responding appropriately based on that information can threaten the safety and livelihood of victims. In addition, insufficient cooperation with local governments and the national government makes it difficult to optimize support.

[0916] 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. In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for consulting using a generative AI model, guiding the victim to useful information, and proposing actions based on the received response, a means for generating an appropriate response to the message from the disaster victim using the generative AI model, and a means for coordinating the consultation content with the local government or the government. This makes it possible to quickly collect information from the disaster victim and provide appropriate support. Furthermore, by strengthening cooperation with the local government or the government, optimization of support can be achieved.

[0917] "Victims" refers to people affected by a disaster.

[0918] "Means for sending a message" refers to a communication means for sending a specific message to a disaster victim.

[0919] "Means of receiving responses" refers to the means of communication for receiving messages and information from disaster victims.

[0920] A "generative AI model" refers to a model that uses artificial intelligence to generate appropriate responses and suggestions to messages from disaster victims.

[0921] "Means of providing consultation, directing people to useful information, and suggesting actions" refers to means of providing appropriate consultation and useful information based on information from disaster victims, and suggesting specific actions.

[0922] "Means of collaboration with local governments and the government" refers to the means of sharing information about disaster victims and the details of their concerns with local governments and government agencies, and working together to provide support.

[0923] "Means for generating an appropriate response" refers to means for automatically generating an appropriate response to a message from a disaster victim using a generative AI model.

[0924] A system for implementing this invention includes means for sending a message to disaster victims asking "Is there anything you need help with?", means for receiving responses from disaster victims, means for using a generative AI model to provide advice and guide users to useful information and suggest actions based on the received answers, means for generating appropriate responses to messages from disaster victims using the generative AI model, and means for coordinating the content of the consultation with local governments and the government.

[0925] Hardware and Software Used

[0926] Hardware: Smartphones, servers

[0927] Software: Messenger apps (e.g. LINE, WhatsApp), OpenAI API

[0928] Data processing and calculation

[0929] 1. Sending a message: The server uses the messenger app's API to send a message to the victim asking, "Is there anything you need help with?"

[0930] 2. Receiving response: The server receives the response sent by the victim through the messenger app.

[0931] 3. Response generation using a generative AI model: The server inputs the received answer into a generative AI model (e.g., OpenAI GPT-3) to generate an appropriate response.

[0932] 4. Providing a response: The server provides the generated response to the victim.

[0933] 5. Collaboration with local governments and the government: The server will share information and inquiries from disaster victims with local governments and government agencies, and work together to provide support.

[0934] Examples

[0935] If the server receives a message from a victim saying, "Your house is flooded and you need to evacuate," it will use the generative AI model to generate a response such as, "Please evacuate to a nearby evacuation shelter. Please let us know if you need any assistance," and provide this to the victim.

[0936] Examples of prompt statements

[0937] Message from the victim: My house is flooded and I need to evacuate

[0938] Generate an appropriate response.

[0939] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0940] Step 1:

[0941] The server uses the messenger app's API to send a message to the victim asking, "Is there anything you need help with?"

[0942] Input: Victim's contact information

[0943] Output: Message sent to victim

[0944] Specific operation: The server sends an HTTP request to the API endpoint of the messenger app to send a message to the victim.

[0945] Step 2:

[0946] The user (victim) sends the response via a messenger app.

[0947] Input: Victim's response message

[0948] Output: Reply message sent to messenger app

[0949] What happens: A victim uses a messenger app to type a text message and presses send.

[0950] Step 3:

[0951] The server receives the responses from the victims.

[0952] Input: Message sent by victim

[0953] Output: Message data of victims stored on the server

[0954] Specific operation: The server stores messages received through the messenger app's API in a database.

[0955] Step 4:

[0956] The server inputs the received answers into a generative AI model to generate an appropriate response.

[0957] Input: Message data from victims

[0958] Output: The generated response message

[0959] Specific operation: The server sends an API request to a generative AI model (e.g., OpenAI GPT-3) and generates an appropriate response using the prompt sentence as input.

[0960] Step 5:

[0961] The server provides the generated response to the victim.

[0962] Input: The generated response message

[0963] Output: Response message sent to victim

[0964] Specific operation: The server generates a response message using the messenger app's API and sends it to the victim.

[0965] Step 6:

[0966] The server will share information and consultation details from disaster victims with local governments and government agencies.

[0967] Input: victim's message data and generated response message

[0968] Output: Information sent to local government or government agencies

[0969] Specific operation: The server sends an HTTP request to the API endpoint of a local government or government agency to share information about disaster victims.

[0970] Example 3

[0971] Next, a third embodiment of the third embodiment will be described. 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".

[0972] There is a problem in that it is difficult to provide disaster victims with the information they need quickly and accurately. It is also difficult to effectively communicate with local governments and the government on the content of inquiries from disaster victims and optimize support.

[0973] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for extracting keywords based on the received response using natural language processing technology, a means for generating appropriate information using a generative AI model based on the extracted keywords, a means for providing the generated information to the disaster victim, and a means for coordinating the consultation content with a local government or the government. This makes it possible to quickly and accurately provide the information required by the disaster victim and optimize support through cooperation with the local government or the government.

[0974] "Disaster Victim" refers to an individual or group affected by a disaster.

[0975] "Means for sending a message" refers to a communication means for sending information to disaster victims in the form of text, voice, or the like.

[0976] "Means of receiving a response" refers to the means of communication for receiving responses or feedback from affected people.

[0977] "Natural language processing technology" refers to technology that enables computers to understand, analyze, and generate human language.

[0978] "Keyword extraction means" refers to techniques for identifying and extracting important words and phrases from received text data.

[0979] A "generative AI model" refers to a model that uses artificial intelligence to generate appropriate responses or information based on input data.

[0980] "Means for generating information" refers to technology for using a generative AI model to create appropriate information based on extracted keywords.

[0981] "Means for providing information" refers to communication means for conveying the generated information to disaster victims.

[0982] "Means of collaboration with local governments and the government" refers to means for sharing information from disaster victims with local governments and government agencies and working together to carry out relief activities.

[0983] This invention is a system that quickly and accurately provides disaster victims with the information they need in the event of a disaster, and optimizes support through cooperation with local governments and the government. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0984] Hardware and Software Used

[0985] Server: Use a server with high-performance computing power. The server plays a central role in receiving, analyzing, generating, and transmitting data.

[0986] Terminal: A device used by a user, such as a smartphone, tablet, or computer. The terminal sends messages from the user and receives information from the server.

[0987] Natural language processing technology: Uses Python libraries NLTK and spaCy to extract keywords from messages.

[0988] Generative AI models: Generative AI models such as OpenAI's GPT-4 are used to generate appropriate information based on the extracted keywords.

[0989] Program Processing

[0990] 1. Receiving a message from a user

[0991] A user uses a terminal to send a message. For example, the user types, "Please tell me where the evacuation shelter is" and presses the send button.

[0992] The terminal sends a message to the server.

[0993] 2. Extracting keywords from messages

[0994] The server analyzes the received messages using natural language processing techniques, specifically using Python's NLTK and spaCy to extract important keywords from the messages.

[0995] For example, from the message "Please tell me where the evacuation shelter is," the keywords "evacuation shelter" and "location" are extracted.

[0996] 3. Producing the right information

[0997] The server uses a generative AI model to generate appropriate information based on the extracted keywords. A prompt sentence is input to the generative AI model to generate a response.

[0998] For example, a prompt sentence such as "Please tell me where the evacuation shelter is" can be input into a generative AI model, and the model can generate the information, "The nearest evacuation shelter is next to City Hall. The address is XX."

[0999] 4. Provision of generated information

[1000] The server transmits the generated information to the terminal, which then displays the received information to the user.

[1001] For example, the user's screen might display, "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[1002] 5. Data aggregation and sharing

[1003] The server stores messages from users in a database. Periodically, the server aggregates the stored data and provides it to local governments and governments.

[1004] Use a secure internet connection (e.g., HTTPS) for data sharing.

[1005] Examples

[1006] User message: "Where are the evacuation shelters?"

[1007] Keyword extraction: "shelter", "place"

[1008] Prompt for generative AI model: "When asked where the evacuation shelters are located, please provide the appropriate evacuation shelter information."

[1009] Generated information: "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[1010] This system is a powerful tool for providing support to disaster victims quickly and accurately. By combining natural language processing technology and generative AI models, it realizes optimization of information provision and support according to user needs. The flow of the identification process in the third embodiment will be explained with reference to FIG. 15.

[1011] Step 1:

[1012] Receiving messages from users

[1013] Input: A user uses a device to type a message and presses the send button. For example, "Please tell me where the evacuation shelters are."

[1014] Specific operation: The terminal sends the user's message to the server as an HTTP request.

[1015] Output: The server stores the received message in a database and passes it on to the next processing step.

[1016] Step 2:

[1017] Extracting keywords from messages

[1018] Input: The user's message received by the server. For example, "Please tell me where the evacuation shelter is."

[1019] What it does: The server uses natural language processing libraries such as Python's NLTK or spaCy to extract important keywords from messages.

[1020] Data processing: Tokenize messages, tag parts of speech, and extract key keywords.

[1021] Output: Extracted keywords, e.g. "shelter", "location".

[1022] Step 3:

[1023] Producing the right information

[1024] Input: Extracted keywords, e.g. "shelter", "location".

[1025] Specific operation: The server creates and inputs a prompt sentence to the generative AI model (e.g., GPT-4).

[1026] Data calculation: The generative AI model generates appropriate information based on the prompt.

[1027] Output: The generated information. For example, "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[1028] Step 4:

[1029] Providing generated information

[1030] Input: Generated information. For example, "The nearest evacuation shelter is next to ____ City Hall. The address is ____."

[1031] Specific operation: The server sends the generated information to the terminal as an HTTP response.

[1032] Output: The device displays the received information to the user. For example, the user's screen might display "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[1033] Step 5:

[1034] Data aggregation and sharing

[1035] Input: Message from user and generated information.

[1036] What happens: The server stores this data in a database and aggregates it periodically.

[1037] Data processing: Collecting and analyzing stored data.

[1038] Output: Provide aggregated data to local governments and / or governments using a secure internet connection (e.g. HTTPS) to share data.

[1039] (Application example 3)

[1040] Next, a description will be given of Application Example 3 of Form Example 3. 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".

[1041] There is a problem that it is difficult for disaster victims to quickly obtain appropriate information in an emergency. In addition, there is a problem that support for disaster victims is not optimized due to insufficient cooperation with local governments and the government. Furthermore, there is a lack of means to efficiently process messages from disaster victims and propose appropriate actions.

[1042] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1043] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice and guidance to useful information and suggest actions based on the received answer, a means for coordinating the consultation content with a local government or the government, a means for extracting keywords from the message from the disaster victim using natural language processing technology, a means for providing appropriate information based on the extracted keywords, and a means for sharing the message from the disaster victim with the local government or the government. This enables the disaster victim to quickly obtain appropriate information, strengthens cooperation with the local government or the government, and optimizes support for the disaster victim.

[1044] "Disaster Victim" refers to an individual or group of people affected by a disaster or emergency.

[1045] "Message" refers to text data sent to disaster victims to ask questions or provide information.

[1046] "Response" refers to a reply or response to a message sent by a disaster victim.

[1047] "Generative AI" refers to a system that uses artificial intelligence technology to provide information and suggest actions based on the data it receives.

[1048] "Consultation" refers to the act of providing advice and solutions to problems and questions that disaster victims have.

[1049] "Useful information" refers to information that is important and useful to disaster victims.

[1050] "Suggested actions" refers to advice that provides specific actions that survivors should take.

[1051] "Local government" refers to local public entities, specifically including cities, towns, villages, and prefectures.

[1052] "Government" refers to the administrative organs of a nation, including central and local governments.

[1053] "Collaboration" refers to different organizations and agencies working together to share information and respond jointly.

[1054] "Natural language processing technology" refers to technology that enables computers to understand and process human language.

[1055] "Keywords" refer to important words or phrases extracted from a message.

[1056] "Means of providing information" refers to the method of conveying appropriate information to disaster victims based on the extracted keywords.

[1057] "Means of sharing data" refers to the methods of conveying messages from disaster victims to local governments and the government.

[1058] The system for implementing this invention has the function of sending a message to disaster victims asking "Is there anything you are struggling with?" and receiving responses from them. Based on the responses received, a generative AI model is used to provide advice, guide users to useful information, and suggest actions. It also has the function of sharing the details of consultations with local governments and the national government.

[1059] Hardware and Software Used

[1060] Hardware: Smartphones, servers

[1061] Software: Python, spaCy, Transformers library

[1062] Data processing and calculation

[1063] 1. Message transmission: The server sends a message to the disaster victim asking, "Is there anything you need help with?" This message is sent as text data.

[1064] 2. Response reception: The server receives the responses from the victims. The received responses are stored as text data.

[1065] 3. Keyword extraction: The server uses natural language processing technology (spaCy) to extract keywords from messages from disaster victims. The extracted keywords are compiled into a list of important words and phrases.

[1066] 4. Information provision: Based on the extracted keywords, the server uses a generative AI model (Transformers library) to provide appropriate information, such as the location of evacuation shelters and emergency contact information.

[1067] 5. Data sharing: The server shares messages from disaster victims with local governments and the government. This sharing is done via the Internet.

[1068] Examples

[1069] For example, if a disaster victim sends a message saying, "My house is flooded and I need to evacuate. Where should I go?", the server receives this message and uses natural language processing technology to extract the keywords "flooded," "evacuation," and "where should I go." It then uses a generative AI model to provide the location of the evacuation shelter. This message is also shared with local governments and the government, enabling them to provide rapid assistance.

[1070] Examples of prompt statements

[1071] Please receive messages from disaster victims, extract keywords, and provide appropriate information. Also, please tell us how to share the messages with local governments and the government.

[1072] In this way, a specific embodiment for carrying out the invention has been shown, which enables disaster victims to quickly obtain appropriate information, strengthens cooperation with local governments and the government, and optimizes support for disaster victims.

[1073] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1074] Step 1:

[1075] The server sends a message to the victim asking, "Is there anything you need help with?"

[1076] Input: Victim's contact information

[1077] Output: The message sent.

[1078] Specific operation: The server retrieves the victim's contact information from a database and generates and sends a text message.

[1079] Step 2:

[1080] The user (victim) sends a reply to the message from the server.

[1081] Input: Message from the server

[1082] Output: Reply message from the victim

[1083] Specific operations: The victim enters a response via text message using a device such as a smartphone and sends it to the server.

[1084] Step 3:

[1085] The server receives the responses from the victims.

[1086] Input: Response message from the victim

[1087] Output: Received response message

[1088] Specific operation: The server receives messages from disaster victims via the network and stores them in a database.

[1089] Step 4:

[1090] The server uses natural language processing technology to extract keywords from messages from disaster victims.

[1091] Input: Received response message

[1092] Output: Extracted keywords

[1093] What it does: The server uses the spaCy library to parse the message and extract important words and phrases.

[1094] Step 5:

[1095] The server provides appropriate information based on the extracted keywords.

[1096] Input: Extracted keywords

[1097] Output: Information provided

[1098] Specific operation: The server runs a generative AI model using the Transformers library to generate information related to keywords and send it to the victim.

[1099] Step 6:

[1100] The server shares messages from disaster victims with local governments and the government.

[1101] Input: Received response message

[1102] Output: Message shared with local governments

[1103] Specific operation: The server sends messages via the Internet to local government and government systems for sharing.

[1104] In this manner, the specific operations performed at each processing step and their inputs and outputs have been described.

[1105] In addition, 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.

[1106] "Example 1"

[1107] In one embodiment of the present invention, the emotion engine recognizes emotions based on the response from the victim. Specifically, the emotion engine analyzes text information included in the response message from the victim and estimates the emotional state of the victim from the text information. For example, if the response message contains words such as "scary" or "anxiety," it is determined that the victim is feeling fear or anxiety.

[1108] "Example 2"

[1109] In another embodiment of the present invention, the emotion engine adjusts the consultation content and the method of providing useful information according to the emotion of the victim. Specifically, when it is determined that the victim is feeling fear or anxiety, the emotion engine adjusts the consultation content and the method of providing useful information to the victim based on the emotional state. For example, when it is determined that the victim is feeling anxiety, information that provides a sense of security is provided preferentially.

[1110] "Example 3"

[1111] In yet another embodiment of the present invention, the emotion engine adjusts the report content to the local government or government according to the emotions of the victims. Specifically, the emotion engine reports the information to the local government or government based on the emotional state of the victims. For example, if responses indicating fear or anxiety are obtained from many victims, the information is reported to the local government or government and used as reference information for optimizing support measures for the victims.

[1112] The process flow of each embodiment will be described below.

[1113] "Example 1"

[1114] Step 1: Receive a response message from the victim.

[1115] Step 2: Analyze the text information contained in the received message.

[1116] Step 3: Estimate the emotional state of the victim from the text information.

[1117] "Example 2"

[1118] Step 1: Determine the victim's emotional state.

[1119] Step 2: Adjust the content of your consultation and the way you provide useful information based on the person's emotional state.

[1120] Step 3: Provide the adjusted information to the victims.

[1121] "Example 3"

[1122] Step 1: Determine the victim's emotional state.

[1123] Step 2: Tailor your reporting based on your emotional state.

[1124] Step 3: Report the adjusted information to the local government or government.

[1125] Example 1

[1126] Next, a description will be given of Example 1 of Form 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".

[1127] It is necessary to quickly grasp the anxiety and fear that disaster victims feel in the event of a disaster and provide appropriate support. However, conventional systems have difficulty accurately recognizing the emotional state of victims, making it difficult to provide appropriate support. In addition, there was a lack of means to effectively utilize information from disaster victims in cooperation with local governments and the national government.

[1128] 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.

[1129] In this invention, the server includes a means for sending a message to the disaster victim asking "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for performing emotion analysis based on the received response, a means for using a generative AI to provide advice or guide the victim to useful information and suggest actions based on the results of the emotion analysis, and a means for coordinating the consultation content with local governments and the government. This makes it possible to quickly and accurately grasp the emotional state of the disaster victim and provide appropriate support. In addition, the information from the disaster victim can be effectively utilized to strengthen cooperation with local governments and the government.

[1130] "Disaster Victim" refers to an individual or group affected by a disaster.

[1131] "Means for sending a message" refers to a communication means for sending a specific message to a disaster victim.

[1132] "Means of receiving a response" refers to the means of communication for receiving replies or responses from disaster victims.

[1133] "Means for performing emotion analysis" refers to technology for analyzing the text information contained in responses from disaster victims and inferring their emotional state.

[1134] "Generative AI" refers to a system that uses artificial intelligence technology to provide appropriate information and suggest actions based on the responses of disaster victims.

[1135] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to technology that provides appropriate consultation, information, and action suggestions to disaster victims based on the results of emotion analysis.

[1136] "Means of collaborating with local governments and the government" refers to technology for sharing information obtained from disaster victims with local governments and government agencies and working together to carry out relief activities.

[1137] This invention is a system that sends a message to a disaster victim asking "Is there anything you are struggling with?", analyzes the response, recognizes the emotion, and provides appropriate support. A specific embodiment of this system will be described below.

[1138] System Configuration

[1139] Sending a message

[1140] The server sends a message to the disaster victim through the official account of the messenger app, asking "Is there anything you need help with?". This message is sent using a messenger app such as LINE or Facebook Messenger. The server uses the API of these applications to send the message.

[1141] Response received

[1142] The user uses the messenger app to reply to the message from the server. For example, the user replies, "My house is broken into and I'm scared." The device transmits the user's reply to the server.

[1143] Emotion analysis

[1144] When the server receives the user's answer, it sends the answer to the emotion engine. The emotion engine uses natural language processing tools such as IBM Watson or Google Cloud Natural Language API. The emotion engine analyzes the text information included in the answer message and estimates the emotion, such as "fear" or "anxiety."

[1145] Save and notify results

[1146] The server stores the results of emotion analysis obtained from the emotion engine in a database. If necessary, the server notifies the relevant parties of the analysis results. For example, it sends an email using the SMTP protocol to notify the disaster relief team.

[1147] Examples

[1148] scenario:

[1149] The user receives a message from the official LINE account asking, "Is there anything you're struggling with?" The user replies, "My house is broken into and I'm scared."

[1150] Process flow:

[1151] 1. The server sends a message to the user via the LINE official account.

[1152] 2. The user responds, "My house is broken into and I'm scared."

[1153] 3. The server receives the user's answer and sends it to the emotion engine.

[1154] 4. The emotion engine analyzes the reply message and determines that the user is feeling scared based on the word "scary."

[1155] 5. The server stores the results of the emotion analysis in a database and notifies the victim support team via email.

[1156] Example prompts for generative AI models

[1157] "A user receives a message from the LINE official account asking, 'Is there anything troubling you?' and responds, 'My house is broken and I'm scared.' Please infer the user's emotions from this response."

[1158] In this way, a specific embodiment of the system will be described while clarifying the roles of the server, the terminal, and the user.

[1159] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1160] Step 1:

[1161] The server sends a message to the disaster victim asking "Is there anything you need help with?" through the official account of the messenger app. Specifically, the server uses the LINE API or Facebook Messenger API to send an HTTP request and deliver the message. The input is the contact information of the disaster victim, and the output is the message sent.

[1162] Step 2:

[1163] The user uses a messenger app to reply to the message from the server. For example, the user replies, "My house is broken into and I'm scared." The device sends the user's input to the server through the LINE API. The input is the user's reply message, and the output is the reply data sent to the server.

[1164] Step 3:

[1165] When the server receives the user's answer, it sends the answer to the emotion engine. Specifically, the server sends an HTTP request to the Google Cloud Natural Language API to request text analysis. The input is the user's answer message, and the output is the result of the emotion analysis.

[1166] Step 4:

[1167] The emotion engine analyzes the reply message and estimates emotions such as "fear" or "anxiety." Specifically, it uses natural language processing technology to extract emotional expressions in the text and estimate the emotional state. The input is the user's reply message, and the output is the estimated emotional state.

[1168] Step 5:

[1169] The server stores the emotion analysis results obtained from the emotion engine in a database. Specifically, the server uses a SQL query to insert the analysis results into the database. The input is the emotion analysis result, and the output is the data stored in the database.

[1170] Step 6:

[1171] The server notifies the relevant parties of the analysis results as necessary. For example, to notify the disaster victim support team, it sends an email using the SMTP protocol. The input is the result of the sentiment analysis and the notification destination information, and the output is the sent notification email.

[1172] (Application example 1)

[1173] Next, a description will be given of Application Example 1 of Form 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".

[1174] In the event of a disaster, it is necessary to quickly and accurately grasp the emotions such as fear and anxiety felt by disaster victims and provide appropriate support information. However, conventional systems have difficulty accurately recognizing the emotional state of disaster victims, which can lead to delays in providing appropriate support. In addition, there has been a lack of consultation and information provision by generative AI based on responses from disaster victims, which has led to issues with providing support that meets the needs of disaster victims.

[1175] 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.

[1176] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice or guide users to useful information and suggest actions based on the received response, a means for coordinating the consultation content with a local government or the government, a means for analyzing the response message from the disaster victim and recognizing the emotional state, and a means for providing appropriate support information based on the recognized emotional state. This makes it possible to quickly and accurately grasp the emotional state of the disaster victim and provide appropriate support information.

[1177] "Victims" refers to people affected by a disaster.

[1178] "Means for sending a message" refers to a communications means for sending a text message to a disaster victim.

[1179] "Means of receiving a response" refers to the means of communication for receiving a reply message from the disaster victim.

[1180] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate consultation and information.

[1181] "Means of consultation, guidance to useful information, and suggested actions" refers to means of providing appropriate advice and information based on the responses of disaster victims and suggesting actions.

[1182] "Means of collaboration with local governments and the government" refers to the means of sharing the consultation details of disaster victims with local governments and government agencies and working together to provide support.

[1183] "Means for recognizing emotional states" refers to means for analyzing response messages from disaster victims and recognizing the emotions contained therein.

[1184] The "means for providing appropriate support information" refers to a means for providing necessary support information to a disaster victim based on the recognized emotional state.

[1185] A system for carrying out this invention includes a communication means for sending a message to a disaster victim asking "Is there anything you need help with?" and receiving a response from the disaster victim. Specifically, a messenger app installed on a terminal such as a smartphone or tablet is used. A server receives the response message from the disaster victim and analyzes the response using a generative AI model.

[1186] The generative AI model analyzes the text information contained in the victim's response message and recognizes the emotions contained therein. For example, if the message contains words such as "scared" or "anxious," it determines that the victim is feeling fear or anxiety. TextBlob or other natural language processing libraries can be used as the emotion engine.

[1187] The server provides appropriate support information based on the recognized emotional state. For example, if a victim answers, "I'm scared. What should I do?", the server recognizes that the victim is "feeling scared and anxious" and provides appropriate support information. Support information is provided in cooperation with local governments and the national government.

[1188] As a concrete example, the following prompt sentence can be input to a generative AI model to perform sentiment analysis:

[1189] Analyze the response messages from the victims and recognize their emotional state. For example, if the messages contain words such as "scared" or "anxious," determine that the victim is feeling fear or anxiety.

[1190] Response message: "I'm scared. What should I do?"

[1191] This system makes it possible to quickly and accurately grasp the emotional state of disaster victims and provide appropriate support information. It is expected that this will lead to faster support that meets the needs of disaster victims and more effective support activities during disasters.

[1192] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1193] Step 1:

[1194] The server sends a message to the victim asking, "Is there anything you need help with?"

[1195] Input: Victim's contact information

[1196] Output: Message sent to victim's device

[1197] What it does: The server uses the messenger app's API to send messages based on the victim's contact information.

[1198] Step 2:

[1199] The victim inputs a response to the received message and sends it.

[1200] Input: Victim's response message

[1201] Output: The response message sent to the server.

[1202] Specific operations: Victims use a device such as a smartphone or tablet to enter and send responses via a messenger app.

[1203] Step 3:

[1204] The server receives the reply messages from the victims.

[1205] Input: Victim's response message

[1206] Output: The answer message stored on the server

[1207] Specific operation: The server uses the messenger app's API to receive response messages from victims and store them in a database.

[1208] Step 4:

[1209] The server uses a generative AI model to analyze the reply message and recognize the emotional state.

[1210] Input: Victim's response message

[1211] Output: Perceived emotional state

[1212] How it works: The server uses a natural language processing library such as TextBlob to analyze the reply message and recognize the emotional state of the message. For example, it detects keywords such as "scared" and "anxious."

[1213] Step 5:

[1214] The server generates appropriate assistance information based on the recognized emotional state.

[1215] Input: Perceived emotional state

[1216] Output: Appropriate supporting information

[1217] How it works: The server uses the generative AI model to generate support information appropriate for the victim based on their recognized emotional state. For example, if they are feeling scared or anxious, it provides reassuring information and action guidelines.

[1218] Step 6:

[1219] The server transmits the generated support information to the disaster victims.

[1220] Input: Generated support information

[1221] Output: Support information sent to the victim's device

[1222] Specific operation: The server uses the messenger app's API to send the generated support information to the victim's device.

[1223] Step 7:

[1224] The server will share the consultation details in order to collaborate with local governments and the government.

[1225] Input: victim's counseling content and perceived emotional state

[1226] Output: Information shared with local governments and governments

[1227] Specific operation: The server transmits the details of the victim's consultation and their recognized emotional state to local government and government systems to coordinate with them.

[1228] Example 2

[1229] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[1230] There is a need to reduce the fear and anxiety that disaster victims feel during disasters and provide them with appropriate information quickly. However, conventional systems have difficulty providing information that takes into account the emotions of disaster victims, and there are cases where the information that disaster victims need cannot be provided appropriately. In addition, there is a problem that cooperation with local governments and the national government is insufficient, and support for disaster victims is not optimized.

[1231] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1232] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are struggling with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice or guide users to useful information and suggest actions based on the received answer, a means for coordinating the consultation content with a local government or the government, a means for sending a message from the disaster victim to an emotion analysis engine and identifying emotions, a means for selecting information to be provided according to the identified emotions, and a means for returning the selected information to the disaster victim. This makes it possible to provide appropriate information that takes into account the emotions of the disaster victim, and to optimize support for the disaster victim through collaboration with the local government or the government.

[1233] "Disaster Victim" refers to an individual or group affected by a disaster.

[1234] "Means for sending a message" refers to a communication means for sending a message, such as text or voice, to a disaster victim.

[1235] "Means of receiving a response" refers to the means of communication for receiving replies or responses from disaster victims.

[1236] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate consultation and information.

[1237] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to the means by which the generative AI provides appropriate consultation content and useful information based on the victims' responses, and suggests specific actions.

[1238] "Means of collaboration with local governments and the government" refers to the means of sharing information about disaster victims and the details of their concerns with local governments and government agencies, and working together to carry out support activities.

[1239] An "emotion analysis engine" refers to a system that analyzes messages from disaster victims and identifies their emotions from their content.

[1240] "Means for identifying emotions" refers to means for identifying emotions of a disaster victim using an emotion analysis engine.

[1241] "Means for selecting information to provide" refers to means for selecting appropriate information to provide to disaster victims according to the identified emotions.

[1242] "Means of returning information" refers to the means of communication for returning selected information to the disaster victims.

[1243] The present invention is a system that receives messages from disaster victims, analyzes their emotions, and provides appropriate information. A specific embodiment of this system is described below.

[1244] System Configuration

[1245] The server receives messages from disaster victims using communication means such as a messenger app, an internet search tool, etc. For example, messages from disaster victims can be received using an official account of a messenger app.

[1246] The server then sends the received messages to a sentiment analysis engine, which uses natural language processing technology to analyze the content of the messages and identify the emotions of the victims. For example, the Google Cloud Natural Language API can be used to detect emotions such as "fear" and "anxiety" from the messages of the victims.

[1247] After the emotion analysis engine identifies the emotion, the server selects the information to provide according to that emotion. For example, if it determines that the victim is feeling "anxiety," the server will prioritize information that provides a sense of security, such as "how to act safely in the event of an earthquake" and "information on evacuation sites." The server extracts appropriate information from a database of information prepared in advance.

[1248] Finally, the server sends the selected information back to the victim via the messenger app. For example, it sends specific advice such as, "If an earthquake occurs, first ensure your safety and move to a shelter. Information on evacuation shelters is available here." The server uses the API of the messenger app to send the reply message.

[1249] Examples

[1250] As a concrete example, consider the case where a disaster victim sends a message via a messenger app saying, "I'm scared of earthquakes. What should I do?" The server that receives this message sends it to an emotion analysis engine, which detects "fear." Based on the results, the server prioritizes sending information that provides a sense of security to the disaster victim, such as "how to act safely in the event of an earthquake" and "information on evacuation sites."

[1251] Examples of prompt statements

[1252] Examples of prompts to be input to a generative AI model include:

[1253] "Analyze messages from disaster victims and identify their emotions. Then suggest ways to provide appropriate information based on those emotions. For example, if a disaster victim sends a message saying, 'I'm scared of the earthquake. What should I do?', show them what information they should provide."

[1254] In this way, it will be possible to provide appropriate information that takes into account the feelings of disaster victims, and support for disaster victims can be optimized through collaboration with local governments and the national government.

[1255] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1256] Step 1:

[1257] The server uses the messenger app's API to receive messages from disaster victims in real time.

[1258] Input: Message from the victim (e.g. "I'm scared of the earthquake. What should I do?")

[1259] Output: Received message data

[1260] Specific operation: The server receives messages sent by disaster victims through the official account of the messenger app. The received messages are stored on the server in text format.

[1261] Step 2:

[1262] The server sends the received message to a sentiment analysis engine.

[1263] Input: Received message data

[1264] Output: Emotion identification by the emotion analysis engine (e.g. "fear")

[1265] How it works: The server uses a sentiment analysis engine, such as the Google Cloud Natural Language API, to analyze the content of the received message. The sentiment analysis engine uses natural language processing techniques to identify the sentiment of the message and returns the results to the server.

[1266] Step 3:

[1267] The server selects information to provide to disaster victims based on the emotional information obtained from the emotion analysis engine.

[1268] Input: Emotion identification result (e.g. "fear")

[1269] Output: Selected information (e.g. "How to act safely in the event of an earthquake")

[1270] Specific operation: The server extracts appropriate information from a pre-prepared information database based on the emotion identification results returned by the emotion analysis engine. For example, if the victim is feeling "fear," the server selects information that provides a sense of security, such as "how to act safely in the event of an earthquake" and "information on evacuation sites."

[1271] Step 4:

[1272] The server then sends the selected information back to the victim via a messenger app.

[1273] Input: Selected information (e.g. "How to act safely in the event of an earthquake")

[1274] Output: Reply message to the victim

[1275] Specific operation: The server uses the API of the messenger app to send the selected information back to the victim. For example, it sends specific advice such as, "If an earthquake occurs, first ensure your safety and move to a shelter. Information on evacuation shelters is available here."

[1276] (Application example 2)

[1277] Next, a description will be given of Application Example 2 of Form 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".

[1278] Conventional victim support systems provide uniform information without considering the emotional state of the victim, which means that the anxiety and fear felt by the victim cannot be fully alleviated. In addition, there is a lack of means to provide appropriate support information according to the victim's emotions, making it difficult to alleviate the psychological burden on the victim.

[1279] 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.

[1280] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are struggling with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice and guidance to useful information and suggest actions based on the received answer, a means for coordinating the consultation content with a local government or the government, a means for analyzing the emotional state of the disaster victim using an emotion engine and adjusting the method of providing information according to the emotion, and a means for preferentially providing information that provides a sense of security based on the emotional state of the disaster victim. This makes it possible to provide appropriate information according to the emotional state of the disaster victim, thereby reducing the anxiety and fear of the disaster victim and reducing the psychological burden.

[1281] "Disaster Victim" refers to an individual or group affected by a natural or man-made disaster.

[1282] "Means for sending a message" refers to a communication means for sending information to disaster victims in the form of text, voice, or the like.

[1283] "Means of receiving a response" refers to the means of communication for receiving responses or feedback from affected people.

[1284] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate consultation and information.

[1285] "Means of providing consultation, directing people to useful information, and suggesting actions" refers to means of providing appropriate advice and information based on the situation of disaster victims and suggesting specific actions to take.

[1286] "Means of cooperation with local governments and the government" refers to means for sharing information and cooperating with local governments and government agencies to provide support to disaster victims.

[1287] An "emotion engine" refers to technology that analyzes the emotional state of disaster victims and adjusts the way information is provided based on the results.

[1288] "Emotional state" refers to the psychological state, such as anxiety, fear, or relief, felt by the disaster victim.

[1289] "Measures to adjust the method of providing information" refers to measures for changing the content and format of the information provided depending on the emotional state of the disaster victims.

[1290] "Information that provides a sense of security" refers to information that reduces the anxiety and fear of disaster victims and gives them a sense of security.

[1291] The system for implementing this invention is realized by installing a disaster victim support application on a smartphone. This application receives messages from disaster victims, analyzes the messages using an emotion engine, and provides appropriate information according to the emotional state of the disaster victim.

[1292] The server has a means to send a message to the disaster victims asking "Is there anything you need help with?" This means uses a Messenger API to send a text message. The server also uses a Messenger API to receive responses from the disaster victims, and receives messages sent by the disaster victims.

[1293] Incoming messages are analyzed using an emotion engine, which uses the TextBlob library to analyze the emotional state of the message and classify it as positive, negative, or neutral. Based on this emotional state, a generative AI provides appropriate information.

[1294] For example, if a disaster victim sends a message saying, "I'm so scared. Please help me," the emotion engine will analyze this message as a negative emotion. Based on this negative emotion, the generative AI will prioritize providing information like, "Don't worry. Help is on the way soon."

[1295] This system will also work with local governments and the government to share information on the emotional state of disaster victims and the support they need, optimizing support for disaster victims. This will reduce the anxiety and fear of disaster victims and ease their psychological burden.

[1296] As an illustration, consider the following prompt:

[1297] Message from survivor: "I'm so scared. Please help."

[1298] Sentiment analysis result: Negative

[1299] Provide information: "Don't worry, help is on the way."

[1300] In this way, it is possible to provide appropriate information according to the emotional state of the victim, thereby reducing the victim's anxiety and fear.

[1301] The flow of the identification process in the application example 2 will be described with reference to FIG.

[1302] Step 1:

[1303] The server sends a message to the victim asking, "Is there anything you need help with?" The victim's contact information is required as input, and the message is displayed on the victim's smartphone as output. The specific operation is to send a text message using a messenger API.

[1304] Step 2:

[1305] The user (victim) sends a response to the message sent from the server. The input is the victim's text message, and the output is the response being sent to the server. The specific operation is that the victim enters a text message using a messenger app on their smartphone and presses the send button.

[1306] Step 3:

[1307] The server receives responses from the victims. The input requires a text message sent by the victim, and the output is that the received message is stored on the server. Specifically, the server receives messages using a messenger API and stores them in a database.

[1308] Step 4:

[1309] The server analyzes the received messages with an emotion engine. As input, it requires the text messages of the victims, and as output, it obtains their emotional state (positive, negative, neutral). Specifically, it uses the TextBlob library to analyze the emotions of the messages and classify the emotional state.

[1310] Step 5:

[1311] The server uses a generative AI to generate appropriate information based on the emotional state. The inputs required are the emotional state and the victim's text message, and the output is information to be provided to the victim. The specific operation is to use a generative AI model to generate information according to the emotional state.

[1312] Step 6:

[1313] The server provides the generated information to the disaster victims. The generated information is required as input, and the information is displayed on the disaster victim's smartphone as output. The specific operation is to send the generated information as a text message using a messenger API.

[1314] Step 7:

[1315] The server shares the emotional state of the victims and the necessary support information with the local government or government. The inputs are the emotional state of the victims and the support information, and the output is to send the information to the local government or government. The specific operation is to send the information to the local government or government system using API.

[1316] Step 8:

[1317] Local governments and governments optimize support for disaster victims based on the received information. The inputs are the emotional state and support information sent from the server, and the output is the creation of an optimized support plan. The specific operation is to analyze the received information and create a support plan.

[1318] Example 3

[1319] Next, a third embodiment of the third embodiment will be described. 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".

[1320] There is a need to provide prompt and appropriate support for the problems that disaster victims face during disasters. However, conventional systems have the challenge of being unable to accurately grasp the specific needs and emotional state of disaster victims and provide appropriate information and support based on that. In addition, there is insufficient cooperation with local governments and the national government, making it difficult to optimize support.

[1321] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1322] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for analyzing the message based on the received response using natural language processing technology, a means for extracting keywords from the analysis result, a means for providing appropriate information based on the extracted keywords, a means for analyzing the emotional state of the disaster victim using emotion analysis technology, a means for reporting to the local government or the government based on the result of the emotion analysis, and a means for coordinating with the local government or the government regarding the consultation content. This makes it possible to accurately grasp the specific needs and emotional state of the disaster victim, and to provide prompt and appropriate information and support based on the grasp. It is also possible to strengthen cooperation with the local government or the government and optimize support.

[1323] "Disaster Victim" refers to an individual or group affected by a disaster.

[1324] "Message" refers to text information sent by a disaster victim to the system.

[1325] "Server" refers to a computer system for receiving messages from disaster victims, analyzing them, and providing appropriate information.

[1326] "Natural language processing technology" refers to technology that enables computers to understand, analyze, and generate human language.

[1327] "Keywords" refer to important words or phrases extracted from disaster victims' messages.

[1328] "Emotion analysis technology" refers to technology for analyzing the emotional state of disaster victims from their messages.

[1329] "Local government" refers to local government entities and organizations that provide support to disaster victims.

[1330] "Government" refers to the national administrative body and organizations that provide support to disaster victims.

[1331] "Information provision" refers to the act of providing data and advice that disaster victims need.

[1332] "Collaboration" refers to multiple organizations or systems working together.

[1333] "Optimizing assistance" refers to providing assistance to disaster victims in the most effective and efficient manner possible.

[1334] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1335] The present invention is a system for providing prompt and appropriate support to disaster victims for solving problems they face during a disaster. A specific embodiment of this system will be described below.

[1336] System Configuration

[1337] This system consists of three main elements: a server, a terminal, and a user. The server is a computer system that receives messages from disaster victims, analyzes them, and provides appropriate information. The terminal is a device (such as a smartphone or PC) that disaster victims use to send messages. The user is the disaster victim themselves.

[1338] Hardware and Software Used

[1339] The server is a computer system with a powerful processor and a large amount of memory. The following software is installed on the server:

[1340] Generative AI models for implementing natural language processing techniques (e.g., Google's BERT, OpenAI's GPT-3)

[1341] Software for implementing emotion analysis technology (e.g. IBM's Watson Tone Analyzer)

[1342] Database management systems (e.g. MySQL, PostgreSQL)

[1343] Data processing and calculation

[1344] When the server receives a message from a disaster victim, it first analyzes the message using natural language processing technology. For this analysis, it uses generative AI models such as Google's BERT and OpenAI's GPT-3. It extracts keywords from the analysis results and provides appropriate information based on those keywords.

[1345] Specifically, if a disaster victim sends a message saying, "My house has been destroyed. What should I do?", the server will extract the keywords "house," "broken," and "what should I do." Based on this, the server will retrieve information about nearby evacuation shelters and contact information for repair companies from the database and provide this information to the user.

[1346] In addition, the server uses emotion analysis technology to analyze the emotional state of the victims. IBM's Watson Tone Analyzer is used for this emotion analysis. From the analysis results, it is determined whether the victims are feeling fear or anxiety. Based on the results of the emotion analysis, the server reports to local governments and the government to optimize assistance measures.

[1347] Examples and prompts

[1348] For example, if a user sends a message saying "My house is broken into, what should I do?" the server processes it as follows:

[1349] 1. The user sends a message.

[1350] 2. The server receives the message and analyzes it using Google's BERT model.

[1351] 3. The server extracts the keywords "house," "broken," and "what should I do."

[1352] 4. The server retrieves information about nearby evacuation shelters and contact information for repair companies from the database and provides it to the user.

[1353] 5. The server performs emotion analysis using IBM's Watson Tone Analyzer to detect whether the user is feeling fear or anxiety.

[1354] 6. The server reports the results of the sentiment analysis to local governments and the government in order to optimize support measures.

[1355] Examples of prompts to be input to a generative AI model include:

[1356] "Please analyze messages from disaster victims and provide them with appropriate information. Message content: 'My house has been destroyed. What should I do?'"

[1357] By using this prompt sentence, the generative AI model analyzes the message of the victim and performs processing to provide appropriate information. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1358] Step 1:

[1359] A user uses a terminal to send a response to the message "Is there anything I can help you with?". The input is the text message the user sends from the terminal. The output is the user's message received by the server.

[1360] Step 2:

[1361] The server analyzes the received message using natural language processing techniques. The input is the text message received from the user. The server analyzes the message's context and intent using a generative AI model (e.g., BERT or GPT-3). The output is the analyzed message's contextual information.

[1362] Step 3:

[1363] The server extracts keywords from the analysis results. The input is the context information of the message analyzed by natural language processing technology. The server extracts important keywords using text mining technology. The output is a list of extracted keywords.

[1364] Step 4:

[1365] The server provides appropriate information based on the extracted keywords. The input is a list of extracted keywords. The server retrieves related information from a database or external API. Specifically, the server retrieves information about nearby evacuation shelters and contact information for repair companies for the keywords "house," "broken," and "what should I do." The output is the retrieved information.

[1366] Step 5:

[1367] The server analyzes the emotional state of the victim using emotion analysis technology. The input is a text message received from a user. The server analyzes the emotional state from the message using emotion analysis software (e.g., Watson Tone Analyzer). The output is the analyzed emotional state information.

[1368] Step 6:

[1369] The server reports to the local government or government based on the results of the emotion analysis. The input is the analyzed emotional state information. The server reports to the local government or government using a data sharing means via the Internet. In concrete terms, if many victims show signs of fear or anxiety, the server provides that information to the local government or government. The output is the report information sent to the local government or government.

[1370] Step 7:

[1371] The server transmits the provided information to the user. The input is the acquired information and the analyzed emotional state information. The server transmits the appropriate information to the user's terminal. In concrete terms, the server provides the user with information on nearby evacuation shelters and contact information for repair businesses. The output is the information transmitted to the user's terminal.

[1372] (Application example 3)

[1373] Next, a description will be given of Application Example 3 of Form Example 3. 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".

[1374] In order for disaster victims to receive prompt and appropriate support during a disaster, it is necessary to accurately grasp the victim's situation and emotional state, and provide appropriate information and optimize support measures. However, conventional systems do not adequately take into account the emotional state of the victim when providing information or optimizing support measures, which can result in delays in providing the support that the victim needs.

[1375] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means. In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for consulting using a generation AI based on the received response, a means for directing the user to useful information and proposing actions, a means for coordinating the consultation content with the local government or the government, a means for analyzing the emotional state of the disaster victim, a means for adjusting the content of a report to the local government or the government based on the emotional state, and a means for transmitting data via the Internet. This makes it possible to provide information quickly and appropriately and optimize support measures taking into account the emotional state of the disaster victim.

[1376] "Victims" refers to people affected by a disaster.

[1377] "Means of sending a message" refers to a communication means for sending specific questions or information to disaster victims.

[1378] "Means of receiving a response" refers to the means of communication for receiving replies and information from disaster victims.

[1379] "Generative AI" refers to a system that uses artificial intelligence technology to generate appropriate information and suggestions based on the data it receives.

[1380] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to means of using generative AI to provide appropriate advice and information to disaster victims.

[1381] "Means of collaboration with local governments and the government" refers to means of sharing information obtained from disaster victims with local governments and government agencies and working together to carry out support activities.

[1382] "Means of analyzing emotional states" refers to technology for analyzing emotions from messages from disaster victims and understanding their state.

[1383] "Means for adjusting the content of reports" refers to means for appropriately changing the content of reports to local governments or governments based on the analyzed emotional state.

[1384] "Means for transmitting data via the Internet" refers to communication means for transmitting data using the Internet.

[1385] The system for carrying out this invention includes a means for sending a message to disaster victims asking "Is there anything you're struggling with?" and receiving a response from the disaster victim. It also includes a means for using a generation AI to provide advice, guide users to useful information, and suggest actions based on the received response. It also includes a means for coordinating the consultation content with local governments and the government, a means for analyzing the emotional state of the disaster victim, a means for adjusting the content of reports to local governments and the government based on the emotional state, and a means for transmitting data via the internet.

[1386] Hardware and software used

[1387] Hardware: Smartphones, servers

[1388] Software: Python, Transformers library, Requests library

[1389] Data processing and calculation

[1390] The server first sends a message to the victim asking, "Is there anything you need help with?" When it receives a response from the victim, it uses a generative AI model to analyze the response and provide appropriate advice, guide the victim to useful information, and suggest actions. The generative AI model uses the Transformers library to perform sentiment analysis and analyze the emotional state of the victim.

[1391] Based on the analyzed emotional state, the server adjusts the report to the local government or government. For example, if many of the victims show fear or anxiety, the server reports the information to the local government or government and uses it as reference information for taking prompt assistance measures. The data is sent via the Internet using the Requests library.

[1392] Examples

[1393] If a disaster victim sends a message saying, "My house has been destroyed. I'm very scared," the server receives the message and performs sentiment analysis using a generative AI model. If the result of the sentiment analysis is determined to be "NEGATIVE," the server reports the information to the local government or the government.

[1394] Examples of prompt statements

[1395] Please enter a message from the victim: My house is destroyed. I'm very scared.

[1396] In this way, the emotional state of the victim can be analyzed in real time and appropriate support information can be provided.

[1397] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1398] Step 1:

[1399] The server sends a message to the victim asking, "Is there anything you need help with?" The input is the victim's contact information, and the output is the sent message. This message is displayed on the victim's smartphone.

[1400] Step 2:

[1401] The victim inputs the answer using a smartphone and sends it to the server. The input is the text message entered by the victim, and the output is the answer sent to the server.

[1402] Step 3:

[1403] The server inputs the received answers into a generative AI model and performs sentiment analysis. The input is the text message from the disaster victim, and the output is the result of the sentiment analysis. Specifically, the Transformers library is used to analyze the emotional state of the message (e.g., positive, negative, neutral).

[1404] Step 4:

[1405] The server provides appropriate advice and guidance to useful information and suggests actions based on the results of the sentiment analysis. The input is the result of the sentiment analysis and the message from the victim, and the output is the generated advice and information. Using the generative AI model, appropriate advice and information is provided to the victim.

[1406] Step 5:

[1407] The server adjusts the report content to the local government or the government based on the emotional state of the victim. The input is the result of the emotion analysis and the message of the victim, and the output is the adjusted report content. If the emotional state is negative, the report content is emphasized to encourage a quick response.

[1408] Step 6:

[1409] The server sends the reconciled reports over the Internet to the local government or government. The input is the reconciled reports and the output is the submitted reports. The Requests library is used to submit the data.

[1410] Step 7:

[1411] Local governments and the government take measures to support disaster victims based on the reports they receive. The input is the report sent from the server, and the output is the support measures to be implemented. This allows disaster victims to receive prompt and appropriate support.

[1412] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1413] 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> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1414] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1415] 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 smart glasses 214.

[1416] [Third embodiment]

[1417] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1418] 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.

[1419] 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 wide area network (WAN) and / or a local area network (LAN).

[1420] 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.

[1421] 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 the voice according to instructions from the processor 46.

[1422] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1423] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1424] Fig. 6 shows an example of 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.

[1425] 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.

[1426] 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.

[1427] In the headset type terminal 314, 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.

[1428] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1429] "Example 1"

[1430] The system of the present invention uses communication means such as a messenger app or an internet search tool as a means for sending a message to disaster victims asking, "Is there anything you need help with?" For example, a message can be sent to disaster victims from an official account of a messenger app.

[1431] "Example 2"

[1432] To receive responses from disaster victims, communication methods such as messenger apps and internet search tools are used. For example, messages from disaster victims can be received from official messenger app accounts.

[1433] "Example 3"

[1434] Based on the answers received, the AI ​​can provide advice, guide users to useful information, and suggest actions, using natural language processing and machine learning technologies. For example, it can extract keywords contained in messages from disaster victims and provide appropriate information based on them.

[1435] "Example 4"

[1436] As a means of coordinating consultations with local governments and the government, data sharing methods via the Internet will be used. For example, messages from disaster victims will be collected and provided to local governments and the government to optimize support for disaster victims.

[1437] The process flow of each embodiment will be described below.

[1438] "Example 1"

[1439] Step 1: The system sends a message to the victim via the official account of the messenger app asking, "Is there anything you need help with?"

[1440] Step 2: Receive a response message from the victim, the message including information indicating the victim's problems and needs.

[1441] Step 3: Analyze the messages received and understand the information needed by the victims.

[1442] Step 4: Based on the information gathered, the generating AI provides appropriate consultation to victims, directs them to useful information, and suggests actions to take.

[1443] "Example 2"

[1444] Step 1: The system sends a message to victims via an Internet search tool asking, "Is there anything you need help with?"

[1445] Step 2: Receive a response message from the victim, the message including information indicating the victim's problems and needs.

[1446] Step 3: Analyze the messages received and understand the information needed by the victims.

[1447] Step 4: Based on the information gathered, the generating AI provides appropriate consultation to victims, directs them to useful information, and suggests actions to take.

[1448] "Example 3"

[1449] Step 1: The system aggregates messages from disaster victims.

[1450] Step 2: Provide aggregated messages to local governments and governments.

[1451] Step 3: Local governments and governments will optimize assistance to disaster victims based on the messages provided.

[1452] Example 1

[1453] Next, a description will be given of Example 1 of the embodiment 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".

[1454] There is a problem in that it is difficult for disaster victims to receive prompt and appropriate support. In particular, support is often delayed because disaster victims have limited means to properly communicate their problems. Another challenge is efficiently collecting information from disaster victims and providing optimal support in cooperation with local governments and the national government.

[1455] 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.

[1456] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for acquiring the contact information of the disaster victim from a database, a means for generating a message using the API of a messenger app, a means for sending the generated message to the disaster victim, a means for receiving a reply from the disaster victim and storing it in a database, a means for using a generation AI to provide advice based on the received reply, for directing the victim to useful information and for suggesting actions, and a means for coordinating the details of the consultation with the local government or the government. This enables the disaster victim to receive prompt and appropriate support.

[1457] "Disaster Victim" refers to an individual or group affected by a disaster.

[1458] "Means for sending messages" refers to a communication means for sending information such as text or images to disaster victims.

[1459] "Contact information" refers to information for contacting disaster victims, and includes, for example, phone numbers, email addresses, and messenger app IDs.

[1460] A "database" refers to a system that systematically stores information and allows it to be searched and updated as needed.

[1461] "Messenger App API" refers to the program interface provided by a messenger app, and means by which external systems can use the functions of a messenger app.

[1462] "Means for generating a message" refers to a program or algorithm used to create the content of the message to be sent.

[1463] "Means for receiving a reply" refers to a communication means for receiving a reply from the disaster victim.

[1464] "Generative AI" refers to a system that uses artificial intelligence technology to generate appropriate information and suggestions based on the responses of disaster victims.

[1465] "Means of providing consultation, directing people to useful information, and suggesting actions" refers to means of providing appropriate advice and information based on the situation of disaster victims and suggesting specific actions to take.

[1466] "Means of collaboration with local governments and the government" refers to means for sharing information with local governments and government agencies and working together to provide support to disaster victims.

[1467] This invention is a system for providing prompt and appropriate support to disaster victims. The system operates in cooperation with three parties: a server, a terminal, and a user.

[1468] The server runs a program to send a message to disaster victims asking, "Is there anything you need help with?" This program retrieves the contact information of the disaster victims from a database, and uses the messenger app's API to generate and send a message. Specifically, the server connects to the database using AWS's RDS (Relational Database Service) to retrieve the contact information of the disaster victims. It then uses the LINE Messaging API or Facebook Messenger API to generate a message and send it to the disaster victims.

[1469] The terminal is a device that disaster victims use to receive and reply to messages. The disaster victim opens a messenger app on their smartphone or tablet and receives messages sent from the server. The disaster victim replies to the message, and the reply is sent to the server.

[1470] The server receives replies from the victims and stores them in a database. The server receives replies from the victims using the LINE Messaging API Webhook, analyzes the content of the replies, and stores them in a database. The stored information is analyzed by a generation AI, which provides consultation to the victims, guides them to useful information, and suggests actions to take.

[1471] As a concrete example, the server runs on an AWS EC2 instance and uses the LINE Messaging API to send messages to disaster victims. The server first retrieves the LINE ID of the disaster victim from the database and calls the LINE Messaging API using that ID. It then sends a message via the API asking, "Is there anything you need help with?"

[1472] Examples of prompts to be input to a generative AI model include:

[1473] "Please create a program to send a message to disaster victims asking, 'Is there anything you need help with?' Use the official account of the messenger app and send the message using the LINE Messaging API."

[1474] In this way, the server can send messages to provide assistance to disaster victims quickly and store the replies in the database, enabling disaster victims to receive prompt and appropriate assistance.

[1475] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1476] Step 1:

[1477] The server retrieves the victim's contact information from a database.

[1478] Input: Database connection information, victim status (e.g. active)

[1479] Specific operation: The server connects to AWS RDS and executes an SQL query to obtain contact information (e.g. LINE ID) of active victims.

[1480] Output: Contact information of victims (e.g. list of LINE IDs)

[1481] Step 2:

[1482] The server generates the message using the messenger app's API.

[1483] Input: Contact information of the victim, message content (e.g. "Is there anything you need help with?")

[1484] Specific behavior: The server uses the obtained contact information to send an HTTP POST request to the LINE Messaging API or Facebook Messenger API to generate a message.

[1485] Output: API request for the generated message

[1486] Step 3:

[1487] A server-generated message is sent to the victim.

[1488] Input: The API request for the generated message

[1489] Specific operation: The server sends an API request, checks the response from the API, and verifies that the status code is 200 to confirm that the message was sent successfully.

[1490] Output: API response (e.g., successful submission status)

[1491] Step 4:

[1492] The victim receives the message and replies.

[1493] Input: Message sent to victim's device

[1494] Specific operation: The victim opens a messenger app on their smartphone or tablet and receives the message sent from the server. The victim then replies to the message.

[1495] Output: Reply message from the victim

[1496] Step 5:

[1497] The server receives replies from victims and stores them in a database.

[1498] Input: Reply message from the victim

[1499] Specific operation: The server receives replies from disaster victims using the LINE Messaging API Webhook, analyzes the contents of the replies, and stores them in a database.

[1500] Output: Responses stored in the database

[1501] Step 6:

[1502] Based on the answers received by the server, the generative AI will provide consultation, guide the user to useful information, and suggest actions.

[1503] Input: Responses stored in the database

[1504] Specific operation: The server uses the generative AI model to analyze the content of the victim's replies and generate appropriate advice, guidance to useful information, and suggestions for action.

[1505] Output: Generated consultation content and action suggestions

[1506] Step 7:

[1507] The server will share the consultation information with local governments and the government.

[1508] Input: Generated consultation content and action suggestions

[1509] Specific operation: The server connects with local government and government systems to share the generated consultation content and action suggestions.

[1510] Output: Information shared with local governments and governments

[1511] In this way, the server, terminals, and users can work together to provide quick and appropriate support to disaster victims.

[1512] (Application example 1)

[1513] Next, a description will be given of Application Example 1 of Form 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".

[1514] In order for disaster victims to receive prompt and appropriate support, it is important to accurately understand the situation and needs of the victims. However, with conventional methods, there were often delays in collecting information from victims and appropriate support was not provided. In addition, there were cases where it was difficult for victims to request support themselves, resulting in delays in providing support.

[1515] 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.

[1516] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice or guide the victim to useful information and suggest actions based on the received response, a means for coordinating the consultation content with a local government or the government, a means for sending a message using an API of a messenger app, and a means for obtaining a reply using the user ID of the disaster victim. This makes it possible to quickly and accurately grasp the situation and needs of the disaster victim and provide appropriate support.

[1517] "Victims" refers to people affected by a disaster.

[1518] "Means for sending a message" refers to a communication means for sending a specific message to a disaster victim.

[1519] "Means of receiving a response" refers to the means of communication for receiving replies or responses from disaster victims.

[1520] "Generative AI" refers to a system that uses artificial intelligence technology to analyze the responses of disaster victims and provide appropriate information and suggested actions.

[1521] "Means of providing consultation, directing users to useful information, and suggesting actions" refers to the means by which the generative AI provides necessary information and suggests appropriate actions based on the victims' responses.

[1522] "Means of collaboration with local governments and the government" refers to the means of sharing the consultation details and needs of disaster victims with local governments and government agencies, and of coordinating support activities.

[1523] "Messenger app API" refers to the program interface provided by a messenger application that can be used to send and receive messages.

[1524] "User ID" refers to a unique identifier used to identify a disaster victim.

[1525] "Means of obtaining a reply" refers to a communication means for obtaining a reply from the disaster victim.

[1526] The system for carrying out the present invention provides prompt and appropriate support to disaster victims by sending them a message asking, "Is there anything you need help with?" and receiving a reply from the disaster victim. A specific embodiment of this system will be described below.

[1527] System Configuration

[1528] The system consists of the following main components:

[1529] 1. Server: Sends messages, receives responses, analyzes using generative AI, and coordinates with local governments and the government.

[1530] 2. Victim's device: A device with a messenger app installed, such as a smartphone or tablet.

[1531] 3. Generative AI model: An artificial intelligence system that analyzes responses from disaster victims and provides appropriate information and suggests actions.

[1532] Program Processing

[1533] The server performs the process in the following procedure.

[1534] 1. Send a message:

[1535] The server uses the victim's user ID to send a message to the messenger app's API asking, "Is there anything you need help with?". To do this, the server uses the requests library to send an HTTP POST request.

[1536] 2. Receiving a response:

[1537] When the victim replies to the message, the reply is sent to the server, which uses the Messenger app's API to retrieve the reply based on the victim's user ID, again using the requests library to send an HTTP GET request.

[1538] 3. Generative AI Analysis:

[1539] The server inputs the received responses into a generative AI model to generate information and action suggestions needed by disaster victims. The generative AI model uses natural language processing technology to analyze the responses and provide appropriate information.

[1540] 4. Collaboration with local governments and governments:

[1541] The server will share the information and suggestions generated by the generative AI model with local governments and government agencies to optimize support for disaster victims.

[1542] Hardware and Software Used

[1543] Hardware: Servers, smartphones, tablets

[1544] Software: Messenger app, generative AI model, requests library

[1545] Examples

[1546] For example, for victims in a disaster-hit area, the following prompt sentences are input into the generative AI model:

[1547] Example prompt:

[1548] A disaster has occurred. Please create a system to send a message to the victims asking "Is there anything you need help with?" and receive a reply. Please use the following information.

[1549] Victim's user ID: "12345"

[1550] Message: "Is there anything I can help you with?"

[1551] Messenger app API endpoint: "https: / / api.messagingapp.com"

[1552] By inputting this prompt sentence into the generative AI model, it is possible to propose specific implementation methods for a disaster victim support system.

[1553] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1554] Step 1:

[1555] The server obtains the victim's user ID and uses the messenger app's API to send a message saying "Is there anything I can help you with?". The input requires the victim's user ID and the message content, and the output is the success or failure status of the message transmission. In this step, the specific operation of sending an HTTP POST request using the requests library is performed.

[1556] Step 2:

[1557] The victim's device receives the message sent from the server and displays it to the user. As input, the message sent from the server is required, and as output, the message displayed to the user is obtained. In this step, the specific operation of the messenger app to display the message is performed.

[1558] Step 3:

[1559] The user replies to the message. The input requires the reply content entered by the user, and the output requires the reply content to be sent to the server via the messenger app. In this step, the specific actions of the user operating the messenger app to enter and send the reply are performed.

[1560] Step 4:

[1561] The server uses the API of the messenger app to get the reply based on the victim's user ID. The input requires the victim's user ID, and the output is the reply from the victim. In this step, the concrete operation of sending an HTTP GET request using the requests library is performed.

[1562] Step 5:

[1563] The server inputs the retrieved reply content into the generative AI model for analysis. The input requires the reply content from the victim, and the output is appropriate information provision and action suggestions as the analysis result. In this step, the generative AI model performs the specific operation of analyzing the reply content using natural language processing technology.

[1564] Step 6:

[1565] The server shares the information and suggestions generated by the generative AI model with the local government or government agency. As input, the analysis results of the generative AI model are required, and as output, the information and suggestions are obtained to be sent to the local government or government agency. In this step, the specific operation of the server to communicate with the local government or government agency is performed.

[1566] Step 7:

[1567] Local governments and government agencies optimize support for disaster victims based on the information and proposals received from the server. The input requires the information and proposals sent from the server, and the output is specific support activities for disaster victims. In this step, local governments and government agencies take concrete actions to plan and execute support activities.

[1568] Example 2

[1569] Next, a second embodiment of the second form will be described. 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".

[1570] It is necessary to quickly and accurately grasp the problems and difficulties that disaster victims face and provide appropriate support. However, in conventional systems, the collection and analysis of information from victims is often done manually, making it difficult to respond quickly. In addition, the provision of information and support according to the needs of victims is not adequately optimized. This can result in delays in providing the support that victims need.

[1571] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1572] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generative AI model to provide advice and guidance to useful information and suggest actions based on the received response, a means for linking the consultation content with a public institution, a means for using natural language processing technology to analyze the message, and a means for storing the analysis results and executing necessary actions. This makes it possible to quickly and accurately collect and analyze information from the disaster victim and provide appropriate support.

[1573] "Victims" refers to people affected by a disaster.

[1574] "Means for sending a message" refers to a communications means for sending a text message to a disaster victim.

[1575] "Means of receiving a response" refers to a means of communication for receiving messages sent by disaster victims.

[1576] A "generative AI model" refers to a model that uses artificial intelligence technology to analyze messages from disaster victims and generate appropriate information and suggestions.

[1577] "Means of providing consultation, guidance to useful information, and suggested actions" refers to the use of generative AI models to provide appropriate advice and information to disaster victims.

[1578] "Public institutions" refers to public institutions such as local governments and governments.

[1579] "Natural language processing technology" refers to technology for analyzing human language and understanding its meaning.

[1580] "Means for storing the analysis results" refers to means for storing the analyzed information in a database or the like.

[1581] "Means of taking necessary actions" refers to the means of carrying out appropriate responses and support based on the analysis results.

[1582] The present invention is a system for quickly and accurately collecting and analyzing information from disaster victims, and providing appropriate support. A specific embodiment of this system will be described below.

[1583] The server has a means to send a message to the disaster victims asking, "Is there anything you need help with?". This means uses the API of a messenger app (for example, the LINE Messaging API or the Facebook Graph API). The server sends messages to the disaster victims through these APIs and receives responses.

[1584] The server has a means of receiving responses from disaster victims. The received messages are stored in a database. The server uses natural language processing technology to analyze the received messages. Specifically, it uses Google Cloud Natural Language API and IBM Watson Natural Language Understanding. This allows it to analyze the content of the messages and extract important information.

[1585] The server uses the generative AI model to analyze messages from disaster victims and generate appropriate information and suggestions. The generative AI model provides information and suggests actions according to the needs of the disaster victim. For example, it extracts the information "Arrived at the evacuation shelter" from the message "Arrived at the evacuation shelter" and sends a notification to the evacuation shelter manager.

[1586] The server stores the analysis results in a database and has the means to take necessary actions, such as using an email sending API (e.g., the SendGrid API) or a notification system, to respond appropriately or provide assistance based on the analysis results.

[1587] The terminal is a device that disaster victims use to send messages. This can be a smartphone, tablet, or computer. Disaster victims can use a messenger app to send messages to the official account. For example, they can send messages such as "We have arrived at the evacuation shelter" or "Food is running low."

[1588] A user (disaster victim) sends a message to the official account using a messenger app. As a concrete example, consider a case where a disaster victim sends a message to the official LINE account saying "I have arrived at the evacuation shelter." The server receives this message, analyzes it using the Google Cloud Natural Language API, and extracts the information that "I have arrived at the evacuation shelter."

[1589] Examples of prompt sentences to be input to a generative AI model include the following:

[1590] Example prompt:

[1591] "Please analyze the messages from the disaster victims and extract the necessary information. The message content is 'I have arrived at the evacuation shelter.'"

[1592] By inputting this prompt sentence into a generative AI model, the model will provide an analysis of the message, for example extracting the information "arrived at the evacuation shelter."

[1593] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1594] Step 1:

[1595] A user sends a message using a messenger app.

[1596] Specifically, a user opens a messenger app on a smartphone, tablet, or other device, types a message to the official account such as "I've arrived at the evacuation shelter" or "There is a shortage of food," and presses the send button.

[1597] Input: The message entered by the user.

[1598] Output: Messages sent through the Messenger app

[1599] Step 2:

[1600] The server receives the message.

[1601] Specifically, the server receives messages sent by users using the API of the messenger app. For example, it uses the LINE Messaging API or the Facebook Graph API to obtain message data. The server then stores the received messages in a database.

[1602] Input: Message sent from Messenger app

[1603] Output: Message data stored in the database

[1604] Step 3:

[1605] The server parses the message.

[1606] Specifically, the server uses natural language processing technology to analyze the received messages. Specifically, it uses Google Cloud Natural Language API and IBM Watson Natural Language Understanding. The server analyzes the content of the messages and extracts important information.

[1607] Input: Message data stored in the database

[1608] Output: Analyzed information (e.g. "arrived at evacuation shelter")

[1609] Step 4:

[1610] The server stores the analysis results and performs the necessary actions.

[1611] Specifically, the server saves the analysis results in a database. It then executes actions as necessary. For example, it can send a notification to the shelter manager or arrange for relief supplies. To do this, it uses an email sending API or a notification system.

[1612] Input: Parsed information

[1613] Output: Actions taken (e.g. notifications sent to shelter administrators)

[1614] (Application example 2)

[1615] Next, a description will be given of Application Example 2 of Form 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".

[1616] In the event of a disaster, it is difficult for victims to receive prompt and appropriate support. In particular, delays in collecting information from victims and responding appropriately based on that information can threaten the safety and livelihood of victims. In addition, insufficient cooperation with local governments and the national government makes it difficult to optimize support.

[1617] 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. In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you are having trouble with?", a means for receiving a response from the disaster victim, a means for consulting using a generative AI model, guiding the victim to useful information, and proposing actions based on the received response, a means for generating an appropriate response to the message from the disaster victim using the generative AI model, and a means for coordinating the consultation content with the local government or the government. This makes it possible to quickly collect information from the disaster victim and provide appropriate support. Furthermore, by strengthening cooperation with the local government or the government, optimization of support can be achieved.

[1618] "Victims" refers to people affected by a disaster.

[1619] "Means for sending a message" refers to a communication means for sending a specific message to a disaster victim.

[1620] "Means of receiving responses" refers to the means of communication for receiving messages and information from disaster victims.

[1621] A "generative AI model" refers to a model that uses artificial intelligence to generate appropriate responses and suggestions to messages from disaster victims.

[1622] "Means of providing consultation, directing people to useful information, and suggesting actions" refers to means of providing appropriate consultation and useful information based on information from disaster victims, and suggesting specific actions.

[1623] "Means of collaboration with local governments and the government" refers to the means of sharing information about disaster victims and the details of their concerns with local governments and government agencies, and working together to provide support.

[1624] "Means for generating an appropriate response" refers to means for automatically generating an appropriate response to a message from a disaster victim using a generative AI model.

[1625] A system for implementing this invention includes means for sending a message to disaster victims asking "Is there anything you need help with?", means for receiving responses from disaster victims, means for using a generative AI model to provide advice and guide users to useful information and suggest actions based on the received answers, means for generating appropriate responses to messages from disaster victims using the generative AI model, and means for coordinating the content of the consultation with local governments and the government.

[1626] Hardware and Software Used

[1627] Hardware: Smartphones, servers

[1628] Software: Messenger apps (e.g. LINE, WhatsApp), OpenAI API

[1629] Data processing and calculation

[1630] 1. Sending a message: The server uses the messenger app's API to send a message to the victim asking, "Is there anything you need help with?"

[1631] 2. Receiving response: The server receives the response sent by the victim through the messenger app.

[1632] 3. Response generation using a generative AI model: The server inputs the received answer into a generative AI model (e.g., OpenAI GPT-3) to generate an appropriate response.

[1633] 4. Providing a response: The server provides the generated response to the victim.

[1634] 5. Collaboration with local governments and the government: The server will share information and inquiries from disaster victims with local governments and government agencies, and work together to provide support.

[1635] Examples

[1636] If the server receives a message from a victim saying, "Your house is flooded and you need to evacuate," it will use the generative AI model to generate a response such as, "Please evacuate to a nearby evacuation shelter. Please let us know if you need any assistance," and provide this to the victim.

[1637] Examples of prompt statements

[1638] Message from the victim: My house is flooded and I need to evacuate

[1639] Generate an appropriate response.

[1640] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1641] Step 1:

[1642] The server uses the messenger app's API to send a message to the victim asking, "Is there anything you need help with?"

[1643] Input: Victim's contact information

[1644] Output: Message sent to victim

[1645] Specific operation: The server sends an HTTP request to the API endpoint of the messenger app to send a message to the victim.

[1646] Step 2:

[1647] The user (victim) sends the response via a messenger app.

[1648] Input: Victim's response message

[1649] Output: Reply message sent to messenger app

[1650] What happens: A victim uses a messenger app to type a text message and presses send.

[1651] Step 3:

[1652] The server receives the responses from the victims.

[1653] Input: Message sent by victim

[1654] Output: Message data of victims stored on the server

[1655] Specific operation: The server stores messages received through the messenger app's API in a database.

[1656] Step 4:

[1657] The server inputs the received answers into a generative AI model to generate an appropriate response.

[1658] Input: Message data from victims

[1659] Output: The generated response message

[1660] Specific operation: The server sends an API request to a generative AI model (e.g., OpenAI GPT-3) and generates an appropriate response using the prompt sentence as input.

[1661] Step 5:

[1662] The server provides the generated response to the victim.

[1663] Input: The generated response message

[1664] Output: Response message sent to victim

[1665] Specific operation: The server generates a response message using the messenger app's API and sends it to the victim.

[1666] Step 6:

[1667] The server will share information and consultation details from disaster victims with local governments and government agencies.

[1668] Input: victim's message data and generated response message

[1669] Output: Information sent to local government or government agencies

[1670] Specific operation: The server sends an HTTP request to the API endpoint of a local government or government agency to share information about disaster victims.

[1671] Example 3

[1672] Next, a third embodiment of the third embodiment will be described. 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".

[1673] There is a problem in that it is difficult to provide disaster victims with the information they need quickly and accurately. It is also difficult to effectively communicate with local governments and the government on the content of inquiries from disaster victims and optimize support.

[1674] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for extracting keywords based on the received response using natural language processing technology, a means for generating appropriate information using a generative AI model based on the extracted keywords, a means for providing the generated information to the disaster victim, and a means for coordinating the consultation content with a local government or the government. This makes it possible to quickly and accurately provide the information required by the disaster victim and optimize support through cooperation with the local government or the government.

[1675] "Disaster Victim" refers to an individual or group affected by a disaster.

[1676] "Means for sending a message" refers to a communication means for sending information to disaster victims in the form of text, voice, or the like.

[1677] "Means of receiving a response" refers to the means of communication for receiving responses or feedback from affected people.

[1678] "Natural language processing technology" refers to technology that enables computers to understand, analyze, and generate human language.

[1679] "Keyword extraction means" refers to techniques for identifying and extracting important words and phrases from received text data.

[1680] A "generative AI model" refers to a model that uses artificial intelligence to generate appropriate responses or information based on input data.

[1681] "Means for generating information" refers to technology for using a generative AI model to create appropriate information based on extracted keywords.

[1682] "Means for providing information" refers to communication means for conveying the generated information to disaster victims.

[1683] "Means of collaboration with local governments and the government" refers to means for sharing information from disaster victims with local governments and government agencies and working together to carry out relief activities.

[1684] This invention is a system that quickly and accurately provides disaster victims with the information they need in the event of a disaster, and optimizes support through cooperation with local governments and the government. This system operates in cooperation with three parties: a server, a terminal, and a user.

[1685] Hardware and Software Used

[1686] Server: Use a server with high-performance computing power. The server plays a central role in receiving, analyzing, generating, and transmitting data.

[1687] Terminal: A device used by a user, such as a smartphone, tablet, or computer. The terminal sends messages from the user and receives information from the server.

[1688] Natural language processing technology: Uses Python libraries NLTK and spaCy to extract keywords from messages.

[1689] Generative AI models: Generative AI models such as OpenAI's GPT-4 are used to generate appropriate information based on the extracted keywords.

[1690] Program Processing

[1691] 1. Receiving a message from a user

[1692] A user uses a terminal to send a message. For example, the user types, "Please tell me where the evacuation shelter is" and presses the send button.

[1693] The terminal sends a message to the server.

[1694] 2. Extracting keywords from messages

[1695] The server analyzes the received messages using natural language processing techniques, specifically using Python's NLTK and spaCy to extract important keywords from the messages.

[1696] For example, from the message "Please tell me where the evacuation shelter is," the keywords "evacuation shelter" and "location" are extracted.

[1697] 3. Producing the right information

[1698] The server uses a generative AI model to generate appropriate information based on the extracted keywords. A prompt sentence is input to the generative AI model to generate a response.

[1699] For example, a prompt sentence such as "Please tell me where the evacuation shelter is" can be input into a generative AI model, and the model can generate the information, "The nearest evacuation shelter is next to City Hall. The address is XX."

[1700] 4. Provision of generated information

[1701] The server transmits the generated information to the terminal, which then displays the received information to the user.

[1702] For example, the user's screen might display, "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[1703] 5. Data aggregation and sharing

[1704] The server stores messages from users in a database. Periodically, the server aggregates the stored data and provides it to local governments and governments.

[1705] Use a secure internet connection (e.g., HTTPS) for data sharing.

[1706] Examples

[1707] User message: "Where are the evacuation shelters?"

[1708] Keyword extraction: "shelter", "place"

[1709] Prompt for generative AI model: "When asked where the evacuation shelters are located, please provide the appropriate evacuation shelter information."

[1710] Generated information: "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[1711] This system is a powerful tool for providing support to disaster victims quickly and accurately. By combining natural language processing technology and generative AI models, it realizes optimization of information provision and support according to user needs. The flow of the identification process in the third embodiment will be explained with reference to FIG. 15.

[1712] Step 1:

[1713] Receiving messages from users

[1714] Input: A user uses a device to type a message and presses the send button. For example, "Please tell me where the evacuation shelters are."

[1715] Specific operation: The terminal sends the user's message to the server as an HTTP request.

[1716] Output: The server stores the received message in a database and passes it on to the next processing step.

[1717] Step 2:

[1718] Extracting keywords from messages

[1719] Input: The user's message received by the server. For example, "Please tell me where the evacuation shelter is."

[1720] What it does: The server uses natural language processing libraries such as Python's NLTK or spaCy to extract important keywords from messages.

[1721] Data processing: Tokenize messages, tag parts of speech, and extract key keywords.

[1722] Output: Extracted keywords, e.g. "shelter", "location".

[1723] Step 3:

[1724] Producing the right information

[1725] Input: Extracted keywords, e.g. "shelter", "location".

[1726] Specific operation: The server creates and inputs a prompt sentence to the generative AI model (e.g., GPT-4).

[1727] Data calculation: The generative AI model generates appropriate information based on the prompt.

[1728] Output: The generated information. For example, "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[1729] Step 4:

[1730] Providing generated information

[1731] Input: Generated information. For example, "The nearest evacuation shelter is next to ____ City Hall. The address is ____."

[1732] Specific operation: The server sends the generated information to the terminal as an HTTP response.

[1733] Output: The device displays the received information to the user. For example, the user's screen might display "The nearest evacuation shelter is next to XX City Hall. The address is XX."

[1734] Step 5:

[1735] Data aggregation and sharing

[1736] Input: Message from user and generated information.

[1737] What happens: The server stores this data in a database and aggregates it periodically.

[1738] Data processing: Collecting and analyzing stored data.

[1739] Output: Provide aggregated data to local governments and / or governments using a secure internet connection (e.g. HTTPS) to share data.

[1740] (Application example 3)

[1741] Next, a description will be given of Application Example 3 of Form Example 3. 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".

[1742] There is a problem that it is difficult for disaster victims to quickly obtain appropriate information in an emergency. In addition, there is a problem that support for disaster victims is not optimized due to insufficient cooperation with local governments and the government. Furthermore, there is a lack of means to efficiently process messages from disaster victims and propose appropriate actions.

[1743] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1744] In this invention, the server includes a means for sending a message to the disaster victim saying "Is there anything you need help with?", a means for receiving a response from the disaster victim, a means for using a generation AI to provide advice and guidance to useful information and suggest actions based on the received answer, a means for coordinating the consultation content with a local government or the government, a means for extracting keywords from the message from the disaster victim using natural language processing technology, a means for providing appropriate information based on the extracted keywords, and a means for sharing the message from the disaster victim with the local government or the government. This enables the disaster victim to quickly obtain appropriate information, strengthens cooperation with the local government or the government, and optimizes support for the disaster victim.

[1745] "Disaster Victim" refers to an individual or group of people affected by a disaster or emergency.

[1746] "Message" refers to text data sent to disaster victims to ask questions or provide information.

[1747] "Response" refers to a reply or response to a message sent by a disaster victim.

[1748] "Generative AI" refers to a system that uses artificial intelligence technology to provide information and suggest actions based on the data it receives.

[1749] "Consultation" refers to the act of providing advice and solutions to problems and questions that disaster victims have.

[1750] "Useful information" refers to information that is important and useful to disaster victims.

[1751] "Suggested actions" refers to advice that provides specific actions that survivors should take.

[1752] "Local government" refers to local public entities, specifically including cities, towns, villages, and prefectures.

[1753] "Government" refers to the administrative organs of a nation, including central and local governments.

[1754] "Collaboration" refers to different organizations and agencies working together to share information and respond jointly.

[1755] "Natural language processing technology" refers to technology that enables computers to understand and process human language.

[1756] "Keywords" refer to important words or phrases extracted from a message.

[1757] "Means of providing information" refers to the method of conveying appropriate information to disaster victims based on the extracted keywords.

[1758] "Means of sharing data" refers to the methods of conveying messages from disaster victims to local governments and the government.

[1759] The system for implementing this invention has the function of sending a message to disaster victims asking "Is there anything you are struggling with?" and receiving responses from them. Based on the responses received, a generative AI model is used to provide advice, guide users to useful information, and suggest actions. It also has the function of sharing the details of consultations with local governments and the national government.

[1760] Hardware and Software Used

[1761] Hardware: Smartphones, servers

[1762] Software: Python, spaCy, Transformers library

[1763] Data processing and calculation

[1764] 1. Message transmission: The server sends a message to the disaster victim asking, "Is there anything you need help with?" This message is sent as text data.

[1765] 2. Response reception: The server receives the responses from the victims. The received responses are stored as text data.

[1766] 3. Keyword extraction: The server uses natural language processing technology (spaCy) to extract keywords from messages from disaster victims. The extracted keywords are compiled into a list of important words and phrases.

[1767] 4. Information provision: Based on the extracted keywords, the server uses a generative AI model (Transformers library) to provide appropriate information, such as the location of evacuation shelters and emergency contact information.

[1768] 5. Data sharing: The server shares messages from disaster victims with local governments and the government. This sharing is done via the Internet.

[1769] Examples

[1770] For example, if a disaster victim sends a message saying, "My house is flooded and I need to evacuate. Where should I go?", the server receives this message and uses natural language processing technology to extract the keywords "flooded," "evacuation," and "where should I go." It then uses a generative AI model to provide the location of the evacuation shelter. This message is also shared with local governments and the government, enabling them to provide rapid assistance.

[1771] Examples of prompt statements

[1772] Please receive messages from disaster victims, extract keywords, and provide appropriate information. Also, please tell us how to share the messages with local governments and the government.

[1773] In this way, a specific embodiment for carrying out the invention has been shown, which enables disaster victims to quickly obtain appropriate information, strengthens cooperation with local governments and the government, and optimizes support for disaster victims.

[1774] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1775] Step 1:

[1776] The server sends a message to the victim asking, "Is there anything you need help with?"

[1777] Input: Victim's contact information

[1778] Output: The message sent.

[1779] Specific operation: The server retrieves the victim's contact information from a database and generates and sends a text message.

[1780] Step 2:

[1781] The user (victim) sends a reply to the message from the server.

[1782] Input: Message from the server

[1783] Output: Reply message from the victim

[1784] Specific operations: The victim enters a response via text message using a device such as a smartphone and sends it to the server.

[1785] Step 3:

[1786] The server receives the responses from the victims.

[1787] Input: Response message from the victim

[1788] Output: Received response message

[1789] Specific operation: The server receives messages from disaster victims via the network and stores them in a database.

[1790] Step 4:

[1791] The server uses natural language processing technology to extract keywords from messages from disaster victims.

[1792] Input: Received response message

[1793] Output: Extracted keywords

[1794] What it does: The server uses the spaCy library to parse the message and extract important words and phrases.

[1795] Step 5:

[1796] The server provides appropriate information based on the extracted keywords.

[1797] Input: Extracted keywords

[1798] Output: Information provided

[1799] Specific operation: The server runs a generative AI model using the Transformers library to generate information related to keywords and send it to the victim.

[1800] Step 6:

[1801] The server shares messages from disaster victims with local governments and the government.

[1802] Input: Received response message

[1803] Output: Message shared with local governments

[1804] Specific operation: The server sends messages via the Internet to local government and government systems for sharing.

[1805] In this manner, the specific operations performed at each processing step and their inputs and outputs have been described.

[1806] In addition, 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.

[1807] "Example 1"

[1808] In one embodiment of the present invention, the emotion engine recognizes emotions based on the response from the victim. Specifically, the emotion engine analyzes text information included in the response message from the victim and estimates the emotional state of the victim from the text information. For example, if the response message contains words such as "scary" or "anxiety," it is determined that the victim is feeling fear or anxiety.

[1809] "Example 2"

[1810] In another embodiment of the present invention, the emotion engine adjusts the consultation content and the method of providing useful information according to the emotion of the victim. Specifically, when it is determined that the victim is feeling fear or anxiety, the emotion engine adjusts the consultation content and the method of providing useful information to the victim based on the emotional state. For example, when it is determined that the victim is feeling anxiety, information that provides a sense of security is provided preferentially.

[1811] "Example 3"

[1812] In yet another embodiment of the present invention, the emotion engine adjusts the report content to the local government or government according to the emotions of the victims. Specifically, the emotion engine reports the information to the local government or government based on the emotional state of the victims. For example, if responses indicating fear or anxiety are obtained from many victims, the information is reported to the local government or government and used as reference information for optimizing support measures for the victims.

[1813] The process flow of each embodiment will be described below.

[1814] "Example 1"

[1815] Step 1: Receive a response message from the victim.

[1816] Step 2: Analyze the text information contained in the received message.

[1817] Step 3: Estimate the emotional state of the victim from the text information.

[1818] "Example 2"

[1819] Step 1: Determine the victim's emotional state.

[1820] Step 2: Adjust the content of your consultation and the way you provide useful information based on the person's emotional state.

[1821] Step 3: Provide the adjusted information to the victims.

[1822] "Example 3"

[1823] Step 1: Determine the victim's emotional state.

[1824] Step 2: Tailor your reporting based on your emotional state.

[1825] Step 3: Report the adjusted information to the local government or government.

[1826] Example 1

[1827] Next, a description will be given of Example 1 of the embodiment 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".

[1828] It is necessary to quickly grasp the anxiety and fear that disaster victims feel in the event of a disaster and provide appropriate support. However, conventional systems have difficulty accurately recognizing the emotional state of victims, making it difficult to provide appropriate support. In addition, there was a lack of means to effectively utilize information from disaster victims in cooperation with local governments and the national government.

[1829] 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.

[1830] In this invention, the server includes a means for sending a message to the disaster victim asking "Is there anything you are having troub...

Claims

1. A means for sending a message to disaster victims saying "Is there anything you need help with?" by inputting a specific prompt sentence into the generative AI model; an emotion engine that recognizes the emotion of the disaster victim based on the disaster victim's response to the message; A suggestion means for providing the victim with information that will be useful to the victim in the event of a disaster and suggesting actions that the victim should take in the event of a disaster, based on the recognized emotions, using a generative AI model; A means for adjusting the content of reports to local governments and the government at the time of a disaster based on the emotions; A means for transmitting the report to the local government and the national government via the Internet; A system including:

2. The system described in claim 1, wherein when the suggestion means determines that the victim is feeling anxious based on the recognized emotions, it provides the victim with information that will be useful to the victim, such as how to act safely in the event of an earthquake and information on evacuation sites.

3. The system according to claim 1 , wherein the suggestion means preferentially provides information that provides a sense of security to the disaster victim based on the recognized emotion.

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