System

Abstract

A system is provided.SOLUTION: This system includes a means for registering refugee information, a means for displaying the state of the refuge on a map in real time, a means for automatically calculating necessary supplies and generating a distribution plan, a means for automatically collecting information on the Internet and displaying a road damage state, a means for providing disaster prevention information, and a means for recommending a disaster kit on the basis of the individual information of the refugee.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In areas where natural disasters such as earthquakes occur frequently, it is difficult to predict where a disaster will occur, and there is a need to quickly and efficiently distribute necessary supplies to disaster victims and evacuation centers. It is also important to grasp the situation at evacuation centers in real time and provide accurate information, including road damage status. Furthermore, there is a need to distribute supplies that meet the individual needs of evacuees and recommend disaster prevention goods. However, current systems have difficulty meeting these needs, and there is a risk of support being delayed due to information delays or errors. The present invention aims to solve these problems and provide a system that enables rapid and accurate response. [Means for solving the problem]

[0005] The present invention is a system that includes a means for registering evacuee information, a means for displaying the status of evacuation shelters on a map in real time, a means for automatically calculating the amount of supplies needed and generating a distribution plan, a means for automatically collecting information from the Internet and displaying road damage status, a means for providing disaster prevention information, and a means for recommending disaster prevention goods based on individual evacuees' information. This system allows detailed registration of evacuee information and evacuation shelter status using video and audio, making it possible to create accurate and prompt support plans. It also allows for flexible response by accepting support requests from outside the evacuation shelter.

[0006] "Evacuee information" refers to information about people who have taken refuge in evacuation shelters during a disaster, including their names, ages, health conditions, allergy information, special needs, and the like.

[0007] "Shelter status" refers to information such as the current capacity of each shelter, necessary supplies, health status, and emergency situation.

[0008] "Displaying on the map in real time" means instantly reflecting the latest information on evacuation shelters, road conditions, etc. on the map.

[0009] "Automatic calculation of necessary supplies" means using algorithms and AI to calculate the necessary amounts of food, water, medicine, and other supplies required at each evacuation shelter based on collected information about evacuees.

[0010] "Generating a distribution plan" means automatically generating a plan for distributing what supplies and in what quantities to which shelters based on the automatically calculated required supplies.

[0011] "Automatic collection of information on the Internet" refers to the process of automatically obtaining disaster information and road condition information that is publicly available via the Internet.

[0012] "Displaying road damage status" refers to visually displaying collected road damage information on a map.

[0013] "Providing disaster prevention information" means notifying users in advance of information and measures to prepare for disasters.

[0014] "Recommend disaster prevention goods" means presenting a list of disaster prevention goods that are most suitable for a user based on the user information. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] 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.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] 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.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] 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.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] During normal times: Dissemination of disaster prevention information and advance registration

[0037] 1. Launch the app and view the latest information

[0038] The user launches the "Hoshikuru★" app on a smartphone or tablet.

[0039] The device requests the latest disaster prevention information from the server.

[0040] The server retrieves the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the terminal.

[0041] The terminal displays the received information on the disaster prevention portal screen.

[0042] 2. User Information Registration

[0043] The user opens the "Information Registration" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[0044] The terminal encrypts the entered information and sends it to the server.

[0045] The server stores the received user information in a database.

[0046] 3. Disaster Preparedness Goods Recommendations

[0047] The server generates a list of optimal anti-theft products based on the user's registered information (such as allergy information and disease history).

[0048] The server sends the generated list to the terminal.

[0049] The device displays a list of recommended disaster preparedness items to the user.

[0050] In the event of a disaster: Registration of evacuee information and visualization of supplies

[0051] 1. Launch the app at the evacuation shelter

[0052] The user arrives at an evacuation site (e.g., a community center or school) and launches the app.

[0053] The terminal displays a screen for registering evacuee information and prompts the user to enter information.

[0054] 2. Register your evacuation shelter status

[0055] Users record video or audio of the current situation at the evacuation center (e.g., food shortages, requests for medicine, etc.).

[0056] The device uploads recorded video and audio files to the server.

[0057] The server analyzes the video and audio data it receives and extracts important information (such as the number of evacuees and the supplies they need).

[0058] 3. Real-time display on the map

[0059] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[0060] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[0061] 4. Automatic calculation and display of materials

[0062] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[0063] For example, consider the number of people in the shelter, their health status, and any special needs (allergies, illnesses, etc.).

[0064] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[0065] The device displays a list of supplies needed on a map.

[0066] Specific examples

[0067] Example of normal operation

[0068] 1. Launch the app and view the latest information

[0069] User: Taro launches the "Hoshikuru★" app.

[0070] Terminal: Displays the latest typhoon information and countermeasures from the disaster prevention portal.

[0071] 2. User Information Registration

[0072] User: Taro enters his name, family members' names, and allergy information.

[0073] Terminal: Sends input information to the server and stores it.

[0074] 3. Disaster Preparedness Goods Recommendations

[0075] Server: Based on Taro's allergy information, recommend food and medicines that are suitable for specific allergies.

[0076] Device: Display a list of recommended disaster prevention items to Taro.

[0077] Example of operation during a disaster

[0078] 1. Launch the app at the evacuation shelter

[0079] User: Hanako is affected by the disaster, evacuates to the nearest community center, and launches the app.

[0080] Terminal: Display the evacuee information registration screen.

[0081] 2. Register your evacuation shelter status

[0082] User: Hanako records the situation at the evacuation center (food shortages, requests for medicine, etc.) on video.

[0083] Device: Upload the recorded video to the server.

[0084] 3. Real-time display on the map

[0085] Server: Updates the map database with information about the community center where Hanako will take refuge.

[0086] Terminal: Displays evacuation shelter information on a map in real time.

[0087] 4. Automatic calculation and display of materials

[0088] Server: The AI ​​calculates the amount of supplies needed, taking into account the number of evacuees at the community center and Hanako's special needs.

[0089] Terminal: Display a list of food, water, and medicine needed at the community center on a map.

[0090] The processing flow will be explained below.

[0091] During normal times: Dissemination of disaster prevention information and advance registration

[0092] Launching the app and displaying the latest information

[0093] Step 1:

[0094] The user launches the "Hoshikuru★" app.

[0095] The device displays the Start screen.

[0096] Step 2:

[0097] The device requests the latest disaster prevention information from the server.

[0098] Step 3:

[0099] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[0100] Step 4:

[0101] The terminal displays the received information on the disaster prevention portal screen.

[0102] Registering user information

[0103] Step 1:

[0104] The user opens the "Register" section in the app.

[0105] Step 2:

[0106] The terminal displays a form for the user to enter information such as name, age, medical history, and allergy information.

[0107] Step 3:

[0108] The user enters the required information and presses the "Save" button.

[0109] Step 4:

[0110] The terminal encrypts the entered information and sends it to the server.

[0111] Step 5:

[0112] The server stores the received information in a database.

[0113] Disaster preparedness goods recommendations

[0114] Step 1:

[0115] The server analyzes the user's registration information (e.g., allergy information and medical history).

[0116] Step 2:

[0117] Based on the analysis results, the server generates an optimal list of disaster prevention supplies.

[0118] Step 3:

[0119] The server sends the generated list to the terminal.

[0120] Step 4:

[0121] The device displays a list of recommended disaster preparedness items to the user.

[0122] In the event of a disaster: Registration of evacuee information and visualization of supplies

[0123] Launching the app at an evacuation shelter

[0124] Step 1:

[0125] The user arrives at the evacuation site and launches the app.

[0126] Step 2:

[0127] The terminal displays the evacuee information registration screen.

[0128] Registering evacuation shelter status

[0129] Step 1:

[0130] Users record video or audio of the current situation at the evacuation shelter.

[0131] Step 2:

[0132] The device uploads recorded video and audio files to the server.

[0133] Step 3:

[0134] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[0135] Real-time display on a map

[0136] Step 1:

[0137] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[0138] Step 2:

[0139] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[0140] Automatic calculation and display of materials

[0141] Step 1:

[0142] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[0143] Step 2:

[0144] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[0145] Step 3:

[0146] The device displays a list of supplies needed on a map.

[0147] Example 1

[0148] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0149] In emergencies such as natural disasters, it is difficult to quickly and accurately register information about evacuees in shelters and grasp the situation at the shelters in real time. It is also difficult to properly calculate and distribute the necessary supplies. Therefore, a system that effectively solves these issues is needed to ensure the safety and security of evacuees. Furthermore, it is also important to recommend disaster prevention goods based on the individual information of evacuees, record the current situation at the shelters using video and audio, and extract important data from that information.

[0150] 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.

[0151] In this invention, the server includes a means for registering evacuee information, a means for displaying the status of evacuation shelters on a map in real time, and a means for automatically calculating the amount of supplies needed and generating a distribution plan. This allows for quick and accurate registration of evacuee information and understanding of the real-time situation at evacuation shelters. Furthermore, by appropriately calculating and distributing the necessary supplies, the safety and security of evacuees can be ensured. Furthermore, it is possible to recommend disaster prevention goods based on individual evacuee information, record the current situation at evacuation shelters using video and audio, and extract important data from that information.

[0152] A "means for registering evacuee information" is a device or software that allows evacuees to enter their own information (such as name, age, health status, etc.) and store that information in a database.

[0153] "Means for displaying the status of evacuation centers on a map in real time" refers to a device or software that visualizes the status of evacuation centers (number of people, supply status, etc.) on a map and updates and displays the current situation in real time.

[0154] "Means for automatically calculating the amount of supplies needed and generating a distribution plan" refers to a device or software that uses AI or other data analysis technology to calculate the amount of supplies needed at evacuation shelters and automatically create a subsequent distribution plan.

[0155] "Means for automatically collecting information on the Internet and displaying the status of road damage" refers to a device or software for automatically collecting information obtained from the Internet and displaying the status of road damage caused by disasters.

[0156] The "means for providing disaster prevention information" refers to a device or software for providing users with disaster prevention information such as disaster predictions and evacuation instructions.

[0157] "Means for recommending disaster prevention goods based on individual information of evacuees" refers to a device or software that suggests the most suitable disaster prevention goods for evacuees based on individual information such as allergy information and disease history of the evacuees.

[0158] "Means for recording the current situation at the evacuation shelter using video or audio and uploading that information to a server" refers to a device or software for recording the situation at the evacuation shelter using video or audio and sending the recorded data to a server.

[0159] "Means for analyzing uploaded video and audio data and extracting important information" refers to a device or software that analyzes video and audio data uploaded to a server and automatically extracts important information such as the number of evacuees and necessary supplies.

[0160] "Means for generating a list of required supplies for each evacuation shelter and sending it to the terminal" refers to a device or software for creating a list of the amount of supplies needed at each evacuation shelter based on evacuee information and sending that list to the user's terminal.

[0161] The present invention relates to a system that registers information on evacuees, grasps the situation at evacuation shelters in real time, and appropriately calculates and distributes necessary supplies. The detailed configuration of the system of the present invention is shown below.

[0162] This system is operated by the user using a smartphone or tablet device. When the user launches the "disaster prevention app," the device communicates with the server via the internet to obtain and send the necessary information. The server uses a database and AI models to analyze and process various pieces of information. Specific hardware and software used include a smartphone, tablet, internet connection, database, and AI analysis tool.

[0163] First, the user launches the "disaster prevention app" on their smartphone or tablet device. The device then requests the latest disaster prevention information from the server via the Internet. The server then retrieves the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the device. The device then displays the received information on its screen, providing the user with the latest disaster prevention information.

[0164] Next, the user opens the "Information Registration" section in the app and enters information about themselves and their family members (such as name, age, medical history, allergies, etc.). The device encrypts the entered information using AES and sends it to the server, which then stores the received user information in a database.

[0165] The server then reads the user's registration information from the database and uses an AI model to generate a list of optimal disaster preparedness supplies that takes into account allergies and medical history. The generated disaster preparedness supply list is then sent from the server to the device and displayed on the device.

[0166] In the event of a disaster, the user reaches an evacuation site and launches the "disaster prevention app." The device displays a screen for registering evacuee information and asks the user to enter the necessary information. The user records video or audio of the current situation at the evacuation site (e.g., food shortages, requests for medicine, etc.) and uploads it to the server on the device. The server analyzes the received video and audio data using an AI analysis tool to extract important information such as food shortages and requests for medicine. The analyzed information is integrated into a map database, and the status of all evacuation sites is updated in real time. The device obtains the latest evacuation site information and displays it on a map.

[0167] The server then uses AI to calculate the amount of supplies needed based on information about the evacuees at the shelters, and generates a list of the required supplies for each shelter. The list is then sent to the device and displayed on the device.

[0168] As a concrete example, a user is affected by a disaster, evacuates to the nearest evacuation shelter, and launches a "disaster prevention app." The user records video of the situation at the evacuation shelter and uploads the video. The server analyzes the video, extracts important information, and displays it on a map. The server calculates the necessary supplies based on the evacuee's information, creates a list, and displays it on the device.

[0169] An example of a prompt sentence is, "A large-scale earthquake has occurred and I have arrived at a shelter. I would like to record a video of the situation at the shelter, upload it to the server, and receive appropriate material support. How can I do this?" By inputting such a prompt sentence into a generative AI model, detailed instructions can be automatically provided.

[0170] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0171] System program processing flow

[0172] During normal times: Dissemination of disaster prevention information and advance registration

[0173] Step 1: Launch the app and view the latest information

[0174] 1. The user launches the "disaster prevention app" on their smartphone or tablet.

[0175] Input: User initiated actions.

[0176] Output: None.

[0177] 2. The terminal sends a request for the latest disaster prevention information to the server via the Internet.

[0178] Input: App launch signal.

[0179] Output: Disaster prevention information request to the server.

[0180] 3. The server accesses the disaster prevention portal database and obtains the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.).

[0181] Input: A request from the terminal.

[0182] Output: Latest disaster prevention information data.

[0183] 4. The server sends the acquired information to the terminal.

[0184] Input: Latest disaster prevention information data.

[0185] Output: Data sent to the terminal.

[0186] 5. The terminal displays the received information on the screen, providing the user with the latest disaster prevention information.

[0187] Input: Disaster prevention information from the server.

[0188] Output: Disaster prevention information displayed on screen.

[0189] Step 2: Register user information

[0190] 1. The user opens the "Register Information" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[0191] Input: Manually enter user information.

[0192] Output: The entered user information.

[0193] 2. The terminal encrypts the user's input data using AES and sends it to the server.

[0194] Input: The user information entered.

[0195] Output: Encrypted user information data.

[0196] 3. The server stores the received user information data in a database.

[0197] Input: Encrypted user information data.

[0198] Output: User information stored in the database.

[0199] Step 3: Recommend disaster preparedness supplies

[0200] 1. The server reads the user's registration information from the database.

[0201] Input: User information retrieved from the database.

[0202] Output: User registration information.

[0203] 2. The server uses an AI model to generate a list of disaster preparedness items tailored to each user based on their registration information.

[0204] Input: User registration information.

[0205] Output: The generated disaster preparedness kit list.

[0206] 3. The server sends the generated disaster prevention goods list to the terminal.

[0207] Input: The generated disaster preparedness kit list.

[0208] Output: Data sent to the terminal.

[0209] 4. The device will display a list of recommended disaster preparedness items on the screen.

[0210] Input: Disaster preparedness supplies list from the server.

[0211] Output: Screen display of disaster preparedness item list.

[0212] In the event of a disaster: Registration of evacuee information and visualization of supplies

[0213] Step 1: Launch the app at the evacuation shelter

[0214] 1. The user arrives at the evacuation site and launches the app.

[0215] Input: User operation to launch the app.

[0216] Output: None.

[0217] 2. The terminal displays the evacuee information registration screen and prompts the user to enter information.

[0218] Input: App launch signal.

[0219] Output: Display of evacuee information registration screen.

[0220] Step 2: Register your evacuation status

[0221] 1. Users record video or audio of the current situation at the evacuation shelter.

[0222] Input: Shelter situation.

[0223] Output: Recorded video and audio files.

[0224] 2. The device uploads the recorded video and audio files to the server.

[0225] Input: Recorded video and audio files.

[0226] Output: Upload data to server.

[0227] 3. The server uses AI analysis tools to analyze the video and audio data received and extract important information such as food shortages and requests for medicine.

[0228] Input: Uploaded video and audio data.

[0229] Output: Important information data of the analysis results.

[0230] Step 3: Real-time display on a map

[0231] 1. The server integrates the analyzed information into a map database and updates the real-time status of all evacuation centers.

[0232] Input: Important information data of the analysis results.

[0233] Output: Updated map database.

[0234] 2. The device retrieves the latest evacuation shelter information from the server and displays that information on a map.

[0235] Input: Shelter information data from the server.

[0236] Output: Real-time display on map.

[0237] Step 4: Automatic calculation and display of materials

[0238] 1. The server uses AI to calculate the amount of supplies needed based on information about evacuees at shelters.

[0239] Input: Evacuee information data.

[0240] Output: Calculated material requirements data.

[0241] 2. The server generates a list of required supplies for each evacuation shelter.

[0242] Input: Material requirements data.

[0243] Output: List of supplies required.

[0244] 3. The server sends the list of required supplies to the terminal.

[0245] Input: Supply requirements list.

[0246] Output: Data sent to the terminal.

[0247] 4. The device displays a list of required supplies on a map.

[0248] Input: A list of material requirements from the server.

[0249] Output: Map display of supplies list.

[0250] (Application example 1)

[0251] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0252] The problem that this invention aims to solve is to provide a method for quickly and accurately registering information on evacuees during disasters, and efficiently aggregating and displaying the current status of evacuation centers and necessary supplies in real time. It also aims to provide a system that supports effective rescue efforts by recommending disaster prevention goods based on the individual circumstances of evacuees and accurately calculating the amount of supplies needed using AI technology. Furthermore, it aims to increase convenience and information accuracy for evacuees and rescue workers by constantly obtaining and displaying the latest disaster prevention information using smartphones.

[0253] 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.

[0254] In this invention, the server includes a means for registering evacuee information, a means for displaying the status of evacuation centers on a map in real time, and a means for automatically calculating the amount of supplies needed and generating a distribution plan. This allows for quick and accurate understanding of the status of evacuees during a disaster and for appropriate assistance to be provided. Furthermore, the server also includes a means for automatically collecting information from the Internet, displaying road damage status, and providing disaster prevention information. It also includes a means for recommending disaster prevention goods based on individual evacuees' information and a means for calculating the amount of supplies needed using AI technology. This enables efficient distribution of supplies at evacuation centers and access to the latest information via smartphone, significantly improving assistance activities during disasters.

[0255] "Means for registering evacuee information" refers to a function that allows evacuees to enter information about themselves and their families using smartphones or other devices and store it in a database.

[0256] "A means to display the situation at evacuation centers on a map in real time" is a function that displays the current situation at evacuation centers on a map in real time, allowing evacuees and supporters to immediately understand the current situation.

[0257] "Means to automatically calculate the amount of supplies needed and generate a distribution plan" is a function that uses AI technology to calculate the amount of supplies needed based on information about evacuees at each shelter, and then creates an efficient distribution plan based on that.

[0258] "Means for automatically collecting information on the Internet and displaying road damage status" is a function for automatically collecting data on the Internet and displaying road damage status and passable routes.

[0259] "Means for providing disaster prevention information" refers to a function that obtains the latest information on disaster prevention (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the server and provides it to users.

[0260] "Means for recommending disaster prevention goods based on individual information of evacuees" is a function that generates a list of optimal disaster prevention goods based on the health information and special needs of evacuees and recommends them to users.

[0261] "Means using AI technology" refers to functions that use artificial intelligence (AI) to perform various advanced data processing tasks, such as analyzing evacuee information and calculating needed supplies.

[0262] "Means of obtaining and displaying the latest disaster prevention information via smartphone" refers to a function that obtains the latest disaster prevention information from a server via a smartphone app and displays it to the user.

[0263] This invention is a system for quickly and accurately registering information on evacuees in the event of a disaster, and efficiently aggregating and displaying the current status of evacuation centers and necessary supplies in real time. This system includes a means for registering evacuee information, a means for displaying the status of evacuation centers on a map in real time, a means for automatically calculating necessary supplies and generating a distribution plan, a means for automatically collecting information from the Internet and displaying the status of road damage, a means for providing disaster prevention information, a means for recommending disaster prevention goods based on individual information on evacuees, a means for using AI technology, and a means for obtaining and displaying the latest disaster prevention information via a smartphone.

[0264] System configuration and operation

[0265] 1. Registering evacuee information:

[0266] The user uses a smartphone to enter information about themselves and their family (e.g., name, age, allergy information, etc.).

[0267] The terminal encrypts the entered information and sends it to the server.

[0268] The server stores the received information in a database.

[0269] 2. Shelter status display:

[0270] The server collects information on the current situation at the evacuation center (e.g., number of people, necessary supplies, medical status, etc.) in real time.

[0271] The information collected by the server is integrated into a map database.

[0272] The device displays a map and provides the user with up-to-date evacuation shelter information.

[0273] 3. Automatic calculation of supplies and generation of distribution plans:

[0274] The server uses AI technology to calculate the amount of supplies needed based on information about evacuees.

[0275] An efficient distribution plan is generated based on the amount of supplies calculated by the server and notified to the terminal.

[0276] 4. Road damage status display:

[0277] The server automatically collects information from the Internet and analyzes the damage to the roads.

[0278] The server displays the collected information on a map and provides it to the user.

[0279] 5. Provision of disaster prevention information:

[0280] The server obtains the latest disaster prevention information (e.g., natural disaster predictions, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the terminal.

[0281] The terminal displays disaster prevention information to the user.

[0282] 6. Recommended disaster preparedness items:

[0283] The server generates an optimal disaster prevention goods list based on the evacuees' individual information (e.g., allergy information, health status, etc.).

[0284] The device displays a list of recommended disaster preparedness items to the user.

[0285] Specific examples

[0286] Users launch the app on their smartphone and register their own and their family's allergy information.

[0287] Based on the registration information, the server recommends disaster prevention products suitable for specific allergies and displays them on the device.

[0288] Hardware and software used

[0289] Hardware: Smartphones, smart glasses

[0290] Software: requests (server communication), geopy (geographic information acquisition), json (data serialization and encryption)

[0291] Prompt Sentence Examples

[0292] "Taro launches the app and registers allergy information for himself and his family. Please write the code to have the server recommend disaster preparedness products that are suitable for specific allergies."

[0293] The present invention, configured as described above, enables a wide range of support in the event of a disaster, such as rapid and accurate information registration, efficient distribution planning for supplies, and provision of disaster prevention information, thereby significantly improving the convenience and accuracy of information for evacuees and relief workers.

[0294] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0295] Step 1: Register user information

[0296] The user uses their smartphone to enter their own and their family's names, ages, allergy information, etc. The entered data is encrypted and sent from the device to a server. The server then stores the received data in a database. This allows for individualized response in emergencies.

[0297] Input: User information (name, age, allergy information, etc.)

[0298] Output: User information stored in the database

[0299] Step 2: Obtaining and displaying disaster prevention information

[0300] The terminal sends a request for disaster prevention information to the server. The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal. The terminal displays the disaster prevention information to the user. This allows the user to quickly obtain information.

[0301] Input: Disaster prevention information request

[0302] Output: Latest disaster information displayed on the device

[0303] Step 3: Register the current status of the evacuation shelter

[0304] Users record video and audio of the situation at the evacuation shelter. The device then uploads the data to a server. The server then analyzes the video and audio data and extracts important information (e.g., number of evacuees, necessary supplies, etc.).

[0305] Input: Video and audio data

[0306] Output: Analyzed current status information of evacuation shelters

[0307] Step 4: Map display of evacuation shelter information

[0308] The server integrates the analysis results into a map database. The device retrieves the data from the server and displays it on a map in real time, allowing users to visually check the occupancy status of evacuation shelters and requests for assistance.

[0309] Input: Evacuation shelter information after analysis

[0310] Output: Real-time evacuation shelter information displayed on a map

[0311] Step 5: Automatically calculate supplies and generate distribution plans

[0312] The server uses AI technology to analyze evacuee information and calculate the amount of supplies needed. It then generates an efficient distribution plan and notifies the device, thereby reducing waste of supplies.

[0313] Input: Evacuee information

[0314] Output: Calculated supply quantities and distribution plan

[0315] Step 6: Recommend disaster preparedness supplies

[0316] The server generates a list of the most suitable disaster prevention goods based on the individual information of the evacuee (e.g., allergy information, health condition). The terminal displays the list to the user, enabling support tailored to individual needs.

[0317] Input: Individual information of evacuees

[0318] Output: Recommended disaster preparedness supplies list

[0319] Step 7: View road damage

[0320] The server automatically collects information from the Internet and analyzes the state of road damage. The analysis results are displayed on a map and sent to the device, allowing users to plan safe evacuation routes.

[0321] Input: Road information on the Internet

[0322] Output: Road damage status displayed on a map

[0323] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0324] The present invention is a system that combines the following: registering evacuee information, grasping the status of evacuation centers, automatically calculating the amount of supplies and generating distribution plans, displaying road damage status by collecting information from the Internet, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion engine that recognizes the user's emotions.

[0325] During normal times: Dissemination of disaster prevention information and advance registration

[0326] Launching the app and displaying the latest information

[0327] 1. The user launches the "Hoshikuru★" app on their smartphone or tablet.

[0328] 2. The device requests the latest disaster prevention information from the server.

[0329] 3. The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[0330] 4. The device displays the received information on the disaster prevention portal screen.

[0331] Registering user information

[0332] 1. The user opens the "Register Information" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[0333] 2. The device encrypts the entered information and sends it to the server.

[0334] 3. The server stores the received user information in a database.

[0335] Disaster preparedness goods recommendations

[0336] 1. The server generates an optimal disaster preparedness goods list based on the user's registered information (such as allergy information and disease history).

[0337] 2. The server sends the generated list to the terminal.

[0338] 3. The device displays a list of recommended disaster preparedness items to the user.

[0339] In the event of a disaster: Registration of evacuee information and visualization of supplies

[0340] Launching the app at an evacuation shelter

[0341] 1. The user arrives at the evacuation site and launches the app.

[0342] 2. The device will display the evacuation information registration screen.

[0343] Registering evacuation shelter status

[0344] 1. Users record video or audio of the current situation at the evacuation shelter.

[0345] 2. The device uploads the recorded video and audio files to the server.

[0346] 3. The server analyzes the received video and audio files and extracts important information (e.g., the number of evacuees and necessary supplies).

[0347] Real-time display on a map

[0348] 1. The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[0349] 2. The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[0350] Automatic calculation and display of materials

[0351] 1. The server uses AI to calculate the amount of supplies needed based on evacuee information.

[0352] 2. The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[0353] 3. The device displays a list of supplies needed on a map.

[0354] Combining Emotion Engines

[0355] Recognizing and responding to user emotions

[0356] 1. Record the user's voice and facial expressions while using the app.

[0357] 2. The device sends voice and facial expression data to the emotion engine.

[0358] 3. The emotion engine analyzes the user's voice and facial expressions to recognize emotions.

[0359] 4. The emotion engine sends the recognition results to the server.

[0360] 5. The server adjusts the supplies and support needed based on the user's emotional state (e.g., providing additional relaxation items if stress levels are high).

[0361] 6. The device notifies the user of countermeasures and additional support information.

[0362] Specific examples

[0363] Specific examples of using the emotion engine

[0364] 1. User: Hanako, who is feeling stressed at the evacuation shelter, answers the app's questions by voice.

[0365] 2. Terminal: Sends Hanako's recorded voice to the emotion engine.

[0366] 3. Emotion engine: Recognizes high stress levels from Hanako's tone of voice and the content of her words.

[0367] 4. Emotion engine: Reports stress state to the server.

[0368] 5. Server: Suggest adding relaxation items to help Hanako reduce stress and update the support plan.

[0369] 6. Terminal: Display information about relaxation goods to Hanako.

[0370] The processing flow will be explained below.

[0371] During normal times: Dissemination of disaster prevention information and advance registration

[0372] Launching the app and displaying the latest information

[0373] Step 1:

[0374] The user launches the "Hoshikuru★" app.

[0375] Step 2:

[0376] The device requests the latest disaster prevention information from the server.

[0377] Step 3:

[0378] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[0379] Step 4:

[0380] The terminal displays the received information on the disaster prevention portal screen.

[0381] Registering user information

[0382] Step 1:

[0383] The user opens the "Register" section in the app.

[0384] Step 2:

[0385] The terminal displays a form for the user to enter information such as name, age, medical history, and allergy information.

[0386] Step 3:

[0387] The user enters the required information and presses the "Save" button.

[0388] Step 4:

[0389] The terminal encrypts the entered information and sends it to the server.

[0390] Step 5:

[0391] The server stores the received information in a database.

[0392] Disaster preparedness goods recommendations

[0393] Step 1:

[0394] The server analyzes the user's registration information (e.g., allergy information and medical history).

[0395] Step 2:

[0396] Based on the analysis results, the server generates an optimal list of disaster prevention supplies.

[0397] Step 3:

[0398] The server sends the generated list to the terminal.

[0399] Step 4:

[0400] The device displays a list of recommended disaster preparedness items to the user.

[0401] In the event of a disaster: Registration of evacuee information and visualization of supplies

[0402] Launching the app at an evacuation shelter

[0403] Step 1:

[0404] The user arrives at the evacuation site and launches the app.

[0405] Step 2:

[0406] The terminal displays the evacuee information registration screen.

[0407] Registering evacuation shelter status

[0408] Step 1:

[0409] Users record video or audio of the current situation at the evacuation shelter.

[0410] Step 2:

[0411] The device uploads recorded video and audio files to the server.

[0412] Step 3:

[0413] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[0414] Real-time display on a map

[0415] Step 1:

[0416] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[0417] Step 2:

[0418] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[0419] Automatic calculation and display of materials

[0420] Step 1:

[0421] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[0422] Step 2:

[0423] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[0424] Step 3:

[0425] The device displays a list of supplies needed on a map.

[0426] Combining Emotion Engines

[0427] Recognizing and responding to user emotions

[0428] Step 1:

[0429] Records voice and facial expressions while the user is using the app.

[0430] Step 2:

[0431] The device sends voice and facial expression data to the emotion engine.

[0432] Step 3:

[0433] The emotion engine analyzes the user's voice and facial expressions to recognize their emotions.

[0434] Step 4:

[0435] The emotion engine sends the recognition results to the server.

[0436] Step 5:

[0437] The server adjusts the supplies and support needed based on the user's emotional state (e.g., providing additional relaxation products if stress levels are high).

[0438] Step 6:

[0439] The device notifies the user of countermeasures and additional support information.

[0440] Specific examples

[0441] Specific examples of using the emotion engine

[0442] Step 1:

[0443] User: Hanako, who is feeling stressed at the evacuation shelter, answers the app's questions by voice.

[0444] Step 2:

[0445] Terminal: Sends Hanako's recorded voice to the emotion engine.

[0446] Step 3:

[0447] Emotion engine: Recognizes high stress levels from Hanako's tone of voice and the content of her words.

[0448] Step 4:

[0449] Emotion engine: Reports stress state to the server.

[0450] Step 5:

[0451] Server: Suggest adding relaxation items to help Hanako reduce stress and update the support plan.

[0452] Step 6:

[0453] Terminal: Display information about relaxation goods to Hanako.

[0454] Example 2

[0455] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0456] In recent years, the frequency and scale of natural disasters have increased, creating a need for information registration for evacuees, understanding the situation at evacuation centers, and quickly distributing relief supplies. However, current systems have problems in that they do not adequately provide support that takes into account the detailed information and emotional state of evacuees. Another issue is that they lack the functionality to display the situation at evacuation centers on a map in real time, making it difficult to create effective evacuation plans.

[0457] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for registering evacuee information, a means for displaying the situation of the evacuation center on a map in real time, a means for automatically calculating the amount of supplies needed and generating a distribution plan, and a means for recognizing the emotional state of the evacuees using an emotion analysis engine and providing appropriate support. This enables support that takes into account the detailed information and emotional state of the evacuees, and enables a quick response by understanding the situation of the evacuation center in real time.

[0458] "Evacuee information" is detailed data about individuals and families who evacuated during a disaster, including their names, ages, medical history, and allergies.

[0459] "Shelter status" refers to data that includes current information such as the number of evacuees and necessary supplies in the shelter, as well as the physical condition and environment of the shelter.

[0460] "Means of displaying on a map" refers to a technology that imports data onto an electronic map and displays it in real time in order to visually represent information about evacuation shelters and evacuees.

[0461] "Means for automatically calculating supplies" refers to technology that uses artificial intelligence and algorithms to automatically calculate the amount of relief supplies needed, such as food, water, and blankets, based on information about evacuees.

[0462] The "means for generating a distribution plan" is a means for planning and formulating the optimal distribution route and timing based on the calculated required amount of supplies.

[0463] "Means for automatically collecting information on the Internet" refers to technology for automatically collecting and analyzing road conditions, weather information, etc. from the web.

[0464] "Road damage status" is data showing the status of road damage and road closures caused by disasters.

[0465] "Disaster prevention information" includes information necessary in the event of a disaster, such as the location of evacuation shelters, emergency contact information, and evacuation procedures.

[0466] The "means for recommending disaster prevention goods" is a technology that suggests the most appropriate disaster prevention products, such as medicines, food, and bedding, based on the individual information of evacuees.

[0467] An "emotion analysis engine" is an algorithm or software that analyzes voice and facial expression data to recognize the emotional state of evacuees and present appropriate support measures.

[0468] The present invention is a system that combines the registration of evacuee information, grasping the situation at evacuation centers, automatically calculating and generating distribution plans for supplies, displaying road damage status, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion analysis engine.

[0469] Processing during normal times

[0470] Disaster prevention information dissemination and advance registration

[0471] The user launches the dedicated app on their smartphone or tablet. The device requests the latest disaster prevention information from the server, and the server retrieves the information from the disaster prevention portal database and sends it to the device. The device then displays the received information on the disaster prevention portal screen.

[0472] Users open the information registration section in the app and enter information about themselves and their family members (name, age, medical history, allergies, etc.). The device encrypts the entered information and sends it to the server, which then stores the received user information in a database.

[0473] The server generates a list of suitable disaster prevention goods based on the user's registration information and sends it to the terminal, which then displays the received list.

[0474] Disaster Preparedness

[0475] Registration of evacuee information and visualization of supplies

[0476] The user arrives at the evacuation shelter and launches the app. The device displays the evacuee information registration screen. The user records video or audio of the current situation at the evacuation shelter. The device uploads the recorded video and audio files to the server. The server analyzes the received files and extracts important information (e.g., the number of evacuees and necessary supplies).

[0477] The server integrates the analyzed information into a map database and updates the status of all evacuation shelters. The device retrieves the updated evacuation shelter information from the server and displays it on a map in real time.

[0478] The server uses AI to calculate the amount of supplies needed based on evacuee information and generates a list of supplies needed for each evacuation shelter. The terminal displays the received list of supplies on a map.

[0479] Combining Emotion Engines

[0480] When using the app, the user records their voice and facial expressions. The device then sends the voice and facial expression data to the emotion engine. The emotion engine analyzes the user's voice and facial expressions to recognize their emotions. The emotion engine then sends the recognition results to the server. The server then adjusts the supplies and support needed based on the user's emotional state (e.g., if stress levels are high, providing additional relaxation products). The device then notifies the user of countermeasures and additional support information.

[0481] Specific examples

[0482] Specific examples of using the emotion engine

[0483] 1. User: An individual experiencing stress in a shelter answers questions from the app by voice.

[0484] 2. Terminal: Sends the recorded audio to the emotion engine.

[0485] 3. Emotion Engine: Recognizes high stress levels from tone and verbal content.

[0486] 4. Emotion engine: Reports stress state to the server.

[0487] 5. Server: Suggest adding relaxation items to reduce stress and update the support plan.

[0488] 6. Terminal: Display information about relaxation products.

[0489] Example prompt for a generative AI model:

[0490] "Please explain how the emotion engine responds when evacuees are experiencing stress in an evacuation center."

[0491] As described above, the present invention makes it possible to provide support that takes into account detailed information and emotional state of evacuees, and enables quick response by understanding the situation at the evacuation shelter in real time.

[0492] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0493] Step 1:

[0494] The user launches a dedicated app on a smartphone or tablet.

[0495] Specific action: The user taps the app icon on the smartphone screen to launch the app.

[0496] Input: User taps

[0497] Output: App launch

[0498] Step 2:

[0499] The device requests the latest disaster prevention information from the server.

[0500] Specific operation: The terminal sends an HTTP request to the server, requesting the latest disaster prevention information.

[0501] Input: App launch signal

[0502] Output: HTTP request

[0503] Step 3:

[0504] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[0505] Specific operation: The server executes a database query, obtains the latest disaster prevention information data, and returns a response to the terminal.

[0506] Input: HTTP request

[0507] Output: Disaster prevention measures information

[0508] Step 4:

[0509] The terminal displays the received information on the disaster prevention portal screen.

[0510] Specific behavior: Parse the received data and display it in the user interface.

[0511] Input: Disaster prevention measures information

[0512] Output: Update the disaster prevention portal screen

[0513] Step 5:

[0514] The user opens the registration section within the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[0515] Specific operation: The user enters the required information into each input field on the app screen.

[0516] Input: User details

[0517] Output: Input data

[0518] Step 6:

[0519] The terminal encrypts the entered information and sends it to the server.

[0520] Specific operation: The terminal encrypts the input data (for example, AES encryption) and securely sends it to the server via an HTTP POST request.

[0521] Input: Input data

[0522] Output: Encrypted data

[0523] Step 7:

[0524] The server stores the received user information in a database.

[0525] Specific operation: Execute a query to insert the received data into the database.

[0526] Input: Encrypted data

[0527] Output: Save to database

[0528] Step 8:

[0529] The server generates a list of optimal disaster prevention goods based on the user's registration information and sends it to the terminal.

[0530] Specific operation: The server runs a recommendation algorithm to extract appropriate disaster prevention goods information from the database.

[0531] Input: User information

[0532] Output: Disaster preparedness kit list

[0533] Step 9:

[0534] The device displays a list of recommended disaster preparedness items to the user.

[0535] Specific operation: Parse the received list data and display it in the user interface.

[0536] Input: Disaster Preparedness Supplies List

[0537] Output: Update the recommendation screen

[0538] Step 10:

[0539] The user arrives at the evacuation shelter and launches the app.

[0540] Specific action: The user taps the app icon on their smartphone to launch it.

[0541] Input: Reached shelter

[0542] Output: App launch

[0543] Step 11:

[0544] The terminal displays the evacuee information registration screen.

[0545] Specific operation: The app will automatically transition to the evacuation information registration screen and display the input field.

[0546] Input: App launch signal

[0547] Output: Evacuee information registration screen

[0548] Step 12:

[0549] Users record video or audio of the current situation at the evacuation shelter.

[0550] Specific actions: Recording video or audio using the app's video recording or audio recording features.

[0551] Input: Shelter status

[0552] Output: Video or audio file

[0553] Step 13:

[0554] The device uploads recorded video and audio files to the server.

[0555] Specific operation: Sends the file to the server via the Web API.

[0556] Input: Video or audio file

[0557] Output: Uploaded file

[0558] Step 14:

[0559] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[0560] Specific operation: Extract important information from received files using appropriate analysis algorithms (e.g., voice recognition, video analysis).

[0561] Input: Video or audio file

[0562] Output: Extracted information

[0563] Step 15:

[0564] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[0565] Specific operation: The analysis results are updated to a geographic information system (GIS) database.

[0566] Input: Extracted information

[0567] Output: Updated map data

[0568] Step 16:

[0569] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[0570] Specific operation: Uses the map API to display the latest evacuation shelter information on a map.

[0571] Input: Updated map data

[0572] Output: Real-time map display

[0573] Step 17:

[0574] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[0575] Specific operation: Using an AI algorithm, the amount of supplies needed is calculated based on evacuee information.

[0576] Input: Evacuee information

[0577] Output: Material requirements data

[0578] Step 18:

[0579] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[0580] Specific operation: Create a list of supplies and send it to the terminal in JSON format.

[0581] Input: Material requirements data

[0582] Output: Supplies list

[0583] Step 19:

[0584] The device displays a list of supplies needed on a map.

[0585] Specific operation: Uses the map API to overlay the list of supplies on the map.

[0586] Input: Supply list

[0587] Output: Map display

[0588] Step 20:

[0589] Records voice and facial expressions while the user is using the app.

[0590] Specific operation: Use the recording and video recording functions within the app to record the user's voice and facial expressions.

[0591] Input: User's voice and facial expressions

[0592] Output: Audio and facial expression files

[0593] Step 21:

[0594] The device sends voice and facial expression data to the emotion engine.

[0595] Specific operation: Sends data to the sentiment analysis API via a POST request.

[0596] Input: Audio and facial expression files

[0597] Output: API request

[0598] Step 22:

[0599] The emotion engine analyzes the user's voice and facial expressions to recognize their emotions.

[0600] Specific operation: Using an analysis algorithm, voice tone and facial expression patterns are analyzed to generate emotion data.

[0601] Input: API request data

[0602] Output: Emotion data

[0603] Step 23:

[0604] The emotion engine sends the recognition results to the server.

[0605] Specific operation: Recognition results are sent to the server in JSON format.

[0606] Input: Emotion data

[0607] Output: Send data to the server

[0608] Step 24:

[0609] The server coordinates the necessary supplies and assistance based on the user's emotional state.

[0610] Specific actions: Update the supply list and support plan based on the recognition results.

[0611] Input: Emotion data

[0612] Output: Updated supply lists and support plans

[0613] Step 25:

[0614] The device notifies the user of countermeasures and additional support information.

[0615] Specific operation: Use the notification function to display additional support information to the user.

[0616] Input: Updated supply lists and assistance plans

[0617] Output: Notification message

[0618] (Application example 2)

[0619] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0620] Conventional evacuation support systems are limited to registering evacuee information and understanding the situation at evacuation shelters, and do not adequately provide supplies and support that take into account the emotional state and dynamics of individual evacuees. This can increase stress and anxiety in evacuation shelters, potentially damaging the mental and physical health of evacuees. Furthermore, efficient distribution of supplies using autonomous vehicles has not yet been realized, making it difficult to quickly provide supplies to evacuation shelters.

[0621] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for registering evacuee information, means for displaying the status of evacuation shelters on a map in real time, means for automatically calculating the amount of supplies needed and generating a distribution plan, means for automatically collecting information on the Internet and displaying road damage status, means for providing disaster prevention information, means for recommending disaster prevention goods based on individual information of evacuees, means for analyzing the voices and facial expressions of evacuees to recognize their emotions and coordinating the necessary supplies and support, and means for collecting evacuee information and efficiently distributing supplies using autonomous vehicles. This enables individual responses that take into account the emotional state of evacuees and rapid and efficient distribution of supplies using autonomous vehicles.

[0622] "Refugee information" refers to personal data such as the evacuee's name, age, health condition, and allergy information.

[0623] "Shelter status" refers to information about the current number of evacuees at the shelter, the type and amount of supplies needed, and the environmental condition of the shelter.

[0624] "Displaying on a map" means visually displaying the collected information on the evacuation shelter situation on a map in real time.

[0625] "Automatic calculation of supplies" means using artificial intelligence or algorithms to automatically calculate the type and amount of supplies needed based on information about evacuees and the situation at evacuation shelters.

[0626] "Generating a distribution plan" means planning the route and timing for distributing the calculated supplies to evacuation centers.

[0627] "Automatically collecting information on the Internet" means autonomously collecting relevant information from public data on the Internet and various information sources.

[0628] "Road damage status" is information about the state of damage to roads that have been damaged by earthquakes or other disasters.

[0629] "Disaster prevention information" refers to information on disaster risks, evacuation methods, safety measures, etc.

[0630] "Disaster prevention goods" refers to emergency supplies and equipment needed in the event of a disaster.

[0631] "Emotion recognition" means analyzing the voices and facial expressions of evacuees to determine their psychological state and emotions.

[0632] An "autonomous vehicle" is a vehicle that can operate autonomously without human operation, and uses sensors and AI to recognize the surrounding environment while driving.

[0633] "Efficient distribution of supplies" means setting and executing optimal routes and schedules to distribute needed supplies quickly and to the right places.

[0634] The present invention is a system that combines the following functions: registering evacuee information, grasping the status of evacuation shelters, automatically calculating the amount of supplies needed and creating distribution plans, displaying road damage status by collecting information from the Internet, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion engine that recognizes the user's emotions. A specific embodiment of this system is described below.

[0635] 1.Registering evacuee information

[0636] The server receives and encrypts information about evacuees entered by users through their smartphones or smart glasses, and stores it in a database, including the evacuees' names, ages, health conditions, and allergies.

[0637] 2. Understanding the situation at evacuation shelters

[0638] The devices record real-time video and audio of the current situation at evacuation centers and send it to a server. The server analyzes the data, extracts important information such as the number of evacuees and necessary supplies, and integrates it into a map database. The status of all evacuation centers is then updated and displayed on a map.

[0639] 3. Automatic calculation of supplies and generation of distribution plans

[0640] The server uses AI to automatically calculate the amount of supplies needed based on evacuee information and real-time evacuation shelter conditions. It then generates a list of supplies needed for each shelter and creates an efficient distribution plan. This plan is sent to autonomous vehicles, which distribute the supplies along the appropriate routes and at the appropriate times.

[0641] 4.Collecting information from the Internet and displaying road damage status

[0642] The server automatically collects road damage information from various sources on the Internet, verifies the safety of evacuation routes, and calculates the optimal evacuation route based on the collected information and displays it on a map.

[0643] 5. Provision of disaster prevention information

[0644] Users can receive the latest disaster prevention information provided by the server in real time on their smartphones or smart glasses, enabling them to take appropriate evacuation actions.

[0645] 6. Recommend disaster prevention goods based on individual evacuees' information

[0646] The server generates a list of necessary disaster prevention goods based on registered evacuee information and recommends them to the user. For example, it provides the most suitable foods and medicines based on allergies and illnesses.

[0647] 7. Emotion recognition and support with emotion engine

[0648] The device records the evacuees' voices and facial expressions and sends them to the emotion engine. The server uses the emotion engine to recognize the evacuees' stress levels and adjust the supplies and support they need. For example, if stress levels are high, the server will provide additional relaxation products.

[0649] Specific examples

[0650] 1. Registering evacuee information:

[0651] The user enters their own information (name, age, health condition, etc.) using their smartphone and sends it to the server.

[0652] 2. Assessing the situation at evacuation shelters:

[0653] The self-driving vehicle arrives at the evacuation shelter, records the current situation at the shelter using its onboard camera, and transmits the footage to a server.

[0654] 3. Emotion Recognition with Emotion Engine:

[0655] Evacuees who feel stressed in shelters answer questions in the app by voice, and the server sends the recorded voice data to an emotion engine to recognize their stress level.

[0656] Prompt Sentence Examples

[0657] Below are some example prompts to input to a generative AI model:

[0658] "Please create a program for a crisis management system. It will use smartphones and self-driving vehicles to register evacuee information, grasp the situation at evacuation centers, automatically calculate and plan distribution of supplies, and recognize user emotions. Users enter information about themselves and their families on their smartphones, and as soon as the self-driving vehicle arrives at the evacuation center, it will send the situation to the server in real time. The emotion engine will analyze the user's stress level and adjust the necessary supplies."

[0659] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0660] Step 1:

[0661] The user launches the "Evacuee Information Registration" app on their smartphone or smart glasses and enters information about themselves and their family members (such as name, age, health condition, allergy information, etc.). The entered evacuee information is encrypted by the device and sent to the server.

[0662] Input: User information (name, age, health condition, allergy information)

[0663] Output: Encrypted evacuee information

[0664] Step 2:

[0665] The server decrypts the encrypted evacuee information it receives and stores it in a database. At the same time, it generates a list of disaster prevention goods suitable for each evacuee and sends it to the terminal.

[0666] Input: Encrypted evacuee information

[0667] Output: Evacuee information database, disaster prevention goods list

[0668] Step 3:

[0669] When the user arrives at the evacuation shelter and launches the app, the device records video and audio of the situation at the shelter and uploads the data to the server.

[0670] Input: Video and audio data from the evacuation center

[0671] Output: Uploaded shelter status data

[0672] Step 4:

[0673] The server analyzes the video and audio data received from the evacuation shelters to extract the number of evacuees and necessary supplies. The extracted information is integrated into a map database, and the status of all evacuation shelters is updated on the map in real time.

[0674] Input: Video and audio data from the evacuation center

[0675] Output: Analyzed evacuation shelter status, updated map data

[0676] Step 5:

[0677] The server analyzes the evacuation shelter situation and evacuee information, and then automatically calculates the amount of supplies needed using AI. It then generates a list of the required supplies for each shelter and sends it to the device.

[0678] Input: Evacuee information, evacuation shelter status

[0679] Output: List of required supplies

[0680] Step 6:

[0681] The server uploads the generated supply distribution plan to the autonomous vehicles, which then calculate the optimal route and efficiently distribute supplies to evacuation centers.

[0682] Input: Supply distribution plan

[0683] Output: Optimal route, delivery of goods

[0684] Step 7:

[0685] When a user uses the app, their voice and facial expressions are recorded. The device then sends the voice and facial expression data to an emotion engine, which then analyzes the user's emotions. The analysis results are then sent to a server, and the assistance plan is updated based on the evacuees' emotional state.

[0686] Input: Speech and facial expression data

[0687] Output: Analyzed emotional state, updated support plan

[0688] Step 8:

[0689] The server sends the updated support plan to the device, which then notifies the user of the support and supplies they need. For example, if stress levels are high, the device suggests adding relaxation products.

[0690] Input: Updated support plan

[0691] Output: Support information notification, relaxation goods information

[0692] In this way, it is possible to consistently carry out everything from registering evacuee information to understanding the situation at evacuation centers, planning and executing the distribution of supplies, and even optimizing support through emotion recognition.

[0693] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0694] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0695] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0696] [Second embodiment]

[0697] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0698] 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.

[0699] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0700] 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.

[0701] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0702] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0703] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0704] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0705] 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.

[0706] 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.

[0707] 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.

[0708] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0709] During normal times: Dissemination of disaster prevention information and advance registration

[0710] 1. Launch the app and view the latest information

[0711] The user launches the "Hoshikuru★" app on a smartphone or tablet.

[0712] The device requests the latest disaster prevention information from the server.

[0713] The server retrieves the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the terminal.

[0714] The terminal displays the received information on the disaster prevention portal screen.

[0715] 2. User Information Registration

[0716] The user opens the "Information Registration" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[0717] The terminal encrypts the entered information and sends it to the server.

[0718] The server stores the received user information in a database.

[0719] 3. Disaster Preparedness Goods Recommendations

[0720] The server generates a list of optimal anti-theft products based on the user's registered information (such as allergy information and disease history).

[0721] The server sends the generated list to the terminal.

[0722] The device displays a list of recommended disaster preparedness items to the user.

[0723] In the event of a disaster: Registration of evacuee information and visualization of supplies

[0724] 1. Launch the app at the evacuation shelter

[0725] The user arrives at an evacuation site (e.g., a community center or school) and launches the app.

[0726] The terminal displays a screen for registering evacuee information and prompts the user to enter information.

[0727] 2. Register your evacuation shelter status

[0728] Users record video or audio of the current situation at the evacuation center (e.g., food shortages, requests for medicine, etc.).

[0729] The device uploads recorded video and audio files to the server.

[0730] The server analyzes the video and audio data it receives and extracts important information (such as the number of evacuees and the supplies they need).

[0731] 3. Real-time display on the map

[0732] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[0733] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[0734] 4. Automatic calculation and display of materials

[0735] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[0736] For example, consider the number of people in the shelter, their health status, and any special needs (allergies, illnesses, etc.).

[0737] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[0738] The device displays a list of supplies needed on a map.

[0739] Specific examples

[0740] Example of normal operation

[0741] 1. Launch the app and view the latest information

[0742] User: Taro launches the "Hoshikuru★" app.

[0743] Terminal: Displays the latest typhoon information and countermeasures from the disaster prevention portal.

[0744] 2. User Information Registration

[0745] User: Taro enters his name, family members' names, and allergy information.

[0746] Terminal: Sends input information to the server and stores it.

[0747] 3. Disaster Preparedness Goods Recommendations

[0748] Server: Based on Taro's allergy information, recommend food and medicines that are suitable for specific allergies.

[0749] Device: Display a list of recommended disaster prevention items to Taro.

[0750] Example of operation during a disaster

[0751] 1. Launch the app at the evacuation shelter

[0752] User: Hanako is affected by the disaster, evacuates to the nearest community center, and launches the app.

[0753] Terminal: Display the evacuee information registration screen.

[0754] 2. Register your evacuation shelter status

[0755] User: Hanako records the situation at the evacuation center (food shortages, requests for medicine, etc.) on video.

[0756] Device: Upload the recorded video to the server.

[0757] 3. Real-time display on the map

[0758] Server: Updates the map database with information about the community center where Hanako will take refuge.

[0759] Terminal: Displays evacuation shelter information on a map in real time.

[0760] 4. Automatic calculation and display of materials

[0761] Server: The AI ​​calculates the amount of supplies needed, taking into account the number of evacuees at the community center and Hanako's special needs.

[0762] Terminal: Display a list of food, water, and medicine needed at the community center on a map.

[0763] The processing flow will be explained below.

[0764] During normal times: Dissemination of disaster prevention information and advance registration

[0765] Launching the app and displaying the latest information

[0766] Step 1:

[0767] The user launches the "Hoshikuru★" app.

[0768] The device displays the Start screen.

[0769] Step 2:

[0770] The device requests the latest disaster prevention information from the server.

[0771] Step 3:

[0772] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[0773] Step 4:

[0774] The terminal displays the received information on the disaster prevention portal screen.

[0775] Registering user information

[0776] Step 1:

[0777] The user opens the "Register" section in the app.

[0778] Step 2:

[0779] The terminal displays a form for the user to enter information such as name, age, medical history, and allergy information.

[0780] Step 3:

[0781] The user enters the required information and presses the "Save" button.

[0782] Step 4:

[0783] The terminal encrypts the entered information and sends it to the server.

[0784] Step 5:

[0785] The server stores the received information in a database.

[0786] Disaster preparedness goods recommendations

[0787] Step 1:

[0788] The server analyzes the user's registration information (e.g., allergy information and medical history).

[0789] Step 2:

[0790] Based on the analysis results, the server generates an optimal list of disaster prevention supplies.

[0791] Step 3:

[0792] The server sends the generated list to the terminal.

[0793] Step 4:

[0794] The device displays a list of recommended disaster preparedness items to the user.

[0795] In the event of a disaster: Registration of evacuee information and visualization of supplies

[0796] Launching the app at an evacuation shelter

[0797] Step 1:

[0798] The user arrives at the evacuation site and launches the app.

[0799] Step 2:

[0800] The terminal displays the evacuee information registration screen.

[0801] Registering evacuation shelter status

[0802] Step 1:

[0803] Users record video or audio of the current situation at the evacuation shelter.

[0804] Step 2:

[0805] The device uploads recorded video and audio files to the server.

[0806] Step 3:

[0807] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[0808] Real-time display on a map

[0809] Step 1:

[0810] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[0811] Step 2:

[0812] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[0813] Automatic calculation and display of materials

[0814] Step 1:

[0815] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[0816] Step 2:

[0817] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[0818] Step 3:

[0819] The device displays a list of supplies needed on a map.

[0820] Example 1

[0821] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0822] In emergencies such as natural disasters, it is difficult to quickly and accurately register information about evacuees in shelters and grasp the situation at the shelters in real time. It is also difficult to properly calculate and distribute the necessary supplies. Therefore, a system that effectively solves these issues is needed to ensure the safety and security of evacuees. Furthermore, it is also important to recommend disaster prevention goods based on the individual information of evacuees, record the current situation at the shelters using video and audio, and extract important data from that information.

[0823] 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.

[0824] In this invention, the server includes a means for registering evacuee information, a means for displaying the status of evacuation shelters on a map in real time, and a means for automatically calculating the amount of supplies needed and generating a distribution plan. This allows for quick and accurate registration of evacuee information and understanding of the real-time situation at evacuation shelters. Furthermore, by appropriately calculating and distributing the necessary supplies, the safety and security of evacuees can be ensured. Furthermore, it is possible to recommend disaster prevention goods based on individual evacuee information, record the current situation at evacuation shelters using video and audio, and extract important data from that information.

[0825] A "means for registering evacuee information" is a device or software that allows evacuees to enter their own information (such as name, age, health status, etc.) and store that information in a database.

[0826] "Means for displaying the status of evacuation centers on a map in real time" refers to a device or software that visualizes the status of evacuation centers (number of people, supply status, etc.) on a map and updates and displays the current situation in real time.

[0827] "Means for automatically calculating the amount of supplies needed and generating a distribution plan" refers to a device or software that uses AI or other data analysis technology to calculate the amount of supplies needed at evacuation shelters and automatically create a subsequent distribution plan.

[0828] "Means for automatically collecting information on the Internet and displaying the status of road damage" refers to a device or software for automatically collecting information obtained from the Internet and displaying the status of road damage caused by disasters.

[0829] The "means for providing disaster prevention information" refers to a device or software for providing users with disaster prevention information such as disaster predictions and evacuation instructions.

[0830] "Means for recommending disaster prevention goods based on individual information of evacuees" refers to a device or software that suggests the most suitable disaster prevention goods for evacuees based on individual information such as allergy information and disease history of the evacuees.

[0831] "Means for recording the current situation at the evacuation shelter using video or audio and uploading that information to a server" refers to a device or software for recording the situation at the evacuation shelter using video or audio and sending the recorded data to a server.

[0832] "Means for analyzing uploaded video and audio data and extracting important information" refers to a device or software that analyzes video and audio data uploaded to a server and automatically extracts important information such as the number of evacuees and necessary supplies.

[0833] "Means for generating a list of required supplies for each evacuation shelter and sending it to the terminal" refers to a device or software for creating a list of the amount of supplies needed at each evacuation shelter based on evacuee information and sending that list to the user's terminal.

[0834] The present invention relates to a system that registers information on evacuees, grasps the situation at evacuation shelters in real time, and appropriately calculates and distributes necessary supplies. The detailed configuration of the system of the present invention is shown below.

[0835] This system is operated by the user using a smartphone or tablet device. When the user launches the "disaster prevention app," the device communicates with the server via the internet to obtain and send the necessary information. The server uses a database and AI models to analyze and process various pieces of information. Specific hardware and software used include a smartphone, tablet, internet connection, database, and AI analysis tool.

[0836] First, the user launches the "disaster prevention app" on their smartphone or tablet device. The device then requests the latest disaster prevention information from the server via the Internet. The server then retrieves the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the device. The device then displays the received information on its screen, providing the user with the latest disaster prevention information.

[0837] Next, the user opens the "Information Registration" section in the app and enters information about themselves and their family members (such as name, age, medical history, allergies, etc.). The device encrypts the entered information using AES and sends it to the server, which then stores the received user information in a database.

[0838] The server then reads the user's registration information from the database and uses an AI model to generate a list of optimal disaster preparedness supplies that takes into account allergies and medical history. The generated disaster preparedness supply list is then sent from the server to the device and displayed on the device.

[0839] In the event of a disaster, the user reaches an evacuation site and launches the "disaster prevention app." The device displays a screen for registering evacuee information and asks the user to enter the necessary information. The user records video or audio of the current situation at the evacuation site (e.g., food shortages, requests for medicine, etc.) and uploads it to the server on the device. The server analyzes the received video and audio data using an AI analysis tool to extract important information such as food shortages and requests for medicine. The analyzed information is integrated into a map database, and the status of all evacuation sites is updated in real time. The device obtains the latest evacuation site information and displays it on a map.

[0840] The server then uses AI to calculate the amount of supplies needed based on information about the evacuees at the shelters, and generates a list of the required supplies for each shelter. The list is then sent to the device and displayed on the device.

[0841] As a concrete example, a user is affected by a disaster, evacuates to the nearest evacuation shelter, and launches a "disaster prevention app." The user records video of the situation at the evacuation shelter and uploads the video. The server analyzes the video, extracts important information, and displays it on a map. The server calculates the necessary supplies based on the evacuee's information, creates a list, and displays it on the device.

[0842] An example of a prompt sentence is, "A large-scale earthquake has occurred and I have arrived at a shelter. I would like to record a video of the situation at the shelter, upload it to the server, and receive appropriate material support. How can I do this?" By inputting such a prompt sentence into a generative AI model, detailed instructions can be automatically provided.

[0843] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0844] System program processing flow

[0845] During normal times: Dissemination of disaster prevention information and advance registration

[0846] Step 1: Launch the app and view the latest information

[0847] 1. The user launches the "disaster prevention app" on their smartphone or tablet.

[0848] Input: User initiated actions.

[0849] Output: None.

[0850] 2. The terminal sends a request for the latest disaster prevention information to the server via the Internet.

[0851] Input: App launch signal.

[0852] Output: Disaster prevention information request to the server.

[0853] 3. The server accesses the disaster prevention portal database and obtains the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.).

[0854] Input: A request from the terminal.

[0855] Output: Latest disaster prevention information data.

[0856] 4. The server sends the acquired information to the terminal.

[0857] Input: Latest disaster prevention information data.

[0858] Output: Data sent to the terminal.

[0859] 5. The terminal displays the received information on the screen, providing the user with the latest disaster prevention information.

[0860] Input: Disaster prevention information from the server.

[0861] Output: Disaster prevention information displayed on screen.

[0862] Step 2: Register user information

[0863] 1. The user opens the "Register Information" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[0864] Input: Manually enter user information.

[0865] Output: The entered user information.

[0866] 2. The terminal encrypts the user's input data using AES and sends it to the server.

[0867] Input: The user information entered.

[0868] Output: Encrypted user information data.

[0869] 3. The server stores the received user information data in a database.

[0870] Input: Encrypted user information data.

[0871] Output: User information stored in the database.

[0872] Step 3: Recommend disaster preparedness supplies

[0873] 1. The server reads the user's registration information from the database.

[0874] Input: User information retrieved from the database.

[0875] Output: User registration information.

[0876] 2. The server uses an AI model to generate a list of disaster preparedness items tailored to each user based on their registration information.

[0877] Input: User registration information.

[0878] Output: The generated disaster preparedness kit list.

[0879] 3. The server sends the generated disaster prevention goods list to the terminal.

[0880] Input: The generated disaster preparedness kit list.

[0881] Output: Data sent to the terminal.

[0882] 4. The device will display a list of recommended disaster preparedness items on the screen.

[0883] Input: Disaster preparedness supplies list from the server.

[0884] Output: Screen display of disaster preparedness item list.

[0885] In the event of a disaster: Registration of evacuee information and visualization of supplies

[0886] Step 1: Launch the app at the evacuation shelter

[0887] 1. The user arrives at the evacuation site and launches the app.

[0888] Input: User operation to launch the app.

[0889] Output: None.

[0890] 2. The terminal displays the evacuee information registration screen and prompts the user to enter information.

[0891] Input: App launch signal.

[0892] Output: Display of evacuee information registration screen.

[0893] Step 2: Register your evacuation status

[0894] 1. Users record video or audio of the current situation at the evacuation shelter.

[0895] Input: Shelter situation.

[0896] Output: Recorded video and audio files.

[0897] 2. The device uploads the recorded video and audio files to the server.

[0898] Input: Recorded video and audio files.

[0899] Output: Upload data to server.

[0900] 3. The server uses AI analysis tools to analyze the video and audio data received and extract important information such as food shortages and requests for medicine.

[0901] Input: Uploaded video and audio data.

[0902] Output: Important information data of the analysis results.

[0903] Step 3: Real-time display on a map

[0904] 1. The server integrates the analyzed information into a map database and updates the real-time status of all evacuation centers.

[0905] Input: Important information data of the analysis results.

[0906] Output: Updated map database.

[0907] 2. The device retrieves the latest evacuation shelter information from the server and displays that information on a map.

[0908] Input: Shelter information data from the server.

[0909] Output: Real-time display on map.

[0910] Step 4: Automatic calculation and display of materials

[0911] 1. The server uses AI to calculate the amount of supplies needed based on information about evacuees at shelters.

[0912] Input: Evacuee information data.

[0913] Output: Calculated material requirements data.

[0914] 2. The server generates a list of required supplies for each evacuation shelter.

[0915] Input: Material requirements data.

[0916] Output: List of supplies required.

[0917] 3. The server sends the list of required supplies to the terminal.

[0918] Input: Supply requirements list.

[0919] Output: Data sent to the terminal.

[0920] 4. The device displays a list of required supplies on a map.

[0921] Input: A list of material requirements from the server.

[0922] Output: Map display of supplies list.

[0923] (Application example 1)

[0924] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0925] The problem that this invention aims to solve is to provide a method for quickly and accurately registering information on evacuees during disasters, and efficiently aggregating and displaying the current status of evacuation centers and necessary supplies in real time. It also aims to provide a system that supports effective rescue efforts by recommending disaster prevention goods based on the individual circumstances of evacuees and accurately calculating the amount of supplies needed using AI technology. Furthermore, it aims to increase convenience and information accuracy for evacuees and rescue workers by constantly obtaining and displaying the latest disaster prevention information using smartphones.

[0926] 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.

[0927] In this invention, the server includes a means for registering evacuee information, a means for displaying the status of evacuation centers on a map in real time, and a means for automatically calculating the amount of supplies needed and generating a distribution plan. This allows for quick and accurate understanding of the status of evacuees during a disaster and for appropriate assistance to be provided. Furthermore, the server also includes a means for automatically collecting information from the Internet, displaying road damage status, and providing disaster prevention information. It also includes a means for recommending disaster prevention goods based on individual evacuees' information and a means for calculating the amount of supplies needed using AI technology. This enables efficient distribution of supplies at evacuation centers and access to the latest information via smartphone, significantly improving assistance activities during disasters.

[0928] "Means for registering evacuee information" refers to a function that allows evacuees to enter information about themselves and their families using smartphones or other devices and store it in a database.

[0929] "A means to display the situation at evacuation centers on a map in real time" is a function that displays the current situation at evacuation centers on a map in real time, allowing evacuees and supporters to immediately understand the current situation.

[0930] "Means to automatically calculate the amount of supplies needed and generate a distribution plan" is a function that uses AI technology to calculate the amount of supplies needed based on information about evacuees at each shelter, and then creates an efficient distribution plan based on that.

[0931] "Means for automatically collecting information on the Internet and displaying road damage status" is a function for automatically collecting data on the Internet and displaying road damage status and passable routes.

[0932] "Means for providing disaster prevention information" refers to a function that obtains the latest information on disaster prevention (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the server and provides it to users.

[0933] "Means for recommending disaster prevention goods based on individual information of evacuees" is a function that generates a list of optimal disaster prevention goods based on the health information and special needs of evacuees and recommends them to users.

[0934] "Means using AI technology" refers to functions that use artificial intelligence (AI) to perform various advanced data processing tasks, such as analyzing evacuee information and calculating needed supplies.

[0935] "Means of obtaining and displaying the latest disaster prevention information via smartphone" refers to a function that obtains the latest disaster prevention information from a server via a smartphone app and displays it to the user.

[0936] This invention is a system for quickly and accurately registering information on evacuees in the event of a disaster, and efficiently aggregating and displaying the current status of evacuation centers and necessary supplies in real time. This system includes a means for registering evacuee information, a means for displaying the status of evacuation centers on a map in real time, a means for automatically calculating necessary supplies and generating a distribution plan, a means for automatically collecting information from the Internet and displaying the status of road damage, a means for providing disaster prevention information, a means for recommending disaster prevention goods based on individual information on evacuees, a means for using AI technology, and a means for obtaining and displaying the latest disaster prevention information via a smartphone.

[0937] System configuration and operation

[0938] 1. Registering evacuee information:

[0939] The user uses a smartphone to enter information about themselves and their family (e.g., name, age, allergy information, etc.).

[0940] The terminal encrypts the entered information and sends it to the server.

[0941] The server stores the received information in a database.

[0942] 2. Shelter status display:

[0943] The server collects information on the current situation at the evacuation center (e.g., number of people, necessary supplies, medical status, etc.) in real time.

[0944] The information collected by the server is integrated into a map database.

[0945] The device displays a map and provides the user with up-to-date evacuation shelter information.

[0946] 3. Automatic calculation of supplies and generation of distribution plans:

[0947] The server uses AI technology to calculate the amount of supplies needed based on information about evacuees.

[0948] An efficient distribution plan is generated based on the amount of supplies calculated by the server and notified to the terminal.

[0949] 4. Road damage status display:

[0950] The server automatically collects information from the Internet and analyzes the damage to the roads.

[0951] The server displays the collected information on a map and provides it to the user.

[0952] 5. Provision of disaster prevention information:

[0953] The server obtains the latest disaster prevention information (e.g., natural disaster predictions, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the terminal.

[0954] The terminal displays disaster prevention information to the user.

[0955] 6. Recommended disaster preparedness items:

[0956] The server generates an optimal disaster prevention goods list based on the evacuees' individual information (e.g., allergy information, health status, etc.).

[0957] The device displays a list of recommended disaster preparedness items to the user.

[0958] Specific examples

[0959] Users launch the app on their smartphone and register their own and their family's allergy information.

[0960] Based on the registration information, the server recommends disaster prevention products suitable for specific allergies and displays them on the device.

[0961] Hardware and software used

[0962] Hardware: Smartphones, smart glasses

[0963] Software: requests (server communication), geopy (geographic information acquisition), json (data serialization and encryption)

[0964] Prompt Sentence Examples

[0965] "Taro launches the app and registers allergy information for himself and his family. Please write the code to have the server recommend disaster preparedness products that are suitable for specific allergies."

[0966] The present invention, configured as described above, enables a wide range of support in the event of a disaster, such as rapid and accurate information registration, efficient distribution planning for supplies, and provision of disaster prevention information, thereby significantly improving the convenience and accuracy of information for evacuees and relief workers.

[0967] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0968] Step 1: Register user information

[0969] The user uses their smartphone to enter their own and their family's names, ages, allergy information, etc. The entered data is encrypted and sent from the device to a server. The server then stores the received data in a database. This allows for individualized response in emergencies.

[0970] Input: User information (name, age, allergy information, etc.)

[0971] Output: User information stored in the database

[0972] Step 2: Obtaining and displaying disaster prevention information

[0973] The terminal sends a request for disaster prevention information to the server. The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal. The terminal displays the disaster prevention information to the user. This allows the user to quickly obtain information.

[0974] Input: Disaster prevention information request

[0975] Output: Latest disaster information displayed on the device

[0976] Step 3: Register the current status of the evacuation shelter

[0977] Users record video and audio of the situation at the evacuation shelter. The device then uploads the data to a server. The server then analyzes the video and audio data and extracts important information (e.g., number of evacuees, necessary supplies, etc.).

[0978] Input: Video and audio data

[0979] Output: Analyzed current status information of evacuation shelters

[0980] Step 4: Map display of evacuation shelter information

[0981] The server integrates the analysis results into a map database. The device retrieves the data from the server and displays it on a map in real time, allowing users to visually check the occupancy status of evacuation shelters and requests for assistance.

[0982] Input: Evacuation shelter information after analysis

[0983] Output: Real-time evacuation shelter information displayed on a map

[0984] Step 5: Automatically calculate supplies and generate distribution plans

[0985] The server uses AI technology to analyze evacuee information and calculate the amount of supplies needed. It then generates an efficient distribution plan and notifies the device, thereby reducing waste of supplies.

[0986] Input: Evacuee information

[0987] Output: Calculated supply quantities and distribution plan

[0988] Step 6: Recommend disaster preparedness supplies

[0989] The server generates a list of the most suitable disaster prevention goods based on the individual information of the evacuee (e.g., allergy information, health condition). The terminal displays the list to the user, enabling support tailored to individual needs.

[0990] Input: Individual information of evacuees

[0991] Output: Recommended disaster preparedness supplies list

[0992] Step 7: View road damage

[0993] The server automatically collects information from the Internet and analyzes the state of road damage. The analysis results are displayed on a map and sent to the device, allowing users to plan safe evacuation routes.

[0994] Input: Road information on the Internet

[0995] Output: Road damage status displayed on a map

[0996] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0997] The present invention is a system that combines the following: registering evacuee information, grasping the status of evacuation centers, automatically calculating the amount of supplies and generating distribution plans, displaying road damage status by collecting information from the Internet, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion engine that recognizes the user's emotions.

[0998] During normal times: Dissemination of disaster prevention information and advance registration

[0999] Launching the app and displaying the latest information

[1000] 1. The user launches the "Hoshikuru★" app on their smartphone or tablet.

[1001] 2. The device requests the latest disaster prevention information from the server.

[1002] 3. The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[1003] 4. The device displays the received information on the disaster prevention portal screen.

[1004] Registering user information

[1005] 1. The user opens the "Register Information" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[1006] 2. The device encrypts the entered information and sends it to the server.

[1007] 3. The server stores the received user information in a database.

[1008] Disaster preparedness goods recommendations

[1009] 1. The server generates an optimal disaster preparedness goods list based on the user's registered information (such as allergy information and disease history).

[1010] 2. The server sends the generated list to the terminal.

[1011] 3. The device displays a list of recommended disaster preparedness items to the user.

[1012] In the event of a disaster: Registration of evacuee information and visualization of supplies

[1013] Launching the app at an evacuation shelter

[1014] 1. The user arrives at the evacuation site and launches the app.

[1015] 2. The device will display the evacuation information registration screen.

[1016] Registering evacuation shelter status

[1017] 1. Users record video or audio of the current situation at the evacuation shelter.

[1018] 2. The device uploads the recorded video and audio files to the server.

[1019] 3. The server analyzes the received video and audio files and extracts important information (e.g., the number of evacuees and necessary supplies).

[1020] Real-time display on a map

[1021] 1. The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[1022] 2. The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[1023] Automatic calculation and display of materials

[1024] 1. The server uses AI to calculate the amount of supplies needed based on evacuee information.

[1025] 2. The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[1026] 3. The device displays a list of supplies needed on a map.

[1027] Combining Emotion Engines

[1028] Recognizing and responding to user emotions

[1029] 1. Record the user's voice and facial expressions while using the app.

[1030] 2. The device sends voice and facial expression data to the emotion engine.

[1031] 3. The emotion engine analyzes the user's voice and facial expressions to recognize emotions.

[1032] 4. The emotion engine sends the recognition results to the server.

[1033] 5. The server adjusts the supplies and support needed based on the user's emotional state (e.g., providing additional relaxation items if stress levels are high).

[1034] 6. The device notifies the user of countermeasures and additional support information.

[1035] Specific examples

[1036] Specific examples of using the emotion engine

[1037] 1. User: Hanako, who is feeling stressed at the evacuation shelter, answers the app's questions by voice.

[1038] 2. Terminal: Sends Hanako's recorded voice to the emotion engine.

[1039] 3. Emotion engine: Recognizes high stress levels from Hanako's tone of voice and the content of her words.

[1040] 4. Emotion engine: Reports stress state to the server.

[1041] 5. Server: Suggest adding relaxation items to help Hanako reduce stress and update the support plan.

[1042] 6. Terminal: Display information about relaxation goods to Hanako.

[1043] The processing flow will be explained below.

[1044] During normal times: Dissemination of disaster prevention information and advance registration

[1045] Launching the app and displaying the latest information

[1046] Step 1:

[1047] The user launches the "Hoshikuru★" app.

[1048] Step 2:

[1049] The device requests the latest disaster prevention information from the server.

[1050] Step 3:

[1051] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[1052] Step 4:

[1053] The terminal displays the received information on the disaster prevention portal screen.

[1054] Registering user information

[1055] Step 1:

[1056] The user opens the "Register" section in the app.

[1057] Step 2:

[1058] The terminal displays a form for the user to enter information such as name, age, medical history, and allergy information.

[1059] Step 3:

[1060] The user enters the required information and presses the "Save" button.

[1061] Step 4:

[1062] The terminal encrypts the entered information and sends it to the server.

[1063] Step 5:

[1064] The server stores the received information in a database.

[1065] Disaster preparedness goods recommendations

[1066] Step 1:

[1067] The server analyzes the user's registration information (e.g., allergy information and medical history).

[1068] Step 2:

[1069] Based on the analysis results, the server generates an optimal list of disaster prevention supplies.

[1070] Step 3:

[1071] The server sends the generated list to the terminal.

[1072] Step 4:

[1073] The device displays a list of recommended disaster preparedness items to the user.

[1074] In the event of a disaster: Registration of evacuee information and visualization of supplies

[1075] Launching the app at an evacuation shelter

[1076] Step 1:

[1077] The user arrives at the evacuation site and launches the app.

[1078] Step 2:

[1079] The terminal displays the evacuee information registration screen.

[1080] Registering evacuation shelter status

[1081] Step 1:

[1082] Users record video or audio of the current situation at the evacuation shelter.

[1083] Step 2:

[1084] The device uploads recorded video and audio files to the server.

[1085] Step 3:

[1086] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[1087] Real-time display on a map

[1088] Step 1:

[1089] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[1090] Step 2:

[1091] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[1092] Automatic calculation and display of materials

[1093] Step 1:

[1094] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[1095] Step 2:

[1096] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[1097] Step 3:

[1098] The device displays a list of supplies needed on a map.

[1099] Combining Emotion Engines

[1100] Recognizing and responding to user emotions

[1101] Step 1:

[1102] Records voice and facial expressions while the user is using the app.

[1103] Step 2:

[1104] The device sends voice and facial expression data to the emotion engine.

[1105] Step 3:

[1106] The emotion engine analyzes the user's voice and facial expressions to recognize their emotions.

[1107] Step 4:

[1108] The emotion engine sends the recognition results to the server.

[1109] Step 5:

[1110] The server adjusts the supplies and support needed based on the user's emotional state (e.g., providing additional relaxation products if stress levels are high).

[1111] Step 6:

[1112] The device notifies the user of countermeasures and additional support information.

[1113] Specific examples

[1114] Specific examples of using the emotion engine

[1115] Step 1:

[1116] User: Hanako, who is feeling stressed at the evacuation shelter, answers the app's questions by voice.

[1117] Step 2:

[1118] Terminal: Sends Hanako's recorded voice to the emotion engine.

[1119] Step 3:

[1120] Emotion engine: Recognizes high stress levels from Hanako's tone of voice and the content of her words.

[1121] Step 4:

[1122] Emotion engine: Reports stress state to the server.

[1123] Step 5:

[1124] Server: Suggest adding relaxation items to help Hanako reduce stress and update the support plan.

[1125] Step 6:

[1126] Terminal: Display information about relaxation goods to Hanako.

[1127] Example 2

[1128] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1129] In recent years, the frequency and scale of natural disasters have increased, creating a need for information registration for evacuees, understanding the situation at evacuation centers, and quickly distributing relief supplies. However, current systems have problems in that they do not adequately provide support that takes into account the detailed information and emotional state of evacuees. Another issue is that they lack the functionality to display the situation at evacuation centers on a map in real time, making it difficult to create effective evacuation plans.

[1130] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for registering evacuee information, a means for displaying the situation of the evacuation center on a map in real time, a means for automatically calculating the amount of supplies needed and generating a distribution plan, and a means for recognizing the emotional state of the evacuees using an emotion analysis engine and providing appropriate support. This enables support that takes into account the detailed information and emotional state of the evacuees, and enables a quick response by understanding the situation of the evacuation center in real time.

[1131] "Evacuee information" is detailed data about individuals and families who evacuated during a disaster, including their names, ages, medical history, and allergies.

[1132] "Shelter status" refers to data that includes current information such as the number of evacuees and necessary supplies in the shelter, as well as the physical condition and environment of the shelter.

[1133] "Means of displaying on a map" refers to a technology that imports data onto an electronic map and displays it in real time in order to visually represent information about evacuation shelters and evacuees.

[1134] "Means for automatically calculating supplies" refers to technology that uses artificial intelligence and algorithms to automatically calculate the amount of relief supplies needed, such as food, water, and blankets, based on information about evacuees.

[1135] The "means for generating a distribution plan" is a means for planning and formulating the optimal distribution route and timing based on the calculated required amount of supplies.

[1136] "Means for automatically collecting information on the Internet" refers to technology for automatically collecting and analyzing road conditions, weather information, etc. from the web.

[1137] "Road damage status" is data showing the status of road damage and road closures caused by disasters.

[1138] "Disaster prevention information" includes information necessary in the event of a disaster, such as the location of evacuation shelters, emergency contact information, and evacuation procedures.

[1139] The "means for recommending disaster prevention goods" is a technology that suggests the most appropriate disaster prevention products, such as medicines, food, and bedding, based on the individual information of evacuees.

[1140] An "emotion analysis engine" is an algorithm or software that analyzes voice and facial expression data to recognize the emotional state of evacuees and present appropriate support measures.

[1141] The present invention is a system that combines the registration of evacuee information, grasping the situation at evacuation centers, automatically calculating and generating distribution plans for supplies, displaying road damage status, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion analysis engine.

[1142] Processing during normal times

[1143] Disaster prevention information dissemination and advance registration

[1144] The user launches the dedicated app on their smartphone or tablet. The device requests the latest disaster prevention information from the server, and the server retrieves the information from the disaster prevention portal database and sends it to the device. The device then displays the received information on the disaster prevention portal screen.

[1145] Users open the information registration section in the app and enter information about themselves and their family members (name, age, medical history, allergies, etc.). The device encrypts the entered information and sends it to the server, which then stores the received user information in a database.

[1146] The server generates a list of suitable disaster prevention goods based on the user's registration information and sends it to the terminal, which then displays the received list.

[1147] Disaster Preparedness

[1148] Registration of evacuee information and visualization of supplies

[1149] The user arrives at the evacuation shelter and launches the app. The device displays the evacuee information registration screen. The user records video or audio of the current situation at the evacuation shelter. The device uploads the recorded video and audio files to the server. The server analyzes the received files and extracts important information (e.g., the number of evacuees and necessary supplies).

[1150] The server integrates the analyzed information into a map database and updates the status of all evacuation shelters. The device retrieves the updated evacuation shelter information from the server and displays it on a map in real time.

[1151] The server uses AI to calculate the amount of supplies needed based on evacuee information and generates a list of supplies needed for each evacuation shelter. The terminal displays the received list of supplies on a map.

[1152] Combining Emotion Engines

[1153] When using the app, the user records their voice and facial expressions. The device then sends the voice and facial expression data to the emotion engine. The emotion engine analyzes the user's voice and facial expressions to recognize their emotions. The emotion engine then sends the recognition results to the server. The server then adjusts the supplies and support needed based on the user's emotional state (e.g., if stress levels are high, providing additional relaxation products). The device then notifies the user of countermeasures and additional support information.

[1154] Specific examples

[1155] Specific examples of using the emotion engine

[1156] 1. User: An individual experiencing stress in a shelter answers questions from the app by voice.

[1157] 2. Terminal: Sends the recorded audio to the emotion engine.

[1158] 3. Emotion Engine: Recognizes high stress levels from tone and verbal content.

[1159] 4. Emotion engine: Reports stress state to the server.

[1160] 5. Server: Suggest adding relaxation items to reduce stress and update the support plan.

[1161] 6. Terminal: Display information about relaxation products.

[1162] Example prompt for a generative AI model:

[1163] "Please explain how the emotion engine responds when evacuees are experiencing stress in an evacuation center."

[1164] As described above, the present invention makes it possible to provide support that takes into account detailed information and emotional state of evacuees, and enables quick response by understanding the situation at the evacuation shelter in real time.

[1165] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1166] Step 1:

[1167] The user launches a dedicated app on a smartphone or tablet.

[1168] Specific action: The user taps the app icon on the smartphone screen to launch the app.

[1169] Input: User taps

[1170] Output: App launch

[1171] Step 2:

[1172] The device requests the latest disaster prevention information from the server.

[1173] Specific operation: The terminal sends an HTTP request to the server, requesting the latest disaster prevention information.

[1174] Input: App launch signal

[1175] Output: HTTP request

[1176] Step 3:

[1177] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[1178] Specific operation: The server executes a database query, obtains the latest disaster prevention information data, and returns a response to the terminal.

[1179] Input: HTTP request

[1180] Output: Disaster prevention measures information

[1181] Step 4:

[1182] The terminal displays the received information on the disaster prevention portal screen.

[1183] Specific behavior: Parse the received data and display it in the user interface.

[1184] Input: Disaster prevention measures information

[1185] Output: Update the disaster prevention portal screen

[1186] Step 5:

[1187] The user opens the registration section within the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[1188] Specific operation: The user enters the required information into each input field on the app screen.

[1189] Input: User details

[1190] Output: Input data

[1191] Step 6:

[1192] The terminal encrypts the entered information and sends it to the server.

[1193] Specific operation: The terminal encrypts the input data (for example, AES encryption) and securely sends it to the server via an HTTP POST request.

[1194] Input: Input data

[1195] Output: Encrypted data

[1196] Step 7:

[1197] The server stores the received user information in a database.

[1198] Specific operation: Execute a query to insert the received data into the database.

[1199] Input: Encrypted data

[1200] Output: Save to database

[1201] Step 8:

[1202] The server generates a list of optimal disaster prevention goods based on the user's registration information and sends it to the terminal.

[1203] Specific operation: The server runs a recommendation algorithm to extract appropriate disaster prevention goods information from the database.

[1204] Input: User information

[1205] Output: Disaster preparedness kit list

[1206] Step 9:

[1207] The device displays a list of recommended disaster preparedness items to the user.

[1208] Specific operation: Parse the received list data and display it in the user interface.

[1209] Input: Disaster Preparedness Supplies List

[1210] Output: Update the recommendation screen

[1211] Step 10:

[1212] The user arrives at the evacuation shelter and launches the app.

[1213] Specific action: The user taps the app icon on their smartphone to launch it.

[1214] Input: Reached shelter

[1215] Output: App launch

[1216] Step 11:

[1217] The terminal displays the evacuee information registration screen.

[1218] Specific operation: The app will automatically transition to the evacuation information registration screen and display the input field.

[1219] Input: App launch signal

[1220] Output: Evacuee information registration screen

[1221] Step 12:

[1222] Users record video or audio of the current situation at the evacuation shelter.

[1223] Specific actions: Recording video or audio using the app's video recording or audio recording features.

[1224] Input: Shelter status

[1225] Output: Video or audio file

[1226] Step 13:

[1227] The device uploads recorded video and audio files to the server.

[1228] Specific operation: Sends the file to the server via the Web API.

[1229] Input: Video or audio file

[1230] Output: Uploaded file

[1231] Step 14:

[1232] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[1233] Specific operation: Extract important information from received files using appropriate analysis algorithms (e.g., voice recognition, video analysis).

[1234] Input: Video or audio file

[1235] Output: Extracted information

[1236] Step 15:

[1237] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[1238] Specific operation: The analysis results are updated to a geographic information system (GIS) database.

[1239] Input: Extracted information

[1240] Output: Updated map data

[1241] Step 16:

[1242] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[1243] Specific operation: Uses the map API to display the latest evacuation shelter information on a map.

[1244] Input: Updated map data

[1245] Output: Real-time map display

[1246] Step 17:

[1247] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[1248] Specific operation: Using an AI algorithm, the amount of supplies needed is calculated based on evacuee information.

[1249] Input: Evacuee information

[1250] Output: Material requirements data

[1251] Step 18:

[1252] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[1253] Specific operation: Create a list of supplies and send it to the terminal in JSON format.

[1254] Input: Material requirements data

[1255] Output: Supplies list

[1256] Step 19:

[1257] The device displays a list of supplies needed on a map.

[1258] Specific operation: Uses the map API to overlay the list of supplies on the map.

[1259] Input: Supply list

[1260] Output: Map display

[1261] Step 20:

[1262] Records voice and facial expressions while the user is using the app.

[1263] Specific operation: Use the recording and video recording functions within the app to record the user's voice and facial expressions.

[1264] Input: User's voice and facial expressions

[1265] Output: Audio and facial expression files

[1266] Step 21:

[1267] The device sends voice and facial expression data to the emotion engine.

[1268] Specific operation: Sends data to the sentiment analysis API via a POST request.

[1269] Input: Audio and facial expression files

[1270] Output: API request

[1271] Step 22:

[1272] The emotion engine analyzes the user's voice and facial expressions to recognize their emotions.

[1273] Specific operation: Using an analysis algorithm, voice tone and facial expression patterns are analyzed to generate emotion data.

[1274] Input: API request data

[1275] Output: Emotion data

[1276] Step 23:

[1277] The emotion engine sends the recognition results to the server.

[1278] Specific operation: Recognition results are sent to the server in JSON format.

[1279] Input: Emotion data

[1280] Output: Send data to the server

[1281] Step 24:

[1282] The server coordinates the necessary supplies and assistance based on the user's emotional state.

[1283] Specific actions: Update the supply list and support plan based on the recognition results.

[1284] Input: Emotion data

[1285] Output: Updated supply lists and support plans

[1286] Step 25:

[1287] The device notifies the user of countermeasures and additional support information.

[1288] Specific operation: Use the notification function to display additional support information to the user.

[1289] Input: Updated supply lists and assistance plans

[1290] Output: Notification message

[1291] (Application example 2)

[1292] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1293] Conventional evacuation support systems are limited to registering evacuee information and understanding the situation at evacuation shelters, and do not adequately provide supplies and support that take into account the emotional state and dynamics of individual evacuees. This can increase stress and anxiety in evacuation shelters, potentially damaging the mental and physical health of evacuees. Furthermore, efficient distribution of supplies using autonomous vehicles has not yet been realized, making it difficult to quickly provide supplies to evacuation shelters.

[1294] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for registering evacuee information, means for displaying the status of evacuation shelters on a map in real time, means for automatically calculating the amount of supplies needed and generating a distribution plan, means for automatically collecting information on the Internet and displaying road damage status, means for providing disaster prevention information, means for recommending disaster prevention goods based on individual information of evacuees, means for analyzing the voices and facial expressions of evacuees to recognize their emotions and coordinating the necessary supplies and support, and means for collecting evacuee information and efficiently distributing supplies using autonomous vehicles. This enables individual responses that take into account the emotional state of evacuees and rapid and efficient distribution of supplies using autonomous vehicles.

[1295] "Refugee information" refers to personal data such as the evacuee's name, age, health condition, and allergy information.

[1296] "Shelter status" refers to information about the current number of evacuees at the shelter, the type and amount of supplies needed, and the environmental condition of the shelter.

[1297] "Displaying on a map" means visually displaying the collected information on the evacuation shelter situation on a map in real time.

[1298] "Automatic calculation of supplies" means using artificial intelligence or algorithms to automatically calculate the type and amount of supplies needed based on information about evacuees and the situation at evacuation shelters.

[1299] "Generating a distribution plan" means planning the route and timing for distributing the calculated supplies to evacuation centers.

[1300] "Automatically collecting information on the Internet" means autonomously collecting relevant information from public data on the Internet and various information sources.

[1301] "Road damage status" is information about the state of damage to roads that have been damaged by earthquakes or other disasters.

[1302] "Disaster prevention information" refers to information on disaster risks, evacuation methods, safety measures, etc.

[1303] "Disaster prevention goods" refers to emergency supplies and equipment needed in the event of a disaster.

[1304] "Emotion recognition" means analyzing the voices and facial expressions of evacuees to determine their psychological state and emotions.

[1305] An "autonomous vehicle" is a vehicle that can operate autonomously without human operation, and uses sensors and AI to recognize the surrounding environment while driving.

[1306] "Efficient distribution of supplies" means setting and executing optimal routes and schedules to distribute needed supplies quickly and to the right places.

[1307] The present invention is a system that combines the following functions: registering evacuee information, grasping the status of evacuation shelters, automatically calculating the amount of supplies needed and creating distribution plans, displaying road damage status by collecting information from the Internet, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion engine that recognizes the user's emotions. A specific embodiment of this system is described below.

[1308] 1.Registering evacuee information

[1309] The server receives and encrypts information about evacuees entered by users through their smartphones or smart glasses, and stores it in a database, including the evacuees' names, ages, health conditions, and allergies.

[1310] 2. Understanding the situation at evacuation shelters

[1311] The devices record real-time video and audio of the current situation at evacuation centers and send it to a server. The server analyzes the data, extracts important information such as the number of evacuees and necessary supplies, and integrates it into a map database. The status of all evacuation centers is then updated and displayed on a map.

[1312] 3. Automatic calculation of supplies and generation of distribution plans

[1313] The server uses AI to automatically calculate the amount of supplies needed based on evacuee information and real-time evacuation shelter conditions. It then generates a list of supplies needed for each shelter and creates an efficient distribution plan. This plan is sent to autonomous vehicles, which distribute the supplies along the appropriate routes and at the appropriate times.

[1314] 4.Collecting information from the Internet and displaying road damage status

[1315] The server automatically collects road damage information from various sources on the Internet, verifies the safety of evacuation routes, and calculates the optimal evacuation route based on the collected information and displays it on a map.

[1316] 5. Provision of disaster prevention information

[1317] Users can receive the latest disaster prevention information provided by the server in real time on their smartphones or smart glasses, enabling them to take appropriate evacuation actions.

[1318] 6. Recommend disaster prevention goods based on individual evacuees' information

[1319] The server generates a list of necessary disaster prevention goods based on registered evacuee information and recommends them to the user. For example, it provides the most suitable foods and medicines based on allergies and illnesses.

[1320] 7. Emotion recognition and support with emotion engine

[1321] The device records the evacuees' voices and facial expressions and sends them to the emotion engine. The server uses the emotion engine to recognize the evacuees' stress levels and adjust the supplies and support they need. For example, if stress levels are high, the server will provide additional relaxation products.

[1322] Specific examples

[1323] 1. Registering evacuee information:

[1324] The user enters their own information (name, age, health condition, etc.) using their smartphone and sends it to the server.

[1325] 2. Assessing the situation at evacuation shelters:

[1326] The self-driving vehicle arrives at the evacuation shelter, records the current situation at the shelter using its onboard camera, and transmits the footage to a server.

[1327] 3. Emotion Recognition with Emotion Engine:

[1328] Evacuees who feel stressed in shelters answer questions in the app by voice, and the server sends the recorded voice data to an emotion engine to recognize their stress level.

[1329] Prompt Sentence Examples

[1330] Below are some example prompts to input to a generative AI model:

[1331] "Please create a program for a crisis management system. It will use smartphones and self-driving vehicles to register evacuee information, grasp the situation at evacuation centers, automatically calculate and plan distribution of supplies, and recognize user emotions. Users enter information about themselves and their families on their smartphones, and as soon as the self-driving vehicle arrives at the evacuation center, it will send the situation to the server in real time. The emotion engine will analyze the user's stress level and adjust the necessary supplies."

[1332] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1333] Step 1:

[1334] The user launches the "Evacuee Information Registration" app on their smartphone or smart glasses and enters information about themselves and their family members (such as name, age, health condition, allergy information, etc.). The entered evacuee information is encrypted by the device and sent to the server.

[1335] Input: User information (name, age, health condition, allergy information)

[1336] Output: Encrypted evacuee information

[1337] Step 2:

[1338] The server decrypts the encrypted evacuee information it receives and stores it in a database. At the same time, it generates a list of disaster prevention goods suitable for each evacuee and sends it to the terminal.

[1339] Input: Encrypted evacuee information

[1340] Output: Evacuee information database, disaster prevention goods list

[1341] Step 3:

[1342] When the user arrives at the evacuation shelter and launches the app, the device records video and audio of the situation at the shelter and uploads the data to the server.

[1343] Input: Video and audio data from the evacuation center

[1344] Output: Uploaded shelter status data

[1345] Step 4:

[1346] The server analyzes the video and audio data received from the evacuation shelters to extract the number of evacuees and necessary supplies. The extracted information is integrated into a map database, and the status of all evacuation shelters is updated on the map in real time.

[1347] Input: Video and audio data from the evacuation center

[1348] Output: Analyzed evacuation shelter status, updated map data

[1349] Step 5:

[1350] The server analyzes the evacuation shelter situation and evacuee information, and then automatically calculates the amount of supplies needed using AI. It then generates a list of the required supplies for each shelter and sends it to the device.

[1351] Input: Evacuee information, evacuation shelter status

[1352] Output: List of required supplies

[1353] Step 6:

[1354] The server uploads the generated supply distribution plan to the autonomous vehicles, which then calculate the optimal route and efficiently distribute supplies to evacuation centers.

[1355] Input: Supply distribution plan

[1356] Output: Optimal route, delivery of goods

[1357] Step 7:

[1358] When a user uses the app, their voice and facial expressions are recorded. The device then sends the voice and facial expression data to an emotion engine, which then analyzes the user's emotions. The analysis results are then sent to a server, and the assistance plan is updated based on the evacuees' emotional state.

[1359] Input: Speech and facial expression data

[1360] Output: Analyzed emotional state, updated support plan

[1361] Step 8:

[1362] The server sends the updated support plan to the device, which then notifies the user of the support and supplies they need. For example, if stress levels are high, the device suggests adding relaxation products.

[1363] Input: Updated support plan

[1364] Output: Support information notification, relaxation goods information

[1365] In this way, it is possible to consistently carry out everything from registering evacuee information to understanding the situation at evacuation centers, planning and executing the distribution of supplies, and even optimizing support through emotion recognition.

[1366] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1367] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1368] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1369] [Third embodiment]

[1370] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1371] 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.

[1372] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1373] 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.

[1374] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1375] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1376] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1377] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1378] 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.

[1379] 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.

[1380] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1381] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1382] During normal times: Dissemination of disaster prevention information and advance registration

[1383] 1. Launch the app and view the latest information

[1384] The user launches the "Hoshikuru★" app on a smartphone or tablet.

[1385] The device requests the latest disaster prevention information from the server.

[1386] The server retrieves the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the terminal.

[1387] The terminal displays the received information on the disaster prevention portal screen.

[1388] 2. User Information Registration

[1389] The user opens the "Information Registration" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[1390] The terminal encrypts the entered information and sends it to the server.

[1391] The server stores the received user information in a database.

[1392] 3. Disaster Preparedness Goods Recommendations

[1393] The server generates a list of optimal anti-theft products based on the user's registered information (such as allergy information and disease history).

[1394] The server sends the generated list to the terminal.

[1395] The device displays a list of recommended disaster preparedness items to the user.

[1396] In the event of a disaster: Registration of evacuee information and visualization of supplies

[1397] 1. Launch the app at the evacuation shelter

[1398] The user arrives at an evacuation site (e.g., a community center or school) and launches the app.

[1399] The terminal displays a screen for registering evacuee information and prompts the user to enter information.

[1400] 2. Register your evacuation shelter status

[1401] Users record video or audio of the current situation at the evacuation center (e.g., food shortages, requests for medicine, etc.).

[1402] The device uploads recorded video and audio files to the server.

[1403] The server analyzes the video and audio data it receives and extracts important information (such as the number of evacuees and the supplies they need).

[1404] 3. Real-time display on the map

[1405] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[1406] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[1407] 4. Automatic calculation and display of materials

[1408] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[1409] For example, consider the number of people in the shelter, their health status, and any special needs (allergies, illnesses, etc.).

[1410] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[1411] The device displays a list of supplies needed on a map.

[1412] Specific examples

[1413] Example of normal operation

[1414] 1. Launch the app and view the latest information

[1415] User: Taro launches the "Hoshikuru★" app.

[1416] Terminal: Displays the latest typhoon information and countermeasures from the disaster prevention portal.

[1417] 2. User Information Registration

[1418] User: Taro enters his name, family members' names, and allergy information.

[1419] Terminal: Sends input information to the server and stores it.

[1420] 3. Disaster Preparedness Goods Recommendations

[1421] Server: Based on Taro's allergy information, recommend food and medicines that are suitable for specific allergies.

[1422] Device: Display a list of recommended disaster prevention items to Taro.

[1423] Example of operation during a disaster

[1424] 1. Launch the app at the evacuation shelter

[1425] User: Hanako is affected by the disaster, evacuates to the nearest community center, and launches the app.

[1426] Terminal: Display the evacuee information registration screen.

[1427] 2. Register your evacuation shelter status

[1428] User: Hanako records the situation at the evacuation center (food shortages, requests for medicine, etc.) on video.

[1429] Device: Upload the recorded video to the server.

[1430] 3. Real-time display on the map

[1431] Server: Updates the map database with information about the community center where Hanako will take refuge.

[1432] Terminal: Displays evacuation shelter information on a map in real time.

[1433] 4. Automatic calculation and display of materials

[1434] Server: The AI ​​calculates the amount of supplies needed, taking into account the number of evacuees at the community center and Hanako's special needs.

[1435] Terminal: Display a list of food, water, and medicine needed at the community center on a map.

[1436] The processing flow will be explained below.

[1437] During normal times: Dissemination of disaster prevention information and advance registration

[1438] Launching the app and displaying the latest information

[1439] Step 1:

[1440] The user launches the "Hoshikuru★" app.

[1441] The device displays the Start screen.

[1442] Step 2:

[1443] The device requests the latest disaster prevention information from the server.

[1444] Step 3:

[1445] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[1446] Step 4:

[1447] The terminal displays the received information on the disaster prevention portal screen.

[1448] Registering user information

[1449] Step 1:

[1450] The user opens the "Register" section in the app.

[1451] Step 2:

[1452] The terminal displays a form for the user to enter information such as name, age, medical history, and allergy information.

[1453] Step 3:

[1454] The user enters the required information and presses the "Save" button.

[1455] Step 4:

[1456] The terminal encrypts the entered information and sends it to the server.

[1457] Step 5:

[1458] The server stores the received information in a database.

[1459] Disaster preparedness goods recommendations

[1460] Step 1:

[1461] The server analyzes the user's registration information (e.g., allergy information and medical history).

[1462] Step 2:

[1463] Based on the analysis results, the server generates an optimal list of disaster prevention supplies.

[1464] Step 3:

[1465] The server sends the generated list to the terminal.

[1466] Step 4:

[1467] The device displays a list of recommended disaster preparedness items to the user.

[1468] In the event of a disaster: Registration of evacuee information and visualization of supplies

[1469] Launching the app at an evacuation shelter

[1470] Step 1:

[1471] The user arrives at the evacuation site and launches the app.

[1472] Step 2:

[1473] The terminal displays the evacuee information registration screen.

[1474] Registering evacuation shelter status

[1475] Step 1:

[1476] Users record video or audio of the current situation at the evacuation shelter.

[1477] Step 2:

[1478] The device uploads recorded video and audio files to the server.

[1479] Step 3:

[1480] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[1481] Real-time display on a map

[1482] Step 1:

[1483] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[1484] Step 2:

[1485] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[1486] Automatic calculation and display of materials

[1487] Step 1:

[1488] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[1489] Step 2:

[1490] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[1491] Step 3:

[1492] The device displays a list of supplies needed on a map.

[1493] Example 1

[1494] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1495] In emergencies such as natural disasters, it is difficult to quickly and accurately register information about evacuees in shelters and grasp the situation at the shelters in real time. It is also difficult to properly calculate and distribute the necessary supplies. Therefore, a system that effectively solves these issues is needed to ensure the safety and security of evacuees. Furthermore, it is also important to recommend disaster prevention goods based on the individual information of evacuees, record the current situation at the shelters using video and audio, and extract important data from that information.

[1496] 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.

[1497] In this invention, the server includes a means for registering evacuee information, a means for displaying the status of evacuation shelters on a map in real time, and a means for automatically calculating the amount of supplies needed and generating a distribution plan. This allows for quick and accurate registration of evacuee information and understanding of the real-time situation at evacuation shelters. Furthermore, by appropriately calculating and distributing the necessary supplies, the safety and security of evacuees can be ensured. Furthermore, it is possible to recommend disaster prevention goods based on individual evacuee information, record the current situation at evacuation shelters using video and audio, and extract important data from that information.

[1498] A "means for registering evacuee information" is a device or software that allows evacuees to enter their own information (such as name, age, health status, etc.) and store that information in a database.

[1499] "Means for displaying the status of evacuation centers on a map in real time" refers to a device or software that visualizes the status of evacuation centers (number of people, supply status, etc.) on a map and updates and displays the current situation in real time.

[1500] "Means for automatically calculating the amount of supplies needed and generating a distribution plan" refers to a device or software that uses AI or other data analysis technology to calculate the amount of supplies needed at evacuation shelters and automatically create a subsequent distribution plan.

[1501] "Means for automatically collecting information on the Internet and displaying the status of road damage" refers to a device or software for automatically collecting information obtained from the Internet and displaying the status of road damage caused by disasters.

[1502] The "means for providing disaster prevention information" refers to a device or software for providing users with disaster prevention information such as disaster predictions and evacuation instructions.

[1503] "Means for recommending disaster prevention goods based on individual information of evacuees" refers to a device or software that suggests the most suitable disaster prevention goods for each evacuee based on individual information such as allergy information and disease history of the evacuee.

[1504] "Means for recording the current situation at the evacuation shelter using video or audio and uploading that information to a server" refers to a device or software for recording the situation at the evacuation shelter using video or audio and sending the recorded data to a server.

[1505] "Means for analyzing uploaded video and audio data and extracting important information" refers to a device or software that analyzes video and audio data uploaded to a server and automatically extracts important information such as the number of evacuees and necessary supplies.

[1506] "Means for generating a list of required supplies for each evacuation shelter and sending it to the terminal" refers to a device or software for creating a list of the amount of supplies needed at each evacuation shelter based on evacuee information and sending that list to the user's terminal.

[1507] The present invention relates to a system that registers information on evacuees, grasps the situation at evacuation shelters in real time, and appropriately calculates and distributes necessary supplies. The detailed configuration of the system of the present invention is shown below.

[1508] This system is operated by the user using a smartphone or tablet device. When the user launches the "disaster prevention app," the device communicates with the server via the internet to obtain and send the necessary information. The server uses a database and AI models to analyze and process various pieces of information. Specific hardware and software used include a smartphone, tablet, internet connection, database, and AI analysis tool.

[1509] First, the user launches the "disaster prevention app" on their smartphone or tablet device. The device then requests the latest disaster prevention information from the server via the Internet. The server then retrieves the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the device. The device then displays the received information on its screen, providing the user with the latest disaster prevention information.

[1510] Next, the user opens the "Information Registration" section in the app and enters information about themselves and their family members (such as name, age, medical history, allergies, etc.). The device encrypts the entered information using AES and sends it to the server, which then stores the received user information in a database.

[1511] The server then reads the user's registration information from the database and uses an AI model to generate a list of optimal disaster preparedness supplies that takes into account allergies and medical history. The generated disaster preparedness supply list is then sent from the server to the device and displayed on the device.

[1512] In the event of a disaster, the user reaches an evacuation site and launches the "disaster prevention app." The device displays a screen for registering evacuee information and asks the user to enter the necessary information. The user records video or audio of the current situation at the evacuation site (e.g., food shortages, requests for medicine, etc.) and uploads it to the server on the device. The server analyzes the received video and audio data using an AI analysis tool to extract important information such as food shortages and requests for medicine. The analyzed information is integrated into a map database, and the status of all evacuation sites is updated in real time. The device obtains the latest evacuation site information and displays it on a map.

[1513] The server then uses AI to calculate the amount of supplies needed based on information about the evacuees at the shelters, and generates a list of the required supplies for each shelter. The list is then sent to the device and displayed on the device.

[1514] As a concrete example, a user is affected by a disaster, evacuates to the nearest evacuation shelter, and launches a "disaster prevention app." The user records video of the situation at the evacuation shelter and uploads the video. The server analyzes the video, extracts important information, and displays it on a map. The server calculates the necessary supplies based on the evacuee's information, creates a list, and displays it on the device.

[1515] An example of a prompt sentence is, "A large-scale earthquake has occurred and I have arrived at a shelter. I would like to record a video of the situation at the shelter, upload it to the server, and receive appropriate material support. How can I do this?" By inputting such a prompt sentence into a generative AI model, detailed instructions can be automatically provided.

[1516] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1517] System program processing flow

[1518] During normal times: Dissemination of disaster prevention information and advance registration

[1519] Step 1: Launch the app and view the latest information

[1520] 1. The user launches the "disaster prevention app" on their smartphone or tablet.

[1521] Input: User initiated actions.

[1522] Output: None.

[1523] 2. The terminal sends a request for the latest disaster prevention information to the server via the Internet.

[1524] Input: App launch signal.

[1525] Output: Disaster prevention information request to the server.

[1526] 3. The server accesses the disaster prevention portal database and obtains the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.).

[1527] Input: A request from the terminal.

[1528] Output: Latest disaster prevention information data.

[1529] 4. The server sends the acquired information to the terminal.

[1530] Input: Latest disaster prevention information data.

[1531] Output: Data sent to the terminal.

[1532] 5. The terminal displays the received information on the screen, providing the user with the latest disaster prevention information.

[1533] Input: Disaster prevention information from the server.

[1534] Output: Disaster prevention information displayed on screen.

[1535] Step 2: Register user information

[1536] 1. The user opens the "Register Information" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[1537] Input: Manually enter user information.

[1538] Output: The entered user information.

[1539] 2. The terminal encrypts the user's input data using AES and sends it to the server.

[1540] Input: The user information entered.

[1541] Output: Encrypted user information data.

[1542] 3. The server stores the received user information data in a database.

[1543] Input: Encrypted user information data.

[1544] Output: User information stored in the database.

[1545] Step 3: Recommend disaster preparedness supplies

[1546] 1. The server reads the user's registration information from the database.

[1547] Input: User information retrieved from the database.

[1548] Output: User registration information.

[1549] 2. The server uses an AI model to generate a list of disaster preparedness items tailored to each user based on their registration information.

[1550] Input: User registration information.

[1551] Output: The generated disaster preparedness kit list.

[1552] 3. The server sends the generated disaster prevention goods list to the terminal.

[1553] Input: The generated disaster preparedness kit list.

[1554] Output: Data sent to the terminal.

[1555] 4. The device will display a list of recommended disaster preparedness items on the screen.

[1556] Input: Disaster preparedness supplies list from the server.

[1557] Output: Screen display of disaster preparedness item list.

[1558] In the event of a disaster: Registration of evacuee information and visualization of supplies

[1559] Step 1: Launch the app at the evacuation shelter

[1560] 1. The user arrives at the evacuation site and launches the app.

[1561] Input: User operation to launch the app.

[1562] Output: None.

[1563] 2. The terminal displays the evacuee information registration screen and prompts the user to enter information.

[1564] Input: App launch signal.

[1565] Output: Display of evacuee information registration screen.

[1566] Step 2: Register your evacuation status

[1567] 1. Users record video or audio of the current situation at the evacuation shelter.

[1568] Input: Shelter situation.

[1569] Output: Recorded video and audio files.

[1570] 2. The device uploads the recorded video and audio files to the server.

[1571] Input: Recorded video and audio files.

[1572] Output: Upload data to server.

[1573] 3. The server uses AI analysis tools to analyze the video and audio data received and extract important information such as food shortages and requests for medicine.

[1574] Input: Uploaded video and audio data.

[1575] Output: Important information data of the analysis results.

[1576] Step 3: Real-time display on a map

[1577] 1. The server integrates the analyzed information into a map database and updates the real-time status of all evacuation centers.

[1578] Input: Important information data of the analysis results.

[1579] Output: Updated map database.

[1580] 2. The device retrieves the latest evacuation shelter information from the server and displays that information on a map.

[1581] Input: Shelter information data from the server.

[1582] Output: Real-time display on map.

[1583] Step 4: Automatic calculation and display of materials

[1584] 1. The server uses AI to calculate the amount of supplies needed based on information about evacuees at shelters.

[1585] Input: Evacuee information data.

[1586] Output: Calculated material requirements data.

[1587] 2. The server generates a list of required supplies for each evacuation shelter.

[1588] Input: Material requirements data.

[1589] Output: List of supplies required.

[1590] 3. The server sends the list of required supplies to the terminal.

[1591] Input: Supply requirements list.

[1592] Output: Data sent to the terminal.

[1593] 4. The device displays a list of required supplies on a map.

[1594] Input: A list of material requirements from the server.

[1595] Output: Map display of supplies list.

[1596] (Application example 1)

[1597] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1598] The problem that this invention aims to solve is to provide a method for quickly and accurately registering information on evacuees during disasters, and efficiently aggregating and displaying the current status of evacuation centers and necessary supplies in real time. It also aims to provide a system that supports effective rescue efforts by recommending disaster prevention goods based on the individual circumstances of evacuees and accurately calculating the amount of supplies needed using AI technology. Furthermore, it aims to increase convenience and information accuracy for evacuees and rescue workers by constantly obtaining and displaying the latest disaster prevention information using smartphones.

[1599] 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.

[1600] In this invention, the server includes a means for registering evacuee information, a means for displaying the status of evacuation centers on a map in real time, and a means for automatically calculating the amount of supplies needed and generating a distribution plan. This allows for quick and accurate understanding of the status of evacuees during a disaster and for appropriate assistance to be provided. Furthermore, the server also includes a means for automatically collecting information from the Internet, displaying road damage status, and providing disaster prevention information. It also includes a means for recommending disaster prevention goods based on individual evacuees' information and a means for calculating the amount of supplies needed using AI technology. This enables efficient distribution of supplies at evacuation centers and access to the latest information via smartphone, significantly improving assistance activities during disasters.

[1601] "Means for registering evacuee information" refers to a function that allows evacuees to use smartphones or other devices to enter information about themselves and their families and store it in a database.

[1602] "A means of displaying the situation at evacuation centers on a map in real time" is a function that displays the current situation at evacuation centers on a map in real time, allowing evacuees and supporters to immediately understand the current situation.

[1603] "Means to automatically calculate the amount of supplies needed and generate a distribution plan" is a function that uses AI technology to calculate the amount of supplies needed based on information about evacuees at each shelter, and then creates an efficient distribution plan based on that.

[1604] "Means for automatically collecting information on the Internet and displaying road damage status" is a function for automatically collecting data on the Internet and displaying road damage status and passable routes.

[1605] "Means for providing disaster prevention information" refers to a function that obtains the latest information on disaster prevention (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the server and provides it to users.

[1606] "Means for recommending disaster prevention goods based on individual information of evacuees" is a function that generates a list of optimal disaster prevention goods based on the health information and special needs of evacuees and recommends them to users.

[1607] "Means using AI technology" refers to functions that use artificial intelligence (AI) to perform various advanced data processing tasks, such as analyzing evacuee information and calculating needed supplies.

[1608] "Means of obtaining and displaying the latest disaster prevention information via smartphone" refers to a function that obtains the latest disaster prevention information from a server via a smartphone app and displays it to the user.

[1609] This invention is a system for quickly and accurately registering information on evacuees in the event of a disaster, and efficiently aggregating and displaying the current status of evacuation centers and necessary supplies in real time. This system includes a means for registering evacuee information, a means for displaying the status of evacuation centers on a map in real time, a means for automatically calculating necessary supplies and generating a distribution plan, a means for automatically collecting information from the Internet and displaying the status of road damage, a means for providing disaster prevention information, a means for recommending disaster prevention goods based on individual information on evacuees, a means for using AI technology, and a means for obtaining and displaying the latest disaster prevention information via a smartphone.

[1610] System configuration and operation

[1611] 1. Registering evacuee information:

[1612] The user uses a smartphone to enter information about themselves and their family (e.g., name, age, allergy information, etc.).

[1613] The terminal encrypts the entered information and sends it to the server.

[1614] The server stores the received information in a database.

[1615] 2. Shelter status display:

[1616] The server collects information on the current situation at the evacuation center (e.g., number of people, necessary supplies, medical status, etc.) in real time.

[1617] The information collected by the server is integrated into a map database.

[1618] The device displays a map and provides the user with up-to-date evacuation shelter information.

[1619] 3. Automatic calculation of supplies and generation of distribution plans:

[1620] The server uses AI technology to calculate the amount of supplies needed based on information about evacuees.

[1621] An efficient distribution plan is generated based on the amount of supplies calculated by the server and notified to the terminal.

[1622] 4. Road damage status display:

[1623] The server automatically collects information from the Internet and analyzes the damage to the roads.

[1624] The server displays the collected information on a map and provides it to the user.

[1625] 5. Provision of disaster prevention information:

[1626] The server obtains the latest disaster prevention information (e.g., natural disaster predictions, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the terminal.

[1627] The terminal displays disaster prevention information to the user.

[1628] 6. Recommended disaster preparedness items:

[1629] The server generates an optimal disaster prevention goods list based on the evacuees' individual information (e.g., allergy information, health status, etc.).

[1630] The device displays a list of recommended disaster preparedness items to the user.

[1631] Specific examples

[1632] Users launch the app on their smartphone and register their own and their family's allergy information.

[1633] Based on the registration information, the server recommends disaster prevention products suitable for specific allergies and displays them on the device.

[1634] Hardware and software used

[1635] Hardware: Smartphones, smart glasses

[1636] Software: requests (server communication), geopy (geographic information acquisition), json (data serialization and encryption)

[1637] Prompt Sentence Examples

[1638] "Taro launches the app and registers allergy information for himself and his family. Please write the code to have the server recommend disaster preparedness products that are suitable for specific allergies."

[1639] The present invention, configured as described above, enables a wide range of support in the event of a disaster, such as rapid and accurate information registration, efficient distribution planning for supplies, and provision of disaster prevention information, thereby significantly improving the convenience and accuracy of information for evacuees and relief workers.

[1640] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1641] Step 1: Register user information

[1642] The user uses their smartphone to enter their own and their family's names, ages, allergy information, etc. The entered data is encrypted and sent from the device to a server. The server then stores the received data in a database. This allows for individualized response in emergencies.

[1643] Input: User information (name, age, allergy information, etc.)

[1644] Output: User information stored in the database

[1645] Step 2: Obtaining and displaying disaster prevention information

[1646] The terminal sends a request for disaster prevention information to the server. The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal. The terminal displays the disaster prevention information to the user. This allows the user to quickly obtain information.

[1647] Input: Disaster prevention information request

[1648] Output: Latest disaster information displayed on the device

[1649] Step 3: Register the current status of the evacuation shelter

[1650] Users record video and audio of the situation at the evacuation shelter. The device then uploads the data to a server. The server then analyzes the video and audio data and extracts important information (e.g., number of evacuees, necessary supplies, etc.).

[1651] Input: Video and audio data

[1652] Output: Analyzed current status information of evacuation shelters

[1653] Step 4: Map display of evacuation shelter information

[1654] The server integrates the analysis results into a map database. The device retrieves the data from the server and displays it on a map in real time, allowing users to visually check the occupancy status of evacuation shelters and requests for assistance.

[1655] Input: Evacuation shelter information after analysis

[1656] Output: Real-time evacuation shelter information displayed on a map

[1657] Step 5: Automatically calculate supplies and generate distribution plans

[1658] The server uses AI technology to analyze evacuee information and calculate the amount of supplies needed. It then generates an efficient distribution plan and notifies the device, thereby reducing waste of supplies.

[1659] Input: Evacuee information

[1660] Output: Calculated supply quantities and distribution plan

[1661] Step 6: Recommend disaster preparedness supplies

[1662] The server generates a list of the most suitable disaster prevention goods based on the individual information of the evacuee (e.g., allergy information, health condition). The terminal displays the list to the user, enabling support tailored to individual needs.

[1663] Input: Individual information of evacuees

[1664] Output: Recommended disaster preparedness supplies list

[1665] Step 7: View road damage

[1666] The server automatically collects information from the Internet and analyzes the state of road damage. The analysis results are displayed on a map and sent to the device, allowing users to plan safe evacuation routes.

[1667] Input: Road information on the Internet

[1668] Output: Road damage status displayed on a map

[1669] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1670] The present invention is a system that combines the following: registering evacuee information, grasping the status of evacuation centers, automatically calculating the amount of supplies and generating distribution plans, displaying road damage status by collecting information from the Internet, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion engine that recognizes the user's emotions.

[1671] During normal times: Dissemination of disaster prevention information and advance registration

[1672] Launching the app and displaying the latest information

[1673] 1. The user launches the "Hoshikuru★" app on their smartphone or tablet.

[1674] 2. The device requests the latest disaster prevention information from the server.

[1675] 3. The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[1676] 4. The device displays the received information on the disaster prevention portal screen.

[1677] Registering user information

[1678] 1. The user opens the "Register Information" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[1679] 2. The device encrypts the entered information and sends it to the server.

[1680] 3. The server stores the received user information in a database.

[1681] Disaster preparedness goods recommendations

[1682] 1. The server generates an optimal disaster preparedness goods list based on the user's registered information (such as allergy information and disease history).

[1683] 2. The server sends the generated list to the terminal.

[1684] 3. The device displays a list of recommended disaster preparedness items to the user.

[1685] In the event of a disaster: Registration of evacuee information and visualization of supplies

[1686] Launching the app at an evacuation shelter

[1687] 1. The user arrives at the evacuation site and launches the app.

[1688] 2. The device will display the evacuation information registration screen.

[1689] Registering evacuation shelter status

[1690] 1. Users record video or audio of the current situation at the evacuation shelter.

[1691] 2. The device uploads the recorded video and audio files to the server.

[1692] 3. The server analyzes the received video and audio files and extracts important information (e.g., the number of evacuees and necessary supplies).

[1693] Real-time display on a map

[1694] 1. The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[1695] 2. The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[1696] Automatic calculation and display of materials

[1697] 1. The server uses AI to calculate the amount of supplies needed based on evacuee information.

[1698] 2. The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[1699] 3. The device displays a list of supplies needed on a map.

[1700] Combining Emotion Engines

[1701] Recognizing and responding to user emotions

[1702] 1. Record the user's voice and facial expressions while using the app.

[1703] 2. The device sends voice and facial expression data to the emotion engine.

[1704] 3. The emotion engine analyzes the user's voice and facial expressions to recognize emotions.

[1705] 4. The emotion engine sends the recognition results to the server.

[1706] 5. The server adjusts the supplies and support needed based on the user's emotional state (e.g., providing additional relaxation items if stress levels are high).

[1707] 6. The device notifies the user of countermeasures and additional support information.

[1708] Specific examples

[1709] Specific examples of using the emotion engine

[1710] 1. User: Hanako, who is feeling stressed at the evacuation shelter, answers the app's questions by voice.

[1711] 2. Terminal: Sends Hanako's recorded voice to the emotion engine.

[1712] 3. Emotion engine: Recognizes high stress levels from Hanako's tone of voice and the content of her words.

[1713] 4. Emotion engine: Reports stress state to the server.

[1714] 5. Server: Suggest adding relaxation items to help Hanako reduce stress and update the support plan.

[1715] 6. Terminal: Display information about relaxation goods to Hanako.

[1716] The processing flow will be explained below.

[1717] During normal times: Dissemination of disaster prevention information and advance registration

[1718] Launching the app and displaying the latest information

[1719] Step 1:

[1720] The user launches the "Hoshikuru★" app.

[1721] Step 2:

[1722] The device requests the latest disaster prevention information from the server.

[1723] Step 3:

[1724] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[1725] Step 4:

[1726] The terminal displays the received information on the disaster prevention portal screen.

[1727] Registering user information

[1728] Step 1:

[1729] The user opens the "Register" section in the app.

[1730] Step 2:

[1731] The terminal displays a form for the user to enter information such as name, age, medical history, and allergy information.

[1732] Step 3:

[1733] The user enters the required information and presses the "Save" button.

[1734] Step 4:

[1735] The terminal encrypts the entered information and sends it to the server.

[1736] Step 5:

[1737] The server stores the received information in a database.

[1738] Disaster preparedness goods recommendations

[1739] Step 1:

[1740] The server analyzes the user's registration information (e.g., allergy information and medical history).

[1741] Step 2:

[1742] Based on the analysis results, the server generates an optimal list of disaster prevention supplies.

[1743] Step 3:

[1744] The server sends the generated list to the terminal.

[1745] Step 4:

[1746] The device displays a list of recommended disaster preparedness items to the user.

[1747] In the event of a disaster: Registration of evacuee information and visualization of supplies

[1748] Launching the app at an evacuation shelter

[1749] Step 1:

[1750] The user arrives at the evacuation site and launches the app.

[1751] Step 2:

[1752] The terminal displays the evacuee information registration screen.

[1753] Registering evacuation shelter status

[1754] Step 1:

[1755] Users record video or audio of the current situation at the evacuation shelter.

[1756] Step 2:

[1757] The device uploads recorded video and audio files to the server.

[1758] Step 3:

[1759] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[1760] Real-time display on a map

[1761] Step 1:

[1762] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[1763] Step 2:

[1764] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[1765] Automatic calculation and display of materials

[1766] Step 1:

[1767] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[1768] Step 2:

[1769] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[1770] Step 3:

[1771] The device displays a list of supplies needed on a map.

[1772] Combining Emotion Engines

[1773] Recognizing and responding to user emotions

[1774] Step 1:

[1775] Records voice and facial expressions while the user is using the app.

[1776] Step 2:

[1777] The device sends voice and facial expression data to the emotion engine.

[1778] Step 3:

[1779] The emotion engine analyzes the user's voice and facial expressions to recognize their emotions.

[1780] Step 4:

[1781] The emotion engine sends the recognition results to the server.

[1782] Step 5:

[1783] The server adjusts the supplies and support needed based on the user's emotional state (e.g., providing additional relaxation products if stress levels are high).

[1784] Step 6:

[1785] The device notifies the user of countermeasures and additional support information.

[1786] Specific examples

[1787] Specific examples of using the emotion engine

[1788] Step 1:

[1789] User: Hanako, who is feeling stressed at the evacuation shelter, answers the app's questions by voice.

[1790] Step 2:

[1791] Terminal: Sends Hanako's recorded voice to the emotion engine.

[1792] Step 3:

[1793] Emotion engine: Recognizes high stress levels from Hanako's tone of voice and the content of her words.

[1794] Step 4:

[1795] Emotion engine: Reports stress state to the server.

[1796] Step 5:

[1797] Server: Suggest adding relaxation items to help Hanako reduce stress and update the support plan.

[1798] Step 6:

[1799] Terminal: Display information about relaxation goods to Hanako.

[1800] Example 2

[1801] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1802] In recent years, the frequency and scale of natural disasters have increased, creating a need for information registration for evacuees, understanding the situation at evacuation centers, and quickly distributing relief supplies. However, current systems have problems in that they do not adequately provide support that takes into account the detailed information and emotional state of evacuees. Another issue is that they lack the functionality to display the situation at evacuation centers on a map in real time, making it difficult to create effective evacuation plans.

[1803] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for registering evacuee information, a means for displaying the situation of the evacuation center on a map in real time, a means for automatically calculating the amount of supplies needed and generating a distribution plan, and a means for recognizing the emotional state of the evacuees using an emotion analysis engine and providing appropriate support. This enables support that takes into account the detailed information and emotional state of the evacuees, and enables a quick response by understanding the situation of the evacuation center in real time.

[1804] "Evacuee information" is detailed data about individuals and families who evacuated during a disaster, including their names, ages, medical history, and allergies.

[1805] "Shelter status" refers to data that includes current information such as the number of evacuees and necessary supplies in the shelter, as well as the physical condition and environment of the shelter.

[1806] "Means of displaying on a map" refers to a technology that imports data onto an electronic map and displays it in real time in order to visually represent information about evacuation shelters and evacuees.

[1807] "Means for automatically calculating supplies" refers to technology that uses artificial intelligence and algorithms to automatically calculate the amount of relief supplies needed, such as food, water, and blankets, based on information about evacuees.

[1808] The "means for generating a distribution plan" is a means for planning and formulating the optimal distribution route and timing based on the calculated required amount of supplies.

[1809] "Means for automatically collecting information on the Internet" refers to technology for automatically collecting and analyzing road conditions, weather information, etc. from the web.

[1810] "Road damage status" is data showing the status of road damage and road closures caused by disasters.

[1811] "Disaster prevention information" includes information necessary in the event of a disaster, such as the location of evacuation shelters, emergency contact information, and evacuation procedures.

[1812] The "means for recommending disaster prevention goods" is a technology that suggests the most appropriate disaster prevention products, such as medicines, food, and bedding, based on the individual information of evacuees.

[1813] An "emotion analysis engine" is an algorithm or software that analyzes voice and facial expression data to recognize the emotional state of evacuees and present appropriate support measures.

[1814] The present invention is a system that combines the registration of evacuee information, grasping the situation at evacuation centers, automatically calculating and generating distribution plans for supplies, displaying road damage status, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion analysis engine.

[1815] Processing during normal times

[1816] Disaster prevention information dissemination and advance registration

[1817] The user launches the dedicated app on their smartphone or tablet. The device requests the latest disaster prevention information from the server, and the server retrieves the information from the disaster prevention portal database and sends it to the device. The device then displays the received information on the disaster prevention portal screen.

[1818] Users open the information registration section in the app and enter information about themselves and their family members (name, age, medical history, allergies, etc.). The device encrypts the entered information and sends it to the server, which then stores the received user information in a database.

[1819] The server generates a list of suitable disaster prevention goods based on the user's registration information and sends it to the terminal, which then displays the received list.

[1820] Disaster Preparedness

[1821] Registration of evacuee information and visualization of supplies

[1822] The user arrives at the evacuation shelter and launches the app. The device displays the evacuee information registration screen. The user records video or audio of the current situation at the evacuation shelter. The device uploads the recorded video and audio files to the server. The server analyzes the received files and extracts important information (e.g., the number of evacuees and necessary supplies).

[1823] The server integrates the analyzed information into a map database and updates the status of all evacuation shelters. The device retrieves the updated evacuation shelter information from the server and displays it on a map in real time.

[1824] The server uses AI to calculate the amount of supplies needed based on evacuee information and generates a list of supplies needed for each evacuation shelter. The terminal displays the received list of supplies on a map.

[1825] Combining Emotion Engines

[1826] When using the app, the user records their voice and facial expressions. The device then sends the voice and facial expression data to the emotion engine. The emotion engine analyzes the user's voice and facial expressions to recognize their emotions. The emotion engine then sends the recognition results to the server. The server then adjusts the supplies and support needed based on the user's emotional state (e.g., if stress levels are high, providing additional relaxation products). The device then notifies the user of countermeasures and additional support information.

[1827] Specific examples

[1828] Specific examples of using the emotion engine

[1829] 1. User: An individual experiencing stress in a shelter answers questions from the app by voice.

[1830] 2. Terminal: Sends the recorded audio to the emotion engine.

[1831] 3. Emotion Engine: Recognizes high stress levels from tone and verbal content.

[1832] 4. Emotion engine: Reports stress state to the server.

[1833] 5. Server: Suggest adding relaxation items to reduce stress and update the support plan.

[1834] 6. Terminal: Display information about relaxation products.

[1835] Example prompt for a generative AI model:

[1836] "Please explain how the emotion engine responds when evacuees are experiencing stress in an evacuation center."

[1837] As described above, the present invention makes it possible to provide support that takes into account detailed information and emotional state of evacuees, and enables quick response by understanding the situation at the evacuation shelter in real time.

[1838] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1839] Step 1:

[1840] The user launches a dedicated app on a smartphone or tablet.

[1841] Specific action: The user taps the app icon on the smartphone screen to launch the app.

[1842] Input: User taps

[1843] Output: App launch

[1844] Step 2:

[1845] The device requests the latest disaster prevention information from the server.

[1846] Specific operation: The terminal sends an HTTP request to the server, requesting the latest disaster prevention information.

[1847] Input: App launch signal

[1848] Output: HTTP request

[1849] Step 3:

[1850] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[1851] Specific operation: The server executes a database query, obtains the latest disaster prevention information data, and returns a response to the terminal.

[1852] Input: HTTP request

[1853] Output: Disaster prevention measures information

[1854] Step 4:

[1855] The terminal displays the received information on the disaster prevention portal screen.

[1856] Specific behavior: Parse the received data and display it in the user interface.

[1857] Input: Disaster prevention measures information

[1858] Output: Update the disaster prevention portal screen

[1859] Step 5:

[1860] The user opens the registration section within the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[1861] Specific operation: The user enters the required information into each input field on the app screen.

[1862] Input: User details

[1863] Output: Input data

[1864] Step 6:

[1865] The terminal encrypts the entered information and sends it to the server.

[1866] Specific operation: The terminal encrypts the input data (for example, AES encryption) and securely sends it to the server via an HTTP POST request.

[1867] Input: Input data

[1868] Output: Encrypted data

[1869] Step 7:

[1870] The server stores the received user information in a database.

[1871] Specific operation: Execute a query to insert the received data into the database.

[1872] Input: Encrypted data

[1873] Output: Save to database

[1874] Step 8:

[1875] The server generates a list of optimal disaster prevention goods based on the user's registration information and sends it to the terminal.

[1876] Specific operation: The server runs a recommendation algorithm to extract appropriate disaster prevention goods information from the database.

[1877] Input: User information

[1878] Output: Disaster preparedness kit list

[1879] Step 9:

[1880] The device displays a list of recommended disaster preparedness items to the user.

[1881] Specific operation: Parse the received list data and display it in the user interface.

[1882] Input: Disaster Preparedness Supplies List

[1883] Output: Update the recommendation screen

[1884] Step 10:

[1885] The user arrives at the evacuation shelter and launches the app.

[1886] Specific action: The user taps the app icon on their smartphone to launch it.

[1887] Input: Reached shelter

[1888] Output: App launch

[1889] Step 11:

[1890] The terminal displays the evacuee information registration screen.

[1891] Specific operation: The app will automatically transition to the evacuation information registration screen and display the input field.

[1892] Input: App launch signal

[1893] Output: Evacuee information registration screen

[1894] Step 12:

[1895] Users record video or audio of the current situation at the evacuation shelter.

[1896] Specific actions: Recording video or audio using the app's video recording or audio recording features.

[1897] Input: Shelter status

[1898] Output: Video or audio file

[1899] Step 13:

[1900] The device uploads recorded video and audio files to the server.

[1901] Specific operation: Sends the file to the server via the Web API.

[1902] Input: Video or audio file

[1903] Output: Uploaded file

[1904] Step 14:

[1905] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[1906] Specific operation: Extract important information from received files using appropriate analysis algorithms (e.g., voice recognition, video analysis).

[1907] Input: Video or audio file

[1908] Output: Extracted information

[1909] Step 15:

[1910] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[1911] Specific operation: The analysis results are updated to a geographic information system (GIS) database.

[1912] Input: Extracted information

[1913] Output: Updated map data

[1914] Step 16:

[1915] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[1916] Specific operation: Uses the map API to display the latest evacuation shelter information on a map.

[1917] Input: Updated map data

[1918] Output: Real-time map display

[1919] Step 17:

[1920] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[1921] Specific operation: Using an AI algorithm, the amount of supplies needed is calculated based on evacuee information.

[1922] Input: Evacuee information

[1923] Output: Material requirements data

[1924] Step 18:

[1925] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[1926] Specific operation: Create a list of supplies and send it to the terminal in JSON format.

[1927] Input: Material requirements data

[1928] Output: Supplies list

[1929] Step 19:

[1930] The device displays a list of supplies needed on a map.

[1931] Specific operation: Uses the map API to overlay the list of supplies on the map.

[1932] Input: Supply list

[1933] Output: Map display

[1934] Step 20:

[1935] Records voice and facial expressions while the user is using the app.

[1936] Specific operation: Use the recording and video recording functions within the app to record the user's voice and facial expressions.

[1937] Input: User's voice and facial expressions

[1938] Output: Audio and facial expression files

[1939] Step 21:

[1940] The device sends voice and facial expression data to the emotion engine.

[1941] Specific operation: Sends data to the sentiment analysis API via a POST request.

[1942] Input: Audio and facial expression files

[1943] Output: API request

[1944] Step 22:

[1945] The emotion engine analyzes the user's voice and facial expressions to recognize their emotions.

[1946] Specific operation: Using an analysis algorithm, voice tone and facial expression patterns are analyzed to generate emotion data.

[1947] Input: API request data

[1948] Output: Emotion data

[1949] Step 23:

[1950] The emotion engine sends the recognition results to the server.

[1951] Specific operation: Recognition results are sent to the server in JSON format.

[1952] Input: Emotion data

[1953] Output: Send data to the server

[1954] Step 24:

[1955] The server coordinates the necessary supplies and assistance based on the user's emotional state.

[1956] Specific actions: Update the supply list and support plan based on the recognition results.

[1957] Input: Emotion data

[1958] Output: Updated supply lists and support plans

[1959] Step 25:

[1960] The device notifies the user of countermeasures and additional support information.

[1961] Specific operation: Use the notification function to display additional support information to the user.

[1962] Input: Updated supply lists and assistance plans

[1963] Output: Notification message

[1964] (Application example 2)

[1965] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1966] Conventional evacuation support systems are limited to registering evacuee information and understanding the situation at evacuation shelters, and do not adequately provide supplies and support that take into account the emotional state and dynamics of individual evacuees. This can increase stress and anxiety in evacuation shelters, potentially damaging the mental and physical health of evacuees. Furthermore, efficient distribution of supplies using autonomous vehicles has not yet been realized, making it difficult to quickly provide supplies to evacuation shelters.

[1967] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for registering evacuee information, means for displaying the status of evacuation shelters on a map in real time, means for automatically calculating the amount of supplies needed and generating a distribution plan, means for automatically collecting information on the Internet and displaying road damage status, means for providing disaster prevention information, means for recommending disaster prevention goods based on individual information of evacuees, means for analyzing the voices and facial expressions of evacuees to recognize their emotions and coordinating the necessary supplies and support, and means for collecting evacuee information and efficiently distributing supplies using autonomous vehicles. This enables individual responses that take into account the emotional state of evacuees and rapid and efficient distribution of supplies using autonomous vehicles.

[1968] "Refugee information" refers to personal data such as the evacuee's name, age, health condition, and allergy information.

[1969] "Shelter status" refers to information about the current number of evacuees at the shelter, the type and amount of supplies needed, and the environmental condition of the shelter.

[1970] "Displaying on a map" means visually displaying the collected information on the evacuation shelter situation on a map in real time.

[1971] "Automatic calculation of supplies" means using artificial intelligence or algorithms to automatically calculate the type and amount of supplies needed based on information about evacuees and the situation at evacuation shelters.

[1972] "Generating a distribution plan" means planning the route and timing for distributing the calculated supplies to evacuation centers.

[1973] "Automatically collecting information on the Internet" means autonomously collecting relevant information from public data on the Internet and various information sources.

[1974] "Road damage status" is information about the state of damage to roads that have been damaged by earthquakes or other disasters.

[1975] "Disaster prevention information" refers to information on disaster risks, evacuation methods, safety measures, etc.

[1976] "Disaster prevention goods" refers to emergency supplies and equipment needed in the event of a disaster.

[1977] "Emotion recognition" means analyzing the voices and facial expressions of evacuees to determine their psychological state and emotions.

[1978] An "autonomous vehicle" is a vehicle that can operate autonomously without human operation, and uses sensors and AI to recognize the surrounding environment while driving.

[1979] "Efficient distribution of supplies" means setting and executing optimal routes and schedules to distribute needed supplies quickly and to the right places.

[1980] The present invention is a system that combines the following functions: registering evacuee information, grasping the status of evacuation shelters, automatically calculating the amount of supplies needed and creating distribution plans, displaying road damage status by collecting information from the Internet, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion engine that recognizes the user's emotions. A specific embodiment of this system is described below.

[1981] 1.Registering evacuee information

[1982] The server receives and encrypts information about evacuees entered by users via their smartphones or smart glasses, and stores it in a database, including the evacuees' names, ages, health conditions, and allergies.

[1983] 2. Understanding the situation at evacuation shelters

[1984] The devices record real-time video and audio of the current situation at evacuation centers and send it to a server. The server analyzes the data, extracts important information such as the number of evacuees and necessary supplies, and integrates it into a map database. The status of all evacuation centers is then updated and displayed on a map.

[1985] 3. Automatic calculation of supplies and generation of distribution plans

[1986] The server uses AI to automatically calculate the amount of supplies needed based on evacuee information and real-time evacuation shelter conditions. It then generates a list of supplies needed for each shelter and creates an efficient distribution plan. This plan is sent to autonomous vehicles, which distribute the supplies along the appropriate routes and at the appropriate times.

[1987] 4.Collecting information from the Internet and displaying road damage status

[1988] The server automatically collects road damage information from various sources on the Internet, verifies the safety of evacuation routes, and calculates the optimal evacuation route based on the collected information and displays it on a map.

[1989] 5. Providing disaster prevention information

[1990] Users can receive the latest disaster prevention information provided by the server in real time on their smartphones or smart glasses, enabling them to take appropriate evacuation actions.

[1991] 6. Recommend disaster prevention goods based on individual evacuees' information

[1992] The server generates a list of necessary disaster prevention goods based on registered evacuee information and recommends them to the user. For example, it provides the most suitable foods and medicines based on allergies and illnesses.

[1993] 7. Emotion recognition and support with emotion engine

[1994] The device records the evacuees' voices and facial expressions and sends them to the emotion engine. The server uses the emotion engine to recognize the evacuees' stress levels and adjust the supplies and support they need. For example, if stress levels are high, the server will provide additional relaxation products.

[1995] Specific examples

[1996] 1. Registering evacuee information:

[1997] The user enters their own information (name, age, health condition, etc.) using their smartphone and sends it to the server.

[1998] 2. Assessing the situation at evacuation shelters:

[1999] The self-driving vehicle arrives at the evacuation shelter, records the current situation at the shelter using its onboard camera, and transmits the footage to a server.

[2000] 3. Emotion Recognition with Emotion Engine:

[2001] Evacuees who feel stressed in shelters answer questions in the app by voice, and the server sends the recorded voice data to an emotion engine to recognize their stress level.

[2002] Prompt Sentence Examples

[2003] Below are some example prompts to input to a generative AI model:

[2004] "Please create a program for a crisis management system. It will use smartphones and self-driving vehicles to register evacuee information, grasp the situation at evacuation centers, automatically calculate and plan distribution of supplies, and recognize user emotions. Users enter information about themselves and their families on their smartphones, and as soon as the self-driving vehicle arrives at the evacuation center, it will send the situation to the server in real time. The emotion engine will analyze the user's stress level and adjust the necessary supplies."

[2005] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2006] Step 1:

[2007] The user launches the "Evacuee Information Registration" app on their smartphone or smart glasses and enters information about themselves and their family members (such as name, age, health condition, allergy information, etc.). The entered evacuee information is encrypted by the device and sent to the server.

[2008] Input: User information (name, age, health condition, allergy information)

[2009] Output: Encrypted evacuee information

[2010] Step 2:

[2011] The server decrypts the encrypted evacuee information it receives and stores it in a database. At the same time, it generates a list of disaster prevention goods suitable for each evacuee and sends it to the terminal.

[2012] Input: Encrypted evacuee information

[2013] Output: Evacuee information database, disaster prevention goods list

[2014] Step 3:

[2015] When the user arrives at the evacuation shelter and launches the app, the device records video and audio of the situation at the shelter and uploads the data to the server.

[2016] Input: Video and audio data from the evacuation center

[2017] Output: Uploaded shelter status data

[2018] Step 4:

[2019] The server analyzes the video and audio data received from the evacuation shelters to extract the number of evacuees and necessary supplies. The extracted information is integrated into a map database, and the status of all evacuation shelters is updated on the map in real time.

[2020] Input: Video and audio data from the evacuation center

[2021] Output: Analyzed evacuation shelter status, updated map data

[2022] Step 5:

[2023] Based on the server's analysis of the evacuation shelter situation and evacuee information, the AI ​​automatically calculates the amount of supplies needed, then generates a list of required supplies for each shelter and sends it to the terminal.

[2024] Input: Evacuee information, evacuation shelter status

[2025] Output: List of required supplies

[2026] Step 6:

[2027] The server uploads the generated supply distribution plan to the autonomous vehicles, which then calculate the optimal route and efficiently distribute supplies to evacuation centers.

[2028] Input: Supply distribution plan

[2029] Output: Optimal route, delivery of goods

[2030] Step 7:

[2031] When a user uses the app, their voice and facial expressions are recorded. The device then sends the voice and facial expression data to an emotion engine, which then analyzes the user's emotions. The analysis results are then sent to a server, and the assistance plan is updated based on the evacuees' emotional state.

[2032] Input: Speech and facial expression data

[2033] Output: Analyzed emotional state, updated support plan

[2034] Step 8:

[2035] The server sends the updated support plan to the device, which then notifies the user of the support and supplies they need. For example, if stress levels are high, the device suggests adding relaxation products.

[2036] Input: Updated support plan

[2037] Output: Support information notification, relaxation goods information

[2038] In this way, it is possible to consistently carry out everything from registering evacuee information to understanding the situation at evacuation centers, planning and executing the distribution of supplies, and even optimizing support through emotion recognition.

[2039] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2040] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2041] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2042] [Fourth embodiment]

[2043] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2044] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2045] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2046] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2047] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[2048] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[2049] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2050] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2051] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2052] 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.

[2053] 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.

[2054] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2055] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2056] During normal times: Dissemination of disaster prevention information and advance registration

[2057] 1. Launch the app and view the latest information

[2058] The user launches the "Hoshikuru★" app on a smartphone or tablet.

[2059] The device requests the latest disaster prevention information from the server.

[2060] The server retrieves the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the terminal.

[2061] The terminal displays the received information on the disaster prevention portal screen.

[2062] 2. User Information Registration

[2063] The user opens the "Information Registration" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[2064] The terminal encrypts the entered information and sends it to the server.

[2065] The server stores the received user information in a database.

[2066] 3. Disaster Preparedness Goods Recommendations

[2067] The server generates a list of optimal anti-theft products based on the user's registered information (such as allergy information and disease history).

[2068] The server sends the generated list to the terminal.

[2069] The device displays a list of recommended disaster preparedness items to the user.

[2070] In the event of a disaster: Registration of evacuee information and visualization of supplies

[2071] 1. Launch the app at the evacuation shelter

[2072] The user arrives at an evacuation site (e.g., a community center or school) and launches the app.

[2073] The terminal displays a screen for registering evacuee information and prompts the user to enter information.

[2074] 2. Register your evacuation shelter status

[2075] Users record video or audio of the current situation at the evacuation center (e.g., food shortages, requests for medicine, etc.).

[2076] The device uploads recorded video and audio files to the server.

[2077] The server analyzes the video and audio data it receives and extracts important information (such as the number of evacuees and the supplies they need).

[2078] 3. Real-time display on the map

[2079] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[2080] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[2081] 4. Automatic calculation and display of materials

[2082] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[2083] For example, consider the number of people in the shelter, their health status, and any special needs (allergies, illnesses, etc.).

[2084] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[2085] The device displays a list of supplies needed on a map.

[2086] Specific examples

[2087] Example of normal operation

[2088] 1. Launch the app and view the latest information

[2089] User: Taro launches the "Hoshikuru★" app.

[2090] Terminal: Displays the latest typhoon information and countermeasures from the disaster prevention portal.

[2091] 2. User Information Registration

[2092] User: Taro enters his name, family members' names, and allergy information.

[2093] Terminal: Sends input information to the server and stores it.

[2094] 3. Disaster Preparedness Goods Recommendations

[2095] Server: Based on Taro's allergy information, recommend food and medicines that are suitable for specific allergies.

[2096] Device: Display a list of recommended disaster prevention items to Taro.

[2097] Example of operation during a disaster

[2098] 1. Launch the app at the evacuation shelter

[2099] User: Hanako is affected by the disaster, evacuates to the nearest community center, and launches the app.

[2100] Terminal: Display the evacuee information registration screen.

[2101] 2. Register your evacuation shelter status

[2102] User: Hanako records the situation at the evacuation center (food shortages, requests for medicine, etc.) on video.

[2103] Device: Upload the recorded video to the server.

[2104] 3. Real-time display on the map

[2105] Server: Updates the map database with information about the community center where Hanako will take refuge.

[2106] Terminal: Displays evacuation shelter information on a map in real time.

[2107] 4. Automatic calculation and display of materials

[2108] Server: The AI ​​calculates the amount of supplies needed, taking into account the number of evacuees at the community center and Hanako's special needs.

[2109] Terminal: Display a list of food, water, and medicine needed at the community center on a map.

[2110] The processing flow will be explained below.

[2111] During normal times: Dissemination of disaster prevention information and advance registration

[2112] Launching the app and displaying the latest information

[2113] Step 1:

[2114] The user launches the "Hoshikuru★" app.

[2115] The device displays the Start screen.

[2116] Step 2:

[2117] The device requests the latest disaster prevention information from the server.

[2118] Step 3:

[2119] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[2120] Step 4:

[2121] The terminal displays the received information on the disaster prevention portal screen.

[2122] Registering user information

[2123] Step 1:

[2124] The user opens the "Register" section in the app.

[2125] Step 2:

[2126] The terminal displays a form for the user to enter information such as name, age, medical history, and allergy information.

[2127] Step 3:

[2128] The user enters the required information and presses the "Save" button.

[2129] Step 4:

[2130] The terminal encrypts the entered information and sends it to the server.

[2131] Step 5:

[2132] The server stores the received information in a database.

[2133] Disaster preparedness goods recommendations

[2134] Step 1:

[2135] The server analyzes the user's registration information (e.g., allergy information and medical history).

[2136] Step 2:

[2137] Based on the analysis results, the server generates an optimal list of disaster prevention supplies.

[2138] Step 3:

[2139] The server sends the generated list to the terminal.

[2140] Step 4:

[2141] The device displays a list of recommended disaster preparedness items to the user.

[2142] In the event of a disaster: Registration of evacuee information and visualization of supplies

[2143] Launching the app at an evacuation shelter

[2144] Step 1:

[2145] The user arrives at the evacuation site and launches the app.

[2146] Step 2:

[2147] The terminal displays the evacuee information registration screen.

[2148] Registering evacuation shelter status

[2149] Step 1:

[2150] Users record video or audio of the current situation at the evacuation shelter.

[2151] Step 2:

[2152] The device uploads recorded video and audio files to the server.

[2153] Step 3:

[2154] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[2155] Real-time display on a map

[2156] Step 1:

[2157] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[2158] Step 2:

[2159] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[2160] Automatic calculation and display of materials

[2161] Step 1:

[2162] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[2163] Step 2:

[2164] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[2165] Step 3:

[2166] The device displays a list of supplies needed on a map.

[2167] Example 1

[2168] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2169] In emergencies such as natural disasters, it is difficult to quickly and accurately register information about evacuees in shelters and grasp the situation at the shelters in real time. It is also difficult to properly calculate and distribute the necessary supplies. Therefore, a system that effectively solves these issues is needed to ensure the safety and security of evacuees. Furthermore, it is also important to recommend disaster prevention goods based on the individual information of evacuees, record the current situation at the shelters using video and audio, and extract important data from that information.

[2170] 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.

[2171] In this invention, the server includes a means for registering evacuee information, a means for displaying the status of evacuation shelters on a map in real time, and a means for automatically calculating the amount of supplies needed and generating a distribution plan. This allows for quick and accurate registration of evacuee information and understanding of the real-time situation at evacuation shelters. Furthermore, by appropriately calculating and distributing the necessary supplies, the safety and security of evacuees can be ensured. Furthermore, it is possible to recommend disaster prevention goods based on individual evacuee information, record the current situation at evacuation shelters using video and audio, and extract important data from that information.

[2172] A "means for registering evacuee information" is a device or software that allows evacuees to enter their own information (such as name, age, health status, etc.) and store that information in a database.

[2173] "Means for displaying the status of evacuation centers on a map in real time" refers to a device or software that visualizes the status of evacuation centers (number of people, supply status, etc.) on a map and updates and displays the current situation in real time.

[2174] "Means for automatically calculating the amount of supplies needed and generating a distribution plan" refers to a device or software that uses AI or other data analysis technology to calculate the amount of supplies needed at evacuation shelters and automatically create a subsequent distribution plan.

[2175] "Means for automatically collecting information on the Internet and displaying the status of road damage" refers to a device or software for automatically collecting information obtained from the Internet and displaying the status of road damage caused by disasters.

[2176] The "means for providing disaster prevention information" refers to a device or software for providing users with disaster prevention information such as disaster predictions and evacuation instructions.

[2177] "Means for recommending disaster prevention goods based on individual information of evacuees" refers to a device or software that suggests the most suitable disaster prevention goods for each evacuee based on individual information such as allergy information and disease history of the evacuee.

[2178] "Means for recording the current situation at the evacuation shelter using video or audio and uploading that information to a server" refers to a device or software for recording the situation at the evacuation shelter using video or audio and sending the recorded data to a server.

[2179] "Means for analyzing uploaded video and audio data and extracting important information" refers to a device or software that analyzes video and audio data uploaded to a server and automatically extracts important information such as the number of evacuees and necessary supplies.

[2180] "Means for generating a list of required supplies for each evacuation shelter and sending it to the terminal" refers to a device or software for creating a list of the amount of supplies needed at each evacuation shelter based on evacuee information and sending that list to the user's terminal.

[2181] The present invention relates to a system that registers information on evacuees, grasps the situation at evacuation shelters in real time, and appropriately calculates and distributes necessary supplies. The detailed configuration of the system of the present invention is shown below.

[2182] This system is operated by the user using a smartphone or tablet device. When the user launches the "disaster prevention app," the device communicates with the server via the internet to obtain and send the necessary information. The server uses a database and AI models to analyze and process various pieces of information. Specific hardware and software used include a smartphone, tablet, internet connection, database, and AI analysis tool.

[2183] First, the user launches the "disaster prevention app" on their smartphone or tablet device. The device then requests the latest disaster prevention information from the server via the Internet. The server then retrieves the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the device. The device then displays the received information on its screen, providing the user with the latest disaster prevention information.

[2184] Next, the user opens the "Information Registration" section in the app and enters information about themselves and their family members (such as name, age, medical history, allergies, etc.). The device encrypts the entered information using AES and sends it to the server, which then stores the received user information in a database.

[2185] The server then reads the user's registration information from the database and uses an AI model to generate a list of optimal disaster preparedness supplies that takes into account allergies and medical history. The generated disaster preparedness supply list is then sent from the server to the device and displayed on the device.

[2186] In the event of a disaster, the user reaches an evacuation site and launches the "disaster prevention app." The device displays a screen for registering evacuee information and asks the user to enter the necessary information. The user records video or audio of the current situation at the evacuation site (e.g., food shortages, requests for medicine, etc.) and uploads it to the server on the device. The server analyzes the received video and audio data using an AI analysis tool to extract important information such as food shortages and requests for medicine. The analyzed information is integrated into a map database, and the status of all evacuation sites is updated in real time. The device obtains the latest evacuation site information and displays it on a map.

[2187] The server then uses AI to calculate the amount of supplies needed based on information about the evacuees at the shelters, and generates a list of the required supplies for each shelter. The list is then sent to the device and displayed on the device.

[2188] As a concrete example, a user is affected by a disaster, evacuates to the nearest evacuation shelter, and launches a "disaster prevention app." The user records video of the situation at the evacuation shelter and uploads the video. The server analyzes the video, extracts important information, and displays it on a map. The server calculates the necessary supplies based on the evacuee's information, creates a list, and displays it on the device.

[2189] An example of a prompt sentence is, "A large-scale earthquake has occurred and I have arrived at a shelter. I would like to record a video of the situation at the shelter, upload it to the server, and receive appropriate material support. How can I do this?" By inputting such a prompt sentence into a generative AI model, detailed instructions can be automatically provided.

[2190] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2191] System program processing flow

[2192] During normal times: Dissemination of disaster prevention information and advance registration

[2193] Step 1: Launch the app and view the latest information

[2194] 1. The user launches the "disaster prevention app" on their smartphone or tablet.

[2195] Input: User initiated actions.

[2196] Output: None.

[2197] 2. The terminal sends a request for the latest disaster prevention information to the server via the Internet.

[2198] Input: App launch signal.

[2199] Output: Disaster prevention information request to the server.

[2200] 3. The server accesses the disaster prevention portal database and obtains the latest disaster prevention information (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.).

[2201] Input: A request from the terminal.

[2202] Output: Latest disaster prevention information data.

[2203] 4. The server sends the acquired information to the terminal.

[2204] Input: Latest disaster prevention information data.

[2205] Output: Data sent to the terminal.

[2206] 5. The terminal displays the received information on the screen, providing the user with the latest disaster prevention information.

[2207] Input: Disaster prevention information from the server.

[2208] Output: Disaster prevention information displayed on screen.

[2209] Step 2: Register user information

[2210] 1. The user opens the "Register Information" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[2211] Input: Manually enter user information.

[2212] Output: The entered user information.

[2213] 2. The terminal encrypts the user's input data using AES and sends it to the server.

[2214] Input: The user information entered.

[2215] Output: Encrypted user information data.

[2216] 3. The server stores the received user information data in a database.

[2217] Input: Encrypted user information data.

[2218] Output: User information stored in the database.

[2219] Step 3: Recommend disaster preparedness supplies

[2220] 1. The server reads the user's registration information from the database.

[2221] Input: User information retrieved from the database.

[2222] Output: User registration information.

[2223] 2. The server uses an AI model to generate a list of disaster preparedness items tailored to each user based on their registration information.

[2224] Input: User registration information.

[2225] Output: The generated disaster preparedness kit list.

[2226] 3. The server sends the generated disaster prevention goods list to the terminal.

[2227] Input: The generated disaster preparedness kit list.

[2228] Output: Data sent to the terminal.

[2229] 4. The device will display a list of recommended disaster preparedness items on the screen.

[2230] Input: Disaster preparedness supplies list from the server.

[2231] Output: Screen display of disaster preparedness item list.

[2232] In the event of a disaster: Registration of evacuee information and visualization of supplies

[2233] Step 1: Launch the app at the evacuation shelter

[2234] 1. The user arrives at the evacuation site and launches the app.

[2235] Input: User operation to launch the app.

[2236] Output: None.

[2237] 2. The terminal displays the evacuee information registration screen and prompts the user to enter information.

[2238] Input: App launch signal.

[2239] Output: Display of evacuee information registration screen.

[2240] Step 2: Register your evacuation status

[2241] 1. Users record video or audio of the current situation at the evacuation shelter.

[2242] Input: Shelter situation.

[2243] Output: Recorded video and audio files.

[2244] 2. The device uploads the recorded video and audio files to the server.

[2245] Input: Recorded video and audio files.

[2246] Output: Upload data to server.

[2247] 3. The server uses AI analysis tools to analyze the video and audio data received and extract important information such as food shortages and requests for medicine.

[2248] Input: Uploaded video and audio data.

[2249] Output: Important information data of the analysis results.

[2250] Step 3: Real-time display on a map

[2251] 1. The server integrates the analyzed information into a map database and updates the real-time status of all evacuation centers.

[2252] Input: Important information data of the analysis results.

[2253] Output: Updated map database.

[2254] 2. The device retrieves the latest evacuation shelter information from the server and displays that information on a map.

[2255] Input: Shelter information data from the server.

[2256] Output: Real-time display on map.

[2257] Step 4: Automatic calculation and display of materials

[2258] 1. The server uses AI to calculate the amount of supplies needed based on information about evacuees at shelters.

[2259] Input: Evacuee information data.

[2260] Output: Calculated material requirements data.

[2261] 2. The server generates a list of required supplies for each evacuation shelter.

[2262] Input: Material requirements data.

[2263] Output: List of supplies required.

[2264] 3. The server sends the list of required supplies to the terminal.

[2265] Input: Supply requirements list.

[2266] Output: Data sent to the terminal.

[2267] 4. The device displays a list of required supplies on a map.

[2268] Input: A list of material requirements from the server.

[2269] Output: Map display of supplies list.

[2270] (Application example 1)

[2271] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2272] The problem that this invention aims to solve is to provide a method for quickly and accurately registering information on evacuees during disasters, and efficiently aggregating and displaying the current status of evacuation centers and necessary supplies in real time. It also aims to provide a system that supports effective rescue efforts by recommending disaster prevention goods based on the individual circumstances of evacuees and accurately calculating the amount of supplies needed using AI technology. Furthermore, it aims to increase convenience and information accuracy for evacuees and rescue workers by constantly obtaining and displaying the latest disaster prevention information using smartphones.

[2273] 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.

[2274] In this invention, the server includes a means for registering evacuee information, a means for displaying the status of evacuation centers on a map in real time, and a means for automatically calculating the amount of supplies needed and generating a distribution plan. This allows for quick and accurate understanding of the status of evacuees during a disaster and for appropriate assistance to be provided. Furthermore, the server also includes a means for automatically collecting information from the Internet, displaying road damage status, and providing disaster prevention information. It also includes a means for recommending disaster prevention goods based on individual evacuees' information and a means for calculating the amount of supplies needed using AI technology. This enables efficient distribution of supplies at evacuation centers and access to the latest information via smartphone, significantly improving assistance activities during disasters.

[2275] "Means for registering evacuee information" refers to a function that allows evacuees to use smartphones or other devices to enter information about themselves and their families and store it in a database.

[2276] "A means of displaying the situation at evacuation centers on a map in real time" is a function that displays the current situation at evacuation centers on a map in real time, allowing evacuees and supporters to immediately understand the current situation.

[2277] "Means to automatically calculate the amount of supplies needed and generate a distribution plan" is a function that uses AI technology to calculate the amount of supplies needed based on information about evacuees at each shelter, and then creates an efficient distribution plan based on that.

[2278] "Means for automatically collecting information on the Internet and displaying road damage status" is a function for automatically collecting data on the Internet and displaying road damage status and passable routes.

[2279] "Means for providing disaster prevention information" refers to a function that obtains the latest information on disaster prevention (e.g., earthquake and typhoon forecasts, evacuation instructions, etc.) from the server and provides it to users.

[2280] "Means for recommending disaster prevention goods based on individual information of evacuees" is a function that generates a list of optimal disaster prevention goods based on the health information and special needs of evacuees and recommends them to users.

[2281] "Means using AI technology" refers to functions that use artificial intelligence (AI) to perform various advanced data processing tasks, such as analyzing evacuee information and calculating needed supplies.

[2282] "Means of obtaining and displaying the latest disaster prevention information via smartphone" refers to a function that obtains the latest disaster prevention information from a server via a smartphone app and displays it to the user.

[2283] This invention is a system for quickly and accurately registering information on evacuees in the event of a disaster, and efficiently aggregating and displaying the current status of evacuation centers and necessary supplies in real time. This system includes a means for registering evacuee information, a means for displaying the status of evacuation centers on a map in real time, a means for automatically calculating necessary supplies and generating a distribution plan, a means for automatically collecting information from the Internet and displaying the status of road damage, a means for providing disaster prevention information, a means for recommending disaster prevention goods based on individual information on evacuees, a means for using AI technology, and a means for obtaining and displaying the latest disaster prevention information via a smartphone.

[2284] System configuration and operation

[2285] 1. Registering evacuee information:

[2286] The user uses a smartphone to enter information about themselves and their family (e.g., name, age, allergy information, etc.).

[2287] The terminal encrypts the entered information and sends it to the server.

[2288] The server stores the received information in a database.

[2289] 2. Shelter status display:

[2290] The server collects information on the current situation at the evacuation center (e.g., number of people, necessary supplies, medical status, etc.) in real time.

[2291] The information collected by the server is integrated into a map database.

[2292] The device displays a map and provides the user with up-to-date evacuation shelter information.

[2293] 3. Automatic calculation of supplies and generation of distribution plans:

[2294] The server uses AI technology to calculate the amount of supplies needed based on information about evacuees.

[2295] An efficient distribution plan is generated based on the amount of supplies calculated by the server and notified to the terminal.

[2296] 4. Road damage status display:

[2297] The server automatically collects information from the Internet and analyzes the damage to the roads.

[2298] The server displays the collected information on a map and provides it to the user.

[2299] 5. Provision of disaster prevention information:

[2300] The server obtains the latest disaster prevention information (e.g., natural disaster predictions, evacuation instructions, etc.) from the disaster prevention portal database and sends it to the terminal.

[2301] The terminal displays disaster prevention information to the user.

[2302] 6. Recommended disaster preparedness items:

[2303] The server generates an optimal disaster prevention goods list based on the evacuees' individual information (e.g., allergy information, health status, etc.).

[2304] The device displays a list of recommended disaster preparedness items to the user.

[2305] Specific examples

[2306] Users launch the app on their smartphone and register their own and their family's allergy information.

[2307] Based on the registration information, the server recommends disaster prevention products suitable for specific allergies and displays them on the device.

[2308] Hardware and software used

[2309] Hardware: Smartphones, smart glasses

[2310] Software: requests (server communication), geopy (geographic information acquisition), json (data serialization and encryption)

[2311] Prompt Sentence Examples

[2312] "Taro launches the app and registers allergy information for himself and his family. Please write the code to have the server recommend disaster preparedness products that are suitable for specific allergies."

[2313] The present invention, configured as described above, enables a wide range of support in the event of a disaster, such as rapid and accurate information registration, efficient distribution planning for supplies, and provision of disaster prevention information, thereby significantly improving the convenience and accuracy of information for evacuees and relief workers.

[2314] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2315] Step 1: Register user information

[2316] The user uses their smartphone to enter their own and their family's names, ages, allergy information, etc. The entered data is encrypted and sent from the device to a server. The server then stores the received data in a database. This allows for individualized response in emergencies.

[2317] Input: User information (name, age, allergy information, etc.)

[2318] Output: User information stored in the database

[2319] Step 2: Obtaining and displaying disaster prevention information

[2320] The terminal sends a request for disaster prevention information to the server. The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal. The terminal displays the disaster prevention information to the user. This allows the user to quickly obtain information.

[2321] Input: Disaster prevention information request

[2322] Output: Latest disaster information displayed on the device

[2323] Step 3: Register the current status of the evacuation shelter

[2324] Users record video and audio of the situation at the evacuation shelter. The device then uploads the data to a server. The server then analyzes the video and audio data and extracts important information (e.g., number of evacuees, necessary supplies, etc.).

[2325] Input: Video and audio data

[2326] Output: Analyzed current status information of evacuation shelters

[2327] Step 4: Map display of evacuation shelter information

[2328] The server integrates the analysis results into a map database. The device retrieves the data from the server and displays it on a map in real time, allowing users to visually check the occupancy status of evacuation shelters and requests for assistance.

[2329] Input: Evacuation shelter information after analysis

[2330] Output: Real-time evacuation shelter information displayed on a map

[2331] Step 5: Automatically calculate supplies and generate distribution plans

[2332] The server uses AI technology to analyze evacuee information and calculate the amount of supplies needed. It then generates an efficient distribution plan and notifies the device, thereby reducing waste of supplies.

[2333] Input: Evacuee information

[2334] Output: Calculated supply quantities and distribution plan

[2335] Step 6: Recommend disaster preparedness supplies

[2336] The server generates a list of the most suitable disaster prevention goods based on the individual information of the evacuee (e.g., allergy information, health condition). The terminal displays the list to the user, enabling support tailored to individual needs.

[2337] Input: Individual information of evacuees

[2338] Output: Recommended disaster preparedness supplies list

[2339] Step 7: View road damage

[2340] The server automatically collects information from the Internet and analyzes the state of road damage. The analysis results are displayed on a map and sent to the device, allowing users to plan safe evacuation routes.

[2341] Input: Road information on the Internet

[2342] Output: Road damage status displayed on a map

[2343] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2344] The present invention is a system that combines the following: registering evacuee information, grasping the status of evacuation centers, automatically calculating the amount of supplies and generating distribution plans, displaying road damage status by collecting information from the Internet, providing disaster prevention information, recommending disaster prevention goods based on individual evacuee information, and an emotion engine that recognizes the user's emotions.

[2345] During normal times: Dissemination of disaster prevention information and advance registration

[2346] Launching the app and displaying the latest information

[2347] 1. The user launches the "Hoshikuru★" app on their smartphone or tablet.

[2348] 2. The device requests the latest disaster prevention information from the server.

[2349] 3. The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[2350] 4. The device displays the received information on the disaster prevention portal screen.

[2351] Registering user information

[2352] 1. The user opens the "Register Information" section in the app and enters information about themselves and their family members (name, age, medical history, allergies, etc.).

[2353] 2. The device encrypts the entered information and sends it to the server.

[2354] 3. The server stores the received user information in a database.

[2355] Disaster preparedness goods recommendations

[2356] 1. The server generates an optimal disaster preparedness goods list based on the user's registered information (such as allergy information and disease history).

[2357] 2. The server sends the generated list to the terminal.

[2358] 3. The device displays a list of recommended disaster preparedness items to the user.

[2359] In the event of a disaster: Registration of evacuee information and visualization of supplies

[2360] Launching the app at an evacuation shelter

[2361] 1. The user arrives at the evacuation site and launches the app.

[2362] 2. The device will display the evacuation information registration screen.

[2363] Registering evacuation shelter status

[2364] 1. Users record video or audio of the current situation at the evacuation shelter.

[2365] 2. The device uploads the recorded video and audio files to the server.

[2366] 3. The server analyzes the received video and audio files and extracts important information (e.g., the number of evacuees and necessary supplies).

[2367] Real-time display on a map

[2368] 1. The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[2369] 2. The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[2370] Automatic calculation and display of materials

[2371] 1. The server uses AI to calculate the amount of supplies needed based on evacuee information.

[2372] 2. The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[2373] 3. The device displays a list of supplies needed on a map.

[2374] Combining Emotion Engines

[2375] Recognizing and responding to user emotions

[2376] 1. Record the user's voice and facial expressions while using the app.

[2377] 2. The device sends voice and facial expression data to the emotion engine.

[2378] 3. The emotion engine analyzes the user's voice and facial expressions to recognize emotions.

[2379] 4. The emotion engine sends the recognition results to the server.

[2380] 5. The server adjusts the supplies and support needed based on the user's emotional state (e.g., providing additional relaxation items if stress levels are high).

[2381] 6. The device notifies the user of countermeasures and additional support information.

[2382] Specific examples

[2383] Specific examples of using the emotion engine

[2384] 1. User: Hanako, who is feeling stressed at the evacuation shelter, answers the app's questions by voice.

[2385] 2. Terminal: Sends Hanako's recorded voice to the emotion engine.

[2386] 3. Emotion engine: Recognizes high stress levels from Hanako's tone of voice and the content of her words.

[2387] 4. Emotion engine: Reports stress state to the server.

[2388] 5. Server: Suggest adding relaxation items to help Hanako reduce stress and update the support plan.

[2389] 6. Terminal: Display information about relaxation goods to Hanako.

[2390] The processing flow will be explained below.

[2391] During normal times: Dissemination of disaster prevention information and advance registration

[2392] Launching the app and displaying the latest information

[2393] Step 1:

[2394] The user launches the "Hoshikuru★" app.

[2395] Step 2:

[2396] The device requests the latest disaster prevention information from the server.

[2397] Step 3:

[2398] The server retrieves the latest disaster prevention information from the disaster prevention portal database and sends it to the terminal.

[2399] Step 4:

[2400] The terminal displays the received information on the disaster prevention portal screen.

[2401] Registering user information

[2402] Step 1:

[2403] The user opens the "Register" section in the app.

[2404] Step 2:

[2405] The terminal displays a form for the user to enter information such as name, age, medical history, and allergy information.

[2406] Step 3:

[2407] The user enters the required information and presses the "Save" button.

[2408] Step 4:

[2409] The terminal encrypts the entered information and sends it to the server.

[2410] Step 5:

[2411] The server stores the received information in a database.

[2412] Disaster preparedness goods recommendations

[2413] Step 1:

[2414] The server analyzes the user's registration information (e.g., allergy information and medical history).

[2415] Step 2:

[2416] Based on the analysis results, the server generates an optimal list of disaster prevention supplies.

[2417] Step 3:

[2418] The server sends the generated list to the terminal.

[2419] Step 4:

[2420] The device displays a list of recommended disaster preparedness items to the user.

[2421] In the event of a disaster: Registration of evacuee information and visualization of supplies

[2422] Launching the app at an evacuation shelter

[2423] Step 1:

[2424] The user arrives at the evacuation site and launches the app.

[2425] Step 2:

[2426] The terminal displays the evacuee information registration screen.

[2427] Registering evacuation shelter status

[2428] Step 1:

[2429] Users record video or audio of the current situation at the evacuation shelter.

[2430] Step 2:

[2431] The device uploads recorded video and audio files to the server.

[2432] Step 3:

[2433] The server analyzes the video and audio files it receives and extracts important information (e.g., the number of evacuees and the supplies they need).

[2434] Real-time display on a map

[2435] Step 1:

[2436] The server integrates the analyzed information into a map database and updates the status of all evacuation centers.

[2437] Step 2:

[2438] The device retrieves updated evacuation shelter information from the server and displays it on a map in real time.

[2439] Automatic calculation and display of materials

[2440] Step 1:

[2441] The server uses AI to calculate the amount of supplies needed based on information about evacuees.

[2442] Step 2:

[2443] The server generates a list of required supplies for each evacuation shelter and sends it to the terminal.

[2444] Step 3:

[2445] The device displays a list of supplies needed on a map.

[2446] Combining Emotion Engines

[2447] Recognizing and responding to user emotions

[2448] Step 1:

[2449] Records voice and facial expressions while the user is using the app.

[2450] Step 2:

[2451] The device sends voice and facial expression data to the emotion engine.

[2452] Step 3:

[2453] The emotion engine analyzes the user's voice and facial expressions to recognize their emotions.

[2454] Step 4:

[2455] The emotion engine sends the recognition results to the server.

[2456] Step 5:

[2457] The server adjusts the supplies and support needed based on the user's emotional state (e.g., providing additional relaxation products if stress levels are high).

[2458] Step 6:

[2459] The device notifies the user of countermeasures and additional support information.

[2460] Specific examples

[2461] Specific examples of using the emotion engine

[2462] Step 1:

[2463] User: Hanako, who is feeling stressed at the evacuation shelter, answers the app's questions by voice.

[2464] Step 2:

[2465] Terminal: Sends Hanako's recorded voice to the emotion engine.

[2466] Step 3:

[2467] Emotion engine: Recognizes high stress levels from Hanako's tone of voice and the content of her words.

[2468] Step 4:

[2469] Emotion engine: Reports stress state to the server.

[2470] Step 5:

[2471] Server: Suggest adding relaxation items to help Hanako reduce stress and update the support plan.

[2472] Step 6:

[2473] Terminal: Display information about relaxation goods to Hanako.

[2474] Example 2

[2475] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2476] In recent years, the frequency and scale of natural disasters have increased, creating a need for information registration for evacuees, understanding the situation at evacuation centers, and quickly distributing relief supplies. However, current systems have problems in that they do not adequately provide support that takes into account the detailed information and emotional state of evacuees. Another issue is that they lack the functionality to display the situation at evacuation centers on a map in real time, making it difficult to create effective evacuation plans.

[2477] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for registering evacuee information, a means for displaying the situation of the evacuation center on a map in real time, a means for automatically calculating the amount of supplies needed and generating a distribution plan, and a means for recognizing the emotional state of the evacuees using an emotion analysis engine and providing appropriate support. This enables support that takes into account the detailed information and emotional state of the evacuees, and enables a quick response by understanding the situation of the evacuation center in real time.

[2478] "Evacuee information" is detailed data about individuals and families who evacuated during a disaster, including their names, ages, medical history, and allergies.

[2479] "Shelter status" refers to data that includes current information such as the number of evacuees and necessary supplies in the shelter, as well as the physical condition and environment of the shelter.

[2480] "Means of displaying on a map" refers to a technology that imports data onto an electronic map and displays it in real time in order to visually represent information about evacuation shelters and evacuees.

[2481] "Means for automatically calculating supplies" refers to technology that uses artificial intelligence and algorithms to automatically calculate the amount of relief supplies needed, such as food, water, and blankets, based on information about evacuees.

[2482] The "means for generating a distribution plan" is a means for planning and formulating the optimal distribution route and timing based on the calculated required amount of supplies.

[2483] "Means for automatically collecting information on the Internet" refers to technology for automatically collecting and analyzing road conditions, weather information, etc. from the web.

[2484] "Road damage status" is data showing the status of road damage and road closures caused by disasters. 【24...

Claims

1. a means for registering evacuee information; A means to display the situation at evacuation centers on a map in real time, a means for automatically calculating required supplies and generating a distribution plan; A means for automatically collecting information on the Internet and displaying road damage status; a means for providing disaster prevention information; A method to recommend disaster prevention goods based on individual information of evacuees, A system including:

2. 2. The system according to claim 1, wherein information about evacuees and the status of evacuation shelters is registered by video and audio.

3. The system of claim 1 , which enables requests for assistance from outside the evacuation center.

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