System

Abstract

A system is provided.SOLUTION: The system includes a means for a user to input basic information such as an address and a family structure, a means for transmitting the input basic information to a server and storing the information in a database, a means for collecting past purchase histories and search histories of the user and storing the histories in the database, a means for collecting disaster information and shelter information of a local government and storing the information in the database, a means for an AI system to propose an optimal disaster prevention measure based on the stored information, and a means for displaying a list of the proposed disaster prevention measures on a terminal of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, the frequency of natural disasters is increasing, and many people are increasingly aware of the importance of taking appropriate disaster prevention measures. However, it is difficult for individual users to independently gather the necessary disaster prevention information and products and take measures, and they often lack the knowledge and time. In this situation, there is a growing need for a system that can easily propose and provide the optimal disaster prevention measures that meet individual needs. [Means for solving the problem]

[0005] The present invention includes a means for a user to input basic information such as address and family composition, and a means for transmitting the input basic information to a server and storing it in a database. It also includes a means for collecting the user's past purchase history and search history and storing them in a database, and a means for collecting disaster information and evacuation shelter information from local governments and storing them in a database. This allows the AI ​​system to propose optimal disaster prevention measures based on the stored information. It also includes a means for displaying a list of proposed disaster prevention measures on the user's device. It also includes a shopping function that allows the user to select and purchase necessary disaster prevention products, and a means for acquiring current location information, calculating a route to the nearest evacuation shelter, and displaying and guiding the route as a disaster prevention map. This series of means allows users to easily and quickly take appropriate disaster prevention measures.

[0006] "User" refers to an individual who uses the application to obtain disaster prevention measures.

[0007] "Address" refers to information that indicates the specific geographic location where a user resides.

[0008] "Family composition" refers to information indicating the status of members of the household to which the user belongs (e.g., spouse, children, parents, etc.).

[0009] "Basic information" refers to information necessary to identify an individual, such as the user's name, address, age, and family composition.

[0010] "Server" refers to a computer system that stores, processes, and serves data.

[0011] A "database" refers to a system for efficiently managing, storing, and retrieving structured data.

[0012] "Purchase history" refers to information about products and services that a user has previously purchased through an application.

[0013] "Search history" refers to historical information about searches that a user has performed within an application.

[0014] "Municipal disaster information" refers to the latest information and warnings about disasters provided by local governments.

[0015] "Evacuation shelter information" refers to information about locations and facilities where people can evacuate in the event of a disaster.

[0016] An "AI system" refers to a system that uses artificial intelligence to analyze data and propose optimal disaster prevention measures to users.

[0017] The "disaster prevention measures list" refers to a list of disaster prevention supplies and measures that the AI ​​system suggests are necessary for the user.

[0018] "Terminal" refers to a device (e.g., smartphone, tablet, etc.) operated by a user to use an application.

[0019] "Shopping function" refers to a function that allows users to select and purchase disaster prevention supplies within the application.

[0020] "Current location information" refers to real-time location information provided by the user's device.

[0021] An "evacuation route" refers to the optimal route from your current location to the nearest evacuation shelter.

[0022] A "disaster prevention map" refers to a map that visually shows disaster information and evacuation routes. [Brief explanation of the drawings]

[0023] [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

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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."

[0044] MODE FOR CARRYING OUT THE INVENTION

[0045] The "Easy Disaster Prevention Response App" of the present invention is a system designed to enable users to easily and efficiently take disaster countermeasures. A detailed embodiment of this system will be described.

[0046] 1. User registration and basic information entry

[0047] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which then stores it in a database.

[0048] 2. Collection of purchase and search history

[0049] When a user searches for or purchases disaster preparedness products within the app, the device collects the search query and purchase history in real time and sends it to the server, which stores this data in a database and updates the user's profile.

[0050] 3. Collecting disaster and evacuation shelter information

[0051] The server periodically checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in a database and used to create customized suggestions for each user.

[0052] 4. Proposal of disaster prevention measures

[0053] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the AI ​​system to calculate optimal disaster prevention measures. The proposed disaster prevention measures list is stored in a database and sent to the user's device, where it is displayed for the user to review.

[0054] 5. Shopping function

[0055] When the user checks the proposed disaster prevention measures list and adds the necessary items to the cart, the device sends the list of items they wish to purchase to the server. The server checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, along with delivery information.

[0056] 6. Disaster prevention map and route guidance

[0057] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store.

[0058] Specific examples

[0059] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as their address and family composition, the AI ​​system suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilets." The user adds the suggested items to their cart and completes the purchase process. The system then displays a route to the nearest evacuation shelter, allowing for smooth evacuation in the event of a disaster. The user can also print out the necessary disaster prevention and evacuation shelter information using a copy machine at a convenience store.

[0060] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures.

[0061] The processing flow will be explained below.

[0062] User registration and basic information entry

[0063] Step 1:

[0064] The user installs the app and accesses the user information input screen when launching it for the first time.

[0065] Step 2:

[0066] The user enters basic information such as name, address, age, and family composition.

[0067] Step 3:

[0068] The device generates an API request to send the basic information entered to the server.

[0069] Step 4:

[0070] The server stores the received information in a database.

[0071] Step 5:

[0072] After the server has completed the storage, it generates a registration confirmation message and sends it to the terminal.

[0073] Collection of purchase and search history

[0074] Step 1:

[0075] A user searches for disaster preparedness products within the app.

[0076] Step 2:

[0077] The device sends a search query to the server.

[0078] Step 3:

[0079] The user adds the product they like to the cart and completes the purchase.

[0080] Step 4:

[0081] The device sends purchase history and cart information to the server.

[0082] Step 5:

[0083] The server stores your search and purchase history in a database.

[0084] Collecting disaster and evacuation shelter information

[0085] Step 1:

[0086] The server periodically queries local government APIs and various public data sources to collect the latest disaster and evacuation shelter information.

[0087] Step 2:

[0088] The server stores the collected data in a database and formats the relevant information.

[0089] Disaster prevention measures proposals

[0090] Step 1:

[0091] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the AI ​​system and calculates the optimal disaster prevention measures.

[0092] Step 2:

[0093] The server generates a list of proposed disaster prevention measures and stores it in a database.

[0094] Step 3:

[0095] The server generates a response to send the generated list to the user's terminal.

[0096] Step 4:

[0097] The device displays a list of disaster prevention measures to the user and provides an interface where the user can check the proposed measures.

[0098] Shopping feature

[0099] Step 1:

[0100] The user checks the disaster preparedness list and adds the necessary items to the cart.

[0101] Step 2:

[0102] The device generates an API request to send the list of products desired for purchase to the server.

[0103] Step 3:

[0104] Based on the product list received by the server, the server checks stock status and price information and processes the payment.

[0105] Step 4:

[0106] The server generates a purchase confirmation message and sends it to the user's terminal.

[0107] Step 5:

[0108] The terminal displays a notification to the user that the purchase is complete and displays product delivery information.

[0109] Disaster prevention map and route guidance

[0110] Step 1:

[0111] The user opens the disaster prevention map function within the app.

[0112] Step 2:

[0113] The device obtains the user's current location information and generates an API request to send to the server.

[0114] Step 3:

[0115] The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route.

[0116] Step 4:

[0117] The server generates a response including the calculated route information and sends it to the terminal.

[0118] Step 5:

[0119] The device displays evacuation routes and disaster prevention maps to the user and provides voice guidance.

[0120] Step 6:

[0121] Users can print out disaster prevention information and evacuation shelter information as needed using a copy machine at a convenience store.

[0122] Example 1

[0123] 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."

[0124] Disaster prevention measures are becoming increasingly important in modern society, and individual users are being asked to take appropriate measures quickly and efficiently. However, currently available disaster prevention applications and tools do not fully utilize individual user information, making it difficult to propose optimal disaster prevention measures to users. Furthermore, there are issues with the accuracy and timeliness of collecting disaster and evacuation shelter information and presenting optimal evacuation routes. For this reason, there is a demand for disaster response systems that are easy for users to use and offer advanced functions.

[0125] 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.

[0126] In this invention, the server includes: means for a user to input basic information such as place of residence and family composition; means for transmitting the input basic information to the server and storing it in a data management device; means for collecting the user's past purchase history and search history and storing it in the data management device; means for automatically collecting disaster information and evacuation shelter information from local governments and storing it in the data management device; means for a generative AI model to propose optimal disaster prevention measures based on the stored information; means for displaying a list of the proposed disaster prevention measures on the user's connected device; means for the user to acquire current location information from the screen of the connected device and send it to the server; means for the server to compare the current location information with the evacuation shelter information and calculate the optimal evacuation route; and means for transmitting the calculation results to the connected device and displaying them. This allows users to quickly and effectively check and prepare individually optimized disaster prevention measures and take appropriate evacuation actions in the event of a disaster.

[0127] "User" refers to an individual who uses this system to manage disaster prevention measures and evacuation actions.

[0128] "Basic information" refers to personal data entered by the user, such as place of residence, family composition, age, and gender.

[0129] "Server" refers to an online computer system that receives, processes, and stores data sent by users.

[0130] A "data management device" refers to a system that is connected to a server and includes a database for storing and managing basic user information, purchase history, search history, disaster information, and the like.

[0131] "Purchase history" refers to a record of disaster prevention related products and the like that a user has purchased in the past.

[0132] "Search History" refers to a record of queries or items that a User has searched for within an Application.

[0133] "Disaster information" refers to data on the occurrence, intensity, and scope of impact of a disaster.

[0134] "Shelter information" refers to data provided by local governments regarding the location, capacity, and facility status of shelters.

[0135] A "generative AI model" refers to a system that uses artificial intelligence technology to suggest optimal disaster prevention measures to users.

[0136] "Disaster prevention measures list" refers to a list of disaster prevention measures optimized for the user proposed by the generative AI model.

[0137] "Connection device" refers to a terminal device (smartphone, tablet, PC, etc.) that a user uses to connect to a server.

[0138] "E-commerce function" refers to the function that allows users to select and purchase suggested disaster prevention related products online.

[0139] "Current location information" refers to location information (such as GPS data) acquired by the user's device.

[0140] An "evacuation route" refers to a route that allows a user to travel safely and quickly to the nearest evacuation shelter in the event of a disaster.

[0141] A "disaster prevention map" refers to a map that visually displays information related to disaster prevention, such as evacuation routes and the locations of evacuation shelters.

[0142] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to take disaster countermeasures quickly and efficiently. This system has functions such as user registration and basic information input, collection of purchase history and search history, collection of disaster information and evacuation shelter information, disaster prevention measures proposals, shopping function, disaster prevention map and route guidance, etc.

[0143] Hardware and Software Details

[0144] server:

[0145] It is an online server equipped with a data management device for storing and processing information. It uses MySQL or PostgreSQL as its database.

[0146] As an AI system, we use a generative AI model (e.g., OpenAI's GPT).

[0147] Run a script that periodically collects information from the city's APIs and public data sources.

[0148] Device:

[0149] This refers to devices such as smartphones, tablets, and PCs on which users install applications.

[0150] Search queries and purchase history are collected in real time and sent to the server.

[0151] User:

[0152] This is an individual who downloads and installs the app and enters basic information.

[0153] Review the proposed disaster prevention measures and purchase the necessary items.

[0154] Program processing flow

[0155] 1. User registration and basic information entry

[0156] Device: The user downloads and installs the app and enters basic information the first time they launch it.

[0157] Terminal: Sends the entered information to the server as an HTTP request.

[0158] Server: Stores the received user information in a database.

[0159] 2. Collection of purchase and search history

[0160] Device: Every time a user searches for or purchases a disaster prevention product, the data is collected in real time and sent to the server.

[0161] Server: Stores the received data and updates the user's profile.

[0162] 3. Collecting disaster and evacuation shelter information

[0163] Server: Automatically checks local government APIs and public data sources, and stores the latest disaster and evacuation shelter information in a database.

[0164] 4. Proposal of disaster prevention measures

[0165] Server: Inputs the user's basic information, historical data, and disaster information into the generative AI model and calculates optimal disaster prevention measures.

[0166] Generative AI model: Generates a disaster prevention measures list based on input information.

[0167] Server: Sends the generated list to the device.

[0168] Device: Display the list in the user interface so that the user can see it.

[0169] 5. Shopping function

[0170] User: Selects an item from the list of suggested disaster preparedness measures and adds it to their cart.

[0171] Terminal: Sends cart information to the server.

[0172] Server: After checking the stock, the purchase is processed through the payment system.

[0173] Server: Sends a notification of purchase completion and shipping information to the device.

[0174] 6. Disaster prevention map and route guidance

[0175] User: Use the disaster prevention map function to obtain current location information.

[0176] Device: Sends current location information to the server.

[0177] Server: Compares with evacuation shelter information and calculates the optimal evacuation route.

[0178] Server: Sends the calculation results to the terminal.

[0179] Terminal: Displays disaster prevention maps and evacuation routes.

[0180] Specific examples

[0181] For example, consider the case where a user living in Shibuya Ward launches the app and checks new disaster prevention measures.

[0182] 1. User: Launches the app and enters basic information such as name, address, and family composition.

[0183] 2. Terminal: Sends information to the server.

[0184] 3. Server: Stores the input information in a database and inputs the data into the AI ​​system to calculate disaster prevention measures.

[0185] 4. Generative AI model: Generates a list of disaster prevention measures such as "three days' worth of water," "emergency food," and "portable toilet."

[0186] 5. Server: Sends the list to the terminal and displays it for the user to review.

[0187] 6. User: Adds the desired items to the cart and checks out.

[0188] 7. Server: Once the payment process is complete, a notification of purchase completion and delivery information is sent to the terminal.

[0189] 8. User: Check the route to the nearest evacuation shelter and use the disaster prevention map. If necessary, this information can be printed out on a copy machine at a convenience store.

[0190] Prompt Sentence Examples

[0191] For example, the following prompt sentence can be input to a generative AI model to generate a list of disaster prevention measures:

[0192] "A single man in his 30s living in Shibuya Ward wants to check his disaster preparedness. Please make a list of the best disaster preparedness measures for him."

[0193] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures.

[0194] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0195] Step 1:

[0196] User registration and basic information entry

[0197] The user downloads and installs the app.

[0198] Enter: Install app

[0199] Output: App ready to launch

[0200] How it works: Download the app from the app store (Google Play or Apple App Store) and install it.

[0201] When the user starts the app for the first time, they enter basic information (place of residence, family composition, etc.).

[0202] Input: User's basic information (name, address, age, family composition, etc.)

[0203] Output: Local storage of input information

[0204] How it works: Launch the installed app and follow the on-screen instructions to enter your basic information.

[0205] The terminal sends the entered basic information to the server as an HTTP request.

[0206] Input: Basic information entered by the user

[0207] Output: Data transmission to server begins

[0208] How it works: When you press the send button in the app, the information is sent to the server.

[0209] The server stores the received user information in a database.

[0210] Input: User information sent from the device

[0211] Output: Information saved to database

[0212] What happens: A script is executed on the server side to save the data to the database.

[0213] Step 2:

[0214] Collection of purchase and search history

[0215] The device collects information in real time when a user searches for or purchases disaster prevention products.

[0216] Input: User search queries, purchase history

[0217] Output: Recorded to local cache

[0218] How it works: Temporarily stores data when users search for and purchase products.

[0219] The terminal transmits the collected data to the server.

[0220] Input: Collected search queries, purchase history

[0221] Output: Data sent to server completed

[0222] Operation: Collected data is sent to the server periodically or when an event occurs.

[0223] The server stores the received data in a database and updates the user profile.

[0224] Input: Search queries sent from the device, purchase history

[0225] Output: Saved to database and user profile updated

[0226] What it does: Saves the data in the database and keeps each user's profile up to date.

[0227] Step 3:

[0228] Collecting disaster and evacuation shelter information

[0229] The server regularly checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information.

[0230] Input: API calls and public data access

[0231] Output: Latest disaster information, evacuation shelter information

[0232] What it does: Runs a script periodically and calls an API to retrieve data.

[0233] The server stores the collected information in a database.

[0234] Input: Collected disaster information, evacuation shelter information

[0235] Output: Information saved to database

[0236] Behavior: Store in a database and make it accessible to other functions.

[0237] Step 4:

[0238] Disaster prevention measures proposals

[0239] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the generated AI model.

[0240] Input: User basic information, history data, disaster information

[0241] Output: Input to generative AI model completed

[0242] How it works: Preprocesses a dataset to feed into a generative AI model.

[0243] A generative AI model calculates and suggests a list of disaster prevention measures.

[0244] Input: Generated dataset

[0245] Output: List of optimal disaster prevention measures

[0246] How it works: A generative AI model processes data and generates a list of suggestions.

[0247] The server stores the proposed list in a database and sends it to the terminal.

[0248] Input: A list of disaster prevention measures from a generative AI model

[0249] Output: Saved to database, sent to terminal

[0250] Behavior: Save in database and send to user's device.

[0251] The terminal displays the received list on the user interface.

[0252] Input: Disaster prevention measures list sent from the server

[0253] Output: Displayed on the user interface

[0254] Behavior: Display on screen so the user can see it.

[0255] Step 5:

[0256] Shopping feature

[0257] The user selects an item from the list of suggested disaster prevention measures and adds it to the cart.

[0258] Input: User selection of product

[0259] Output: List of items added to cart

[0260] What happens: A user selects a product's checkbox and clicks the Add to Cart button.

[0261] The terminal transmits the cart information to the server.

[0262] Input: List of items added to cart

[0263] Output: Sending to server completed

[0264] What it does: Sends cart information to the server as an HTTP request.

[0265] The server checks the stock status and completes the purchase process through the payment system.

[0266] Input: Cart information

[0267] Output: Inventory check and payment processing completed

[0268] Operation: Check inventory and process payments using a back-end system (e.g., an e-commerce system).

[0269] The server sends a notification of purchase completion and delivery information to the user's terminal.

[0270] Input: Payment processing result

[0271] output: Notification and delivery information sent

[0272] Operation: After payment is completed, payment results and delivery information are sent to the terminal.

[0273] Step 6:

[0274] Disaster prevention map and route guidance

[0275] The user uses the disaster prevention map function to obtain current location information.

[0276] Input: User's current location (GPS information)

[0277] Output: Current location information acquisition completed

[0278] What it does: Click a button in the app to enable location tracking.

[0279] The device sends the current location information to the server.

[0280] Input: Acquired GPS information

[0281] Output: Sending to server completed

[0282] What it does: Sends your current location to the server as an HTTP request.

[0283] The server compares the current location information with the evacuation shelter information and calculates the optimal evacuation route.

[0284] Input: Current location information, evacuation shelter information

[0285] Output: Optimal evacuation route

[0286] How it works: It retrieves the necessary information from a database and uses an algorithm to calculate the optimal evacuation route.

[0287] The server sends the calculation results to the terminal.

[0288] Input: Calculated evacuation route

[0289] Output: Sent to terminal

[0290] Operation: Sends an evacuation route to the device as an HTTP response.

[0291] The evacuation route and disaster prevention map received by the terminal are displayed on the user interface.

[0292] Input: Evacuation route sent from the server

[0293] Output: Displayed on the user interface

[0294] Operation: Disaster prevention maps and evacuation routes are displayed on the screen so that users can check them.

[0295] (Application example 1)

[0296] 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."

[0297] Until now, there have been limited means of swift and efficient evacuation and delivery of emergency supplies during disasters. Furthermore, few systems existed that considered individual purchase and search histories to provide optimal disaster prevention measures, placing a heavy burden on users. Furthermore, systems lacked the ability to obtain real-time information on available evacuation sites and calculate evacuation routes. This made it difficult for many people to respond quickly and efficiently during disasters. A new system was needed to solve this problem.

[0298] 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.

[0299] In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and storing it in a database; means for collecting the user's past purchase history and search history and storing it in a database; means for collecting disaster information and evacuation site information from public institutions and storing it in a database; means for an AI system to propose optimal disaster prevention measures based on the stored information; means for displaying a list of the proposed disaster prevention measures on the user's processing device; means for an autonomous vehicle to calculate an optimal evacuation route in the event of a disaster and transport the user to the optimal evacuation site; means for calculating a delivery route for disaster prevention supplies based on the user's disaster prevention plan list and quickly delivering the supplies; and means for checking the availability of evacuation sites in real time and notifying the user. This enables fast and efficient evacuation and delivery of emergency supplies.

[0300] "Address" refers to the specific area or place where a user resides.

[0301] "Family structure" refers to the composition of members in the user's household, including, for example, parents, children, spouse, etc.

[0302] "Basic information" refers to key data about the user, including address, family composition, date of birth, etc.

[0303] A "server" is a computing device that processes and stores data over a network.

[0304] A "database" is a collection of electronic information that is systematically organized and stored, and that can be easily searched and updated.

[0305] "Purchase history" refers to a record of products purchased by a user in the past.

[0306] "Search history" refers to a record of searches a user has conducted in the past.

[0307] "Public institutions" refer to organizations that function for the public, such as national and local governments.

[0308] "Disaster information" refers to information related to natural disasters such as earthquakes, typhoons, and floods.

[0309] "Evacuation site information" refers to information about places where people should evacuate to ensure their safety in the event of a disaster.

[0310] An "artificial intelligence system" refers to a technological system that analyzes data and learns to make human-like judgments and predictions.

[0311] "Disaster prevention measures" refer to preventive and response measures taken in preparation for the occurrence of a disaster.

[0312] "Processing device" refers to a device for processing data, and primarily includes computers and smartphones.

[0313] An "autonomous vehicle" is a vehicle that has the ability to drive itself without driver intervention.

[0314] An "evacuation route" refers to a route to a safe location in the event of a disaster.

[0315] "Disaster prevention supplies" refer to supplies needed in the event of a disaster, such as disaster prevention equipment and emergency food.

[0316] "Delivery route" refers to the route along which goods are delivered.

[0317] "Real-time confirmation" refers to checking information immediately without delay.

[0318] MODE FOR CARRYING OUT THE INVENTION

[0319] The present invention is a system for realizing rapid evacuation and delivery of emergency supplies in the event of a disaster, and provides functions for proposing evacuation routes and delivering disaster prevention supplies using autonomous vehicles. Specific embodiments of the system are described below.

[0320] User registration and basic information entry

[0321] Users first download and install a dedicated application onto their smartphone or tablet. After installation, they launch the application and a screen appears where they can enter basic information such as their address and family composition. The basic information entered by the user is sent to the server and stored in a database.

[0322] Collection of purchase and search history

[0323] When a user searches for or purchases disaster prevention-related products within the application, their search queries and purchase history are automatically collected and sent to the server, where they are stored in a database and their individual profile is updated.

[0324] Collecting disaster information and evacuation site information

[0325] The server periodically checks APIs provided by public institutions and public data sources to collect the latest disaster information and evacuation site information. This information is also stored in a database and used as material for disaster prevention measures customized for each user.

[0326] Disaster prevention measures proposals

[0327] The server inputs the user's basic information, purchase history, search history, and disaster information from public institutions into an AI system to calculate optimal disaster prevention measures. The proposed disaster prevention measures list is stored in a database and sent to the user's device. The user can view this list on the application.

[0328] Emergency evacuation route suggestions

[0329] When a disaster occurs, if a user gets into an autonomous vehicle, the vehicle uses a GPS device to acquire the user's current location information. The server calculates the optimal evacuation route based on the disaster information and the current location information and sends it to the autonomous vehicle. The vehicle then automatically transports the user to the optimal evacuation location according to this route.

[0330] Delivery of emergency supplies

[0331] Based on the user's disaster prevention plan, the server calculates the optimal delivery route for emergency supplies. The supplies are quickly delivered to the user's address by autonomous vehicles from the disaster prevention center. The server tracks the delivery status in real time and notifies the user.

[0332] Displaying evacuation shelter availability information

[0333] The server checks the availability of evacuation shelters in real time and sends that information to the user's device, where the user can check the availability of evacuation shelters on the application.

[0334] Hardware and software used

[0335] The system requires a server, a GPS device, an autonomous vehicle, a smartphone, and an internet connection. The software includes a dedicated application and an API for collecting disaster information. It also uses an artificial intelligence model for data analysis and recommendations.

[0336] Specific examples

[0337] For example, if a user lives in a certain area of ​​Tokyo and a disaster occurs, an autonomous vehicle will calculate an evacuation route and automatically drive to a safe evacuation site. Also, if a user purchases emergency food and water using a disaster prevention app, the autonomous vehicle will quickly deliver these supplies to the specified address in the event of an emergency.

[0338] Prompt Sentence Examples

[0339] Calculating the best evacuation route in case of a disaster: "Calculate the best route from your current location to a safe evacuation location."

[0340] Emergency supply delivery route calculation: "Calculate the delivery route from the disaster prevention center to a specified address."

[0341] Get information on available evacuation shelters: "Get the latest information on available evacuation shelters."

[0342] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0343] Step 1:

[0344] The user installs a dedicated application and enters basic information such as address and family composition.

[0345] (Input) Basic information entered by the user (address, family composition, age, etc.).

[0346] (Processing) The terminal sends the entered basic information to the server and stores it in the database.

[0347] (Output) Basic information saved in the database.

[0348] Step 2:

[0349] When users search for or purchase disaster prevention-related products within the app, that information is collected.

[0350] (Input) User search queries and purchase history.

[0351] The (processing) terminal sends this information to the server in real time and stores it in a database.

[0352] (Output) Purchase history and search history are saved in the database.

[0353] Step 3:

[0354] The server collects the latest disaster information and evacuation site information from public APIs and public data sources.

[0355] (Input) Data feeds from public APIs and public data sources.

[0356] (Processing) The server periodically calls the API and stores the retrieved information in a database.

[0357] (Output) The latest disaster information and evacuation location information is saved in the database.

[0358] Step 4:

[0359] Based on the stored information, an artificial intelligence system calculates the optimal disaster prevention measures.

[0360] (Input) User's basic information, purchase history, search history, and latest disaster information.

[0361] The (processing) server inputs this information into an artificial intelligence model to calculate the optimal disaster prevention measures.

[0362] (Output) A list of proposed disaster prevention measures.

[0363] Step 5:

[0364] A list of proposed disaster prevention measures is displayed on the user's terminal.

[0365] (Input) Disaster prevention measures list sent from the server.

[0366] (Processing) The list received by the terminal is displayed on the application interface.

[0367] (Output) A display screen that the user can see.

[0368] Step 6:

[0369] When a disaster occurs, autonomous vehicles acquire information about the user's current location and calculate evacuation routes.

[0370] (Input) User's current location information (GPS data).

[0371] (Processing) The server calculates the optimal evacuation route based on the current location information and disaster information, and sends it to the autonomous vehicle.

[0372] (Output) An evacuation route is calculated and directed to the autonomous vehicle.

[0373] Step 7:

[0374] The system calculates delivery routes for emergency supplies based on the user's disaster prevention plan list, and delivers the supplies quickly.

[0375] (Input) User's disaster prevention plan list and disaster prevention goods delivery base information.

[0376] (Processing) The server calculates a delivery route based on this information and gives instructions to the autonomous vehicle.

[0377] (Output) A supply delivery route is calculated and directed to the autonomous vehicle.

[0378] Step 8:

[0379] Check the availability of evacuation shelters in real time and notify users of that information.

[0380] (Input) Information on available evacuation shelters.

[0381] (Processing) The server periodically checks availability information and sends it to the user's terminal.

[0382] (Output) Information about available evacuation shelters displayed on the user's device.

[0383] 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.

[0384] MODE FOR CARRYING OUT THE INVENTION

[0385] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to easily and efficiently take disaster prevention measures, and by combining it with an emotion engine, it provides disaster prevention measures based on the user's emotional state. A detailed embodiment of this system will be described.

[0386] 1. User registration and basic information entry

[0387] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which then stores it in a database.

[0388] 2. Collection of purchase and search history

[0389] When a user searches for or purchases disaster preparedness products within the app, the device collects the search query and purchase history in real time and sends it to the server, which stores this data in a database and updates the user's profile.

[0390] 3. Collecting disaster and evacuation shelter information

[0391] The server periodically checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in a database and used to create customized suggestions for each user.

[0392] 4. Emotion engine integration

[0393] When a user uses the app, the camera and microphone are used to analyze the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state. The device then processes the results of the emotion engine and sends them to the server.

[0394] 5. Proposal of disaster prevention measures

[0395] The server inputs the user's basic information, purchase history, search history, disaster information from local governments, and emotional information obtained from an emotion engine into the AI ​​system to calculate optimal disaster prevention measures. The list of proposed disaster prevention measures is stored in a database and sent to the user's device. The device displays the list so that the user can review it. Based on the user's emotional state, advice and relaxation methods for reducing stress are also suggested.

[0396] 6. Shopping function

[0397] When the user checks the proposed disaster prevention measures list and adds the necessary items to the cart, the device sends the list of items they wish to purchase to the server. The server checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, along with delivery information.

[0398] 7. Disaster Prevention Map and Route Guidance

[0399] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store.

[0400] Specific examples

[0401] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as their address and family composition, the AI ​​system suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilets." Furthermore, if the emotion engine recognizes that the user is emotionally unstable, it also offers advice on stress reduction and relaxation techniques. The user adds the suggested items to their cart and completes the purchase process. The route to the nearest evacuation shelter is then displayed, allowing for smooth evacuation in the event of a disaster. The user can also print out necessary disaster prevention and evacuation shelter information using a convenience store copy machine.

[0402] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures. Furthermore, by integrating an emotion engine, appropriate measures are suggested according to the user's emotional state, thereby reducing the user's physical and mental burden.

[0403] The processing flow will be explained below.

[0404] User registration and basic information entry

[0405] Step 1:

[0406] The user installs the app and accesses the user information input screen when launching it for the first time.

[0407] Step 2:

[0408] The user enters basic information such as name, address, age, and family composition.

[0409] Step 3:

[0410] The device generates an API request to send the basic information entered to the server.

[0411] Step 4:

[0412] The server stores the received information in a database.

[0413] Step 5:

[0414] After the server has completed the storage, it generates a registration confirmation message and sends it to the terminal.

[0415] Collection of purchase and search history

[0416] Step 1:

[0417] A user searches for disaster preparedness products within the app.

[0418] Step 2:

[0419] The device sends a search query to the server.

[0420] Step 3:

[0421] The user adds the product they like to the cart and completes the purchase.

[0422] Step 4:

[0423] The device sends purchase history and cart information to the server.

[0424] Step 5:

[0425] The server stores your search and purchase history in a database.

[0426] Collecting disaster and evacuation shelter information

[0427] Step 1:

[0428] The server periodically queries local government APIs and various public data sources to collect the latest disaster and evacuation shelter information.

[0429] Step 2:

[0430] The server stores the collected data in a database and formats the relevant information.

[0431] Emotion engine integration

[0432] Step 1:

[0433] When a user uses an app, the app asks for permission to use the camera and microphone.

[0434] Step 2:

[0435] If the user gives permission, the device will collect the user's facial expressions and voice in real time.

[0436] Step 3:

[0437] The facial expression and voice data collected by the device is sent to an emotion engine to analyze the emotional state.

[0438] Step 4:

[0439] The emotion engine generates the analysis results and sends them back to the device.

[0440] Disaster prevention measures proposals

[0441] Step 1:

[0442] The server inputs the user's basic information, purchase history, search history, disaster information from local governments, and the analysis results of the emotion engine into the AI ​​system.

[0443] Step 2:

[0444] The AI ​​system calculates the optimal disaster prevention measures.

[0445] Step 3:

[0446] The server generates a list of proposed disaster prevention measures and stores it in a database.

[0447] Step 4:

[0448] The server generates a response to send the generated list to the user's terminal.

[0449] Step 5:

[0450] The terminal displays the disaster prevention measures list to the user and provides an interface that the user can check.

[0451] Step 6:

[0452] The device displays advice and relaxation methods to reduce stress based on the user's emotions.

[0453] Shopping feature

[0454] Step 1:

[0455] The user checks the disaster preparedness list and adds the necessary items to the cart.

[0456] Step 2:

[0457] The device generates an API request to send the list of products desired for purchase to the server.

[0458] Step 3:

[0459] Based on the product list received by the server, the server checks stock status and price information and processes the payment.

[0460] Step 4:

[0461] The server generates a purchase confirmation message and sends it to the user's terminal.

[0462] Step 5:

[0463] The terminal displays a notification to the user that the purchase is complete and displays product delivery information.

[0464] Disaster prevention map and route guidance

[0465] Step 1:

[0466] The user opens the disaster prevention map function within the app.

[0467] Step 2:

[0468] The device obtains the current location information and generates an API request to send to the server.

[0469] Step 3:

[0470] The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route.

[0471] Step 4:

[0472] The server generates a response including the calculated route information and sends it to the terminal.

[0473] Step 5:

[0474] The device displays evacuation routes and disaster prevention maps to the user and provides voice guidance.

[0475] Step 6:

[0476] Users can print out disaster prevention information and evacuation shelter information as needed using a copy machine at a convenience store.

[0477] Example 2

[0478] 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."

[0479] Conventional disaster response systems primarily propose disaster prevention measures based on a user's basic information and purchase and search history, but they do not provide measures that take into account the user's emotional state. Furthermore, when displaying optimal evacuation routes and disaster prevention maps, a rapid response linked to real-time disaster information is required. Furthermore, the lack of a function to easily purchase the proposed disaster prevention products increases the user's workload and hinders actual disaster response.

[0480] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and storing it in a database; means for collecting the user's past purchase history and search history and storing it in a database; means for collecting disaster information and evacuation shelter information from local governments and storing it in a database; emotion analysis means for recognizing the user's emotional state in real time based on the stored information; means for proposing optimal disaster prevention measures using a generative AI model based on the stored information and the emotion analysis results; means for displaying a list of proposed disaster prevention measures on the user's terminal; means for adding necessary disaster prevention products based on the proposed disaster prevention measures list to a shopping cart and performing a purchase process; and means for acquiring the user's current location information, calculating a route to the nearest evacuation shelter, and displaying and guiding the route as a disaster prevention map. This allows optimal disaster prevention measures to be provided in real time while taking the user's emotional state into consideration, enabling quick and efficient evacuation. Furthermore, disaster prevention products can be purchased easily, significantly reducing the user's effort.

[0481] "User" refers to any person or entity that uses the System.

[0482] "Basic information" refers to personal information such as the user's address, family structure, age, and name.

[0483] "Server" refers to a computer system that receives, processes, stores, and provides information from users.

[0484] "Database" refers to an electronic record system in which a server stores and manages information in an organized manner.

[0485] "Purchase History" refers to a record of products purchased by a user within the system.

[0486] "Search History" refers to the record of search queries made by a User within the System.

[0487] "Municipality" refers to local public bodies and local administrative agencies.

[0488] "Disaster information" refers to information related to emergencies such as earthquakes, typhoons, and heavy rain provided by the government and local governments.

[0489] "Evacuation shelter information" refers to information about places where people can evacuate in the event of an emergency.

[0490] "Emotion analysis means" refers to technology for recognizing a user's emotional state based on their facial expressions and voice.

[0491] A "generative AI model" refers to an artificial intelligence model that uses machine learning techniques to predict outcomes from data.

[0492] "Disaster prevention measures" refer to various preparations and guidelines for action to be taken in preparation for the occurrence of a disaster.

[0493] "Shopping cart" refers to a function for carrying out online product purchase procedures.

[0494] "Purchase processing" refers to the payment and delivery procedures for the products selected by the user.

[0495] "Location information" refers to data regarding a user's physical location.

[0496] An "evacuation route" refers to the optimal route to a designated evacuation site in the event of a disaster.

[0497] "Disaster Prevention MAP" refers to a function that displays and guides users to map information for evacuation.

[0498] MODE FOR CARRYING OUT THE INVENTION

[0499] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to easily and efficiently take disaster prevention measures, and by combining it with emotion analysis means, provides disaster prevention measures based on the user's emotional state. A detailed embodiment of this system will be described.

[0500] User registration and basic information entry

[0501] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which stores it in a database. For this purpose, a sending module written in Python and the Django framework are used.

[0502] Collection of purchase and search history

[0503] When a user searches for or purchases disaster prevention products within the app, the device collects the search query and purchase history in real time and sends it to the server. The server stores this history data in a database and updates the user's profile. For example, if a user searches for "emergency food" and purchases a "5-year emergency food set," the search query and purchase history are recorded.

[0504] Collecting disaster and evacuation shelter information

[0505] The server periodically checks local government APIs and public data sources (e.g., the Ministry of Land, Infrastructure, Transport and Tourism's real-time disaster information service) to collect the latest disaster information and evacuation shelter information. This information is stored in a database and used to make customized suggestions for each user. The server sets up a cron job to check the API every day at 9:00 AM.

[0506] Emotion engine integration

[0507] When a user uses the app, the device activates the camera and microphone and analyzes the user's facial expressions and voice in real time. The emotion engine (e.g., Affectiva SDK) recognizes the user's emotional state from their facial expressions and voice and sends the recognition results to the server. For example, when a user taps the "Check evacuation shelter information" button, "anxiety" is recognized from the data collected by the camera.

[0508] Disaster prevention measures proposals

[0509] The server combines the user's basic information, purchase history, search history, disaster information, and emotional information obtained through emotion analysis, and uses a generative AI model (e.g., TensorFlow, PyTorch) to calculate optimal disaster prevention measures. The calculated disaster prevention measures list is stored in a database and sent to the user's device. The device displays this list so that the user can review it. Based on the user's emotional state, advice for reducing stress and relaxation methods are also suggested. For example, specific measures such as "three days' worth of water," "emergency food," and "portable toilet" are presented.

[0510] Shopping feature

[0511] The user checks the proposed disaster prevention measures list and adds the necessary items to the cart. The device sends the list of items desired for purchase to the server, which checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, and delivery information is also displayed.

[0512] Disaster prevention map and route guidance

[0513] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store. The Google Maps API is used to implement this function.

[0514] Specific examples

[0515] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as address and family composition, the generative AI model suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilet." Furthermore, if the emotion engine recognizes that the user's emotions are unstable, it also provides advice on stress reduction and relaxation techniques. The user adds the suggested items to their cart and completes the purchase process. The route to the nearest evacuation shelter is then displayed, allowing for smooth evacuation in the event of a disaster. The user can also print out the necessary disaster prevention and evacuation shelter information using a convenience store copy machine.

[0516] Prompt Sentence Examples

[0517] "A 45-year-old man living in Shibuya Ward with a wife and two children. His current emotional state is unstable. I would like to see a list of optimal disaster prevention measures and shopping suggestions based on that list."

[0518] As a result, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures. In addition, by integrating emotion analysis means, appropriate measures according to the user's emotional state are also suggested, thereby reducing the physical and mental burden on the user.

[0519] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0520] Program processing flow

[0521] Step 1: User registration and basic information entry

[0522] 1. The user downloads and launches the app.

[0523] 2. The terminal displays a screen for entering user information.

[0524] 3. The user enters basic information.

[0525] Input: Name, address, age, family composition

[0526] Output: Basic information data entered

[0527] 4. The device sends the input information to the server.

[0528] Input: Basic information data

[0529] Output: Data transferred to the server

[0530] 5. The server stores the received information in a database.

[0531] Input: Basic information data

[0532] Output: User information stored in the database

[0533] Step 2: Collect purchase and search history

[0534] 1. The user searches for and purchases products within the app.

[0535] 2. The device collects search queries and purchase history.

[0536] Input: search query, purchase information

[0537] Output: Collected historical data

[0538] 3. The device sends the collected information to the server.

[0539] Input: Historical data

[0540] Output: Data transferred to the server

[0541] 4. The server stores the received information in a database and updates the user's profile.

[0542] Input: Historical data

[0543] Output: History and profile updates stored in database

[0544] Step 3: Collect disaster and evacuation information

[0545] 1. The server checks the local government's API or public data sources.

[0546] Input: Municipality API endpoint

[0547] Output: Latest disaster information and evacuation shelter information

[0548] 2. The server stores the disaster information and evacuation shelter information it has acquired in a database.

[0549] Input: Disaster information, evacuation shelter information

[0550] Output: Disaster information and evacuation shelter information stored in a database

[0551] Step 4: Integrating the Emotion Engine

[0552] 1. The user uses the app.

[0553] 2. The device activates the camera and microphone and analyzes the user's facial expressions and voice in real time.

[0554] Input: User's facial expression data, voice data

[0555] Output: Parsed emotion data

[0556] 3. The emotion engine recognizes the user's emotional state.

[0557] Input: facial expression data, voice data

[0558] Output: Perceived emotional state (e.g., "anxiety")

[0559] 4. The device sends the emotion recognition results to the server.

[0560] Input: Emotional state data

[0561] Output: Emotion data sent to the server

[0562] Step 5: Propose disaster prevention measures

[0563] 1. The server collects the user's basic information, purchase history, search history, disaster information, and emotional information.

[0564] Input: Basic information, purchase history, search history, disaster information, emotional information

[0565] Output: Aggregated data

[0566] 2. The server inputs this data into the generative AI model.

[0567] Input: Aggregated data

[0568] Output: Input data for the generative AI model

[0569] 3. The server creates a disaster prevention measures list calculated by the AI ​​model.

[0570] Input: Input data for the AI ​​model

[0571] Output: Disaster prevention measures list

[0572] 4. The server saves the list in a database and sends it to the device.

[0573] Input: Disaster prevention measures list

[0574] Output: Data stored in the database and sent to the device

[0575] 5. The device will display a list of disaster prevention measures.

[0576] Input: Disaster prevention measures list

[0577] Output: The displayed list

[0578] Step 6: Shopping Function

[0579] 1. A user adds an item from their disaster preparedness list to their cart.

[0580] Input: Item information

[0581] Output: Items added to cart

[0582] 2. The terminal sends the list of items desired for purchase to the server.

[0583] Input: Cart information

[0584] Output: Purchase wish list transferred to the server

[0585] 3. The server checks the inventory status.

[0586] Input: List of products you wish to purchase

[0587] Output: Inventory check results

[0588] 4. The server processes the payment and sends a purchase completion notification to the terminal.

[0589] Input: Inventory check results, payment information

[0590] Output: Purchase completion notification and shipping information

[0591] 5. Your device will display a confirmation of purchase and shipping information.

[0592] Input: Purchase completion notification, delivery information

[0593] Output: Displayed notification and shipping information

[0594] Step 7: Disaster prevention map and route guidance

[0595] 1. The user selects the disaster prevention map function.

[0596] 2. The device obtains the current location information.

[0597] Input: GPS data

[0598] Output: Current location information

[0599] 3. The device sends its current location information to the server.

[0600] Input: Current location information

[0601] Output: Current location information sent to the server

[0602] 4. The server calculates the optimal evacuation route.

[0603] Input: Current location information, evacuation shelter information

[0604] Output: Evacuation route data

[0605] 5. The server sends the calculation results to the terminal.

[0606] Input: Evacuation route data

[0607] Output: Route information sent to the device

[0608] 6. The device will display evacuation routes and disaster prevention maps.

[0609] Input: Route information

[0610] Output: Displayed evacuation route and disaster prevention map

[0611] 7. If necessary, print out this information using a copy machine at a convenience store.

[0612] Input: Route information, MAP data

[0613] Output: Printed data

[0614] This provides a concrete explanation of each processing step, making it clear to users how to use this system to take disaster prevention measures.

[0615] (Application example 2)

[0616] 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."

[0617] In recent years, the number of natural disasters has increased, creating a need for rapid and effective disaster prevention measures. However, conventional disaster prevention applications do not provide measures based on the user's emotional state, and they lack functions to reduce stress and anxiety, especially during disasters. Furthermore, in autonomous vehicles, there is a problem that it is difficult to ensure the safety of the driver because there is no system that analyzes the situation inside the vehicle in real time and proposes the optimal evacuation route.

[0618] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0619] In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and saving it in a database; means for collecting the user's past purchase history and search history and saving it in a database; means for collecting disaster information and evacuation shelter information from local governments and saving it in a database; means for the AI ​​system to propose optimal disaster prevention measures based on the saved information; means for displaying a list of proposed disaster prevention measures on the user's terminal; means for recognizing the driver's emotional state based on data collected from sensors in the vehicle and providing advice for reducing stress; and means for acquiring current location information, comparing it with disaster information from local governments to calculate an optimal evacuation route and displaying it on the driver's terminal. This makes it possible to provide appropriate disaster prevention measures and evacuation routes according to the user's emotional state.

[0620] definition statement

[0621] "Basic information" refers to information such as name, address, age, and family composition entered by the user.

[0622] A "means" is a combination of hardware and software for realizing a specific function or operation.

[0623] A "server" is a computer that stores, processes, and manages data over a network.

[0624] A "database" is a system for systematically storing and managing data.

[0625] "Purchase history" is a record of products and services that a user has purchased in the past.

[0626] "Search history" is a record of keywords or queries a user has searched for in the past.

[0627] "Municipal disaster information" is the latest information on natural disasters provided by local government agencies.

[0628] "Evacuation shelter information" is information about designated places to evacuate to in the event of a disaster.

[0629] An "AI system" is a system that uses artificial intelligence technology to analyze data and calculate optimal disaster prevention measures.

[0630] The "disaster prevention measures list" is a list of disaster prevention supplies and measures suggested to the user.

[0631] "In-vehicle sensors" are devices that detect the environment inside the vehicle and the driver's condition in real time.

[0632] "Emotional state" refers to the driver's emotional and psychological state.

[0633] "Stress reduction advice" is a suggestion or instruction to reduce driver stress or anxiety.

[0634] "Current location information" is information about the user's current location obtained using a GPS or the like.

[0635] An "evacuation route" is the optimal route for a user to safely evacuate.

[0636] A "terminal" is a device used by a user, such as a smartphone, tablet, or vehicle infotainment system.

[0637] MODE FOR CARRYING OUT THE INVENTION

[0638] The present invention relates to a disaster prevention support app for an autonomous driving vehicle that is designed to enable a user to respond quickly and accurately in the event of a disaster. Hereinafter, an embodiment of the present invention will be described in detail.

[0639] 1. System Configuration

[0640] This system consists of a server, in-vehicle terminals, various sensors, and a network environment. The server manages user information, disaster information, emotional state, etc., and the in-vehicle terminals provide this information to the user.

[0641] 2. Server Roles

[0642] The server has the following roles:

[0643] User registration and basic information management

[0644] When a user enters basic information such as address and family composition, it is sent to a server and stored in a database. This information is used in emergency response.

[0645] Historical data collection and management

[0646] The system collects and stores users' past purchase and search history in a database, which then suggests individually optimized disaster prevention measures.

[0647] Collecting disaster information

[0648] It regularly checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information and stores it in a database.

[0649] Sentiment Analysis and Recommendations

[0650] It uses generative AI models such as TensorFlow to analyze the driver's emotional state in real time using cameras and microphones in the vehicle, and provides advice to reduce stress based on the analysis results.

[0651] 3. Role of terminals inside the vehicle

[0652] The terminals in the vehicles have the following functions:

[0653] Display of basic information and disaster prevention measures

[0654] Basic information and a list of disaster prevention measures sent from the server are displayed on the vehicle's infotainment system.

[0655] Collecting and transmitting emotional states

[0656] The vehicle's cameras and microphones collect the driver's facial expressions and voice, which are then sent to a server for use in an emotion analysis model.

[0657] Calculating and displaying evacuation routes

[0658] The system acquires current location information and sends it to a server. The server then calculates the optimal evacuation route based on this information and displays it on the vehicle's infotainment system. The route calculation is performed using Google Maps API and other tools.

[0659] 4. Hardware and Software Used

[0660] Specific hardware used includes in-vehicle cameras, microphones, GPS modules, and infotainment systems, while specific software used includes Python, TensorFlow (sentiment analysis), Open Data API (disaster information collection), Google Maps API (route calculation), and Django (server-side).

[0661] 5. Specific Examples

[0662] For example, imagine a driver gets into an autonomous vehicle and the system starts up. The driver's basic information, past search history, and purchase history are stored on a server. Suddenly, a disaster occurs, and the server collects the latest disaster information. A camera inside the vehicle captures the driver's facial expressions, and a TensorFlow model analyzes the driver's emotional state. If the system determines that the driver is anxious, it will advise them on how to relax and calculate and display the optimal evacuation route.

[0663] 6. Examples of prompts

[0664] Examples of specific prompts for an AI model include:

[0665] Prompt sentence for sentiment analysis model:

[0666] "Predict the driver's emotions from image and audio data and output one of the following: stress, tension, anxiety, or calm."

[0667] Prompt for disaster information acquisition:

[0668] "Get the following disaster information: type of disaster, location, evacuation shelter."

[0669] Prompt for evacuation route calculation:

[0670] "Calculate the next evacuation route. Starting point: {current_location}, Destination: {safe_place}."

[0671] As described above, the present invention takes into account the emotional state of the user and provides optimal disaster prevention measures and evacuation routes in real time, enabling a quick and safe response in the event of a disaster.

[0672] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0673] Program processing steps

[0674] Step 1:

[0675] The user inputs basic information such as address and family composition. The device sends the input basic information to the server and stores it in a database. The input includes the user's name, address, age, family composition, etc., and the output is the basic information stored in the database.

[0676] Step 2:

[0677] The system collects the user's past purchases of disaster prevention products and search history. The device sends this historical data to the server in real time and stores it in the server's database. The input is the user's purchase history and search history, and the output is an updated user profile.

[0678] Step 3:

[0679] The server periodically checks the local government's API and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in the server's database. The input is disaster information and evacuation shelter information obtained from the API, and the output is the latest information stored in the database.

[0680] Step 4:

[0681] The system uses cameras and microphones inside the vehicle to collect the driver's facial expressions and voice in real time. The device then sends this data to a server where it is analyzed by an emotion engine. The inputs are camera images and voice data, and the output is analyzed emotional state data.

[0682] Step 5:

[0683] The server uses an AI system to calculate optimal disaster prevention measures based on the collected basic information, historical data, disaster information, evacuation shelter information, and analyzed emotional states. This calculation is performed using a generative AI model such as TensorFlow. The inputs are basic information, historical data, disaster information, evacuation shelter information, and emotional states, and the output is a list of disaster prevention measures.

[0684] Step 6:

[0685] The server sends the generated disaster prevention measures list to the user's device and displays it on the vehicle's infotainment system. The user checks the list and takes specific disaster prevention measures. The input to this step is the generated disaster prevention measures list, and the output is a display and user actions.

[0686] Step 7:

[0687] The server obtains current location information from the device and compares it with the vehicle's GPS data to calculate the optimal evacuation route. The calculated evacuation route is sent to the device and displayed on the vehicle's infotainment system. The inputs are current location information, disaster information, and evacuation shelter information, and the optimal evacuation route is generated as the output.

[0688] Step 8:

[0689] The device provides voice and text advice to reduce stress based on the driver's emotional state, allowing the driver to evacuate safely while remaining relaxed. The input is the analyzed emotional state, and the output is the presentation of advice.

[0690] As described above, by dividing the process into multiple steps, users can be provided with prompt and appropriate disaster prevention measures and evacuation routes in the event of a disaster, and can also receive advice based on their emotional state.

[0691] 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.

[0692] 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.

[0693] 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.

[0694] [Second embodiment]

[0695] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0696] 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.

[0697] 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).

[0698] 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.

[0699] 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.

[0700] 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).

[0701] 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.

[0702] 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.

[0703] 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.

[0704] 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.

[0705] 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.

[0706] 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."

[0707] MODE FOR CARRYING OUT THE INVENTION

[0708] The "Easy Disaster Prevention Response App" of the present invention is a system designed to enable users to easily and efficiently take disaster countermeasures. A detailed embodiment of this system will be described.

[0709] 1. User registration and basic information entry

[0710] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which then stores it in a database.

[0711] 2. Collection of purchase and search history

[0712] When a user searches for or purchases disaster preparedness products within the app, the device collects the search query and purchase history in real time and sends it to the server, which stores this data in a database and updates the user's profile.

[0713] 3. Collecting disaster and evacuation shelter information

[0714] The server periodically checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in a database and used to create customized suggestions for each user.

[0715] 4. Proposal of disaster prevention measures

[0716] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the AI ​​system to calculate optimal disaster prevention measures. The proposed disaster prevention measures list is stored in a database and sent to the user's device, where it is displayed for the user to review.

[0717] 5. Shopping function

[0718] When the user checks the proposed disaster prevention measures list and adds the necessary items to the cart, the device sends the list of items they wish to purchase to the server. The server checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, along with delivery information.

[0719] 6. Disaster prevention map and route guidance

[0720] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store.

[0721] Specific examples

[0722] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as their address and family composition, the AI ​​system suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilets." The user adds the suggested items to their cart and completes the purchase process. The system then displays a route to the nearest evacuation shelter, allowing for smooth evacuation in the event of a disaster. The user can also print out the necessary disaster prevention and evacuation shelter information using a copy machine at a convenience store.

[0723] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures.

[0724] The processing flow will be explained below.

[0725] User registration and basic information entry

[0726] Step 1:

[0727] The user installs the app and accesses the user information input screen when launching it for the first time.

[0728] Step 2:

[0729] The user enters basic information such as name, address, age, and family composition.

[0730] Step 3:

[0731] The device generates an API request to send the basic information entered to the server.

[0732] Step 4:

[0733] The server stores the received information in a database.

[0734] Step 5:

[0735] After the server has completed the storage, it generates a registration confirmation message and sends it to the terminal.

[0736] Collection of purchase and search history

[0737] Step 1:

[0738] A user searches for disaster preparedness products within the app.

[0739] Step 2:

[0740] The device sends a search query to the server.

[0741] Step 3:

[0742] The user adds the product they like to the cart and completes the purchase.

[0743] Step 4:

[0744] The device sends purchase history and cart information to the server.

[0745] Step 5:

[0746] The server stores your search and purchase history in a database.

[0747] Collecting disaster and evacuation shelter information

[0748] Step 1:

[0749] The server periodically queries local government APIs and various public data sources to collect the latest disaster and evacuation shelter information.

[0750] Step 2:

[0751] The server stores the collected data in a database and formats the relevant information.

[0752] Disaster prevention measures proposals

[0753] Step 1:

[0754] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the AI ​​system and calculates the optimal disaster prevention measures.

[0755] Step 2:

[0756] The server generates a list of proposed disaster prevention measures and stores it in a database.

[0757] Step 3:

[0758] The server generates a response to send the generated list to the user's terminal.

[0759] Step 4:

[0760] The device displays a list of disaster prevention measures to the user and provides an interface where the user can check the proposed measures.

[0761] Shopping feature

[0762] Step 1:

[0763] The user checks the disaster preparedness list and adds the necessary items to the cart.

[0764] Step 2:

[0765] The device generates an API request to send the list of products desired for purchase to the server.

[0766] Step 3:

[0767] Based on the product list received by the server, the server checks stock status and price information and processes the payment.

[0768] Step 4:

[0769] The server generates a purchase confirmation message and sends it to the user's terminal.

[0770] Step 5:

[0771] The terminal displays a notification to the user that the purchase is complete and displays product delivery information.

[0772] Disaster prevention map and route guidance

[0773] Step 1:

[0774] The user opens the disaster prevention map function within the app.

[0775] Step 2:

[0776] The device obtains the user's current location information and generates an API request to send to the server.

[0777] Step 3:

[0778] The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route.

[0779] Step 4:

[0780] The server generates a response including the calculated route information and sends it to the terminal.

[0781] Step 5:

[0782] The device displays evacuation routes and disaster prevention maps to the user and provides voice guidance.

[0783] Step 6:

[0784] Users can print out disaster prevention information and evacuation shelter information as needed using a copy machine at a convenience store.

[0785] Example 1

[0786] 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."

[0787] Disaster prevention measures are becoming increasingly important in modern society, and individual users are being asked to take appropriate measures quickly and efficiently. However, currently available disaster prevention applications and tools do not fully utilize individual user information, making it difficult to propose optimal disaster prevention measures to users. Furthermore, there are issues with the accuracy and timeliness of collecting disaster and evacuation shelter information and presenting optimal evacuation routes. For this reason, there is a demand for disaster response systems that are easy for users to use and offer advanced functions.

[0788] 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.

[0789] In this invention, the server includes: means for a user to input basic information such as place of residence and family composition; means for transmitting the input basic information to the server and storing it in a data management device; means for collecting the user's past purchase history and search history and storing it in the data management device; means for automatically collecting disaster information and evacuation shelter information from local governments and storing it in the data management device; means for a generative AI model to propose optimal disaster prevention measures based on the stored information; means for displaying a list of the proposed disaster prevention measures on the user's connected device; means for the user to acquire current location information from the screen of the connected device and send it to the server; means for the server to compare the current location information with the evacuation shelter information and calculate the optimal evacuation route; and means for transmitting the calculation results to the connected device and displaying them. This allows users to quickly and effectively check and prepare individually optimized disaster prevention measures and take appropriate evacuation actions in the event of a disaster.

[0790] "User" refers to an individual who uses this system to manage disaster prevention measures and evacuation actions.

[0791] "Basic information" refers to personal data entered by the user, such as place of residence, family composition, age, and gender.

[0792] "Server" refers to an online computer system that receives, processes, and stores data sent by users.

[0793] A "data management device" refers to a system that is connected to a server and includes a database for storing and managing basic user information, purchase history, search history, disaster information, and the like.

[0794] "Purchase history" refers to a record of disaster prevention related products and the like that a user has purchased in the past.

[0795] "Search History" refers to a record of queries or items that a User has searched for within an Application.

[0796] "Disaster information" refers to data on the occurrence, intensity, and scope of impact of a disaster.

[0797] "Shelter information" refers to data provided by local governments regarding the location, capacity, and facility status of shelters.

[0798] A "generative AI model" refers to a system that uses artificial intelligence technology to suggest optimal disaster prevention measures to users.

[0799] "Disaster prevention measures list" refers to a list of disaster prevention measures optimized for the user proposed by the generative AI model.

[0800] "Connection device" refers to a terminal device (smartphone, tablet, PC, etc.) that a user uses to connect to a server.

[0801] "E-commerce function" refers to the function that allows users to select and purchase suggested disaster prevention related products online.

[0802] "Current location information" refers to location information (such as GPS data) acquired by the user's device.

[0803] An "evacuation route" refers to a route that allows a user to travel safely and quickly to the nearest evacuation shelter in the event of a disaster.

[0804] A "disaster prevention map" refers to a map that visually displays information related to disaster prevention, such as evacuation routes and the locations of evacuation shelters.

[0805] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to take disaster countermeasures quickly and efficiently. This system has functions such as user registration and basic information input, collection of purchase history and search history, collection of disaster information and evacuation shelter information, disaster prevention measures proposals, shopping function, disaster prevention map and route guidance, etc.

[0806] Hardware and Software Details

[0807] server:

[0808] It is an online server equipped with a data management device for storing and processing information. It uses MySQL or PostgreSQL as its database.

[0809] As an AI system, we use a generative AI model (e.g., OpenAI's GPT).

[0810] Run a script that periodically collects information from the city's APIs and public data sources.

[0811] Device:

[0812] This refers to devices such as smartphones, tablets, and PCs on which users install applications.

[0813] Search queries and purchase history are collected in real time and sent to the server.

[0814] User:

[0815] This is an individual who downloads and installs the app and enters basic information.

[0816] Review the proposed disaster prevention measures and purchase the necessary items.

[0817] Program processing flow

[0818] 1. User registration and basic information entry

[0819] Device: The user downloads and installs the app and enters basic information the first time they launch it.

[0820] Terminal: Sends the entered information to the server as an HTTP request.

[0821] Server: Stores the received user information in a database.

[0822] 2. Collection of purchase and search history

[0823] Device: Every time a user searches for or purchases a disaster prevention product, the data is collected in real time and sent to the server.

[0824] Server: Stores the received data and updates the user's profile.

[0825] 3. Collecting disaster and evacuation shelter information

[0826] Server: Automatically checks local government APIs and public data sources, and stores the latest disaster and evacuation shelter information in a database.

[0827] 4. Proposal of disaster prevention measures

[0828] Server: Inputs the user's basic information, historical data, and disaster information into the generative AI model and calculates optimal disaster prevention measures.

[0829] Generative AI model: Generates a disaster prevention measures list based on input information.

[0830] Server: Sends the generated list to the device.

[0831] Device: Display the list in the user interface so that the user can see it.

[0832] 5. Shopping function

[0833] User: Selects an item from the list of suggested disaster preparedness measures and adds it to their cart.

[0834] Terminal: Sends cart information to the server.

[0835] Server: After checking the stock, the purchase is processed through the payment system.

[0836] Server: Sends a notification of purchase completion and shipping information to the device.

[0837] 6. Disaster prevention map and route guidance

[0838] User: Use the disaster prevention map function to obtain current location information.

[0839] Device: Sends current location information to the server.

[0840] Server: Compares with evacuation shelter information and calculates the optimal evacuation route.

[0841] Server: Sends the calculation results to the terminal.

[0842] Terminal: Displays disaster prevention maps and evacuation routes.

[0843] Specific examples

[0844] For example, consider the case where a user living in Shibuya Ward launches the app and checks new disaster prevention measures.

[0845] 1. User: Launches the app and enters basic information such as name, address, and family composition.

[0846] 2. Terminal: Sends information to the server.

[0847] 3. Server: Stores the input information in a database and inputs the data into the AI ​​system to calculate disaster prevention measures.

[0848] 4. Generative AI model: Generates a list of disaster prevention measures such as "three days' worth of water," "emergency food," and "portable toilet."

[0849] 5. Server: Sends the list to the terminal and displays it for the user to review.

[0850] 6. User: Adds the desired items to the cart and checks out.

[0851] 7. Server: Once the payment process is complete, a notification of purchase completion and delivery information is sent to the terminal.

[0852] 8. User: Check the route to the nearest evacuation shelter and use the disaster prevention map. If necessary, this information can be printed out on a copy machine at a convenience store.

[0853] Prompt Sentence Examples

[0854] For example, the following prompt sentence can be input to a generative AI model to generate a list of disaster prevention measures:

[0855] "A single man in his 30s living in Shibuya Ward wants to check his disaster preparedness. Please make a list of the best disaster preparedness measures for him."

[0856] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures.

[0857] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0858] Step 1:

[0859] User registration and basic information entry

[0860] The user downloads and installs the app.

[0861] Enter: Install app

[0862] Output: App ready to launch

[0863] How it works: Download the app from the app store (Google Play or Apple App Store) and install it.

[0864] When the user starts the app for the first time, they enter basic information (place of residence, family composition, etc.).

[0865] Input: User's basic information (name, address, age, family composition, etc.)

[0866] Output: Local storage of input information

[0867] How it works: Launch the installed app and follow the on-screen instructions to enter your basic information.

[0868] The terminal sends the entered basic information to the server as an HTTP request.

[0869] Input: Basic information entered by the user

[0870] Output: Data transmission to server begins

[0871] How it works: When you press the send button in the app, the information is sent to the server.

[0872] The server stores the received user information in a database.

[0873] Input: User information sent from the device

[0874] Output: Information saved to database

[0875] What happens: A script is executed on the server side to save the data to the database.

[0876] Step 2:

[0877] Collection of purchase and search history

[0878] The device collects information in real time when a user searches for or purchases disaster prevention products.

[0879] Input: User search queries, purchase history

[0880] Output: Recorded to local cache

[0881] How it works: Temporarily stores data when users search for and purchase products.

[0882] The terminal transmits the collected data to the server.

[0883] Input: Collected search queries, purchase history

[0884] Output: Data sent to server completed

[0885] Operation: Collected data is sent to the server periodically or when an event occurs.

[0886] The server stores the received data in a database and updates the user profile.

[0887] Input: Search queries sent from the device, purchase history

[0888] Output: Saved to database and user profile updated

[0889] What it does: Saves the data in the database and keeps each user's profile up to date.

[0890] Step 3:

[0891] Collecting disaster and evacuation shelter information

[0892] The server regularly checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information.

[0893] Input: API calls and public data access

[0894] Output: Latest disaster information, evacuation shelter information

[0895] What it does: Runs a script periodically and calls an API to retrieve data.

[0896] The server stores the collected information in a database.

[0897] Input: Collected disaster information, evacuation shelter information

[0898] Output: Information saved to database

[0899] Behavior: Store in a database and make it accessible to other functions.

[0900] Step 4:

[0901] Disaster prevention measures proposals

[0902] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the generated AI model.

[0903] Input: User basic information, history data, disaster information

[0904] Output: Input to generative AI model completed

[0905] How it works: Preprocesses a dataset to feed into a generative AI model.

[0906] A generative AI model calculates and suggests a list of disaster prevention measures.

[0907] Input: Generated dataset

[0908] Output: List of optimal disaster prevention measures

[0909] How it works: A generative AI model processes data and generates a list of suggestions.

[0910] The server stores the proposed list in a database and sends it to the terminal.

[0911] Input: A list of disaster prevention measures from a generative AI model

[0912] Output: Saved to database, sent to terminal

[0913] Behavior: Save in database and send to user's device.

[0914] The terminal displays the received list on the user interface.

[0915] Input: Disaster prevention measures list sent from the server

[0916] Output: Displayed on the user interface

[0917] Behavior: Display on screen so the user can see it.

[0918] Step 5:

[0919] Shopping feature

[0920] The user selects an item from the list of suggested disaster prevention measures and adds it to the cart.

[0921] Input: User selection of product

[0922] Output: List of items added to cart

[0923] What happens: A user selects a product's checkbox and clicks the Add to Cart button.

[0924] The terminal transmits the cart information to the server.

[0925] Input: List of items added to cart

[0926] Output: Sending to server completed

[0927] What it does: Sends cart information to the server as an HTTP request.

[0928] The server checks the stock status and completes the purchase process through the payment system.

[0929] Input: Cart information

[0930] Output: Inventory check and payment processing completed

[0931] Operation: Check inventory and process payments using a back-end system (e.g., an e-commerce system).

[0932] The server sends a notification of purchase completion and delivery information to the user's terminal.

[0933] Input: Payment processing result

[0934] output: Notification and delivery information sent

[0935] Operation: After payment is completed, payment results and delivery information are sent to the terminal.

[0936] Step 6:

[0937] Disaster prevention map and route guidance

[0938] The user uses the disaster prevention map function to obtain current location information.

[0939] Input: User's current location (GPS information)

[0940] Output: Current location information acquisition completed

[0941] What it does: Click a button in the app to enable location tracking.

[0942] The device sends the current location information to the server.

[0943] Input: Acquired GPS information

[0944] Output: Sending to server completed

[0945] What it does: Sends your current location to the server as an HTTP request.

[0946] The server compares the current location information with the evacuation shelter information and calculates the optimal evacuation route.

[0947] Input: Current location information, evacuation shelter information

[0948] Output: Optimal evacuation route

[0949] How it works: It retrieves the necessary information from a database and uses an algorithm to calculate the optimal evacuation route.

[0950] The server sends the calculation results to the terminal.

[0951] Input: Calculated evacuation route

[0952] Output: Sent to terminal

[0953] Operation: Sends an evacuation route to the device as an HTTP response.

[0954] The evacuation route and disaster prevention map received by the terminal are displayed on the user interface.

[0955] Input: Evacuation route sent from the server

[0956] Output: Displayed on the user interface

[0957] Operation: Disaster prevention maps and evacuation routes are displayed on the screen so that users can check them.

[0958] (Application example 1)

[0959] 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."

[0960] Until now, there have been limited means of swift and efficient evacuation and delivery of emergency supplies during disasters. Furthermore, few systems existed that considered individual purchase and search histories to provide optimal disaster prevention measures, placing a heavy burden on users. Furthermore, systems lacked the ability to obtain real-time information on available evacuation sites and calculate evacuation routes. This made it difficult for many people to respond quickly and efficiently during disasters. A new system was needed to solve this problem.

[0961] 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.

[0962] In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and storing it in a database; means for collecting the user's past purchase history and search history and storing it in a database; means for collecting disaster information and evacuation site information from public institutions and storing it in a database; means for an AI system to propose optimal disaster prevention measures based on the stored information; means for displaying a list of the proposed disaster prevention measures on the user's processing device; means for an autonomous vehicle to calculate an optimal evacuation route in the event of a disaster and transport the user to the optimal evacuation site; means for calculating a delivery route for disaster prevention supplies based on the user's disaster prevention plan list and quickly delivering the supplies; and means for checking the availability of evacuation sites in real time and notifying the user. This enables fast and efficient evacuation and delivery of emergency supplies.

[0963] "Address" refers to the specific area or place where a user resides.

[0964] "Family structure" refers to the composition of members in the user's household, including, for example, parents, children, spouse, etc.

[0965] "Basic information" refers to key data about the user, including address, family composition, date of birth, etc.

[0966] A "server" is a computing device that processes and stores data over a network.

[0967] A "database" is a collection of electronic information that is systematically organized and stored, and that can be easily searched and updated.

[0968] "Purchase history" refers to a record of products purchased by a user in the past.

[0969] "Search history" refers to a record of searches a user has conducted in the past.

[0970] "Public institutions" refer to organizations that function for the public, such as national and local governments.

[0971] "Disaster information" refers to information related to natural disasters such as earthquakes, typhoons, and floods.

[0972] "Evacuation site information" refers to information about places where people should evacuate to ensure their safety in the event of a disaster.

[0973] An "artificial intelligence system" refers to a technological system that analyzes data and learns to make human-like judgments and predictions.

[0974] "Disaster prevention measures" refer to preventive and response measures taken in preparation for the occurrence of a disaster.

[0975] "Processing device" refers to a device for processing data, and primarily includes computers and smartphones.

[0976] An "autonomous vehicle" is a vehicle that has the ability to drive itself without driver intervention.

[0977] An "evacuation route" refers to a route to a safe location in the event of a disaster.

[0978] "Disaster prevention supplies" refer to supplies needed in the event of a disaster, such as disaster prevention equipment and emergency food.

[0979] "Delivery route" refers to the route along which goods are delivered.

[0980] "Real-time confirmation" refers to checking information immediately without delay.

[0981] MODE FOR CARRYING OUT THE INVENTION

[0982] The present invention is a system for realizing rapid evacuation and delivery of emergency supplies in the event of a disaster, and provides functions for proposing evacuation routes and delivering disaster prevention supplies using autonomous vehicles. Specific embodiments of the system are described below.

[0983] User registration and basic information entry

[0984] Users first download and install the dedicated application onto their smartphone or tablet. After installation, they launch the application and a screen appears where they can enter basic information such as their address and family composition. The basic information entered by the user is sent to the server and stored in a database.

[0985] Collection of purchase and search history

[0986] When a user searches for or purchases disaster prevention-related products within the application, their search queries and purchase history are automatically collected and sent to the server, where they are stored in a database and their individual profile is updated.

[0987] Collecting disaster information and evacuation site information

[0988] The server periodically checks APIs provided by public institutions and public data sources to collect the latest disaster information and evacuation site information. This information is also stored in a database and used as material for disaster prevention measures customized for each user.

[0989] Disaster prevention measures proposals

[0990] The server inputs the user's basic information, purchase history, search history, and disaster information from public institutions into an AI system to calculate optimal disaster prevention measures. The proposed disaster prevention measures list is stored in a database and sent to the user's device. The user can view this list on the application.

[0991] Emergency evacuation route suggestions

[0992] When a disaster occurs, if a user gets into an autonomous vehicle, the vehicle uses a GPS device to acquire the user's current location information. The server calculates the optimal evacuation route based on the disaster information and the current location information and sends it to the autonomous vehicle. The vehicle then automatically transports the user to the optimal evacuation location according to this route.

[0993] Delivery of emergency supplies

[0994] Based on the user's disaster prevention plan, the server calculates the optimal delivery route for emergency supplies. The supplies are quickly delivered to the user's address by autonomous vehicles from the disaster prevention center. The server tracks the delivery status in real time and notifies the user.

[0995] Displaying evacuation shelter availability information

[0996] The server checks the availability of evacuation shelters in real time and sends that information to the user's device, where the user can check the availability of evacuation shelters on the application.

[0997] Hardware and software used

[0998] The system requires a server, a GPS device, an autonomous vehicle, a smartphone, and an internet connection. The software includes a dedicated application and an API for collecting disaster information. It also uses an artificial intelligence model for data analysis and recommendations.

[0999] Specific examples

[1000] For example, if a user lives in a certain area of ​​Tokyo and a disaster occurs, an autonomous vehicle will calculate an evacuation route and automatically drive to a safe evacuation site. Also, if a user purchases emergency food and water using a disaster prevention app, the autonomous vehicle will quickly deliver these supplies to the specified address in the event of an emergency.

[1001] Prompt Sentence Examples

[1002] Calculating the best evacuation route in case of a disaster: "Calculate the best route from your current location to a safe evacuation location."

[1003] Emergency supply delivery route calculation: "Calculate the delivery route from the disaster prevention center to a specified address."

[1004] Get information on available evacuation shelters: "Get the latest information on available evacuation shelters."

[1005] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1006] Step 1:

[1007] The user installs a dedicated application and enters basic information such as address and family composition.

[1008] (Input) Basic information entered by the user (address, family composition, age, etc.).

[1009] (Processing) The terminal sends the entered basic information to the server and stores it in the database.

[1010] (Output) Basic information saved in the database.

[1011] Step 2:

[1012] When users search for or purchase disaster prevention-related products within the app, that information is collected.

[1013] (Input) User search queries and purchase history.

[1014] The (processing) terminal sends this information to the server in real time and stores it in a database.

[1015] (Output) Purchase history and search history are saved in the database.

[1016] Step 3:

[1017] The server collects the latest disaster information and evacuation site information from public APIs and public data sources.

[1018] (Input) Data feeds from public APIs and public data sources.

[1019] (Processing) The server periodically calls the API and stores the retrieved information in a database.

[1020] (Output) The latest disaster information and evacuation location information is saved in the database.

[1021] Step 4:

[1022] Based on the stored information, an artificial intelligence system calculates the optimal disaster prevention measures.

[1023] (Input) User's basic information, purchase history, search history, and latest disaster information.

[1024] The (processing) server inputs this information into an artificial intelligence model to calculate the optimal disaster prevention measures.

[1025] (Output) A list of proposed disaster prevention measures.

[1026] Step 5:

[1027] A list of proposed disaster prevention measures is displayed on the user's terminal.

[1028] (Input) Disaster prevention measures list sent from the server.

[1029] (Processing) The list received by the terminal is displayed on the application interface.

[1030] (Output) A display screen that the user can see.

[1031] Step 6:

[1032] When a disaster occurs, autonomous vehicles acquire information about the user's current location and calculate evacuation routes.

[1033] (Input) User's current location information (GPS data).

[1034] (Processing) The server calculates the optimal evacuation route based on the current location information and disaster information, and sends it to the autonomous vehicle.

[1035] (Output) An evacuation route is calculated and directed to the autonomous vehicle.

[1036] Step 7:

[1037] The system calculates delivery routes for emergency supplies based on the user's disaster prevention plan list, and delivers the supplies quickly.

[1038] (Input) User's disaster prevention plan list and disaster prevention goods delivery base information.

[1039] (Processing) The server calculates a delivery route based on this information and gives instructions to the autonomous vehicle.

[1040] (Output) A supply delivery route is calculated and directed to the autonomous vehicle.

[1041] Step 8:

[1042] Check the availability of evacuation shelters in real time and notify users of that information.

[1043] (Input) Information on available evacuation shelters.

[1044] (Processing) The server periodically checks availability information and sends it to the user's terminal.

[1045] (Output) Information about available evacuation shelters displayed on the user's device.

[1046] 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.

[1047] MODE FOR CARRYING OUT THE INVENTION

[1048] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to easily and efficiently take disaster prevention measures, and by combining it with an emotion engine, it provides disaster prevention measures based on the user's emotional state. A detailed embodiment of this system will be described.

[1049] 1. User registration and basic information entry

[1050] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which then stores it in a database.

[1051] 2. Collection of purchase and search history

[1052] When a user searches for or purchases disaster preparedness products within the app, the device collects the search query and purchase history in real time and sends it to the server, which stores this data in a database and updates the user's profile.

[1053] 3. Collecting disaster and evacuation shelter information

[1054] The server periodically checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in a database and used to create customized suggestions for each user.

[1055] 4. Emotion engine integration

[1056] When a user uses the app, the camera and microphone are used to analyze the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state. The device then processes the results of the emotion engine and sends them to the server.

[1057] 5. Proposal of disaster prevention measures

[1058] The server inputs the user's basic information, purchase history, search history, disaster information from local governments, and emotional information obtained from an emotion engine into the AI ​​system to calculate optimal disaster prevention measures. The list of proposed disaster prevention measures is stored in a database and sent to the user's device. The device displays the list so that the user can review it. Based on the user's emotional state, advice and relaxation methods for reducing stress are also suggested.

[1059] 6. Shopping function

[1060] When the user checks the proposed disaster prevention measures list and adds the necessary items to the cart, the device sends the list of items they wish to purchase to the server. The server checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, along with delivery information.

[1061] 7. Disaster Prevention Map and Route Guidance

[1062] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store.

[1063] Specific examples

[1064] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as their address and family composition, the AI ​​system suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilets." Furthermore, if the emotion engine recognizes that the user is emotionally unstable, it also offers advice on stress reduction and relaxation techniques. The user adds the suggested items to their cart and completes the purchase process. The route to the nearest evacuation shelter is then displayed, allowing for smooth evacuation in the event of a disaster. The user can also print out necessary disaster prevention and evacuation shelter information using a convenience store copy machine.

[1065] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures. Furthermore, by integrating an emotion engine, appropriate measures are suggested according to the user's emotional state, thereby reducing the user's physical and mental burden.

[1066] The processing flow will be explained below.

[1067] User registration and basic information entry

[1068] Step 1:

[1069] The user installs the app and accesses the user information input screen when launching it for the first time.

[1070] Step 2:

[1071] The user enters basic information such as name, address, age, and family composition.

[1072] Step 3:

[1073] The device generates an API request to send the basic information entered to the server.

[1074] Step 4:

[1075] The server stores the received information in a database.

[1076] Step 5:

[1077] After the server has completed the storage, it generates a registration confirmation message and sends it to the terminal.

[1078] Collection of purchase and search history

[1079] Step 1:

[1080] A user searches for disaster preparedness products within the app.

[1081] Step 2:

[1082] The device sends a search query to the server.

[1083] Step 3:

[1084] The user adds the product they like to the cart and completes the purchase.

[1085] Step 4:

[1086] The device sends purchase history and cart information to the server.

[1087] Step 5:

[1088] The server stores your search and purchase history in a database.

[1089] Collecting disaster and evacuation shelter information

[1090] Step 1:

[1091] The server periodically queries local government APIs and various public data sources to collect the latest disaster and evacuation shelter information.

[1092] Step 2:

[1093] The server stores the collected data in a database and formats the relevant information.

[1094] Emotion engine integration

[1095] Step 1:

[1096] When a user uses an app, the app asks for permission to use the camera and microphone.

[1097] Step 2:

[1098] If the user gives permission, the device will collect the user's facial expressions and voice in real time.

[1099] Step 3:

[1100] The facial expression and voice data collected by the device is sent to an emotion engine to analyze the emotional state.

[1101] Step 4:

[1102] The emotion engine generates the analysis results and sends them back to the device.

[1103] Disaster prevention measures proposals

[1104] Step 1:

[1105] The server inputs the user's basic information, purchase history, search history, disaster information from local governments, and the analysis results of the emotion engine into the AI ​​system.

[1106] Step 2:

[1107] The AI ​​system calculates the optimal disaster prevention measures.

[1108] Step 3:

[1109] The server generates a list of proposed disaster prevention measures and stores it in a database.

[1110] Step 4:

[1111] The server generates a response to send the generated list to the user's terminal.

[1112] Step 5:

[1113] The terminal displays the disaster prevention measures list to the user and provides an interface that the user can check.

[1114] Step 6:

[1115] The device displays advice and relaxation methods to reduce stress based on the user's emotions.

[1116] Shopping feature

[1117] Step 1:

[1118] The user checks the disaster preparedness list and adds the necessary items to the cart.

[1119] Step 2:

[1120] The device generates an API request to send the list of products desired for purchase to the server.

[1121] Step 3:

[1122] Based on the product list received by the server, the server checks stock status and price information and processes the payment.

[1123] Step 4:

[1124] The server generates a purchase confirmation message and sends it to the user's terminal.

[1125] Step 5:

[1126] The terminal displays a notification to the user that the purchase is complete and displays product delivery information.

[1127] Disaster prevention map and route guidance

[1128] Step 1:

[1129] The user opens the disaster prevention map function within the app.

[1130] Step 2:

[1131] The device obtains the current location information and generates an API request to send to the server.

[1132] Step 3:

[1133] The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route.

[1134] Step 4:

[1135] The server generates a response including the calculated route information and sends it to the terminal.

[1136] Step 5:

[1137] The device displays evacuation routes and disaster prevention maps to the user and provides voice guidance.

[1138] Step 6:

[1139] Users can print out disaster prevention information and evacuation shelter information as needed using a copy machine at a convenience store.

[1140] Example 2

[1141] 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."

[1142] Conventional disaster response systems primarily propose disaster prevention measures based on a user's basic information and purchase and search history, but they do not provide measures that take into account the user's emotional state. Furthermore, when displaying optimal evacuation routes and disaster prevention maps, a rapid response linked to real-time disaster information is required. Furthermore, the lack of a function to easily purchase the proposed disaster prevention products increases the user's workload and hinders actual disaster response.

[1143] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and storing it in a database; means for collecting the user's past purchase history and search history and storing it in a database; means for collecting disaster information and evacuation shelter information from local governments and storing it in a database; emotion analysis means for recognizing the user's emotional state in real time based on the stored information; means for proposing optimal disaster prevention measures using a generative AI model based on the stored information and the emotion analysis results; means for displaying a list of proposed disaster prevention measures on the user's terminal; means for adding necessary disaster prevention products based on the proposed disaster prevention measures list to a shopping cart and performing a purchase process; and means for acquiring the user's current location information, calculating a route to the nearest evacuation shelter, and displaying and guiding the route as a disaster prevention map. This allows optimal disaster prevention measures to be provided in real time while taking the user's emotional state into consideration, enabling quick and efficient evacuation. Furthermore, disaster prevention products can be purchased easily, significantly reducing the user's effort.

[1144] "User" refers to any person or entity that uses the System.

[1145] "Basic information" refers to personal information such as the user's address, family structure, age, and name.

[1146] "Server" refers to a computer system that receives, processes, stores, and provides information from users.

[1147] "Database" refers to an electronic record system in which a server stores and manages information in an organized manner.

[1148] "Purchase History" refers to a record of products purchased by a user within the system.

[1149] "Search History" refers to the record of search queries made by a User within the System.

[1150] "Municipality" refers to local public bodies and local administrative agencies.

[1151] "Disaster information" refers to information related to emergencies such as earthquakes, typhoons, and heavy rain provided by the government and local governments.

[1152] "Evacuation shelter information" refers to information about places where people can evacuate in the event of an emergency.

[1153] "Emotion analysis means" refers to technology for recognizing a user's emotional state based on their facial expressions and voice.

[1154] A "generative AI model" refers to an artificial intelligence model that uses machine learning techniques to predict outcomes from data.

[1155] "Disaster prevention measures" refer to various preparations and guidelines for action to be taken in preparation for the occurrence of a disaster.

[1156] "Shopping cart" refers to a function for carrying out online product purchase procedures.

[1157] "Purchase processing" refers to the payment and delivery procedures for the products selected by the user.

[1158] "Location information" refers to data regarding a user's physical location.

[1159] An "evacuation route" refers to the optimal route to a designated evacuation site in the event of a disaster.

[1160] "Disaster Prevention MAP" refers to a function that displays and guides users to map information for evacuation.

[1161] MODE FOR CARRYING OUT THE INVENTION

[1162] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to easily and efficiently take disaster prevention measures, and by combining it with emotion analysis means, provides disaster prevention measures based on the user's emotional state. A detailed embodiment of this system will be described.

[1163] User registration and basic information entry

[1164] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which stores it in a database. For this purpose, a sending module written in Python and the Django framework are used.

[1165] Collection of purchase and search history

[1166] When a user searches for or purchases disaster prevention products within the app, the device collects the search query and purchase history in real time and sends it to the server. The server stores this history data in a database and updates the user's profile. For example, if a user searches for "emergency food" and purchases a "5-year emergency food set," the search query and purchase history are recorded.

[1167] Collecting disaster and evacuation shelter information

[1168] The server periodically checks local government APIs and public data sources (e.g., the Ministry of Land, Infrastructure, Transport and Tourism's real-time disaster information service) to collect the latest disaster information and evacuation shelter information. This information is stored in a database and used to make customized suggestions for each user. The server sets up a cron job to check the API every day at 9:00 AM.

[1169] Emotion engine integration

[1170] When a user uses the app, the device activates the camera and microphone and analyzes the user's facial expressions and voice in real time. The emotion engine (e.g., Affectiva SDK) recognizes the user's emotional state from their facial expressions and voice and sends the recognition results to the server. For example, when a user taps the "Check evacuation shelter information" button, "anxiety" is recognized from the data collected by the camera.

[1171] Disaster prevention measures proposals

[1172] The server combines the user's basic information, purchase history, search history, disaster information, and emotional information obtained through emotion analysis, and uses a generative AI model (e.g., TensorFlow, PyTorch) to calculate optimal disaster prevention measures. The calculated disaster prevention measures list is stored in a database and sent to the user's device. The device displays this list so that the user can review it. Based on the user's emotional state, advice for reducing stress and relaxation methods are also suggested. For example, specific measures such as "three days' worth of water," "emergency food," and "portable toilet" are presented.

[1173] Shopping feature

[1174] The user checks the proposed disaster prevention measures list and adds the necessary items to the cart. The device sends the list of items desired for purchase to the server, which checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, and delivery information is also displayed.

[1175] Disaster prevention map and route guidance

[1176] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store. The Google Maps API is used to implement this function.

[1177] Specific examples

[1178] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as address and family composition, the generative AI model suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilet." Furthermore, if the emotion engine recognizes that the user's emotions are unstable, it also provides advice on stress reduction and relaxation techniques. The user adds the suggested items to their cart and completes the purchase process. The route to the nearest evacuation shelter is then displayed, allowing for smooth evacuation in the event of a disaster. The user can also print out the necessary disaster prevention and evacuation shelter information using a convenience store copy machine.

[1179] Prompt Sentence Examples

[1180] "A 45-year-old man living in Shibuya Ward with a wife and two children. His current emotional state is unstable. I would like to see a list of optimal disaster prevention measures and shopping suggestions based on that list."

[1181] As a result, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures. In addition, by integrating emotion analysis means, appropriate measures according to the user's emotional state are also suggested, thereby reducing the physical and mental burden on the user.

[1182] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1183] Program processing flow

[1184] Step 1: User registration and basic information entry

[1185] 1. The user downloads and launches the app.

[1186] 2. The terminal displays a screen for entering user information.

[1187] 3. The user enters basic information.

[1188] Input: Name, address, age, family composition

[1189] Output: Basic information data entered

[1190] 4. The device sends the input information to the server.

[1191] Input: Basic information data

[1192] Output: Data transferred to the server

[1193] 5. The server stores the received information in a database.

[1194] Input: Basic information data

[1195] Output: User information stored in the database

[1196] Step 2: Collect purchase and search history

[1197] 1. The user searches for and purchases products within the app.

[1198] 2. The device collects search queries and purchase history.

[1199] Input: search query, purchase information

[1200] Output: Collected historical data

[1201] 3. The device sends the collected information to the server.

[1202] Input: Historical data

[1203] Output: Data transferred to the server

[1204] 4. The server stores the received information in a database and updates the user's profile.

[1205] Input: Historical data

[1206] Output: History and profile updates stored in database

[1207] Step 3: Collect disaster and evacuation information

[1208] 1. The server checks the local government's API or public data sources.

[1209] Input: Municipality API endpoint

[1210] Output: Latest disaster information and evacuation shelter information

[1211] 2. The server stores the disaster information and evacuation shelter information it has acquired in a database.

[1212] Input: Disaster information, evacuation shelter information

[1213] Output: Disaster information and evacuation shelter information stored in a database

[1214] Step 4: Integrating the Emotion Engine

[1215] 1. The user uses the app.

[1216] 2. The device activates the camera and microphone and analyzes the user's facial expressions and voice in real time.

[1217] Input: User's facial expression data, voice data

[1218] Output: Parsed emotion data

[1219] 3. The emotion engine recognizes the user's emotional state.

[1220] Input: facial expression data, voice data

[1221] Output: Perceived emotional state (e.g., "anxiety")

[1222] 4. The device sends the emotion recognition results to the server.

[1223] Input: Emotional state data

[1224] Output: Emotion data sent to the server

[1225] Step 5: Propose disaster prevention measures

[1226] 1. The server collects the user's basic information, purchase history, search history, disaster information, and emotional information.

[1227] Input: Basic information, purchase history, search history, disaster information, emotional information

[1228] Output: Aggregated data

[1229] 2. The server inputs this data into the generative AI model.

[1230] Input: Aggregated data

[1231] Output: Input data for the generative AI model

[1232] 3. The server creates a disaster prevention measures list calculated by the AI ​​model.

[1233] Input: Input data for the AI ​​model

[1234] Output: Disaster prevention measures list

[1235] 4. The server saves the list in a database and sends it to the device.

[1236] Input: Disaster prevention measures list

[1237] Output: Data stored in the database and sent to the device

[1238] 5. The device will display a list of disaster prevention measures.

[1239] Input: Disaster prevention measures list

[1240] Output: The displayed list

[1241] Step 6: Shopping Function

[1242] 1. A user adds an item from their disaster preparedness list to their cart.

[1243] Input: Item information

[1244] Output: Items added to cart

[1245] 2. The terminal sends the list of items desired for purchase to the server.

[1246] Input: Cart information

[1247] Output: Purchase wish list transferred to the server

[1248] 3. The server checks the inventory status.

[1249] Input: List of products you wish to purchase

[1250] Output: Inventory check results

[1251] 4. The server processes the payment and sends a purchase completion notification to the terminal.

[1252] Input: Inventory check results, payment information

[1253] Output: Purchase completion notification and shipping information

[1254] 5. Your device will display a confirmation of purchase and shipping information.

[1255] Input: Purchase completion notification, delivery information

[1256] Output: Displayed notification and shipping information

[1257] Step 7: Disaster prevention map and route guidance

[1258] 1. The user selects the disaster prevention map function.

[1259] 2. The device obtains the current location information.

[1260] Input: GPS data

[1261] Output: Current location information

[1262] 3. The device sends its current location information to the server.

[1263] Input: Current location information

[1264] Output: Current location information sent to the server

[1265] 4. The server calculates the optimal evacuation route.

[1266] Input: Current location information, evacuation shelter information

[1267] Output: Evacuation route data

[1268] 5. The server sends the calculation results to the terminal.

[1269] Input: Evacuation route data

[1270] Output: Route information sent to the device

[1271] 6. The device will display evacuation routes and disaster prevention maps.

[1272] Input: Route information

[1273] Output: Displayed evacuation route and disaster prevention map

[1274] 7. If necessary, print out this information using a copy machine at a convenience store.

[1275] Input: Route information, MAP data

[1276] Output: Printed data

[1277] This provides a concrete explanation of each processing step, making it clear to users how to use this system to take disaster prevention measures.

[1278] (Application example 2)

[1279] 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."

[1280] In recent years, the number of natural disasters has increased, creating a need for rapid and effective disaster prevention measures. However, conventional disaster prevention applications do not provide measures based on the user's emotional state, and they lack functions to reduce stress and anxiety, especially during disasters. Furthermore, in autonomous vehicles, there is a problem that it is difficult to ensure the safety of the driver because there is no system that analyzes the situation inside the vehicle in real time and proposes the optimal evacuation route.

[1281] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1282] In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and saving it in a database; means for collecting the user's past purchase history and search history and saving it in a database; means for collecting disaster information and evacuation shelter information from local governments and saving it in a database; means for the AI ​​system to propose optimal disaster prevention measures based on the saved information; means for displaying a list of proposed disaster prevention measures on the user's terminal; means for recognizing the driver's emotional state based on data collected from sensors in the vehicle and providing advice for reducing stress; and means for acquiring current location information, comparing it with disaster information from local governments to calculate an optimal evacuation route and displaying it on the driver's terminal. This makes it possible to provide appropriate disaster prevention measures and evacuation routes according to the user's emotional state.

[1283] definition statement

[1284] "Basic information" refers to information such as name, address, age, and family composition entered by the user.

[1285] A "means" is a combination of hardware and software for realizing a specific function or operation.

[1286] A "server" is a computer that stores, processes, and manages data over a network.

[1287] A "database" is a system for systematically storing and managing data.

[1288] "Purchase history" is a record of products and services that a user has purchased in the past.

[1289] "Search history" is a record of keywords or queries a user has searched for in the past.

[1290] "Municipal disaster information" is the latest information on natural disasters provided by local government agencies.

[1291] "Evacuation shelter information" is information about designated places to evacuate to in the event of a disaster.

[1292] An "AI system" is a system that uses artificial intelligence technology to analyze data and calculate optimal disaster prevention measures.

[1293] The "disaster prevention measures list" is a list of disaster prevention supplies and measures suggested to the user.

[1294] "In-vehicle sensors" are devices that detect the environment inside the vehicle and the driver's condition in real time.

[1295] "Emotional state" refers to the driver's emotional and psychological state.

[1296] "Stress reduction advice" is a suggestion or instruction to reduce driver stress or anxiety.

[1297] "Current location information" is information about the user's current location obtained using a GPS or the like.

[1298] An "evacuation route" is the optimal route for a user to safely evacuate.

[1299] A "terminal" is a device used by a user, such as a smartphone, tablet, or vehicle infotainment system.

[1300] MODE FOR CARRYING OUT THE INVENTION

[1301] The present invention relates to a disaster prevention support app for an autonomous driving vehicle that is designed to enable a user to respond quickly and accurately in the event of a disaster. Hereinafter, an embodiment of the present invention will be described in detail.

[1302] 1. System Configuration

[1303] This system consists of a server, in-vehicle terminals, various sensors, and a network environment. The server manages user information, disaster information, emotional state, etc., and the in-vehicle terminals provide this information to the user.

[1304] 2. Server Roles

[1305] The server has the following roles:

[1306] User registration and basic information management

[1307] When a user enters basic information such as address and family composition, it is sent to a server and stored in a database. This information is used in emergency response.

[1308] Historical data collection and management

[1309] The system collects and stores users' past purchase and search history in a database, which then suggests individually optimized disaster prevention measures.

[1310] Collecting disaster information

[1311] It regularly checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information and stores it in a database.

[1312] Sentiment Analysis and Recommendations

[1313] It uses generative AI models such as TensorFlow to analyze the driver's emotional state in real time using cameras and microphones in the vehicle, and provides advice to reduce stress based on the analysis results.

[1314] 3. Role of terminals inside the vehicle

[1315] The terminals in the vehicles have the following functions:

[1316] Display of basic information and disaster prevention measures

[1317] Basic information and a list of disaster prevention measures sent from the server are displayed on the vehicle's infotainment system.

[1318] Collecting and transmitting emotional states

[1319] The vehicle's cameras and microphones collect the driver's facial expressions and voice, which are then sent to a server for use in an emotion analysis model.

[1320] Calculating and displaying evacuation routes

[1321] The system acquires current location information and sends it to a server. The server then calculates the optimal evacuation route based on this information and displays it on the vehicle's infotainment system. The route calculation is performed using Google Maps API and other tools.

[1322] 4. Hardware and Software Used

[1323] Specific hardware used includes in-vehicle cameras, microphones, GPS modules, and infotainment systems, while specific software used includes Python, TensorFlow (sentiment analysis), Open Data API (disaster information collection), Google Maps API (route calculation), and Django (server-side).

[1324] 5. Specific Examples

[1325] For example, imagine a driver gets into an autonomous vehicle and the system starts up. The driver's basic information, past search history, and purchase history are stored on a server. Suddenly, a disaster occurs, and the server collects the latest disaster information. A camera inside the vehicle captures the driver's facial expressions, and a TensorFlow model analyzes the driver's emotional state. If the system determines that the driver is anxious, it will advise them on how to relax and calculate and display the optimal evacuation route.

[1326] 6. Examples of prompts

[1327] Examples of specific prompts for an AI model include:

[1328] Prompt sentence for sentiment analysis model:

[1329] "Predict the driver's emotions from image and audio data and output one of the following: stress, tension, anxiety, or calm."

[1330] Prompt for disaster information acquisition:

[1331] "Get the following disaster information: type of disaster, location, evacuation shelter."

[1332] Prompt for evacuation route calculation:

[1333] "Calculate the next evacuation route. Starting point: {current_location}, Destination: {safe_place}."

[1334] As described above, the present invention takes into account the emotional state of the user and provides optimal disaster prevention measures and evacuation routes in real time, enabling a quick and safe response in the event of a disaster.

[1335] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1336] Program processing steps

[1337] Step 1:

[1338] The user inputs basic information such as address and family composition. The device sends the input basic information to the server and stores it in a database. The input includes the user's name, address, age, family composition, etc., and the output is the basic information stored in the database.

[1339] Step 2:

[1340] The system collects the user's past purchases of disaster prevention products and search history. The device sends this historical data to the server in real time and stores it in the server's database. The input is the user's purchase history and search history, and the output is an updated user profile.

[1341] Step 3:

[1342] The server periodically checks the local government's API and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in the server's database. The input is disaster information and evacuation shelter information obtained from the API, and the output is the latest information stored in the database.

[1343] Step 4:

[1344] The system uses cameras and microphones inside the vehicle to collect the driver's facial expressions and voice in real time. The device then sends this data to a server where it is analyzed by an emotion engine. The inputs are camera images and voice data, and the output is analyzed emotional state data.

[1345] Step 5:

[1346] The server uses an AI system to calculate optimal disaster prevention measures based on the collected basic information, historical data, disaster information, evacuation shelter information, and analyzed emotional states. This calculation is performed using a generative AI model such as TensorFlow. The inputs are basic information, historical data, disaster information, evacuation shelter information, and emotional states, and the output is a list of disaster prevention measures.

[1347] Step 6:

[1348] The server sends the generated disaster prevention measures list to the user's device and displays it on the vehicle's infotainment system. The user checks the list and takes specific disaster prevention measures. The input to this step is the generated disaster prevention measures list, and the output is a display and user actions.

[1349] Step 7:

[1350] The server obtains current location information from the device and compares it with the vehicle's GPS data to calculate the optimal evacuation route. The calculated evacuation route is sent to the device and displayed on the vehicle's infotainment system. The inputs are current location information, disaster information, and evacuation shelter information, and the optimal evacuation route is generated as the output.

[1351] Step 8:

[1352] The device provides voice and text advice to reduce stress based on the driver's emotional state, allowing the driver to evacuate safely while remaining relaxed. The input is the analyzed emotional state, and the output is the presentation of advice.

[1353] As described above, by dividing the process into multiple steps, users can be provided with prompt and appropriate disaster prevention measures and evacuation routes in the event of a disaster, and can also receive advice based on their emotional state.

[1354] 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.

[1355] 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.

[1356] 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.

[1357] [Third embodiment]

[1358] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1359] 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.

[1360] 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).

[1361] 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.

[1362] 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.

[1363] 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).

[1364] 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.

[1365] 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.

[1366] 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.

[1367] 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.

[1368] 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.

[1369] 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."

[1370] MODE FOR CARRYING OUT THE INVENTION

[1371] The "Easy Disaster Prevention Response App" of the present invention is a system designed to enable users to easily and efficiently take disaster countermeasures. A detailed embodiment of this system will be described.

[1372] 1. User registration and basic information entry

[1373] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which then stores it in a database.

[1374] 2. Collection of purchase and search history

[1375] When a user searches for or purchases disaster preparedness products within the app, the device collects the search query and purchase history in real time and sends it to the server, which stores this data in a database and updates the user's profile.

[1376] 3. Collecting disaster and evacuation shelter information

[1377] The server periodically checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in a database and used to create customized suggestions for each user.

[1378] 4. Proposal of disaster prevention measures

[1379] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the AI ​​system to calculate optimal disaster prevention measures. The proposed disaster prevention measures list is stored in a database and sent to the user's device, where it is displayed for the user to review.

[1380] 5. Shopping function

[1381] When the user checks the proposed disaster prevention measures list and adds the necessary items to the cart, the device sends the list of items they wish to purchase to the server. The server checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, along with delivery information.

[1382] 6. Disaster prevention map and route guidance

[1383] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store.

[1384] Specific examples

[1385] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as their address and family composition, the AI ​​system suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilets." The user adds the suggested items to their cart and completes the purchase process. The system then displays a route to the nearest evacuation shelter, allowing for smooth evacuation in the event of a disaster. The user can also print out the necessary disaster prevention and evacuation shelter information using a copy machine at a convenience store.

[1386] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures.

[1387] The processing flow will be explained below.

[1388] User registration and basic information entry

[1389] Step 1:

[1390] The user installs the app and accesses the user information input screen when launching it for the first time.

[1391] Step 2:

[1392] The user enters basic information such as name, address, age, and family composition.

[1393] Step 3:

[1394] The device generates an API request to send the basic information entered to the server.

[1395] Step 4:

[1396] The server stores the received information in a database.

[1397] Step 5:

[1398] After the server has completed the storage, it generates a registration confirmation message and sends it to the terminal.

[1399] Collection of purchase and search history

[1400] Step 1:

[1401] A user searches for disaster preparedness products within the app.

[1402] Step 2:

[1403] The device sends a search query to the server.

[1404] Step 3:

[1405] The user adds the product they like to the cart and completes the purchase.

[1406] Step 4:

[1407] The device sends purchase history and cart information to the server.

[1408] Step 5:

[1409] The server stores your search and purchase history in a database.

[1410] Collecting disaster and evacuation shelter information

[1411] Step 1:

[1412] The server periodically queries local government APIs and various public data sources to collect the latest disaster and evacuation shelter information.

[1413] Step 2:

[1414] The server stores the collected data in a database and formats the relevant information.

[1415] Disaster prevention measures proposals

[1416] Step 1:

[1417] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the AI ​​system and calculates the optimal disaster prevention measures.

[1418] Step 2:

[1419] The server generates a list of proposed disaster prevention measures and stores it in a database.

[1420] Step 3:

[1421] The server generates a response to send the generated list to the user's terminal.

[1422] Step 4:

[1423] The device displays a list of disaster prevention measures to the user and provides an interface where the user can check the proposed measures.

[1424] Shopping feature

[1425] Step 1:

[1426] The user checks the disaster preparedness list and adds the necessary items to the cart.

[1427] Step 2:

[1428] The device generates an API request to send the list of products desired for purchase to the server.

[1429] Step 3:

[1430] Based on the product list received by the server, the server checks stock status and price information and processes the payment.

[1431] Step 4:

[1432] The server generates a purchase confirmation message and sends it to the user's terminal.

[1433] Step 5:

[1434] The terminal displays a notification to the user that the purchase is complete and displays product delivery information.

[1435] Disaster prevention map and route guidance

[1436] Step 1:

[1437] The user opens the disaster prevention map function within the app.

[1438] Step 2:

[1439] The device obtains the user's current location information and generates an API request to send to the server.

[1440] Step 3:

[1441] The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route.

[1442] Step 4:

[1443] The server generates a response including the calculated route information and sends it to the terminal.

[1444] Step 5:

[1445] The device displays evacuation routes and disaster prevention maps to the user and provides voice guidance.

[1446] Step 6:

[1447] Users can print out disaster prevention information and evacuation shelter information as needed using a copy machine at a convenience store.

[1448] Example 1

[1449] 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."

[1450] Disaster prevention measures are becoming increasingly important in modern society, and individual users are being asked to take appropriate measures quickly and efficiently. However, currently available disaster prevention applications and tools do not fully utilize individual user information, making it difficult to propose optimal disaster prevention measures to users. Furthermore, there are issues with the accuracy and timeliness of collecting disaster and evacuation shelter information and presenting optimal evacuation routes. For this reason, there is a demand for disaster response systems that are easy for users to use and offer advanced functions.

[1451] 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.

[1452] In this invention, the server includes: means for a user to input basic information such as place of residence and family composition; means for transmitting the input basic information to the server and storing it in a data management device; means for collecting the user's past purchase history and search history and storing it in the data management device; means for automatically collecting disaster information and evacuation shelter information from local governments and storing it in the data management device; means for a generative AI model to propose optimal disaster prevention measures based on the stored information; means for displaying a list of the proposed disaster prevention measures on the user's connected device; means for the user to acquire current location information from the screen of the connected device and send it to the server; means for the server to compare the current location information with the evacuation shelter information and calculate the optimal evacuation route; and means for transmitting the calculation results to the connected device and displaying them. This allows users to quickly and effectively check and prepare individually optimized disaster prevention measures and take appropriate evacuation actions in the event of a disaster.

[1453] "User" refers to an individual who uses this system to manage disaster prevention measures and evacuation actions.

[1454] "Basic information" refers to personal data entered by the user, such as place of residence, family composition, age, and gender.

[1455] "Server" refers to an online computer system that receives, processes, and stores data sent by users.

[1456] A "data management device" refers to a system that is connected to a server and includes a database for storing and managing users' basic information, purchase history, search history, disaster information, and the like.

[1457] "Purchase history" refers to a record of disaster prevention related products and the like that a user has purchased in the past.

[1458] "Search History" refers to a record of queries or items that a User has searched for within an Application.

[1459] "Disaster information" refers to data on the occurrence, intensity, and scope of impact of a disaster.

[1460] "Shelter information" refers to data provided by local governments regarding the location, capacity, and facility status of shelters.

[1461] A "generative AI model" refers to a system that uses artificial intelligence technology to suggest optimal disaster prevention measures to users.

[1462] "Disaster prevention measures list" refers to a list of disaster prevention measures optimized for the user proposed by the generative AI model.

[1463] "Connection device" refers to a terminal device (smartphone, tablet, PC, etc.) that a user uses to connect to a server.

[1464] "E-commerce function" refers to the function that allows users to select and purchase suggested disaster prevention related products online.

[1465] "Current location information" refers to location information (such as GPS data) acquired by the user's device.

[1466] An "evacuation route" refers to a route that allows a user to travel safely and quickly to the nearest evacuation shelter in the event of a disaster.

[1467] A "disaster prevention map" refers to a map that visually displays information related to disaster prevention, such as evacuation routes and the locations of evacuation shelters.

[1468] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to take disaster countermeasures quickly and efficiently. This system has functions such as user registration and basic information input, collection of purchase history and search history, collection of disaster information and evacuation shelter information, disaster prevention measures proposals, shopping function, disaster prevention map and route guidance, etc.

[1469] Hardware and Software Details

[1470] server:

[1471] It is an online server equipped with a data management device for storing and processing information. It uses MySQL or PostgreSQL as its database.

[1472] As an AI system, we use a generative AI model (e.g., OpenAI's GPT).

[1473] Run a script that periodically collects information from the city's APIs and public data sources.

[1474] Device:

[1475] This refers to devices such as smartphones, tablets, and PCs on which users install applications.

[1476] Search queries and purchase history are collected in real time and sent to the server.

[1477] User:

[1478] This is an individual who downloads and installs the app and enters basic information.

[1479] Review the proposed disaster prevention measures and purchase the necessary items.

[1480] Program processing flow

[1481] 1. User registration and basic information entry

[1482] Device: The user downloads and installs the app and enters basic information the first time they launch it.

[1483] Terminal: Sends the entered information to the server as an HTTP request.

[1484] Server: Stores the received user information in a database.

[1485] 2. Collection of purchase and search history

[1486] Device: Every time a user searches for or purchases a disaster prevention product, the data is collected in real time and sent to the server.

[1487] Server: Stores the received data and updates the user's profile.

[1488] 3. Collecting disaster and evacuation shelter information

[1489] Server: Automatically checks local government APIs and public data sources, and stores the latest disaster and evacuation shelter information in a database.

[1490] 4. Proposal of disaster prevention measures

[1491] Server: Inputs the user's basic information, historical data, and disaster information into the generative AI model and calculates optimal disaster prevention measures.

[1492] Generative AI model: Generates a disaster prevention measures list based on input information.

[1493] Server: Sends the generated list to the device.

[1494] Device: Display the list in the user interface so that the user can see it.

[1495] 5. Shopping function

[1496] User: Selects an item from the list of suggested disaster preparedness measures and adds it to their cart.

[1497] Terminal: Sends cart information to the server.

[1498] Server: After checking the stock, the purchase is processed through the payment system.

[1499] Server: Sends a notification of purchase completion and shipping information to the device.

[1500] 6. Disaster prevention map and route guidance

[1501] User: Use the disaster prevention map function to obtain current location information.

[1502] Device: Sends current location information to the server.

[1503] Server: Compares with evacuation shelter information and calculates the optimal evacuation route.

[1504] Server: Sends the calculation results to the terminal.

[1505] Terminal: Displays disaster prevention maps and evacuation routes.

[1506] Specific examples

[1507] For example, consider the case where a user living in Shibuya Ward launches the app and checks new disaster prevention measures.

[1508] 1. User: Launches the app and enters basic information such as name, address, and family composition.

[1509] 2. Terminal: Sends information to the server.

[1510] 3. Server: Stores the input information in a database and inputs the data into the AI ​​system to calculate disaster prevention measures.

[1511] 4. Generative AI model: Generates a list of disaster prevention measures such as "three days' worth of water," "emergency food," and "portable toilet."

[1512] 5. Server: Sends the list to the terminal and displays it for the user to review.

[1513] 6. User: Adds the desired items to the cart and checks out.

[1514] 7. Server: Once the payment process is complete, a notification of purchase completion and delivery information is sent to the terminal.

[1515] 8. User: Check the route to the nearest evacuation shelter and use the disaster prevention map. If necessary, this information can be printed out on a copy machine at a convenience store.

[1516] Prompt Sentence Examples

[1517] For example, the following prompt sentence can be input to a generative AI model to generate a list of disaster prevention measures:

[1518] "A single man in his 30s living in Shibuya Ward wants to check his disaster preparedness. Please make a list of the best disaster preparedness measures for him."

[1519] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures.

[1520] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1521] Step 1:

[1522] User registration and basic information entry

[1523] The user downloads and installs the app.

[1524] Enter: Install app

[1525] Output: App ready to launch

[1526] How it works: Download the app from the app store (Google Play or Apple App Store) and install it.

[1527] When the user starts the app for the first time, they enter basic information (place of residence, family composition, etc.).

[1528] Input: User's basic information (name, address, age, family composition, etc.)

[1529] Output: Local storage of input information

[1530] How it works: Launch the installed app and follow the on-screen instructions to enter your basic information.

[1531] The terminal sends the entered basic information to the server as an HTTP request.

[1532] Input: Basic information entered by the user

[1533] Output: Data transmission to server begins

[1534] How it works: When you press the send button in the app, the information is sent to the server.

[1535] The server stores the received user information in a database.

[1536] Input: User information sent from the device

[1537] Output: Information saved to database

[1538] What happens: A script is executed on the server side to save the data to the database.

[1539] Step 2:

[1540] Collection of purchase and search history

[1541] The device collects information in real time when a user searches for or purchases disaster prevention products.

[1542] Input: User search queries, purchase history

[1543] Output: Recorded to local cache

[1544] How it works: Temporarily stores data when users search for and purchase products.

[1545] The terminal transmits the collected data to the server.

[1546] Input: Collected search queries, purchase history

[1547] Output: Data sent to server completed

[1548] Operation: Collected data is sent to the server periodically or when an event occurs.

[1549] The server stores the received data in a database and updates the user profile.

[1550] Input: Search queries sent from the device, purchase history

[1551] Output: Saved to database and user profile updated

[1552] What it does: Saves the data in the database and keeps each user's profile up to date.

[1553] Step 3:

[1554] Collecting disaster and evacuation shelter information

[1555] The server regularly checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information.

[1556] Input: API calls and public data access

[1557] Output: Latest disaster information, evacuation shelter information

[1558] What it does: Runs a script periodically and calls an API to retrieve data.

[1559] The server stores the collected information in a database.

[1560] Input: Collected disaster information, evacuation shelter information

[1561] Output: Information saved to database

[1562] Behavior: Store in a database and make it accessible to other functions.

[1563] Step 4:

[1564] Disaster prevention measures proposals

[1565] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the generated AI model.

[1566] Input: User basic information, history data, disaster information

[1567] Output: Input to generative AI model completed

[1568] How it works: Preprocesses a dataset to feed into a generative AI model.

[1569] A generative AI model calculates and suggests a list of disaster prevention measures.

[1570] Input: Generated dataset

[1571] Output: List of optimal disaster prevention measures

[1572] How it works: A generative AI model processes data and generates a list of suggestions.

[1573] The server stores the proposed list in a database and sends it to the terminal.

[1574] Input: A list of disaster prevention measures from a generative AI model

[1575] Output: Saved to database, sent to terminal

[1576] Behavior: Save in database and send to user's device.

[1577] The terminal displays the received list on the user interface.

[1578] Input: Disaster prevention measures list sent from the server

[1579] Output: Displayed on the user interface

[1580] Behavior: Display on screen so the user can see it.

[1581] Step 5:

[1582] Shopping feature

[1583] The user selects an item from the list of suggested disaster prevention measures and adds it to the cart.

[1584] Input: User selection of product

[1585] Output: List of items added to cart

[1586] What happens: A user selects a product's checkbox and clicks the Add to Cart button.

[1587] The terminal transmits the cart information to the server.

[1588] Input: List of items added to cart

[1589] Output: Sending to server completed

[1590] What it does: Sends cart information to the server as an HTTP request.

[1591] The server checks the stock status and completes the purchase process through the payment system.

[1592] Input: Cart information

[1593] Output: Inventory check and payment processing completed

[1594] Operation: Check inventory and process payments using a back-end system (e.g., an e-commerce system).

[1595] The server sends a notification of purchase completion and delivery information to the user's terminal.

[1596] Input: Payment processing result

[1597] output: Notification and delivery information sent

[1598] Operation: After payment is completed, payment results and delivery information are sent to the terminal.

[1599] Step 6:

[1600] Disaster prevention map and route guidance

[1601] The user uses the disaster prevention map function to obtain current location information.

[1602] Input: User's current location (GPS information)

[1603] Output: Current location information acquisition completed

[1604] What it does: Click a button in the app to enable location tracking.

[1605] The device sends the current location information to the server.

[1606] Input: Acquired GPS information

[1607] Output: Sending to server completed

[1608] What it does: Sends your current location to the server as an HTTP request.

[1609] The server compares the current location information with the evacuation shelter information and calculates the optimal evacuation route.

[1610] Input: Current location information, evacuation shelter information

[1611] Output: Optimal evacuation route

[1612] How it works: It retrieves the necessary information from a database and uses an algorithm to calculate the optimal evacuation route.

[1613] The server sends the calculation results to the terminal.

[1614] Input: Calculated evacuation route

[1615] Output: Sent to terminal

[1616] Operation: Sends an evacuation route to the device as an HTTP response.

[1617] The evacuation route and disaster prevention map received by the terminal are displayed on the user interface.

[1618] Input: Evacuation route sent from the server

[1619] Output: Displayed on the user interface

[1620] Operation: Disaster prevention maps and evacuation routes are displayed on the screen so that users can check them.

[1621] (Application example 1)

[1622] 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."

[1623] Until now, there have been limited means of swift and efficient evacuation and delivery of emergency supplies during disasters. Furthermore, few systems existed that considered individual purchase and search histories to provide optimal disaster prevention measures, placing a heavy burden on users. Furthermore, systems lacked the ability to obtain real-time information on available evacuation sites and calculate evacuation routes. This made it difficult for many people to respond quickly and efficiently during disasters. A new system was needed to solve this problem.

[1624] 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.

[1625] In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and storing it in a database; means for collecting the user's past purchase history and search history and storing it in a database; means for collecting disaster information and evacuation site information from public institutions and storing it in a database; means for an AI system to propose optimal disaster prevention measures based on the stored information; means for displaying a list of the proposed disaster prevention measures on the user's processing device; means for an autonomous vehicle to calculate an optimal evacuation route in the event of a disaster and transport the user to the optimal evacuation site; means for calculating a delivery route for disaster prevention supplies based on the user's disaster prevention plan list and quickly delivering the supplies; and means for checking the availability of evacuation sites in real time and notifying the user. This enables fast and efficient evacuation and delivery of emergency supplies.

[1626] "Address" refers to the specific area or place where a user resides.

[1627] "Family structure" refers to the composition of members in the user's household, including, for example, parents, children, spouse, etc.

[1628] "Basic information" refers to key data about the user, including address, family composition, date of birth, etc.

[1629] A "server" is a computing device that processes and stores data over a network.

[1630] A "database" is a collection of electronic information that is systematically organized and stored, and that can be easily searched and updated.

[1631] "Purchase history" refers to a record of products purchased by a user in the past.

[1632] "Search history" refers to a record of searches a user has conducted in the past.

[1633] "Public institutions" refer to organizations that function for the public, such as national and local governments.

[1634] "Disaster information" refers to information related to natural disasters such as earthquakes, typhoons, and floods.

[1635] "Evacuation site information" refers to information about places where people should evacuate to ensure their safety in the event of a disaster.

[1636] An "artificial intelligence system" refers to a technological system that analyzes data and learns to make human-like judgments and predictions.

[1637] "Disaster prevention measures" refer to preventive and response measures taken in preparation for the occurrence of a disaster.

[1638] "Processing device" refers to a device for processing data, and primarily includes computers and smartphones.

[1639] An "autonomous vehicle" is a vehicle that has the ability to drive itself without driver intervention.

[1640] An "evacuation route" refers to a route to a safe location in the event of a disaster.

[1641] "Disaster prevention supplies" refer to supplies needed in the event of a disaster, such as disaster prevention equipment and emergency food.

[1642] "Delivery route" refers to the route along which goods are delivered.

[1643] "Real-time confirmation" refers to checking information immediately without delay.

[1644] MODE FOR CARRYING OUT THE INVENTION

[1645] The present invention is a system for realizing rapid evacuation and delivery of emergency supplies in the event of a disaster, and provides functions for proposing evacuation routes and delivering disaster prevention supplies using autonomous vehicles. Specific embodiments of the system are described below.

[1646] User registration and basic information entry

[1647] Users first download and install a dedicated application onto their smartphone or tablet. After installation, they launch the application and a screen appears where they can enter basic information such as their address and family composition. The basic information entered by the user is sent to the server and stored in a database.

[1648] Collection of purchase and search history

[1649] When a user searches for or purchases disaster prevention-related products within the application, their search queries and purchase history are automatically collected and sent to the server, where they are stored in a database and their individual profile is updated.

[1650] Collecting disaster information and evacuation site information

[1651] The server periodically checks APIs provided by public institutions and public data sources to collect the latest disaster information and evacuation site information. This information is also stored in a database and used as material for disaster prevention measures customized for each user.

[1652] Disaster prevention measures proposals

[1653] The server inputs the user's basic information, purchase history, search history, and disaster information from public institutions into an AI system to calculate optimal disaster prevention measures. The proposed disaster prevention measures list is stored in a database and sent to the user's device. The user can view this list on the application.

[1654] Emergency evacuation route suggestions

[1655] When a disaster occurs, if a user gets into an autonomous vehicle, the vehicle uses a GPS device to acquire the user's current location information. The server calculates the optimal evacuation route based on the disaster information and the current location information and sends it to the autonomous vehicle. The vehicle then automatically transports the user to the optimal evacuation location according to this route.

[1656] Delivery of emergency supplies

[1657] Based on the user's disaster prevention plan, the server calculates the optimal delivery route for emergency supplies. The supplies are quickly delivered to the user's address by autonomous vehicles from the disaster prevention center. The server tracks the delivery status in real time and notifies the user.

[1658] Displaying evacuation shelter availability information

[1659] The server checks the availability of evacuation shelters in real time and sends that information to the user's device, where the user can check the availability of evacuation shelters on the application.

[1660] Hardware and software used

[1661] The system requires a server, a GPS device, an autonomous vehicle, a smartphone, and an internet connection. The software includes a dedicated application and an API for collecting disaster information. It also uses an artificial intelligence model for data analysis and recommendations.

[1662] Specific examples

[1663] For example, if a user lives in a certain area of ​​Tokyo and a disaster occurs, an autonomous vehicle will calculate an evacuation route and automatically drive to a safe evacuation site. Also, if a user purchases emergency food and water using a disaster prevention app, the autonomous vehicle will quickly deliver these supplies to the specified address in the event of an emergency.

[1664] Prompt Sentence Examples

[1665] Calculating the best evacuation route in case of a disaster: "Calculate the best route from your current location to a safe evacuation location."

[1666] Emergency supply delivery route calculation: "Calculate the delivery route from the disaster prevention center to a specified address."

[1667] Get information on available evacuation shelters: "Get the latest information on available evacuation shelters."

[1668] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1669] Step 1:

[1670] The user installs a dedicated application and enters basic information such as address and family composition.

[1671] (Input) Basic information entered by the user (address, family composition, age, etc.).

[1672] (Processing) The terminal sends the entered basic information to the server and stores it in the database.

[1673] (Output) Basic information saved in the database.

[1674] Step 2:

[1675] When users search for or purchase disaster prevention-related products within the app, that information is collected.

[1676] (Input) User search queries and purchase history.

[1677] The (processing) terminal sends this information to the server in real time and stores it in a database.

[1678] (Output) Purchase history and search history are saved in the database.

[1679] Step 3:

[1680] The server collects the latest disaster information and evacuation site information from public APIs and public data sources.

[1681] (Input) Data feeds from public APIs and public data sources.

[1682] (Processing) The server periodically calls the API and stores the retrieved information in a database.

[1683] (Output) The latest disaster information and evacuation location information is saved in the database.

[1684] Step 4:

[1685] Based on the stored information, an artificial intelligence system calculates the optimal disaster prevention measures.

[1686] (Input) User's basic information, purchase history, search history, and latest disaster information.

[1687] The (processing) server inputs this information into an artificial intelligence model to calculate the optimal disaster prevention measures.

[1688] (Output) A list of proposed disaster prevention measures.

[1689] Step 5:

[1690] A list of proposed disaster prevention measures is displayed on the user's terminal.

[1691] (Input) Disaster prevention measures list sent from the server.

[1692] (Processing) The list received by the terminal is displayed on the application interface.

[1693] (Output) A display screen that the user can see.

[1694] Step 6:

[1695] When a disaster occurs, autonomous vehicles acquire information about the user's current location and calculate evacuation routes.

[1696] (Input) User's current location information (GPS data).

[1697] (Processing) The server calculates the optimal evacuation route based on the current location information and disaster information, and sends it to the autonomous vehicle.

[1698] (Output) An evacuation route is calculated and directed to the autonomous vehicle.

[1699] Step 7:

[1700] The system calculates delivery routes for emergency supplies based on the user's disaster prevention plan list, and delivers the supplies quickly.

[1701] (Input) User's disaster prevention plan list and disaster prevention goods delivery base information.

[1702] (Processing) The server calculates a delivery route based on this information and gives instructions to the autonomous vehicle.

[1703] (Output) A supply delivery route is calculated and directed to the autonomous vehicle.

[1704] Step 8:

[1705] Check the availability of evacuation shelters in real time and notify users of that information.

[1706] (Input) Information on available evacuation shelters.

[1707] (Processing) The server periodically checks availability information and sends it to the user's terminal.

[1708] (Output) Information about available evacuation shelters displayed on the user's device.

[1709] 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.

[1710] MODE FOR CARRYING OUT THE INVENTION

[1711] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to easily and efficiently take disaster prevention measures, and by combining it with an emotion engine, it provides disaster prevention measures based on the user's emotional state. A detailed embodiment of this system will be described.

[1712] 1. User registration and basic information entry

[1713] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which then stores it in a database.

[1714] 2. Collection of purchase and search history

[1715] When a user searches for or purchases disaster preparedness products within the app, the device collects the search query and purchase history in real time and sends it to the server, which stores this data in a database and updates the user's profile.

[1716] 3. Collecting disaster and evacuation shelter information

[1717] The server periodically checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in a database and used to create customized suggestions for each user.

[1718] 4. Emotion engine integration

[1719] When a user uses the app, the camera and microphone are used to analyze the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state. The device then processes the results of the emotion engine and sends them to the server.

[1720] 5. Proposal of disaster prevention measures

[1721] The server inputs the user's basic information, purchase history, search history, disaster information from local governments, and emotional information obtained from an emotion engine into the AI ​​system to calculate optimal disaster prevention measures. The list of proposed disaster prevention measures is stored in a database and sent to the user's device. The device displays the list so that the user can review it. Based on the user's emotional state, advice and relaxation methods for reducing stress are also suggested.

[1722] 6. Shopping function

[1723] When the user checks the proposed disaster prevention measures list and adds the necessary items to the cart, the device sends the list of items they wish to purchase to the server. The server checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, along with delivery information.

[1724] 7. Disaster Prevention Map and Route Guidance

[1725] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store.

[1726] Specific examples

[1727] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as their address and family composition, the AI ​​system suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilets." Furthermore, if the emotion engine recognizes that the user is emotionally unstable, it also offers advice on stress reduction and relaxation techniques. The user adds the suggested items to their cart and completes the purchase process. The route to the nearest evacuation shelter is then displayed, allowing for smooth evacuation in the event of a disaster. The user can also print out necessary disaster prevention and evacuation shelter information using a convenience store copy machine.

[1728] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures. Furthermore, by integrating an emotion engine, appropriate measures are suggested according to the user's emotional state, thereby reducing the user's physical and mental burden.

[1729] The processing flow will be explained below.

[1730] User registration and basic information entry

[1731] Step 1:

[1732] The user installs the app and accesses the user information input screen when launching it for the first time.

[1733] Step 2:

[1734] The user enters basic information such as name, address, age, and family composition.

[1735] Step 3:

[1736] The device generates an API request to send the basic information entered to the server.

[1737] Step 4:

[1738] The server stores the received information in a database.

[1739] Step 5:

[1740] After the server has completed the storage, it generates a registration confirmation message and sends it to the terminal.

[1741] Collection of purchase and search history

[1742] Step 1:

[1743] A user searches for disaster preparedness products within the app.

[1744] Step 2:

[1745] The device sends a search query to the server.

[1746] Step 3:

[1747] The user adds the product they like to the cart and completes the purchase.

[1748] Step 4:

[1749] The device sends purchase history and cart information to the server.

[1750] Step 5:

[1751] The server stores your search and purchase history in a database.

[1752] Collecting disaster and evacuation shelter information

[1753] Step 1:

[1754] The server periodically queries local government APIs and various public data sources to collect the latest disaster and evacuation shelter information.

[1755] Step 2:

[1756] The server stores the collected data in a database and formats the relevant information.

[1757] Emotion engine integration

[1758] Step 1:

[1759] When a user uses an app, the app asks for permission to use the camera and microphone.

[1760] Step 2:

[1761] If the user gives permission, the device will collect the user's facial expressions and voice in real time.

[1762] Step 3:

[1763] The facial expression and voice data collected by the device is sent to an emotion engine to analyze the emotional state.

[1764] Step 4:

[1765] The emotion engine generates the analysis results and sends them back to the device.

[1766] Disaster prevention measures proposals

[1767] Step 1:

[1768] The server inputs the user's basic information, purchase history, search history, disaster information from local governments, and the analysis results of the emotion engine into the AI ​​system.

[1769] Step 2:

[1770] The AI ​​system calculates the optimal disaster prevention measures.

[1771] Step 3:

[1772] The server generates a list of proposed disaster prevention measures and stores it in a database.

[1773] Step 4:

[1774] The server generates a response to send the generated list to the user's terminal.

[1775] Step 5:

[1776] The terminal displays the disaster prevention measures list to the user and provides an interface that the user can check.

[1777] Step 6:

[1778] The device displays advice and relaxation methods to reduce stress based on the user's emotions.

[1779] Shopping feature

[1780] Step 1:

[1781] The user checks the disaster preparedness list and adds the necessary items to the cart.

[1782] Step 2:

[1783] The device generates an API request to send the list of products desired for purchase to the server.

[1784] Step 3:

[1785] Based on the product list received by the server, the server checks stock status and price information and processes the payment.

[1786] Step 4:

[1787] The server generates a purchase confirmation message and sends it to the user's terminal.

[1788] Step 5:

[1789] The terminal displays a notification to the user that the purchase is complete and displays product delivery information.

[1790] Disaster prevention map and route guidance

[1791] Step 1:

[1792] The user opens the disaster prevention map function within the app.

[1793] Step 2:

[1794] The device obtains the current location information and generates an API request to send to the server.

[1795] Step 3:

[1796] The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route.

[1797] Step 4:

[1798] The server generates a response including the calculated route information and sends it to the terminal.

[1799] Step 5:

[1800] The device displays evacuation routes and disaster prevention maps to the user and provides voice guidance.

[1801] Step 6:

[1802] Users can print out disaster prevention information and evacuation shelter information as needed using a copy machine at a convenience store.

[1803] Example 2

[1804] 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."

[1805] Conventional disaster response systems primarily propose disaster prevention measures based on a user's basic information and purchase and search history, but they do not provide measures that take into account the user's emotional state. Furthermore, when displaying optimal evacuation routes and disaster prevention maps, a rapid response linked to real-time disaster information is required. Furthermore, the lack of a function to easily purchase the proposed disaster prevention products increases the user's workload and hinders actual disaster response.

[1806] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and storing it in a database; means for collecting the user's past purchase history and search history and storing it in a database; means for collecting disaster information and evacuation shelter information from local governments and storing it in a database; emotion analysis means for recognizing the user's emotional state in real time based on the stored information; means for proposing optimal disaster prevention measures using a generative AI model based on the stored information and the emotion analysis results; means for displaying a list of proposed disaster prevention measures on the user's terminal; means for adding necessary disaster prevention products based on the proposed disaster prevention measures list to a shopping cart and performing a purchase process; and means for acquiring the user's current location information, calculating a route to the nearest evacuation shelter, and displaying and guiding the route as a disaster prevention map. This allows optimal disaster prevention measures to be provided in real time while taking the user's emotional state into consideration, enabling quick and efficient evacuation. Furthermore, disaster prevention products can be purchased easily, significantly reducing the user's effort.

[1807] "User" refers to any person or entity that uses the System.

[1808] "Basic information" refers to personal information such as the user's address, family structure, age, and name.

[1809] "Server" refers to a computer system that receives, processes, stores, and provides information from users.

[1810] "Database" refers to an electronic record system in which a server stores and manages information in an organized manner.

[1811] "Purchase History" refers to a record of products purchased by a user within the system.

[1812] "Search History" refers to the record of search queries made by a User within the System.

[1813] "Municipality" refers to local public bodies and local administrative agencies.

[1814] "Disaster information" refers to information related to emergencies such as earthquakes, typhoons, and heavy rain provided by the government and local governments.

[1815] "Evacuation shelter information" refers to information about places where people can evacuate in the event of an emergency.

[1816] "Emotion analysis means" refers to technology for recognizing a user's emotional state based on their facial expressions and voice.

[1817] A "generative AI model" refers to an artificial intelligence model that uses machine learning techniques to predict outcomes from data.

[1818] "Disaster prevention measures" refer to various preparations and guidelines for action to be taken in preparation for the occurrence of a disaster.

[1819] "Shopping cart" refers to a function for carrying out online product purchase procedures.

[1820] "Purchase processing" refers to the payment and delivery procedures for the products selected by the user.

[1821] "Location information" refers to data regarding a user's physical location.

[1822] An "evacuation route" refers to the optimal route to a designated evacuation site in the event of a disaster.

[1823] "Disaster Prevention MAP" refers to a function that displays and guides users to map information for evacuation.

[1824] MODE FOR CARRYING OUT THE INVENTION

[1825] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to easily and efficiently take disaster prevention measures, and by combining it with emotion analysis means, provides disaster prevention measures based on the user's emotional state. A detailed embodiment of this system will be described.

[1826] User registration and basic information entry

[1827] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which stores it in a database. For this purpose, a sending module written in Python and the Django framework are used.

[1828] Collection of purchase and search history

[1829] When a user searches for or purchases disaster prevention products within the app, the device collects the search query and purchase history in real time and sends it to the server. The server stores this history data in a database and updates the user's profile. For example, if a user searches for "emergency food" and purchases a "5-year emergency food set," the search query and purchase history are recorded.

[1830] Collecting disaster and evacuation shelter information

[1831] The server periodically checks local government APIs and public data sources (e.g., the Ministry of Land, Infrastructure, Transport and Tourism's real-time disaster information service) to collect the latest disaster information and evacuation shelter information. This information is stored in a database and used to make customized suggestions for each user. The server sets up a cron job to check the API every day at 9:00 AM.

[1832] Emotion engine integration

[1833] When a user uses the app, the device activates the camera and microphone and analyzes the user's facial expressions and voice in real time. The emotion engine (e.g., Affectiva SDK) recognizes the user's emotional state from their facial expressions and voice and sends the recognition results to the server. For example, when a user taps the "Check evacuation shelter information" button, "anxiety" is recognized from the data collected by the camera.

[1834] Disaster prevention measures proposals

[1835] The server combines the user's basic information, purchase history, search history, disaster information, and emotional information obtained through emotion analysis, and uses a generative AI model (e.g., TensorFlow, PyTorch) to calculate optimal disaster prevention measures. The calculated disaster prevention measures list is stored in a database and sent to the user's device. The device displays this list so that the user can review it. Based on the user's emotional state, advice for reducing stress and relaxation methods are also suggested. For example, specific measures such as "three days' worth of water," "emergency food," and "portable toilet" are presented.

[1836] Shopping feature

[1837] The user checks the proposed disaster prevention measures list and adds the necessary items to the cart. The device sends the list of items desired for purchase to the server, which checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, and delivery information is also displayed.

[1838] Disaster prevention map and route guidance

[1839] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store. The Google Maps API is used to implement this function.

[1840] Specific examples

[1841] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as address and family composition, the generative AI model suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilet." Furthermore, if the emotion engine recognizes that the user's emotions are unstable, it also provides advice on stress reduction and relaxation techniques. The user adds the suggested items to their cart and completes the purchase process. The route to the nearest evacuation shelter is then displayed, allowing for smooth evacuation in the event of a disaster. The user can also print out the necessary disaster prevention and evacuation shelter information using a convenience store copy machine.

[1842] Prompt Sentence Examples

[1843] "A 45-year-old man living in Shibuya Ward with a wife and two children. His current emotional state is unstable. I would like to see a list of optimal disaster prevention measures and shopping suggestions based on that list."

[1844] As a result, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures. In addition, by integrating emotion analysis means, appropriate measures according to the user's emotional state are also suggested, thereby reducing the physical and mental burden on the user.

[1845] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1846] Program processing flow

[1847] Step 1: User registration and basic information entry

[1848] 1. The user downloads and launches the app.

[1849] 2. The terminal displays a screen for entering user information.

[1850] 3. The user enters basic information.

[1851] Input: Name, address, age, family composition

[1852] Output: Basic information data entered

[1853] 4. The device sends the input information to the server.

[1854] Input: Basic information data

[1855] Output: Data transferred to the server

[1856] 5. The server stores the received information in a database.

[1857] Input: Basic information data

[1858] Output: User information stored in the database

[1859] Step 2: Collect purchase and search history

[1860] 1. The user searches for and purchases products within the app.

[1861] 2. The device collects search queries and purchase history.

[1862] Input: search query, purchase information

[1863] Output: Collected historical data

[1864] 3. The device sends the collected information to the server.

[1865] Input: Historical data

[1866] Output: Data transferred to the server

[1867] 4. The server stores the received information in a database and updates the user's profile.

[1868] Input: Historical data

[1869] Output: History and profile updates stored in database

[1870] Step 3: Collect disaster and evacuation information

[1871] 1. The server checks the local government's API or public data sources.

[1872] Input: Municipality API endpoint

[1873] Output: Latest disaster information and evacuation shelter information

[1874] 2. The server stores the disaster information and evacuation shelter information it has acquired in a database.

[1875] Input: Disaster information, evacuation shelter information

[1876] Output: Disaster information and evacuation shelter information stored in a database

[1877] Step 4: Integrating the Emotion Engine

[1878] 1. The user uses the app.

[1879] 2. The device activates the camera and microphone and analyzes the user's facial expressions and voice in real time.

[1880] Input: User's facial expression data, voice data

[1881] Output: Parsed emotion data

[1882] 3. The emotion engine recognizes the user's emotional state.

[1883] Input: facial expression data, voice data

[1884] Output: Perceived emotional state (e.g., "anxiety")

[1885] 4. The device sends the emotion recognition results to the server.

[1886] Input: Emotional state data

[1887] Output: Emotion data sent to the server

[1888] Step 5: Propose disaster prevention measures

[1889] 1. The server collects the user's basic information, purchase history, search history, disaster information, and emotional information.

[1890] Input: Basic information, purchase history, search history, disaster information, emotional information

[1891] Output: Aggregated data

[1892] 2. The server inputs this data into the generative AI model.

[1893] Input: Aggregated data

[1894] Output: Input data for the generative AI model

[1895] 3. The server creates a disaster prevention measures list calculated by the AI ​​model.

[1896] Input: Input data for the AI ​​model

[1897] Output: Disaster prevention measures list

[1898] 4. The server saves the list in a database and sends it to the device.

[1899] Input: Disaster prevention measures list

[1900] Output: Data stored in the database and sent to the device

[1901] 5. The device will display a list of disaster prevention measures.

[1902] Input: Disaster prevention measures list

[1903] Output: The displayed list

[1904] Step 6: Shopping Function

[1905] 1. A user adds an item from their disaster preparedness list to their cart.

[1906] Input: Item information

[1907] Output: Items added to cart

[1908] 2. The terminal sends the list of items desired for purchase to the server.

[1909] Input: Cart information

[1910] Output: Purchase wish list transferred to the server

[1911] 3. The server checks the inventory status.

[1912] Input: List of products you wish to purchase

[1913] Output: Inventory check results

[1914] 4. The server processes the payment and sends a purchase completion notification to the terminal.

[1915] Input: Inventory check results, payment information

[1916] Output: Purchase completion notification and shipping information

[1917] 5. Your device will display a confirmation of purchase and shipping information.

[1918] Input: Purchase completion notification, delivery information

[1919] Output: Displayed notification and shipping information

[1920] Step 7: Disaster prevention map and route guidance

[1921] 1. The user selects the disaster prevention map function.

[1922] 2. The device obtains the current location information.

[1923] Input: GPS data

[1924] Output: Current location information

[1925] 3. The device sends its current location information to the server.

[1926] Input: Current location information

[1927] Output: Current location information sent to the server

[1928] 4. The server calculates the optimal evacuation route.

[1929] Input: Current location information, evacuation shelter information

[1930] Output: Evacuation route data

[1931] 5. The server sends the calculation results to the terminal.

[1932] Input: Evacuation route data

[1933] Output: Route information sent to the device

[1934] 6. The device will display evacuation routes and disaster prevention maps.

[1935] Input: Route information

[1936] Output: Displayed evacuation route and disaster prevention map

[1937] 7. If necessary, print out this information using a copy machine at a convenience store.

[1938] Input: Route information, MAP data

[1939] Output: Printed data

[1940] This provides a concrete explanation of each processing step, making it clear to users how to use this system to take disaster prevention measures.

[1941] (Application example 2)

[1942] 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."

[1943] In recent years, the number of natural disasters has increased, creating a need for rapid and effective disaster prevention measures. However, conventional disaster prevention applications do not provide measures based on the user's emotional state, and they lack functions to reduce stress and anxiety, especially during disasters. Furthermore, in autonomous vehicles, there is a problem that it is difficult to ensure the safety of the driver because there is no system that analyzes the situation inside the vehicle in real time and proposes the optimal evacuation route.

[1944] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1945] In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and saving it in a database; means for collecting the user's past purchase history and search history and saving it in a database; means for collecting disaster information and evacuation shelter information from local governments and saving it in a database; means for the AI ​​system to propose optimal disaster prevention measures based on the saved information; means for displaying a list of proposed disaster prevention measures on the user's terminal; means for recognizing the driver's emotional state based on data collected from sensors in the vehicle and providing advice for reducing stress; and means for acquiring current location information, comparing it with disaster information from local governments to calculate an optimal evacuation route and displaying it on the driver's terminal. This makes it possible to provide appropriate disaster prevention measures and evacuation routes according to the user's emotional state.

[1946] definition statement

[1947] "Basic information" refers to information such as name, address, age, and family composition entered by the user.

[1948] A "means" is a combination of hardware and software for realizing a specific function or operation.

[1949] A "server" is a computer that stores, processes, and manages data over a network.

[1950] A "database" is a system for systematically storing and managing data.

[1951] "Purchase history" is a record of products and services that a user has purchased in the past.

[1952] "Search history" is a record of keywords or queries a user has searched for in the past.

[1953] "Municipal disaster information" is the latest information on natural disasters provided by local government agencies.

[1954] "Evacuation shelter information" is information about designated places to evacuate to in the event of a disaster.

[1955] An "AI system" is a system that uses artificial intelligence technology to analyze data and calculate optimal disaster prevention measures.

[1956] The "disaster prevention measures list" is a list of disaster prevention supplies and measures suggested to the user.

[1957] "In-vehicle sensors" are devices that detect the environment inside the vehicle and the driver's condition in real time.

[1958] "Emotional state" refers to the driver's emotional and psychological state.

[1959] "Stress reduction advice" is a suggestion or instruction to reduce driver stress or anxiety.

[1960] "Current location information" is information about the user's current location obtained using a GPS or the like.

[1961] An "evacuation route" is the optimal route for a user to safely evacuate.

[1962] A "terminal" is a device used by a user, such as a smartphone, tablet, or vehicle infotainment system.

[1963] MODE FOR CARRYING OUT THE INVENTION

[1964] The present invention relates to a disaster prevention support app for an autonomous driving vehicle that is designed to enable a user to respond quickly and accurately in the event of a disaster. Hereinafter, an embodiment of the present invention will be described in detail.

[1965] 1. System Configuration

[1966] This system consists of a server, in-vehicle terminals, various sensors, and a network environment. The server manages user information, disaster information, emotional state, etc., and the in-vehicle terminals provide this information to the user.

[1967] 2. Server Roles

[1968] The server has the following roles:

[1969] User registration and basic information management

[1970] When a user enters basic information such as address and family composition, it is sent to a server and stored in a database. This information is used in emergency response.

[1971] Historical data collection and management

[1972] The system collects and stores users' past purchase and search history in a database, which then suggests individually optimized disaster prevention measures.

[1973] Collecting disaster information

[1974] It regularly checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information and stores it in a database.

[1975] Sentiment Analysis and Recommendations

[1976] It uses generative AI models such as TensorFlow to analyze the driver's emotional state in real time using cameras and microphones in the vehicle, and provides advice to reduce stress based on the analysis results.

[1977] 3. Role of terminals inside the vehicle

[1978] The terminals in the vehicles have the following functions:

[1979] Display of basic information and disaster prevention measures

[1980] Basic information and a list of disaster prevention measures sent from the server are displayed on the vehicle's infotainment system.

[1981] Collecting and transmitting emotional states

[1982] The vehicle's cameras and microphones collect the driver's facial expressions and voice, which are then sent to a server for use in an emotion analysis model.

[1983] Calculating and displaying evacuation routes

[1984] The system acquires current location information and sends it to a server. The server then calculates the optimal evacuation route based on this information and displays it on the vehicle's infotainment system. The route calculation is performed using Google Maps API and other tools.

[1985] 4. Hardware and Software Used

[1986] Specific hardware used includes in-vehicle cameras, microphones, GPS modules, and infotainment systems, while specific software used includes Python, TensorFlow (sentiment analysis), Open Data API (disaster information collection), Google Maps API (route calculation), and Django (server-side).

[1987] 5. Specific Examples

[1988] For example, imagine a driver gets into an autonomous vehicle and the system starts up. The driver's basic information, past search history, and purchase history are stored on a server. Suddenly, a disaster occurs, and the server collects the latest disaster information. A camera inside the vehicle captures the driver's facial expressions, and a TensorFlow model analyzes the driver's emotional state. If the system determines that the driver is anxious, it will advise them on how to relax and calculate and display the optimal evacuation route.

[1989] 6. Examples of prompts

[1990] Examples of specific prompts for an AI model include:

[1991] Prompt sentence for sentiment analysis model:

[1992] "Predict the driver's emotions from image and audio data and output one of the following: stress, tension, anxiety, or calm."

[1993] Prompt for disaster information acquisition:

[1994] "Get the following disaster information: type of disaster, location, evacuation shelter."

[1995] Prompt for evacuation route calculation:

[1996] "Calculate the next evacuation route. Starting point: {current_location}, Destination: {safe_place}."

[1997] As described above, the present invention takes into account the emotional state of the user and provides optimal disaster prevention measures and evacuation routes in real time, enabling a quick and safe response in the event of a disaster.

[1998] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1999] Program processing steps

[2000] Step 1:

[2001] The user inputs basic information such as address and family composition. The device sends the input basic information to the server and stores it in a database. The input includes the user's name, address, age, family composition, etc., and the output is the basic information stored in the database.

[2002] Step 2:

[2003] The system collects the user's past purchases of disaster prevention products and search history. The device sends this historical data to the server in real time and stores it in the server's database. The input is the user's purchase history and search history, and the output is an updated user profile.

[2004] Step 3:

[2005] The server periodically checks the local government's API and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in the server's database. The input is disaster information and evacuation shelter information obtained from the API, and the output is the latest information stored in the database.

[2006] Step 4:

[2007] The system uses cameras and microphones inside the vehicle to collect the driver's facial expressions and voice in real time. The device then sends this data to a server where it is analyzed by an emotion engine. The inputs are camera images and voice data, and the output is analyzed emotional state data.

[2008] Step 5:

[2009] The server uses an AI system to calculate optimal disaster prevention measures based on the collected basic information, historical data, disaster information, evacuation shelter information, and analyzed emotional states. This calculation is performed using a generative AI model such as TensorFlow. The inputs are basic information, historical data, disaster information, evacuation shelter information, and emotional states, and the output is a list of disaster prevention measures.

[2010] Step 6:

[2011] The server sends the generated disaster prevention measures list to the user's device and displays it on the vehicle's infotainment system. The user checks the list and takes specific disaster prevention measures. The input to this step is the generated disaster prevention measures list, and the output is a display and user actions.

[2012] Step 7:

[2013] The server obtains current location information from the device and compares it with the vehicle's GPS data to calculate the optimal evacuation route. The calculated evacuation route is sent to the device and displayed on the vehicle's infotainment system. The inputs are current location information, disaster information, and evacuation shelter information, and the optimal evacuation route is generated as the output.

[2014] Step 8:

[2015] The device provides voice and text advice to reduce stress based on the driver's emotional state, allowing the driver to evacuate safely while remaining relaxed. The input is the analyzed emotional state, and the output is the presentation of advice.

[2016] As described above, by dividing the process into multiple steps, users can be provided with prompt and appropriate disaster prevention measures and evacuation routes in the event of a disaster, and can also receive advice based on their emotional state.

[2017] 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.

[2018] 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.

[2019] 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.

[2020] [Fourth embodiment]

[2021] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2022] 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.

[2023] 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).

[2024] 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.

[2025] 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.

[2026] 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).

[2027] 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.

[2028] 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.

[2029] 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.

[2030] 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.

[2031] 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.

[2032] 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.

[2033] 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."

[2034] MODE FOR CARRYING OUT THE INVENTION

[2035] The "Easy Disaster Prevention Response App" of the present invention is a system designed to enable users to easily and efficiently take disaster countermeasures. A detailed embodiment of this system will be described.

[2036] 1. User registration and basic information entry

[2037] First, the user downloads and installs the app. When the app is launched for the first time, a user information entry screen appears, where the user enters basic information such as name, address, age, and family composition. The device then sends this basic information to the server, which then stores it in a database.

[2038] 2. Collection of purchase and search history

[2039] When a user searches for or purchases disaster preparedness products within the app, the device collects the search query and purchase history in real time and sends it to the server, which stores this data in a database and updates the user's profile.

[2040] 3. Collecting disaster and evacuation shelter information

[2041] The server periodically checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information. This information is stored in a database and used to create customized suggestions for each user.

[2042] 4. Proposal of disaster prevention measures

[2043] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the AI ​​system to calculate optimal disaster prevention measures. The proposed disaster prevention measures list is stored in a database and sent to the user's device, where it is displayed for the user to review.

[2044] 5. Shopping function

[2045] When the user checks the proposed disaster prevention measures list and adds the necessary items to the cart, the device sends the list of items they wish to purchase to the server. The server checks the inventory status and processes the payment. A notification of purchase completion is sent to the user's device, along with delivery information.

[2046] 6. Disaster prevention map and route guidance

[2047] When a user uses the disaster prevention map function, the device obtains current location information and sends it to the server. The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route. The calculation results are sent to the device, and the user can check the evacuation route and disaster prevention map. If necessary, this information can also be printed out on a copy machine at a convenience store.

[2048] Specific examples

[2049] For example, a user living in Shibuya Ward launches the app and attempts to check new disaster prevention measures. Based on basic information entered by the user, such as their address and family composition, the AI ​​system suggests optimal disaster prevention measures. This list includes items such as "three days' worth of water," "emergency food," and "portable toilets." The user adds the suggested items to their cart and completes the purchase process. The system then displays a route to the nearest evacuation shelter, allowing for smooth evacuation in the event of a disaster. The user can also print out the necessary disaster prevention and evacuation shelter information using a copy machine at a convenience store.

[2050] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures.

[2051] The processing flow will be explained below.

[2052] User registration and basic information entry

[2053] Step 1:

[2054] The user installs the app and accesses the user information input screen when launching it for the first time.

[2055] Step 2:

[2056] The user enters basic information such as name, address, age, and family composition.

[2057] Step 3:

[2058] The device generates an API request to send the basic information entered to the server.

[2059] Step 4:

[2060] The server stores the received information in a database.

[2061] Step 5:

[2062] After the server has completed the storage, it generates a registration confirmation message and sends it to the terminal.

[2063] Collection of purchase and search history

[2064] Step 1:

[2065] A user searches for disaster preparedness products within the app.

[2066] Step 2:

[2067] The device sends a search query to the server.

[2068] Step 3:

[2069] The user adds the product they like to the cart and completes the purchase.

[2070] Step 4:

[2071] The device sends purchase history and cart information to the server.

[2072] Step 5:

[2073] The server stores your search and purchase history in a database.

[2074] Collecting disaster and evacuation shelter information

[2075] Step 1:

[2076] The server periodically queries local government APIs and various public data sources to collect the latest disaster and evacuation shelter information.

[2077] Step 2:

[2078] The server stores the collected data in a database and formats the relevant information.

[2079] Disaster prevention measures proposals

[2080] Step 1:

[2081] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the AI ​​system and calculates the optimal disaster prevention measures.

[2082] Step 2:

[2083] The server generates a list of proposed disaster prevention measures and stores it in a database.

[2084] Step 3:

[2085] The server generates a response to send the generated list to the user's terminal.

[2086] Step 4:

[2087] The device displays a list of disaster prevention measures to the user and provides an interface where the user can check the proposed measures.

[2088] Shopping feature

[2089] Step 1:

[2090] The user checks the disaster preparedness list and adds the necessary items to the cart.

[2091] Step 2:

[2092] The device generates an API request to send the list of products desired for purchase to the server.

[2093] Step 3:

[2094] Based on the product list received by the server, the server checks stock status and price information and processes the payment.

[2095] Step 4:

[2096] The server generates a purchase confirmation message and sends it to the user's terminal.

[2097] Step 5:

[2098] The terminal displays a notification to the user that the purchase is complete and displays product delivery information.

[2099] Disaster prevention map and route guidance

[2100] Step 1:

[2101] The user opens the disaster prevention map function within the app.

[2102] Step 2:

[2103] The device obtains the user's current location information and generates an API request to send to the server.

[2104] Step 3:

[2105] The server compares the current location information with the local government's evacuation shelter information and calculates the optimal evacuation route.

[2106] Step 4:

[2107] The server generates a response including the calculated route information and sends it to the terminal.

[2108] Step 5:

[2109] The device displays evacuation routes and disaster prevention maps to the user and provides voice guidance.

[2110] Step 6:

[2111] Users can print out disaster prevention information and evacuation shelter information as needed using a copy machine at a convenience store.

[2112] Example 1

[2113] 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."

[2114] Disaster prevention measures are becoming increasingly important in modern society, and individual users are being asked to take appropriate measures quickly and efficiently. However, currently available disaster prevention applications and tools do not fully utilize individual user information, making it difficult to propose optimal disaster prevention measures to users. Furthermore, there are issues with the accuracy and timeliness of collecting disaster and evacuation shelter information and presenting optimal evacuation routes. For this reason, there is a demand for disaster response systems that are easy for users to use and offer advanced functions.

[2115] 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.

[2116] In this invention, the server includes: means for a user to input basic information such as place of residence and family composition; means for transmitting the input basic information to the server and storing it in a data management device; means for collecting the user's past purchase history and search history and storing it in the data management device; means for automatically collecting disaster information and evacuation shelter information from local governments and storing it in the data management device; means for a generative AI model to propose optimal disaster prevention measures based on the stored information; means for displaying a list of the proposed disaster prevention measures on the user's connected device; means for the user to acquire current location information from the screen of the connected device and send it to the server; means for the server to compare the current location information with the evacuation shelter information and calculate the optimal evacuation route; and means for transmitting the calculation results to the connected device and displaying them. This allows users to quickly and effectively check and prepare individually optimized disaster prevention measures and take appropriate evacuation actions in the event of a disaster.

[2117] "User" refers to an individual who uses this system to manage disaster prevention measures and evacuation actions.

[2118] "Basic information" refers to personal data entered by the user, such as place of residence, family composition, age, and gender.

[2119] "Server" refers to an online computer system that receives, processes, and stores data sent by users.

[2120] A "data management device" refers to a system that is connected to a server and includes a database for storing and managing basic user information, purchase history, search history, disaster information, and the like.

[2121] "Purchase history" refers to a record of disaster prevention related products and the like that a user has purchased in the past.

[2122] "Search History" refers to a record of queries or items that a User has searched for within an Application.

[2123] "Disaster information" refers to data on the occurrence, intensity, and scope of impact of a disaster.

[2124] "Shelter information" refers to data provided by local governments regarding the location, capacity, and facility status of shelters.

[2125] A "generative AI model" refers to a system that uses artificial intelligence technology to suggest optimal disaster prevention measures to users.

[2126] "Disaster prevention measures list" refers to a list of disaster prevention measures optimized for the user proposed by the generative AI model.

[2127] "Connection device" refers to a terminal device (smartphone, tablet, PC, etc.) that a user uses to connect to a server.

[2128] "E-commerce function" refers to the function that allows users to select and purchase suggested disaster prevention related products online.

[2129] "Current location information" refers to location information (such as GPS data) acquired by the user's device.

[2130] An "evacuation route" refers to a route that allows a user to travel safely and quickly to the nearest evacuation shelter in the event of a disaster.

[2131] A "disaster prevention map" refers to a map that visually displays information related to disaster prevention, such as evacuation routes and the locations of evacuation shelters.

[2132] The "Easy Disaster Prevention App" of the present invention is a system designed to enable users to take disaster countermeasures quickly and efficiently. This system has functions such as user registration and basic information input, collection of purchase history and search history, collection of disaster information and evacuation shelter information, disaster prevention measures proposals, shopping function, disaster prevention map and route guidance, etc.

[2133] Hardware and Software Details

[2134] server:

[2135] It is an online server equipped with a data management device for storing and processing information. It uses MySQL or PostgreSQL as its database.

[2136] As an AI system, we use a generative AI model (e.g., OpenAI's GPT).

[2137] Run a script that periodically collects information from the city's APIs and public data sources.

[2138] Device:

[2139] This refers to devices such as smartphones, tablets, and PCs on which users install applications.

[2140] Search queries and purchase history are collected in real time and sent to the server.

[2141] User:

[2142] This is an individual who downloads and installs the app and enters basic information.

[2143] Review the proposed disaster prevention measures and purchase the necessary items.

[2144] Program processing flow

[2145] 1. User registration and basic information entry

[2146] Device: The user downloads and installs the app and enters basic information the first time they launch it.

[2147] Terminal: Sends the entered information to the server as an HTTP request.

[2148] Server: Stores the received user information in a database.

[2149] 2. Collection of purchase and search history

[2150] Device: Every time a user searches for or purchases a disaster prevention product, the data is collected in real time and sent to the server.

[2151] Server: Stores the received data and updates the user's profile.

[2152] 3. Collecting disaster and evacuation shelter information

[2153] Server: Automatically checks local government APIs and public data sources, and stores the latest disaster and evacuation shelter information in a database.

[2154] 4. Proposal of disaster prevention measures

[2155] Server: Inputs the user's basic information, historical data, and disaster information into the generative AI model and calculates optimal disaster prevention measures.

[2156] Generative AI model: Generates a disaster prevention measures list based on input information.

[2157] Server: Sends the generated list to the device.

[2158] Device: Display the list in the user interface so that the user can see it.

[2159] 5. Shopping function

[2160] User: Selects an item from the list of suggested disaster preparedness measures and adds it to their cart.

[2161] Terminal: Sends cart information to the server.

[2162] Server: After checking the stock, the purchase is processed through the payment system.

[2163] Server: Sends a notification of purchase completion and shipping information to the device.

[2164] 6. Disaster prevention map and route guidance

[2165] User: Use the disaster prevention map function to obtain current location information.

[2166] Device: Sends current location information to the server.

[2167] Server: Compares with evacuation shelter information and calculates the optimal evacuation route.

[2168] Server: Sends the calculation results to the terminal.

[2169] Terminal: Displays disaster prevention maps and evacuation routes.

[2170] Specific examples

[2171] For example, consider the case where a user living in Shibuya Ward launches the app and checks new disaster prevention measures.

[2172] 1. User: Launches the app and enters basic information such as name, address, and family composition.

[2173] 2. Terminal: Sends information to the server.

[2174] 3. Server: Stores the input information in a database and inputs the data into the AI ​​system to calculate disaster prevention measures.

[2175] 4. Generative AI model: Generates a list of disaster prevention measures such as "three days' worth of water," "emergency food," and "portable toilet."

[2176] 5. Server: Sends the list to the terminal and displays it for the user to review.

[2177] 6. User: Adds the desired items to the cart and checks out.

[2178] 7. Server: Once the payment process is complete, a notification of purchase completion and delivery information is sent to the terminal.

[2179] 8. User: Check the route to the nearest evacuation shelter and use the disaster prevention map. If necessary, this information can be printed out on a copy machine at a convenience store.

[2180] Prompt Sentence Examples

[2181] For example, the following prompt sentence can be input to a generative AI model to generate a list of disaster prevention measures:

[2182] "A single man in his 30s living in Shibuya Ward wants to check his disaster preparedness. Please make a list of the best disaster preparedness measures for him."

[2183] In this way, by using the system of the present invention, users can quickly and easily check and prepare individually optimized disaster prevention measures.

[2184] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2185] Step 1:

[2186] User registration and basic information entry

[2187] The user downloads and installs the app.

[2188] Enter: Install app

[2189] Output: App ready to launch

[2190] How it works: Download the app from the app store (Google Play or Apple App Store) and install it.

[2191] When the user starts the app for the first time, they enter basic information (place of residence, family composition, etc.).

[2192] Input: User's basic information (name, address, age, family composition, etc.)

[2193] Output: Local storage of input information

[2194] How it works: Launch the installed app and follow the on-screen instructions to enter your basic information.

[2195] The terminal sends the entered basic information to the server as an HTTP request.

[2196] Input: Basic information entered by the user

[2197] Output: Data transmission to server begins

[2198] How it works: When you press the send button in the app, the information is sent to the server.

[2199] The server stores the received user information in a database.

[2200] Input: User information sent from the device

[2201] Output: Information saved to database

[2202] What happens: A script is executed on the server side to save the data to the database.

[2203] Step 2:

[2204] Collection of purchase and search history

[2205] The device collects information in real time when a user searches for or purchases disaster prevention products.

[2206] Input: User search queries, purchase history

[2207] Output: Recorded to local cache

[2208] How it works: Temporarily stores data when users search for and purchase products.

[2209] The terminal transmits the collected data to the server.

[2210] Input: Collected search queries, purchase history

[2211] Output: Data sent to server completed

[2212] Operation: Collected data is sent to the server periodically or when an event occurs.

[2213] The server stores the received data in a database and updates the user profile.

[2214] Input: Search queries sent from the device, purchase history

[2215] Output: Saved to database and user profile updated

[2216] What it does: Saves the data in the database and keeps each user's profile up to date.

[2217] Step 3:

[2218] Collecting disaster and evacuation shelter information

[2219] The server regularly checks local government APIs and public data sources to collect the latest disaster and evacuation shelter information.

[2220] Input: API calls and public data access

[2221] Output: Latest disaster information, evacuation shelter information

[2222] What it does: Runs a script periodically and calls an API to retrieve data.

[2223] The server stores the collected information in a database.

[2224] Input: Collected disaster information, evacuation shelter information

[2225] Output: Information saved to database

[2226] Behavior: Store in a database and make it accessible to other functions.

[2227] Step 4:

[2228] Disaster prevention measures proposals

[2229] The server inputs the user's basic information, purchase history, search history, and local government disaster information into the generated AI model.

[2230] Input: User basic information, history data, disaster information

[2231] Output: Input to generative AI model completed

[2232] How it works: Preprocesses a dataset to feed into a generative AI model.

[2233] A generative AI model calculates and suggests a list of disaster prevention measures.

[2234] Input: Generated dataset

[2235] Output: List of optimal disaster prevention measures

[2236] How it works: A generative AI model processes data and generates a list of suggestions.

[2237] The server stores the proposed list in a database and sends it to the terminal.

[2238] Input: A list of disaster prevention measures from a generative AI model

[2239] Output: Saved to database, sent to terminal

[2240] Behavior: Save in database and send to user's device.

[2241] The terminal displays the received list on the user interface.

[2242] Input: Disaster prevention measures list sent from the server

[2243] Output: Displayed on the user interface

[2244] Behavior: Display on screen so the user can see it.

[2245] Step 5:

[2246] Shopping feature

[2247] The user selects an item from the list of suggested disaster prevention measures and adds it to the cart.

[2248] Input: User selection of product

[2249] Output: List of items added to cart

[2250] What happens: A user selects a product's checkbox and clicks the Add to Cart button.

[2251] The terminal transmits the cart information to the server.

[2252] Input: List of items added to cart

[2253] Output: Sending to server completed

[2254] What it does: Sends cart information to the server as an HTTP request.

[2255] The server checks the stock status and completes the purchase process through the payment system.

[2256] Input: Cart information

[2257] Output: Inventory check and payment processing completed

[2258] Operation: Check inventory and process payments using a back-end system (e.g., an e-commerce system).

[2259] The server sends a notification of purchase completion and delivery information to the user's terminal.

[2260] Input: Payment processing result

[2261] output: Notification and delivery information sent

[2262] Operation: After payment is completed, payment results and delivery information are sent to the terminal.

[2263] Step 6:

[2264] Disaster prevention map and route guidance

[2265] The user uses the disaster prevention map function to obtain current location information.

[2266] Input: User's current location (GPS information)

[2267] Output: Current location information acquisition completed

[2268] What it does: Click a button in the app to enable location tracking.

[2269] The device sends the current location information to the server.

[2270] Input: Acquired GPS information

[2271] Output: Sending to server completed

[2272] What it does: Sends your current location to the server as an HTTP request.

[2273] The server compares the current location information with the evacuation shelter information and calculates the optimal evacuation route.

[2274] Input: Current location information, evacuation shelter information

[2275] Output: Optimal evacuation route

[2276] How it works: It retrieves the necessary information from a database and uses an algorithm to calculate the optimal evacuation route.

[2277] The server sends the calculation results to the terminal.

[2278] Input: Calculated evacuation route

[2279] Output: Sent to terminal

[2280] Operation: Sends an evacuation route to the device as an HTTP response.

[2281] The evacuation route and disaster prevention map received by the terminal are displayed on the user interface.

[2282] Input: Evacuation route sent from the server

[2283] Output: Displayed on the user interface

[2284] Operation: Disaster prevention maps and evacuation routes are displayed on the screen so that users can check them.

[2285] (Application example 1)

[2286] 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."

[2287] Until now, there have been limited means of swift and efficient evacuation and delivery of emergency supplies during disasters. Furthermore, few systems existed that considered individual purchase and search histories to provide optimal disaster prevention measures, placing a heavy burden on users. Furthermore, systems lacked the ability to obtain real-time information on available evacuation sites and calculate evacuation routes. This made it difficult for many people to respond quickly and efficiently during disasters. A new system was needed to solve this problem.

[2288] 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.

[2289] In this invention, the server includes: means for a user to input basic information such as address and family composition; means for transmitting the input basic information to the server and storing it in a database; means for collecting the user's past purchase history and search history and storing it in a database; means for collecting disaster information and evacuation site information from public institutions and storing it in a database; means for an AI system to propose optimal disaster prevention measures based on the stored information; means for displaying a list of the proposed disaster prevention measures on the user's processing device; means for an autonomous vehicle to calculate an optimal evacuation route in the event of a disaster and transport the user to the optimal evacuation site; means for calculating a delivery route for disaster prevention supplies based on the user's disaster prevention plan list and quickly delivering the supplies; and means for checking the availability of evacuation sites in real time and notifying the user. This enables fast and efficient evacuation and delivery of emergency supplies.

[2290] "Address" refers to the specific area or place where a user resides.

[2291] "Family structure" refers to the composition of members in the user's household, including, for example, parents, children, spouse, etc.

[2292] "Basic information" refers to key data about the user, including address, family composition, date of birth, etc.

[2293] A "server" is a computing device that processes and stores data over a network.

[2294] A "database" is a collection of electronic information that is systematically organized and stored, and that can be easily searched and updated.

[2295] "Purchase history" refers to a record of products purchased by a user in the past.

[2296] "Search history" refers to a record of searches a user has conducted in the past.

[2297] "Public institutions" refer to organizations that function for the public, such as national and local governments.

[2298] "Disaster information" refers to information related to natural disasters such as earthquakes, typhoons, and floods.

[2299] "Evacuation site information" refers to information about places where people should evacuate to ensure their safety in the event of a disaster.

[2300] An "artificial intelligence system" refers to a technological system that analyzes data and learns to make human-like judgments and predictions.

[2301] "Disaster prevention measures" refer to preventive and response measures taken in preparation for the occurrence of a disaster.

[2302] "Processing device" refers to a device for processing data, and primarily includes computers and smartphones.

[2303] An "autonomous vehicle" is a vehicle that has the ability to drive itself without driver intervention.

[2304] An "evacuation route" refers to a route to a safe location in the event of a disaster.

[2305] "Disaster prevention supplies" refer to supplies needed in the event of a disaster, such as disaster prevention equipment and emergency food.

[2306] "Delivery route" refers to the route along which goods are delivered.

[2307] "Real-time confirmation" refers to checking information immediately without delay.

[2308] MODE FOR CARRYING OUT THE INVENTION

[2309] The present invention is a system for realizing rapid evacuation and delivery of emergency supplies in the event of a disaster, and provides functions for proposing evacuation routes and delivering disaster prevention supplies using autonomous vehicles. Specific embodiments of the system are described below.

[2310] User registration and basic information entry

[2311] Users first download and install a dedicated application onto their smartphone or tablet. After installation, they launch the application and a screen appears where they can enter basic information such as their address and family composition. The basic information entered by the user is sent to the server and stored in a database.

[2312] Collection of purchase and search history

[2313] When a user searches for or purchases disaster prevention-related products within the application, their search queries and purchase history are automatically collected and sent to the server, where they are stored in a database and their individual profile is updated.

[2314] Collecting disaster information and evacuation site information

[2315] The server periodically checks APIs provided by public institutions and public data sources to collect the latest disaster information and evacuation site information. This information is also stored in a database and used as material for disaster prevention measures customized for each user.

[2316] Disaster prevention measures proposals

[2317] The server inputs the user's basic information, purchase history, search history, and disaster information from public institutions into an AI system to calculate optimal disaster prevention measures. The proposed disaster prevention measures list is stored in a database and sent to the user's device. The user can view this list on the application.

[2318] Emergency evacuation route suggestions

[2319] When a disaster occurs, if a user gets into an autonomous vehicle, the vehicle uses a GPS device to acquire the user's current location information. The server calculates the optimal evacuation route based on the disaster information and the current location information and sends it to the autonomous vehicle. The vehicle then automatically transports the user to the optimal evacuation location according to this route.

[2320] Delivery of emergency supplies

[2321] Based on the user's disaster prevention plan, the server calculates the optimal delivery route for emergency supplies. The supplies are quickly delivered to the user's address by autonomous vehicles from the disaster prevention center. The server tracks the delivery status in real time and notifies the user.

[2322] Displaying evacuation shelter availability information

[2323] The server checks the availability of evacuation shelters in real time and sends that information to the user's device, where the user can check the availability of evacuation shelters on the application.

[2324] Hardware and software used

[2325] The system requires a server, a GPS device, an autonomous vehicle, a smartphone, and an internet connection. The software includes a dedicated application and an API for collecting disaster information. It also uses an artificial intelligence model for data analysis and recommendations.

[2326] Specific examples

[2327] For example, if a user lives in a certain area of ​​Tokyo and a disaster occurs, an autonomous vehicle will calculate an evacuation route and automatically drive to a safe evacuation site. Also, if a user purchases emergency food and water using a disaster prevention app, the autonomous vehicle will quickly deliver these supplies to the specified address in the event of an emergency.

[2328] Prompt Sentence Examples

[2329] Calculating the best evacuation route in case of a disaster: "Calculate the best route from your current location to a safe evacuation location."

[2330] Emergency supply delivery route calculation: "Calculate the delivery route from the disaster prevention center to a specified address."

[2331] Get information on available evacuation shelters: "Get the latest information on available evacuation shelters."

[2332] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2333] Step 1:

[2334] The user installs a dedicated application and enters basic information such as address and family composition.

[2335] (Input) Basic information entered by the user (address, family composition, age, etc.).

[2336] (Processing) The terminal sends the entered basic information to the server and stores it in the database.

[2337] (Output) Basic information saved in the database.

[2338] Step 2:

[2339] When users search for or purchase disaster prevention-related products within the app, that information is collected.

[2340] (Input) User search queries and purchase history.

[2341] The (processing) terminal sends this information to the server in real time and stores it in a database.

[2342] (Output) Purchase history and search history are saved in the database.

[2343] Step 3:

[2344] The server collects the latest disaster information and evacuation site information from public APIs and public data sources.

[2345] (Input) Data feeds from public APIs and public data sources.

[2346] (Processing) The server periodically calls the API and stores the retrieved information in a database.

[2347] (Output) The latest disaster information and evacuation location information is saved in the database.

[2348] Step 4:

[2349] Based on the stored information, an artificial intelligence system calculates the optimal disaster prevention measures.

[2350] (Input) User's basic information, purchase history, search history, and latest disaster information.

[2351] The (processing) server inputs this information into an artificial intelligence model to calculate the optimal disaster prevention measures.

[2352] (Output) A list of proposed disaster prevention measures.

[2353] Step 5:

[2354] A list of proposed disaster prevention measures is displayed on the user's terminal.

[2355] (Input) Disaster prevention measures list sent from the server.

[2356] (Processing) The list received by the terminal is displayed on the application interface.

[2357] (Output) A display screen that the user can see.

[2358] Step 6:

[2359] When a disaster occurs, autonomous vehicles acquire information about the user's current location and calculate evacuation routes.

[2360] (Input) User's current location information (GPS data).

[2361] (Processing) The server calculates the optimal evacuation route based on the current location information and disaster information, and sends it to the autonomous vehicle.

[2362] (Output) An evacuation route is calculated and directed to the autonomous vehicle.

[2363] Step 7:

[2364] The system calculates delivery routes for emergency supplies based on the user's disaster prevention plan list, and delivers the supplies quickly.

[2365] (Input) User's disaster prevention plan list and disaster prevention goods delivery base information.

[2366] (Processing) The server calculates a delivery route based on this information and gives instructions to the autonomous vehicle.

[2367] (Output) A supply delivery route is calculated and directed to the autonomous vehicle.

[2368] Step 8: ...

Claims

1. A means for users to enter basic information such as address and family composition; A means for transmitting the input basic information to a server and storing it in a database; A means for collecting and storing users' past purchase and search histories in a database; A means of collecting disaster information and evacuation shelter information from local governments and storing it in a database, Based on the stored information, the AI ​​system will propose optimal disaster prevention measures. and means for displaying the list of proposed disaster prevention measures on a user's terminal.

2. The system according to claim 1 , further comprising means for providing a shopping function for a user to select and purchase necessary disaster prevention products.

3. 2. The system according to claim 1, further comprising means for acquiring information on the user's current location, calculating a route to the nearest evacuation shelter, and displaying and providing guidance on a disaster prevention map.

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