System

Abstract

A system is provided.SOLUTION: A system for providing accurate information in a disaster area, comprising: terminal means for connecting to a network via a satellite; server means for receiving and analyzing data transmitted from said terminal means; generating means for generating accurate information based on the data analyzed by said server means; and information providing means for providing the generated information to a 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] Internet connections are often cut off in disaster-stricken areas, making it difficult to disseminate accurate information. In particular, even major media outlets sometimes circulate inaccurate information, making it difficult for victims to obtain accurate information and causing confusion. Therefore, a system that allows victims to obtain reliable information quickly and accurately is needed. [Means for solving the problem]

[0005] The system of the present invention includes terminal means connected to a network via satellite, server means for receiving and analyzing data transmitted from the terminal means, generation means for generating accurate information based on the data analyzed by the server means, and information provision means for providing the generated information to users. This allows accurate information to be provided quickly in disaster-stricken areas, enabling victims to obtain the information they need in real time. For example, the terminal means is installed at an evacuation shelter and collects input data from users, and the server means analyzes and cross-checks the data to generate accurate and consistent information. Furthermore, since this information is provided to users via the terminals, it becomes possible to bridge information between disaster-stricken areas and the rest of the country.

[0006] "Terminal means" refers to a device that connects to a network via satellite and collects input data and sensor information from users.

[0007] The "server means" is a central processing unit for receiving and analyzing data sent from the terminal means.

[0008] The "generation means" refers to software or algorithms for generating accurate information based on the data analyzed by the server means.

[0009] The "information providing means" refers to a display or communication device for providing the information generated by the generating means to the user.

[0010] "Users" are individuals and organizations that use terminal means to collect and input information in the disaster area.

[0011] A "disaster area" is an area that has been affected by a natural or man-made disaster.

[0012] An "evacuation shelter" is a facility set up for disaster victims to take temporary refuge.

[0013] "Data integrity" is the process or state of verifying that information sent by multiple users is consistent.

[0014] A "cross-checking method" is a process or function that compares and checks multiple pieces of data to ensure data consistency. [Brief explanation of the drawings]

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

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

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

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

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

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

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

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

[0023] [First embodiment]

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

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

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

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

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

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

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

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

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

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

[0036] The system according to the present invention is intended to provide accurate information in disaster areas, and is mainly implemented in the following form.

[0037] First, the system includes a terminal that connects to the network via satellite, a server that receives and analyzes data sent from the terminal, a generation AI that generates accurate information based on the analyzed data, and an information provision means that provides the generated information to users.

[0038] Device role and operation

[0039] Terminal

[0040] The terminals are installed in disaster-stricken areas, such as evacuation centers, and are connected to the Internet via satellite. They are equipped with sensors and cameras to collect real-time data such as temperature, humidity, and damage status. They also collect information entered by users (e.g., the status of evacuation centers, food shortages, etc.).

[0041] Server Roles and Operations

[0042] server

[0043] The server receives the data sent from the devices and analyzes it using the generating AI. Specifically, the server checks the integrity of the data and cross-checks information from multiple devices to increase reliability. For example, if the same information is sent from multiple evacuation centers, it will determine that the information is accurate.

[0044] Role and behavior of generative AI

[0045] Generation AI

[0046] The AI ​​generates accurate and reliable information based on the data analyzed by the server. For example, if the information that "a certain evacuation shelter is short of food" is confirmed by cross-checking, the AI ​​creates a specific message saying, "There is a food shortage at this evacuation shelter."

[0047] Roles and operations of information provision means

[0048] Information provision means

[0049] The information provided by the AI ​​is presented to users via a variety of methods, including displaying information on the evacuation center's screen, allowing users to obtain accurate information in real time. Information can also be provided via voice notifications and push notifications to mobile devices.

[0050] Specific examples

[0051] 1. Setting up the shelter

[0052] Terminals are installed in evacuation centers and connected to a satellite network. They use sensors and cameras to collect information about the surrounding environment (temperature, humidity, population, damage, etc.).

[0053] 2. User input

[0054] The user types "There is a food shortage at the evacuation center" into the device, and the information is sent from the device to the server.

[0055] 3. Data analysis and information generation

[0056] The server analyzes the received data and cross-checks multiple similar reports. The generator AI generates an accurate message based on the information that "food is in short supply."

[0057] 4. Provision of Information

[0058] The generated information is displayed on the device's screen, and users at the evacuation center are notified with messages such as, "There is a food shortage. We are arranging relief supplies based on this information."

[0059] This system allows disaster victims to quickly and accurately obtain the information they need. For example, if there is a shortage of food or relief supplies, or if local traffic information is needed, the system will respond appropriately in real time. This will minimize confusion in the disaster-stricken areas and support effective relief efforts.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] Terminal

[0063] The terminal is installed in the evacuation center and connects to the network via satellite. At this time, the terminal is supplied with power and basic settings (location information, basic information about the evacuation center, etc.) are configured. The sensors and cameras are activated and begin collecting environmental data about the evacuation center (temperature, humidity, images, etc.).

[0064] Step 2:

[0065] User

[0066] Users input the status of the evacuation shelter into the device. Specifically, they use the device's touch panel or voice input function to report information such as "food is in short supply" or "the toilets are out of order." The device temporarily stores this user-entered data.

[0067] Step 3:

[0068] Terminal

[0069] The terminal formats the collected environmental data and user-input data and transmits it to the server via satellite communication. At this time, it checks whether the data was transmitted correctly and attempts to retransmit it if an error occurs.

[0070] Step 4:

[0071] server

[0072] The server receives data sent from the devices. It passes the received data to the generation AI, which begins analyzing it. It cross-checks similar information sent from multiple devices to confirm the consistency and reliability of the data. For example, if information that "food is running low" is sent from multiple evacuation centers, it will match this information.

[0073] Step 5:

[0074] Server (Generating AI)

[0075] The AI ​​then generates accurate information based on the cross-checked data. For example, if a report is confirmed that "food is in short supply at shelters A, B, and C," the AI ​​generates a specific message saying, "There is a food shortage at these shelters."

[0076] Step 6:

[0077] Information provision means

[0078] The generated information is sent from the server to the device and displayed on the device's display. It can also be provided to the user as a voice notification or a push notification to the mobile device, as needed. For example, a message such as "There is a food shortage. We are currently arranging relief supplies based on this information" can be displayed.

[0079] Step 7:

[0080] server

[0081] The server periodically receives and analyzes new data and updates the information. Every time new data is sent, the generating AI reanalyzes it and updates the information based on the latest state. The updated information is then sent back to the device, and the display is updated in real time.

[0082] This process will enable accurate information to be provided at evacuation centers in disaster-stricken areas, enabling support activities to be carried out quickly and effectively.

[0083] Example 1

[0084] 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."

[0085] In disaster-stricken areas, it was difficult to quickly and accurately collect information and provide it to victims with reliable information, which led to delays in relief efforts and confusion over information, resulting in victims not receiving the support they needed in a timely manner.

[0086] 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.

[0087] In this invention, the server includes a terminal means, a means for receiving and analyzing sensor and user input data, a generating AI model means for generating highly reliable information, and a means for displaying or announcing the generated information, thereby enabling the rapid provision of highly reliable information based on data collected in disaster areas.

[0088] "Disaster area" refers to an area that has been affected by a natural or man-made disaster.

[0089] A "satellite network" refers to a network system that provides internet and communication services via artificial satellites.

[0090] "Terminal means" refers to electronic devices that are installed in the disaster area and that collect and transmit data.

[0091] "Server means" refers to a computer system for receiving and analyzing data sent from terminal means.

[0092] "Sensor" refers to a device that measures environmental data such as temperature and humidity.

[0093] "User-input data" refers to information provided by a User through a Terminal.

[0094] "Generative AI model" refers to an artificial intelligence model that generates reliable information based on data analyzed by a server means.

[0095] "Cross-checking measures" refers to the process of collating information from multiple data sources and assessing its consistency and reliability.

[0096] "Information providing means" refers to a device or method for notifying the user of the generated information.

[0097] "Display" refers to a device that visually displays generated information.

[0098] "Audio notification" refers to a means of conveying generated information to the user audibly.

[0099] "Data analysis means" refers to the server's function of verifying the integrity of collected data and performing any necessary cleansing or cross-checking.

[0100] "Cellular terminal" refers to a mobile device such as a mobile phone or smartphone.

[0101] This invention is a system for providing rapid and accurate information in disaster-stricken areas, and is mainly composed of terminal means, server means, generation AI model means, and information provision means. The specific operation and implementation method of each means will be explained below.

[0102] Terminal means

[0103] The terminal means is an electronic device installed in evacuation shelters in disaster areas and connected to the Internet via a satellite network. This terminal is equipped with sensors to collect environmental data such as temperature and humidity, and a camera to capture images of the damage. It also provides an interface for users to input information about the evacuation shelter situation and shortages of supplies.

[0104] As a specific example of use, a terminal means is installed in a shelter and collects information on the surrounding situation in real time using sensors and cameras. Furthermore, when a user inputs "There is a shortage of food at the shelter," this information is recorded in the terminal means. The terminal means packages this data and transmits it to the server means in the next phase.

[0105] Server Means

[0106] The server means is a computer system that receives and analyzes data sent from the terminal means. First, it checks the integrity of the received data and performs data cleansing if there are missing or invalid values. Then it cross-checks the same type of data sent from multiple terminals and evaluates its reliability. For example, if the same information is reported from multiple evacuation shelters, it is determined that the information is accurate.

[0107] The server means stores the received data in a database and then prepares to provide the data to the generative AI model means.

[0108] Generative AI model means

[0109] The generating AI model means is an artificial intelligence model that generates reliable information based on the data analyzed by the server means. The AI ​​model receives the analyzed data as input and generates a specific and reliable message. For example, it creates a notification message such as "There is a food shortage. Based on this information, relief supplies are being arranged."

[0110] Information provision means

[0111] The information provision means plays a role in providing the information generated by the generative AI model means to the user. The information is displayed on the display of the terminal means so that the user can obtain accurate information in real time. The information can also be provided in multiple ways, such as voice notification or push notification to the mobile device.

[0112] Specific examples

[0113] 1. Setting up the shelter

[0114] Terminal devices are installed in evacuation centers and connected to a satellite network. They use sensors and cameras to collect information on the surrounding environment (temperature, humidity, population, damage status, etc.) in real time.

[0115] 2. User input

[0116] The user inputs "There is a shortage of food at the evacuation shelter" into the terminal means. The information is transmitted from the terminal means to the server means.

[0117] 3. Data analysis and information generation

[0118] The server means analyzes the received data and cross-checks multiple similar reports. The generative AI model means generates an accurate message based on the information that "food is in short supply."

[0119] 4. Provision of Information

[0120] The generated information is displayed on the terminal display, and users at the evacuation shelter are notified, such as, "There is a food shortage. We are arranging relief supplies based on this information." It is also possible to send voice notifications and push notifications to mobile devices.

[0121] Prompt Sentence Examples

[0122] 1. Prompt example 1

[0123] We have installed devices in evacuation shelters in the affected areas that use sensors and cameras to collect information on temperature, humidity, and damage. Please enter information on the evacuation shelter situation and food shortages.

[0124] 2. Prompt example 2

[0125] Based on the data collected on the device, the server analyzed and cross-checked the data. Based on this information, the AI ​​generated the message "Food is running low." Please check the generated notification content.

[0126] 3. Prompt example 3

[0127] Based on the above information, a notice was sent to the terminal displays at the evacuation center. Please check the status of food supply arrangements.

[0128] As described above, by having each means work in coordination, it becomes possible to provide disaster victims with quick and accurate information and provide effective support.

[0129] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0130] Step 1: Placement and connection of terminal means

[0131] Specific operation: The terminal means is installed at an evacuation shelter in the disaster area. A technician installs the terminal means and establishes an Internet connection using a satellite antenna.

[0132] Input: Information about evacuation shelters and their locations

[0133] Output: Internet connection established and terminal means operational

[0134] Step 2: Start the sensors and cameras

[0135] Specific operation: The system administrator remotely activates the sensors and cameras of the terminal device, which completes preparations for data collection.

[0136] Input: Sensor and camera initial configuration information

[0137] Output: Sensors and cameras are up and running and ready to collect data.

[0138] Step 3: Collect environmental data

[0139] Specific operation: The terminal device uses sensors to collect environmental data such as temperature, humidity, and population in real time, and also uses a camera to take photos of the damage situation and save the image data.

[0140] Input: Local environmental information of the evacuation shelter

[0141] Output: Collected environmental and image data

[0142] Step 4: User input

[0143] Specific operation: The user uses the input interface of the terminal means to input information such as "food shortage at the evacuation center." The terminal means records this information.

[0144] Input: User-entered shelter status information

[0145] Output: User input data recorded on the terminal means

[0146] Step 5: Packaging and preparing the data for transmission

[0147] Specific operation: The terminal means packages the collected environmental data and user input data into one data packet and prepares to send it to the server means.

[0148] Input: Collected environmental data and user-entered data

[0149] Output: Data packets ready to be sent

[0150] Step 6: Sending data to the server

[0151] Specific operation: The terminal means transmits data packets to the server means via satellite communication. The data is encrypted and transmitted.

[0152] Input: Data packet ready to send

[0153] Output: Data packets received by the server

[0154] Step 7: Receiving and storing data

[0155] Specific operation: The server means receives the data packets sent from the terminal means and stores them in a database for analysis.

[0156] Input: Data packets sent from the terminal means

[0157] Output: Saved data

[0158] Step 8: Data integrity check and cleansing

[0159] Specific operation: The server means checks the integrity of the data and performs data cleansing if there are missing or invalid values.

[0160] Input: Saved data

[0161] Output: Cleansed data with integrity checks

[0162] Step 9: Cross-check from multiple devices

[0163] Specific operation: The server means cross-checks the same type of data sent from different terminal means and evaluates its reliability. For example, if multiple evacuation centers report the same content, such as "food shortages," the information is judged to be accurate.

[0164] Input: Homogeneous data sent from multiple terminal means

[0165] Output: Data whose reliability has been assessed by cross-checking

[0166] Step 10: Generate information using generative AI models

[0167] Specific operation: The server executes the generative AI model based on the analyzed data to generate a reliable message, such as "There is a food shortage. Based on this information, we are arranging relief supplies."

[0168] Input: Data whose reliability has been assessed by cross-checking

[0169] Output: Highly reliable informational messages generated

[0170] Step 11: Prepare to distribute information

[0171] Specific operation: The server means assembles the generated information messages into packets for delivery and prepares them for transmission.

[0172] Input: Generated information message

[0173] Output: Data packets ready for delivery

[0174] Step 12: Sending information to the terminal means

[0175] Specific operation: The server means transmits a distribution data packet to the terminal means.

[0176] Input: Data packets ready for delivery

[0177] Output: Information received by terminal means

[0178] Step 13: Providing information through display and audio notifications

[0179] Specific operation: The terminal displays the received information on the display of the evacuation center, providing users with accurate information in real time, and also provides voice notifications as necessary.

[0180] Input: Information received by terminal means

[0181] Output: Information displayed on the screen and audio notifications

[0182] Step 14: Push notification to mobile device

[0183] Specific operation: The terminal means or the server means also sends a push notification to the mobile device, so that the user can check detailed information on their mobile device.

[0184] Input: Information generated by terminal or server means.

[0185] Output: Push notification received on mobile device

[0186] (Application example 1)

[0187] 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."

[0188] In conventional disaster response systems, information collection and provision is often not done in real time, making it difficult to provide victims with quick and accurate information. In addition, the means of providing information are limited, and a lack of adaptive evacuation information, especially in dangerous situations, has been a problem. This has led to the risk that victims are unable to take appropriate action, and the damage may worsen.

[0189] 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.

[0190] In this invention, the server includes a terminal means connected to the network via a satellite, a means for receiving and analyzing data transmitted from the terminal means, a generating means for generating accurate information based on the data analyzed by the server means, an information providing means using a smart device (including smart glasses) for providing the generated information to users, a cross-checking means for checking the consistency of data transmitted from multiple users, and an adaptive evacuation information providing means based on location information. This enables prompt and accurate information to be provided in disaster-stricken areas, allowing disaster victims to take appropriate action.

[0191] "Terminal means" refers to a device that connects to a network via satellite and collects data using sensors and cameras in the disaster area.

[0192] The "server means" is a server device that receives and analyzes data sent from the terminal means.

[0193] The "analysis means" is a means for verifying the consistency of received data in the server means and analyzing the data.

[0194] The "generation means" is a means for generating accurate information based on the analyzed data.

[0195] A "smart device" is a device that provides generated information to a user, and includes smart glasses and the like.

[0196] The "information providing means" is a means for providing the information generated by the generating means to the user.

[0197] A "cross-check means" is a means for checking the consistency of data sent from multiple users.

[0198] An "adaptive evacuation information provision means" is a means for providing users with optimal evacuation information in real time based on location information.

[0199] The system according to the present invention is for providing accurate information in real time in disaster areas, and is implemented in the following manner.

[0200] 1. Roles and operations of terminal means

[0201] The terminal means is installed in the disaster area and connected to the network via satellite. Specifically, it is a device installed in evacuation shelters and dangerous areas, and is equipped with sensors and cameras. This terminal collects the following data:

[0202] Temperature and humidity

[0203] Damage situation

[0204] Demographics

[0205] Users can use the terminal to input information such as the status of evacuation shelters and food shortages, which is then sent to the server.

[0206] 2. Roles and Operations of Server Means

[0207] The server means is a device that receives data sent from the terminal means and performs analysis processing. The server means processes the data using the following means:

[0208] Analysis method: Check the integrity of the received data and perform analysis.

[0209] Cross-checking measures: verifying the integrity of data submitted by multiple users.

[0210] Generation method: Generate accurate and reliable information based on the analyzed data.

[0211] Specifically, the server cross-checks the consistency of the data. For example, if multiple shelters report the same information, it determines that the information is accurate. As a result of this process, the generator generates specific information such as "food shortage."

[0212] 3. Roles and Functions of Information Provision Means

[0213] The information providing means is a device for providing the information generated by the generating means to the user. In particular, the present invention utilizes a smart device, such as smart glasses:

[0214] Smart glasses: Evacuation information and warnings are displayed on the screen, and voice notifications are also possible.

[0215] Location integration: Shows the nearest evacuation shelters and safe routes based on your current location.

[0216] Hardware / Software used

[0217] Hardware: Satellite-connected devices, smart glasses

[0218] Software: Cloud servers, analytical algorithms, generative AI (e.g., OpenAI's GPT model), speech synthesis engines (e.g., Google Text-to-Speech)

[0219] For example, the following prompts can be sent to the generative AI to provide real-time information:

[0220] Prompt Sentence Examples

[0221] "Disaster information: Earthquake occurred. Current location is city center. Please provide evacuation locations and safe routes."

[0222] Example

[0223] 1. Visual Indication:

[0224] The smart glasses' display read, "The nearest evacuation shelter is 500 meters north from your current location. Take the next right."

[0225] 2. Sound notification:

[0226] The smart glasses will play a voice notification saying, "An earthquake has occurred. Please evacuate immediately. Walk 500 meters to the right to reach the evacuation shelter."

[0227] This will enable disaster victims to take safe action based on prompt and accurate information, minimizing confusion in disaster-stricken areas and supporting effective relief efforts.

[0228] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0229] Step 1:

[0230] Data collection and transmission

[0231] Subject: Terminal

[0232] The device uses sensors and cameras installed in the affected area to collect data such as temperature, humidity, and damage status. It also collects information entered by the user, such as the status of evacuation shelters and food shortages. This data is collected in real time and sent to a server via satellite communication.

[0233] Input: Data from sensors and cameras, user input

[0234] Output: Sending collected data to a server

[0235] Step 2:

[0236] Data reception and integrity check

[0237] Subject: Server

[0238] The server receives the data sent from the terminal. It checks the consistency of the received data. If the same information is sent from multiple terminals, it determines that the information is correct and performs a cross-check.

[0239] Input: Data sent from the terminal

[0240] Output: Data with integrity checked

[0241] Step 3:

[0242] Data analysis

[0243] Subject: Server and Generative AI

[0244] The server analyzes the data whose integrity has been confirmed. By using analytical methods, complex data is statistically analyzed to determine the extent of damage and the status of evacuation shelters. The generation AI generates accurate and reliable information based on this analytical data.

[0245] Input: Integrity checked data

[0246] Output: Information generated by the generative AI

[0247] Step 4:

[0248] information generation

[0249] Subject: Generation AI

[0250] The generative AI generates specific messages based on data analysis. For example, it generates a specific notification such as, "There is a food shortage at this evacuation shelter." The generated information is then customized to be provided to the user.

[0251] Input: Parsed data

[0252] Output: The specific message generated

[0253] Step 5:

[0254] Information provision

[0255] Subject: Means of information provision (smart device)

[0256] The generated information is provided to users via smart devices (such as smart glasses). Real-time information such as the status of evacuation shelters and evacuation routes is provided via display and voice notification. Adaptive evacuation information tailored to the user's current location is also displayed based on location information.

[0257] Input: The specific message to be generated

[0258] Output: Providing information via smart devices

[0259] Illustrative prompt examples

[0260] "Disaster information: Earthquake occurred. Current location is city center. Please provide evacuation locations and safe routes."

[0261] This processing flow enables rapid, real-time information provision in disaster-stricken areas, allowing users to take appropriate action.

[0262] 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.

[0263] The system of the present invention is designed to provide accurate information in disaster areas and is also combined with an emotion engine that recognizes and analyzes user emotions. This system is mainly implemented in the following forms:

[0264] The system includes a terminal connected to a network via satellite, a server that receives and analyzes data transmitted from the terminal, a generation AI that generates accurate information based on the analyzed data, and an information providing means that provides the generated information to the user. Furthermore, the system is equipped with an emotion engine that recognizes the user's emotions.

[0265] Device role and operation

[0266] Terminal

[0267] The terminals are installed in disaster-stricken areas, such as evacuation shelters, and are connected to the Internet via satellite. They are equipped with sensors, cameras, and voice input devices to collect real-time data such as temperature, humidity, and damage status. They also have an emotion engine that collects emotional data from users' facial expressions and voice, in addition to input information from users.

[0268] Server Roles and Operations

[0269] server

[0270] The server receives the data and emotion data sent from the device and analyzes it using generative AI. Specifically, it checks the consistency of the data and cross-checks information from multiple devices to increase reliability. It also analyzes the user's emotion data and adjusts the content and format of the information provided based on that emotion.

[0271] Role and behavior of generative AI

[0272] Generation AI

[0273] The AI ​​generates accurate and reliable information based on the data and emotional data analyzed on the server. For example, if a cross-check confirms that there is a food shortage at a particular evacuation shelter, it generates an appropriate message taking into account the user's emotional data. For example, if the user is feeling anxious, a message that provides reassurance will be provided.

[0274] Roles and operations of information provision means

[0275] Information provision means

[0276] The information provided to users is generated by the AI. Specifically, the device displays the information on the evacuation center's display, allowing users to obtain accurate information in real time. Based on the analysis results of the emotion engine, voice notifications and push notifications are also sent to mobile devices.

[0277] Specific examples

[0278] 1. Setting up the shelter

[0279] The device is installed in the evacuation center and connected to a satellite network. The sensors and cameras are activated to collect information on the surrounding environment (temperature, humidity, population, damage status, etc.). The emotion engine is also activated to analyze the user's facial expressions and voice.

[0280] 2. User input

[0281] The user types into the device, "There is a food shortage at the evacuation center." At this time, the emotion engine analyzes the user's facial expressions and voice and sends the data to the server as the user's emotion data.

[0282] 3. Data analysis and information generation

[0283] The server analyzes the received data and emotion data, cross-checking multiple similar reports. The AI ​​generator confirms the report that "food shortages are occurring at shelters A, B, and C," and generates a specific message based on the user's emotion. For example, if the user is feeling anxious, it will provide a reassuring message such as, "We are arranging to alleviate your anxiety and provide food promptly."

[0284] 4. Provision of Information

[0285] The generated information is displayed on the device's display and provided to users at evacuation shelters. For example, a notification such as, "There is a food shortage. We are arranging relief supplies based on this information. If you are feeling anxious, please rest assured; we are responding quickly."

[0286] This system enables disaster victims to quickly and accurately obtain the information they need, effectively supporting relief efforts. Furthermore, by utilizing an emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a greater sense of security.

[0287] The processing flow will be explained below.

[0288] Step 1:

[0289] Terminal

[0290] The device is installed at the evacuation center and connects to the network via satellite. At this time, the device is supplied with power and location information and basic information about the evacuation center (such as capacity) are entered. Sensors and cameras are activated and begin collecting environmental data (temperature, humidity, damage status, etc.). The emotion engine is also activated, ready to collect the user's facial expressions and voice.

[0291] Step 2:

[0292] User

[0293] Users input information about the evacuation shelter situation into their device. For example, they can use the touch panel or voice input function to report information such as "food is in short supply" or "the toilets are out of order." At this time, the emotion engine analyzes the user's facial expressions and voice to generate emotion data.

[0294] Step 3:

[0295] Terminal

[0296] The device formats the collected environmental data, user input data, and emotion data and transmits them to the server via satellite communication. It checks whether the data was transmitted correctly and attempts to retry if a transmission error occurs.

[0297] Step 4:

[0298] server

[0299] The server receives the data and emotion data sent from the device. The received data is passed to the generation AI, which then begins analyzing the data. Similar information sent from multiple devices is cross-checked to confirm the consistency and reliability of the data. At this time, the user's emotion data is also used in the analysis.

[0300] Step 5:

[0301] Server (Generating AI)

[0302] The generation AI generates accurate information based on the cross-checked data. For example, if the cross-check confirms that "there is a food shortage at a particular evacuation shelter," it generates a message that provides reassurance based on the user's emotional data. For example, it could say, "There is a food shortage at this evacuation shelter. Please rest assured, relief supplies are being quickly arranged."

[0303] Step 6:

[0304] Information provision means

[0305] The generated information is sent from the server to the device. It is then provided to the user as a display, voice notification, or push notification to their mobile device. For example, a message such as "There is a food shortage at evacuation centers. Relief supplies are being quickly arranged. Please rest assured if you are feeling anxious" is displayed.

[0306] Step 7:

[0307] server

[0308] The server periodically receives and analyzes new data and updates the information. Every time new data is sent, the generating AI reanalyzes it and updates the information based on the latest state. The updated information is then resent to the device, and the display content is updated in real time.

[0309] This procedure allows users at evacuation shelters in disaster areas to quickly and accurately obtain the information they need. Furthermore, by utilizing the emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a sense of security.

[0310] Example 2

[0311] 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."

[0312] Conventional information provision systems in disaster areas have difficulty in providing accurate information quickly, and in particular have been unable to provide information that takes into account the user's emotions. As a result, victims are prone to feeling anxious and stressed, and are sometimes unable to obtain accurate information. Furthermore, if information from multiple sources is not cross-checked, there is a risk that unreliable information will be provided.

[0313] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0314] In this invention, the server includes a terminal device that uses sensors, cameras, and a voice input device to collect environmental data of the disaster area and input data from the user, a terminal device that uses an emotion engine to collect user emotion data, a server device that receives and analyzes the data transmitted from the terminal device, a server device that generates accurate information based on the analyzed data and emotion data using a generation AI, and a device that displays the generated information on the display of the terminal device and sends voice notifications and push notifications to mobile devices. This enables the provision of fast and accurate information in disaster areas and information that takes user emotions into consideration and gives a sense of security.

[0315] "Terminal devices" are devices that are installed in disaster areas and evacuation shelters, connect to the Internet via a satellite network, and use sensors, cameras, and voice input devices to collect environmental data and input data from users.

[0316] An "emotion engine" is a software or hardware system that analyzes a user's facial expressions and voice and collects the user's emotional data.

[0317] A "server device" is a computer system that receives and analyzes data sent from a terminal device.

[0318] "Generative AI" is an artificial intelligence algorithm or software that resides within a server device and generates accurate information based on analyzed data and emotional data.

[0319] An "information providing device" is a device for providing generated information to a user, and has the function of displaying information on the display of a terminal device and providing voice notification and push notification to a mobile device.

[0320] A "cross-checking means" is a process or algorithm by which a server device verifies the integrity of data sent from multiple terminal devices and cross-checks the data to increase the reliability of the information.

[0321] The system of the present invention is designed to provide accurate information in disaster-stricken areas and is also combined with an emotion engine that recognizes and analyzes user emotions. This system consists of a terminal device, a server device, a generation AI, and an information providing device.

[0322] Roles and operations of terminal devices

[0323] The terminal devices are installed in disaster areas, such as evacuation shelters. They are equipped with sensors, cameras, and voice input devices, which can be used to collect real-time data such as temperature, humidity, population density, and damage status. They also have a built-in emotion engine that can analyze the user's facial expressions and voice to collect emotional data. The terminal devices are connected to a network via satellite and transmit the collected data to a server device.

[0324] Roles and operations of server devices

[0325] The server device receives data sent from the terminal devices. The server device checks the consistency of the received environmental data and emotion data and cross-checks the information obtained from multiple terminal devices, thereby increasing the reliability of the data. The server device uses a generative AI model written in Python (e.g., GPT-3) to generate accurate information based on the analyzed data.

[0326] Role and behavior of generative AI

[0327] The AI ​​generates accurate and reliable information in a format that is easy for humans to understand, based on the data and emotional data analyzed by the server. For example, if a cross-check confirms that "food is in short supply at a specific evacuation shelter," it generates an appropriate message taking into account the user's emotional data. If the user is feeling anxious, it generates a reassuring message such as, "We are arranging to alleviate your anxiety and quickly provide food."

[0328] Roles and operations of information providing devices

[0329] The information provision device provides users with the information generated by the AI. Specifically, it displays the information on the terminal device's display, providing users with accurate information in real time. It also provides voice notifications and push notifications to mobile devices based on the analysis results of the emotion engine.

[0330] Specific examples

[0331] 1. Setting up the shelter

[0332] Terminal devices are installed in evacuation shelters and connected to a satellite network. Sensors and cameras are activated to collect information on the surrounding environment (temperature, humidity, population density, damage status, etc.). An emotion engine is also activated to analyze the user's facial expressions and voice.

[0333] 2. User input

[0334] The user inputs into the terminal device, "There is a shortage of food at the evacuation shelter." At this time, the emotion engine analyzes the user's facial expressions and voice and transmits the data to the server device as the user's emotion data.

[0335] 3. Data analysis and information generation

[0336] The server analyzes the received data and emotion data, cross-checking multiple similar reports. The AI ​​generator confirms the report that "food shortages are occurring at shelters A, B, and C," and generates a specific message based on the user's emotion. For example, if the user is feeling anxious, it will provide a reassuring message such as, "We are arranging to alleviate your anxiety and provide food promptly."

[0337] 4. Provision of Information

[0338] The generated information is displayed on the terminal device's display and provided to users at the evacuation shelter. For example, a message such as, "There is a food shortage. We are arranging relief supplies based on this information. If you are feeling anxious, please rest assured; we are responding quickly."

[0339] Prompt Sentence Examples

[0340] "Please let us know the current temperature and humidity at the evacuation center in real time. Also, please let us know about any food shortages."

[0341] "Generate and present messages that make users feel safe in the evacuation shelter. Emotional data is unsettling."

[0342] This system allows disaster victims to obtain quick and accurate information, enabling effective support for relief efforts. In addition, by utilizing the emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a greater sense of security.

[0343] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0344] Step 1: Collect data from the device

[0345] How it works: The device is installed in an evacuation center and connected to the Internet via satellite. Sensors and cameras are activated to collect real-time data such as temperature, humidity, population density, and damage status. The emotion engine analyzes the user's facial expressions and voice to collect emotional data. The device then sends all collected data to a server.

[0346] Input: Real-time data on temperature, humidity, population density, damage status, and user facial and voice data

[0347] Output: Collected environmental data and emotional data (e.g., temperature 30°C, humidity 70%, emotion = anxiety)

[0348] Step 2: User enters information

[0349] Specific operation: The user inputs information such as "There is a food shortage at the evacuation shelter" into the device. The device receives this information, and the emotion engine analyzes the user's facial expressions and voice to generate emotion data. The device then sends this data to the server.

[0350] Input: User-supplied text (e.g., "Food shortage at evacuation centers")

[0351] Output: Text information and analyzed emotion data (e.g. emotion = anxiety)

[0352] Step 3: Server receives data

[0353] Specific operation: The server receives data sent from the device. Examples include temperature, humidity, population density, damage status, user input information, and emotional data. The server stores all received data in a database.

[0354] Input: Data sent from the device (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[0355] Output: Received data stored in a database

[0356] Step 4: Data analysis by the server

[0357] Specific operation: The server checks the integrity of the data stored in the database and performs cross-checks to improve the reliability of the data. It checks whether the data is consistent and whether there are any outliers.

[0358] Input: Data stored in the database (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[0359] Output: Trusted data with integrity checks

[0360] Step 5: Information generation by generative AI

[0361] Specific operation: The server inputs the data that has passed the cross-check into the generation AI. Based on this, the generation AI generates information in a format that is easy for humans to understand. For example, it might generate information such as "There is a food shortage at shelters A, B, and C," and then incorporate emotional data to create a reassuring message such as "We are responding quickly."

[0362] Input: Reliable data after cross-checking (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[0363] Output: Generated information (e.g., "There is a food shortage at shelters A, B, and C. We are responding quickly, so please wait without worry.")

[0364] Step 6: Notify users through informational means

[0365] Specific operation: The information generated by the generation AI is displayed on the device's display. In addition, based on the analysis results of the emotion engine, voice notifications and push notifications are also sent to the mobile device.

[0366] Input: Generated information (e.g., "There is a food shortage at shelters A, B, and C. We are responding quickly, so please wait without worry.")

[0367] Output: Information displayed on the device display, audio notification, push notification to mobile device

[0368] The above steps will enable the provision of fast and accurate information in disaster-stricken areas, thereby reducing user anxiety.

[0369] (Application example 2)

[0370] 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."

[0371] In disaster-stricken areas, it is important to provide accurate information and generate information that takes into account the emotions of users. In particular, in fields such as food delivery services, it is necessary to accurately grasp users' emotions and respond accordingly. However, conventional systems have been inadequate in recognizing and reflecting emotions. This has resulted in an incomplete user experience and has made it difficult to respond efficiently.

[0372] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means, adjustment means, and prompt generation means. This makes it possible to analyze the user's emotion data, adjust the content and format of information based on that, and input the information as a prompt sentence into the generation AI model, thereby enabling individual responses that take the user's emotions into consideration.

[0373] "Terminal means" refers to a device that is installed in a disaster area or a service site, connects to a network, and collects and transmits data.

[0374] The "server means" is a central processing unit that receives data sent from the terminal means, analyzes it, and generates necessary information.

[0375] The "generation means" refers to a process or system that automatically generates accurate information based on the data analyzed by the server means.

[0376] "Information provision means" refers to means such as a display, voice notification, or push notification for providing the generated information to the user.

[0377] The "emotion engine means" is a combination of software and hardware for recognizing and analyzing the user's emotions.

[0378] "Adjustment means" refers to a process or system for adjusting the content and format of the information provided based on the analyzed emotional data.

[0379] "Cross-checking means" refers to means used to check the consistency of data sent from multiple users and increase the reliability of the data.

[0380] A "prompt generation means" is a means of inputting information based on the user's emotions into a generative AI model as a prompt sentence.

[0381] A "generative AI model" is an artificial intelligence model that automatically generates meaningful information based on input data.

[0382] A "prompt sentence" is an input sentence that causes a generative AI model to output specific information.

[0383] A system for carrying out the present invention includes the following means.

[0384] 1. Roles and operations of terminal means

[0385] The terminals will be installed at evacuation centers and food delivery service sites. They are connected to a network via satellite and equipped with sensors, cameras, and voice input devices. These sensors and input devices collect real-time data such as temperature, humidity, damage status, and the user's facial expressions and voice. In particular, the emotion engine analyzes the user's emotional data and sends the data based on that to a server.

[0386] 2. Roles and Operations of Server Means

[0387] The server receives and analyzes the data and emotional data sent from the terminals. The server uses a cross-checking means to confirm the consistency of information from multiple users and increase its reliability. It also has an adjustment means that adjusts the content and format of the information based on the emotional data. The adjusted data is then generated as a prompt sentence to be input into the generative AI model using a prompt generation means.

[0388] 3. Role and operation of the generating means

[0389] The generative AI model generates accurate information that takes into consideration the user's emotions based on the data analyzed on the server and emotional data. For example, if the user is feeling anxious, it generates a reassuring message such as, "We are arranging to alleviate your anxiety and quickly deliver food."

[0390] 4. Roles and Functions of Information Provision Means

[0391] The generated information is displayed on the device screen and is also provided to the user via voice notifications and push notifications to their mobile device. The information is provided in an appropriate format and with appropriate content based on emotional data, giving the user a sense of security.

[0392] Specific examples

[0393] A food delivery service collects emotional data when a user places an order.

[0394] 1. Device-based data collection and sentiment analysis:

[0395] When a user places an order from their smartphone, the system uses a camera and voice input device to analyze their facial expressions and voice and recognize whether they are in a hurry.

[0396] 2. Server-based data analysis and prompt generation:

[0397] The server analyzes the collected user emotional data and inputs the prompt sentence, "Please tell me what to do if I'm in a hurry," into the generative AI model.

[0398] 3. Information generation using generative AI models:

[0399] The generative AI model generates messages based on the emotion of "being in a hurry," such as, "We will start cooking immediately and arrange for delivery staff. We are doing our best to avoid keeping you waiting."

[0400] Prompt Sentence Examples

[0401] "Please tell me what to do if I'm in a hurry."

[0402] This system will enable disaster-stricken areas and food delivery services to accurately grasp user emotions and provide information tailored to them, resulting in an improved user experience and more efficient responses.

[0403] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0404] Step 1:

[0405] The device collects input information from the user and environmental sensor data. Specifically, it uses the camera and voice input device of a smartphone or robot to capture the user's facial expressions and voice, and simultaneously collects data such as temperature, humidity, and surrounding damage. The inputs include the user's order information, facial image, voice data, and sensor data. The output is sent to the server.

[0406] Step 2:

[0407] The device passes the collected facial image and voice data to the emotion engine means for analysis. The specific analysis operation involves using an emotion recognition library (e.g., DeepFace) to extract the main emotion felt by the user (e.g., feeling rushed or anxious). The facial image and voice data are used as input. The output is generated as data on the user's main emotion, and this data is sent to the server.

[0408] Step 3:

[0409] The server receives the user's emotion data and input information sent from the device. Specifically, it retrieves the data via an HTTP request and formats it into a format suitable for analysis. As input, it receives the user's order data, emotion data, and environmental sensor data. As output, it creates a dataset that has undergone preprocessing for data analysis.

[0410] Step 4:

[0411] The server cross-checks the received data. Specifically, it compares and examines similar data sent from multiple devices to confirm the reliability of the data. It uses a cross-checking method. As input, it uses the same type of data set sent by multiple users. As output, it generates data whose reliability has been confirmed.

[0412] Step 5:

[0413] The server uses a prompt generation means to generate a prompt sentence to be input to the generative AI model based on the user's emotional data. Specifically, if the emotional data indicates "I'm in a hurry," the server creates a prompt sentence saying, "Please tell me what to do if I'm in a hurry." The emotional data is used as input. The server generates a prompt sentence to be input to the generative AI model as output.

[0414] Step 6:

[0415] The server uses the generative AI model to generate an appropriate response message. Specifically, the prompt sentence is passed to the model as input, and the message generated by the AI ​​is obtained. For example, if the prompt sentence is "Please tell me what to do if I'm in a hurry," the generated message will be "We will start cooking immediately and arrange for a delivery person. We are doing our best to avoid keeping you waiting." The prompt sentence is used as input. The response message created by the generative AI model is obtained as output.

[0416] Step 7:

[0417] The server sends the generated message to the device and provides it to the user using the device's information provision means. Specifically, the message is not only displayed on the screen, but also provided as a voice notification or push notification. The generated message is used as input. The message is displayed on the user's smartphone or device as output.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] [Second embodiment]

[0422] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0423] 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.

[0424] 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).

[0425] 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.

[0426] 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.

[0427] 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).

[0428] 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.

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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."

[0434] The system according to the present invention is intended to provide accurate information in disaster areas, and is mainly implemented in the following form.

[0435] First, the system includes a terminal that connects to the network via satellite, a server that receives and analyzes data sent from the terminal, a generation AI that generates accurate information based on the analyzed data, and an information provision means that provides the generated information to users.

[0436] Device role and operation

[0437] Terminal

[0438] The terminals are installed in disaster-stricken areas, such as evacuation centers, and are connected to the Internet via satellite. They are equipped with sensors and cameras to collect real-time data such as temperature, humidity, and damage status. They also collect information entered by users (e.g., the status of evacuation centers, food shortages, etc.).

[0439] Server Roles and Operations

[0440] server

[0441] The server receives the data sent from the devices and analyzes it using the generating AI. Specifically, the server checks the integrity of the data and cross-checks information from multiple devices to increase reliability. For example, if the same information is sent from multiple evacuation centers, it will determine that the information is accurate.

[0442] Role and behavior of generative AI

[0443] Generation AI

[0444] The AI ​​generates accurate and reliable information based on the data analyzed by the server. For example, if the information that "a certain evacuation shelter is short of food" is confirmed by cross-checking, the AI ​​creates a specific message saying, "There is a food shortage at this evacuation shelter."

[0445] Roles and operations of information provision means

[0446] Information provision means

[0447] The information provided by the AI ​​is presented to users via a variety of methods, including displaying information on the evacuation center's screen, allowing users to obtain accurate information in real time. Information can also be provided via voice notifications and push notifications to mobile devices.

[0448] Specific examples

[0449] 1. Setting up the shelter

[0450] Terminals are installed in evacuation centers and connected to a satellite network. They use sensors and cameras to collect information about the surrounding environment (temperature, humidity, population, damage, etc.).

[0451] 2. User input

[0452] The user types "There is a food shortage at the evacuation center" into the device, and the information is sent from the device to the server.

[0453] 3. Data analysis and information generation

[0454] The server analyzes the received data and cross-checks multiple similar reports. The generator AI generates an accurate message based on the information that "food is in short supply."

[0455] 4. Provision of Information

[0456] The generated information is displayed on the device's screen, and users at the evacuation center are notified with messages such as, "There is a food shortage. We are arranging relief supplies based on this information."

[0457] This system allows disaster victims to quickly and accurately obtain the information they need. For example, if there is a shortage of food or relief supplies, or if local traffic information is needed, the system will respond appropriately in real time. This will minimize confusion in the disaster-stricken areas and support effective relief efforts.

[0458] The processing flow will be explained below.

[0459] Step 1:

[0460] Terminal

[0461] The terminal is installed in the evacuation center and connects to the network via satellite. At this time, the terminal is supplied with power and basic settings (location information, basic information about the evacuation center, etc.) are configured. The sensors and cameras are activated and begin collecting environmental data about the evacuation center (temperature, humidity, images, etc.).

[0462] Step 2:

[0463] User

[0464] Users input the status of the evacuation shelter into the device. Specifically, they use the device's touch panel or voice input function to report information such as "food is in short supply" or "the toilets are out of order." The device temporarily stores this user-entered data.

[0465] Step 3:

[0466] Terminal

[0467] The terminal formats the collected environmental data and user-input data and transmits it to the server via satellite communication. At this time, it checks whether the data was transmitted correctly and attempts to retransmit it if an error occurs.

[0468] Step 4:

[0469] server

[0470] The server receives data sent from the devices. It passes the received data to the generation AI, which begins analyzing it. It cross-checks similar information sent from multiple devices to confirm the consistency and reliability of the data. For example, if information that "food is running low" is sent from multiple evacuation centers, it will match this information.

[0471] Step 5:

[0472] Server (Generating AI)

[0473] The AI ​​then generates accurate information based on the cross-checked data. For example, if a report is confirmed that "food is in short supply at shelters A, B, and C," the AI ​​generates a specific message saying, "There is a food shortage at these shelters."

[0474] Step 6:

[0475] Information provision means

[0476] The generated information is sent from the server to the device and displayed on the device's display. It can also be provided to the user as a voice notification or a push notification to the mobile device, as needed. For example, a message such as "There is a food shortage. We are currently arranging relief supplies based on this information" can be displayed.

[0477] Step 7:

[0478] server

[0479] The server periodically receives and analyzes new data and updates the information. Every time new data is sent, the generating AI reanalyzes it and updates the information based on the latest state. The updated information is then sent back to the device, and the display is updated in real time.

[0480] This process will enable accurate information to be provided at evacuation centers in disaster-stricken areas, enabling support activities to be carried out quickly and effectively.

[0481] Example 1

[0482] 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."

[0483] In disaster-stricken areas, it was difficult to quickly and accurately collect information and provide it to victims with reliable information, which led to delays in relief efforts and confusion over information, resulting in victims not receiving the support they needed in a timely manner.

[0484] 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.

[0485] In this invention, the server includes a terminal means, a means for receiving and analyzing sensor and user input data, a generating AI model means for generating highly reliable information, and a means for displaying or announcing the generated information, thereby enabling the rapid provision of highly reliable information based on data collected in disaster areas.

[0486] "Disaster area" refers to an area that has been affected by a natural or man-made disaster.

[0487] A "satellite network" refers to a network system that provides internet and communication services via artificial satellites.

[0488] "Terminal means" refers to electronic devices that are installed in the disaster area and that collect and transmit data.

[0489] "Server means" refers to a computer system for receiving and analyzing data sent from terminal means.

[0490] "Sensor" refers to a device that measures environmental data such as temperature and humidity.

[0491] "User-input data" refers to information provided by a User through a Terminal.

[0492] "Generative AI model" refers to an artificial intelligence model that generates reliable information based on data analyzed by a server means.

[0493] "Cross-checking measures" refers to the process of collating information from multiple data sources and assessing its consistency and reliability.

[0494] "Information providing means" refers to a device or method for notifying the user of the generated information.

[0495] "Display" refers to a device that visually displays generated information.

[0496] "Audio notification" refers to a means of conveying generated information to the user audibly.

[0497] "Data analysis means" refers to the server's function of verifying the integrity of collected data and performing any necessary cleansing or cross-checking.

[0498] "Cellular terminal" refers to a mobile device such as a mobile phone or smartphone.

[0499] This invention is a system for providing rapid and accurate information in disaster-stricken areas, and is mainly composed of terminal means, server means, generation AI model means, and information provision means. The specific operation and implementation method of each means will be explained below.

[0500] Terminal means

[0501] The terminal means is an electronic device installed in evacuation shelters in disaster areas and connected to the Internet via a satellite network. This terminal is equipped with sensors to collect environmental data such as temperature and humidity, and a camera to capture images of the damage. It also provides an interface for users to input information about the evacuation shelter situation and shortages of supplies.

[0502] As a specific example of use, a terminal means is installed in a shelter and collects information on the surrounding situation in real time using sensors and cameras. Furthermore, when a user inputs "There is a shortage of food at the shelter," this information is recorded in the terminal means. The terminal means packages this data and transmits it to the server means in the next phase.

[0503] Server Means

[0504] The server means is a computer system that receives and analyzes data sent from the terminal means. First, it checks the integrity of the received data and performs data cleansing if there are missing or invalid values. Then it cross-checks the same type of data sent from multiple terminals and evaluates its reliability. For example, if the same information is reported from multiple evacuation shelters, it is determined that the information is accurate.

[0505] The server means stores the received data in a database and then prepares to provide the data to the generative AI model means.

[0506] Generative AI model means

[0507] The generating AI model means is an artificial intelligence model that generates reliable information based on the data analyzed by the server means. The AI ​​model receives the analyzed data as input and generates a specific and reliable message. For example, it creates a notification message such as "There is a food shortage. Based on this information, relief supplies are being arranged."

[0508] Information provision means

[0509] The information provision means plays a role in providing the information generated by the generative AI model means to the user. The information is displayed on the display of the terminal means so that the user can obtain accurate information in real time. The information can also be provided in multiple ways, such as voice notification or push notification to the mobile device.

[0510] Specific examples

[0511] 1. Setting up the shelter

[0512] Terminal devices are installed in evacuation centers and connected to a satellite network. They use sensors and cameras to collect information on the surrounding environment (temperature, humidity, population, damage status, etc.) in real time.

[0513] 2. User input

[0514] The user inputs "There is a shortage of food at the evacuation shelter" into the terminal means. The information is transmitted from the terminal means to the server means.

[0515] 3. Data analysis and information generation

[0516] The server means analyzes the received data and cross-checks multiple similar reports. The generative AI model means generates an accurate message based on the information that "food is in short supply."

[0517] 4. Provision of Information

[0518] The generated information is displayed on the terminal display, and users at the evacuation shelter are notified, such as, "There is a food shortage. We are arranging relief supplies based on this information." It is also possible to send voice notifications and push notifications to mobile devices.

[0519] Prompt Sentence Examples

[0520] 1. Prompt example 1

[0521] We have installed devices in evacuation shelters in the affected areas that use sensors and cameras to collect information on temperature, humidity, and damage. Please enter information on the evacuation shelter situation and food shortages.

[0522] 2. Prompt example 2

[0523] Based on the data collected on the device, the server analyzed and cross-checked the data. Based on this information, the AI ​​generated the message "Food is running low." Please check the generated notification content.

[0524] 3. Prompt example 3

[0525] Based on the above information, a notice was sent to the terminal displays at the evacuation center. Please check the status of food supply arrangements.

[0526] As described above, by having each means work in coordination, it becomes possible to provide disaster victims with quick and accurate information and provide effective support.

[0527] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0528] Step 1: Placement and connection of terminal means

[0529] Specific operation: The terminal means is installed at an evacuation shelter in the disaster area. A technician installs the terminal means and establishes an Internet connection using a satellite antenna.

[0530] Input: Information about evacuation shelters and their locations

[0531] Output: Internet connection established and terminal means operational

[0532] Step 2: Start the sensors and cameras

[0533] Specific operation: The system administrator remotely activates the sensors and cameras of the terminal device, which completes preparations for data collection.

[0534] Input: Sensor and camera initial configuration information

[0535] Output: Sensors and cameras are up and running and ready to collect data.

[0536] Step 3: Collect environmental data

[0537] Specific operation: The terminal device uses sensors to collect environmental data such as temperature, humidity, and population in real time, and also uses a camera to take photos of the damage situation and save the image data.

[0538] Input: Local environmental information of the evacuation shelter

[0539] Output: Collected environmental and image data

[0540] Step 4: User input

[0541] Specific operation: The user uses the input interface of the terminal means to input information such as "food shortage at the evacuation center." The terminal means records this information.

[0542] Input: User-entered shelter status information

[0543] Output: User input data recorded on the terminal means

[0544] Step 5: Packaging and preparing the data for transmission

[0545] Specific operation: The terminal means packages the collected environmental data and user input data into one data packet and prepares to send it to the server means.

[0546] Input: Collected environmental data and user-entered data

[0547] Output: Data packets ready to be sent

[0548] Step 6: Sending data to the server

[0549] Specific operation: The terminal means transmits data packets to the server means via satellite communication. The data is encrypted and transmitted.

[0550] Input: Data packet ready to send

[0551] Output: Data packets received by the server

[0552] Step 7: Receiving and storing data

[0553] Specific operation: The server means receives the data packets sent from the terminal means and stores them in a database for analysis.

[0554] Input: Data packets sent from the terminal means

[0555] Output: Saved data

[0556] Step 8: Data integrity check and cleansing

[0557] Specific operation: The server means checks the integrity of the data and performs data cleansing if there are missing or invalid values.

[0558] Input: Saved data

[0559] Output: Cleansed data with integrity checks

[0560] Step 9: Cross-check from multiple devices

[0561] Specific operation: The server means cross-checks the same type of data sent from different terminal means and evaluates its reliability. For example, if multiple evacuation centers report the same content, such as "food shortages," the information is judged to be accurate.

[0562] Input: Homogeneous data sent from multiple terminal means

[0563] Output: Data whose reliability has been assessed by cross-checking

[0564] Step 10: Generate information using generative AI models

[0565] Specific operation: The server executes the generative AI model based on the analyzed data to generate a reliable message, such as "There is a food shortage. Based on this information, we are arranging relief supplies."

[0566] Input: Data whose reliability has been assessed by cross-checking

[0567] Output: Highly reliable informational messages generated

[0568] Step 11: Prepare to distribute information

[0569] Specific operation: The server means assembles the generated information messages into packets for delivery and prepares them for transmission.

[0570] Input: Generated information message

[0571] Output: Data packets ready for delivery

[0572] Step 12: Sending information to the terminal means

[0573] Specific operation: The server means transmits a distribution data packet to the terminal means.

[0574] Input: Data packets ready for delivery

[0575] Output: Information received by terminal means

[0576] Step 13: Providing information through display and audio notifications

[0577] Specific operation: The terminal displays the received information on the display of the evacuation center, providing users with accurate information in real time, and also provides voice notifications as necessary.

[0578] Input: Information received by terminal means

[0579] Output: Information displayed on the screen and audio notifications

[0580] Step 14: Push notification to mobile device

[0581] Specific operation: The terminal means or the server means also sends a push notification to the mobile device, so that the user can check detailed information on their mobile device.

[0582] Input: Information generated by terminal or server means.

[0583] Output: Push notification received on mobile device

[0584] (Application example 1)

[0585] 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."

[0586] In conventional disaster response systems, information collection and provision is often not done in real time, making it difficult to provide victims with quick and accurate information. In addition, the means of providing information are limited, and a lack of adaptive evacuation information, especially in dangerous situations, has been a problem. This has led to the risk that victims are unable to take appropriate action, and the damage may worsen.

[0587] 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.

[0588] In this invention, the server includes a terminal means connected to the network via a satellite, a means for receiving and analyzing data transmitted from the terminal means, a generating means for generating accurate information based on the data analyzed by the server means, an information providing means using a smart device (including smart glasses) for providing the generated information to users, a cross-checking means for checking the consistency of data transmitted from multiple users, and an adaptive evacuation information providing means based on location information. This enables prompt and accurate information to be provided in disaster-stricken areas, allowing disaster victims to take appropriate action.

[0589] "Terminal means" refers to a device that connects to a network via satellite and collects data using sensors and cameras in the disaster area.

[0590] The "server means" is a server device that receives and analyzes data sent from the terminal means.

[0591] The "analysis means" is a means for verifying the consistency of received data in the server means and analyzing the data.

[0592] The "generation means" is a means for generating accurate information based on the analyzed data.

[0593] A "smart device" is a device that provides generated information to a user, and includes smart glasses and the like.

[0594] The "information providing means" is a means for providing the information generated by the generating means to the user.

[0595] A "cross-check means" is a means for checking the consistency of data sent from multiple users.

[0596] An "adaptive evacuation information provision means" is a means for providing users with optimal evacuation information in real time based on location information.

[0597] The system according to the present invention is for providing accurate information in real time in disaster areas, and is implemented in the following manner.

[0598] 1. Roles and operations of terminal means

[0599] The terminal means is installed in the disaster area and connected to the network via satellite. Specifically, it is a device installed in evacuation shelters and dangerous areas, and is equipped with sensors and cameras. This terminal collects the following data:

[0600] Temperature and humidity

[0601] Damage situation

[0602] Demographics

[0603] Users can use the terminal to input information such as the status of evacuation shelters and food shortages, which is then sent to the server.

[0604] 2. Roles and Operations of Server Means

[0605] The server means is a device that receives data sent from the terminal means and performs analysis processing. The server means processes the data using the following means:

[0606] Analysis method: Check the integrity of the received data and perform analysis.

[0607] Cross-checking measures: verifying the integrity of data submitted by multiple users.

[0608] Generation method: Generate accurate and reliable information based on the analyzed data.

[0609] Specifically, the server cross-checks the consistency of the data. For example, if multiple shelters report the same information, it determines that the information is accurate. As a result of this process, the generator generates specific information such as "food shortage."

[0610] 3. Roles and Functions of Information Provision Means

[0611] The information providing means is a device for providing the information generated by the generating means to the user. In particular, the present invention utilizes a smart device, such as smart glasses:

[0612] Smart glasses: Evacuation information and warnings are displayed on the screen, and voice notifications are also possible.

[0613] Location integration: Shows the nearest evacuation shelters and safe routes based on your current location.

[0614] Hardware / Software used

[0615] Hardware: Satellite-connected devices, smart glasses

[0616] Software: Cloud servers, analytical algorithms, generative AI (e.g., OpenAI's GPT model), speech synthesis engines (e.g., Google Text-to-Speech)

[0617] For example, the following prompts can be sent to the generative AI to provide real-time information:

[0618] Prompt Sentence Examples

[0619] "Disaster information: Earthquake occurred. Current location is city center. Please provide evacuation locations and safe routes."

[0620] Example

[0621] 1. Visual Indication:

[0622] The smart glasses' display read, "The nearest evacuation shelter is 500 meters north from your current location. Take the next right."

[0623] 2. Sound notification:

[0624] The smart glasses will play a voice notification saying, "An earthquake has occurred. Please evacuate immediately. Walk 500 meters to the right to reach the evacuation shelter."

[0625] This will enable disaster victims to take safe action based on prompt and accurate information, minimizing confusion in disaster-stricken areas and supporting effective relief efforts.

[0626] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0627] Step 1:

[0628] Data collection and transmission

[0629] Subject: Terminal

[0630] The device uses sensors and cameras installed in the affected area to collect data such as temperature, humidity, and damage status. It also collects information entered by the user, such as the status of evacuation shelters and food shortages. This data is collected in real time and sent to a server via satellite communication.

[0631] Input: Data from sensors and cameras, user input

[0632] Output: Sending collected data to a server

[0633] Step 2:

[0634] Data reception and integrity check

[0635] Subject: Server

[0636] The server receives the data sent from the terminal. It checks the consistency of the received data. If the same information is sent from multiple terminals, it determines that the information is correct and performs a cross-check.

[0637] Input: Data sent from the terminal

[0638] Output: Data with integrity checked

[0639] Step 3:

[0640] Data analysis

[0641] Subject: Server and Generative AI

[0642] The server analyzes the data whose integrity has been confirmed. By using analytical methods, complex data is statistically analyzed to determine the extent of damage and the status of evacuation shelters. The generation AI generates accurate and reliable information based on this analytical data.

[0643] Input: Integrity checked data

[0644] Output: Information generated by the generative AI

[0645] Step 4:

[0646] information generation

[0647] Subject: Generation AI

[0648] The generative AI generates specific messages based on data analysis. For example, it generates a specific notification such as, "There is a food shortage at this evacuation shelter." The generated information is then customized to be provided to the user.

[0649] Input: Parsed data

[0650] Output: The specific message generated

[0651] Step 5:

[0652] Information provision

[0653] Subject: Means of information provision (smart device)

[0654] The generated information is provided to users via smart devices (such as smart glasses). Real-time information such as the status of evacuation shelters and evacuation routes is provided via display and voice notification. Adaptive evacuation information tailored to the user's current location is also displayed based on location information.

[0655] Input: The specific message to be generated

[0656] Output: Providing information via smart devices

[0657] Illustrative prompt examples

[0658] "Disaster information: Earthquake occurred. Current location is city center. Please provide evacuation locations and safe routes."

[0659] This processing flow enables rapid, real-time information provision in disaster-stricken areas, allowing users to take appropriate action.

[0660] 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.

[0661] The system of the present invention is designed to provide accurate information in disaster areas and is also combined with an emotion engine that recognizes and analyzes user emotions. This system is mainly implemented in the following forms:

[0662] The system includes a terminal connected to a network via satellite, a server that receives and analyzes data transmitted from the terminal, a generation AI that generates accurate information based on the analyzed data, and an information providing means that provides the generated information to the user. Furthermore, the system is equipped with an emotion engine that recognizes the user's emotions.

[0663] Device role and operation

[0664] Terminal

[0665] The terminals are installed in disaster-stricken areas, such as evacuation shelters, and are connected to the Internet via satellite. They are equipped with sensors, cameras, and voice input devices to collect real-time data such as temperature, humidity, and damage status. They also have an emotion engine that collects emotional data from users' facial expressions and voice, in addition to input information from users.

[0666] Server Roles and Operations

[0667] server

[0668] The server receives the data and emotion data sent from the device and analyzes it using generative AI. Specifically, it checks the consistency of the data and cross-checks information from multiple devices to increase reliability. It also analyzes the user's emotion data and adjusts the content and format of the information provided based on that emotion.

[0669] Role and behavior of generative AI

[0670] Generation AI

[0671] The AI ​​generates accurate and reliable information based on the data and emotional data analyzed on the server. For example, if a cross-check confirms that there is a food shortage at a particular evacuation shelter, it generates an appropriate message taking into account the user's emotional data. For example, if the user is feeling anxious, a message that provides reassurance will be provided.

[0672] Roles and operations of information provision means

[0673] Information provision means

[0674] The information provided to users is generated by the AI. Specifically, the device displays the information on the evacuation center's display, allowing users to obtain accurate information in real time. Based on the analysis results of the emotion engine, voice notifications and push notifications are also sent to mobile devices.

[0675] Specific examples

[0676] 1. Setting up the shelter

[0677] The device is installed in the evacuation center and connected to a satellite network. The sensors and cameras are activated to collect information on the surrounding environment (temperature, humidity, population, damage status, etc.). The emotion engine is also activated to analyze the user's facial expressions and voice.

[0678] 2. User input

[0679] The user types into the device, "There is a food shortage at the evacuation center." At this time, the emotion engine analyzes the user's facial expressions and voice and sends the data to the server as the user's emotion data.

[0680] 3. Data analysis and information generation

[0681] The server analyzes the received data and emotion data, cross-checking multiple similar reports. The AI ​​generator confirms the report that "food shortages are occurring at shelters A, B, and C," and generates a specific message based on the user's emotion. For example, if the user is feeling anxious, it will provide a reassuring message such as, "We are arranging to alleviate your anxiety and provide food promptly."

[0682] 4. Provision of Information

[0683] The generated information is displayed on the device's display and provided to users at evacuation shelters. For example, a notification such as, "There is a food shortage. We are arranging relief supplies based on this information. If you are feeling anxious, please rest assured; we are responding quickly."

[0684] This system enables disaster victims to quickly and accurately obtain the information they need, effectively supporting relief efforts. Furthermore, by utilizing an emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a greater sense of security.

[0685] The processing flow will be explained below.

[0686] Step 1:

[0687] Terminal

[0688] The device is installed at the evacuation center and connects to the network via satellite. At this time, the device is supplied with power and location information and basic information about the evacuation center (such as capacity) are entered. Sensors and cameras are activated and begin collecting environmental data (temperature, humidity, damage status, etc.). The emotion engine is also activated, ready to collect the user's facial expressions and voice.

[0689] Step 2:

[0690] User

[0691] Users input information about the evacuation shelter situation into their device. For example, they can use the touch panel or voice input function to report information such as "food is in short supply" or "the toilets are out of order." At this time, the emotion engine analyzes the user's facial expressions and voice to generate emotion data.

[0692] Step 3:

[0693] Terminal

[0694] The device formats the collected environmental data, user input data, and emotion data and transmits them to the server via satellite communication. It checks whether the data was transmitted correctly and attempts to retry if a transmission error occurs.

[0695] Step 4:

[0696] server

[0697] The server receives the data and emotion data sent from the device. The received data is passed to the generation AI, which then begins analyzing the data. Similar information sent from multiple devices is cross-checked to confirm the consistency and reliability of the data. At this time, the user's emotion data is also used in the analysis.

[0698] Step 5:

[0699] Server (Generating AI)

[0700] The generation AI generates accurate information based on the cross-checked data. For example, if the cross-check confirms that "there is a food shortage at a particular evacuation shelter," it generates a message that provides reassurance based on the user's emotional data. For example, it could say, "There is a food shortage at this evacuation shelter. Please rest assured, relief supplies are being quickly arranged."

[0701] Step 6:

[0702] Information provision means

[0703] The generated information is sent from the server to the device. It is then provided to the user as a display, voice notification, or push notification to their mobile device. For example, a message such as "There is a food shortage at evacuation centers. Relief supplies are being quickly arranged. Please rest assured if you are feeling anxious" is displayed.

[0704] Step 7:

[0705] server

[0706] The server periodically receives and analyzes new data and updates the information. Every time new data is sent, the generating AI reanalyzes it and updates the information based on the latest state. The updated information is then resent to the device, and the display content is updated in real time.

[0707] This procedure allows users at evacuation shelters in disaster areas to quickly and accurately obtain the information they need. Furthermore, by utilizing the emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a sense of security.

[0708] Example 2

[0709] 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."

[0710] Conventional information provision systems in disaster areas have difficulty in providing accurate information quickly, and in particular have been unable to provide information that takes into account the user's emotions. As a result, victims are prone to feeling anxious and stressed, and are sometimes unable to obtain accurate information. Furthermore, if information from multiple sources is not cross-checked, there is a risk that unreliable information will be provided.

[0711] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0712] In this invention, the server includes a terminal device that uses sensors, cameras, and a voice input device to collect environmental data of the disaster area and input data from the user, a terminal device that uses an emotion engine to collect user emotion data, a server device that receives and analyzes the data transmitted from the terminal device, a server device that generates accurate information based on the analyzed data and emotion data using a generation AI, and a device that displays the generated information on the display of the terminal device and sends voice notifications and push notifications to mobile devices. This enables the provision of fast and accurate information in disaster areas and information that takes user emotions into consideration and gives a sense of security.

[0713] "Terminal devices" are devices that are installed in disaster areas and evacuation shelters, connect to the Internet via a satellite network, and use sensors, cameras, and voice input devices to collect environmental data and input data from users.

[0714] An "emotion engine" is a software or hardware system that analyzes a user's facial expressions and voice and collects the user's emotional data.

[0715] A "server device" is a computer system that receives and analyzes data sent from a terminal device.

[0716] "Generative AI" is an artificial intelligence algorithm or software that resides within a server device and generates accurate information based on analyzed data and emotional data.

[0717] An "information providing device" is a device for providing generated information to a user, and has the function of displaying information on the display of a terminal device and providing voice notification and push notification to a mobile device.

[0718] A "cross-checking means" is a process or algorithm by which a server device verifies the integrity of data sent from multiple terminal devices and cross-checks the data to increase the reliability of the information.

[0719] The system of the present invention is designed to provide accurate information in disaster-stricken areas and is also combined with an emotion engine that recognizes and analyzes user emotions. This system consists of a terminal device, a server device, a generation AI, and an information providing device.

[0720] Roles and operations of terminal devices

[0721] The terminal devices are installed in disaster areas, such as evacuation shelters. They are equipped with sensors, cameras, and voice input devices, which can be used to collect real-time data such as temperature, humidity, population density, and damage status. They also have a built-in emotion engine that can analyze the user's facial expressions and voice to collect emotional data. The terminal devices are connected to a network via satellite and transmit the collected data to a server device.

[0722] Roles and operations of server devices

[0723] The server device receives data sent from the terminal devices. The server device checks the consistency of the received environmental data and emotion data and cross-checks the information obtained from multiple terminal devices, thereby increasing the reliability of the data. The server device uses a generative AI model written in Python (e.g., GPT-3) to generate accurate information based on the analyzed data.

[0724] Role and behavior of generative AI

[0725] The AI ​​generates accurate and reliable information in a format that is easy for humans to understand, based on the data and emotional data analyzed by the server. For example, if a cross-check confirms that "food is in short supply at a specific evacuation shelter," it generates an appropriate message taking into account the user's emotional data. If the user is feeling anxious, it generates a reassuring message such as, "We are arranging to alleviate your anxiety and quickly provide food."

[0726] Roles and operations of information providing devices

[0727] The information provision device provides users with the information generated by the AI. Specifically, it displays the information on the terminal device's display, providing users with accurate information in real time. It also provides voice notifications and push notifications to mobile devices based on the analysis results of the emotion engine.

[0728] Specific examples

[0729] 1. Setting up the shelter

[0730] Terminal devices are installed in evacuation shelters and connected to a satellite network. Sensors and cameras are activated to collect information on the surrounding environment (temperature, humidity, population density, damage status, etc.). An emotion engine is also activated to analyze the user's facial expressions and voice.

[0731] 2. User input

[0732] The user inputs into the terminal device, "There is a shortage of food at the evacuation shelter." At this time, the emotion engine analyzes the user's facial expressions and voice and transmits the data to the server device as the user's emotion data.

[0733] 3. Data analysis and information generation

[0734] The server analyzes the received data and emotion data, cross-checking multiple similar reports. The AI ​​generator confirms the report that "food shortages are occurring at shelters A, B, and C," and generates a specific message based on the user's emotion. For example, if the user is feeling anxious, it will provide a reassuring message such as, "We are arranging to alleviate your anxiety and provide food promptly."

[0735] 4. Provision of Information

[0736] The generated information is displayed on the terminal device's display and provided to users at the evacuation shelter. For example, a message such as, "There is a food shortage. We are arranging relief supplies based on this information. If you are feeling anxious, please rest assured; we are responding quickly."

[0737] Prompt Sentence Examples

[0738] "Please let us know the current temperature and humidity at the evacuation center in real time. Also, please let us know about any food shortages."

[0739] "Generate and present messages that make users feel safe in the evacuation shelter. Emotional data is unsettling."

[0740] This system allows disaster victims to obtain quick and accurate information, enabling effective support for relief efforts. In addition, by utilizing the emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a greater sense of security.

[0741] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0742] Step 1: Collect data from the device

[0743] How it works: The device is installed in an evacuation center and connected to the Internet via satellite. Sensors and cameras are activated to collect real-time data such as temperature, humidity, population density, and damage status. The emotion engine analyzes the user's facial expressions and voice to collect emotional data. The device then sends all collected data to a server.

[0744] Input: Real-time data on temperature, humidity, population density, damage status, and user facial and voice data

[0745] Output: Collected environmental data and emotional data (e.g., temperature 30°C, humidity 70%, emotion = anxiety)

[0746] Step 2: User enters information

[0747] Specific operation: The user inputs information such as "There is a food shortage at the evacuation shelter" into the device. The device receives this information, and the emotion engine analyzes the user's facial expressions and voice to generate emotion data. The device then sends this data to the server.

[0748] Input: User-supplied text (e.g., "Food shortage at evacuation centers")

[0749] Output: Text information and analyzed emotion data (e.g. emotion = anxiety)

[0750] Step 3: Server receives data

[0751] Specific operation: The server receives data sent from the device. Examples include temperature, humidity, population density, damage status, user input information, and emotional data. The server stores all received data in a database.

[0752] Input: Data sent from the device (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[0753] Output: Received data stored in a database

[0754] Step 4: Data analysis by the server

[0755] Specific operation: The server checks the integrity of the data stored in the database and performs cross-checks to improve the reliability of the data. It checks whether the data is consistent and whether there are any outliers.

[0756] Input: Data stored in the database (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[0757] Output: Trusted data with integrity checks

[0758] Step 5: Information generation by generative AI

[0759] Specific operation: The server inputs the data that has passed the cross-check into the generation AI. Based on this, the generation AI generates information in a format that is easy for humans to understand. For example, it might generate information such as "There is a food shortage at shelters A, B, and C," and then incorporate emotional data to create a reassuring message such as "We are responding quickly."

[0760] Input: Reliable data after cross-checking (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[0761] Output: Generated information (e.g., "There is a food shortage at shelters A, B, and C. We are responding quickly, so please wait without worry.")

[0762] Step 6: Notify users through informational means

[0763] Specific operation: The information generated by the generation AI is displayed on the device's display. In addition, based on the analysis results of the emotion engine, voice notifications and push notifications are also sent to the mobile device.

[0764] Input: Generated information (e.g., "There is a food shortage at shelters A, B, and C. We are responding quickly, so please wait without worry.")

[0765] Output: Information displayed on the device display, audio notification, push notification to mobile device

[0766] The above steps will enable the provision of fast and accurate information in disaster-stricken areas, thereby reducing user anxiety.

[0767] (Application example 2)

[0768] 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."

[0769] In disaster-stricken areas, it is important to provide accurate information and generate information that takes into account the emotions of users. In particular, in fields such as food delivery services, it is necessary to accurately grasp users' emotions and respond accordingly. However, conventional systems have been inadequate in recognizing and reflecting emotions. This has resulted in an incomplete user experience and has made it difficult to respond efficiently.

[0770] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means, adjustment means, and prompt generation means. This makes it possible to analyze the user's emotion data, adjust the content and format of information based on that, and input the information as a prompt sentence into the generation AI model, thereby enabling individual responses that take the user's emotions into consideration.

[0771] "Terminal means" refers to a device that is installed in a disaster area or a service site, connects to a network, and collects and transmits data.

[0772] The "server means" is a central processing unit that receives data sent from the terminal means, analyzes it, and generates necessary information.

[0773] The "generation means" refers to a process or system that automatically generates accurate information based on the data analyzed by the server means.

[0774] "Information provision means" refers to means such as a display, voice notification, or push notification for providing the generated information to the user.

[0775] The "emotion engine means" is a combination of software and hardware for recognizing and analyzing the user's emotions.

[0776] "Adjustment means" refers to a process or system for adjusting the content and format of the information provided based on the analyzed emotional data.

[0777] "Cross-checking means" refers to means used to check the consistency of data sent from multiple users and increase the reliability of the data.

[0778] A "prompt generation means" is a means of inputting information based on the user's emotions into a generative AI model as a prompt sentence.

[0779] A "generative AI model" is an artificial intelligence model that automatically generates meaningful information based on input data.

[0780] A "prompt sentence" is an input sentence that causes a generative AI model to output specific information.

[0781] A system for carrying out the present invention includes the following means.

[0782] 1. Roles and operations of terminal means

[0783] The terminals will be installed at evacuation centers and food delivery service sites. They are connected to a network via satellite and equipped with sensors, cameras, and voice input devices. These sensors and input devices collect real-time data such as temperature, humidity, damage status, and the user's facial expressions and voice. In particular, the emotion engine analyzes the user's emotional data and sends the data based on that to a server.

[0784] 2. Roles and Operations of Server Means

[0785] The server receives and analyzes the data and emotional data sent from the terminals. The server uses a cross-checking means to confirm the consistency of information from multiple users and increase its reliability. It also has an adjustment means that adjusts the content and format of the information based on the emotional data. The adjusted data is then generated as a prompt sentence to be input into the generative AI model using a prompt generation means.

[0786] 3. Role and operation of the generating means

[0787] The generative AI model generates accurate information that takes into consideration the user's emotions based on the data analyzed on the server and emotional data. For example, if the user is feeling anxious, it generates a reassuring message such as, "We are arranging to alleviate your anxiety and quickly deliver food."

[0788] 4. Roles and Functions of Information Provision Means

[0789] The generated information is displayed on the device screen and is also provided to the user via voice notifications and push notifications to their mobile device. The information is provided in an appropriate format and with appropriate content based on emotional data, giving the user a sense of security.

[0790] Specific examples

[0791] A food delivery service collects emotional data when a user places an order.

[0792] 1. Device-based data collection and sentiment analysis:

[0793] When a user places an order from their smartphone, the system uses a camera and voice input device to analyze their facial expressions and voice and recognize whether they are in a hurry.

[0794] 2. Server-based data analysis and prompt generation:

[0795] The server analyzes the collected user emotional data and inputs the prompt sentence, "Please tell me what to do if I'm in a hurry," into the generative AI model.

[0796] 3. Information generation using generative AI models:

[0797] The generative AI model generates messages based on the emotion of "being in a hurry," such as, "We will start cooking immediately and arrange for delivery staff. We are doing our best to avoid keeping you waiting."

[0798] Prompt Sentence Examples

[0799] "Please tell me what to do if I'm in a hurry."

[0800] This system will enable disaster-stricken areas and food delivery services to accurately grasp user emotions and provide information tailored to them, resulting in an improved user experience and more efficient responses.

[0801] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0802] Step 1:

[0803] The device collects input information from the user and environmental sensor data. Specifically, it uses the camera and voice input device of a smartphone or robot to capture the user's facial expressions and voice, and simultaneously collects data such as temperature, humidity, and surrounding damage. The inputs include the user's order information, facial image, voice data, and sensor data. The output is sent to the server.

[0804] Step 2:

[0805] The device passes the collected facial image and voice data to the emotion engine means for analysis. The specific analysis operation involves using an emotion recognition library (e.g., DeepFace) to extract the main emotion felt by the user (e.g., feeling rushed or anxious). The facial image and voice data are used as input. The output is generated as data on the user's main emotion, and this data is sent to the server.

[0806] Step 3:

[0807] The server receives the user's emotion data and input information sent from the device. Specifically, it retrieves the data via an HTTP request and formats it into a format suitable for analysis. As input, it receives the user's order data, emotion data, and environmental sensor data. As output, it creates a dataset that has undergone preprocessing for data analysis.

[0808] Step 4:

[0809] The server cross-checks the received data. Specifically, it compares and examines similar data sent from multiple devices to confirm the reliability of the data. It uses a cross-checking method. As input, it uses the same type of data set sent by multiple users. As output, it generates data whose reliability has been confirmed.

[0810] Step 5:

[0811] The server uses a prompt generation means to generate a prompt sentence to be input to the generative AI model based on the user's emotional data. Specifically, if the emotional data indicates "I'm in a hurry," the server creates a prompt sentence saying, "Please tell me what to do if I'm in a hurry." The emotional data is used as input. The server generates a prompt sentence to be input to the generative AI model as output.

[0812] Step 6:

[0813] The server uses the generative AI model to generate an appropriate response message. Specifically, the prompt sentence is passed to the model as input, and the message generated by the AI ​​is obtained. For example, if the prompt sentence is "Please tell me what to do if I'm in a hurry," the generated message will be "We will start cooking immediately and arrange for a delivery person. We are doing our best to avoid keeping you waiting." The prompt sentence is used as input. The response message created by the generative AI model is obtained as output.

[0814] Step 7:

[0815] The server sends the generated message to the device and provides it to the user using the device's information provision means. Specifically, the message is not only displayed on the screen, but also provided as a voice notification or push notification. The generated message is used as input. The message is displayed on the user's smartphone or device as output.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] [Third embodiment]

[0820] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0821] 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.

[0822] 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).

[0823] 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.

[0824] 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.

[0825] 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).

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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."

[0832] The system according to the present invention is intended to provide accurate information in disaster areas, and is mainly implemented in the following form.

[0833] First, the system includes a terminal that connects to the network via satellite, a server that receives and analyzes data sent from the terminal, a generation AI that generates accurate information based on the analyzed data, and an information provision means that provides the generated information to users.

[0834] Device role and operation

[0835] Terminal

[0836] The terminals are installed in disaster-stricken areas, such as evacuation centers, and are connected to the Internet via satellite. They are equipped with sensors and cameras to collect real-time data such as temperature, humidity, and damage status. They also collect information entered by users (e.g., the status of evacuation centers, food shortages, etc.).

[0837] Server Roles and Operations

[0838] server

[0839] The server receives the data sent from the devices and analyzes it using the generating AI. Specifically, the server checks the integrity of the data and cross-checks information from multiple devices to increase reliability. For example, if the same information is sent from multiple evacuation centers, it will determine that the information is accurate.

[0840] Role and behavior of generative AI

[0841] Generation AI

[0842] The AI ​​generates accurate and reliable information based on the data analyzed by the server. For example, if the information that "a certain evacuation shelter is short of food" is confirmed by cross-checking, the AI ​​creates a specific message saying, "There is a food shortage at this evacuation shelter."

[0843] Roles and operations of information provision means

[0844] Information provision means

[0845] The information provided by the AI ​​is presented to users via a variety of methods, including displaying information on the evacuation center's screen, allowing users to obtain accurate information in real time. Information can also be provided via voice notifications and push notifications to mobile devices.

[0846] Specific examples

[0847] 1. Setting up the shelter

[0848] Terminals are installed in evacuation centers and connected to a satellite network. They use sensors and cameras to collect information about the surrounding environment (temperature, humidity, population, damage, etc.).

[0849] 2. User input

[0850] The user types "There is a food shortage at the evacuation center" into the device, and the information is sent from the device to the server.

[0851] 3. Data analysis and information generation

[0852] The server analyzes the received data and cross-checks multiple similar reports. The generator AI generates an accurate message based on the information that "food is in short supply."

[0853] 4. Provision of Information

[0854] The generated information is displayed on the device's screen, and users at the evacuation center are notified with messages such as, "There is a food shortage. We are arranging relief supplies based on this information."

[0855] This system allows disaster victims to quickly and accurately obtain the information they need. For example, if there is a shortage of food or relief supplies, or if local traffic information is needed, the system will respond appropriately in real time. This will minimize confusion in the disaster-stricken areas and support effective relief efforts.

[0856] The processing flow will be explained below.

[0857] Step 1:

[0858] Terminal

[0859] The terminal is installed in the evacuation center and connects to the network via satellite. At this time, the terminal is supplied with power and basic settings (location information, basic information about the evacuation center, etc.) are configured. The sensors and cameras are activated and begin collecting environmental data about the evacuation center (temperature, humidity, images, etc.).

[0860] Step 2:

[0861] User

[0862] Users input the status of the evacuation shelter into the device. Specifically, they use the device's touch panel or voice input function to report information such as "food is in short supply" or "the toilets are out of order." The device temporarily stores this user-entered data.

[0863] Step 3:

[0864] Terminal

[0865] The terminal formats the collected environmental data and user-input data and transmits it to the server via satellite communication. At this time, it checks whether the data was transmitted correctly and attempts to retransmit it if an error occurs.

[0866] Step 4:

[0867] server

[0868] The server receives data sent from the devices. It passes the received data to the generation AI, which begins analyzing it. It cross-checks similar information sent from multiple devices to confirm the consistency and reliability of the data. For example, if information that "food is running low" is sent from multiple evacuation centers, it will match this information.

[0869] Step 5:

[0870] Server (Generating AI)

[0871] The AI ​​then generates accurate information based on the cross-checked data. For example, if a report is confirmed that "food is in short supply at shelters A, B, and C," the AI ​​generates a specific message saying, "There is a food shortage at these shelters."

[0872] Step 6:

[0873] Information provision means

[0874] The generated information is sent from the server to the device and displayed on the device's display. It can also be provided to the user as a voice notification or a push notification to the mobile device, as needed. For example, a message such as "There is a food shortage. We are currently arranging relief supplies based on this information" can be displayed.

[0875] Step 7:

[0876] server

[0877] The server periodically receives and analyzes new data and updates the information. Every time new data is sent, the generating AI reanalyzes it and updates the information based on the latest state. The updated information is then sent back to the device, and the display is updated in real time.

[0878] This process will enable accurate information to be provided at evacuation centers in disaster-stricken areas, enabling support activities to be carried out quickly and effectively.

[0879] Example 1

[0880] 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."

[0881] In disaster-stricken areas, it was difficult to quickly and accurately collect information and provide it to victims with reliable information, which led to delays in relief efforts and confusion over information, resulting in victims not receiving the support they needed in a timely manner.

[0882] 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.

[0883] In this invention, the server includes a terminal means, a means for receiving and analyzing sensor and user input data, a generating AI model means for generating highly reliable information, and a means for displaying or announcing the generated information, thereby enabling the rapid provision of highly reliable information based on data collected in disaster areas.

[0884] "Disaster area" refers to an area that has been affected by a natural or man-made disaster.

[0885] A "satellite network" refers to a network system that provides internet and communication services via artificial satellites.

[0886] "Terminal means" refers to electronic devices that are installed in the disaster area and that collect and transmit data.

[0887] "Server means" refers to a computer system for receiving and analyzing data sent from terminal means.

[0888] "Sensor" refers to a device that measures environmental data such as temperature and humidity.

[0889] "User-input data" refers to information provided by a User through a Terminal.

[0890] "Generative AI model" refers to an artificial intelligence model that generates reliable information based on data analyzed by a server means.

[0891] "Cross-checking measures" refers to the process of collating information from multiple data sources and assessing its consistency and reliability.

[0892] "Information providing means" refers to a device or method for notifying the user of the generated information.

[0893] "Display" refers to a device that visually displays generated information.

[0894] "Audio notification" refers to a means of conveying generated information to the user audibly.

[0895] "Data analysis means" refers to the server's function of verifying the integrity of collected data and performing any necessary cleansing or cross-checking.

[0896] "Cellular terminal" refers to a mobile device such as a mobile phone or smartphone.

[0897] This invention is a system for providing rapid and accurate information in disaster-stricken areas, and is mainly composed of terminal means, server means, generation AI model means, and information provision means. The specific operation and implementation method of each means will be explained below.

[0898] Terminal means

[0899] The terminal means is an electronic device installed in evacuation shelters in disaster areas and connected to the Internet via a satellite network. This terminal is equipped with sensors to collect environmental data such as temperature and humidity, and a camera to capture images of the damage. It also provides an interface for users to input information about the evacuation shelter situation and shortages of supplies.

[0900] As a specific example of use, a terminal means is installed in a shelter and collects information on the surrounding situation in real time using sensors and cameras. Furthermore, when a user inputs "There is a shortage of food at the shelter," this information is recorded in the terminal means. The terminal means packages this data and transmits it to the server means in the next phase.

[0901] Server Means

[0902] The server means is a computer system that receives and analyzes data sent from the terminal means. First, it checks the integrity of the received data and performs data cleansing if there are missing or invalid values. Then it cross-checks the same type of data sent from multiple terminals and evaluates its reliability. For example, if the same information is reported from multiple evacuation shelters, it is determined that the information is accurate.

[0903] The server means stores the received data in a database and then prepares to provide the data to the generative AI model means.

[0904] Generative AI model means

[0905] The generating AI model means is an artificial intelligence model that generates reliable information based on the data analyzed by the server means. The AI ​​model receives the analyzed data as input and generates a specific and reliable message. For example, it creates a notification message such as "There is a food shortage. Based on this information, relief supplies are being arranged."

[0906] Information provision means

[0907] The information provision means plays a role in providing the information generated by the generative AI model means to the user. The information is displayed on the display of the terminal means so that the user can obtain accurate information in real time. The information can also be provided in multiple ways, such as voice notification or push notification to the mobile device.

[0908] Specific examples

[0909] 1. Setting up the shelter

[0910] Terminal devices are installed in evacuation centers and connected to a satellite network. They use sensors and cameras to collect information on the surrounding environment (temperature, humidity, population, damage status, etc.) in real time.

[0911] 2. User input

[0912] The user inputs "There is a shortage of food at the evacuation shelter" into the terminal means. The information is transmitted from the terminal means to the server means.

[0913] 3. Data analysis and information generation

[0914] The server means analyzes the received data and cross-checks multiple similar reports. The generative AI model means generates an accurate message based on the information that "food is in short supply."

[0915] 4. Provision of Information

[0916] The generated information is displayed on the terminal display, and users at the evacuation shelter are notified, such as, "There is a food shortage. We are arranging relief supplies based on this information." It is also possible to send voice notifications and push notifications to mobile devices.

[0917] Prompt Sentence Examples

[0918] 1. Prompt example 1

[0919] We have installed devices in evacuation shelters in the affected areas that use sensors and cameras to collect information on temperature, humidity, and damage. Please enter information on the evacuation shelter situation and food shortages.

[0920] 2. Prompt example 2

[0921] Based on the data collected on the device, the server analyzed and cross-checked the data. Based on this information, the AI ​​generated the message "Food is running low." Please check the generated notification content.

[0922] 3. Prompt example 3

[0923] Based on the above information, a notice was sent to the terminal displays at the evacuation center. Please check the status of food supply arrangements.

[0924] As described above, by having each means work in coordination, it becomes possible to provide disaster victims with quick and accurate information and provide effective support.

[0925] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0926] Step 1: Placement and connection of terminal means

[0927] Specific operation: The terminal means is installed at an evacuation shelter in the disaster area. A technician installs the terminal means and establishes an Internet connection using a satellite antenna.

[0928] Input: Information about evacuation shelters and their locations

[0929] Output: Internet connection established and terminal means operational

[0930] Step 2: Start the sensors and cameras

[0931] Specific operation: The system administrator remotely activates the sensors and cameras of the terminal device, which completes preparations for data collection.

[0932] Input: Sensor and camera initial configuration information

[0933] Output: Sensors and cameras are up and running and ready to collect data.

[0934] Step 3: Collect environmental data

[0935] Specific operation: The terminal device uses sensors to collect environmental data such as temperature, humidity, and population in real time, and also uses a camera to take photos of the damage situation and save the image data.

[0936] Input: Local environmental information of the evacuation shelter

[0937] Output: Collected environmental and image data

[0938] Step 4: User input

[0939] Specific operation: The user uses the input interface of the terminal means to input information such as "food shortage at the evacuation center." The terminal means records this information.

[0940] Input: User-entered shelter status information

[0941] Output: User input data recorded on the terminal means

[0942] Step 5: Packaging and preparing the data for transmission

[0943] Specific operation: The terminal means packages the collected environmental data and user input data into one data packet and prepares to send it to the server means.

[0944] Input: Collected environmental data and user-entered data

[0945] Output: Data packets ready to be sent

[0946] Step 6: Sending data to the server

[0947] Specific operation: The terminal means transmits data packets to the server means via satellite communication. The data is encrypted and transmitted.

[0948] Input: Data packet ready to send

[0949] Output: Data packets received by the server

[0950] Step 7: Receiving and storing data

[0951] Specific operation: The server means receives the data packets sent from the terminal means and stores them in a database for analysis.

[0952] Input: Data packets sent from the terminal means

[0953] Output: Saved data

[0954] Step 8: Data integrity check and cleansing

[0955] Specific operation: The server means checks the integrity of the data and performs data cleansing if there are missing or invalid values.

[0956] Input: Saved data

[0957] Output: Cleansed data with integrity checks

[0958] Step 9: Cross-check from multiple devices

[0959] Specific operation: The server means cross-checks the same type of data sent from different terminal means and evaluates its reliability. For example, if multiple evacuation centers report the same content, such as "food shortages," the information is judged to be accurate.

[0960] Input: Homogeneous data sent from multiple terminal means

[0961] Output: Data whose reliability has been assessed by cross-checking

[0962] Step 10: Generate information using generative AI models

[0963] Specific operation: The server executes the generative AI model based on the analyzed data to generate a reliable message, such as "There is a food shortage. Based on this information, we are arranging relief supplies."

[0964] Input: Data whose reliability has been assessed by cross-checking

[0965] Output: Highly reliable informational messages generated

[0966] Step 11: Prepare to distribute information

[0967] Specific operation: The server means assembles the generated information messages into packets for delivery and prepares them for transmission.

[0968] Input: Generated information message

[0969] Output: Data packets ready for delivery

[0970] Step 12: Sending information to the terminal means

[0971] Specific operation: The server means transmits a distribution data packet to the terminal means.

[0972] Input: Data packets ready for delivery

[0973] Output: Information received by terminal means

[0974] Step 13: Providing information through display and audio notifications

[0975] Specific operation: The terminal displays the received information on the display of the evacuation center, providing users with accurate information in real time, and also provides voice notifications as necessary.

[0976] Input: Information received by terminal means

[0977] Output: Information displayed on the screen and audio notifications

[0978] Step 14: Push notification to mobile device

[0979] Specific operation: The terminal means or the server means also sends a push notification to the mobile device, so that the user can check detailed information on their mobile device.

[0980] Input: Information generated by terminal or server means.

[0981] Output: Push notification received on mobile device

[0982] (Application example 1)

[0983] 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."

[0984] In conventional disaster response systems, information collection and provision is often not done in real time, making it difficult to provide victims with quick and accurate information. In addition, the means of providing information are limited, and a lack of adaptive evacuation information, especially in dangerous situations, has been a problem. This has led to the risk that victims are unable to take appropriate action, and the damage may worsen.

[0985] 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.

[0986] In this invention, the server includes a terminal means connected to the network via a satellite, a means for receiving and analyzing data transmitted from the terminal means, a generating means for generating accurate information based on the data analyzed by the server means, an information providing means using a smart device (including smart glasses) for providing the generated information to users, a cross-checking means for checking the consistency of data transmitted from multiple users, and an adaptive evacuation information providing means based on location information. This enables prompt and accurate information to be provided in disaster-stricken areas, allowing disaster victims to take appropriate action.

[0987] "Terminal means" refers to a device that connects to a network via satellite and collects data using sensors and cameras in the disaster area.

[0988] The "server means" is a server device that receives and analyzes data sent from the terminal means.

[0989] The "analysis means" is a means for verifying the consistency of received data in the server means and analyzing the data.

[0990] The "generation means" is a means for generating accurate information based on the analyzed data.

[0991] A "smart device" is a device that provides generated information to a user, and includes smart glasses and the like.

[0992] The "information providing means" is a means for providing the information generated by the generating means to the user.

[0993] A "cross-check means" is a means for checking the consistency of data sent from multiple users.

[0994] An "adaptive evacuation information provision means" is a means for providing users with optimal evacuation information in real time based on location information.

[0995] The system according to the present invention is for providing accurate information in real time in disaster areas, and is implemented in the following manner.

[0996] 1. Roles and operations of terminal means

[0997] The terminal means is installed in the disaster area and connected to the network via satellite. Specifically, it is a device installed in evacuation shelters and dangerous areas, and is equipped with sensors and cameras. This terminal collects the following data:

[0998] Temperature and humidity

[0999] Damage situation

[1000] Demographics

[1001] Users can use the terminal to input information such as the status of evacuation shelters and food shortages, which is then sent to the server.

[1002] 2. Roles and Operations of Server Means

[1003] The server means is a device that receives data sent from the terminal means and performs analysis processing. The server means processes the data using the following means:

[1004] Analysis method: Check the integrity of the received data and perform analysis.

[1005] Cross-checking measures: verifying the integrity of data submitted by multiple users.

[1006] Generation method: Generate accurate and reliable information based on the analyzed data.

[1007] Specifically, the server cross-checks the consistency of the data. For example, if multiple shelters report the same information, it determines that the information is accurate. As a result of this process, the generator generates specific information such as "food shortage."

[1008] 3. Roles and Functions of Information Provision Means

[1009] The information providing means is a device for providing the information generated by the generating means to the user. In particular, the present invention utilizes a smart device, such as smart glasses:

[1010] Smart glasses: Evacuation information and warnings are displayed on the screen, and voice notifications are also possible.

[1011] Location integration: Shows the nearest evacuation shelters and safe routes based on your current location.

[1012] Hardware / Software used

[1013] Hardware: Satellite-connected devices, smart glasses

[1014] Software: Cloud servers, analytical algorithms, generative AI (e.g., OpenAI's GPT model), speech synthesis engines (e.g., Google Text-to-Speech)

[1015] For example, the following prompts can be sent to the generative AI to provide real-time information:

[1016] Prompt Sentence Examples

[1017] "Disaster information: Earthquake occurred. Current location is city center. Please provide evacuation locations and safe routes."

[1018] Example

[1019] 1. Visual Indication:

[1020] The smart glasses' display read, "The nearest evacuation shelter is 500 meters north from your current location. Take the next right."

[1021] 2. Sound notification:

[1022] The smart glasses will play a voice notification saying, "An earthquake has occurred. Please evacuate immediately. Walk 500 meters to the right to reach the evacuation shelter."

[1023] This will enable disaster victims to take safe action based on prompt and accurate information, minimizing confusion in disaster-stricken areas and supporting effective relief efforts.

[1024] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1025] Step 1:

[1026] Data collection and transmission

[1027] Subject: Terminal

[1028] The device uses sensors and cameras installed in the affected area to collect data such as temperature, humidity, and damage status. It also collects information entered by the user, such as the status of evacuation shelters and food shortages. This data is collected in real time and sent to a server via satellite communication.

[1029] Input: Data from sensors and cameras, user input

[1030] Output: Sending collected data to a server

[1031] Step 2:

[1032] Data reception and integrity check

[1033] Subject: Server

[1034] The server receives the data sent from the terminal. It checks the consistency of the received data. If the same information is sent from multiple terminals, it determines that the information is correct and performs a cross-check.

[1035] Input: Data sent from the terminal

[1036] Output: Data with integrity checked

[1037] Step 3:

[1038] Data analysis

[1039] Subject: Server and Generative AI

[1040] The server analyzes the data whose integrity has been confirmed. By using analytical methods, complex data is statistically analyzed to determine the extent of damage and the status of evacuation shelters. The generation AI generates accurate and reliable information based on this analytical data.

[1041] Input: Integrity checked data

[1042] Output: Information generated by the generative AI

[1043] Step 4:

[1044] information generation

[1045] Subject: Generation AI

[1046] The generative AI generates specific messages based on data analysis. For example, it generates a specific notification such as, "There is a food shortage at this evacuation shelter." The generated information is then customized to be provided to the user.

[1047] Input: Parsed data

[1048] Output: The specific message generated

[1049] Step 5:

[1050] Information provision

[1051] Subject: Means of information provision (smart device)

[1052] The generated information is provided to users via smart devices (such as smart glasses). Real-time information such as the status of evacuation shelters and evacuation routes is provided via display and voice notification. Adaptive evacuation information tailored to the user's current location is also displayed based on location information.

[1053] Input: The specific message to be generated

[1054] Output: Providing information via smart devices

[1055] Illustrative prompt examples

[1056] "Disaster information: Earthquake occurred. Current location is city center. Please provide evacuation locations and safe routes."

[1057] This processing flow enables rapid, real-time information provision in disaster-stricken areas, allowing users to take appropriate action.

[1058] 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.

[1059] The system of the present invention is designed to provide accurate information in disaster areas and is also combined with an emotion engine that recognizes and analyzes user emotions. This system is mainly implemented in the following forms:

[1060] The system includes a terminal connected to a network via satellite, a server that receives and analyzes data transmitted from the terminal, a generation AI that generates accurate information based on the analyzed data, and an information providing means that provides the generated information to the user. Furthermore, the system is equipped with an emotion engine that recognizes the user's emotions.

[1061] Device role and operation

[1062] Terminal

[1063] The terminals are installed in disaster-stricken areas, such as evacuation shelters, and are connected to the Internet via satellite. They are equipped with sensors, cameras, and voice input devices to collect real-time data such as temperature, humidity, and damage status. They also have an emotion engine that collects emotional data from users' facial expressions and voice, in addition to input information from users.

[1064] Server Roles and Operations

[1065] server

[1066] The server receives the data and emotion data sent from the device and analyzes it using generative AI. Specifically, it checks the consistency of the data and cross-checks information from multiple devices to increase reliability. It also analyzes the user's emotion data and adjusts the content and format of the information provided based on that emotion.

[1067] Role and behavior of generative AI

[1068] Generation AI

[1069] The AI ​​generates accurate and reliable information based on the data and emotional data analyzed on the server. For example, if a cross-check confirms that there is a food shortage at a particular evacuation shelter, it generates an appropriate message taking into account the user's emotional data. For example, if the user is feeling anxious, a message that provides reassurance will be provided.

[1070] Roles and operations of information provision means

[1071] Information provision means

[1072] The information provided to users is generated by the AI. Specifically, the device displays the information on the evacuation center's display, allowing users to obtain accurate information in real time. Based on the analysis results of the emotion engine, voice notifications and push notifications are also sent to mobile devices.

[1073] Specific examples

[1074] 1. Setting up the shelter

[1075] The device is installed in the evacuation center and connected to a satellite network. The sensors and cameras are activated to collect information on the surrounding environment (temperature, humidity, population, damage status, etc.). The emotion engine is also activated to analyze the user's facial expressions and voice.

[1076] 2. User input

[1077] The user types into the device, "There is a food shortage at the evacuation center." At this time, the emotion engine analyzes the user's facial expressions and voice and sends the data to the server as the user's emotion data.

[1078] 3. Data analysis and information generation

[1079] The server analyzes the received data and emotion data, cross-checking multiple similar reports. The AI ​​generator confirms the report that "food shortages are occurring at shelters A, B, and C," and generates a specific message based on the user's emotion. For example, if the user is feeling anxious, it will provide a reassuring message such as, "We are arranging to alleviate your anxiety and provide food promptly."

[1080] 4. Provision of Information

[1081] The generated information is displayed on the device's display and provided to users at evacuation shelters. For example, a notification such as, "There is a food shortage. We are arranging relief supplies based on this information. If you are feeling anxious, please rest assured; we are responding quickly."

[1082] This system enables disaster victims to quickly and accurately obtain the information they need, effectively supporting relief efforts. Furthermore, by utilizing an emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a greater sense of security.

[1083] The processing flow will be explained below.

[1084] Step 1:

[1085] Terminal

[1086] The device is installed at the evacuation center and connects to the network via satellite. At this time, the device is supplied with power and location information and basic information about the evacuation center (such as capacity) are entered. Sensors and cameras are activated and begin collecting environmental data (temperature, humidity, damage status, etc.). The emotion engine is also activated, ready to collect the user's facial expressions and voice.

[1087] Step 2:

[1088] User

[1089] Users input information about the evacuation shelter situation into their device. For example, they can use the touch panel or voice input function to report information such as "food is in short supply" or "the toilets are out of order." At this time, the emotion engine analyzes the user's facial expressions and voice to generate emotion data.

[1090] Step 3:

[1091] Terminal

[1092] The device formats the collected environmental data, user input data, and emotion data and transmits them to the server via satellite communication. It checks whether the data was transmitted correctly and attempts to retry if a transmission error occurs.

[1093] Step 4:

[1094] server

[1095] The server receives the data and emotion data sent from the device. The received data is passed to the generation AI, which then begins analyzing the data. Similar information sent from multiple devices is cross-checked to confirm the consistency and reliability of the data. At this time, the user's emotion data is also used in the analysis.

[1096] Step 5:

[1097] Server (Generating AI)

[1098] The generation AI generates accurate information based on the cross-checked data. For example, if the cross-check confirms that "there is a food shortage at a particular evacuation shelter," it generates a message that provides reassurance based on the user's emotional data. For example, it could say, "There is a food shortage at this evacuation shelter. Please rest assured, relief supplies are being quickly arranged."

[1099] Step 6:

[1100] Information provision means

[1101] The generated information is sent from the server to the device. It is then provided to the user as a display, voice notification, or push notification to their mobile device. For example, a message such as "There is a food shortage at evacuation centers. Relief supplies are being quickly arranged. Please rest assured if you are feeling anxious" is displayed.

[1102] Step 7:

[1103] server

[1104] The server periodically receives and analyzes new data and updates the information. Every time new data is sent, the generating AI reanalyzes it and updates the information based on the latest state. The updated information is then resent to the device, and the display content is updated in real time.

[1105] This procedure allows users at evacuation shelters in disaster areas to quickly and accurately obtain the information they need. Furthermore, by utilizing the emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a sense of security.

[1106] Example 2

[1107] 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."

[1108] Conventional information provision systems in disaster areas have difficulty in providing accurate information quickly, and in particular have been unable to provide information that takes into account the user's emotions. As a result, victims are prone to feeling anxious and stressed, and are sometimes unable to obtain accurate information. Furthermore, if information from multiple sources is not cross-checked, there is a risk that unreliable information will be provided.

[1109] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1110] In this invention, the server includes a terminal device that uses sensors, cameras, and a voice input device to collect environmental data of the disaster area and input data from the user, a terminal device that uses an emotion engine to collect user emotion data, a server device that receives and analyzes the data transmitted from the terminal device, a server device that generates accurate information based on the analyzed data and emotion data using a generation AI, and a device that displays the generated information on the display of the terminal device and sends voice notifications and push notifications to mobile devices. This enables the provision of fast and accurate information in disaster areas and information that takes user emotions into consideration and gives a sense of security.

[1111] "Terminal devices" are devices that are installed in disaster areas and evacuation shelters, connect to the Internet via a satellite network, and use sensors, cameras, and voice input devices to collect environmental data and input data from users.

[1112] An "emotion engine" is a software or hardware system that analyzes a user's facial expressions and voice and collects the user's emotional data.

[1113] A "server device" is a computer system that receives and analyzes data sent from a terminal device.

[1114] "Generative AI" is an artificial intelligence algorithm or software that resides within a server device and generates accurate information based on analyzed data and emotional data.

[1115] An "information providing device" is a device for providing generated information to a user, and has the function of displaying information on the display of a terminal device and providing voice notification and push notification to a mobile device.

[1116] A "cross-checking means" is a process or algorithm by which a server device verifies the integrity of data sent from multiple terminal devices and cross-checks the data to increase the reliability of the information.

[1117] The system of the present invention is designed to provide accurate information in disaster-stricken areas and is also combined with an emotion engine that recognizes and analyzes user emotions. This system consists of a terminal device, a server device, a generation AI, and an information providing device.

[1118] Roles and operations of terminal devices

[1119] The terminal devices are installed in disaster areas, such as evacuation shelters. They are equipped with sensors, cameras, and voice input devices, which can be used to collect real-time data such as temperature, humidity, population density, and damage status. They also have a built-in emotion engine that can analyze the user's facial expressions and voice to collect emotional data. The terminal devices are connected to a network via satellite and transmit the collected data to a server device.

[1120] Roles and operations of server devices

[1121] The server device receives data sent from the terminal devices. The server device checks the consistency of the received environmental data and emotion data and cross-checks the information obtained from multiple terminal devices, thereby increasing the reliability of the data. The server device uses a generative AI model written in Python (e.g., GPT-3) to generate accurate information based on the analyzed data.

[1122] Role and behavior of generative AI

[1123] The AI ​​generates accurate and reliable information in a format that is easy for humans to understand, based on the data and emotional data analyzed by the server. For example, if a cross-check confirms that "food is in short supply at a specific evacuation shelter," it generates an appropriate message taking into account the user's emotional data. If the user is feeling anxious, it generates a reassuring message such as, "We are arranging to alleviate your anxiety and quickly provide food."

[1124] Roles and operations of information providing devices

[1125] The information provision device provides users with the information generated by the AI. Specifically, it displays the information on the terminal device's display, providing users with accurate information in real time. It also provides voice notifications and push notifications to mobile devices based on the analysis results of the emotion engine.

[1126] Specific examples

[1127] 1. Setting up the shelter

[1128] Terminal devices are installed in evacuation shelters and connected to a satellite network. Sensors and cameras are activated to collect information on the surrounding environment (temperature, humidity, population density, damage status, etc.). An emotion engine is also activated to analyze the user's facial expressions and voice.

[1129] 2. User input

[1130] The user inputs into the terminal device, "There is a shortage of food at the evacuation shelter." At this time, the emotion engine analyzes the user's facial expressions and voice and transmits the data to the server device as the user's emotion data.

[1131] 3. Data analysis and information generation

[1132] The server analyzes the received data and emotion data, cross-checking multiple similar reports. The AI ​​generator confirms the report that "food shortages are occurring at shelters A, B, and C," and generates a specific message based on the user's emotion. For example, if the user is feeling anxious, it will provide a reassuring message such as, "We are arranging to alleviate your anxiety and provide food promptly."

[1133] 4. Provision of Information

[1134] The generated information is displayed on the terminal device's display and provided to users at the evacuation shelter. For example, a message such as, "There is a food shortage. We are arranging relief supplies based on this information. If you are feeling anxious, please rest assured; we are responding quickly."

[1135] Prompt Sentence Examples

[1136] "Please let us know the current temperature and humidity at the evacuation center in real time. Also, please let us know about any food shortages."

[1137] "Generate and present messages that make users feel safe in the evacuation shelter. Emotional data is unsettling."

[1138] This system allows disaster victims to obtain quick and accurate information, enabling effective support for relief efforts. In addition, by utilizing the emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a greater sense of security.

[1139] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1140] Step 1: Collect data from the device

[1141] How it works: The device is installed in an evacuation center and connected to the Internet via satellite. Sensors and cameras are activated to collect real-time data such as temperature, humidity, population density, and damage status. The emotion engine analyzes the user's facial expressions and voice to collect emotional data. The device then sends all collected data to a server.

[1142] Input: Real-time data on temperature, humidity, population density, damage status, and user facial and voice data

[1143] Output: Collected environmental data and emotional data (e.g., temperature 30°C, humidity 70%, emotion = anxiety)

[1144] Step 2: User enters information

[1145] Specific operation: The user inputs information such as "There is a food shortage at the evacuation shelter" into the device. The device receives this information, and the emotion engine analyzes the user's facial expressions and voice to generate emotion data. The device then sends this data to the server.

[1146] Input: User-supplied text (e.g., "Food shortage at evacuation centers")

[1147] Output: Text information and analyzed emotion data (e.g. emotion = anxiety)

[1148] Step 3: Server receives data

[1149] Specific operation: The server receives data sent from the device. Examples include temperature, humidity, population density, damage status, user input information, and emotional data. The server stores all received data in a database.

[1150] Input: Data sent from the device (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[1151] Output: Received data stored in a database

[1152] Step 4: Data analysis by the server

[1153] Specific operation: The server checks the integrity of the data stored in the database and performs cross-checks to improve the reliability of the data. It checks whether the data is consistent and whether there are any outliers.

[1154] Input: Data stored in the database (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[1155] Output: Trusted data with integrity checks

[1156] Step 5: Information generation by generative AI

[1157] Specific operation: The server inputs the data that has passed the cross-check into the generation AI. Based on this, the generation AI generates information in a format that is easy for humans to understand. For example, it might generate information such as "There is a food shortage at shelters A, B, and C," and then incorporate emotional data to create a reassuring message such as "We are responding quickly."

[1158] Input: Reliable data after cross-checking (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[1159] Output: Generated information (e.g., "There is a food shortage at shelters A, B, and C. We are responding quickly, so please wait without worry.")

[1160] Step 6: Notify users through informational means

[1161] Specific operation: The information generated by the generation AI is displayed on the device's display. In addition, based on the analysis results of the emotion engine, voice notifications and push notifications are also sent to the mobile device.

[1162] Input: Generated information (e.g., "There is a food shortage at shelters A, B, and C. We are responding quickly, so please wait without worry.")

[1163] Output: Information displayed on the device display, audio notification, push notification to mobile device

[1164] The above steps will enable the provision of fast and accurate information in disaster-stricken areas, thereby reducing user anxiety.

[1165] (Application example 2)

[1166] 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."

[1167] In disaster-stricken areas, it is important to provide accurate information and generate information that takes into account the emotions of users. In particular, in fields such as food delivery services, it is necessary to accurately grasp users' emotions and respond accordingly. However, conventional systems have been inadequate in recognizing and reflecting emotions. This has resulted in an incomplete user experience and has made it difficult to respond efficiently.

[1168] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means, adjustment means, and prompt generation means. This makes it possible to analyze the user's emotion data, adjust the content and format of information based on that, and input the information as a prompt sentence into the generation AI model, thereby enabling individual responses that take the user's emotions into consideration.

[1169] "Terminal means" refers to a device that is installed in a disaster area or a service site, connects to a network, and collects and transmits data.

[1170] The "server means" is a central processing unit that receives data sent from the terminal means, analyzes it, and generates necessary information.

[1171] The "generation means" refers to a process or system that automatically generates accurate information based on the data analyzed by the server means.

[1172] "Information provision means" refers to means such as a display, voice notification, or push notification for providing the generated information to the user.

[1173] The "emotion engine means" is a combination of software and hardware for recognizing and analyzing the user's emotions.

[1174] "Adjustment means" refers to a process or system for adjusting the content and format of the information provided based on the analyzed emotional data.

[1175] "Cross-checking means" refers to means used to check the consistency of data sent from multiple users and increase the reliability of the data.

[1176] A "prompt generation means" is a means of inputting information based on the user's emotions into a generative AI model as a prompt sentence.

[1177] A "generative AI model" is an artificial intelligence model that automatically generates meaningful information based on input data.

[1178] A "prompt sentence" is an input sentence that causes a generative AI model to output specific information.

[1179] A system for carrying out the present invention includes the following means.

[1180] 1. Roles and operations of terminal means

[1181] The terminals will be installed at evacuation centers and food delivery service sites. They are connected to a network via satellite and equipped with sensors, cameras, and voice input devices. These sensors and input devices collect real-time data such as temperature, humidity, damage status, and the user's facial expressions and voice. In particular, the emotion engine analyzes the user's emotional data and sends the data based on that to a server.

[1182] 2. Roles and Operations of Server Means

[1183] The server receives and analyzes the data and emotional data sent from the terminals. The server uses a cross-checking means to confirm the consistency of information from multiple users and increase its reliability. It also has an adjustment means that adjusts the content and format of the information based on the emotional data. The adjusted data is then generated as a prompt sentence to be input into the generative AI model using a prompt generation means.

[1184] 3. Role and operation of the generating means

[1185] The generative AI model generates accurate information that takes into consideration the user's emotions based on the data analyzed on the server and emotional data. For example, if the user is feeling anxious, it generates a reassuring message such as, "We are arranging to alleviate your anxiety and quickly deliver food."

[1186] 4. Roles and Functions of Information Provision Means

[1187] The generated information is displayed on the device screen and is also provided to the user via voice notifications and push notifications to their mobile device. The information is provided in an appropriate format and with appropriate content based on emotional data, giving the user a sense of security.

[1188] Specific examples

[1189] A food delivery service collects emotional data when a user places an order.

[1190] 1. Device-based data collection and sentiment analysis:

[1191] When a user places an order from their smartphone, the system uses a camera and voice input device to analyze their facial expressions and voice and recognize whether they are in a hurry.

[1192] 2. Server-based data analysis and prompt generation:

[1193] The server analyzes the collected user emotional data and inputs the prompt sentence, "Please tell me what to do if I'm in a hurry," into the generative AI model.

[1194] 3. Information generation using generative AI models:

[1195] The generative AI model generates messages based on the emotion of "being in a hurry," such as, "We will start cooking immediately and arrange for delivery staff. We are doing our best to avoid keeping you waiting."

[1196] Prompt Sentence Examples

[1197] "Please tell me what to do if I'm in a hurry."

[1198] This system will enable disaster-stricken areas and food delivery services to accurately grasp user emotions and provide information tailored to them, resulting in an improved user experience and more efficient responses.

[1199] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1200] Step 1:

[1201] The device collects input information from the user and environmental sensor data. Specifically, it uses the camera and voice input device of a smartphone or robot to capture the user's facial expressions and voice, and simultaneously collects data such as temperature, humidity, and surrounding damage. The inputs include the user's order information, facial image, voice data, and sensor data. The output is sent to the server.

[1202] Step 2:

[1203] The device passes the collected facial image and voice data to the emotion engine means for analysis. The specific analysis operation involves using an emotion recognition library (e.g., DeepFace) to extract the main emotion felt by the user (e.g., feeling rushed or anxious). The facial image and voice data are used as input. The output is generated as data on the user's main emotion, and this data is sent to the server.

[1204] Step 3:

[1205] The server receives the user's emotion data and input information sent from the device. Specifically, it retrieves the data via an HTTP request and formats it into a format suitable for analysis. As input, it receives the user's order data, emotion data, and environmental sensor data. As output, it creates a dataset that has undergone preprocessing for data analysis.

[1206] Step 4:

[1207] The server cross-checks the received data. Specifically, it compares and examines similar data sent from multiple devices to confirm the reliability of the data. It uses a cross-checking method. As input, it uses the same type of data set sent by multiple users. As output, it generates data whose reliability has been confirmed.

[1208] Step 5:

[1209] The server uses a prompt generation means to generate a prompt sentence to be input to the generative AI model based on the user's emotional data. Specifically, if the emotional data indicates "I'm in a hurry," the server creates a prompt sentence saying, "Please tell me what to do if I'm in a hurry." The emotional data is used as input. The server generates a prompt sentence to be input to the generative AI model as output.

[1210] Step 6:

[1211] The server uses the generative AI model to generate an appropriate response message. Specifically, the prompt sentence is passed to the model as input, and the message generated by the AI ​​is obtained. For example, if the prompt sentence is "Please tell me what to do if I'm in a hurry," the generated message will be "We will start cooking immediately and arrange for a delivery person. We are doing our best to avoid keeping you waiting." The prompt sentence is used as input. The response message created by the generative AI model is obtained as output.

[1212] Step 7:

[1213] The server sends the generated message to the device and provides it to the user using the device's information provision means. Specifically, the message is not only displayed on the screen, but also provided as a voice notification or push notification. The generated message is used as input. The message is displayed on the user's smartphone or device as output.

[1214] 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.

[1215] 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.

[1216] 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.

[1217] [Fourth embodiment]

[1218] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1219] 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.

[1220] 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).

[1221] 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.

[1222] 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.

[1223] 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).

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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.

[1228] 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.

[1229] 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.

[1230] 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."

[1231] The system according to the present invention is intended to provide accurate information in disaster areas, and is mainly implemented in the following form.

[1232] First, the system includes a terminal that connects to the network via satellite, a server that receives and analyzes data sent from the terminal, a generation AI that generates accurate information based on the analyzed data, and an information provision means that provides the generated information to users.

[1233] Device role and operation

[1234] Terminal

[1235] The terminals are installed in disaster-stricken areas, such as evacuation centers, and are connected to the Internet via satellite. They are equipped with sensors and cameras to collect real-time data such as temperature, humidity, and damage status. They also collect information entered by users (e.g., the status of evacuation centers, food shortages, etc.).

[1236] Server Roles and Operations

[1237] server

[1238] The server receives the data sent from the devices and analyzes it using the generating AI. Specifically, the server checks the integrity of the data and cross-checks information from multiple devices to increase reliability. For example, if the same information is sent from multiple evacuation centers, it will determine that the information is accurate.

[1239] Role and behavior of generative AI

[1240] Generation AI

[1241] The AI ​​generates accurate and reliable information based on the data analyzed by the server. For example, if the information that "a certain evacuation shelter is short of food" is confirmed by cross-checking, the AI ​​creates a specific message saying, "There is a food shortage at this evacuation shelter."

[1242] Roles and operations of information provision means

[1243] Information provision means

[1244] The information provided by the AI ​​is presented to users via a variety of methods, including displaying information on the evacuation center's screen, allowing users to obtain accurate information in real time. Information can also be provided via voice notifications and push notifications to mobile devices.

[1245] Specific examples

[1246] 1. Setting up the shelter

[1247] Terminals are installed in evacuation centers and connected to a satellite network. They use sensors and cameras to collect information about the surrounding environment (temperature, humidity, population, damage, etc.).

[1248] 2. User input

[1249] The user types "There is a food shortage at the evacuation center" into the device, and the information is sent from the device to the server.

[1250] 3. Data analysis and information generation

[1251] The server analyzes the received data and cross-checks multiple similar reports. The generator AI generates an accurate message based on the information that "food is in short supply."

[1252] 4. Provision of Information

[1253] The generated information is displayed on the device's screen, and users at the evacuation center are notified with messages such as, "There is a food shortage. We are arranging relief supplies based on this information."

[1254] This system allows disaster victims to quickly and accurately obtain the information they need. For example, if there is a shortage of food or relief supplies, or if local traffic information is needed, the system will respond appropriately in real time. This will minimize confusion in the disaster-stricken areas and support effective relief efforts.

[1255] The processing flow will be explained below.

[1256] Step 1:

[1257] Terminal

[1258] The terminal is installed in the evacuation center and connects to the network via satellite. At this time, the terminal is supplied with power and basic settings (location information, basic information about the evacuation center, etc.) are configured. The sensors and cameras are activated and begin collecting environmental data about the evacuation center (temperature, humidity, images, etc.).

[1259] Step 2:

[1260] User

[1261] Users input the status of the evacuation shelter into the device. Specifically, they use the device's touch panel or voice input function to report information such as "food is in short supply" or "the toilets are out of order." The device temporarily stores this user-entered data.

[1262] Step 3:

[1263] Terminal

[1264] The terminal formats the collected environmental data and user-input data and transmits it to the server via satellite communication. At this time, it checks whether the data was transmitted correctly and attempts to retransmit it if an error occurs.

[1265] Step 4:

[1266] server

[1267] The server receives data sent from the devices. It passes the received data to the generation AI, which begins analyzing it. It cross-checks similar information sent from multiple devices to confirm the consistency and reliability of the data. For example, if information that "food is running low" is sent from multiple evacuation centers, it will match this information.

[1268] Step 5:

[1269] Server (Generating AI)

[1270] The AI ​​then generates accurate information based on the cross-checked data. For example, if a report is confirmed that "food is in short supply at shelters A, B, and C," the AI ​​generates a specific message saying, "There is a food shortage at these shelters."

[1271] Step 6:

[1272] Information provision means

[1273] The generated information is sent from the server to the device and displayed on the device's display. It can also be provided to the user as a voice notification or a push notification to the mobile device, as needed. For example, a message such as "There is a food shortage. We are currently arranging relief supplies based on this information" can be displayed.

[1274] Step 7:

[1275] server

[1276] The server periodically receives and analyzes new data and updates the information. Every time new data is sent, the generating AI reanalyzes it and updates the information based on the latest state. The updated information is then sent back to the device, and the display is updated in real time.

[1277] This process will enable accurate information to be provided at evacuation centers in disaster-stricken areas, enabling support activities to be carried out quickly and effectively.

[1278] Example 1

[1279] 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."

[1280] In disaster-stricken areas, it was difficult to quickly and accurately collect information and provide it to victims with reliable information, which led to delays in relief efforts and confusion over information, resulting in victims not receiving the support they needed in a timely manner.

[1281] 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.

[1282] In this invention, the server includes a terminal means, a means for receiving and analyzing sensor and user input data, a generating AI model means for generating highly reliable information, and a means for displaying or announcing the generated information, thereby enabling the rapid provision of highly reliable information based on data collected in disaster areas.

[1283] "Disaster area" refers to an area that has been affected by a natural or man-made disaster.

[1284] A "satellite network" refers to a network system that provides internet and communication services via artificial satellites.

[1285] "Terminal means" refers to electronic devices that are installed in the disaster area and that collect and transmit data.

[1286] "Server means" refers to a computer system for receiving and analyzing data sent from terminal means.

[1287] "Sensor" refers to a device that measures environmental data such as temperature and humidity.

[1288] "User-input data" refers to information provided by a User through a Terminal.

[1289] "Generative AI model" refers to an artificial intelligence model that generates reliable information based on data analyzed by a server means.

[1290] "Cross-checking measures" refers to the process of collating information from multiple data sources and assessing its consistency and reliability.

[1291] "Information providing means" refers to a device or method for notifying the user of the generated information.

[1292] "Display" refers to a device that visually displays generated information.

[1293] "Audio notification" refers to a means of conveying generated information to the user audibly.

[1294] "Data analysis means" refers to the server's function of verifying the integrity of collected data and performing any necessary cleansing or cross-checking.

[1295] "Cellular terminal" refers to a mobile device such as a mobile phone or smartphone.

[1296] This invention is a system for providing rapid and accurate information in disaster-stricken areas, and is mainly composed of terminal means, server means, generation AI model means, and information provision means. The specific operation and implementation method of each means will be explained below.

[1297] Terminal means

[1298] The terminal means is an electronic device installed in evacuation shelters in disaster areas and connected to the Internet via a satellite network. This terminal is equipped with sensors to collect environmental data such as temperature and humidity, and a camera to capture images of the damage. It also provides an interface for users to input information about the evacuation shelter situation and shortages of supplies.

[1299] As a specific example of use, a terminal means is installed in a shelter and collects information on the surrounding situation in real time using sensors and cameras. Furthermore, when a user inputs "There is a shortage of food at the shelter," this information is recorded in the terminal means. The terminal means packages this data and transmits it to the server means in the next phase.

[1300] Server Means

[1301] The server means is a computer system that receives and analyzes data sent from the terminal means. First, it checks the integrity of the received data and performs data cleansing if there are missing or invalid values. Then it cross-checks the same type of data sent from multiple terminals and evaluates its reliability. For example, if the same information is reported from multiple evacuation shelters, it is determined that the information is accurate.

[1302] The server means stores the received data in a database and then prepares to provide the data to the generative AI model means.

[1303] Generative AI model means

[1304] The generating AI model means is an artificial intelligence model that generates reliable information based on the data analyzed by the server means. The AI ​​model receives the analyzed data as input and generates a specific and reliable message. For example, it creates a notification message such as "There is a food shortage. Based on this information, relief supplies are being arranged."

[1305] Information provision means

[1306] The information provision means plays a role in providing the information generated by the generative AI model means to the user. The information is displayed on the display of the terminal means so that the user can obtain accurate information in real time. The information can also be provided in multiple ways, such as voice notification or push notification to the mobile device.

[1307] Specific examples

[1308] 1. Setting up the shelter

[1309] Terminal devices are installed in evacuation centers and connected to a satellite network. They use sensors and cameras to collect information on the surrounding environment (temperature, humidity, population, damage status, etc.) in real time.

[1310] 2. User input

[1311] The user inputs "There is a shortage of food at the evacuation shelter" into the terminal means. The information is transmitted from the terminal means to the server means.

[1312] 3. Data analysis and information generation

[1313] The server means analyzes the received data and cross-checks multiple similar reports. The generative AI model means generates an accurate message based on the information that "food is in short supply."

[1314] 4. Provision of Information

[1315] The generated information is displayed on the terminal display, and users at the evacuation shelter are notified, such as, "There is a food shortage. We are arranging relief supplies based on this information." It is also possible to send voice notifications and push notifications to mobile devices.

[1316] Prompt Sentence Examples

[1317] 1. Prompt example 1

[1318] We have installed devices in evacuation shelters in the affected areas that use sensors and cameras to collect information on temperature, humidity, and damage. Please enter information on the evacuation shelter situation and food shortages.

[1319] 2. Prompt example 2

[1320] Based on the data collected on the device, the server analyzed and cross-checked the data. Based on this information, the AI ​​generated the message "Food is running low." Please check the generated notification content.

[1321] 3. Prompt example 3

[1322] Based on the above information, a notice was sent to the terminal displays at the evacuation center. Please check the status of food supply arrangements.

[1323] As described above, by having each means work in coordination, it becomes possible to provide disaster victims with quick and accurate information and provide effective support.

[1324] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1325] Step 1: Placement and connection of terminal means

[1326] Specific operation: The terminal means is installed at an evacuation shelter in the disaster area. A technician installs the terminal means and establishes an Internet connection using a satellite antenna.

[1327] Input: Information about evacuation shelters and their locations

[1328] Output: Internet connection established and terminal means operational

[1329] Step 2: Start the sensors and cameras

[1330] Specific operation: The system administrator remotely activates the sensors and cameras of the terminal device, which completes preparations for data collection.

[1331] Input: Sensor and camera initial configuration information

[1332] Output: Sensors and cameras are up and running and ready to collect data.

[1333] Step 3: Collect environmental data

[1334] Specific operation: The terminal device uses sensors to collect environmental data such as temperature, humidity, and population in real time, and also uses a camera to take photos of the damage situation and save the image data.

[1335] Input: Local environmental information of the evacuation shelter

[1336] Output: Collected environmental and image data

[1337] Step 4: User input

[1338] Specific operation: The user uses the input interface of the terminal means to input information such as "food shortage at the evacuation center." The terminal means records this information.

[1339] Input: User-entered shelter status information

[1340] Output: User input data recorded on the terminal means

[1341] Step 5: Packaging and preparing the data for transmission

[1342] Specific operation: The terminal means packages the collected environmental data and user input data into one data packet and prepares to send it to the server means.

[1343] Input: Collected environmental data and user-entered data

[1344] Output: Data packets ready to be sent

[1345] Step 6: Sending data to the server

[1346] Specific operation: The terminal means transmits data packets to the server means via satellite communication. The data is encrypted and transmitted.

[1347] Input: Data packet ready to send

[1348] Output: Data packets received by the server

[1349] Step 7: Receiving and storing data

[1350] Specific operation: The server means receives the data packets sent from the terminal means and stores them in a database for analysis.

[1351] Input: Data packets sent from the terminal means

[1352] Output: Saved data

[1353] Step 8: Data integrity check and cleansing

[1354] Specific operation: The server means checks the integrity of the data and performs data cleansing if there are missing or invalid values.

[1355] Input: Saved data

[1356] Output: Cleansed data with integrity checks

[1357] Step 9: Cross-check from multiple devices

[1358] Specific operation: The server means cross-checks the same type of data sent from different terminal means and evaluates its reliability. For example, if multiple evacuation centers report the same content, such as "food shortages," the information is judged to be accurate.

[1359] Input: Homogeneous data sent from multiple terminal means

[1360] Output: Data whose reliability has been assessed by cross-checking

[1361] Step 10: Generate information using generative AI models

[1362] Specific operation: The server executes the generative AI model based on the analyzed data to generate a reliable message, such as "There is a food shortage. Based on this information, we are arranging relief supplies."

[1363] Input: Data whose reliability has been assessed by cross-checking

[1364] Output: Highly reliable informational messages generated

[1365] Step 11: Prepare to distribute information

[1366] Specific operation: The server means assembles the generated information messages into packets for delivery and prepares them for transmission.

[1367] Input: Generated information message

[1368] Output: Data packets ready for delivery

[1369] Step 12: Sending information to the terminal means

[1370] Specific operation: The server means transmits a distribution data packet to the terminal means.

[1371] Input: Data packets ready for delivery

[1372] Output: Information received by terminal means

[1373] Step 13: Providing information through display and audio notifications

[1374] Specific operation: The terminal displays the received information on the display of the evacuation center, providing users with accurate information in real time, and also provides voice notifications as necessary.

[1375] Input: Information received by terminal means

[1376] Output: Information displayed on the screen and audio notifications

[1377] Step 14: Push notification to mobile device

[1378] Specific operation: The terminal means or the server means also sends a push notification to the mobile device, so that the user can check detailed information on their mobile device.

[1379] Input: Information generated by terminal or server means.

[1380] Output: Push notification received on mobile device

[1381] (Application example 1)

[1382] 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."

[1383] In conventional disaster response systems, information collection and provision is often not done in real time, making it difficult to provide victims with quick and accurate information. In addition, the means of providing information are limited, and a lack of adaptive evacuation information, especially in dangerous situations, has been a problem. This has led to the risk that victims are unable to take appropriate action, and the damage may worsen.

[1384] 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.

[1385] In this invention, the server includes a terminal means connected to the network via a satellite, a means for receiving and analyzing data transmitted from the terminal means, a generating means for generating accurate information based on the data analyzed by the server means, an information providing means using a smart device (including smart glasses) for providing the generated information to users, a cross-checking means for checking the consistency of data transmitted from multiple users, and an adaptive evacuation information providing means based on location information. This enables prompt and accurate information to be provided in disaster-stricken areas, allowing disaster victims to take appropriate action.

[1386] "Terminal means" refers to a device that connects to a network via satellite and collects data using sensors and cameras in the disaster area.

[1387] The "server means" is a server device that receives and analyzes data sent from the terminal means.

[1388] The "analysis means" is a means for verifying the consistency of received data in the server means and analyzing the data.

[1389] The "generation means" is a means for generating accurate information based on the analyzed data.

[1390] A "smart device" is a device that provides generated information to a user, and includes smart glasses and the like.

[1391] The "information providing means" is a means for providing the information generated by the generating means to the user.

[1392] A "cross-check means" is a means for checking the consistency of data sent from multiple users.

[1393] An "adaptive evacuation information provision means" is a means for providing users with optimal evacuation information in real time based on location information.

[1394] The system according to the present invention is for providing accurate information in real time in disaster areas, and is implemented in the following manner.

[1395] 1. Roles and operations of terminal means

[1396] The terminal means is installed in the disaster area and connected to the network via satellite. Specifically, it is a device installed in evacuation shelters and dangerous areas, and is equipped with sensors and cameras. This terminal collects the following data:

[1397] Temperature and humidity

[1398] Damage situation

[1399] Demographics

[1400] Users can use the terminal to input information such as the status of evacuation shelters and food shortages, which is then sent to the server.

[1401] 2. Roles and Operations of Server Means

[1402] The server means is a device that receives data sent from the terminal means and performs analysis processing. The server means processes the data using the following means:

[1403] Analysis method: Check the integrity of the received data and perform analysis.

[1404] Cross-checking measures: verifying the integrity of data submitted by multiple users.

[1405] Generation method: Generate accurate and reliable information based on the analyzed data.

[1406] Specifically, the server cross-checks the consistency of the data. For example, if multiple shelters report the same information, it determines that the information is accurate. As a result of this process, the generator generates specific information such as "food shortage."

[1407] 3. Roles and Functions of Information Provision Means

[1408] The information providing means is a device for providing the information generated by the generating means to the user. In particular, the present invention utilizes a smart device, such as smart glasses:

[1409] Smart glasses: Evacuation information and warnings are displayed on the screen, and voice notifications are also possible.

[1410] Location integration: Shows the nearest evacuation shelters and safe routes based on your current location.

[1411] Hardware / Software used

[1412] Hardware: Satellite-connected devices, smart glasses

[1413] Software: Cloud servers, analytical algorithms, generative AI (e.g., OpenAI's GPT model), speech synthesis engines (e.g., Google Text-to-Speech)

[1414] For example, the following prompts can be sent to the generative AI to provide real-time information:

[1415] Prompt Sentence Examples

[1416] "Disaster information: Earthquake occurred. Current location is city center. Please provide evacuation locations and safe routes."

[1417] Example

[1418] 1. Visual Indication:

[1419] The smart glasses' display read, "The nearest evacuation shelter is 500 meters north from your current location. Take the next right."

[1420] 2. Sound notification:

[1421] The smart glasses will play a voice notification saying, "An earthquake has occurred. Please evacuate immediately. Walk 500 meters to the right to reach the evacuation shelter."

[1422] This will enable disaster victims to take safe action based on prompt and accurate information, minimizing confusion in disaster-stricken areas and supporting effective relief efforts.

[1423] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1424] Step 1:

[1425] Data collection and transmission

[1426] Subject: Terminal

[1427] The device uses sensors and cameras installed in the affected area to collect data such as temperature, humidity, and damage status. It also collects information entered by the user, such as the status of evacuation shelters and food shortages. This data is collected in real time and sent to a server via satellite communication.

[1428] Input: Data from sensors and cameras, user input

[1429] Output: Sending collected data to a server

[1430] Step 2:

[1431] Data reception and integrity check

[1432] Subject: Server

[1433] The server receives the data sent from the terminal. It checks the consistency of the received data. If the same information is sent from multiple terminals, it determines that the information is correct and performs a cross-check.

[1434] Input: Data sent from the terminal

[1435] Output: Data with integrity checked

[1436] Step 3:

[1437] Data analysis

[1438] Subject: Server and Generative AI

[1439] The server analyzes the data whose integrity has been confirmed. By using analytical methods, complex data is statistically analyzed to determine the extent of damage and the status of evacuation shelters. The generation AI generates accurate and reliable information based on this analytical data.

[1440] Input: Integrity checked data

[1441] Output: Information generated by the generative AI

[1442] Step 4:

[1443] information generation

[1444] Subject: Generation AI

[1445] The generative AI generates specific messages based on data analysis. For example, it generates a specific notification such as, "There is a food shortage at this evacuation shelter." The generated information is then customized to be provided to the user.

[1446] Input: Parsed data

[1447] Output: The specific message generated

[1448] Step 5:

[1449] Information provision

[1450] Subject: Means of information provision (smart device)

[1451] The generated information is provided to users via smart devices (such as smart glasses). Real-time information such as the status of evacuation shelters and evacuation routes is provided via display and voice notification. Adaptive evacuation information tailored to the user's current location is also displayed based on location information.

[1452] Input: The specific message to be generated

[1453] Output: Providing information via smart devices

[1454] Illustrative prompt examples

[1455] "Disaster information: Earthquake occurred. Current location is city center. Please provide evacuation locations and safe routes."

[1456] This processing flow enables rapid, real-time information provision in disaster-stricken areas, allowing users to take appropriate action.

[1457] 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.

[1458] The system of the present invention is designed to provide accurate information in disaster areas and is also combined with an emotion engine that recognizes and analyzes user emotions. This system is mainly implemented in the following forms:

[1459] The system includes a terminal connected to a network via satellite, a server that receives and analyzes data transmitted from the terminal, a generation AI that generates accurate information based on the analyzed data, and an information providing means that provides the generated information to the user. Furthermore, the system is equipped with an emotion engine that recognizes the user's emotions.

[1460] Device role and operation

[1461] Terminal

[1462] The terminals are installed in disaster-stricken areas, such as evacuation shelters, and are connected to the Internet via satellite. They are equipped with sensors, cameras, and voice input devices to collect real-time data such as temperature, humidity, and damage status. They also have an emotion engine that collects emotional data from users' facial expressions and voice, in addition to input information from users.

[1463] Server Roles and Operations

[1464] server

[1465] The server receives the data and emotion data sent from the device and analyzes it using generative AI. Specifically, it checks the consistency of the data and cross-checks information from multiple devices to increase reliability. It also analyzes the user's emotion data and adjusts the content and format of the information provided based on that emotion.

[1466] Role and behavior of generative AI

[1467] Generation AI

[1468] The AI ​​generates accurate and reliable information based on the data and emotional data analyzed on the server. For example, if a cross-check confirms that there is a food shortage at a particular evacuation shelter, it generates an appropriate message taking into account the user's emotional data. For example, if the user is feeling anxious, a message that provides reassurance will be provided.

[1469] Roles and operations of information provision means

[1470] Information provision means

[1471] The information provided to users is generated by the AI. Specifically, the device displays the information on the evacuation center's display, allowing users to obtain accurate information in real time. Based on the analysis results of the emotion engine, voice notifications and push notifications are also sent to mobile devices.

[1472] Specific examples

[1473] 1. Setting up the shelter

[1474] The device is installed in the evacuation center and connected to a satellite network. The sensors and cameras are activated to collect information on the surrounding environment (temperature, humidity, population, damage status, etc.). The emotion engine is also activated to analyze the user's facial expressions and voice.

[1475] 2. User input

[1476] The user types into the device, "There is a food shortage at the evacuation center." At this time, the emotion engine analyzes the user's facial expressions and voice and sends the data to the server as the user's emotion data.

[1477] 3. Data analysis and information generation

[1478] The server analyzes the received data and emotion data, cross-checking multiple similar reports. The AI ​​generator confirms the report that "food shortages are occurring at shelters A, B, and C," and generates a specific message based on the user's emotion. For example, if the user is feeling anxious, it will provide a reassuring message such as, "We are arranging to alleviate your anxiety and provide food promptly."

[1479] 4. Provision of Information

[1480] The generated information is displayed on the device's display and provided to users at evacuation shelters. For example, a notification such as, "There is a food shortage. We are arranging relief supplies based on this information. If you are feeling anxious, please rest assured; we are responding quickly."

[1481] This system enables disaster victims to quickly and accurately obtain the information they need, effectively supporting relief efforts. Furthermore, by utilizing an emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a greater sense of security.

[1482] The processing flow will be explained below.

[1483] Step 1:

[1484] Terminal

[1485] The device is installed at the evacuation center and connects to the network via satellite. At this time, the device is supplied with power and location information and basic information about the evacuation center (such as capacity) are entered. Sensors and cameras are activated and begin collecting environmental data (temperature, humidity, damage status, etc.). The emotion engine is also activated, ready to collect the user's facial expressions and voice.

[1486] Step 2:

[1487] User

[1488] Users input information about the evacuation shelter situation into their device. For example, they can use the touch panel or voice input function to report information such as "food is in short supply" or "the toilets are out of order." At this time, the emotion engine analyzes the user's facial expressions and voice to generate emotion data.

[1489] Step 3:

[1490] Terminal

[1491] The device formats the collected environmental data, user input data, and emotion data and transmits them to the server via satellite communication. It checks whether the data was transmitted correctly and attempts to retry if a transmission error occurs.

[1492] Step 4:

[1493] server

[1494] The server receives the data and emotion data sent from the device. The received data is passed to the generation AI, which then begins analyzing the data. Similar information sent from multiple devices is cross-checked to confirm the consistency and reliability of the data. At this time, the user's emotion data is also used in the analysis.

[1495] Step 5:

[1496] Server (Generating AI)

[1497] The generation AI generates accurate information based on the cross-checked data. For example, if the cross-check confirms that "there is a food shortage at a particular evacuation shelter," it generates a message that provides reassurance based on the user's emotional data. For example, it could say, "There is a food shortage at this evacuation shelter. Please rest assured, relief supplies are being quickly arranged."

[1498] Step 6:

[1499] Information provision means

[1500] The generated information is sent from the server to the device. It is then provided to the user as a display, voice notification, or push notification to their mobile device. For example, a message such as "There is a food shortage at evacuation centers. Relief supplies are being quickly arranged. Please rest assured if you are feeling anxious" is displayed.

[1501] Step 7:

[1502] server

[1503] The server periodically receives and analyzes new data and updates the information. Every time new data is sent, the generating AI reanalyzes it and updates the information based on the latest state. The updated information is then resent to the device, and the display content is updated in real time.

[1504] This procedure allows users at evacuation shelters in disaster areas to quickly and accurately obtain the information they need. Furthermore, by utilizing the emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a sense of security.

[1505] Example 2

[1506] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1507] Conventional information provision systems in disaster areas have difficulty in providing accurate information quickly, and in particular have been unable to provide information that takes into account the user's emotions. As a result, victims are prone to feeling anxious and stressed, and are sometimes unable to obtain accurate information. Furthermore, if information from multiple sources is not cross-checked, there is a risk that unreliable information will be provided.

[1508] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1509] In this invention, the server includes a terminal device that uses sensors, cameras, and a voice input device to collect environmental data of the disaster area and input data from the user, a terminal device that uses an emotion engine to collect user emotion data, a server device that receives and analyzes the data transmitted from the terminal device, a server device that generates accurate information based on the analyzed data and emotion data using a generation AI, and a device that displays the generated information on the display of the terminal device and sends voice notifications and push notifications to mobile devices. This enables the provision of fast and accurate information in disaster areas and information that takes user emotions into consideration and gives a sense of security.

[1510] "Terminal devices" are devices that are installed in disaster areas and evacuation shelters, connect to the Internet via a satellite network, and use sensors, cameras, and voice input devices to collect environmental data and input data from users.

[1511] An "emotion engine" is a software or hardware system that analyzes a user's facial expressions and voice and collects the user's emotional data.

[1512] A "server device" is a computer system that receives and analyzes data sent from a terminal device.

[1513] "Generative AI" is an artificial intelligence algorithm or software that resides within a server device and generates accurate information based on analyzed data and emotional data.

[1514] An "information providing device" is a device for providing generated information to a user, and has the function of displaying information on the display of a terminal device and providing voice notification and push notification to a mobile device.

[1515] A "cross-checking means" is a process or algorithm by which a server device verifies the integrity of data sent from multiple terminal devices and cross-checks the data to increase the reliability of the information.

[1516] The system of the present invention is designed to provide accurate information in disaster-stricken areas and is also combined with an emotion engine that recognizes and analyzes user emotions. This system consists of a terminal device, a server device, a generation AI, and an information providing device.

[1517] Roles and operations of terminal devices

[1518] The terminal devices are installed in disaster areas, such as evacuation shelters. They are equipped with sensors, cameras, and voice input devices, which can be used to collect real-time data such as temperature, humidity, population density, and damage status. They also have a built-in emotion engine that can analyze the user's facial expressions and voice to collect emotional data. The terminal devices are connected to a network via satellite and transmit the collected data to a server device.

[1519] Roles and operations of server devices

[1520] The server device receives data sent from the terminal devices. The server device checks the consistency of the received environmental data and emotion data and cross-checks the information obtained from multiple terminal devices, thereby increasing the reliability of the data. The server device uses a generative AI model written in Python (e.g., GPT-3) to generate accurate information based on the analyzed data.

[1521] Role and behavior of generative AI

[1522] The AI ​​generates accurate and reliable information in a format that is easy for humans to understand, based on the data and emotional data analyzed by the server. For example, if a cross-check confirms that "food is in short supply at a specific evacuation shelter," it generates an appropriate message taking into account the user's emotional data. If the user is feeling anxious, it generates a reassuring message such as, "We are arranging to alleviate your anxiety and quickly provide food."

[1523] Roles and operations of information providing devices

[1524] The information provision device provides users with the information generated by the AI. Specifically, it displays the information on the terminal device's display, providing users with accurate information in real time. It also provides voice notifications and push notifications to mobile devices based on the analysis results of the emotion engine.

[1525] Specific examples

[1526] 1. Setting up the shelter

[1527] Terminal devices are installed in evacuation shelters and connected to a satellite network. Sensors and cameras are activated to collect information on the surrounding environment (temperature, humidity, population density, damage status, etc.). An emotion engine is also activated to analyze the user's facial expressions and voice.

[1528] 2. User input

[1529] The user inputs into the terminal device, "There is a shortage of food at the evacuation shelter." At this time, the emotion engine analyzes the user's facial expressions and voice and transmits the data to the server device as the user's emotion data.

[1530] 3. Data analysis and information generation

[1531] The server analyzes the received data and emotion data, cross-checking multiple similar reports. The AI ​​generator confirms the report that "food shortages are occurring at shelters A, B, and C," and generates a specific message based on the user's emotion. For example, if the user is feeling anxious, it will provide a reassuring message such as, "We are arranging to alleviate your anxiety and provide food promptly."

[1532] 4. Provision of Information

[1533] The generated information is displayed on the terminal device's display and provided to users at the evacuation shelter. For example, a message such as, "There is a food shortage. We are arranging relief supplies based on this information. If you are feeling anxious, please rest assured; we are responding quickly."

[1534] Prompt Sentence Examples

[1535] "Please let us know the current temperature and humidity at the evacuation center in real time. Also, please let us know about any food shortages."

[1536] "Generate and present messages that make users feel safe in the evacuation shelter. Emotional data is unsettling."

[1537] This system allows disaster victims to obtain quick and accurate information, enabling effective support for relief efforts. In addition, by utilizing the emotion engine, it is possible to provide information that reduces the psychological burden on disaster victims and gives them a greater sense of security.

[1538] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1539] Step 1: Collect data from the device

[1540] How it works: The device is installed in an evacuation center and connected to the Internet via satellite. Sensors and cameras are activated to collect real-time data such as temperature, humidity, population density, and damage status. The emotion engine analyzes the user's facial expressions and voice to collect emotional data. The device then sends all collected data to a server.

[1541] Input: Real-time data on temperature, humidity, population density, damage status, and user facial and voice data

[1542] Output: Collected environmental data and emotional data (e.g., temperature 30°C, humidity 70%, emotion = anxiety)

[1543] Step 2: User enters information

[1544] Specific operation: The user inputs information such as "There is a food shortage at the evacuation shelter" into the device. The device receives this information, and the emotion engine analyzes the user's facial expressions and voice to generate emotion data. The device then sends this data to the server.

[1545] Input: User-supplied text (e.g., "Food shortage at evacuation centers")

[1546] Output: Text information and analyzed emotion data (e.g. emotion = anxiety)

[1547] Step 3: Server receives data

[1548] Specific operation: The server receives data sent from the device. Examples include temperature, humidity, population density, damage status, user input information, and emotional data. The server stores all received data in a database.

[1549] Input: Data sent from the device (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[1550] Output: Received data stored in a database

[1551] Step 4: Data analysis by the server

[1552] Specific operation: The server checks the integrity of the data stored in the database and performs cross-checks to improve the reliability of the data. It checks whether the data is consistent and whether there are any outliers.

[1553] Input: Data stored in the database (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[1554] Output: Trusted data with integrity checks

[1555] Step 5: Information generation by generative AI

[1556] Specific operation: The server inputs the data that has passed the cross-check into the generation AI. Based on this, the generation AI generates information in a format that is easy for humans to understand. For example, it might generate information such as "There is a food shortage at shelters A, B, and C," and then incorporate emotional data to create a reassuring message such as "We are responding quickly."

[1557] Input: Reliable data after cross-checking (e.g., temperature 30°C, humidity 70%, emotion = anxiety, user input "food shortage at evacuation shelters")

[1558] Output: Generated information (e.g., "There is a food shortage at shelters A, B, and C. We are responding quickly, so please wait without worry.")

[1559] Step 6: Notify users through informational means

[1560] Specific operation: The information generated by the generation AI is displayed on the device's display. In addition, based on the analysis results of the emotion engine, voice notifications and push notifications are also sent to the mobile device.

[1561] Input: Generated information (e.g., "There is a food shortage at shelters A, B, and C. We are responding quickly, so please wait without worry.")

[1562] Output: Information displayed on the device display, audio notification, push notification to mobile device

[1563] The above steps will enable the provision of fast and accurate information in disaster-stricken areas, thereby reducing user anxiety.

[1564] (Application example 2)

[1565] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1566] In disaster-stricken areas, it is important to provide accurate information and generate information that takes into account the emotions of users. In particular, in fields such as food delivery services, it is necessary to accurately grasp users' emotions and respond accordingly. However, conventional systems have been inadequate in recognizing and reflecting emotions. This has resulted in an incomplete user experience and has made it difficult to respond efficiently.

[1567] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means, adjustment means, and prompt generation means. This makes it possible to analyze the user's emotion data, adjust the content and format of information based on that, and input the information as a prompt sentence into the generation AI model, thereby enabling individual responses that take the user's emotions into consideration.

[1568] "Terminal means" refers to a device that is installed in a disaster area or a service site, connects to a network, and collects and transmits data.

[1569] The "server means" is a central processing unit that receives data sent from the terminal means, analyzes it, and generates necessary information.

[1570] The "generation means" refers to a process or system that automatically generates accurate information based on the data analyzed by the server means.

[1571] "Information provision means" refers to means such as a display, voice notification, or push notification for providing the generated information to the user.

[1572] The "emotion engine means" is a combination of software and hardware for recognizing and analyzing the user's emotions.

[1573] "Adjustment means" refers to a process or system for adjusting the content and format of the information provided based on the analyzed emotional data.

[1574] "Cross-checking means" refers to means used to check the consistency of data sent from multiple users and increase the reliability of the data.

[1575] A "prompt generation means" is a means of inputting information based on the user's emotions into a generative AI model as a prompt sentence.

[1576] A "generative AI model" is an artificial intelligence model that automatically generates meaningful information based on input data.

[1577] A "prompt sentence" is an input sentence that causes a generative AI model to output specific information.

[1578] A system for carrying out the present invention includes the following means.

[1579] 1. Roles and operations of terminal means

[1580] The terminals will be installed at evacuation centers and food delivery service sites. They are connected to a network via satellite and equipped with sensors, cameras, and voice input devices. These sensors and input devices collect real-time data such as temperature, humidity, damage status, and the user's facial expressions and voice. In particular, the emotion engine analyzes the user's emotional data and sends the data based on that to a server.

[1581] 2. Roles and Operations of Server Means

[1582] The server receives and analyzes the data and emotional data sent from the terminals. The server uses a cross-checking means to confirm the consistency of information from multiple users and increase its reliability. It also has an adjustment means that adjusts the content and format of the information based on the emotional data. The adjusted data is then generated as a prompt sentence to be input into the generative AI model using a prompt generation means.

[1583] 3. Role and operation of the generating means

[1584] The generative AI model generates accurate information that takes into consideration the user's emotions based on the data analyzed on the server and emotional data. For example, if the user is feeling anxious, it generates a reassuring message such as, "We are arranging to alleviate your anxiety and quickly deliver food."

[1585] 4. Roles and Functions of Information Provision Means

[1586] The generated information is displayed on the device screen and is also provided to the user via voice notifications and push notifications to their mobile device. The information is provided in an appropriate format and with appropriate content based on emotional data, giving the user a sense of security.

[1587] Specific examples

[1588] A food delivery service collects emotional data when a user places an order.

[1589] 1. Device-based data collection and sentiment analysis:

[1590] When a user places an order from their smartphone, the system uses a camera and voice input device to analyze their facial expressions and voice and recognize whether they are in a hurry.

[1591] 2. Server-based data analysis and prompt generation:

[1592] The server analyzes the collected user emotional data and inputs the prompt sentence, "Please tell me what to do if I'm in a hurry," into the generative AI model.

[1593] 3. Information generation using generative AI models:

[1594] The generative AI model generates messages based on the emotion of "being in a hurry," such as, "We will start cooking immediately and arrange for delivery staff. We are doing our best to avoid keeping you waiting."

[1595] Prompt Sentence Examples

[1596] "Please tell me what to do if I'm in a hurry."

[1597] This system will enable disaster-stricken areas and food delivery services to accurately grasp user emotions and provide information tailored to them, resulting in an improved user experience and more efficient responses.

[1598] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1599] Step 1:

[1600] The device collects input information from the user and environmental sensor data. Specifically, it uses the camera and voice input device of a smartphone or robot to capture the user's facial expressions and voice, and simultaneously collects data such as temperature, humidity, and surrounding damage. The inputs include the user's order information, facial image, voice data, and sensor data. The output is sent to the server.

[1601] Step 2:

[1602] The device passes the collected facial image and voice data to the emotion engine means for analysis. The specific analysis operation involves using an emotion recognition library (e.g., DeepFace) to extract the main emotion felt by the user (e.g., feeling rushed or anxious). The facial image and voice data are used as input. The output is generated as data on the user's main emotion, and this data is sent to the server.

[1603] Step 3:

[1604] The server receives the user's emotion data and input information sent from the device. Specifically, it retrieves the data via an HTTP request and formats it into a format suitable for analysis. As input, it receives the user's order data, emotion data, and environmental sensor data. As output, it creates a dataset that has undergone preprocessing for data analysis.

[1605] Step 4:

[1606] The server cross-checks the received data. Specifically, it compares and examines similar data sent from multiple devices to confirm the reliability of the data. It uses a cross-checking method. As input, it uses the same type of data set sent by multiple users. As output, it generates data whose reliability has been confirmed.

[1607] Step 5:

[1608] The server uses a prompt generation means to generate a prompt sentence to be input to the generative AI model based on the user's emotional data. Specifically, if the emotional data indicates "I'm in a hurry," the server creates a prompt sentence saying, "Please tell me what to do if I'm in a hurry." The emotional data is used as input. The server generates a prompt sentence to be input to the generative AI model as output.

[1609] Step 6:

[1610] The server uses the generative AI model to generate an appropriate response message. Specifically, the prompt sentence is passed to the model as input, and the message generated by the AI ​​is obtained. For example, if the prompt sentence is "Please tell me what to do if I'm in a hurry," the generated message will be "We will start cooking immediately and arrange for a delivery person. We are doing our best to avoid keeping you waiting." The prompt sentence is used as input. The response message created by the generative AI model is obtained as output.

[1611] Step 7:

[1612] The server sends the generated message to the device and provides it to the user using the device's information provision means. Specifically, the message is not only displayed on the screen, but also provided as a voice notification or push notification. The generated message is used as input. The message is displayed on the user's smartphone or device as output.

[1613] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1614] 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.

[1615] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1616] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1617] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1618] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1619] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1620] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1621] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1622] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1623] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1624] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1625] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1626] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1627] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1628] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1629] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1630] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1631] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1632] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1633] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1634] The following is further disclosed regarding the above embodiment.

[1635] (Claim 1)

[1636] A system for providing accurate information in disaster-stricken areas,

[1637] a terminal means for connecting to a network via a satellite;

[1638] a server means for receiving and analyzing data transmitted from the terminal means;

[1639] generating means for generating accurate information based on the data analyzed by the server means;

[1640] The system includes an information providing means for providing the generated information to a user.

[1641] (Claim 2)

[1642] the terminal means is installed at an evacuation shelter in a disaster area and collects input data from users;

[1643] The system of claim 1.

[1644] (Claim 3)

[1645] The server means has a cross-check means for verifying the consistency of data transmitted from a plurality of users.

[1646] The system of claim 1.

[1647] "Example 1"

[1648] (Claim 1)

[1649] A system for providing accurate information in disaster-stricken areas,

[1650] a terminal means for connecting to a network via a satellite;

[1651] a server means for receiving and analyzing sensor and user input data transmitted from the terminal means;

[1652] a generating AI model means for generating highly reliable information based on the data analyzed by the server means;

[1653] an information providing means for displaying or audibly notifying the generated information to the user;

[1654] Data analysis means for verifying the consistency of data collected by the terminal means and performing cross-checks

[1655] A system including:

[1656] (Claim 2)

[1657] It will be installed in evacuation shelters in disaster areas and will collect real-time data through user input and sensors.

[1658] 10. The system of claim 1.

[1659] (Claim 3)

[1660] The system has an information providing means for providing notifications via a display or a mobile device based on the information analyzed by the generating AI model means.

[1661] 10. The system of claim 1.

[1662] "Application Example 1"

[1663] (Claim 1)

[1664] A system for providing accurate information in disaster-stricken areas,

[1665] a terminal means for connecting to a network via a satellite;

[1666] a server means for receiving and analyzing data transmitted from the terminal means;

[1667] generating means for generating accurate information based on the data analyzed by the server means;

[1668] A system including an information provision means using a smart device (including smart glasses) to provide the generated information to the user.

[1669] (Claim 2)

[1670] the terminal means is installed at an evacuation shelter in a disaster area and collects input data from users;

[1671] 10. The system of claim 1.

[1672] (Claim 3)

[1673] The server means has a cross-check means for verifying the consistency of data transmitted from a plurality of users, and has a means for providing adaptive evacuation information based on location information.

[1674] 10. The system of claim 1.

[1675] "Example 2: Combining Emotion Engines"

[1676] (Claim 1)

[1677] A means for connecting a terminal device to a network via a satellite;

[1678] a means for the terminal device to collect environmental data of the disaster area and input data from users using sensors, cameras, and voice input devices;

[1679] means for collecting user emotion data using an emotion engine in the terminal device;

[1680] a server device that receives and analyzes the data transmitted from the terminal device;

[1681] means for the server device to verify data consistency and cross-check information from multiple terminal devices;

[1682] A means for generating accurate information based on the data and emotion data analyzed by the server device using the generation AI;

[1683] an information providing device that provides the generated information to a user;

[1684] a means for displaying the information generated by the information providing device on a display of a terminal device and for providing a voice notification or a push notification to a mobile terminal;

[1685] A system including:

[1686] (Claim 2)

[1687] 2. The system according to claim 1, wherein the terminal device is installed at an evacuation shelter in a disaster area and collects input data and emotion data from users.

[1688] (Claim 3)

[1689] The system according to claim 1, wherein the server device has a cross-checking means for checking the consistency of data transmitted from a plurality of users.

[1690] "Application example 2 when combining emotion engines"

[1691] (Claim 1)

[1692] A system for providing accurate information in disaster-stricken areas,

[1693] a terminal means for connecting to a network via a satellite;

[1694] a server means for receiving and analyzing data transmitted from the terminal means;

[1695] generating means for generating accurate information based on the data analyzed by the server means;

[1696] an information providing means for providing the generated information to a user;

[1697] An emotion engine means for recognizing and analyzing user emotions;

[1698] an adjustment means for adjusting the content and format of the information to be provided based on the analyzed emotion data;

[1699] A system including:

[1700] (Claim 2)

[1701] The terminal means is installed at evacuation centers and food delivery services in disaster areas, and collects input data and emotion data from users.

[1702] 10. The system of claim 1.

[1703] (Claim 3)

[1704] The server means has a cross-check means for checking the consistency of data sent from multiple users and a prompt generation means for inputting information based on the user's emotions as a prompt sentence to the generative AI model.

[1705] 10. The system of claim 1. [Explanation of symbols]

[1706] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A system for providing accurate information in disaster-stricken areas, a terminal means for connecting to a network via a satellite; a server means for receiving and analyzing data transmitted from the terminal means; generating means for generating accurate information based on the data analyzed by the server means; The system includes an information providing means for providing the generated information to a user.

2. the terminal means is installed at an evacuation shelter in a disaster area and collects input data from users; The system of claim 1 .

3. The server means has a cross-check means for verifying the consistency of data transmitted from a plurality of users. The system of claim 1 .

Images