system

Abstract

Provide a system. A means for acquiring location information; A means of collecting information on damage when a disaster occurs, A means for transmitting the collected location information and damage situation; A means to analyze the transmitted location information and damage situation and select the optimal recovery solution; A means of communicating the analysis results and selected recovery solutions to disaster response personnel; and A system including:

Description

[Technical Field]

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

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

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

[0004] When a disaster occurs, it is difficult to quickly and accurately grasp the damage situation over a wide area and immediately determine the optimal recovery solution. Conventional methods take time to collect and analyze information, which can reduce the efficiency of disaster response. Therefore, there is a need for a system that can grasp the damage situation in real time and quickly provide appropriate recovery solutions. [Means for solving the problem]

[0005] The present invention is a system including a means for acquiring location information, a means for collecting damage status when a disaster occurs, a means for transmitting the collected location information and damage status, a means for analyzing the transmitted location information and damage status and selecting an optimal restoration solution, and a means for notifying disaster response personnel of the analysis results and the selected restoration solution. The means for acquiring location information utilizes a global positioning system (GPS), and the means for collecting damage status when a disaster occurs includes multiple built-in sensors. Furthermore, the means for selecting the optimal restoration solution utilizes a geographic information system (GIS) to analyze the range and scale of the damage, thereby quickly and accurately grasping the damage status and providing appropriate countermeasures.

[0006] "Means for obtaining location information" refers to technologies and devices for identifying the user's current location, and primarily utilizes the Global Positioning System (GPS).

[0007] "Means for collecting information on damage when a disaster occurs" refers to sensors and equipment for collecting information on damage when a disaster occurs, and includes multiple sensors such as vibration sensors and humidity sensors.

[0008] The "means for transmitting collected location information and damage status" refers to communication technology or devices for transmitting user location information and damage status data to a receiving device such as a server.

[0009] "Means for analyzing and selecting optimal recovery solutions" refers to technologies and software that analyze received location information and damage situation data and determine optimal recovery measures based on the results, and utilizes a geographic information system (GIS).

[0010] "Means for notifying disaster response personnel of the analysis results and the selected recovery solutions" refers to communication technologies and devices for communicating the analysis results and the selected recovery measures to disaster response personnel. [Brief explanation of the drawings]

[0011] [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

[0012] 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.

[0013] First, the terms used in the following description will be explained.

[0014] 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).

[0015] 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.

[0016] 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.

[0017] 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.

[0018] 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."

[0019] [First embodiment]

[0020] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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."

[0032] This invention is a system that aims to quickly and accurately grasp the damage situation when a disaster occurs and provide optimal recovery solutions. This system uses a GPS device embedded in the user to collect location information, and when a disaster occurs, it collects damage information through sensors. Based on the collected data, a server selects the optimal recovery solution and notifies disaster response personnel.

[0033] Program processing (outline)

[0034] 1. Location information acquisition:

[0035] The terminal periodically acquires the user's location information using GPS.

[0036] For example, the device identifies the user's location within Tokyo and collects the user's latitude and longitude information.

[0037] 2. Collecting damage information:

[0038] When a disaster occurs, the device uses built-in sensors (such as vibration sensors and humidity sensors) to collect data on the damage situation.

[0039] For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record the data.

[0040] 3. Data transmission:

[0041] The terminal transmits the collected location information and damage situation data to the server.

[0042] Specifically, the device transmits this data to a server via a mobile network or Wi-Fi.

[0043] 4. Data Receipt and Analysis:

[0044] The server receives the data sent from the device and analyzes the scope and scale of the damage.

[0045] For example, the server uses a geographic information system (GIS) to analyze the impact of building collapses or earthquakes in a particular area.

[0046] 5. Solution Selection:

[0047] The server selects the optimal recovery solution based on the analysis results.

[0048] For example, if communications infrastructure is severely damaged, drone base stations will be deployed to ensure communications.

[0049] 6. Sending notifications:

[0050] The server notifies disaster response personnel of the analysis results and the selected recovery solution.

[0051] For example, information such as "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications" will be sent to disaster response personnel.

[0052] Specific examples

[0053] 1. Obtaining location information

[0054] Terminal: If the user is in Shinjuku-ku, Tokyo, location information of latitude 35.6938 degrees and longitude 139.7034 degrees is obtained using GPS.

[0055] 2. Collecting information on damage

[0056] Terminal: When a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect strong shaking and record the data.

[0057] 3. Data transmission

[0058] Terminal: The collected location information and damage situation data is sent to the server via Wi-Fi.

[0059] 4. Data Receipt and Analysis

[0060] Server: Receives location information and vibration data from Shinjuku Ward and analyzes the state of building collapse using a geographic information system.

[0061] 5. Solution Selection

[0062] Server: After confirming that communication has been disrupted due to the collapse of a building, it is decided to deploy a drone base station.

[0063] 6. Sending Notifications

[0064] Server: Notifies disaster response personnel of the analysis results along with instructions for drone base station placement.

[0065] In this way, the present invention makes it possible to quickly and accurately grasp the extent of damage when a disaster occurs and to provide optimal recovery solutions, thereby significantly improving the efficiency of disaster response.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] The device periodically obtains the user's location information: the device's built-in GPS module receives signals from the Global Positioning System (GPS) and calculates the latitude and longitude coordinates.

[0069] Step 2:

[0070] The device temporarily stores the acquired location information in memory, thereby retaining the user's current location as data.

[0071] Step 3:

[0072] When a disaster occurs, the device activates various built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation. For example, if the vibration sensor detects earthquake tremors, it will record the strength and duration of the tremors.

[0073] Step 4:

[0074] The device compiles the collected location information and damage situation data into a single data package, which includes the user's latitude and longitude and damage information collected from sensors.

[0075] Step 5:

[0076] The device then sends the created data package to the server via a mobile network or Wi-Fi. Specifically, the device establishes communication with the server at regular intervals and transmits the data via the Internet.

[0077] Step 6:

[0078] The server receives the data package sent from the terminal, and according to the receiving protocol, the data is stored in the server's storage.

[0079] Step 7:

[0080] The server analyzes the received data. During the analysis process, a geographic information system (GIS) is used to identify the extent and scale of the damage and map the latitude and longitude information.

[0081] Step 8:

[0082] The server selects the optimal recovery solution based on the analysis results. For example, if widespread building collapse is confirmed, one option would be to use drone base stations to ensure communications.

[0083] Step 9:

[0084] The server creates a notification containing the selected recovery solution, along with details of the damage and instructions on how to implement the solution.

[0085] Step 10:

[0086] The server then sends the created notifications to disaster response personnel in real time via email or a dedicated application.

[0087] Step 11:

[0088] The user (disaster response officer) receives the notification and decides on a prompt response based on the information provided.

[0089] Step 12:

[0090] The user (disaster response officer) instructs the local response team on the decided response measures, for example, by issuing instructions to the local operator to deploy drone base stations, aiming to quickly restore the damage situation.

[0091] Through the above processing steps, the system of the present invention responds to disasters quickly and accurately, contributing to minimizing damage and improving the efficiency of recovery.

[0092] Example 1

[0093] 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."

[0094] When a disaster occurs, it is important to quickly and accurately grasp the damage situation, but current methods often result in delays in collecting and analyzing damage information. As a result, there is a problem of delays in selecting and implementing appropriate recovery solutions. Furthermore, there is an issue of the inability to respond to disasters quickly due to limited means of quickly communicating damage information.

[0095] 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.

[0096] In this invention, the server includes means for periodically acquiring user location information, means for collecting damage status using a built-in sensor when a disaster occurs, means for transmitting the collected location information and damage status data via a network, means for receiving the transmitted location information and damage status data and analyzing the range and scale of the damage using a geographic information system (GIS), means for automatically selecting an optimal recovery solution based on the analysis results, and means for notifying disaster response personnel of the selected recovery solution and the analysis results in real time, thereby enabling a quick and accurate understanding of the damage status and the provision of an optimal recovery solution.

[0097] The "means for periodically obtaining location information" is a device, system, or method for measuring and recording the latitude and longitude of the user's current location at regular intervals.

[0098] "Means for collecting damage information using built-in sensors when a disaster occurs" refers to a device, system, or method that uses various sensors built into a terminal, such as vibration sensors and humidity sensors, to obtain information on damage when a disaster occurs.

[0099] "Means for transmitting collected location information and damage situation data via a network" refers to a device, system, or method for transmitting collected data to a server using communication infrastructure such as Wi-Fi or a mobile network (LTE, 5G, etc.).

[0100] "Means for receiving the transmitted location information and damage situation data and analyzing the extent and scale of the damage using a geographic information system (GIS)" refers to a device, system, or method in which a server receives data sent from a terminal, analyzes it, and uses a geographic information system (GIS) to measure the extent and severity of the damage.

[0101] A "means for automatically selecting an optimal recovery solution based on analysis results" is a device, system, or method that uses an algorithm or program to automatically select the most effective recovery measures based on the results of data analysis.

[0102] "Means for notifying disaster response personnel of selected recovery solutions and analysis results in real time" means a device, system, or method that uses a communication device (e.g., smartphone, tablet, etc.) to quickly communicate selected recovery solutions and analysis results to disaster response personnel.

[0103] This invention is a system that aims to quickly and accurately grasp the damage situation when a disaster occurs and provide optimal recovery solutions. This system uses GPS devices and various sensors (vibration sensors, humidity sensors, etc.) embedded in the user's device to collect location information and disaster damage information, and sends the collected information to a server. The server analyzes this information, automatically selects the optimal recovery solution, and notifies disaster response personnel in real time.

[0104] Hardware and Software Details

[0105] The device uses the following hardware and software:

[0106] GPS module: A device for obtaining user location information. It outputs latitude and longitude information.

[0107] Vibration and humidity sensors: Devices for detecting vibrations and changes in humidity during disasters. Each sensor converts analog signals into digital data and stores it in its internal memory.

[0108] Communication module: A device that supports Wi-Fi and mobile networks (LTE, 5G, etc.) and transmits collected data to a server.

[0109] The server uses the following software:

[0110] Data receiving module: Receives location information and damage situation data sent from the terminal.

[0111] GIS (Geographic Information System): Software that analyzes received location information and damage situation data to visualize the scope and scale of damage.

[0112] Analysis and restoration solution selection algorithm: An algorithm that analyzes damage data and selects the optimal restoration solution (e.g., drone base station placement).

[0113] Notification module: Notifies disaster response personnel in real time of analysis results and selected recovery solutions.

[0114] Specific examples

[0115] For example, if a user is in Shinjuku Ward, Tokyo, the device will periodically obtain location information (latitude 35.6938 degrees, longitude 139.7034 degrees) using GPS. If a major earthquake occurs in Shinjuku Ward and the vibration sensor detects strong shaking, the device will record the data in its internal memory. The device will then use Wi-Fi if available, or send the location information and damage data to the server via the mobile network if not.

[0116] The server receives this data and uses GIS to analyze the impact of building collapses and earthquakes in a specific area. Based on the analysis results, the server selects the optimal recovery solution, for example, if communication infrastructure is damaged, it decides to deploy drone base stations. After making a decision, the server sends notifications to disaster response personnel in real time and instructs them on actual response measures.

[0117] Prompt Sentence Examples

[0118] An example of a prompt to be input to the generative AI model is as follows:

[0119] Location information acquisition: "If the user is in Shinjuku Ward, Tokyo, please use GPS to acquire latitude and longitude information."

[0120] Collecting damage information: "When a major earthquake occurs in Shinjuku Ward, please use the vibration sensor to record the strength of the shaking."

[0121] Data transmission: "Please send the collected location information and damage situation data to the server via Wi-Fi."

[0122] Receiving and analyzing data: "The server will receive location information and vibration data from Shinjuku Ward, and will use GIS to analyze the state of building collapse."

[0123] Solution Selection: "The server should determine the optimal recovery solution based on the analysis results, and decide to deploy a drone base station."

[0124] Send notification: "The server will notify disaster response personnel of the analysis results and provide instructions for drone base station placement."

[0125] In this way, the present invention realizes a system that enables rapid and accurate understanding of the damage situation and the provision of appropriate recovery solutions.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1:

[0128] Obtaining location information

[0129] The terminal acquires the user's location information at regular intervals using the GPS module.

[0130] Input: The device's built-in GPS module provides current latitude and longitude data.

[0131] Data processing: The acquired latitude and longitude data is recorded in the internal memory. For example, if the user is in Shinjuku Ward, Tokyo, the GPS module will generate information on latitude 35.6938 degrees and longitude 139.7034 degrees.

[0132] Output: Recorded location data.

[0133] Step 2:

[0134] Collecting information on damage

[0135] When the device detects signs of a disaster (such as an earthquake), it activates its built-in sensors (vibration sensor and humidity sensor).

[0136] Input: Earthquake tremors detected by a vibration sensor and humidity changes detected by a humidity sensor.

[0137] Data processing: The data acquired by the sensor is converted into a digital signal and stored in the internal memory. For example, if a major earthquake occurs in Shinjuku Ward and the vibration sensor detects strong shaking of magnitude 7, that data will be recorded.

[0138] Output: Recorded damage status data.

[0139] Step 3:

[0140] Sending data

[0141] The terminal transmits the acquired location information and damage situation data to a server via the network.

[0142] Input: Location information and damage situation data recorded in memory.

[0143] Data processing: Converts data into packets and prepares it for transmission. The device first checks whether a Wi-Fi connection is available, and if so, uses Wi-Fi to transmit the data. If Wi-Fi is not available, it uses the mobile network (LTE or 5G) to transmit the data.

[0144] Output: Location information and damage situation data sent to the server.

[0145] Step 4:

[0146] Data reception and analysis

[0147] The server receives and analyzes the data sent from the terminal.

[0148] Input: Received location information and damage situation data.

[0149] Data processing: Using a GIS (geographic information system), the received data is visualized on a map to analyze the extent and scale of the damage. For example, the GIS system generates a heat map of the affected area, visually showing the impact of a specific region.

[0150] Output: Analysis results of the extent and scale of damage.

[0151] Step 5:

[0152] Solution Selection

[0153] The server selects the optimal recovery solution based on the analysis results.

[0154] Input: Analysis results of the extent and scale of the damage.

[0155] Data processing: Based on the analysis results, an algorithm is run to automatically select the optimal recovery method (e.g., deploying a drone base station if communications infrastructure is damaged).

[0156] Output: The selected recovery solution.

[0157] Step 6:

[0158] Sending notifications

[0159] The server notifies disaster response personnel in real time of the analysis results and the selected recovery solution.

[0160] Input: Selected restoration solution and analysis results.

[0161] Data processing: Generates notification content and prepares it for transmission to communication devices (smartphones, tablets, etc.).

[0162] Output: A notification sent to disaster response personnel, including specific instructions such as "Large-scale building collapse confirmed in Shinjuku Ward. Deploy drone base stations to restore communications."

[0163] In this way, each step works in coordination to quickly and accurately grasp the extent of the damage and provide appropriate recovery solutions.

[0164] (Application example 1)

[0165] 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."

[0166] Conventional disaster management systems were slow to grasp the extent of damage when a disaster occurred, making it difficult to provide appropriate recovery solutions. Furthermore, the means of collecting damage data were limited, making it impossible to effectively collect and utilize real-time information from the site. As a result, disaster response was inefficient, and recovery was delayed, potentially leading to greater damage.

[0167] 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.

[0168] In this invention, the server includes means for acquiring location information, means for collecting damage status when a disaster occurs, means for transmitting the collected location information and damage status, means for analyzing the transmitted location information and damage status and selecting an optimal recovery solution, means for notifying disaster response personnel of the analysis results and the selected recovery solution, and means for collecting damage data using a smart device, thereby enabling the collection of damage information in real time and the provision of optimal recovery solutions.

[0169] "Location information" is latitude and longitude data that indicates a specific point on Earth.

[0170] "Damage situation" is data that indicates the extent of damage and impact to buildings and infrastructure when a disaster occurs.

[0171] The "server" is a central processing unit that analyzes the collected data and provides optimal recovery solutions.

[0172] A "GPS device" is a device that obtains location information using the Global Positioning System.

[0173] A "sensor" is a device that detects and collects data about the physical environment. Examples include vibration sensors and humidity sensors.

[0174] "Network interface" is a general term for hardware and software for wirelessly transmitting data to other devices or servers.

[0175] "Smart devices" refers to mobile terminals with advanced functions, including smart glasses and smartphones.

[0176] A "geographic information system (GIS)" is a system for analyzing and visualizing geospatial data.

[0177] A "generative AI model" is a model that uses machine learning and deep learning to analyze and predict data.

[0178] A "prompt sentence" is an instruction sentence in natural language format that is input to a generative AI model.

[0179] To implement this invention, a GPS device for acquiring location information, multiple sensors for collecting damage information, a network interface for transmitting data, and a server for analysis and notification are required. In particular, smart glasses and a smartphone are used as smart devices.

[0180] Obtaining location information

[0181] The server periodically obtains the user's location information using a GPS device, which is built into the smart glasses and smartphone, and accurately collects the user's current latitude and longitude information.

[0182] Collecting information on damage

[0183] When a disaster occurs, the server collects data on the damage situation using the vibration and humidity sensors built into smart devices. For example, if a major earthquake occurs, the vibration sensor will detect strong shaking and record that data.

[0184] Sending data

[0185] The collected location information and damage situation data are sent to a server via a network interface. Specifically, smart devices use mobile networks or Wi-Fi to send this data to the server.

[0186] Data reception and analysis

[0187] The server receives the data sent from the devices and uses a geographic information system (GIS) to analyze the extent and scale of the damage, making it possible to clarify the extent of building collapses and the impact of the earthquake in a specific area.

[0188] Selecting a recovery solution

[0189] The server uses a generative AI model to select the optimal recovery solution, using prompts to input to the generative AI model for analysis.

[0190] Sending notifications

[0191] The analysis results and the selected restoration solution are then communicated to disaster response personnel. For example, if communications infrastructure is severely damaged, the server will instruct drone base stations to be deployed to restore communications.

[0192] Specific examples

[0193] If the user is in Shinjuku Ward, Tokyo, the smart glasses' GPS will be used to obtain location information at latitude 35.6938 degrees and longitude 139.7034 degrees. When a major earthquake occurs in Shinjuku Ward, the smart glasses' vibration sensor will detect strong shaking and send the data to a server via Wi-Fi. The server will use a geographic information system to analyze the state of building collapse and, since communication disruptions have been confirmed, will decide to deploy a drone base station. Disaster response personnel will receive a notification stating, "Large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communication."

[0194] Prompt Sentence Examples

[0195] "When a large earthquake occurs, please explain the system in which a server analyzes the damage situation based on data detected by vibration sensors and location information obtained by GPS devices, and selects the optimal recovery solution. In this system, smart glasses have built-in sensors and GPS devices that collect and communicate data. Example: Specific processing procedures when a large earthquake occurs in Shinjuku Ward."

[0196] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0197] Step 1: Obtaining location information

[0198] The server periodically obtains the user's location information using a GPS device. The input is the user's current location, and the output is latitude and longitude data. This data is collected from GPS devices built into smart glasses or smartphones. For example, if a user is in Shinjuku Ward, Tokyo, the server collects location information of latitude 35.6938 degrees and longitude 139.7034 degrees.

[0199] Step 2: Collect damage information

[0200] When a disaster occurs, the server collects data on the damage situation using sensors (vibration sensors and humidity sensors) built into smart devices. The input is sensor data, and the output is damage situation data such as earthquake shaking and humidity changes. For example, when a major earthquake occurs, the vibration sensor in the smart glasses detects strong shaking and records that data.

[0201] Step 3: Sending data

[0202] The server transmits the collected location information and damage status data through a network interface. Location information and damage status data are input, and these data are sent to the server as output. This transmission is done from the smart device using a mobile network or Wi-Fi. For example, location information and vibration data collected in Shinjuku Ward are sent to the server via Wi-Fi.

[0203] Step 4: Receiving and analyzing data

[0204] The server receives the data sent from the terminals and uses a geographic information system (GIS) to analyze the extent and scale of the damage. Location information and damage data are input, and damage analysis results are obtained as output. For example, the server receives location information and vibration data from Shinjuku Ward and analyzes the collapse and impact of buildings in that area.

[0205] Step 5: Select a recovery solution

[0206] The server uses a generative AI model based on the analysis results to select the optimal recovery solution. This analysis is driven by a prompt statement. The inputs are the damage analysis results and the prompt statement, and the output is a specific recovery solution. For example, the server may determine that communication infrastructure is damaged and decide to deploy a drone base station.

[0207] Step 6: Sending notifications

[0208] The server notifies disaster response personnel of the analysis results and the selected recovery solution. The inputs are the recovery solution and notification text, and the output is the notification that is sent to the personnel. For example, disaster response personnel receive information such as, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications."

[0209] 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.

[0210] This invention is a system that, in addition to quickly and accurately grasping the damage situation and providing optimal recovery solutions when a disaster occurs, recognizes the user's emotions and takes these into consideration when responding. This system uses a GPS device and emotion engine embedded in the user to collect location information and emotion data, and transmits the damage situation and emotion data to a server when a disaster occurs. The server analyzes the collected data and works with the emotion engine to provide optimal recovery solutions and communicates with the user in a way that takes their emotions into consideration.

[0211] Program processing (outline)

[0212] 1. Location and emotion data acquisition:

[0213] The device periodically acquires the user's location information using GPS and collects the user's emotion data using an emotion engine.

[0214] For example, if the device is located within Tokyo, it will analyze the user's location information (latitude and longitude) and their voice and facial expressions to collect emotions (such as stress level).

[0215] 2. Collecting damage information:

[0216] When a disaster occurs, the device activates its built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation.

[0217] For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record the data.

[0218] 3. Creating and sending a data package:

[0219] The device compiles the collected location information, damage situation data, and user emotion data into a single data package and sends it to the server.

[0220] Specifically, the device transmits this data to a server via a mobile network or Wi-Fi.

[0221] 4. Data Receipt and Analysis:

[0222] The server receives the data package sent from the device and analyzes the scope and scale of the damage, as well as the user's emotional state.

[0223] For example, the server may use a geographic information system (GIS) to analyze the impact of building collapses or earthquakes in a particular area, while simultaneously using an emotion engine to assess the user's stress level.

[0224] 5. Solution Selection and Emotional Response:

[0225] The server selects the optimal recovery solution based on the analysis results, and also selects the optimal communication method taking into account the user's emotional data.

[0226] For example, if communications infrastructure is severely damaged, drone base stations can be used to ensure communications, while psychological care information can be provided to users experiencing high levels of stress.

[0227] 6. Create and send notifications:

[0228] The server creates a notification containing the analysis results and the selected recovery solution, and sends it to disaster response personnel and relevant users. The notification to users is sensitive to their emotions.

[0229] For example, disaster response personnel could be notified that "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications," while users could be sent reassuring messages such as "The current situation is serious, but please rest assured, recovery work is underway."

[0230] Specific examples

[0231] 1. Obtaining location and emotion data

[0232] Device: If the user is in Shinjuku Ward, Tokyo, location information of latitude 35.6938 degrees and longitude 139.7034 degrees is obtained using GPS, and at the same time, the stress level is evaluated from the user's voice and facial expression.

[0233] 2. Collecting information on damage

[0234] Terminal: When a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect strong shaking and record the data.

[0235] 3. Creating and sending a data package

[0236] Terminal: Sends location information, damage situation data, and emotion data together to the server.

[0237] 4. Data Receipt and Analysis

[0238] Server: Receives location information, vibration data, and emotion data from Shinjuku Ward and analyzes the data using a geographic information system and emotion engine.

[0239] 5. Solution selection and emotional response

[0240] Server: After building collapses and communication disruptions were confirmed, drone base stations were deployed and psychological care information was provided to users with high stress levels.

[0241] 6. Creating and sending notifications

[0242] Server: Sends detailed notifications along with the analysis results to disaster response personnel, and notifies users with reassurance.

[0243] In this way, the system of the present invention not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also takes user emotions into consideration when responding to disasters, enabling more effective disaster response.

[0244] The processing flow will be explained below.

[0245] Step 1:

[0246] The device periodically obtains the user's location information. Specifically, the device's built-in GPS module receives signals from the Global Positioning System (GPS) and calculates the latitude and longitude coordinates.

[0247] Step 2:

[0248] The device temporarily stores the acquired location information in memory, thereby retaining the user's current location as data.

[0249] Step 3:

[0250] The device uses an emotion engine to acquire the user's emotion data. Specifically, it collects and analyzes the user's voice data and facial expression data to determine their emotional state (e.g., stress level, sense of relief, anxiety).

[0251] Step 4:

[0252] When a disaster occurs, the device activates its built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation. For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record that data.

[0253] Step 5:

[0254] The device compiles the collected location information, emotional data, and damage situation data into a single data package, which includes the user's latitude and longitude, emotional state, and damage information collected from sensors.

[0255] Step 6:

[0256] The device then sends the created data package to the server via a mobile network or Wi-Fi. Specifically, the device establishes communication with the server at regular intervals and transmits the data via the Internet.

[0257] Step 7:

[0258] The server receives the data package sent from the terminal, and according to the receiving protocol, the data is stored in the server's storage.

[0259] Step 8:

[0260] The server analyzes the received data. During the analysis process, it uses a geographic information system (GIS) to identify the extent and scale of the damage and map the latitude and longitude information. At the same time, it uses an emotion engine to evaluate the user's emotional state.

[0261] Step 9:

[0262] The server then selects the optimal recovery solution based on the analysis results. For example, if widespread building collapse is confirmed, it will use drone base stations to ensure communications. On the other hand, if the user's stress level is high, it will include the option to provide psychological care information.

[0263] Step 10:

[0264] The server then creates a notification containing the selected recovery solution, detailing the damage situation and specific steps to implement the solution, and creating communication content that takes into account the user's emotional state.

[0265] Step 11:

[0266] The server then sends the created notifications to disaster response personnel and relevant users. The notifications are sent in real time via email or a dedicated application. The notifications to users are sent with emotional sensitivity.

[0267] Step 12:

[0268] The user (disaster response personnel) receives the notification. After checking the notification, the personnel in charge decide on a prompt response based on the provided information. For example, they issue instructions to the local operator to deploy a drone base station.

[0269] Step 13:

[0270] The user (disaster response officer) then instructs the local response team on the decided response measures, which allows for a quick and effective assessment of the damage situation and progress in recovery work.

[0271] Step 14:

[0272] The user (general user) checks the notification from the server. The notification is sensitive to the user's feelings and includes information on psychological care, giving the user a sense of security.

[0273] In this way, the system of the present invention not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also takes user emotions into consideration when responding to disasters, enabling more effective disaster response.

[0274] Example 2

[0275] 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."

[0276] Conventional disaster response systems are slow to grasp the extent of the damage, making it difficult to provide effective recovery solutions quickly. Furthermore, they do not take into account the emotional state of users, resulting in a lack of psychological support. Therefore, there is a need for systems that can accurately grasp the disaster situation and respond quickly while taking into account users' emotions.

[0277] 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.

[0278] In this invention, the server includes means for acquiring location information and emotion data, means for collecting damage status when a disaster occurs, and means for transmitting the collected location information, emotion data, and damage status, thereby enabling a quick and accurate understanding of the damage status and providing optimal recovery solutions that take into consideration the user's emotions.

[0279] "Location information" refers to data indicating the geographic coordinates of a user's current location, such as latitude and longitude.

[0280] "Emotion data" is data that indicates the user's emotional state, and includes stress levels and types of emotions obtained by analyzing voice and facial expressions.

[0281] "Means of collection" refers to the technologies and devices used to collect data, including sensors and analytics engines.

[0282] "Transmission means" refers to the methods or technologies used to send collected data to other devices or servers, including mobile networks and Wi-Fi.

[0283] "Means for analysis" refers to the technology or equipment used to process received data and understand its content, including geographic information systems (GIS) and sentiment analysis engines.

[0284] "Recovery solutions" refer to specific measures and methods for minimizing damage after a disaster and quickly restoring social functions.

[0285] "Means of notification" refers to the technology or devices used to communicate analysis results and recovery solutions to relevant personnel and users, including text messaging and notification applications.

[0286] overview

[0287] This invention is a system for quickly and accurately assessing the damage situation and providing optimal recovery solutions when a disaster occurs. It also recognizes the user's emotions and responds accordingly. In this system, the device collects the user's location information and emotional data, and sends them to a server along with damage situation data when a disaster occurs. The server analyzes this data, selects the optimal recovery solution and emotional response measures, and notifies the user.

[0288] Specific Embodiments

[0289] 1. Using the Device

[0290] The device uses a built-in GPS module to periodically obtain the user's location information, while at the same time utilizing an emotion engine to analyze and collect the user's emotions from voice and facial expression data. This emotion engine uses voice recognition software and image analysis algorithms.

[0291] Example: Obtain the location information (latitude 35.6938 degrees, longitude 139.7034 degrees) of a user in Shinjuku Ward, Tokyo, and use the emotion engine to analyze the user's voice and facial expressions to assess their stress level.

[0292] 2. Collecting information on damage

[0293] The device activates vibration and humidity sensors in the event of a disaster to collect data on the damage situation. For example, in the event of a major earthquake, the vibration sensor detects strong shaking and records that data. The humidity sensor also measures humidity levels in the event of flooding.

[0294] Example: If a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect high vibrations (e.g., seismic intensity of 6+) and the humidity sensor will measure high humidity (e.g., humidity of 90% or higher).

[0295] 3. Creating and sending a data package

[0296] The device then compiles the collected location information, emotion data, and damage situation data into a single data package, which also includes timestamps for each type of data.

[0297] The device then sends this data package over the mobile network or Wi-Fi to a server, which also encrypts the data before sending it.

[0298] 4. Data analysis on the server

[0299] The server receives the data package sent from the device, unpacks it, and analyzes the various data. Specifically, it uses a geographic information system (GIS) to analyze location information and evaluate the extent and scale of damage in a specific area. It also uses an emotion analysis engine to evaluate emotional data and quantify stress levels.

[0300] Example: Analyzing location information, vibration data, and emotion data in Shinjuku Ward to identify the extent of building collapse and assess the user's stress level.

[0301] 5. Selecting the best recovery solution and emotional response

[0302] The server selects the optimal recovery solution based on the results of the GIS and emotion analysis engine. For example, if there is significant damage to the communications infrastructure, it will deploy a drone base station to ensure communications. It also provides psychological care information based on the user's emotional state.

[0303] Example: If a communication failure is confirmed, a drone base station will be deployed in Shinjuku Ward to restore communication, and psychological care information will be provided to users experiencing high levels of stress.

[0304] 6. Creating and sending notifications

[0305] Based on the analysis and the selected recovery solution, the server generates messages to notify disaster response personnel and users. These notifications include appropriate timestamps and details of specific actions to be taken.

[0306] Example: Disaster response personnel could be notified, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy drone base stations to restore communications," while users could be notified, "The current situation is serious, but please rest assured, recovery work is underway."

[0307] Prompt Sentence Examples

[0308] "Please execute the emergency response protocol in the event of a major earthquake in Shinjuku Ward, Tokyo. Obtain the user's location information and emotion data and send it to the server along with damage status data."

[0309] In this way, the present invention enables effective disaster response by quickly and accurately grasping the damage situation when a disaster occurs and providing optimal recovery solutions that take into consideration the feelings of users.

[0310] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0311] Program processing flow

[0312] Step 1: Obtaining location and emotion data

[0313] The device obtains the user's location information using the built-in GPS module. The input for this operation is the signal from the GPS satellites, and the output is the user's current location (latitude and longitude).

[0314] Specific operation: For a user in Shinjuku Ward, Tokyo, the device obtains location information of latitude 35.6938 degrees and longitude 139.7034 degrees.

[0315] The device activates an emotion engine to analyze the user's voice and facial expressions in real time. The input for this operation is the user's voice and facial image, and the output is the user's emotional data (such as stress level).

[0316] Specific behavior: Analyzes the user's voice and facial expressions to recognize high stress levels.

[0317] Step 2: Collect damage information

[0318] When a disaster occurs, the terminal activates various sensors, such as vibration sensors and humidity sensors. The input for this operation is physical vibrations and changes in humidity, and the output is damage situation data.

[0319] Specific operation: When a major earthquake occurs, the vibration sensor detects and records shaking of a seismic intensity of 6+. The humidity sensor also measures humidity levels of 90% or higher.

[0320] Step 3: Creating and sending a data package

[0321] The terminal processes the collected location information, damage situation data, and emotion data into a single data package. The inputs for this operation are location information, emotion data, and damage situation data, and the output is a data package.

[0322] Specific operation: The device combines location information, emotional data indicating high stress levels, and vibration sensor data into a single package.

[0323] The device sends data packages to the server via a mobile network or Wi-Fi. The input is the data package, and the output is a notification of successful transmission.

[0324] What it does: Encrypts the data package and sends it to a server over the mobile network.

[0325] Step 4: Receiving and analyzing data

[0326] The server receives the data package sent from the terminal. The input of this operation is the data package, and the output is the data to be analyzed.

[0327] Specific operation: The received data package is unzipped and each piece of data is extracted for analysis.

[0328] The server analyzes the location information using a geographic information system (GIS) and simultaneously evaluates the emotional data using an emotion engine. The inputs of this operation are location information and emotional data, and the output is the identification of the damage extent and the evaluation of the stress level.

[0329] Specific operation: Identifies the extent of building collapse based on location information in Shinjuku Ward and evaluates the user's stress level.

[0330] Step 5: Selecting a solution and responding emotionally

[0331] The server selects the optimal recovery solution based on the analysis results. The input of this operation is the analysis results, and the output is the recovery solution.

[0332] Specific operation: If a building collapse and communication failure are confirmed, a solution will be selected to restore communication by placing a drone base station.

[0333] The server selects a communication method according to the user's emotional state. The input of this operation is the emotional evaluation result, and the output is an emotional response plan.

[0334] Specific operation: Provide psychological care information to users with high stress levels.

[0335] Step 6: Create and send notifications

[0336] The server generates a notification based on the analysis results and the selected recovery solution. The inputs to this operation are the analysis results and the solution, and the output is the notification.

[0337] Specific operation: The system notifies the person in charge, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications," and generates a message for the user saying, "The current situation is serious, but please rest assured, recovery work is underway."

[0338] The server then sends the created notification to the disaster response staff and the user. The input for this operation is the notification, and the output is a notification of successful transmission.

[0339] Specific operation: Sends notification text using messaging applications or SMS.

[0340] Through these steps, the system is able to quickly and accurately grasp the extent of the damage and provide optimal recovery solutions that take the user's feelings into consideration.

[0341] (Application example 2)

[0342] 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."

[0343] In disasters and emergencies, it is important to quickly and accurately grasp the damage situation and respond effectively to recovery. However, conventional systems do not take the user's emotional state into consideration when communicating. Furthermore, there is a lack of means to analyze the user's emotional data in real time and provide appropriate responses based on that analysis. Therefore, there is a need for the development of a system that provides quick and effective response measures while reducing the psychological burden on users in emergencies.

[0344] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0345] In this invention, the server includes means for acquiring location information and emotion data, means for generating and transmitting a data package of the damage situation and emotion data, means for analyzing the transmitted data package and selecting an optimal recovery solution, and means for generating and transmitting notification content taking the user's emotion data into consideration, thereby enabling a quick and accurate understanding of the damage situation and effective recovery measures that take the user's emotional state into consideration.

[0346] "Means for acquiring location information" refers to a device or software that receives signals from satellites or ground landmarks to acquire latitude and longitude data in order to identify the user's current location.

[0347] "Means for collecting damage information when a disaster occurs" refers to equipment or software that uses multiple sensors and devices to collect damage information such as building damage and earthquake intensity when a disaster occurs.

[0348] The "means for generating and transmitting a data package" refers to a device or software that assembles the collected location information, damage situation data, and emotion data into a single information packet and transmits it to a server.

[0349] The "means for selecting the optimal recovery solution" is a device or software that analyzes the transmitted data and determines the optimal recovery method or measures based on the extent of the damage and the user's emotional state.

[0350] The "means for recognizing and analyzing user emotional data" refers to a device or software for analyzing the user's voice and facial expressions and determining their emotional state.

[0351] The "means for generating and transmitting notification content" refers to a device or software that generates a notification with appropriate content based on the damage situation and the user's emotions, and transmits it to the user and disaster response personnel.

[0352] The Global Positioning System (GPS) is a system that uses satellites to calculate specific geographic locations and obtain user location information.

[0353] "Multiple built-in sensors" refers to a group of sensors built into a device that collect various environmental information such as vibration, humidity, and temperature.

[0354] A "geographic information system (GIS)" is software for managing, analyzing, and visually displaying geographic data.

[0355] This invention is a system that not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also recognizes the user's emotional state and takes this into consideration when responding. This system is mainly composed of terminals and a server, and each terminal collects location information and emotional data, which the server analyzes and provides appropriate responses.

[0356] System Configuration

[0357] Terminal

[0358] Hardware

[0359] Mobile communication devices such as smartphones

[0360] Built-in GPS module

[0361] Multiple built-in sensors (vibration sensor, humidity sensor, temperature sensor, etc.)

[0362] Camera and microphone

[0363] software

[0364] Location information acquisition module

[0365] Emotion analysis module (performs voice analysis and facial expression analysis)

[0366] Data package generation and transmission module

[0367] server

[0368] Hardware

[0369] High-performance computers

[0370] software

[0371] Data Receiving Module

[0372] Data analysis module (including a geographic information system (GIS) and sentiment analysis engine)

[0373] Restoration Solution Selection Module

[0374] Notification Generation and Sending Module

[0375] Processing steps

[0376] Location and emotion data acquisition

[0377] The device periodically obtains the user's location information using a GPS module. It also uses a camera and microphone to analyze the user's voice and facial expressions to collect emotional data. This allows the device to obtain the user's latitude (35.6938 degrees) and longitude (139.7034 degrees) if the user is in Tokyo, and simultaneously analyze the user's stress level.

[0378] Collecting information on damage

[0379] When a disaster occurs, the device uses its built-in sensors to collect information on the damage situation. For example, if a major earthquake occurs, the vibration sensor will detect strong shaking and record that data.

[0380] Creating and sending data packages

[0381] The device compiles location information, damage situation data, and emotion data into a single data package and sends it to a server via a mobile network or Wi-Fi.

[0382] Data reception and analysis

[0383] The server receives the data packages sent from the devices and analyzes the extent and scale of the damage, as well as the user's emotional state. It uses a geographic information system (GIS) to analyze the impact of building collapses and earthquakes in a specific area, while simultaneously using an emotion engine to assess the user's stress level.

[0384] Solution selection and emotional response

[0385] The server selects the optimal recovery solution based on the analysis results. It also considers the user's emotional data to select the optimal communication method. For example, if the communications infrastructure is severely damaged, it will use drone base stations to ensure communications. Meanwhile, it will provide psychological care information to users experiencing high levels of stress.

[0386] Creating and sending notifications

[0387] The server creates a notification containing the analysis results and the selected recovery solution, and sends it to disaster response personnel and the appropriate users. The notification to users is sensitive to their emotions. For example, disaster response personnel might be notified that "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy drone base stations to restore communications," while users might be notified with a message that provides reassurance, such as "The current situation is serious, but please rest assured that recovery work is underway."

[0388] Adding specific examples

[0389] Example 1: Obtaining location and emotion data

[0390] Example prompt:

[0391] "Collect audio data to analyze the user's stress level and obtain latitude and longitude location information."

[0392] Example 2: Anomaly detection and response

[0393] Example prompt:

[0394] "If the user is in a state of extreme stress, contact the police and notify the user."

[0395] In this way, the system of the present invention makes it possible to quickly and accurately grasp the extent of damage and to take effective recovery measures while taking into consideration the emotional state of the user.

[0396] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0397] Step 1:

[0398] The device periodically obtains the user's location information using a GPS module. The input data is signals obtained from satellites, and the device calculates the latitude and longitude based on this. The output data is the user's current location information (e.g., latitude 35.6938 degrees, longitude 139.7034 degrees).

[0399] Step 2:

[0400] The device uses a camera and microphone to collect the user's voice and facial expressions. The input data is the user's facial image captured by the camera and the voice data recorded by the microphone. This data is input into an emotion analysis module to analyze the user's stress level and emotional state. The output data is the user's emotional data (e.g., high stress level).

[0401] Step 3:

[0402] The device constantly monitors the surrounding situation using built-in sensors (e.g., vibration sensor, humidity sensor). When a disaster occurs, these sensors collect data on the damage situation. The input data is shaking intensity data from the vibration sensor and humidity data from the humidity sensor. The output data is damage situation data (e.g., strong shaking, humidity changes).

[0403] Step 4:

[0404] The device compiles the obtained location information, emotion data, and damage situation data into a single data package. The input data is the information obtained at each step (location information, emotion data, damage situation data). The output data is the compiled data package.

[0405] Step 5:

[0406] The terminal transmits the generated data package to the server using a mobile network or Wi-Fi. The input data is the data package, and the output data is the data package received by the server.

[0407] Step 6:

[0408] The server analyzes the received data package. The input data is the data package sent from the device, and it analyzes it using a geographic information system (GIS) and an emotion analysis engine. The output data is the range and scale of the damage, as well as evaluation information on the user's emotional state.

[0409] Step 7:

[0410] The server selects the optimal recovery solution based on the analysis results. The input data are the analysis results, and based on these, the optimal recovery method (e.g., the placement of drone base stations or the provision of psychological care information) is determined. The output data is the selected recovery solution.

[0411] Step 8:

[0412] The server creates a notification containing the selected recovery solution and the analysis results, and sends it to disaster response personnel and appropriate users. The input data are the recovery solution and the analysis results, and the output data is the configured notification content.

[0413] Step 9:

[0414] The user can receive notifications from the server and feel secure. The input data is the notification sent from the server, and the output data is the user's sense of security.

[0415] 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.

[0416] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0417] 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.

[0418] [Second embodiment]

[0419] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0420] 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.

[0421] 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).

[0422] 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.

[0423] 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.

[0424] 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).

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] 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.

[0430] 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."

[0431] This invention is a system that aims to quickly and accurately grasp the damage situation when a disaster occurs and provide optimal recovery solutions. This system uses a GPS device embedded in the user to collect location information, and when a disaster occurs, it collects damage information through sensors. Based on the collected data, a server selects the optimal recovery solution and notifies disaster response personnel.

[0432] Program processing (outline)

[0433] 1. Location information acquisition:

[0434] The terminal periodically acquires the user's location information using GPS.

[0435] For example, the device identifies the user's location within Tokyo and collects the user's latitude and longitude information.

[0436] 2. Collecting damage information:

[0437] When a disaster occurs, the device uses built-in sensors (such as vibration sensors and humidity sensors) to collect data on the damage situation.

[0438] For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record the data.

[0439] 3. Data transmission:

[0440] The terminal transmits the collected location information and damage situation data to the server.

[0441] Specifically, the device transmits this data to a server via a mobile network or Wi-Fi.

[0442] 4. Data Receipt and Analysis:

[0443] The server receives the data sent from the device and analyzes the scope and scale of the damage.

[0444] For example, the server uses a geographic information system (GIS) to analyze the impact of building collapses or earthquakes in a particular area.

[0445] 5. Solution Selection:

[0446] The server selects the optimal recovery solution based on the analysis results.

[0447] For example, if communications infrastructure is severely damaged, drone base stations will be deployed to ensure communications.

[0448] 6. Sending notifications:

[0449] The server notifies disaster response personnel of the analysis results and the selected recovery solution.

[0450] For example, information such as "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications" will be sent to disaster response personnel.

[0451] Specific examples

[0452] 1. Obtaining location information

[0453] Terminal: If the user is in Shinjuku-ku, Tokyo, location information of latitude 35.6938 degrees and longitude 139.7034 degrees is obtained using GPS.

[0454] 2. Collecting information on damage

[0455] Terminal: When a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect strong shaking and record the data.

[0456] 3. Data transmission

[0457] Terminal: The collected location information and damage situation data is sent to the server via Wi-Fi.

[0458] 4. Data Receipt and Analysis

[0459] Server: Receives location information and vibration data from Shinjuku Ward and analyzes the state of building collapse using a geographic information system.

[0460] 5. Solution Selection

[0461] Server: After confirming that communication has been disrupted due to the collapse of a building, it is decided to deploy a drone base station.

[0462] 6. Sending Notifications

[0463] Server: Notifies disaster response personnel of the analysis results along with instructions for drone base station placement.

[0464] In this way, the present invention makes it possible to quickly and accurately grasp the extent of damage when a disaster occurs and to provide optimal recovery solutions, thereby significantly improving the efficiency of disaster response.

[0465] The processing flow will be explained below.

[0466] Step 1:

[0467] The device periodically obtains the user's location information: the device's built-in GPS module receives signals from the Global Positioning System (GPS) and calculates the latitude and longitude coordinates.

[0468] Step 2:

[0469] The device temporarily stores the acquired location information in memory, thereby retaining the user's current location as data.

[0470] Step 3:

[0471] When a disaster occurs, the device activates various built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation. For example, if the vibration sensor detects earthquake tremors, it will record the strength and duration of the tremors.

[0472] Step 4:

[0473] The device compiles the collected location information and damage situation data into a single data package, which includes the user's latitude and longitude and damage information collected from sensors.

[0474] Step 5:

[0475] The device then sends the created data package to the server via a mobile network or Wi-Fi. Specifically, the device establishes communication with the server at regular intervals and transmits the data via the Internet.

[0476] Step 6:

[0477] The server receives the data package sent from the terminal, and according to the receiving protocol, the data is stored in the server's storage.

[0478] Step 7:

[0479] The server analyzes the received data. During the analysis process, a geographic information system (GIS) is used to identify the extent and scale of the damage and map the latitude and longitude information.

[0480] Step 8:

[0481] The server selects the optimal recovery solution based on the analysis results. For example, if widespread building collapse is confirmed, one option would be to use drone base stations to ensure communications.

[0482] Step 9:

[0483] The server creates a notification containing the selected recovery solution, along with details of the damage and instructions on how to implement the solution.

[0484] Step 10:

[0485] The server then sends the created notifications to disaster response personnel in real time via email or a dedicated application.

[0486] Step 11:

[0487] The user (disaster response officer) receives the notification and decides on a prompt response based on the information provided.

[0488] Step 12:

[0489] The user (disaster response officer) instructs the local response team on the decided response measures, for example, by issuing instructions to the local operator to deploy drone base stations, aiming to quickly restore the damage situation.

[0490] Through the above processing steps, the system of the present invention responds to disasters quickly and accurately, contributing to minimizing damage and improving the efficiency of recovery.

[0491] Example 1

[0492] 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."

[0493] When a disaster occurs, it is important to quickly and accurately grasp the damage situation, but current methods often result in delays in collecting and analyzing damage information. As a result, there is a problem of delays in selecting and implementing appropriate recovery solutions. Furthermore, there is an issue of the inability to respond to disasters quickly due to limited means of quickly communicating damage information.

[0494] 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.

[0495] In this invention, the server includes means for periodically acquiring user location information, means for collecting damage status using a built-in sensor when a disaster occurs, means for transmitting the collected location information and damage status data via a network, means for receiving the transmitted location information and damage status data and analyzing the range and scale of the damage using a geographic information system (GIS), means for automatically selecting an optimal recovery solution based on the analysis results, and means for notifying disaster response personnel of the selected recovery solution and the analysis results in real time, thereby enabling a quick and accurate understanding of the damage status and the provision of an optimal recovery solution.

[0496] The "means for periodically obtaining location information" is a device, system, or method for measuring and recording the latitude and longitude of the user's current location at regular intervals.

[0497] "Means for collecting damage information using built-in sensors when a disaster occurs" refers to a device, system, or method that uses various sensors built into a terminal, such as vibration sensors and humidity sensors, to obtain information on damage when a disaster occurs.

[0498] "Means for transmitting collected location information and damage situation data via a network" refers to a device, system, or method for transmitting collected data to a server using communication infrastructure such as Wi-Fi or a mobile network (LTE, 5G, etc.).

[0499] "Means for receiving the transmitted location information and damage situation data and analyzing the extent and scale of the damage using a geographic information system (GIS)" refers to a device, system, or method in which a server receives data sent from a terminal, analyzes it, and uses a geographic information system (GIS) to measure the extent and severity of the damage.

[0500] A "means for automatically selecting an optimal recovery solution based on analysis results" is a device, system, or method that uses an algorithm or program to automatically select the most effective recovery measures based on the results of data analysis.

[0501] "Means for notifying disaster response personnel of selected recovery solutions and analysis results in real time" means a device, system, or method that uses a communication device (e.g., smartphone, tablet, etc.) to quickly communicate selected recovery solutions and analysis results to disaster response personnel.

[0502] This invention is a system that aims to quickly and accurately grasp the damage situation when a disaster occurs and provide optimal recovery solutions. This system uses GPS devices and various sensors (vibration sensors, humidity sensors, etc.) embedded in the user's device to collect location information and disaster damage information, and sends the collected information to a server. The server analyzes this information, automatically selects the optimal recovery solution, and notifies disaster response personnel in real time.

[0503] Hardware and Software Details

[0504] The device uses the following hardware and software:

[0505] GPS module: A device for obtaining user location information. It outputs latitude and longitude information.

[0506] Vibration and humidity sensors: Devices for detecting vibrations and changes in humidity during disasters. Each sensor converts analog signals into digital data and stores it in its internal memory.

[0507] Communication module: A device that supports Wi-Fi and mobile networks (LTE, 5G, etc.) and transmits collected data to a server.

[0508] The server uses the following software:

[0509] Data receiving module: Receives location information and damage situation data sent from the terminal.

[0510] GIS (Geographic Information System): Software that analyzes received location information and damage situation data to visualize the scope and scale of damage.

[0511] Analysis and restoration solution selection algorithm: An algorithm that analyzes damage data and selects the optimal restoration solution (e.g., drone base station placement).

[0512] Notification module: Notifies disaster response personnel in real time of analysis results and selected recovery solutions.

[0513] Specific examples

[0514] For example, if a user is in Shinjuku Ward, Tokyo, the device will periodically obtain location information (latitude 35.6938 degrees, longitude 139.7034 degrees) using GPS. If a major earthquake occurs in Shinjuku Ward and the vibration sensor detects strong shaking, the device will record the data in its internal memory. The device will then use Wi-Fi if available, or send the location information and damage data to the server via the mobile network if not.

[0515] The server receives this data and uses GIS to analyze the impact of building collapses and earthquakes in a specific area. Based on the analysis results, the server selects the optimal recovery solution, for example, if communication infrastructure is damaged, it decides to deploy drone base stations. After making a decision, the server sends notifications to disaster response personnel in real time and instructs them on actual response measures.

[0516] Prompt Sentence Examples

[0517] An example of a prompt to be input to the generative AI model is as follows:

[0518] Location information acquisition: "If the user is in Shinjuku Ward, Tokyo, please use GPS to acquire latitude and longitude information."

[0519] Collecting damage information: "When a major earthquake occurs in Shinjuku Ward, please use the vibration sensor to record the strength of the shaking."

[0520] Data transmission: "Please send the collected location information and damage situation data to the server via Wi-Fi."

[0521] Receiving and analyzing data: "The server will receive location information and vibration data from Shinjuku Ward, and will use GIS to analyze the state of building collapse."

[0522] Solution Selection: "The server should determine the optimal recovery solution based on the analysis results, and decide to deploy a drone base station."

[0523] Send notification: "The server will notify disaster response personnel of the analysis results and provide instructions for drone base station placement."

[0524] In this way, the present invention realizes a system that enables rapid and accurate understanding of the damage situation and the provision of appropriate recovery solutions.

[0525] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0526] Step 1:

[0527] Obtaining location information

[0528] The terminal acquires the user's location information at regular intervals using the GPS module.

[0529] Input: The device's built-in GPS module provides current latitude and longitude data.

[0530] Data processing: The acquired latitude and longitude data is recorded in the internal memory. For example, if the user is in Shinjuku Ward, Tokyo, the GPS module will generate information on latitude 35.6938 degrees and longitude 139.7034 degrees.

[0531] Output: Recorded location data.

[0532] Step 2:

[0533] Collecting information on damage

[0534] When the device detects signs of a disaster (such as an earthquake), it activates its built-in sensors (vibration sensor and humidity sensor).

[0535] Input: Earthquake tremors detected by a vibration sensor and humidity changes detected by a humidity sensor.

[0536] Data processing: The data acquired by the sensor is converted into a digital signal and stored in the internal memory. For example, if a major earthquake occurs in Shinjuku Ward and the vibration sensor detects strong shaking of magnitude 7, that data will be recorded.

[0537] Output: Recorded damage status data.

[0538] Step 3:

[0539] Sending data

[0540] The terminal transmits the acquired location information and damage situation data to a server via the network.

[0541] Input: Location information and damage situation data recorded in memory.

[0542] Data processing: Converts data into packets and prepares it for transmission. The device first checks whether a Wi-Fi connection is available, and if so, uses Wi-Fi to transmit the data. If Wi-Fi is not available, it uses the mobile network (LTE or 5G) to transmit the data.

[0543] Output: Location information and damage situation data sent to the server.

[0544] Step 4:

[0545] Data reception and analysis

[0546] The server receives and analyzes the data sent from the terminal.

[0547] Input: Received location information and damage situation data.

[0548] Data processing: Using a GIS (geographic information system), the received data is visualized on a map to analyze the extent and scale of the damage. For example, the GIS system generates a heat map of the affected area, visually showing the impact of a specific region.

[0549] Output: Analysis results of the extent and scale of damage.

[0550] Step 5:

[0551] Solution Selection

[0552] The server selects the optimal recovery solution based on the analysis results.

[0553] Input: Analysis results of the extent and scale of the damage.

[0554] Data processing: Based on the analysis results, an algorithm is run to automatically select the optimal recovery method (e.g., deploying a drone base station if communications infrastructure is damaged).

[0555] Output: The selected recovery solution.

[0556] Step 6:

[0557] Sending notifications

[0558] The server notifies disaster response personnel in real time of the analysis results and the selected recovery solution.

[0559] Input: Selected restoration solution and analysis results.

[0560] Data processing: Generates notification content and prepares it for transmission to communication devices (smartphones, tablets, etc.).

[0561] Output: A notification sent to disaster response personnel, including specific instructions such as "Large-scale building collapse confirmed in Shinjuku Ward. Deploy drone base stations to restore communications."

[0562] In this way, each step works in coordination to quickly and accurately grasp the extent of the damage and provide appropriate recovery solutions.

[0563] (Application example 1)

[0564] 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."

[0565] Conventional disaster management systems were slow to grasp the extent of damage when a disaster occurred, making it difficult to provide appropriate recovery solutions. Furthermore, the means of collecting damage data were limited, making it impossible to effectively collect and utilize real-time information from the site. As a result, disaster response was inefficient, and recovery was delayed, potentially leading to greater damage.

[0566] 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.

[0567] In this invention, the server includes means for acquiring location information, means for collecting damage status when a disaster occurs, means for transmitting the collected location information and damage status, means for analyzing the transmitted location information and damage status and selecting an optimal recovery solution, means for notifying disaster response personnel of the analysis results and the selected recovery solution, and means for collecting damage data using a smart device, thereby enabling the collection of damage information in real time and the provision of optimal recovery solutions.

[0568] "Location information" is latitude and longitude data that indicates a specific point on Earth.

[0569] "Damage situation" is data that indicates the extent of damage and impact to buildings and infrastructure when a disaster occurs.

[0570] The "server" is a central processing unit that analyzes the collected data and provides optimal recovery solutions.

[0571] A "GPS device" is a device that obtains location information using the Global Positioning System.

[0572] A "sensor" is a device that detects and collects data about the physical environment. Examples include vibration sensors and humidity sensors.

[0573] "Network interface" is a general term for hardware and software for wirelessly transmitting data to other devices or servers.

[0574] "Smart devices" refers to mobile terminals with advanced functions, including smart glasses and smartphones.

[0575] A "geographic information system (GIS)" is a system for analyzing and visualizing geospatial data.

[0576] A "generative AI model" is a model that uses machine learning and deep learning to analyze and predict data.

[0577] A "prompt sentence" is an instruction sentence in natural language format that is input to a generative AI model.

[0578] To implement this invention, a GPS device for acquiring location information, multiple sensors for collecting damage information, a network interface for transmitting data, and a server for analysis and notification are required. In particular, smart glasses and a smartphone are used as smart devices.

[0579] Obtaining location information

[0580] The server periodically obtains the user's location information using a GPS device, which is built into the smart glasses and smartphone, and accurately collects the user's current latitude and longitude information.

[0581] Collecting information on damage

[0582] When a disaster occurs, the server collects data on the damage situation using the vibration and humidity sensors built into smart devices. For example, if a major earthquake occurs, the vibration sensor will detect strong shaking and record that data.

[0583] Sending data

[0584] The collected location information and damage situation data are sent to a server via a network interface. Specifically, smart devices use mobile networks or Wi-Fi to send this data to the server.

[0585] Data reception and analysis

[0586] The server receives the data sent from the devices and uses a geographic information system (GIS) to analyze the extent and scale of the damage, making it possible to clarify the extent of building collapses and the impact of the earthquake in a specific area.

[0587] Selecting a recovery solution

[0588] The server uses a generative AI model to select the optimal recovery solution, using prompts to input to the generative AI model for analysis.

[0589] Sending notifications

[0590] The analysis results and the selected restoration solution are then communicated to disaster response personnel. For example, if communications infrastructure is severely damaged, the server will instruct drone base stations to be deployed to restore communications.

[0591] Specific examples

[0592] If the user is in Shinjuku Ward, Tokyo, the smart glasses' GPS will be used to obtain location information at latitude 35.6938 degrees and longitude 139.7034 degrees. When a major earthquake occurs in Shinjuku Ward, the smart glasses' vibration sensor will detect strong shaking and send the data to a server via Wi-Fi. The server will use a geographic information system to analyze the state of building collapse and, since communication disruptions have been confirmed, will decide to deploy a drone base station. Disaster response personnel will receive a notification stating, "Large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communication."

[0593] Prompt Sentence Examples

[0594] "When a large earthquake occurs, please explain the system in which a server analyzes the damage situation based on data detected by vibration sensors and location information obtained by GPS devices, and selects the optimal recovery solution. In this system, smart glasses have built-in sensors and GPS devices that collect and communicate data. Example: Specific processing procedures when a large earthquake occurs in Shinjuku Ward."

[0595] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0596] Step 1: Obtaining location information

[0597] The server periodically obtains the user's location information using a GPS device. The input is the user's current location, and the output is latitude and longitude data. This data is collected from GPS devices built into smart glasses or smartphones. For example, if a user is in Shinjuku Ward, Tokyo, the server collects location information of latitude 35.6938 degrees and longitude 139.7034 degrees.

[0598] Step 2: Collect damage information

[0599] When a disaster occurs, the server collects data on the damage situation using sensors (vibration sensors and humidity sensors) built into smart devices. The input is sensor data, and the output is damage situation data such as earthquake shaking and humidity changes. For example, when a major earthquake occurs, the vibration sensor in the smart glasses detects strong shaking and records that data.

[0600] Step 3: Sending data

[0601] The server transmits the collected location information and damage status data through a network interface. Location information and damage status data are input, and these data are sent to the server as output. This transmission is done from the smart device using a mobile network or Wi-Fi. For example, location information and vibration data collected in Shinjuku Ward are sent to the server via Wi-Fi.

[0602] Step 4: Receiving and analyzing data

[0603] The server receives the data sent from the terminals and uses a geographic information system (GIS) to analyze the extent and scale of the damage. Location information and damage data are input, and damage analysis results are obtained as output. For example, the server receives location information and vibration data from Shinjuku Ward and analyzes the collapse and impact of buildings in that area.

[0604] Step 5: Select a recovery solution

[0605] The server uses a generative AI model based on the analysis results to select the optimal recovery solution. This analysis is driven by a prompt statement. The inputs are the damage analysis results and the prompt statement, and the output is a specific recovery solution. For example, the server may determine that communication infrastructure is damaged and decide to deploy a drone base station.

[0606] Step 6: Sending notifications

[0607] The server notifies disaster response personnel of the analysis results and the selected recovery solution. The inputs are the recovery solution and notification text, and the output is the notification that is sent to the personnel. For example, disaster response personnel receive information such as, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications."

[0608] 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.

[0609] This invention is a system that, in addition to quickly and accurately grasping the damage situation and providing optimal recovery solutions when a disaster occurs, recognizes the user's emotions and takes these into consideration when responding. This system uses a GPS device and emotion engine embedded in the user to collect location information and emotion data, and transmits the damage situation and emotion data to a server when a disaster occurs. The server analyzes the collected data and works with the emotion engine to provide optimal recovery solutions and communicates with the user in a way that takes their emotions into consideration.

[0610] Program processing (outline)

[0611] 1. Location and emotion data acquisition:

[0612] The device periodically acquires the user's location information using GPS and collects the user's emotion data using an emotion engine.

[0613] For example, if the device is located within Tokyo, it will analyze the user's location information (latitude and longitude) and their voice and facial expressions to collect emotions (such as stress level).

[0614] 2. Collecting damage information:

[0615] When a disaster occurs, the device activates its built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation.

[0616] For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record the data.

[0617] 3. Creating and sending a data package:

[0618] The device compiles the collected location information, damage situation data, and user emotion data into a single data package and sends it to the server.

[0619] Specifically, the device transmits this data to a server via a mobile network or Wi-Fi.

[0620] 4. Data Receipt and Analysis:

[0621] The server receives the data package sent from the device and analyzes the scope and scale of the damage, as well as the user's emotional state.

[0622] For example, the server may use a geographic information system (GIS) to analyze the impact of building collapses or earthquakes in a particular area, while simultaneously using an emotion engine to assess the user's stress level.

[0623] 5. Solution Selection and Emotional Response:

[0624] The server selects the optimal recovery solution based on the analysis results, and also selects the optimal communication method taking into account the user's emotional data.

[0625] For example, if communications infrastructure is severely damaged, drone base stations can be used to ensure communications, while psychological care information can be provided to users experiencing high levels of stress.

[0626] 6. Create and send notifications:

[0627] The server creates a notification containing the analysis results and the selected recovery solution, and sends it to disaster response personnel and relevant users. The notification to users is sensitive to their emotions.

[0628] For example, disaster response personnel could be notified that "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications," while users could be sent reassuring messages such as "The current situation is serious, but please rest assured, recovery work is underway."

[0629] Specific examples

[0630] 1. Obtaining location and emotion data

[0631] Device: If the user is in Shinjuku Ward, Tokyo, location information of latitude 35.6938 degrees and longitude 139.7034 degrees is obtained using GPS, and at the same time, the stress level is evaluated from the user's voice and facial expression.

[0632] 2. Collecting information on damage

[0633] Terminal: When a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect strong shaking and record the data.

[0634] 3. Creating and sending a data package

[0635] Terminal: Sends location information, damage situation data, and emotion data together to the server.

[0636] 4. Data Receipt and Analysis

[0637] Server: Receives location information, vibration data, and emotion data from Shinjuku Ward and analyzes the data using a geographic information system and emotion engine.

[0638] 5. Solution selection and emotional response

[0639] Server: After building collapses and communication disruptions were confirmed, drone base stations were deployed and psychological care information was provided to users with high stress levels.

[0640] 6. Creating and sending notifications

[0641] Server: Sends detailed notifications along with the analysis results to disaster response personnel, and notifies users with reassurance.

[0642] In this way, the system of the present invention not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also takes user emotions into consideration when responding to disasters, enabling more effective disaster response.

[0643] The processing flow will be explained below.

[0644] Step 1:

[0645] The device periodically obtains the user's location information. Specifically, the device's built-in GPS module receives signals from the Global Positioning System (GPS) and calculates the latitude and longitude coordinates.

[0646] Step 2:

[0647] The device temporarily stores the acquired location information in memory, thereby retaining the user's current location as data.

[0648] Step 3:

[0649] The device uses an emotion engine to acquire the user's emotion data. Specifically, it collects and analyzes the user's voice data and facial expression data to determine their emotional state (e.g., stress level, sense of relief, anxiety).

[0650] Step 4:

[0651] When a disaster occurs, the device activates its built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation. For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record that data.

[0652] Step 5:

[0653] The device compiles the collected location information, emotional data, and damage situation data into a single data package, which includes the user's latitude and longitude, emotional state, and damage information collected from sensors.

[0654] Step 6:

[0655] The device then sends the created data package to the server via a mobile network or Wi-Fi. Specifically, the device establishes communication with the server at regular intervals and transmits the data via the Internet.

[0656] Step 7:

[0657] The server receives the data package sent from the terminal, and according to the receiving protocol, the data is stored in the server's storage.

[0658] Step 8:

[0659] The server analyzes the received data. During the analysis process, it uses a geographic information system (GIS) to identify the extent and scale of the damage and map the latitude and longitude information. At the same time, it uses an emotion engine to evaluate the user's emotional state.

[0660] Step 9:

[0661] The server then selects the optimal recovery solution based on the analysis results. For example, if widespread building collapse is confirmed, it will use drone base stations to ensure communications. On the other hand, if the user's stress level is high, it will include the option to provide psychological care information.

[0662] Step 10:

[0663] The server then creates a notification containing the selected recovery solution, detailing the damage situation and specific steps to implement the solution, and creating communication content that takes into account the user's emotional state.

[0664] Step 11:

[0665] The server then sends the created notifications to disaster response personnel and relevant users. The notifications are sent in real time via email or a dedicated application. The notifications to users are sent with emotional sensitivity.

[0666] Step 12:

[0667] The user (disaster response personnel) receives the notification. After checking the notification, the personnel in charge decide on a prompt response based on the provided information. For example, they issue instructions to the local operator to deploy a drone base station.

[0668] Step 13:

[0669] The user (disaster response officer) then instructs the local response team on the decided response measures, which allows for a quick and effective assessment of the damage situation and progress in recovery work.

[0670] Step 14:

[0671] The user (general user) checks the notification from the server. The notification is sensitive to the user's feelings and includes information on psychological care, giving the user a sense of security.

[0672] In this way, the system of the present invention not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also takes user emotions into consideration when responding to disasters, enabling more effective disaster response.

[0673] Example 2

[0674] 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."

[0675] Conventional disaster response systems are slow to grasp the extent of the damage, making it difficult to provide effective recovery solutions quickly. Furthermore, they do not take into account the emotional state of users, resulting in a lack of psychological support. Therefore, there is a need for systems that can accurately grasp the disaster situation and respond quickly while taking into account users' emotions.

[0676] 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.

[0677] In this invention, the server includes means for acquiring location information and emotion data, means for collecting damage status when a disaster occurs, and means for transmitting the collected location information, emotion data, and damage status, thereby enabling a quick and accurate understanding of the damage status and providing optimal recovery solutions that take into consideration the user's emotions.

[0678] "Location information" refers to data indicating the geographic coordinates of a user's current location, such as latitude and longitude.

[0679] "Emotion data" is data that indicates the user's emotional state, and includes stress levels and types of emotions obtained by analyzing voice and facial expressions.

[0680] "Means of collection" refers to the technologies and devices used to collect data, including sensors and analytics engines.

[0681] "Transmission means" refers to the methods or technologies used to send collected data to other devices or servers, including mobile networks and Wi-Fi.

[0682] "Means for analysis" refers to the technology or equipment used to process received data and understand its content, including geographic information systems (GIS) and sentiment analysis engines.

[0683] "Recovery solutions" refer to specific measures and methods for minimizing damage after a disaster and quickly restoring social functions.

[0684] "Means of notification" refers to the technology or devices used to communicate analysis results and recovery solutions to relevant personnel and users, including text messaging and notification applications.

[0685] overview

[0686] This invention is a system for quickly and accurately assessing the damage situation and providing optimal recovery solutions when a disaster occurs. It also recognizes the user's emotions and responds accordingly. In this system, the device collects the user's location information and emotional data, and sends them to a server along with damage situation data when a disaster occurs. The server analyzes this data, selects the optimal recovery solution and emotional response measures, and notifies the user.

[0687] Specific Embodiments

[0688] 1. Using the Device

[0689] The device uses a built-in GPS module to periodically obtain the user's location information, while at the same time utilizing an emotion engine to analyze and collect the user's emotions from voice and facial expression data. This emotion engine uses voice recognition software and image analysis algorithms.

[0690] Example: Obtain the location information (latitude 35.6938 degrees, longitude 139.7034 degrees) of a user in Shinjuku Ward, Tokyo, and use the emotion engine to analyze the user's voice and facial expressions to assess their stress level.

[0691] 2. Collecting information on damage

[0692] The device activates vibration and humidity sensors in the event of a disaster to collect data on the damage situation. For example, in the event of a major earthquake, the vibration sensor detects strong shaking and records that data. The humidity sensor also measures humidity levels in the event of flooding.

[0693] Example: If a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect high vibrations (e.g., seismic intensity of 6+) and the humidity sensor will measure high humidity (e.g., humidity of 90% or higher).

[0694] 3. Creating and sending a data package

[0695] The device then compiles the collected location information, emotion data, and damage situation data into a single data package, which also includes timestamps for each type of data.

[0696] The device then sends this data package over the mobile network or Wi-Fi to a server, which also encrypts the data before sending it.

[0697] 4. Data analysis on the server

[0698] The server receives the data package sent from the device, unpacks it, and analyzes the various data. Specifically, it uses a geographic information system (GIS) to analyze location information and evaluate the extent and scale of damage in a specific area. It also uses an emotion analysis engine to evaluate emotional data and quantify stress levels.

[0699] Example: Analyzing location information, vibration data, and emotion data in Shinjuku Ward to identify the extent of building collapse and assess the user's stress level.

[0700] 5. Selecting the best recovery solution and emotional response

[0701] The server selects the optimal recovery solution based on the results of the GIS and emotion analysis engine. For example, if there is significant damage to the communications infrastructure, it will deploy a drone base station to ensure communications. It also provides psychological care information based on the user's emotional state.

[0702] Example: If a communication failure is confirmed, a drone base station will be deployed in Shinjuku Ward to restore communication, and psychological care information will be provided to users experiencing high levels of stress.

[0703] 6. Creating and sending notifications

[0704] Based on the analysis and the selected recovery solution, the server generates messages to notify disaster response personnel and users. These notifications include appropriate timestamps and details of specific actions to be taken.

[0705] Example: Disaster response personnel could be notified, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy drone base stations to restore communications," while users could be notified, "The current situation is serious, but please rest assured, recovery work is underway."

[0706] Prompt Sentence Examples

[0707] "Please execute the emergency response protocol in the event of a major earthquake in Shinjuku Ward, Tokyo. Obtain the user's location information and emotion data and send it to the server along with damage status data."

[0708] In this way, the present invention enables effective disaster response by quickly and accurately grasping the damage situation when a disaster occurs and providing optimal recovery solutions that take into consideration the feelings of users.

[0709] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0710] Program processing flow

[0711] Step 1: Obtaining location and emotion data

[0712] The device obtains the user's location information using the built-in GPS module. The input for this operation is the signal from the GPS satellites, and the output is the user's current location (latitude and longitude).

[0713] Specific operation: For a user in Shinjuku Ward, Tokyo, the device obtains location information of latitude 35.6938 degrees and longitude 139.7034 degrees.

[0714] The device activates an emotion engine to analyze the user's voice and facial expressions in real time. The input for this operation is the user's voice and facial image, and the output is the user's emotional data (such as stress level).

[0715] Specific behavior: Analyzes the user's voice and facial expressions to recognize high stress levels.

[0716] Step 2: Collect damage information

[0717] When a disaster occurs, the terminal activates various sensors, such as vibration sensors and humidity sensors. The input for this operation is physical vibrations and changes in humidity, and the output is damage situation data.

[0718] Specific operation: When a major earthquake occurs, the vibration sensor detects and records shaking of a seismic intensity of 6+. The humidity sensor also measures humidity levels of 90% or higher.

[0719] Step 3: Creating and sending a data package

[0720] The terminal processes the collected location information, damage situation data, and emotion data into a single data package. The inputs for this operation are location information, emotion data, and damage situation data, and the output is a data package.

[0721] Specific operation: The device combines location information, emotional data indicating high stress levels, and vibration sensor data into a single package.

[0722] The device sends data packages to the server via a mobile network or Wi-Fi. The input is the data package, and the output is a notification of successful transmission.

[0723] What it does: Encrypts the data package and sends it to a server over the mobile network.

[0724] Step 4: Receiving and analyzing data

[0725] The server receives the data package sent from the terminal. The input of this operation is the data package, and the output is the data to be analyzed.

[0726] Specific operation: The received data package is unzipped and each piece of data is extracted for analysis.

[0727] The server analyzes the location information using a geographic information system (GIS) and simultaneously evaluates the emotional data using an emotion engine. The inputs of this operation are location information and emotional data, and the output is the identification of the damage extent and the evaluation of the stress level.

[0728] Specific operation: Identifies the extent of building collapse based on location information in Shinjuku Ward and evaluates the user's stress level.

[0729] Step 5: Selecting a solution and responding emotionally

[0730] The server selects the optimal recovery solution based on the analysis results. The input of this operation is the analysis results, and the output is the recovery solution.

[0731] Specific operation: If a building collapse and communication failure are confirmed, a solution will be selected to restore communication by placing a drone base station.

[0732] The server selects a communication method according to the user's emotional state. The input of this operation is the emotional evaluation result, and the output is an emotional response plan.

[0733] Specific operation: Provide psychological care information to users with high stress levels.

[0734] Step 6: Create and send notifications

[0735] The server generates a notification based on the analysis results and the selected recovery solution. The inputs to this operation are the analysis results and the solution, and the output is the notification.

[0736] Specific operation: The system notifies the person in charge, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications," and generates a message for the user saying, "The current situation is serious, but please rest assured, recovery work is underway."

[0737] The server then sends the created notification to the disaster response staff and the user. The input for this operation is the notification, and the output is a notification of successful transmission.

[0738] Specific operation: Sends notification text using messaging applications or SMS.

[0739] Through these steps, the system is able to quickly and accurately grasp the extent of the damage and provide optimal recovery solutions that take the user's feelings into consideration.

[0740] (Application example 2)

[0741] 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."

[0742] In disasters and emergencies, it is important to quickly and accurately grasp the damage situation and respond effectively to recovery. However, conventional systems do not take the user's emotional state into consideration when communicating. Furthermore, there is a lack of means to analyze the user's emotional data in real time and provide appropriate responses based on that analysis. Therefore, there is a need for the development of a system that provides quick and effective response measures while reducing the psychological burden on users in emergencies.

[0743] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0744] In this invention, the server includes means for acquiring location information and emotion data, means for generating and transmitting a data package of the damage situation and emotion data, means for analyzing the transmitted data package and selecting an optimal recovery solution, and means for generating and transmitting notification content taking the user's emotion data into consideration, thereby enabling a quick and accurate understanding of the damage situation and effective recovery measures that take the user's emotional state into consideration.

[0745] "Means for acquiring location information" refers to a device or software that receives signals from satellites or ground landmarks to acquire latitude and longitude data in order to identify the user's current location.

[0746] "Means for collecting damage information when a disaster occurs" refers to equipment or software that uses multiple sensors and devices to collect damage information such as building damage and earthquake intensity when a disaster occurs.

[0747] The "means for generating and transmitting a data package" refers to a device or software that assembles the collected location information, damage situation data, and emotion data into a single information packet and transmits it to a server.

[0748] The "means for selecting the optimal recovery solution" is a device or software that analyzes the transmitted data and determines the optimal recovery method or measures based on the extent of the damage and the user's emotional state.

[0749] The "means for recognizing and analyzing user emotional data" refers to a device or software for analyzing the user's voice and facial expressions and determining their emotional state.

[0750] The "means for generating and transmitting notification content" refers to a device or software that generates a notification with appropriate content based on the damage situation and the user's emotions, and transmits it to the user and disaster response personnel.

[0751] The Global Positioning System (GPS) is a system that uses satellites to calculate specific geographic locations and obtain user location information.

[0752] "Multiple built-in sensors" refers to a group of sensors built into a device that collect various environmental information such as vibration, humidity, and temperature.

[0753] A "geographic information system (GIS)" is software for managing, analyzing, and visually displaying geographic data.

[0754] This invention is a system that not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also recognizes the user's emotional state and takes this into consideration when responding. This system is mainly composed of terminals and a server, and each terminal collects location information and emotional data, which the server analyzes and provides appropriate responses.

[0755] System Configuration

[0756] Terminal

[0757] Hardware

[0758] Mobile communication devices such as smartphones

[0759] Built-in GPS module

[0760] Multiple built-in sensors (vibration sensor, humidity sensor, temperature sensor, etc.)

[0761] Camera and microphone

[0762] software

[0763] Location information acquisition module

[0764] Emotion analysis module (performs voice analysis and facial expression analysis)

[0765] Data package generation and transmission module

[0766] server

[0767] Hardware

[0768] High-performance computers

[0769] software

[0770] Data Receiving Module

[0771] Data analysis module (including a geographic information system (GIS) and sentiment analysis engine)

[0772] Restoration Solution Selection Module

[0773] Notification Generation and Sending Module

[0774] Processing steps

[0775] Location and emotion data acquisition

[0776] The device periodically obtains the user's location information using a GPS module. It also uses a camera and microphone to analyze the user's voice and facial expressions to collect emotional data. This allows the device to obtain the user's latitude (35.6938 degrees) and longitude (139.7034 degrees) if the user is in Tokyo, and simultaneously analyze the user's stress level.

[0777] Collecting information on damage

[0778] When a disaster occurs, the device uses its built-in sensors to collect information on the damage situation. For example, if a major earthquake occurs, the vibration sensor will detect strong shaking and record that data.

[0779] Creating and sending data packages

[0780] The device compiles location information, damage situation data, and emotion data into a single data package and sends it to a server via a mobile network or Wi-Fi.

[0781] Data reception and analysis

[0782] The server receives the data packages sent from the devices and analyzes the extent and scale of the damage, as well as the user's emotional state. It uses a geographic information system (GIS) to analyze the impact of building collapses and earthquakes in a specific area, while simultaneously using an emotion engine to assess the user's stress level.

[0783] Solution selection and emotional response

[0784] The server selects the optimal recovery solution based on the analysis results. It also considers the user's emotional data to select the optimal communication method. For example, if the communications infrastructure is severely damaged, it will use drone base stations to ensure communications. Meanwhile, it will provide psychological care information to users experiencing high levels of stress.

[0785] Creating and sending notifications

[0786] The server creates a notification containing the analysis results and the selected recovery solution, and sends it to disaster response personnel and the appropriate users. The notification to users is sensitive to their emotions. For example, disaster response personnel might be notified that "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy drone base stations to restore communications," while users might be notified with a message that provides reassurance, such as "The current situation is serious, but please rest assured that recovery work is underway."

[0787] Adding specific examples

[0788] Example 1: Obtaining location and emotion data

[0789] Example prompt:

[0790] "Collect audio data to analyze the user's stress level and obtain latitude and longitude location information."

[0791] Example 2: Anomaly detection and response

[0792] Example prompt:

[0793] "If the user is in a state of extreme stress, contact the police and notify the user."

[0794] In this way, the system of the present invention makes it possible to quickly and accurately grasp the extent of damage and to take effective recovery measures while taking into consideration the emotional state of the user.

[0795] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0796] Step 1:

[0797] The device periodically obtains the user's location information using a GPS module. The input data is signals obtained from satellites, and the device calculates the latitude and longitude based on this. The output data is the user's current location information (e.g., latitude 35.6938 degrees, longitude 139.7034 degrees).

[0798] Step 2:

[0799] The device uses a camera and microphone to collect the user's voice and facial expressions. The input data is the user's facial image captured by the camera and the voice data recorded by the microphone. This data is input into an emotion analysis module to analyze the user's stress level and emotional state. The output data is the user's emotional data (e.g., high stress level).

[0800] Step 3:

[0801] The device constantly monitors the surrounding situation using built-in sensors (e.g., vibration sensor, humidity sensor). When a disaster occurs, these sensors collect data on the damage situation. The input data is shaking intensity data from the vibration sensor and humidity data from the humidity sensor. The output data is damage situation data (e.g., strong shaking, humidity changes).

[0802] Step 4:

[0803] The device compiles the obtained location information, emotion data, and damage situation data into a single data package. The input data is the information obtained at each step (location information, emotion data, damage situation data). The output data is the compiled data package.

[0804] Step 5:

[0805] The terminal transmits the generated data package to the server using a mobile network or Wi-Fi. The input data is the data package, and the output data is the data package received by the server.

[0806] Step 6:

[0807] The server analyzes the received data package. The input data is the data package sent from the device, and it analyzes it using a geographic information system (GIS) and an emotion analysis engine. The output data is the range and scale of the damage, as well as evaluation information on the user's emotional state.

[0808] Step 7:

[0809] The server selects the optimal recovery solution based on the analysis results. The input data are the analysis results, and based on these, the optimal recovery method (e.g., the placement of drone base stations or the provision of psychological care information) is determined. The output data is the selected recovery solution.

[0810] Step 8:

[0811] The server creates a notification containing the selected recovery solution and the analysis results, and sends it to disaster response personnel and appropriate users. The input data are the recovery solution and the analysis results, and the output data is the configured notification content.

[0812] Step 9:

[0813] The user can receive notifications from the server and feel secure. The input data is the notification sent from the server, and the output data is the user's sense of security.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] [Third embodiment]

[0818] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0819] 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.

[0820] 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).

[0821] 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.

[0822] 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.

[0823] 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).

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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."

[0830] This invention is a system that aims to quickly and accurately grasp the damage situation when a disaster occurs and provide optimal recovery solutions. This system uses a GPS device embedded in the user to collect location information, and when a disaster occurs, it collects damage information through sensors. Based on the collected data, a server selects the optimal recovery solution and notifies disaster response personnel.

[0831] Program processing (outline)

[0832] 1. Location information acquisition:

[0833] The terminal periodically acquires the user's location information using GPS.

[0834] For example, the device identifies the user's location within Tokyo and collects the user's latitude and longitude information.

[0835] 2. Collecting damage information:

[0836] When a disaster occurs, the device uses built-in sensors (such as vibration sensors and humidity sensors) to collect data on the damage situation.

[0837] For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record the data.

[0838] 3. Data transmission:

[0839] The terminal transmits the collected location information and damage situation data to the server.

[0840] Specifically, the device transmits this data to a server via a mobile network or Wi-Fi.

[0841] 4. Data Receipt and Analysis:

[0842] The server receives the data sent from the device and analyzes the scope and scale of the damage.

[0843] For example, the server uses a geographic information system (GIS) to analyze the impact of building collapses or earthquakes in a particular area.

[0844] 5. Solution Selection:

[0845] The server selects the optimal recovery solution based on the analysis results.

[0846] For example, if communications infrastructure is severely damaged, drone base stations will be deployed to ensure communications.

[0847] 6. Sending notifications:

[0848] The server notifies disaster response personnel of the analysis results and the selected recovery solution.

[0849] For example, information such as "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications" will be sent to disaster response personnel.

[0850] Specific examples

[0851] 1. Obtaining location information

[0852] Terminal: If the user is in Shinjuku-ku, Tokyo, location information of latitude 35.6938 degrees and longitude 139.7034 degrees is obtained using GPS.

[0853] 2. Collecting information on damage

[0854] Terminal: When a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect strong shaking and record the data.

[0855] 3. Data transmission

[0856] Terminal: The collected location information and damage situation data is sent to the server via Wi-Fi.

[0857] 4. Data Receipt and Analysis

[0858] Server: Receives location information and vibration data from Shinjuku Ward and analyzes the state of building collapse using a geographic information system.

[0859] 5. Solution Selection

[0860] Server: After confirming that communication has been disrupted due to the collapse of a building, it is decided to deploy a drone base station.

[0861] 6. Sending Notifications

[0862] Server: Notifies disaster response personnel of the analysis results along with instructions for drone base station placement.

[0863] In this way, the present invention makes it possible to quickly and accurately grasp the extent of damage when a disaster occurs and to provide optimal recovery solutions, thereby significantly improving the efficiency of disaster response.

[0864] The processing flow will be explained below.

[0865] Step 1:

[0866] The device periodically obtains the user's location information: the device's built-in GPS module receives signals from the Global Positioning System (GPS) and calculates the latitude and longitude coordinates.

[0867] Step 2:

[0868] The device temporarily stores the acquired location information in memory, thereby retaining the user's current location as data.

[0869] Step 3:

[0870] When a disaster occurs, the device activates various built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation. For example, if the vibration sensor detects earthquake tremors, it will record the strength and duration of the tremors.

[0871] Step 4:

[0872] The device compiles the collected location information and damage situation data into a single data package, which includes the user's latitude and longitude and damage information collected from sensors.

[0873] Step 5:

[0874] The device then sends the created data package to the server via a mobile network or Wi-Fi. Specifically, the device establishes communication with the server at regular intervals and transmits the data via the Internet.

[0875] Step 6:

[0876] The server receives the data package sent from the terminal, and according to the receiving protocol, the data is stored in the server's storage.

[0877] Step 7:

[0878] The server analyzes the received data. During the analysis process, a geographic information system (GIS) is used to identify the extent and scale of the damage and map the latitude and longitude information.

[0879] Step 8:

[0880] The server selects the optimal recovery solution based on the analysis results. For example, if widespread building collapse is confirmed, one option would be to use drone base stations to ensure communications.

[0881] Step 9:

[0882] The server creates a notification containing the selected recovery solution, along with details of the damage and instructions on how to implement the solution.

[0883] Step 10:

[0884] The server then sends the created notifications to disaster response personnel in real time via email or a dedicated application.

[0885] Step 11:

[0886] The user (disaster response officer) receives the notification and decides on a prompt response based on the information provided.

[0887] Step 12:

[0888] The user (disaster response officer) instructs the local response team on the decided response measures, for example, by issuing instructions to the local operator to deploy drone base stations, aiming to quickly restore the damage situation.

[0889] Through the above processing steps, the system of the present invention responds to disasters quickly and accurately, contributing to minimizing damage and improving the efficiency of recovery.

[0890] Example 1

[0891] 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."

[0892] When a disaster occurs, it is important to quickly and accurately grasp the damage situation, but current methods often result in delays in collecting and analyzing damage information. As a result, there is a problem of delays in selecting and implementing appropriate recovery solutions. Furthermore, there is an issue of the inability to respond to disasters quickly due to limited means of quickly communicating damage information.

[0893] 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.

[0894] In this invention, the server includes means for periodically acquiring user location information, means for collecting damage status using a built-in sensor when a disaster occurs, means for transmitting the collected location information and damage status data via a network, means for receiving the transmitted location information and damage status data and analyzing the range and scale of the damage using a geographic information system (GIS), means for automatically selecting an optimal recovery solution based on the analysis results, and means for notifying disaster response personnel of the selected recovery solution and the analysis results in real time, thereby enabling a quick and accurate understanding of the damage status and the provision of an optimal recovery solution.

[0895] The "means for periodically obtaining location information" is a device, system, or method for measuring and recording the latitude and longitude of the user's current location at regular intervals.

[0896] "Means for collecting damage information using built-in sensors when a disaster occurs" refers to a device, system, or method that uses various sensors built into a terminal, such as vibration sensors and humidity sensors, to obtain information on damage when a disaster occurs.

[0897] "Means for transmitting collected location information and damage situation data via a network" refers to a device, system, or method for transmitting collected data to a server using communication infrastructure such as Wi-Fi or a mobile network (LTE, 5G, etc.).

[0898] "Means for receiving the transmitted location information and damage situation data and analyzing the extent and scale of the damage using a geographic information system (GIS)" refers to a device, system, or method in which a server receives data sent from a terminal, analyzes it, and uses a geographic information system (GIS) to measure the extent and severity of the damage.

[0899] A "means for automatically selecting an optimal recovery solution based on analysis results" is a device, system, or method that uses an algorithm or program to automatically select the most effective recovery measures based on the results of data analysis.

[0900] "Means for notifying disaster response personnel of selected recovery solutions and analysis results in real time" means a device, system, or method that uses a communication device (e.g., smartphone, tablet, etc.) to quickly communicate selected recovery solutions and analysis results to disaster response personnel.

[0901] This invention is a system that aims to quickly and accurately grasp the damage situation when a disaster occurs and provide optimal recovery solutions. This system uses GPS devices and various sensors (vibration sensors, humidity sensors, etc.) embedded in the user's device to collect location information and disaster damage information, and sends the collected information to a server. The server analyzes this information, automatically selects the optimal recovery solution, and notifies disaster response personnel in real time.

[0902] Hardware and Software Details

[0903] The device uses the following hardware and software:

[0904] GPS module: A device for obtaining user location information. It outputs latitude and longitude information.

[0905] Vibration and humidity sensors: Devices for detecting vibrations and changes in humidity during disasters. Each sensor converts analog signals into digital data and stores it in its internal memory.

[0906] Communication module: A device that supports Wi-Fi and mobile networks (LTE, 5G, etc.) and transmits collected data to a server.

[0907] The server uses the following software:

[0908] Data receiving module: Receives location information and damage situation data sent from the terminal.

[0909] GIS (Geographic Information System): Software that analyzes received location information and damage situation data to visualize the scope and scale of damage.

[0910] Analysis and restoration solution selection algorithm: An algorithm that analyzes damage data and selects the optimal restoration solution (e.g., drone base station placement).

[0911] Notification module: Notifies disaster response personnel in real time of analysis results and selected recovery solutions.

[0912] Specific examples

[0913] For example, if a user is in Shinjuku Ward, Tokyo, the device will periodically obtain location information (latitude 35.6938 degrees, longitude 139.7034 degrees) using GPS. If a major earthquake occurs in Shinjuku Ward and the vibration sensor detects strong shaking, the device will record the data in its internal memory. The device will then use Wi-Fi if available, or send the location information and damage data to the server via the mobile network if not.

[0914] The server receives this data and uses GIS to analyze the impact of building collapses and earthquakes in a specific area. Based on the analysis results, the server selects the optimal recovery solution, for example, if communication infrastructure is damaged, it decides to deploy drone base stations. After making a decision, the server sends notifications to disaster response personnel in real time and instructs them on actual response measures.

[0915] Prompt Sentence Examples

[0916] An example of a prompt to be input to the generative AI model is as follows:

[0917] Location information acquisition: "If the user is in Shinjuku Ward, Tokyo, please use GPS to acquire latitude and longitude information."

[0918] Collecting damage information: "When a major earthquake occurs in Shinjuku Ward, please use the vibration sensor to record the strength of the shaking."

[0919] Data transmission: "Please send the collected location information and damage situation data to the server via Wi-Fi."

[0920] Receiving and analyzing data: "The server will receive location information and vibration data from Shinjuku Ward, and will use GIS to analyze the state of building collapse."

[0921] Solution Selection: "The server should determine the optimal recovery solution based on the analysis results, and decide to deploy a drone base station."

[0922] Send notification: "The server will notify disaster response personnel of the analysis results and provide instructions for drone base station placement."

[0923] In this way, the present invention realizes a system that enables rapid and accurate understanding of the damage situation and the provision of appropriate recovery solutions.

[0924] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0925] Step 1:

[0926] Obtaining location information

[0927] The terminal acquires the user's location information at regular intervals using the GPS module.

[0928] Input: The device's built-in GPS module provides current latitude and longitude data.

[0929] Data processing: The acquired latitude and longitude data is recorded in the internal memory. For example, if the user is in Shinjuku Ward, Tokyo, the GPS module will generate information on latitude 35.6938 degrees and longitude 139.7034 degrees.

[0930] Output: Recorded location data.

[0931] Step 2:

[0932] Collecting information on damage

[0933] When the device detects signs of a disaster (such as an earthquake), it activates its built-in sensors (vibration sensor and humidity sensor).

[0934] Input: Earthquake tremors detected by a vibration sensor and humidity changes detected by a humidity sensor.

[0935] Data processing: The data acquired by the sensor is converted into a digital signal and stored in the internal memory. For example, if a major earthquake occurs in Shinjuku Ward and the vibration sensor detects strong shaking of magnitude 7, that data will be recorded.

[0936] Output: Recorded damage status data.

[0937] Step 3:

[0938] Sending data

[0939] The terminal transmits the acquired location information and damage situation data to a server via the network.

[0940] Input: Location information and damage situation data recorded in memory.

[0941] Data processing: Converts data into packets and prepares it for transmission. The device first checks whether a Wi-Fi connection is available, and if so, uses Wi-Fi to transmit the data. If Wi-Fi is not available, it uses the mobile network (LTE or 5G) to transmit the data.

[0942] Output: Location information and damage situation data sent to the server.

[0943] Step 4:

[0944] Data reception and analysis

[0945] The server receives and analyzes the data sent from the terminal.

[0946] Input: Received location information and damage situation data.

[0947] Data processing: Using a GIS (geographic information system), the received data is visualized on a map to analyze the extent and scale of the damage. For example, the GIS system generates a heat map of the affected area, visually showing the impact of a specific region.

[0948] Output: Analysis results of the extent and scale of damage.

[0949] Step 5:

[0950] Solution Selection

[0951] The server selects the optimal recovery solution based on the analysis results.

[0952] Input: Analysis results of the extent and scale of the damage.

[0953] Data processing: Based on the analysis results, an algorithm is run to automatically select the optimal recovery method (e.g., deploying a drone base station if communications infrastructure is damaged).

[0954] Output: The selected recovery solution.

[0955] Step 6:

[0956] Sending notifications

[0957] The server notifies disaster response personnel in real time of the analysis results and the selected recovery solution.

[0958] Input: Selected restoration solution and analysis results.

[0959] Data processing: Generates notification content and prepares it for transmission to communication devices (smartphones, tablets, etc.).

[0960] Output: A notification sent to disaster response personnel, including specific instructions such as "Large-scale building collapse confirmed in Shinjuku Ward. Deploy drone base stations to restore communications."

[0961] In this way, each step works in coordination to quickly and accurately grasp the extent of the damage and provide appropriate recovery solutions.

[0962] (Application example 1)

[0963] 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."

[0964] Conventional disaster management systems were slow to grasp the extent of damage when a disaster occurred, making it difficult to provide appropriate recovery solutions. Furthermore, the means of collecting damage data were limited, making it impossible to effectively collect and utilize real-time information from the site. As a result, disaster response was inefficient, and recovery was delayed, potentially leading to greater damage.

[0965] 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.

[0966] In this invention, the server includes means for acquiring location information, means for collecting damage status when a disaster occurs, means for transmitting the collected location information and damage status, means for analyzing the transmitted location information and damage status and selecting an optimal recovery solution, means for notifying disaster response personnel of the analysis results and the selected recovery solution, and means for collecting damage data using a smart device, thereby enabling the collection of damage information in real time and the provision of optimal recovery solutions.

[0967] "Location information" is latitude and longitude data that indicates a specific point on Earth.

[0968] "Damage situation" is data that indicates the extent of damage and impact to buildings and infrastructure when a disaster occurs.

[0969] The "server" is a central processing unit that analyzes the collected data and provides optimal recovery solutions.

[0970] A "GPS device" is a device that obtains location information using the Global Positioning System.

[0971] A "sensor" is a device that detects and collects data about the physical environment. Examples include vibration sensors and humidity sensors.

[0972] "Network interface" is a general term for hardware and software for wirelessly transmitting data to other devices or servers.

[0973] "Smart devices" refers to mobile terminals with advanced functions, including smart glasses and smartphones.

[0974] A "geographic information system (GIS)" is a system for analyzing and visualizing geospatial data.

[0975] A "generative AI model" is a model that uses machine learning and deep learning to analyze and predict data.

[0976] A "prompt sentence" is an instruction sentence in natural language format that is input to a generative AI model.

[0977] To implement this invention, a GPS device for acquiring location information, multiple sensors for collecting damage information, a network interface for transmitting data, and a server for analysis and notification are required. In particular, smart glasses and a smartphone are used as smart devices.

[0978] Obtaining location information

[0979] The server periodically obtains the user's location information using a GPS device, which is built into the smart glasses and smartphone, and accurately collects the user's current latitude and longitude information.

[0980] Collecting information on damage

[0981] When a disaster occurs, the server collects data on the damage situation using the vibration and humidity sensors built into smart devices. For example, if a major earthquake occurs, the vibration sensor will detect strong shaking and record that data.

[0982] Sending data

[0983] The collected location information and damage situation data are sent to a server via a network interface. Specifically, smart devices use mobile networks or Wi-Fi to send this data to the server.

[0984] Data reception and analysis

[0985] The server receives the data sent from the devices and uses a geographic information system (GIS) to analyze the extent and scale of the damage, making it possible to clarify the extent of building collapses and the impact of the earthquake in a specific area.

[0986] Selecting a recovery solution

[0987] The server uses a generative AI model to select the optimal recovery solution, using prompts to input to the generative AI model for analysis.

[0988] Sending notifications

[0989] The analysis results and the selected restoration solution are then communicated to disaster response personnel. For example, if communications infrastructure is severely damaged, the server will instruct drone base stations to be deployed to restore communications.

[0990] Specific examples

[0991] If the user is in Shinjuku Ward, Tokyo, the smart glasses' GPS will be used to obtain location information at latitude 35.6938 degrees and longitude 139.7034 degrees. When a major earthquake occurs in Shinjuku Ward, the smart glasses' vibration sensor will detect strong shaking and send the data to a server via Wi-Fi. The server will use a geographic information system to analyze the state of building collapse and, since communication disruptions have been confirmed, will decide to deploy a drone base station. Disaster response personnel will receive a notification stating, "Large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communication."

[0992] Prompt Sentence Examples

[0993] "When a large earthquake occurs, please explain the system in which a server analyzes the damage situation based on data detected by vibration sensors and location information obtained by GPS devices, and selects the optimal recovery solution. In this system, smart glasses have built-in sensors and GPS devices that collect and communicate data. Example: Specific processing procedures when a large earthquake occurs in Shinjuku Ward."

[0994] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0995] Step 1: Obtaining location information

[0996] The server periodically obtains the user's location information using a GPS device. The input is the user's current location, and the output is latitude and longitude data. This data is collected from GPS devices built into smart glasses or smartphones. For example, if a user is in Shinjuku Ward, Tokyo, the server collects location information of latitude 35.6938 degrees and longitude 139.7034 degrees.

[0997] Step 2: Collect damage information

[0998] When a disaster occurs, the server collects data on the damage situation using sensors (vibration sensors and humidity sensors) built into smart devices. The input is sensor data, and the output is damage situation data such as earthquake shaking and humidity changes. For example, when a major earthquake occurs, the vibration sensor in the smart glasses detects strong shaking and records that data.

[0999] Step 3: Sending data

[1000] The server transmits the collected location information and damage status data through a network interface. Location information and damage status data are input, and these data are sent to the server as output. This transmission is done from the smart device using a mobile network or Wi-Fi. For example, location information and vibration data collected in Shinjuku Ward are sent to the server via Wi-Fi.

[1001] Step 4: Receiving and analyzing data

[1002] The server receives the data sent from the terminals and uses a geographic information system (GIS) to analyze the extent and scale of the damage. Location information and damage data are input, and damage analysis results are obtained as output. For example, the server receives location information and vibration data from Shinjuku Ward and analyzes the collapse and impact of buildings in that area.

[1003] Step 5: Select a recovery solution

[1004] The server uses a generative AI model based on the analysis results to select the optimal recovery solution. This analysis is driven by a prompt statement. The inputs are the damage analysis results and the prompt statement, and the output is a specific recovery solution. For example, the server may determine that communication infrastructure is damaged and decide to deploy a drone base station.

[1005] Step 6: Sending notifications

[1006] The server notifies disaster response personnel of the analysis results and the selected recovery solution. The inputs are the recovery solution and notification text, and the output is the notification that is sent to the personnel. For example, disaster response personnel receive information such as, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications."

[1007] 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.

[1008] This invention is a system that, in addition to quickly and accurately grasping the damage situation and providing optimal recovery solutions when a disaster occurs, recognizes the user's emotions and takes these into consideration when responding. This system uses a GPS device and emotion engine embedded in the user to collect location information and emotion data, and transmits the damage situation and emotion data to a server when a disaster occurs. The server analyzes the collected data and works with the emotion engine to provide optimal recovery solutions and communicates with the user in a way that takes their emotions into consideration.

[1009] Program processing (outline)

[1010] 1. Location and emotion data acquisition:

[1011] The device periodically acquires the user's location information using GPS and collects the user's emotion data using an emotion engine.

[1012] For example, if the device is located within Tokyo, it will analyze the user's location information (latitude and longitude) and their voice and facial expressions to collect emotions (such as stress level).

[1013] 2. Collecting damage information:

[1014] When a disaster occurs, the device activates its built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation.

[1015] For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record the data.

[1016] 3. Creating and sending a data package:

[1017] The device compiles the collected location information, damage situation data, and user emotion data into a single data package and sends it to the server.

[1018] Specifically, the device transmits this data to a server via a mobile network or Wi-Fi.

[1019] 4. Data Receipt and Analysis:

[1020] The server receives the data package sent from the device and analyzes the scope and scale of the damage, as well as the user's emotional state.

[1021] For example, the server may use a geographic information system (GIS) to analyze the impact of building collapses or earthquakes in a particular area, while simultaneously using an emotion engine to assess the user's stress level.

[1022] 5. Solution Selection and Emotional Response:

[1023] The server selects the optimal recovery solution based on the analysis results, and also selects the optimal communication method taking into account the user's emotional data.

[1024] For example, if communications infrastructure is severely damaged, drone base stations can be used to ensure communications, while psychological care information can be provided to users experiencing high levels of stress.

[1025] 6. Create and send notifications:

[1026] The server creates a notification containing the analysis results and the selected recovery solution, and sends it to disaster response personnel and relevant users. The notification to users is sensitive to their emotions.

[1027] For example, disaster response personnel could be notified that "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications," while users could be sent reassuring messages such as "The current situation is serious, but please rest assured, recovery work is underway."

[1028] Specific examples

[1029] 1. Obtaining location and emotion data

[1030] Device: If the user is in Shinjuku Ward, Tokyo, location information of latitude 35.6938 degrees and longitude 139.7034 degrees is obtained using GPS, and at the same time, the stress level is evaluated from the user's voice and facial expression.

[1031] 2. Collecting information on damage

[1032] Terminal: When a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect strong shaking and record the data.

[1033] 3. Creating and sending a data package

[1034] Terminal: Sends location information, damage situation data, and emotion data together to the server.

[1035] 4. Data Receipt and Analysis

[1036] Server: Receives location information, vibration data, and emotion data from Shinjuku Ward and analyzes the data using a geographic information system and emotion engine.

[1037] 5. Solution selection and emotional response

[1038] Server: After building collapses and communication disruptions were confirmed, drone base stations were deployed and psychological care information was provided to users with high stress levels.

[1039] 6. Creating and sending notifications

[1040] Server: Sends detailed notifications along with the analysis results to disaster response personnel, and notifies users with reassurance.

[1041] In this way, the system of the present invention not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also takes user emotions into consideration when responding to disasters, enabling more effective disaster response.

[1042] The processing flow will be explained below.

[1043] Step 1:

[1044] The device periodically obtains the user's location information. Specifically, the device's built-in GPS module receives signals from the Global Positioning System (GPS) and calculates the latitude and longitude coordinates.

[1045] Step 2:

[1046] The device temporarily stores the acquired location information in memory, thereby retaining the user's current location as data.

[1047] Step 3:

[1048] The device uses an emotion engine to acquire the user's emotion data. Specifically, it collects and analyzes the user's voice data and facial expression data to determine their emotional state (e.g., stress level, sense of relief, anxiety).

[1049] Step 4:

[1050] When a disaster occurs, the device activates its built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation. For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record that data.

[1051] Step 5:

[1052] The device compiles the collected location information, emotional data, and damage situation data into a single data package, which includes the user's latitude and longitude, emotional state, and damage information collected from sensors.

[1053] Step 6:

[1054] The device then sends the created data package to the server via a mobile network or Wi-Fi. Specifically, the device establishes communication with the server at regular intervals and transmits the data via the Internet.

[1055] Step 7:

[1056] The server receives the data package sent from the terminal, and according to the receiving protocol, the data is stored in the server's storage.

[1057] Step 8:

[1058] The server analyzes the received data. During the analysis process, it uses a geographic information system (GIS) to identify the extent and scale of the damage and map the latitude and longitude information. At the same time, it uses an emotion engine to evaluate the user's emotional state.

[1059] Step 9:

[1060] The server then selects the optimal recovery solution based on the analysis results. For example, if widespread building collapse is confirmed, it will use drone base stations to ensure communications. On the other hand, if the user's stress level is high, it will include the option to provide psychological care information.

[1061] Step 10:

[1062] The server then creates a notification containing the selected recovery solution, detailing the damage situation and specific steps to implement the solution, and creating communication content that takes into account the user's emotional state.

[1063] Step 11:

[1064] The server then sends the created notifications to disaster response personnel and relevant users. The notifications are sent in real time via email or a dedicated application. The notifications to users are sent with emotional sensitivity.

[1065] Step 12:

[1066] The user (disaster response personnel) receives the notification. After checking the notification, the personnel in charge decide on a prompt response based on the provided information. For example, they issue instructions to the local operator to deploy a drone base station.

[1067] Step 13:

[1068] The user (disaster response officer) then instructs the local response team on the decided response measures, which allows for a quick and effective assessment of the damage situation and progress in recovery work.

[1069] Step 14:

[1070] The user (general user) checks the notification from the server. The notification is sensitive to the user's feelings and includes information on psychological care, giving the user a sense of security.

[1071] In this way, the system of the present invention not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also takes user emotions into consideration when responding to disasters, enabling more effective disaster response.

[1072] Example 2

[1073] 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."

[1074] Conventional disaster response systems are slow to grasp the extent of the damage, making it difficult to provide effective recovery solutions quickly. Furthermore, they do not take into account the emotional state of users, resulting in a lack of psychological support. Therefore, there is a need for systems that can accurately grasp the disaster situation and respond quickly while taking into account users' emotions.

[1075] 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.

[1076] In this invention, the server includes means for acquiring location information and emotion data, means for collecting damage status when a disaster occurs, and means for transmitting the collected location information, emotion data, and damage status, thereby enabling a quick and accurate understanding of the damage status and providing optimal recovery solutions that take into consideration the user's emotions.

[1077] "Location information" refers to data indicating the geographic coordinates of a user's current location, such as latitude and longitude.

[1078] "Emotion data" is data that indicates the user's emotional state, and includes stress levels and types of emotions obtained by analyzing voice and facial expressions.

[1079] "Means of collection" refers to the technologies and devices used to collect data, including sensors and analytics engines.

[1080] "Transmission means" refers to the methods or technologies used to send collected data to other devices or servers, including mobile networks and Wi-Fi.

[1081] "Means for analysis" refers to the technology or equipment used to process received data and understand its content, including geographic information systems (GIS) and sentiment analysis engines.

[1082] "Recovery solutions" refer to specific measures and methods for minimizing damage after a disaster and quickly restoring social functions.

[1083] "Means of notification" refers to the technology or devices used to communicate analysis results and recovery solutions to relevant personnel and users, including text messaging and notification applications.

[1084] overview

[1085] This invention is a system for quickly and accurately assessing the damage situation and providing optimal recovery solutions when a disaster occurs. It also recognizes the user's emotions and responds accordingly. In this system, the device collects the user's location information and emotional data, and sends them to a server along with damage situation data when a disaster occurs. The server analyzes this data, selects the optimal recovery solution and emotional response measures, and notifies the user.

[1086] Specific Embodiments

[1087] 1. Using the Device

[1088] The device uses a built-in GPS module to periodically obtain the user's location information, while at the same time utilizing an emotion engine to analyze and collect the user's emotions from voice and facial expression data. This emotion engine uses voice recognition software and image analysis algorithms.

[1089] Example: Obtain the location information (latitude 35.6938 degrees, longitude 139.7034 degrees) of a user in Shinjuku Ward, Tokyo, and use the emotion engine to analyze the user's voice and facial expressions to assess their stress level.

[1090] 2. Collecting information on damage

[1091] The device activates vibration and humidity sensors in the event of a disaster to collect data on the damage situation. For example, in the event of a major earthquake, the vibration sensor detects strong shaking and records that data. The humidity sensor also measures humidity levels in the event of flooding.

[1092] Example: If a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect high vibrations (e.g., seismic intensity of 6+) and the humidity sensor will measure high humidity (e.g., humidity of 90% or higher).

[1093] 3. Creating and sending a data package

[1094] The device then compiles the collected location information, emotion data, and damage situation data into a single data package, which also includes timestamps for each type of data.

[1095] The device then sends this data package over the mobile network or Wi-Fi to a server, which also encrypts the data before sending it.

[1096] 4. Data analysis on the server

[1097] The server receives the data package sent from the device, unpacks it, and analyzes the various data. Specifically, it uses a geographic information system (GIS) to analyze location information and evaluate the extent and scale of damage in a specific area. It also uses an emotion analysis engine to evaluate emotional data and quantify stress levels.

[1098] Example: Analyzing location information, vibration data, and emotion data in Shinjuku Ward to identify the extent of building collapse and assess the user's stress level.

[1099] 5. Selecting the best recovery solution and emotional response

[1100] The server selects the optimal recovery solution based on the results of the GIS and emotion analysis engine. For example, if there is significant damage to the communications infrastructure, it will deploy a drone base station to ensure communications. It also provides psychological care information based on the user's emotional state.

[1101] Example: If a communication failure is confirmed, a drone base station will be deployed in Shinjuku Ward to restore communication, and psychological care information will be provided to users experiencing high levels of stress.

[1102] 6. Creating and sending notifications

[1103] Based on the analysis and the selected recovery solution, the server generates messages to notify disaster response personnel and users. These notifications include appropriate timestamps and details of specific actions to be taken.

[1104] Example: Disaster response personnel could be notified, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy drone base stations to restore communications," while users could be notified, "The current situation is serious, but please rest assured, recovery work is underway."

[1105] Prompt Sentence Examples

[1106] "Please execute the emergency response protocol in the event of a major earthquake in Shinjuku Ward, Tokyo. Obtain the user's location information and emotion data and send it to the server along with damage status data."

[1107] In this way, the present invention enables effective disaster response by quickly and accurately grasping the damage situation when a disaster occurs and providing optimal recovery solutions that take into consideration the feelings of users.

[1108] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1109] Program processing flow

[1110] Step 1: Obtaining location and emotion data

[1111] The device obtains the user's location information using the built-in GPS module. The input for this operation is the signal from the GPS satellites, and the output is the user's current location (latitude and longitude).

[1112] Specific operation: For a user in Shinjuku Ward, Tokyo, the device obtains location information of latitude 35.6938 degrees and longitude 139.7034 degrees.

[1113] The device activates an emotion engine to analyze the user's voice and facial expressions in real time. The input for this operation is the user's voice and facial image, and the output is the user's emotional data (such as stress level).

[1114] Specific behavior: Analyzes the user's voice and facial expressions to recognize high stress levels.

[1115] Step 2: Collect damage information

[1116] When a disaster occurs, the terminal activates various sensors, such as vibration sensors and humidity sensors. The input for this operation is physical vibrations and changes in humidity, and the output is damage situation data.

[1117] Specific operation: When a major earthquake occurs, the vibration sensor detects and records shaking of a seismic intensity of 6+. The humidity sensor also measures humidity levels of 90% or higher.

[1118] Step 3: Creating and sending a data package

[1119] The terminal processes the collected location information, damage situation data, and emotion data into a single data package. The inputs for this operation are location information, emotion data, and damage situation data, and the output is a data package.

[1120] Specific operation: The device combines location information, emotional data indicating high stress levels, and vibration sensor data into a single package.

[1121] The device sends data packages to the server via a mobile network or Wi-Fi. The input is the data package, and the output is a notification of successful transmission.

[1122] What it does: Encrypts the data package and sends it to a server over the mobile network.

[1123] Step 4: Receiving and analyzing data

[1124] The server receives the data package sent from the terminal. The input of this operation is the data package, and the output is the data to be analyzed.

[1125] Specific operation: The received data package is unzipped and each piece of data is extracted for analysis.

[1126] The server analyzes the location information using a geographic information system (GIS) and simultaneously evaluates the emotional data using an emotion engine. The inputs of this operation are location information and emotional data, and the output is the identification of the damage extent and the evaluation of the stress level.

[1127] Specific operation: Identifies the extent of building collapse based on location information in Shinjuku Ward and evaluates the user's stress level.

[1128] Step 5: Selecting a solution and responding emotionally

[1129] The server selects the optimal recovery solution based on the analysis results. The input of this operation is the analysis results, and the output is the recovery solution.

[1130] Specific operation: If a building collapse and communication failure are confirmed, a solution will be selected to restore communication by placing a drone base station.

[1131] The server selects a communication method according to the user's emotional state. The input of this operation is the emotional evaluation result, and the output is an emotional response plan.

[1132] Specific operation: Provide psychological care information to users with high stress levels.

[1133] Step 6: Create and send notifications

[1134] The server generates a notification based on the analysis results and the selected recovery solution. The inputs to this operation are the analysis results and the solution, and the output is the notification.

[1135] Specific operation: The system notifies the person in charge, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications," and generates a message for the user saying, "The current situation is serious, but please rest assured, recovery work is underway."

[1136] The server then sends the created notification to the disaster response staff and the user. The input for this operation is the notification, and the output is a notification of successful transmission.

[1137] Specific operation: Sends notification text using messaging applications or SMS.

[1138] Through these steps, the system is able to quickly and accurately grasp the extent of the damage and provide optimal recovery solutions that take the user's feelings into consideration.

[1139] (Application example 2)

[1140] 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."

[1141] In disasters and emergencies, it is important to quickly and accurately grasp the damage situation and respond effectively to recovery. However, conventional systems do not take the user's emotional state into consideration when communicating. Furthermore, there is a lack of means to analyze the user's emotional data in real time and provide appropriate responses based on that analysis. Therefore, there is a need for the development of a system that provides quick and effective response measures while reducing the psychological burden on users in emergencies.

[1142] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1143] In this invention, the server includes means for acquiring location information and emotion data, means for generating and transmitting a data package of the damage situation and emotion data, means for analyzing the transmitted data package and selecting an optimal recovery solution, and means for generating and transmitting notification content taking the user's emotion data into consideration, thereby enabling a quick and accurate understanding of the damage situation and effective recovery measures that take the user's emotional state into consideration.

[1144] "Means for acquiring location information" refers to a device or software that receives signals from satellites or ground landmarks to acquire latitude and longitude data in order to identify the user's current location.

[1145] "Means for collecting damage information when a disaster occurs" refers to equipment or software that uses multiple sensors and devices to collect damage information such as building damage and earthquake intensity when a disaster occurs.

[1146] The "means for generating and transmitting a data package" refers to a device or software that assembles the collected location information, damage situation data, and emotion data into a single information packet and transmits it to a server.

[1147] The "means for selecting the optimal recovery solution" is a device or software that analyzes the transmitted data and determines the optimal recovery method or measures based on the extent of the damage and the user's emotional state.

[1148] The "means for recognizing and analyzing user emotional data" refers to a device or software for analyzing the user's voice and facial expressions and determining their emotional state.

[1149] The "means for generating and transmitting notification content" refers to a device or software that generates a notification with appropriate content based on the damage situation and the user's emotions, and transmits it to the user and disaster response personnel.

[1150] The Global Positioning System (GPS) is a system that uses satellites to calculate specific geographic locations and obtain user location information.

[1151] "Multiple built-in sensors" refers to a group of sensors built into a device that collect various environmental information such as vibration, humidity, and temperature.

[1152] A "geographic information system (GIS)" is software for managing, analyzing, and visually displaying geographic data.

[1153] This invention is a system that not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also recognizes the user's emotional state and takes this into consideration when responding. This system is mainly composed of terminals and a server, and each terminal collects location information and emotional data, which the server analyzes and provides appropriate responses.

[1154] System Configuration

[1155] Terminal

[1156] Hardware

[1157] Mobile communication devices such as smartphones

[1158] Built-in GPS module

[1159] Multiple built-in sensors (vibration sensor, humidity sensor, temperature sensor, etc.)

[1160] Camera and microphone

[1161] software

[1162] Location information acquisition module

[1163] Emotion analysis module (performs voice analysis and facial expression analysis)

[1164] Data package generation and transmission module

[1165] server

[1166] Hardware

[1167] High-performance computers

[1168] software

[1169] Data Receiving Module

[1170] Data analysis module (including a geographic information system (GIS) and sentiment analysis engine)

[1171] Restoration Solution Selection Module

[1172] Notification Generation and Sending Module

[1173] Processing steps

[1174] Location and emotion data acquisition

[1175] The device periodically obtains the user's location information using a GPS module. It also uses a camera and microphone to analyze the user's voice and facial expressions to collect emotional data. This allows the device to obtain the user's latitude (35.6938 degrees) and longitude (139.7034 degrees) if the user is in Tokyo, and simultaneously analyze the user's stress level.

[1176] Collecting information on damage

[1177] When a disaster occurs, the device uses its built-in sensors to collect information on the damage situation. For example, if a major earthquake occurs, the vibration sensor will detect strong shaking and record that data.

[1178] Creating and sending data packages

[1179] The device compiles location information, damage situation data, and emotion data into a single data package and sends it to a server via a mobile network or Wi-Fi.

[1180] Data reception and analysis

[1181] The server receives the data packages sent from the devices and analyzes the extent and scale of the damage, as well as the user's emotional state. It uses a geographic information system (GIS) to analyze the impact of building collapses and earthquakes in a specific area, while simultaneously using an emotion engine to assess the user's stress level.

[1182] Solution selection and emotional response

[1183] The server selects the optimal recovery solution based on the analysis results. It also considers the user's emotional data to select the optimal communication method. For example, if the communications infrastructure is severely damaged, it will use drone base stations to ensure communications. Meanwhile, it will provide psychological care information to users experiencing high levels of stress.

[1184] Creating and sending notifications

[1185] The server creates a notification containing the analysis results and the selected recovery solution, and sends it to disaster response personnel and the appropriate users. The notification to users is sensitive to their emotions. For example, disaster response personnel might be notified that "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy drone base stations to restore communications," while users might be notified with a message that provides reassurance, such as "The current situation is serious, but please rest assured that recovery work is underway."

[1186] Adding specific examples

[1187] Example 1: Obtaining location and emotion data

[1188] Example prompt:

[1189] "Collect audio data to analyze the user's stress level and obtain latitude and longitude location information."

[1190] Example 2: Anomaly detection and response

[1191] Example prompt:

[1192] "If the user is in a state of extreme stress, contact the police and notify the user."

[1193] In this way, the system of the present invention makes it possible to quickly and accurately grasp the extent of damage and to take effective recovery measures while taking into consideration the emotional state of the user.

[1194] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1195] Step 1:

[1196] The device periodically obtains the user's location information using a GPS module. The input data is signals obtained from satellites, and the device calculates the latitude and longitude based on this. The output data is the user's current location information (e.g., latitude 35.6938 degrees, longitude 139.7034 degrees).

[1197] Step 2:

[1198] The device uses a camera and microphone to collect the user's voice and facial expressions. The input data is the user's facial image captured by the camera and the voice data recorded by the microphone. This data is input into an emotion analysis module to analyze the user's stress level and emotional state. The output data is the user's emotional data (e.g., high stress level).

[1199] Step 3:

[1200] The device constantly monitors the surrounding situation using built-in sensors (e.g., vibration sensor, humidity sensor). When a disaster occurs, these sensors collect data on the damage situation. The input data is shaking intensity data from the vibration sensor and humidity data from the humidity sensor. The output data is damage situation data (e.g., strong shaking, humidity changes).

[1201] Step 4:

[1202] The device compiles the obtained location information, emotion data, and damage situation data into a single data package. The input data is the information obtained at each step (location information, emotion data, damage situation data). The output data is the compiled data package.

[1203] Step 5:

[1204] The terminal transmits the generated data package to the server using a mobile network or Wi-Fi. The input data is the data package, and the output data is the data package received by the server.

[1205] Step 6:

[1206] The server analyzes the received data package. The input data is the data package sent from the device, and it analyzes it using a geographic information system (GIS) and an emotion analysis engine. The output data is the range and scale of the damage, as well as evaluation information on the user's emotional state.

[1207] Step 7:

[1208] The server selects the optimal recovery solution based on the analysis results. The input data are the analysis results, and based on these, the optimal recovery method (e.g., the placement of drone base stations or the provision of psychological care information) is determined. The output data is the selected recovery solution.

[1209] Step 8:

[1210] The server creates a notification containing the selected recovery solution and the analysis results, and sends it to disaster response personnel and appropriate users. The input data are the recovery solution and the analysis results, and the output data is the configured notification content.

[1211] Step 9:

[1212] The user can receive notifications from the server and feel secure. The input data is the notification sent from the server, and the output data is the user's sense of security.

[1213] 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.

[1214] 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.

[1215] 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.

[1216] [Fourth embodiment]

[1217] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1218] 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.

[1219] 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).

[1220] 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.

[1221] 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.

[1222] 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).

[1223] 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.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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.

[1228] 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.

[1229] 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."

[1230] This invention is a system that aims to quickly and accurately grasp the damage situation when a disaster occurs and provide optimal recovery solutions. This system uses a GPS device embedded in the user to collect location information, and when a disaster occurs, it collects damage information through sensors. Based on the collected data, a server selects the optimal recovery solution and notifies disaster response personnel.

[1231] Program processing (outline)

[1232] 1. Location information acquisition:

[1233] The terminal periodically acquires the user's location information using GPS.

[1234] For example, the device identifies the user's location within Tokyo and collects the user's latitude and longitude information.

[1235] 2. Collecting damage information:

[1236] When a disaster occurs, the device uses built-in sensors (such as vibration sensors and humidity sensors) to collect data on the damage situation.

[1237] For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record the data.

[1238] 3. Data transmission:

[1239] The terminal transmits the collected location information and damage situation data to the server.

[1240] Specifically, the device transmits this data to a server via a mobile network or Wi-Fi.

[1241] 4. Data Receipt and Analysis:

[1242] The server receives the data sent from the device and analyzes the scope and scale of the damage.

[1243] For example, the server uses a geographic information system (GIS) to analyze the impact of building collapses or earthquakes in a particular area.

[1244] 5. Solution Selection:

[1245] The server selects the optimal recovery solution based on the analysis results.

[1246] For example, if communications infrastructure is severely damaged, drone base stations will be deployed to ensure communications.

[1247] 6. Sending notifications:

[1248] The server notifies disaster response personnel of the analysis results and the selected recovery solution.

[1249] For example, information such as "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications" will be sent to disaster response personnel.

[1250] Specific examples

[1251] 1. Obtaining location information

[1252] Terminal: If the user is in Shinjuku-ku, Tokyo, location information of latitude 35.6938 degrees and longitude 139.7034 degrees is obtained using GPS.

[1253] 2. Collecting information on damage

[1254] Terminal: When a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect strong shaking and record the data.

[1255] 3. Data transmission

[1256] Terminal: The collected location information and damage situation data is sent to the server via Wi-Fi.

[1257] 4. Data Receipt and Analysis

[1258] Server: Receives location information and vibration data from Shinjuku Ward and analyzes the state of building collapse using a geographic information system.

[1259] 5. Solution Selection

[1260] Server: After confirming that communication has been disrupted due to the collapse of a building, it is decided to deploy a drone base station.

[1261] 6. Sending Notifications

[1262] Server: Notifies disaster response personnel of the analysis results along with instructions for drone base station placement.

[1263] In this way, the present invention makes it possible to quickly and accurately grasp the extent of damage when a disaster occurs and to provide optimal recovery solutions, thereby significantly improving the efficiency of disaster response.

[1264] The processing flow will be explained below.

[1265] Step 1:

[1266] The device periodically obtains the user's location information: the device's built-in GPS module receives signals from the Global Positioning System (GPS) and calculates the latitude and longitude coordinates.

[1267] Step 2:

[1268] The device temporarily stores the acquired location information in memory, thereby retaining the user's current location as data.

[1269] Step 3:

[1270] When a disaster occurs, the device activates various built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation. For example, if the vibration sensor detects earthquake tremors, it will record the strength and duration of the tremors.

[1271] Step 4:

[1272] The device compiles the collected location information and damage situation data into a single data package, which includes the user's latitude and longitude and damage information collected from sensors.

[1273] Step 5:

[1274] The device then sends the created data package to the server via a mobile network or Wi-Fi. Specifically, the device establishes communication with the server at regular intervals and transmits the data via the Internet.

[1275] Step 6:

[1276] The server receives the data package sent from the terminal, and according to the receiving protocol, the data is stored in the server's storage.

[1277] Step 7:

[1278] The server analyzes the received data. During the analysis process, a geographic information system (GIS) is used to identify the extent and scale of the damage and map the latitude and longitude information.

[1279] Step 8:

[1280] The server selects the optimal recovery solution based on the analysis results. For example, if widespread building collapse is confirmed, one option would be to use drone base stations to ensure communications.

[1281] Step 9:

[1282] The server creates a notification containing the selected recovery solution, along with details of the damage and instructions on how to implement the solution.

[1283] Step 10:

[1284] The server then sends the created notifications to disaster response personnel in real time via email or a dedicated application.

[1285] Step 11:

[1286] The user (disaster response officer) receives the notification and decides on a prompt response based on the information provided.

[1287] Step 12:

[1288] The user (disaster response officer) instructs the local response team on the decided response measures, for example, by issuing instructions to the local operator to deploy drone base stations, aiming to quickly restore the damage situation.

[1289] Through the above processing steps, the system of the present invention responds to disasters quickly and accurately, contributing to minimizing damage and improving the efficiency of recovery.

[1290] Example 1

[1291] 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."

[1292] When a disaster occurs, it is important to quickly and accurately grasp the damage situation, but current methods often result in delays in collecting and analyzing damage information. As a result, there is a problem of delays in selecting and implementing appropriate recovery solutions. Furthermore, there is an issue of the inability to respond to disasters quickly due to limited means of quickly communicating damage information.

[1293] 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.

[1294] In this invention, the server includes means for periodically acquiring user location information, means for collecting damage status using a built-in sensor when a disaster occurs, means for transmitting the collected location information and damage status data via a network, means for receiving the transmitted location information and damage status data and analyzing the range and scale of the damage using a geographic information system (GIS), means for automatically selecting an optimal recovery solution based on the analysis results, and means for notifying disaster response personnel of the selected recovery solution and the analysis results in real time, thereby enabling a quick and accurate understanding of the damage status and the provision of an optimal recovery solution.

[1295] The "means for periodically obtaining location information" is a device, system, or method for measuring and recording the latitude and longitude of the user's current location at regular intervals.

[1296] "Means for collecting damage information using built-in sensors when a disaster occurs" refers to a device, system, or method that uses various sensors built into a terminal, such as vibration sensors and humidity sensors, to obtain information on damage when a disaster occurs.

[1297] "Means for transmitting collected location information and damage situation data via a network" refers to a device, system, or method for transmitting collected data to a server using communication infrastructure such as Wi-Fi or a mobile network (LTE, 5G, etc.).

[1298] "Means for receiving the transmitted location information and damage situation data and analyzing the extent and scale of the damage using a geographic information system (GIS)" refers to a device, system, or method in which a server receives data sent from a terminal, analyzes it, and uses a geographic information system (GIS) to measure the extent and severity of the damage.

[1299] A "means for automatically selecting an optimal recovery solution based on analysis results" is a device, system, or method that uses an algorithm or program to automatically select the most effective recovery measures based on the results of data analysis.

[1300] "Means for notifying disaster response personnel of selected recovery solutions and analysis results in real time" means a device, system, or method that uses a communication device (e.g., smartphone, tablet, etc.) to quickly communicate selected recovery solutions and analysis results to disaster response personnel.

[1301] This invention is a system that aims to quickly and accurately grasp the damage situation when a disaster occurs and provide optimal recovery solutions. This system uses GPS devices and various sensors (vibration sensors, humidity sensors, etc.) embedded in the user's device to collect location information and disaster damage information, and sends the collected information to a server. The server analyzes this information, automatically selects the optimal recovery solution, and notifies disaster response personnel in real time.

[1302] Hardware and Software Details

[1303] The device uses the following hardware and software:

[1304] GPS module: A device for obtaining user location information. It outputs latitude and longitude information.

[1305] Vibration and humidity sensors: Devices for detecting vibrations and changes in humidity during disasters. Each sensor converts analog signals into digital data and stores it in its internal memory.

[1306] Communication module: A device that supports Wi-Fi and mobile networks (LTE, 5G, etc.) and transmits collected data to a server.

[1307] The server uses the following software:

[1308] Data receiving module: Receives location information and damage situation data sent from the terminal.

[1309] GIS (Geographic Information System): Software that analyzes received location information and damage situation data to visualize the scope and scale of damage.

[1310] Analysis and restoration solution selection algorithm: An algorithm that analyzes damage data and selects the optimal restoration solution (e.g., drone base station placement).

[1311] Notification module: Notifies disaster response personnel in real time of analysis results and selected recovery solutions.

[1312] Specific examples

[1313] For example, if a user is in Shinjuku Ward, Tokyo, the device will periodically obtain location information (latitude 35.6938 degrees, longitude 139.7034 degrees) using GPS. If a major earthquake occurs in Shinjuku Ward and the vibration sensor detects strong shaking, the device will record the data in its internal memory. The device will then use Wi-Fi if available, or send the location information and damage data to the server via the mobile network if not.

[1314] The server receives this data and uses GIS to analyze the impact of building collapses and earthquakes in a specific area. Based on the analysis results, the server selects the optimal recovery solution, for example, if communication infrastructure is damaged, it decides to deploy drone base stations. After making a decision, the server sends notifications to disaster response personnel in real time and instructs them on actual response measures.

[1315] Prompt Sentence Examples

[1316] An example of a prompt to be input to the generative AI model is as follows:

[1317] Location information acquisition: "If the user is in Shinjuku Ward, Tokyo, please use GPS to acquire latitude and longitude information."

[1318] Collecting damage information: "When a major earthquake occurs in Shinjuku Ward, please use the vibration sensor to record the strength of the shaking."

[1319] Data transmission: "Please send the collected location information and damage situation data to the server via Wi-Fi."

[1320] Receiving and analyzing data: "The server will receive location information and vibration data from Shinjuku Ward, and will use GIS to analyze the state of building collapse."

[1321] Solution Selection: "The server should determine the optimal recovery solution based on the analysis results, and decide to deploy a drone base station."

[1322] Send notification: "The server will notify disaster response personnel of the analysis results and provide instructions for drone base station placement."

[1323] In this way, the present invention realizes a system that enables rapid and accurate understanding of the damage situation and the provision of appropriate recovery solutions.

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

[1325] Step 1:

[1326] Obtaining location information

[1327] The terminal acquires the user's location information at regular intervals using the GPS module.

[1328] Input: The device's built-in GPS module provides current latitude and longitude data.

[1329] Data processing: The acquired latitude and longitude data is recorded in the internal memory. For example, if the user is in Shinjuku Ward, Tokyo, the GPS module will generate information on latitude 35.6938 degrees and longitude 139.7034 degrees.

[1330] Output: Recorded location data.

[1331] Step 2:

[1332] Collecting information on damage

[1333] When the device detects signs of a disaster (such as an earthquake), it activates its built-in sensors (vibration sensor and humidity sensor).

[1334] Input: Earthquake tremors detected by a vibration sensor and humidity changes detected by a humidity sensor.

[1335] Data processing: The data acquired by the sensor is converted into a digital signal and stored in the internal memory. For example, if a major earthquake occurs in Shinjuku Ward and the vibration sensor detects strong shaking of magnitude 7, that data will be recorded.

[1336] Output: Recorded damage status data.

[1337] Step 3:

[1338] Sending data

[1339] The terminal transmits the acquired location information and damage situation data to a server via the network.

[1340] Input: Location information and damage situation data recorded in memory.

[1341] Data processing: Converts data into packets and prepares it for transmission. The device first checks whether a Wi-Fi connection is available, and if so, uses Wi-Fi to transmit the data. If Wi-Fi is not available, it uses the mobile network (LTE or 5G) to transmit the data.

[1342] Output: Location information and damage situation data sent to the server.

[1343] Step 4:

[1344] Data reception and analysis

[1345] The server receives and analyzes the data sent from the terminal.

[1346] Input: Received location information and damage situation data.

[1347] Data processing: Using a GIS (geographic information system), the received data is visualized on a map to analyze the extent and scale of the damage. For example, the GIS system generates a heat map of the affected area, visually showing the impact of a specific region.

[1348] Output: Analysis results of the extent and scale of damage.

[1349] Step 5:

[1350] Solution Selection

[1351] The server selects the optimal recovery solution based on the analysis results.

[1352] Input: Analysis results of the extent and scale of the damage.

[1353] Data processing: Based on the analysis results, an algorithm is run to automatically select the optimal recovery method (e.g., deploying a drone base station if communications infrastructure is damaged).

[1354] Output: The selected recovery solution.

[1355] Step 6:

[1356] Sending notifications

[1357] The server notifies disaster response personnel in real time of the analysis results and the selected recovery solution.

[1358] Input: Selected restoration solution and analysis results.

[1359] Data processing: Generates notification content and prepares it for transmission to communication devices (smartphones, tablets, etc.).

[1360] Output: A notification sent to disaster response personnel, including specific instructions such as "Large-scale building collapse confirmed in Shinjuku Ward. Deploy drone base stations to restore communications."

[1361] In this way, each step works in coordination to quickly and accurately grasp the extent of the damage and provide appropriate recovery solutions.

[1362] (Application example 1)

[1363] 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."

[1364] Conventional disaster management systems were slow to grasp the extent of damage when a disaster occurred, making it difficult to provide appropriate recovery solutions. Furthermore, the means of collecting damage data were limited, making it impossible to effectively collect and utilize real-time information from the site. As a result, disaster response was inefficient, and recovery was delayed, potentially leading to greater damage.

[1365] 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.

[1366] In this invention, the server includes means for acquiring location information, means for collecting damage status when a disaster occurs, means for transmitting the collected location information and damage status, means for analyzing the transmitted location information and damage status and selecting an optimal recovery solution, means for notifying disaster response personnel of the analysis results and the selected recovery solution, and means for collecting damage data using a smart device, thereby enabling the collection of damage information in real time and the provision of optimal recovery solutions.

[1367] "Location information" is latitude and longitude data that indicates a specific point on Earth.

[1368] "Damage situation" is data that indicates the extent of damage and impact to buildings and infrastructure when a disaster occurs.

[1369] The "server" is a central processing unit that analyzes the collected data and provides optimal recovery solutions.

[1370] A "GPS device" is a device that obtains location information using the Global Positioning System.

[1371] A "sensor" is a device that detects and collects data about the physical environment. Examples include vibration sensors and humidity sensors.

[1372] "Network interface" is a general term for hardware and software for wirelessly transmitting data to other devices or servers.

[1373] "Smart devices" refers to mobile terminals with advanced functions, including smart glasses and smartphones.

[1374] A "geographic information system (GIS)" is a system for analyzing and visualizing geospatial data.

[1375] A "generative AI model" is a model that uses machine learning and deep learning to analyze and predict data.

[1376] A "prompt sentence" is an instruction sentence in natural language format that is input to a generative AI model.

[1377] To implement this invention, a GPS device for acquiring location information, multiple sensors for collecting damage information, a network interface for transmitting data, and a server for analysis and notification are required. In particular, smart glasses and a smartphone are used as smart devices.

[1378] Obtaining location information

[1379] The server periodically obtains the user's location information using a GPS device, which is built into the smart glasses and smartphone, and accurately collects the user's current latitude and longitude information.

[1380] Collecting information on damage

[1381] When a disaster occurs, the server collects data on the damage situation using the vibration and humidity sensors built into smart devices. For example, if a major earthquake occurs, the vibration sensor will detect strong shaking and record that data.

[1382] Sending data

[1383] The collected location information and damage situation data are sent to a server via a network interface. Specifically, smart devices use mobile networks or Wi-Fi to send this data to the server.

[1384] Data reception and analysis

[1385] The server receives the data sent from the devices and uses a geographic information system (GIS) to analyze the extent and scale of the damage, making it possible to clarify the extent of building collapses and the impact of the earthquake in a specific area.

[1386] Selecting a recovery solution

[1387] The server uses a generative AI model to select the optimal recovery solution, using prompts to input to the generative AI model for analysis.

[1388] Sending notifications

[1389] The analysis results and the selected restoration solution are then communicated to disaster response personnel. For example, if communications infrastructure is severely damaged, the server will instruct drone base stations to be deployed to restore communications.

[1390] Specific examples

[1391] If the user is in Shinjuku Ward, Tokyo, the smart glasses' GPS will be used to obtain location information at latitude 35.6938 degrees and longitude 139.7034 degrees. When a major earthquake occurs in Shinjuku Ward, the smart glasses' vibration sensor will detect strong shaking and send the data to a server via Wi-Fi. The server will use a geographic information system to analyze the state of building collapse and, since communication disruptions have been confirmed, will decide to deploy a drone base station. Disaster response personnel will receive a notification stating, "Large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communication."

[1392] Prompt Sentence Examples

[1393] "When a large earthquake occurs, please explain the system in which a server analyzes the damage situation based on data detected by vibration sensors and location information obtained by GPS devices, and selects the optimal recovery solution. In this system, smart glasses have built-in sensors and GPS devices that collect and communicate data. Example: Specific processing procedures when a large earthquake occurs in Shinjuku Ward."

[1394] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1395] Step 1: Obtaining location information

[1396] The server periodically obtains the user's location information using a GPS device. The input is the user's current location, and the output is latitude and longitude data. This data is collected from GPS devices built into smart glasses or smartphones. For example, if a user is in Shinjuku Ward, Tokyo, the server collects location information of latitude 35.6938 degrees and longitude 139.7034 degrees.

[1397] Step 2: Collect damage information

[1398] When a disaster occurs, the server collects data on the damage situation using sensors (vibration sensors and humidity sensors) built into smart devices. The input is sensor data, and the output is damage situation data such as earthquake shaking and humidity changes. For example, when a major earthquake occurs, the vibration sensor in the smart glasses detects strong shaking and records that data.

[1399] Step 3: Sending data

[1400] The server transmits the collected location information and damage status data through a network interface. Location information and damage status data are input, and these data are sent to the server as output. This transmission is done from the smart device using a mobile network or Wi-Fi. For example, location information and vibration data collected in Shinjuku Ward are sent to the server via Wi-Fi.

[1401] Step 4: Receiving and analyzing data

[1402] The server receives the data sent from the terminals and uses a geographic information system (GIS) to analyze the extent and scale of the damage. Location information and damage data are input, and damage analysis results are obtained as output. For example, the server receives location information and vibration data from Shinjuku Ward and analyzes the collapse and impact of buildings in that area.

[1403] Step 5: Select a recovery solution

[1404] The server uses a generative AI model based on the analysis results to select the optimal recovery solution. This analysis is driven by a prompt statement. The inputs are the damage analysis results and the prompt statement, and the output is a specific recovery solution. For example, the server may determine that communication infrastructure is damaged and decide to deploy a drone base station.

[1405] Step 6: Sending notifications

[1406] The server notifies disaster response personnel of the analysis results and the selected recovery solution. The inputs are the recovery solution and notification text, and the output is the notification that is sent to the personnel. For example, disaster response personnel receive information such as, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications."

[1407] 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.

[1408] This invention is a system that, in addition to quickly and accurately grasping the damage situation and providing optimal recovery solutions when a disaster occurs, recognizes the user's emotions and takes these into consideration when responding. This system uses a GPS device and emotion engine embedded in the user to collect location information and emotion data, and transmits the damage situation and emotion data to a server when a disaster occurs. The server analyzes the collected data and works with the emotion engine to provide optimal recovery solutions and communicates with the user in a way that takes their emotions into consideration.

[1409] Program processing (outline)

[1410] 1. Location and emotion data acquisition:

[1411] The device periodically acquires the user's location information using GPS and collects the user's emotion data using an emotion engine.

[1412] For example, if the device is located within Tokyo, it will analyze the user's location information (latitude and longitude) and their voice and facial expressions to collect emotions (such as stress level).

[1413] 2. Collecting damage information:

[1414] When a disaster occurs, the device activates its built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation.

[1415] For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record the data.

[1416] 3. Creating and sending a data package:

[1417] The device compiles the collected location information, damage situation data, and user emotion data into a single data package and sends it to the server.

[1418] Specifically, the device transmits this data to a server via a mobile network or Wi-Fi.

[1419] 4. Data Receipt and Analysis:

[1420] The server receives the data package sent from the device and analyzes the scope and scale of the damage, as well as the user's emotional state.

[1421] For example, the server may use a geographic information system (GIS) to analyze the impact of building collapses or earthquakes in a particular area, while simultaneously using an emotion engine to assess the user's stress level.

[1422] 5. Solution Selection and Emotional Response:

[1423] The server selects the optimal recovery solution based on the analysis results, and also selects the optimal communication method taking into account the user's emotional data.

[1424] For example, if communications infrastructure is severely damaged, drone base stations can be used to ensure communications, while psychological care information can be provided to users experiencing high levels of stress.

[1425] 6. Create and send notifications:

[1426] The server creates a notification containing the analysis results and the selected recovery solution, and sends it to disaster response personnel and relevant users. The notification to users is sensitive to their emotions.

[1427] For example, disaster response personnel could be notified that "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications," while users could be sent reassuring messages such as "The current situation is serious, but please rest assured, recovery work is underway."

[1428] Specific examples

[1429] 1. Obtaining location and emotion data

[1430] Device: If the user is in Shinjuku Ward, Tokyo, location information of latitude 35.6938 degrees and longitude 139.7034 degrees is obtained using GPS, and at the same time, the stress level is evaluated from the user's voice and facial expression.

[1431] 2. Collecting information on damage

[1432] Terminal: When a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect strong shaking and record the data.

[1433] 3. Creating and sending a data package

[1434] Terminal: Sends location information, damage situation data, and emotion data together to the server.

[1435] 4. Data Receipt and Analysis

[1436] Server: Receives location information, vibration data, and emotion data from Shinjuku Ward and analyzes the data using a geographic information system and emotion engine.

[1437] 5. Solution selection and emotional response

[1438] Server: After building collapses and communication disruptions were confirmed, drone base stations were deployed and psychological care information was provided to users with high stress levels.

[1439] 6. Creating and sending notifications

[1440] Server: Sends detailed notifications along with the analysis results to disaster response personnel, and notifies users with reassurance.

[1441] In this way, the system of the present invention not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also takes user emotions into consideration when responding to disasters, enabling more effective disaster response.

[1442] The processing flow will be explained below.

[1443] Step 1:

[1444] The device periodically obtains the user's location information. Specifically, the device's built-in GPS module receives signals from the Global Positioning System (GPS) and calculates the latitude and longitude coordinates.

[1445] Step 2:

[1446] The device temporarily stores the acquired location information in memory, thereby retaining the user's current location as data.

[1447] Step 3:

[1448] The device uses an emotion engine to acquire the user's emotion data. Specifically, it collects and analyzes the user's voice data and facial expression data to determine their emotional state (e.g., stress level, sense of relief, anxiety).

[1449] Step 4:

[1450] When a disaster occurs, the device activates its built-in sensors (vibration sensor, humidity sensor, etc.) to collect data on the damage situation. For example, if a major earthquake occurs, the device's vibration sensor will detect strong shaking and record that data.

[1451] Step 5:

[1452] The device compiles the collected location information, emotional data, and damage situation data into a single data package, which includes the user's latitude and longitude, emotional state, and damage information collected from sensors.

[1453] Step 6:

[1454] The device then sends the created data package to the server via a mobile network or Wi-Fi. Specifically, the device establishes communication with the server at regular intervals and transmits the data via the Internet.

[1455] Step 7:

[1456] The server receives the data package sent from the terminal, and according to the receiving protocol, the data is stored in the server's storage.

[1457] Step 8:

[1458] The server analyzes the received data. During the analysis process, it uses a geographic information system (GIS) to identify the extent and scale of the damage and map the latitude and longitude information. At the same time, it uses an emotion engine to evaluate the user's emotional state.

[1459] Step 9:

[1460] The server then selects the optimal recovery solution based on the analysis results. For example, if widespread building collapse is confirmed, it will use drone base stations to ensure communications. On the other hand, if the user's stress level is high, it will include the option to provide psychological care information.

[1461] Step 10:

[1462] The server then creates a notification containing the selected recovery solution, detailing the damage situation and specific steps to implement the solution, and creating communication content that takes into account the user's emotional state.

[1463] Step 11:

[1464] The server then sends the created notifications to disaster response personnel and relevant users. The notifications are sent in real time via email or a dedicated application. The notifications to users are sent with emotional sensitivity.

[1465] Step 12:

[1466] The user (disaster response personnel) receives the notification. After checking the notification, the personnel in charge decide on a prompt response based on the provided information. For example, they issue instructions to the local operator to deploy a drone base station.

[1467] Step 13:

[1468] The user (disaster response officer) then instructs the local response team on the decided response measures, which allows for a quick and effective assessment of the damage situation and progress in recovery work.

[1469] Step 14:

[1470] The user (general user) checks the notification from the server. The notification is sensitive to the user's feelings and includes information on psychological care, giving the user a sense of security.

[1471] In this way, the system of the present invention not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also takes user emotions into consideration when responding to disasters, enabling more effective disaster response.

[1472] Example 2

[1473] 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."

[1474] Conventional disaster response systems are slow to grasp the extent of the damage, making it difficult to provide effective recovery solutions quickly. Furthermore, they do not take into account the emotional state of users, resulting in a lack of psychological support. Therefore, there is a need for systems that can accurately grasp the disaster situation and respond quickly while taking into account users' emotions.

[1475] 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.

[1476] In this invention, the server includes means for acquiring location information and emotion data, means for collecting damage status when a disaster occurs, and means for transmitting the collected location information, emotion data, and damage status, thereby enabling a quick and accurate understanding of the damage status and providing optimal recovery solutions that take into consideration the user's emotions.

[1477] "Location information" refers to data indicating the geographic coordinates of a user's current location, such as latitude and longitude.

[1478] "Emotion data" is data that indicates the user's emotional state, and includes stress levels and types of emotions obtained by analyzing voice and facial expressions.

[1479] "Means of collection" refers to the technologies and devices used to collect data, including sensors and analytics engines.

[1480] "Transmission means" refers to the methods or technologies used to send collected data to other devices or servers, including mobile networks and Wi-Fi.

[1481] "Means for analysis" refers to the technology or equipment used to process received data and understand its content, including geographic information systems (GIS) and sentiment analysis engines.

[1482] "Recovery solutions" refer to specific measures and methods for minimizing damage after a disaster and quickly restoring social functions.

[1483] "Means of notification" refers to the technology or devices used to communicate analysis results and recovery solutions to relevant personnel and users, including text messaging and notification applications.

[1484] overview

[1485] This invention is a system for quickly and accurately assessing the damage situation and providing optimal recovery solutions when a disaster occurs. It also recognizes the user's emotions and responds accordingly. In this system, the device collects the user's location information and emotional data, and sends them to a server along with damage situation data when a disaster occurs. The server analyzes this data, selects the optimal recovery solution and emotional response measures, and notifies the user.

[1486] Specific Embodiments

[1487] 1. Using the Device

[1488] The device uses a built-in GPS module to periodically obtain the user's location information, while at the same time utilizing an emotion engine to analyze and collect the user's emotions from voice and facial expression data. This emotion engine uses voice recognition software and image analysis algorithms.

[1489] Example: Obtain the location information (latitude 35.6938 degrees, longitude 139.7034 degrees) of a user in Shinjuku Ward, Tokyo, and use the emotion engine to analyze the user's voice and facial expressions to assess their stress level.

[1490] 2. Collecting information on damage

[1491] The device activates vibration and humidity sensors in the event of a disaster to collect data on the damage situation. For example, in the event of a major earthquake, the vibration sensor detects strong shaking and records that data. The humidity sensor also measures humidity levels in the event of flooding.

[1492] Example: If a major earthquake occurs in Shinjuku Ward, the vibration sensor will detect high vibrations (e.g., seismic intensity of 6+) and the humidity sensor will measure high humidity (e.g., humidity of 90% or higher).

[1493] 3. Creating and sending a data package

[1494] The device then compiles the collected location information, emotion data, and damage situation data into a single data package, which also includes timestamps for each type of data.

[1495] The device then sends this data package over the mobile network or Wi-Fi to a server, which also encrypts the data before sending it.

[1496] 4. Data analysis on the server

[1497] The server receives the data package sent from the device, unpacks it, and analyzes the various data. Specifically, it uses a geographic information system (GIS) to analyze location information and evaluate the extent and scale of damage in a specific area. It also uses an emotion analysis engine to evaluate emotional data and quantify stress levels.

[1498] Example: Analyzing location information, vibration data, and emotion data in Shinjuku Ward to identify the extent of building collapse and assess the user's stress level.

[1499] 5. Selecting the best recovery solution and emotional response

[1500] The server selects the optimal recovery solution based on the results of the GIS and emotion analysis engine. For example, if there is significant damage to the communications infrastructure, it will deploy a drone base station to ensure communications. It also provides psychological care information based on the user's emotional state.

[1501] Example: If a communication failure is confirmed, a drone base station will be deployed in Shinjuku Ward to restore communication, and psychological care information will be provided to users experiencing high levels of stress.

[1502] 6. Creating and sending notifications

[1503] Based on the analysis and the selected recovery solution, the server generates messages to notify disaster response personnel and users. These notifications include appropriate timestamps and details of specific actions to be taken.

[1504] Example: Disaster response personnel could be notified, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy drone base stations to restore communications," while users could be notified, "The current situation is serious, but please rest assured, recovery work is underway."

[1505] Prompt Sentence Examples

[1506] "Please execute the emergency response protocol in the event of a major earthquake in Shinjuku Ward, Tokyo. Obtain the user's location information and emotion data and send it to the server along with damage status data."

[1507] In this way, the present invention enables effective disaster response by quickly and accurately grasping the damage situation when a disaster occurs and providing optimal recovery solutions that take into consideration the feelings of users.

[1508] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1509] Program processing flow

[1510] Step 1: Obtaining location and emotion data

[1511] The device obtains the user's location information using the built-in GPS module. The input for this operation is the signal from the GPS satellites, and the output is the user's current location (latitude and longitude).

[1512] Specific operation: For a user in Shinjuku Ward, Tokyo, the device obtains location information of latitude 35.6938 degrees and longitude 139.7034 degrees.

[1513] The device activates an emotion engine to analyze the user's voice and facial expressions in real time. The input for this operation is the user's voice and facial image, and the output is the user's emotional data (such as stress level).

[1514] Specific behavior: Analyzes the user's voice and facial expressions to recognize high stress levels.

[1515] Step 2: Collect damage information

[1516] When a disaster occurs, the terminal activates various sensors, such as vibration sensors and humidity sensors. The input for this operation is physical vibrations and changes in humidity, and the output is damage situation data.

[1517] Specific operation: When a major earthquake occurs, the vibration sensor detects and records shaking of a seismic intensity of 6+. The humidity sensor also measures humidity levels of 90% or higher.

[1518] Step 3: Creating and sending a data package

[1519] The terminal processes the collected location information, damage situation data, and emotion data into a single data package. The inputs for this operation are location information, emotion data, and damage situation data, and the output is a data package.

[1520] Specific operation: The device combines location information, emotional data indicating high stress levels, and vibration sensor data into a single package.

[1521] The device sends data packages to the server via a mobile network or Wi-Fi. The input is the data package, and the output is a notification of successful transmission.

[1522] What it does: Encrypts the data package and sends it to a server over the mobile network.

[1523] Step 4: Receiving and analyzing data

[1524] The server receives the data package sent from the terminal. The input of this operation is the data package, and the output is the data to be analyzed.

[1525] Specific operation: The received data package is unzipped and each piece of data is extracted for analysis.

[1526] The server analyzes the location information using a geographic information system (GIS) and simultaneously evaluates the emotional data using an emotion engine. The inputs of this operation are location information and emotional data, and the output is the identification of the damage extent and the evaluation of the stress level.

[1527] Specific operation: Identifies the extent of building collapse based on location information in Shinjuku Ward and evaluates the user's stress level.

[1528] Step 5: Selecting a solution and responding emotionally

[1529] The server selects the optimal recovery solution based on the analysis results. The input of this operation is the analysis results, and the output is the recovery solution.

[1530] Specific operation: If a building collapse and communication failure are confirmed, a solution will be selected to restore communication by placing a drone base station.

[1531] The server selects a communication method according to the user's emotional state. The input of this operation is the emotional evaluation result, and the output is an emotional response plan.

[1532] Specific operation: Provide psychological care information to users with high stress levels.

[1533] Step 6: Create and send notifications

[1534] The server generates a notification based on the analysis results and the selected recovery solution. The inputs to this operation are the analysis results and the solution, and the output is the notification.

[1535] Specific operation: The system notifies the person in charge, "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy a drone base station to restore communications," and generates a message for the user saying, "The current situation is serious, but please rest assured, recovery work is underway."

[1536] The server then sends the created notification to the disaster response staff and the user. The input for this operation is the notification, and the output is a notification of successful transmission.

[1537] Specific operation: Sends notification text using messaging applications or SMS.

[1538] Through these steps, the system is able to quickly and accurately grasp the extent of the damage and provide optimal recovery solutions that take the user's feelings into consideration.

[1539] (Application example 2)

[1540] 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."

[1541] In disasters and emergencies, it is important to quickly and accurately grasp the damage situation and respond effectively to recovery. However, conventional systems do not take the user's emotional state into consideration when communicating. Furthermore, there is a lack of means to analyze the user's emotional data in real time and provide appropriate responses based on that analysis. Therefore, there is a need for the development of a system that provides quick and effective response measures while reducing the psychological burden on users in emergencies.

[1542] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1543] In this invention, the server includes means for acquiring location information and emotion data, means for generating and transmitting a data package of the damage situation and emotion data, means for analyzing the transmitted data package and selecting an optimal recovery solution, and means for generating and transmitting notification content taking the user's emotion data into consideration, thereby enabling a quick and accurate understanding of the damage situation and effective recovery measures that take the user's emotional state into consideration.

[1544] "Means for acquiring location information" refers to a device or software that receives signals from satellites or ground landmarks to acquire latitude and longitude data in order to identify the user's current location.

[1545] "Means for collecting damage information when a disaster occurs" refers to equipment or software that uses multiple sensors and devices to collect damage information such as building damage and earthquake intensity when a disaster occurs.

[1546] The "means for generating and transmitting a data package" refers to a device or software that assembles the collected location information, damage situation data, and emotion data into a single information packet and transmits it to a server.

[1547] The "means for selecting the optimal recovery solution" is a device or software that analyzes the transmitted data and determines the optimal recovery method or measures based on the extent of the damage and the user's emotional state.

[1548] The "means for recognizing and analyzing user emotional data" refers to a device or software for analyzing the user's voice and facial expressions and determining their emotional state.

[1549] The "means for generating and transmitting notification content" refers to a device or software that generates a notification with appropriate content based on the damage situation and the user's emotions, and transmits it to the user and disaster response personnel.

[1550] The Global Positioning System (GPS) is a system that uses satellites to calculate specific geographic locations and obtain user location information.

[1551] "Multiple built-in sensors" refers to a group of sensors built into a device that collect various environmental information such as vibration, humidity, and temperature.

[1552] A "geographic information system (GIS)" is software for managing, analyzing, and visually displaying geographic data.

[1553] This invention is a system that not only quickly and accurately grasps the damage situation when a disaster occurs and provides optimal recovery solutions, but also recognizes the user's emotional state and takes this into consideration when responding. This system is mainly composed of terminals and a server, and each terminal collects location information and emotional data, which the server analyzes and provides appropriate responses.

[1554] System Configuration

[1555] Terminal

[1556] Hardware

[1557] Mobile communication devices such as smartphones

[1558] Built-in GPS module

[1559] Multiple built-in sensors (vibration sensor, humidity sensor, temperature sensor, etc.)

[1560] Camera and microphone

[1561] software

[1562] Location information acquisition module

[1563] Emotion analysis module (performs voice analysis and facial expression analysis)

[1564] Data package generation and transmission module

[1565] server

[1566] Hardware

[1567] High-performance computers

[1568] software

[1569] Data Receiving Module

[1570] Data analysis module (including a geographic information system (GIS) and sentiment analysis engine)

[1571] Restoration Solution Selection Module

[1572] Notification Generation and Sending Module

[1573] Processing steps

[1574] Location and emotion data acquisition

[1575] The device periodically obtains the user's location information using a GPS module. It also uses a camera and microphone to analyze the user's voice and facial expressions to collect emotional data. This allows the device to obtain the user's latitude (35.6938 degrees) and longitude (139.7034 degrees) if the user is in Tokyo, and simultaneously analyze the user's stress level.

[1576] Collecting information on damage

[1577] When a disaster occurs, the device uses its built-in sensors to collect information on the damage situation. For example, if a major earthquake occurs, the vibration sensor will detect strong shaking and record that data.

[1578] Creating and sending data packages

[1579] The device compiles location information, damage situation data, and emotion data into a single data package and sends it to a server via a mobile network or Wi-Fi.

[1580] Data reception and analysis

[1581] The server receives the data packages sent from the devices and analyzes the extent and scale of the damage, as well as the user's emotional state. It uses a geographic information system (GIS) to analyze the impact of building collapses and earthquakes in a specific area, while simultaneously using an emotion engine to assess the user's stress level.

[1582] Solution selection and emotional response

[1583] The server selects the optimal recovery solution based on the analysis results. It also considers the user's emotional data to select the optimal communication method. For example, if the communications infrastructure is severely damaged, it will use drone base stations to ensure communications. Meanwhile, it will provide psychological care information to users experiencing high levels of stress.

[1584] Creating and sending notifications

[1585] The server creates a notification containing the analysis results and the selected recovery solution, and sends it to disaster response personnel and the appropriate users. The notification to users is sensitive to their emotions. For example, disaster response personnel might be notified that "A large-scale building collapse has been confirmed in Shinjuku Ward. We will deploy drone base stations to restore communications," while users might be notified with a message that provides reassurance, such as "The current situation is serious, but please rest assured that recovery work is underway."

[1586] Adding specific examples

[1587] Example 1: Obtaining location and emotion data

[1588] Example prompt:

[1589] "Collect audio data to analyze the user's stress level and obtain latitude and longitude location information."

[1590] Example 2: Anomaly detection and response

[1591] Example prompt:

[1592] "If the user is in a state of extreme stress, contact the police and notify the user."

[1593] In this way, the system of the present invention makes it possible to quickly and accurately grasp the extent of damage and to take effective recovery measures while taking into consideration the emotional state of the user.

[1594] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1595] Step 1:

[1596] The device periodically obtains the user's location information using a GPS module. The input data is signals obtained from satellites, and the device calculates the latitude and longitude based on this. The output data is the user's current location information (e.g., latitude 35.6938 degrees, longitude 139.7034 degrees).

[1597] Step 2:

[1598] The device uses a camera and microphone to collect the user's voice and facial expressions. The input data is the user's facial image captured by the camera and the voice data recorded by the microphone. This data is input into an emotion analysis module to analyze the user's stress level and emotional state. The output data is the user's emotional data (e.g., high stress level).

[1599] Step 3:

[1600] The device constantly monitors the surrounding situation using built-in sensors (e.g., vibration sensor, humidity sensor). When a disaster occurs, these sensors collect data on the damage situation. The input data is shaking intensity data from the vibration sensor and humidity data from the humidity sensor. The output data is damage situation data (e.g., strong shaking, humidity changes).

[1601] Step 4:

[1602] The device compiles the obtained location information, emotion data, and damage situation data into a single data package. The input data is the information obtained at each step (location information, emotion data, damage situation data). The output data is the compiled data package.

[1603] Step 5:

[1604] The terminal transmits the generated data package to the server using a mobile network or Wi-Fi. The input data is the data package, and the output data is the data package received by the server.

[1605] Step 6:

[1606] The server analyzes the received data package. The input data is the data package sent from the device, and it analyzes it using a geographic information system (GIS) and an emotion analysis engine. The output data is the range and scale of the damage, as well as evaluation information on the user's emotional state.

[1607] Step 7:

[1608] The server selects the optimal recovery solution based on the analysis results. The input data are the analysis results, and based on these, the optimal recovery method (e.g., the placement of drone base stations or the provision of psychological care information) is determined. The output data is the selected recovery solution.

[1609] Step 8:

[1610] The server creates a notification containing the selected recovery solution and the analysis results, and sends it to disaster response personnel and appropriate users. The input data are the recovery solution and the analysis results, and the output data is the configured notification content.

[1611] Step 9:

[1612] The user can receive notifications from the server and feel secure. The input data is the notification sent from the server, and the output data is the user's sense of security.

[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 means for acquiring location information;

[1637] A means of collecting information on damage when a disaster occurs,

[1638] A means for transmitting the collected location information and damage situation;

[1639] A means to analyze the transmitted location information and damage situation and select the optimal recovery solution;

[1640] A means of communicating the analysis results and selected recovery solutions to disaster response personnel; and

[1641] A system including:

[1642] (Claim 2)

[1643] The means of obtaining location information is the Global Positioning System (GPS),

[1644] The means for collecting information on damage in the event of a disaster includes multiple built-in sensors.

[1645] 10. The system of claim 1.

[1646] (Claim 3)

[1647] The means of selecting the most appropriate restoration solution includes analyzing the extent and scale of the damage using a geographic information system (GIS);

[1648] 10. The system of claim 1.

[1649] "Example 1"

[1650] (Claim 1)

[1651] A means for periodically acquiring user location information;

[1652] A means of collecting information on damage using built-in sensors in the event of a disaster, and

[1653] means for transmitting the collected location information and damage situation data via a network;

[1654] a means for receiving the transmitted location information and damage situation data and analyzing the extent and scale of the damage using a geographic information system (GIS);

[1655] A means to automatically select the optimal recovery solution based on the analysis results;

[1656] A means to notify disaster response personnel of the selected recovery solution and analysis results in real time,

[1657] A system including:

[1658] (Claim 2)

[1659] The system according to claim 1, wherein the means for periodically acquiring location information utilizes a global positioning system (GPS), and includes means for collecting damage information using multiple built-in sensors (such as vibration sensors and humidity sensors) when a disaster occurs.

[1660] (Claim 3)

[1661] 10. The system of claim 1, wherein the means for selecting an optimal restoration solution comprises placing autonomous quadrocopter drone base stations based on the scope and scale of the analysis.

[1662] "Application Example 1"

[1663] (Claim 1)

[1664] A means for acquiring location information;

[1665] A means of collecting information on damage when a disaster occurs,

[1666] A means for transmitting the collected location information and damage situation;

[1667] A means to analyze the transmitted location information and damage situation and select the optimal recovery solution;

[1668] A means of communicating the analysis results and selected recovery solutions to disaster response personnel; and

[1669] A means for collecting damage data using a smart device;

[1670] A system including:

[1671] (Claim 2)

[1672] The means of obtaining location information is the Global Positioning System (GPS),

[1673] The means for collecting information on damage in the event of a disaster includes multiple built-in sensors.

[1674] The smart device includes smart glasses and a smartphone.

[1675] 10. The system of claim 1.

[1676] (Claim 3)

[1677] The means of selecting the most appropriate restoration solution includes analyzing the extent and scale of the damage using a geographic information system (GIS);

[1678] When generating analysis results, prompt sentences are used to input into the generative AI model.

[1679] 10. The system of claim 1.

[1680] "Example 2: Combining Emotion Engines"

[1681] (Claim 1)

[1682] means for acquiring location information and emotion data;

[1683] A means of collecting information on damage when a disaster occurs,

[1684] A means for transmitting the collected location information, emotion data, and damage situation;

[1685] A means of analyzing the transmitted location information, emotional data, and damage situation to select the optimal recovery solution;

[1686] A means of communicating the analysis results and selected recovery solutions to disaster response personnel and users; and

[1687] A system including:

[1688] (Claim 2)

[1689] The means for acquiring location information and emotion data utilizes a global positioning system (GPS) and an emotion analysis engine;

[1690] The means for collecting information on damage in the event of a disaster includes multiple built-in sensors.

[1691] 10. The system of claim 1.

[1692] (Claim 3)

[1693] The method for selecting the optimal recovery solution includes analyzing the scope, scale, and emotional state of the damage using a geographic information system (GIS) and a sentiment analysis engine;

[1694] 10. The system of claim 1.

[1695] "Application example 2 when combining emotion engines"

[1696] (Claim 1)

[1697] A means for acquiring location information;

[1698] A means of collecting information on damage when a disaster occurs,

[1699] means for generating and transmitting a data package of the collected location information and damage situation;

[1700] A means of analyzing the transmitted location and damage data package and selecting the optimal recovery solution;

[1701] A means of communicating the analysis results and selected recovery solutions to disaster response personnel and applicable users; and

[1702] means for recognizing and analyzing user emotion data;

[1703] means for generating and transmitting notification content taking into account the user's emotion data;

[1704] A system including:

[1705] (Claim 2)

[1706] The means of obtaining location information is the Global Positioning System (GPS),

[1707] The means for collecting information on damage in the event of a disaster includes multiple built-in sensors.

[1708] 10. The system of claim 1.

[1709] (Claim 3)

[1710] The means of selecting the most appropriate restoration solution includes analyzing the extent and scale of the damage using a geographic information system (GIS);

[1711] 10. The system of claim 1. [Explanation of symbols]

[1712] 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 means for acquiring location information; A means of collecting information on damage when a disaster occurs, A means for transmitting the collected location information and damage situation; A means to analyze the transmitted location information and damage situation and select the optimal recovery solution; A means of communicating the analysis results and selected recovery solutions to disaster response personnel; and A system including:

2. The means for acquiring location information uses the Global Positioning System, The means for collecting information on damage in the event of a disaster includes multiple built-in sensors. The system of claim 1 .

3. The means of selecting the most appropriate recovery solution includes analyzing the extent and scale of the damage using geographic information systems; The system of claim 1 .

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