System

Abstract

To provide a system for quickly collecting and analyzing information in a disaster-stricken area, optimizing a rescue route and securing a communication infrastructure, and for achieving effective disaster countermeasures and rescue activities.SOLUTION: The system includes means for collecting video data in real time by causing a plurality of autonomous flying devices to fly to a designated disaster-stricken area when a disaster occurs, generative artificial intelligence means for analyzing the collected video data, means for calculating a rescue point and a safe rescue route on the basis of an analysis result and providing the rescue point and the safe rescue route to a rescue organization and a medical institution, means for temporarily securing a communication infrastructure of the disaster-stricken area by the autonomous flying devices, and means for specifying an unrescued point, maintaining public security, checking the health condition of a victim, and guiding the victim to an evacuation site.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, the frequent occurrence of natural disasters around the world has created a strong demand for rapid and efficient rescue operations. However, issues remain, such as the complexity of on-site assessment of disaster-stricken areas and the difficulty of obtaining information due to communication disruptions. The purpose of this invention is to solve these issues and achieve effective disaster response and rescue operations by quickly collecting and analyzing information in disaster-stricken areas, optimizing rescue routes, and securing communication infrastructure. [Means for solving the problem]

[0005] The present invention provides a system that includes, when a disaster occurs, a means for multiple autonomous flight devices to fly to a designated disaster area and collect video data in real time, a generating artificial intelligence means for analyzing the collected video data, a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions, a means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices, and a means for identifying unrescue points, maintaining public order, checking the health of victims, and guiding them to evacuation sites.

[0006] An "autonomous flying device" is an unmanned aerial vehicle that can automatically set a flight route using a positioning information system such as GPS, fly to a specified destination, and collect data.

[0007] "Real-time video data" means video and other data that is recorded and collected by an autonomous flying device in real time using cameras and sensors during flight.

[0008] "Generative AI" is a technology that analyzes collected data and automatically generates and provides information tailored to specific purposes.

[0009] A "rescue point" is a specific location within a disaster area where rescue operations are needed.

[0010] A "safe rescue route" is a travel route optimized for rescuing victims after a disaster occurs, and is set up to avoid obstacles and dangerous areas.

[0011] "Communications infrastructure" refers to the general equipment and technology that enables data communication, and plays a role in restoring communications that have been cut off in disaster-stricken areas.

[0012] An "unrescue point" is a location where rescue operations have not yet been carried out and which requires immediate assistance.

[0013] "Maintaining public order" refers to activities aimed at maintaining public order in disaster-stricken areas and preventing chaos and secondary disasters.

[0014] "Checking the health status of disaster victims" involves checking the physical condition and health status of people in the disaster area and providing medical assistance as needed.

[0015] An "evacuation site" is a place set up for disaster victims to safely evacuate and live temporarily. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones) with generative AI technology to carry out disaster relief activities quickly and efficiently. The system of the present invention mainly collects and analyzes information when a disaster occurs, optimizes rescue routes, secures communication infrastructure, and carries out rescue activities. The following describes the overall configuration of the system and the operation of each part.

[0038] System configuration

[0039] The system consists of four main parts:

[0040] 1. Information gathering devices (drones)

[0041] 2. Data analysis device (server)

[0042] 3. Server for linking with rescue and medical institutions

[0043] 4. Communication infrastructure securing device (drone)

[0044] Program for carrying out the invention

[0045] Drone launch and information gathering

[0046] When a disaster occurs, the server immediately sends instructions to launch a fleet of drones. The drones begin flying toward the designated disaster area and collect video and sensor data in real time. This data is then sent from the drones to the server. For example, if a major earthquake occurs, the server sends the coordinates of the disaster area to the drones, who then depart for that location.

[0047] Real-time data analysis and rescue route calculation

[0048] The server receives real-time video data sent from the drone and passes it to the generation AI for analysis. The generation AI analyzes the damage situation in detail and extracts important information such as the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions. As a specific example, the server identifies the building with the most damage among multiple collapsed buildings and provides rescue teams with safe routes around it.

[0049] Calculating necessary supplies

[0050] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drone for delivering the supplies. For example, it calculates the amount of food, water, and medicine needed based on the number and health condition of the victims gathered at evacuation centers and sends this information to the delivery drone.

[0051] Securing communications infrastructure and relief efforts

[0052] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points. This will restore data communications within the affected area and maintain connections with servers and relief organizations. As a specific example, a communications relay drone will fly over a disaster-stricken area where communications have been cut off, maintaining its altitude to provide communications signals.

[0053] Implementing and following up on relief efforts

[0054] Identifying unrescue locations, checking the health of victims, and maintaining public order are also important functions of this system. Based on the analysis results of the generated AI, the server identifies unrescue locations and directs a group of drones to carry out rescue operations. It also checks the health of victims and provides necessary medical assistance. As a specific example, drones fly over the affected area, remotely measuring the body temperature and heart rate of victims, and immediately dispatching rescue teams to victims in urgent need.

[0055] With such a system configuration and operation, the present invention can realize rapid and effective rescue operations in the event of a disaster.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] Server: Upon receiving information about a disaster, it immediately launches multiple drones and sends them commands to fly towards the designated disaster area.

[0059] Example: An earthquake occurs and the server sends a departure command to each drone.

[0060] Step 2:

[0061] Drones: Fly to designated disaster areas to collect real-time video and sensor data. The drones perform a series of flight patterns to ensure comprehensive coverage of the disaster area.

[0062] Example: Drones can capture images of debris and road damage from the sky, and temperature sensors can detect fires.

[0063] Step 3:

[0064] Drone: Collected video and sensor data is sent to a server via 4G / 5G networks or dedicated wireless communication protocols.

[0065] Example: A drone uploads data to a server in real time.

[0066] Step 4:

[0067] Server: Passes the received data to the generation AI, which analyzes the damage situation in detail. The generation AI uses image recognition technology to identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources, and extracts important information.

[0068] Example: Generative AI analyzes video footage and displays the coordinates of collapsed buildings and fire sites on a map.

[0069] Step 5:

[0070] Server: Based on the analysis results of the generation AI, it calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions.

[0071] Example: The server identifies the most affected areas and sends their coordinates and rescue routes to rescue teams.

[0072] Step 6:

[0073] Server: Analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to drones delivering supplies.

[0074] Example: Calculate the amount of food, water, and medicine needed at a shelter and communicate that information to a delivery drone.

[0075] Step 7:

[0076] Drones: Drones equipped with communication capabilities will fly to designated locations and establish temporary communication relay points, thereby temporarily restoring communication infrastructure in the affected areas.

[0077] Example: A communications drone hovers over the affected area and provides a communications signal.

[0078] Step 8:

[0079] Server: Based on the analysis results of the generated AI and real-time data, it identifies unrescue locations and directs a group of drones to carry out rescue operations.

[0080] Example: A drone continuously collects images of unrescue areas identified by the server and updates the information.

[0081] Step 9:

[0082] Drones: Guide victims to safe evacuation sites and deliver necessary emergency supplies. They may also use voice guidance and LED displays to show the route.

[0083] Example: The drone will provide voice guidance to indicate evacuation routes and use LED lights to show evacuation routes even at night.

[0084] This will enable the system to carry out rapid and effective disaster relief efforts in affected areas.

[0085] Example 1

[0086] 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."

[0087] Conventional disaster relief systems had the problem of making it difficult to carry out relief activities quickly and efficiently, resulting in the time it took to rescue victims. Furthermore, due to insufficient understanding of the situation in the affected areas and insufficient communication infrastructure, the transmission of information regarding relief activities was often delayed. Furthermore, due to a lack of means to accurately grasp the amount and type of supplies needed, the supply of supplies was delayed, and in some cases appropriate support was not provided in line with the needs of the victims.

[0088] 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.

[0089] In this invention, the server includes means for flying multiple autonomous flight devices to designated disaster areas and collecting video data and environmental data in real time, a generating artificial intelligence means for analyzing the collected video data and environmental data, a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions, a means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices, and a means for identifying unrescue points, maintaining public order, checking the health of victims, guiding them to evacuation sites, and calculating and issuing transport instructions for necessary supplies. This enables rapid and efficient rescue operations, understanding the situation in the disaster area, securing communication infrastructure, and supplying appropriate supplies.

[0090] An "autonomous flying device" is an unmanned aerial vehicle that can fly by remote control or automatic control.

[0091] "Video data" refers to visual information collected by a video capture device such as a camera or video recorder.

[0092] "Environmental data" is data obtained from sensors that measure environmental parameters such as temperature, humidity, gas concentration, and radiation levels.

[0093] "Generative artificial intelligence means" refers to an artificial intelligence system that has the ability to analyze large amounts of data and automatically generate specific patterns or information.

[0094] "Rescue point" refers to a location within a disaster area where rescue is particularly needed.

[0095] A "rescue route" refers to a route that can be traveled safely and efficiently when carrying out rescue operations.

[0096] "Communications infrastructure" refers to the entire hardware and software that make up a communications network.

[0097] A "communication relay point" is a base that relays communication signals, and is a point that is installed to expand the communication range or to deal with sudden communication interruptions.

[0098] "Unrescue points" refer to locations within the disaster area where rescue efforts have not yet begun.

[0099] "Maintaining public order" refers to activities to ensure safety and maintain order at the scene of a disaster.

[0100] "Health assessment of disaster victims" is the process of assessing the physical condition and medical condition of disaster victims and determining the medical assistance they require.

[0101] An "evacuation site" refers to a safe place designated for temporary evacuation of disaster victims in the event of a disaster.

[0102] "Necessary supplies" refers to basic necessities such as food, water, and medicine that disaster victims need during relief efforts.

[0103] A "materials transport order" is an order to transport needed materials to a specific location.

[0104] "Real-time" refers to data being processed and used as soon as it is generated.

[0105] This invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones) with generative AI technology to carry out disaster relief activities quickly and efficiently. The system of this invention mainly collects and analyzes information when a disaster occurs, calculates rescue routes, secures communication infrastructure, and carries out relief activities.

[0106] System configuration

[0107] The system consists of four main parts:

[0108] 1. Information gathering devices (drones)

[0109] 2. Data analysis device (server)

[0110] 3. Server for linking with rescue and medical institutions

[0111] 4. Communication infrastructure securing device (drone)

[0112] Drone launch and information gathering

[0113] When a disaster occurs, the server immediately sends instructions to activate a fleet of drones, which begin flying toward the designated disaster area and collecting real-time video and sensor data, which is then transmitted from the drones to the server.

[0114] Examples:

[0115] In the event of a major earthquake, the server will send coordinate information of the affected area to the drone, and the drone will then depart for that location.

[0116] Real-time data analysis and rescue route calculation

[0117] The server receives real-time video data sent from the drone and passes it to the AI ​​generator for analysis. The AI ​​generator performs a detailed analysis of the damage situation and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions.

[0118] Examples:

[0119] The server identifies the building that suffered the most damage among several collapsed buildings and provides rescue teams with safe routes around it.

[0120] Calculating necessary supplies

[0121] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drones for delivering the supplies.

[0122] Examples:

[0123] Taking into account the number of disaster victims gathered at the evacuation center and their health condition, the system calculates the amount of food, water, and medicine needed and transmits this information to the transport drone.

[0124] Securing communications infrastructure and relief efforts

[0125] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points, restoring data communications within the affected area and maintaining connections with servers and relief organizations.

[0126] Examples:

[0127] Communication relay drones fly over disaster-stricken areas where communications have been cut off, maintaining altitude to provide communication signals.

[0128] Implementing and following up on relief efforts

[0129] Identifying unrescue locations, checking the health of victims, and maintaining public order are also important functions of this system. Based on the analysis results of the generated AI, the server identifies unrescue locations and directs drones to carry out rescue operations. It also checks the health of victims and provides necessary medical assistance.

[0130] Examples:

[0131] The drones fly over the affected areas, remotely measuring the body temperature and heart rate of victims, and rescue teams are immediately dispatched to those in urgent need.

[0132] Prompt Sentence Examples

[0133] Here are some examples of specific prompts for a generative AI model:

[0134] 1. Prompt for analyzing video data from the disaster area:

[0135] Next, analyze the video data provided to determine the number of collapsed buildings, the location of victims, and whether there were any fires or heat sources.

[0136] 2. Prompt to assess the victim's health:

[0137] Please use the following sensor data to measure the victim's body temperature and heart rate and identify those in need of emergency assistance.

[0138] With this system configuration and specific operation, the present invention can realize rapid and effective rescue operations in the event of a disaster.

[0139] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0140] Step 1:

[0141] The server that detects the occurrence of a disaster sends an instruction to activate the drones.

[0142] Input: Disaster occurrence detection data (e.g., earthquake occurrence notification)

[0143] Data processing / calculation: The server obtains coordinate data of the disaster site and executes the drone activation protocol.

[0144] Output: Commands to launch drones and coordinates of the affected area

[0145] Specific behavior:

[0146] The server automatically receives notification of a disaster and sends the coordinates of the affected area to the drone, which then prepares to fly to the specified location.

[0147] Step 2:

[0148] Based on the transmitted coordinate information, the drone begins flying toward the affected area and collects video and sensor data in real time.

[0149] Input: Coordinate information of affected area

[0150] Data processing / computation: The drone activates its cameras and sensors to collect video and environmental data of the designated area.

[0151] Output: Collected video and sensor data

[0152] Specific behavior:

[0153] The drone flies to specified coordinates, captures real-time footage with a high-resolution camera, and uses sensors to measure environmental data such as temperature and gas concentrations.

[0154] Step 3:

[0155] The collected data is sent to the server in real time.

[0156] Input: Video and sensor data

[0157] Data processing / calculation: The drone transmits the collected data to a server via wireless communication.

[0158] Output: Video data and sensor data uploaded to the server

[0159] Specific behavior:

[0160] The drone wirelessly transmits real-time video and sensor data to a server, which then receives the data.

[0161] Step 4:

[0162] The server passes the received data to the generative AI model for analysis.

[0163] Input: Video data and sensor data sent to the server

[0164] Data processing / calculation: A generative AI model analyzes the data and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fire or heat sources.

[0165] Output: Analysis results of the damage situation

[0166] Specific behavior:

[0167] The server inputs the received data into a generative AI model, and the AI ​​analyzes the data to gain a detailed understanding of the situation in the affected areas.

[0168] Step 5:

[0169] The server calculates the optimal rescue point and safe rescue route based on the analysis results of the generated AI model.

[0170] Input: Analysis results of the damage situation

[0171] Data processing / calculation: The server runs an algorithm based on the analysis results to calculate the optimal rescue point and safe route.

[0172] Output: Rescue location and rescue route information

[0173] Specific behavior:

[0174] The server calculates safe and efficient rescue routes based on the locations of collapsed buildings and victims, and provides them to rescue agencies.

[0175] Step 6:

[0176] The server analyzes detailed data on the affected area and calculates the types and quantities of medical supplies and relief goods needed.

[0177] Input: Detailed data of the affected area

[0178] Data processing / calculation: The server analyzes the number of people, their health status, and the damage situation, and determines the type and amount of supplies needed.

[0179] Output: List of required supplies

[0180] Specific behavior:

[0181] The server calculates and lists the quantities of food, water, and medicine needed based on data on disaster victims gathered at evacuation centers.

[0182] Step 7:

[0183] The server sends instructions to the drone on the route to transport the necessary supplies.

[0184] Input: List of required supplies and destination coordinates

[0185] Data processing / calculation: The server calculates the optimal route for transporting supplies and sends those instructions to the drone.

[0186] Output: Delivery route instructions for drone

[0187] Specific behavior:

[0188] The server indicates to the drone the specific flight route to carry the necessary supplies, and the drone then transports the supplies along that route.

[0189] Step 8:

[0190] If communication infrastructure is destroyed, drones equipped with communication capabilities will move to designated locations and function as communication relay points.

[0191] Input: Communication status data for affected areas

[0192] Data processing / calculation: The server identifies the area where communication has been lost and instructs the communication drone to move to that area.

[0193] Output: Communication infrastructure restored

[0194] Specific behavior:

[0195] Based on instructions from the server, drones equipped with communication capabilities will provide communication relay points over the affected area, temporarily restoring the communication network.

[0196] Step 9:

[0197] Based on the analysis results of the generated AI model, the server identifies unrescue locations and instructs a group of drones to carry out rescue operations.

[0198] Input: Analysis results of the generative AI model

[0199] Data processing / calculation: The server identifies unrescue locations that require rescue operations and issues instructions to the drones.

[0200] Output: Rescue operation instructions

[0201] Specific behavior:

[0202] The drones will fly to unrescue locations, remotely measure the temperature and heart rate of victims, and provide necessary medical assistance.

[0203] The above are the specific processing steps and detailed operations in the system program.

[0204] (Application example 1)

[0205] 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."

[0206] Conventional disaster relief systems have had difficulty quickly and efficiently grasping the situation in disaster-stricken areas and taking appropriate action. They also have issues with delays in sharing information and issuing instructions for rescue operations when communication infrastructure is destroyed. Furthermore, even with standard security monitoring, anomaly detection is not performed in real time, making it difficult to respond quickly.

[0207] 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.

[0208] In this invention, the server includes a means for flying the autonomous flight device to a designated disaster area and collecting video data in real time, a generating artificial intelligence means for analyzing the collected video data, and a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions. This makes it possible to quickly collect and analyze information in the event of a disaster and provide optimal rescue routes.

[0209] Furthermore, it includes a means for temporarily securing communication infrastructure in disaster-stricken areas using autonomous flight devices, and a means for identifying unrescue locations, maintaining public order, checking the health of disaster victims, and guiding them to evacuation sites. This allows for the continuation of information sharing and instructions for rescue operations even if communication infrastructure is destroyed.

[0210] In addition, it includes a means for collecting security monitoring data in real time during operation, detecting anomalies using a generative AI model, and a means for securing communication relay points even in areas with unstable communication infrastructure based on the detection results, which enables rapid anomaly detection and response even in normal security monitoring.

[0211] An "autonomous flight device" is an unmanned aerial vehicle that flies autonomously according to pre-programmed instructions and collects video and sensor data.

[0212] "Generative AI" is an artificial intelligence technology that analyzes collected data and generates and provides necessary information.

[0213] A "rescue route" is a route optimized for safe and rapid rescue operations.

[0214] "Sensor data" refers to physical data such as temperature, humidity, vibration, and pressure obtained from drones and other sensor devices.

[0215] "Anomaly detection" is the process of detecting abnormal situations or behaviors that deviate from normal conditions.

[0216] "Telecommunications infrastructure" refers to the physical and software systems that create telecommunications networks and enable the transmission and reception of data.

[0217] A "communication relay point" is an intermediate point that temporarily relays communications in an area where communications have been cut off, ensuring network connectivity.

[0218] A "generative AI model" is a type of artificial intelligence that generates new information and data patterns based on large amounts of data.

[0219] A "prompt sentence" is an input sentence used to give instructions to a generative AI model.

[0220] "Security surveillance data" refers to video, audio, sensor, and other data collected in real time to ensure the safety of a specific area.

[0221] "Disaster situation" refers to the state of damage in the area where the disaster occurred, including the number of collapsed buildings, the location of victims, and the presence or absence of fires or heat sources.

[0222] An "embodiment" is a form showing how the invention is specifically carried out.

[0223] This invention is a system that combines autonomous flight devices (drones) and generative AI technology to realize rapid and efficient rescue operations in the event of a disaster. The main components of this system are as follows:

[0224] System configuration

[0225] 1. Autonomous flying devices (drones)

[0226] 2. Generative artificial intelligence (AI) means

[0227] 3. Rescue route calculation method

[0228] 4. Measures to secure communications infrastructure

[0229] 5. Anomaly detection and notification methods

[0230] System Operation

[0231] Drone launch and information gathering

[0232] When a disaster occurs, the server immediately activates an autonomous flying device (drone) and has it fly toward the designated disaster area. The drone collects video and sensor data in real time and transmits the data to the server. In particular, the drone uses advanced sensor technology (temperature sensors, humidity sensors, etc.) to collect detailed data.

[0233] Real-time data analysis and rescue route calculation

[0234] The server passes the real-time video and sensor data transmitted from the drone to a generative AI model for analysis. Examples of generative AI models include OpenAI's GPT-4. This AI analyzes the collected data and identifies the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. It then calculates the optimal rescue points and safe rescue routes and provides this information to rescue organizations and medical institutions.

[0235] Calculation and instructions for necessary supplies

[0236] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drones for delivering the supplies. Selecting the appropriate route enables the rapid and efficient delivery of supplies.

[0237] Securing communication infrastructure

[0238] If communications infrastructure is destroyed, drones equipped with communications capabilities will move to designated locations and establish temporary communications relay points. Specifically, the drones will maintain altitude and transmit communications signals to support communications at the scene. This will restore data communications within the disaster area and maintain communication with servers and relief organizations.

[0239] Security monitoring and anomaly detection

[0240] Under normal circumstances, drones collect security monitoring data and use generative AI models to detect anomalies in real time. The analysis results are then immediately communicated to security personnel. Even in areas with unstable communications infrastructure, drones can function as communication relay points, ensuring stable data communication.

[0241] Specific examples

[0242] During nighttime security surveillance at a large commercial facility, if a drone detects a suspicious person entering the facility in real time, by inputting the prompt "Anomaly detection: Analyze video data, detect and report any anomalies" into the generative AI model, details of the anomaly will be immediately sent to the server. As a result, security personnel will receive an immediate notification of the anomaly via their smartphone or smart glasses, enabling them to respond promptly.

[0243] As described above, this system can be applied not only during disasters but also to normal security monitoring, enabling rapid and efficient responses through real-time data collection and analysis using generative AI.

[0244] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0245] Step 1:

[0246] When a disaster occurs, the server immediately activates an autonomous flying device (drone) and sends it off to the designated disaster area. The drone collects video and sensor data in real time. The input is coordinate information of the disaster area, and the output is real-time video and sensor data.

[0247] Step 2:

[0248] The collected video and sensor data is sent to a server, which receives the data and passes it to a generative AI model. The input is real-time video and sensor data, and the output is data that is analyzed by the generative AI model.

[0249] Step 3:

[0250] The server analyzes the collected data using a generative AI model. Specifically, the AI ​​model receives prompts to "analyze the damage situation, identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources," and obtains analysis results. This analysis includes pattern recognition in video and anomaly detection in sensor data. The inputs are prompts and raw data for the AI ​​model, and the output is the analysis results.

[0251] Step 4:

[0252] Based on the analysis results, the server calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions. The input is the analysis results, and the output is optimized rescue route information. Specifically, a route search algorithm is used to calculate the shortest and safest route.

[0253] Step 5:

[0254] The server calculates the type and amount of medical supplies and relief supplies needed and sends route instructions to the drones for delivering the supplies. The input is the number of people in the disaster area and health data, and the output is the delivery route and a list of supplies. A supply supply algorithm determines the amount of supplies needed at each location.

[0255] Step 6:

[0256] If communications infrastructure is destroyed, drones act as communication relay points to establish a temporary communications infrastructure. The input is the coordinate information of the communication-disrupted area, and the output is the area where a constant communication connection is ensured. Communications are stabilized using LoRa networks and other mesh network technologies.

[0257] Step 7:

[0258] Under normal circumstances, drones collect security surveillance data and use generative AI models to detect anomalies in real time. The results are then notified to security personnel. The input is real-time surveillance data, and the output is anomaly detection results and notification information. A specific prompt, "Anomaly detection: Analyze video data, detect anomalies, and report them," is used to prompt the AI ​​to perform analysis.

[0259] By combining these processing steps, this system enables multifunctional and highly efficient operations during disasters and normal security activities.

[0260] 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.

[0261] This invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones), generative AI technology, and an emotion engine to carry out disaster relief activities quickly and efficiently. The system of this invention collects and analyzes information when a disaster occurs, optimizes rescue routes, secures communication infrastructure, and provides psychological support through emotion analysis. The following describes the overall configuration of the system and the operation of each component.

[0262] System configuration

[0263] The system consists of five main parts:

[0264] 1. Information gathering devices (drones)

[0265] 2. Data analysis device (server)

[0266] 3. Emotion Engine

[0267] 4. Server for linking with rescue and medical institutions

[0268] 5. Communication infrastructure securing device (drone)

[0269] Program for carrying out the invention

[0270] Drone launch and information gathering

[0271] When a disaster occurs, the server immediately sends instructions to launch a fleet of drones. The drones begin flying toward the designated disaster area and collect video and sensor data in real time. This data is then sent from the drones to the server. For example, if a major earthquake occurs, the server sends the coordinates of the disaster area to the drones, who then depart for that location.

[0272] Real-time data analysis and rescue route calculation

[0273] The server receives real-time video data sent from the drone and passes it to the generation AI for analysis. The generation AI analyzes the damage situation in detail and extracts important information such as the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions. As a specific example, the server identifies the building with the most damage among multiple collapsed buildings and provides rescue teams with safe routes around it.

[0274] Calculating necessary supplies

[0275] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drone for delivering the supplies. For example, it calculates the amount of food, water, and medicine needed based on the number and health condition of the victims gathered at evacuation centers and sends this information to the delivery drone.

[0276] Securing communications infrastructure and relief efforts

[0277] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points. This will restore data communications within the affected area and maintain connections with servers and relief organizations. As a specific example, a communications relay drone will fly over a disaster-stricken area where communications have been cut off, maintaining its altitude to provide communications signals.

[0278] Emotion analysis and psychological support using an emotion engine

[0279] The server uses an emotion engine to analyze the facial expression data of victims collected by the drone and identify their emotional state. Based on the emotion engine's analysis results, it notifies rescue organizations and medical institutions of locations where psychological support is needed. In addition, even after communication infrastructure is restored, it continues to monitor the emotional state of victims in evacuation centers in real time, and notifies medical institutions if it detects abnormal stress or anxiety. For example, if a victim in an evacuation center becomes extremely anxious or panics, this information is quickly conveyed to the medical team, and the necessary support is provided.

[0280] With such a system configuration and operation, the present invention can realize rapid and effective relief activities in disaster areas and psychological care for disaster victims.

[0281] The processing flow will be explained below.

[0282] Step 1:

[0283] Server: Upon receiving information about a disaster, it immediately launches multiple drones and sends them commands to fly towards the designated disaster area.

[0284] Example: An earthquake occurs and the server sends a departure command to each drone.

[0285] Step 2:

[0286] Drones: Fly to designated disaster areas and collect real-time video and sensor data. Drones follow pre-set flight patterns to collect data over a wide area.

[0287] Example: Drones can capture images of debris and road damage from the sky, and temperature sensors can detect fires.

[0288] Step 3:

[0289] Drone: Collected video and sensor data is sent to a server via 4G / 5G networks or dedicated wireless communication protocols.

[0290] Example: A drone uploads data to a server in real time.

[0291] Step 4:

[0292] Server: Passes the received data to the generation AI, which analyzes the damage situation in detail. The generation AI uses image recognition technology to identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources, and extracts important information.

[0293] Example: Generative AI analyzes video footage and displays the coordinates of collapsed buildings and fire sites on a map.

[0294] Step 5:

[0295] Server: Based on the analysis results of the generation AI, it calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions.

[0296] Example: The server identifies the most affected areas and sends their coordinates and rescue routes to rescue teams.

[0297] Step 6:

[0298] Server: Analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to drones delivering supplies.

[0299] Example: Calculate the amount of food, water, and medicine needed at a shelter and communicate that information to a delivery drone.

[0300] Step 7:

[0301] Drones: Drones equipped with communication capabilities will fly to designated locations and establish temporary communication relay points, thereby temporarily restoring communication infrastructure in the affected areas.

[0302] Example: A communications drone hovers over the affected area and provides a communications signal.

[0303] Step 8:

[0304] Server: The emotion engine analyzes the facial expression data collected by the drone and identifies the emotional state of the victim. The emotion engine reads emotions such as anxiety, fear, and sadness from facial expressions.

[0305] Example: The emotion engine analyzes the facial expression data of a victim and determines that the victim is in a "high stress state."

[0306] Step 9:

[0307] Server: Based on the analysis results of the emotion engine, it notifies rescue organizations of locations where psychological assistance is needed, allowing psychological counseling and emergency psychological assistance to be provided promptly.

[0308] Example: The server sends an instruction to dispatch a psychological counselor to an evacuation site determined to be in a "high stress state."

[0309] Step 10:

[0310] Server: Even after the communication infrastructure is restored, the server monitors the emotional state of disaster victims in evacuation shelters in real time, and notifies medical institutions if it detects abnormal stress or anxiety.

[0311] Example: A server continuously monitors the emotional state of disaster victims in evacuation centers and sends an alert to medical teams if any abnormalities are detected.

[0312] Each processing step of this system enables rapid information gathering in disaster areas, ensuring the safety of victims, efficiently distributing relief supplies, and providing psychological care to victims.

[0313] Example 2

[0314] 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."

[0315] Conventional disaster relief systems have had problems with the collection and analysis of information, securing communication infrastructure, and providing psychological support to victims in a timely and efficient manner. Furthermore, the calculation and transportation of necessary supplies was ineffective, resulting in delayed responses to disaster victims.

[0316] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for flying multiple autonomous flight devices to a designated disaster area when a disaster occurs and collecting video data and sensor data in real time; a generating artificial intelligence means for analyzing the collected video data and sensor data; means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions; means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices; means for analyzing situation data in the disaster area to calculate the type and amount of supplies needed and sending route instructions to an autonomous flight device for delivery; and means for analyzing facial expression data of victims collected by the autonomous flight devices, identifying their emotional states, and providing psychological support. This enables rapid and efficient information collection and analysis, securing communication infrastructure, calculating and delivering needed supplies, and providing psychological support to victims.

[0317] A "disaster" is an abnormal phenomenon caused by natural phenomena or human factors that results in human injury or property damage.

[0318] An "autonomous flying device" is a device that performs a designated mission while flying itself based on pre-programmed instructions or instructions received in real time.

[0319] "Real-time" refers to situations in which data is collected and processed virtually immediately.

[0320] "Video data" refers to visual information acquired by a camera or other optical means.

[0321] "Sensor data" refers to data collected by a sensor that represents changes in physical quantities. Specifically, it includes information on temperature, humidity, air pressure, gas concentration, etc.

[0322] "Generative AI means" refers to a method or device that uses generative AI technology to analyze input data and extract and generate useful information.

[0323] "Rescue point" refers to a specific location within a disaster area where rescue operations should be carried out.

[0324] A "rescue route" refers to the optimal route for rescue teams to reach the rescue point safely and quickly.

[0325] "Communications infrastructure" refers to the hardware and software infrastructure required to conduct data communications.

[0326] "Supplies" refers to basic necessities and relief supplies such as food, medicine, and clothing needed to support disaster victims.

[0327] "Facial expression data" is data that captures a person's facial expressions and records their features and changes.

[0328] "Emotional state" refers to the results of analyzing and identifying the psychological reactions and emotional state of victims.

[0329] "Psychological support" refers to interventions and support activities aimed at reducing psychological stress and anxiety among disaster victims and supporting their mental health.

[0330] The system of the present invention combines multiple autonomous flying devices (hereinafter referred to as drones), generative artificial intelligence technology (generative AI model), and an emotion engine to realize rapid and efficient rescue operations in the event of a disaster. The system operates based on the following main components and their interactions:

[0331] System configuration

[0332] The system consists of five main parts:

[0333] 1. Information gathering devices (drones)

[0334] 2. Data analysis device (server)

[0335] 3. Emotion Engine

[0336] 4. Server for linking with rescue and medical institutions

[0337] 5. Communication infrastructure securing device (drone)

[0338] Information gathering device

[0339] In the event of a disaster, the server launches a fleet of drones and sends them to the affected area. The drones collect video and sensor data in real time and transmit that data to the server. For example, in the event of a major earthquake, the server sends coordinate information of the affected area to the drones, which then fly to that location and transmit the collected video and sensor data in real time.

[0340] Data analysis equipment

[0341] The server passes the received drone footage and sensor data to the generation AI for detailed analysis. The generation AI analyzes the damage situation and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fire or heat sources. This allows rescue points and routes to be optimized, and the information is provided to rescue organizations and medical institutions. For example, the server could identify the building with the most damage among multiple collapsed buildings and provide rescue teams with safe routes around it.

[0342] Calculating necessary supplies

[0343] The server uses the results of the analysis to analyze the situation in the affected area and calculate the type and amount of medical supplies and relief supplies needed. Based on this information, the server sends route instructions to the drone for delivering supplies. For example, the server calculates the necessary supplies and issues instructions, taking into account the number and health status of victims gathered at evacuation centers.

[0344] Securing communication infrastructure

[0345] In areas where communications have been cut off due to a disaster, the server will move drones equipped with communications capabilities to designated locations to establish temporary communications relay points. This will restore data communications within the affected area and maintain coordination with the server and relief organizations. For example, a communications relay drone will fly over a disaster area where communications have been cut off and provide communications signals.

[0346] Emotion Engine

[0347] The server uses an emotion engine to analyze the facial expression data of disaster victims collected by the drone and identify their emotional state. Based on this, it notifies rescue organizations and medical institutions of locations where psychological support is needed. It also monitors the emotional state of disaster victims in evacuation centers in real time and notifies medical institutions if it detects any abnormalities. For example, if a disaster victim in an evacuation center becomes extremely anxious or panicked, it will quickly convey that information to the medical team.

[0348] Prompt Sentence Examples

[0349] Below are some example prompts for each process in the event of a disaster:

[0350] "An earthquake has occurred. Fly a drone based on the coordinate information of the center of City A and collect video and sensor data."

[0351] "Use AI to analyze real-time video data from the disaster area, calculate the optimal rescue route, and provide it to rescue teams."

[0352] "Calculate the necessary medical supplies and relief supplies based on the situation at the evacuation center, and have delivery drones deliver them along the designated route."

[0353] "Send communications relay drones to areas where communications have been cut off and secure communications infrastructure."

[0354] "Analyze the emotional state of the victims and notify medical institutions so that necessary psychological care can be provided."

[0355] In this way, the present invention allows disaster relief efforts to be carried out quickly and efficiently, providing comprehensive assistance to victims.

[0356] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0357] Program processing flow

[0358] Step 1: Detecting a disaster and issuing a command to launch a drone

[0359] Description: When a user confirms that a disaster has occurred, the server immediately sends activation commands to multiple autonomous flying devices (drones).

[0360] Input: Disaster occurrence detection data (obtained from sensor networks or external APIs)

[0361] Data processing and calculation: Receiving and analyzing disaster information

[0362] Output: Start command to drone

[0363] Specific operation: The user confirms the occurrence of a disaster on the system, and the server sends a start-up command to the drone, including coordinate information of the affected area. For example, when the server confirms the occurrence of a disaster, it issues a start-up command to the drone, including coordinate information (center of City A).

[0364] Step 2: Collecting information using drones

[0365] Description: The device (drone) heads to the designated disaster area and collects video and sensor data in real time.

[0366] Input: Drone launch command and coordinate information of the affected area

[0367] Data processing and computation: Autonomous flight control and sensor data collection

[0368] Output: Collected video and sensor data

[0369] Specific operation: Once the drone reaches the designated disaster area, it uses its onboard camera and sensor devices to collect video footage and data such as temperature, humidity, and gas concentration in real time, and transmits the data to a server.

[0370] Step 3: Data analysis and rescue route calculation

[0371] Description: The server passes the data received from the drone to the generative AI model, which analyzes the damage situation.

[0372] Input: Video data and sensor data transmitted from the drone

[0373] Data Processing and Computation: Disaster Situation Analysis Using Generative AI Models

[0374] Output: Analysis results (number of collapsed buildings, location of victims, presence or absence of fire or heat source, etc.)

[0375] Specific operation: The server inputs the received data into the generative AI model and analyzes the damage situation (e.g., the collapsed status of multiple buildings, the location of victims, the location of the fire, etc.). Based on the analysis results, the server calculates the optimal rescue point and safe rescue route.

[0376] Step 4: Provide information to relief agencies and medical institutions

[0377] Description: The server provides rescue routes calculated based on the analysis results to rescue organizations and medical institutions.

[0378] Input: Analysis results of the generative AI model (optimal rescue location and route)

[0379] Data processing and calculation: Optimization and notification of rescue routes

[0380] Output: Providing information to relief agencies and medical institutions

[0381] Specific operation: The server uses the analysis results to calculate the optimal rescue route and transmits that information to rescue teams and hospitals in real time. For example, the server transmits the optimal rescue route and rescue location information to the rescue team's tablet device.

[0382] Step 5: Calculate and order supplies

[0383] Description: The server calculates the type and amount of supplies needed based on situational data from the disaster area and sends route instructions to the transport drone.

[0384] Input: Situation data of the affected area and analysis results

[0385] Data processing and calculation: Calculation of the type and amount of supplies needed

[0386] Output: Route instructions for the transport drone

[0387] Specific operation: Based on the analysis results, the server calculates the amount of food, water, and medical supplies needed, and transmits this information to a delivery drone to transport the supplies along a specified route. For example, the server calculates the amount of supplies needed based on the number of disaster victims in an evacuation shelter and transmits this information to the delivery drone.

[0388] Step 6: Securing communications infrastructure

[0389] Description: The server will move a drone with communication capabilities to a specific location to secure a temporary communication relay point.

[0390] Input: Communication infrastructure status data

[0391] Data processing and calculation: Calculation to secure communication relay points

[0392] Output: Position instructions to communication drone

[0393] Specific operation: To cover areas where communication has been cut off, the server sends instructions to communication relay drones to move to specific locations and secure communication relay points. For example, the server analyzes the communication situation in the affected area and transmits location information to drones that provide communication signals at high altitudes.

[0394] Step 7: Emotional analysis and psychological support

[0395] Description: The server uses an emotion engine to analyze the facial expression data of the victim and identify their emotional state.

[0396] Input: Facial expression data (collected by drone)

[0397] Data Processing and Computation: Emotion Analysis with Emotion Engine

[0398] Output: Identification of locations where psychological support is needed

[0399] Specific operation: The server inputs facial expression data into the emotion engine and analyzes the emotional state of the victim. Based on the results, it notifies medical institutions where psychological support is needed. For example, it identifies victims who are anxious or panicked and conveys that information to the medical team.

[0400] This enables the system to quickly and efficiently collect and analyze information, secure communication infrastructure, calculate and transport necessary supplies, and provide psychological support to disaster victims.

[0401] (Application example 2)

[0402] 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."

[0403] When it comes to fast and efficient rescue operations and support for victims in the event of a disaster, as well as efficient inventory management at logistics centers, conventional systems have faced challenges such as delays in information collection and analysis, difficulty in securing communication infrastructure, and a lack of mental care for workers.

[0404] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for flying an autonomous flight device to a designated disaster area and collecting video data and environmental data in real time; a generative artificial intelligence means for analyzing the collected video data and environmental data; means for calculating optimal material transportation routes and efficient inventory management means based on the analysis results and providing them to management agencies and rescue agencies; means for temporarily securing communication infrastructure using the autonomous flight device and restoring data communication; and means for capturing facial expressions of workers using the autonomous flight device or a fixed camera and providing psychological support using an emotion analysis engine. This enables fast and efficient information collection and analysis at disaster sites and logistics centers, enabling optimal rescue operations, inventory management, and psychological care for workers.

[0405] An "autonomous flying device" is an unmanned aerial vehicle that flies autonomously to a designated location and collects data in real time.

[0406] "Video data" refers to real-time video information acquired by an autonomous flying device or a fixed camera.

[0407] "Environmental data" refers to environmental information such as temperature, humidity, and air pressure collected by sensors on an autonomous flight device.

[0408] The "generative artificial intelligence means" is an artificial intelligence system that analyzes collected image data and environmental data and determines the situation and necessary response.

[0409] The "emotion analysis engine" is an analysis system that analyzes facial expression data of workers and disaster victims to identify their emotional state.

[0410] "Communications infrastructure" refers to network equipment that enables data exchange.

[0411] "Disaster area" means an area that has been affected by a disaster.

[0412] A "logistics center" is a facility that stores, manages, and distributes goods.

[0413] A "relief organization" is an organization or group that carries out relief activities in the event of a disaster.

[0414] "Management agency" means the organization or body that operates and manages the logistics center.

[0415] A "materials transport route" is a route for efficiently transporting materials.

[0416] "Inventory management means" refers to a system and method for efficiently managing inventory within a distribution center.

[0417] The present invention provides a system that enables prompt and efficient information collection and analysis in the event of a disaster or at a logistics center, enabling optimal responses. The detailed configuration and operation of the system are described below.

[0418] System configuration

[0419] The system consists of the following main components:

[0420] 1. Autonomous flying devices (drones)

[0421] 2. Server (for data analysis)

[0422] 3. Sentiment Analysis Engine

[0423] 4. Linkage device with rescue / medical institutions and logistics management organizations

[0424] 5. Communication infrastructure securing equipment

[0425] Hardware and software used

[0426] Drone: An unmanned aerial vehicle that flies autonomously to a designated location and collects video and environmental data in real time.

[0427] Server: AWS EC2 instance used for data analysis

[0428] Generative AI method: Uses a generative AI model (e.g., OpenAI GPT-4)

[0429] Sentiment analysis engine: Affectiva

[0430] Collaborative software: Python, TensorFlow, Flask

[0431] How it works

[0432] 1. Information gathering

[0433] The drones fly to designated locations in disaster situations or within logistics centers, using cameras and sensors to collect real-time video and environmental data, which is then sent to a server in real time.

[0434] 2. Data Analysis

[0435] The server inputs the received video data and environmental data into a generative AI model for analysis. The generative AI performs a detailed analysis of the damage situation and the inventory status of the logistics center, extracting important information such as the number of collapsed buildings, the location of victims, the presence or absence of fires or heat sources, and the location and quantity of inventory. Based on the results of this analysis, it calculates the optimal rescue points and supply transport routes.

[0436] 3. Securing communication infrastructure

[0437] Drones equipped with communication capabilities will set up communication relay points in disaster-stricken areas and logistics centers, securing temporary communication infrastructure, which will restore data communication and enable collaboration with servers and information sharing.

[0438] 4. Emotion analysis and psychological support

[0439] Drones or fixed cameras capture the facial expressions of workers and victims, which are then analyzed using an emotion analysis engine. Based on the results of this analysis, necessary psychological support is provided. If a worker is in a state of high stress, a notification is sent to the manager, urging them to take appropriate action.

[0440] Specific examples

[0441] When a disaster occurs: Drones fly over the affected area and collect information on the damage in real time. This information is analyzed by a generative AI model to determine rescue routes and routes for transporting supplies. If necessary, communication relay drones fly to secure the communications infrastructure.

[0442] Logistics Center: Drones monitor inventory in logistics centers, and generative AI identifies shortages and areas that need restocking. In addition, an emotion analysis engine monitors the psychological state of workers and notifies managers if they are feeling stressed.

[0443] Example prompt sentence:

[0444] Get a real-time view of your inventory and calculate the best route.

[0445] Analyze the emotional state of workers based on facial expression data and notify them if there are any abnormalities.

[0446] In this way, this system aims to solve comprehensive problems by enabling rapid response in the event of a disaster, efficient management at logistics centers, and also providing psychological care for workers.

[0447] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0448] Step 1:

[0449] Drone launch and information gathering

[0450] The server activates an autonomous flight device (drone) to collect information on disasters and within the logistics center. The server transmits coordinate information of a specified location (a specific point in the disaster area or logistics center) to the drone. The drone begins flying and collects video data and environmental data (temperature, humidity, air pressure, etc.) in real time. This data is then transmitted to the server in real time.

[0451] Input: Coordinate information of the disaster site and logistics center

[0452] Output: Real-time video and environmental data

[0453] Specific operations: Data collection using drone cameras and sensors, real-time flight control of drones

[0454] Step 2:

[0455] Receiving and storing data

[0456] The server receives the video and environmental data transmitted from the drone and stores it in a database, where it is temporarily saved for analysis.

[0457] Input: Real-time video and environmental data transmitted from the drone

[0458] Output: Video and environmental data stored in a database

[0459] Specific operation: Receiving data on the server side and writing it to the database

[0460] Step 3:

[0461] Data analysis

[0462] The server inputs the stored video data and environmental data into a generative AI model, which then performs a detailed analysis of the damage and inventory status and extracts important information (e.g., the number of collapsed buildings, the locations of victims, the presence or absence of fires or heat sources, and the location and quantity of inventory).

[0463] Input: Video and environmental data stored in a database

[0464] Output: Important parsed information

[0465] Specific behavior: Data analysis and extraction of important information using generative AI

[0466] Step 4:

[0467] Rescue and transport route calculations

[0468] The server calculates optimal rescue locations and routes for transporting supplies based on the analysis results obtained from the generative AI model. This route information is provided to rescue organizations and logistics management organizations, enabling rapid response.

[0469] Input: Analysis results obtained from the generative AI model

[0470] Output: Optimal rescue and supply routes

[0471] Specific operations: Applying route calculation algorithms, notifying rescue and logistics agencies

[0472] Step 5:

[0473] Securing communication infrastructure

[0474] To secure the communications infrastructure, the server activates drones equipped with communications capabilities and flies them to designated locations, establishing temporary communications relay points that enable data communication within disaster-stricken areas and logistics centers.

[0475] Input: Drone flight instructions and coordinate information of the specified point

[0476] Output: Secured communications infrastructure

[0477] Specific operations: Starting and flying a drone with communication capabilities, setting up a communication relay point

[0478] Step 6:

[0479] Emotion analysis and psychological support

[0480] The server receives facial expression data of workers and disaster victims sent from drones or fixed cameras and inputs it into an emotion analysis engine. The emotion analysis engine identifies their emotional state and identifies individuals who need psychological support. The server notifies administrators of this information and encourages appropriate psychological care.

[0481] Input: Facial expression data of workers and victims

[0482] Output: Identified emotional state and necessary support information

[0483] Specific actions: Data analysis using sentiment analysis engine, notification to administrator

[0484] As a result, the system of the present invention realizes a rapid response in the event of a disaster and efficient management at the logistics center. Furthermore, it aims to provide comprehensive problem-solving by providing psychological care for workers and disaster victims.

[0485] 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.

[0486] 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.

[0487] 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.

[0488] [Second embodiment]

[0489] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0490] 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.

[0491] 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).

[0492] 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.

[0493] 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.

[0494] 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).

[0495] 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.

[0496] 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.

[0497] 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.

[0498] 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.

[0499] 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.

[0500] 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."

[0501] The present invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones) with generative AI technology to carry out disaster relief activities quickly and efficiently. The system of the present invention mainly collects and analyzes information when a disaster occurs, optimizes rescue routes, secures communication infrastructure, and carries out rescue activities. The following describes the overall configuration of the system and the operation of each part.

[0502] System configuration

[0503] The system consists of four main parts:

[0504] 1. Information gathering devices (drones)

[0505] 2. Data analysis device (server)

[0506] 3. Server for linking with rescue and medical institutions

[0507] 4. Communication infrastructure securing device (drone)

[0508] Program for carrying out the invention

[0509] Drone launch and information gathering

[0510] When a disaster occurs, the server immediately sends instructions to launch a fleet of drones. The drones begin flying toward the designated disaster area and collect video and sensor data in real time. This data is then sent from the drones to the server. For example, if a major earthquake occurs, the server sends the coordinates of the disaster area to the drones, who then depart for that location.

[0511] Real-time data analysis and rescue route calculation

[0512] The server receives real-time video data sent from the drone and passes it to the generation AI for analysis. The generation AI analyzes the damage situation in detail and extracts important information such as the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions. As a specific example, the server identifies the building with the most damage among multiple collapsed buildings and provides rescue teams with safe routes around it.

[0513] Calculating necessary supplies

[0514] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drone for delivering the supplies. For example, it calculates the amount of food, water, and medicine needed based on the number and health condition of the victims gathered at evacuation centers and sends this information to the delivery drone.

[0515] Securing communications infrastructure and relief efforts

[0516] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points. This will restore data communications within the affected area and maintain connections with servers and relief organizations. As a specific example, a communications relay drone will fly over a disaster-stricken area where communications have been cut off, maintaining its altitude to provide communications signals.

[0517] Implementing and following up on relief efforts

[0518] Identifying unrescue locations, checking the health of victims, and maintaining public order are also important functions of this system. Based on the analysis results of the generated AI, the server identifies unrescue locations and directs a group of drones to carry out rescue operations. It also checks the health of victims and provides necessary medical assistance. As a specific example, drones fly over the affected area, remotely measuring the body temperature and heart rate of victims, and immediately dispatching rescue teams to victims in urgent need.

[0519] With such a system configuration and operation, the present invention can realize rapid and effective rescue operations in the event of a disaster.

[0520] The processing flow will be explained below.

[0521] Step 1:

[0522] Server: Upon receiving information about a disaster, it immediately launches multiple drones and sends them commands to fly towards the designated disaster area.

[0523] Example: An earthquake occurs and the server sends a departure command to each drone.

[0524] Step 2:

[0525] Drones: Fly to designated disaster areas to collect real-time video and sensor data. The drones perform a series of flight patterns to ensure comprehensive coverage of the disaster area.

[0526] Example: Drones can capture images of debris and road damage from the sky, and temperature sensors can detect fires.

[0527] Step 3:

[0528] Drone: Collected video and sensor data is sent to a server via 4G / 5G networks or dedicated wireless communication protocols.

[0529] Example: A drone uploads data to a server in real time.

[0530] Step 4:

[0531] Server: Passes the received data to the generation AI, which analyzes the damage situation in detail. The generation AI uses image recognition technology to identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources, and extracts important information.

[0532] Example: Generative AI analyzes video footage and displays the coordinates of collapsed buildings and fire sites on a map.

[0533] Step 5:

[0534] Server: Based on the analysis results of the generation AI, it calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions.

[0535] Example: The server identifies the most affected areas and sends their coordinates and rescue routes to rescue teams.

[0536] Step 6:

[0537] Server: Analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to drones delivering supplies.

[0538] Example: Calculate the amount of food, water, and medicine needed at a shelter and communicate that information to a delivery drone.

[0539] Step 7:

[0540] Drones: Drones equipped with communication capabilities will fly to designated locations and establish temporary communication relay points, thereby temporarily restoring communication infrastructure in the affected areas.

[0541] Example: A communications drone hovers over the affected area and provides a communications signal.

[0542] Step 8:

[0543] Server: Based on the analysis results of the generated AI and real-time data, it identifies unrescue locations and directs a group of drones to carry out rescue operations.

[0544] Example: A drone continuously collects images of unrescue areas identified by the server and updates the information.

[0545] Step 9:

[0546] Drones: Guide victims to safe evacuation sites and deliver necessary emergency supplies. They may also use voice guidance and LED displays to show the route.

[0547] Example: The drone will provide voice guidance to indicate evacuation routes and use LED lights to show evacuation routes even at night.

[0548] This will enable the system to carry out rapid and effective disaster relief efforts in affected areas.

[0549] Example 1

[0550] 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."

[0551] Conventional disaster relief systems had the problem of making it difficult to carry out relief activities quickly and efficiently, resulting in the time it took to rescue victims. Furthermore, due to insufficient understanding of the situation in the affected areas and insufficient communication infrastructure, the transmission of information regarding relief activities was often delayed. Furthermore, due to a lack of means to accurately grasp the amount and type of supplies needed, the supply of supplies was delayed, and in some cases appropriate support was not provided in line with the needs of the victims.

[0552] 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.

[0553] In this invention, the server includes means for flying multiple autonomous flight devices to designated disaster areas and collecting video data and environmental data in real time, a generating artificial intelligence means for analyzing the collected video data and environmental data, a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions, a means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices, and a means for identifying unrescue points, maintaining public order, checking the health of victims, guiding them to evacuation sites, and calculating and issuing transport instructions for necessary supplies. This enables rapid and efficient rescue operations, understanding the situation in the disaster area, securing communication infrastructure, and supplying appropriate supplies.

[0554] An "autonomous flying device" is an unmanned aerial vehicle that can fly by remote control or automatic control.

[0555] "Video data" refers to visual information collected by a video capture device such as a camera or video recorder.

[0556] "Environmental data" is data obtained from sensors that measure environmental parameters such as temperature, humidity, gas concentration, and radiation levels.

[0557] "Generative artificial intelligence means" refers to an artificial intelligence system that has the ability to analyze large amounts of data and automatically generate specific patterns or information.

[0558] "Rescue point" refers to a location within a disaster area where rescue is particularly needed.

[0559] A "rescue route" refers to a route that can be traveled safely and efficiently when carrying out rescue operations.

[0560] "Communications infrastructure" refers to the entire hardware and software that make up a communications network.

[0561] A "communication relay point" is a base that relays communication signals, and is a point that is installed to expand the communication range or to deal with sudden communication interruptions.

[0562] "Unrescue points" refer to locations within the disaster area where rescue efforts have not yet begun.

[0563] "Maintaining public order" refers to activities to ensure safety and maintain order at the scene of a disaster.

[0564] "Health assessment of disaster victims" is the process of assessing the physical condition and medical condition of disaster victims and determining the medical assistance they require.

[0565] An "evacuation site" refers to a safe place designated for temporary evacuation of disaster victims in the event of a disaster.

[0566] "Necessary supplies" refers to basic necessities such as food, water, and medicine that disaster victims need during relief efforts.

[0567] A "materials transport order" is an order to transport needed materials to a specific location.

[0568] "Real-time" refers to data being processed and used as soon as it is generated.

[0569] This invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones) with generative AI technology to carry out disaster relief activities quickly and efficiently. The system of this invention mainly collects and analyzes information when a disaster occurs, calculates rescue routes, secures communication infrastructure, and carries out relief activities.

[0570] System configuration

[0571] The system consists of four main parts:

[0572] 1. Information gathering devices (drones)

[0573] 2. Data analysis device (server)

[0574] 3. Server for linking with rescue and medical institutions

[0575] 4. Communication infrastructure securing device (drone)

[0576] Drone launch and information gathering

[0577] When a disaster occurs, the server immediately sends instructions to activate a fleet of drones, which begin flying toward the designated disaster area and collecting real-time video and sensor data, which is then transmitted from the drones to the server.

[0578] Examples:

[0579] In the event of a major earthquake, the server will send coordinate information of the affected area to the drone, and the drone will then depart for that location.

[0580] Real-time data analysis and rescue route calculation

[0581] The server receives real-time video data sent from the drone and passes it to the AI ​​generator for analysis. The AI ​​generator performs a detailed analysis of the damage situation and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions.

[0582] Examples:

[0583] The server identifies the building that suffered the most damage among several collapsed buildings and provides rescue teams with safe routes around it.

[0584] Calculating necessary supplies

[0585] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drones for delivering the supplies.

[0586] Examples:

[0587] Taking into account the number of disaster victims gathered at the evacuation center and their health condition, the system calculates the amount of food, water, and medicine needed and transmits this information to the transport drone.

[0588] Securing communications infrastructure and relief efforts

[0589] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points, restoring data communications within the affected area and maintaining connections with servers and relief organizations.

[0590] Examples:

[0591] Communication relay drones fly over disaster-stricken areas where communications have been cut off, maintaining altitude to provide communication signals.

[0592] Implementing and following up on relief efforts

[0593] Identifying unrescue locations, checking the health of victims, and maintaining public order are also important functions of this system. Based on the analysis results of the generated AI, the server identifies unrescue locations and directs drones to carry out rescue operations. It also checks the health of victims and provides necessary medical assistance.

[0594] Examples:

[0595] The drones fly over the affected areas, remotely measuring the body temperature and heart rate of victims, and rescue teams are immediately dispatched to those in urgent need.

[0596] Prompt Sentence Examples

[0597] Here are some examples of specific prompts for a generative AI model:

[0598] 1. Prompt for analyzing video data from the disaster area:

[0599] Next, analyze the video data provided to determine the number of collapsed buildings, the location of victims, and whether there were any fires or heat sources.

[0600] 2. Prompt to assess the victim's health:

[0601] Please use the following sensor data to measure the victim's body temperature and heart rate and identify those in need of emergency assistance.

[0602] With this system configuration and specific operation, the present invention can realize rapid and effective rescue operations in the event of a disaster.

[0603] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0604] Step 1:

[0605] The server that detects the occurrence of a disaster sends an instruction to activate the drones.

[0606] Input: Disaster occurrence detection data (e.g., earthquake occurrence notification)

[0607] Data processing / calculation: The server obtains coordinate data of the disaster site and executes the drone activation protocol.

[0608] Output: Commands to launch drones and coordinates of the affected area

[0609] Specific behavior:

[0610] The server automatically receives notification of a disaster and sends the coordinates of the affected area to the drone, which then prepares to fly to the specified location.

[0611] Step 2:

[0612] Based on the transmitted coordinate information, the drone begins flying toward the affected area and collects video and sensor data in real time.

[0613] Input: Coordinate information of affected area

[0614] Data processing / computation: The drone activates its cameras and sensors to collect video and environmental data of the designated area.

[0615] Output: Collected video and sensor data

[0616] Specific behavior:

[0617] The drone flies to specified coordinates, captures real-time footage with a high-resolution camera, and uses sensors to measure environmental data such as temperature and gas concentrations.

[0618] Step 3:

[0619] The collected data is sent to the server in real time.

[0620] Input: Video and sensor data

[0621] Data processing / calculation: The drone transmits the collected data to a server via wireless communication.

[0622] Output: Video data and sensor data uploaded to the server

[0623] Specific behavior:

[0624] The drone wirelessly transmits real-time video and sensor data to a server, which then receives the data.

[0625] Step 4:

[0626] The server passes the received data to the generative AI model for analysis.

[0627] Input: Video data and sensor data sent to the server

[0628] Data processing / calculation: A generative AI model analyzes the data and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fire or heat sources.

[0629] Output: Analysis results of the damage situation

[0630] Specific behavior:

[0631] The server inputs the received data into a generative AI model, and the AI ​​analyzes the data to gain a detailed understanding of the situation in the affected areas.

[0632] Step 5:

[0633] The server calculates the optimal rescue point and safe rescue route based on the analysis results of the generated AI model.

[0634] Input: Analysis results of the damage situation

[0635] Data processing / calculation: The server runs an algorithm based on the analysis results to calculate the optimal rescue point and safe route.

[0636] Output: Rescue location and rescue route information

[0637] Specific behavior:

[0638] The server calculates safe and efficient rescue routes based on the locations of collapsed buildings and victims, and provides them to rescue agencies.

[0639] Step 6:

[0640] The server analyzes detailed data on the affected area and calculates the types and quantities of medical supplies and relief goods needed.

[0641] Input: Detailed data of the affected area

[0642] Data processing / calculation: The server analyzes the number of people, their health status, and the damage situation, and determines the type and amount of supplies needed.

[0643] Output: List of required supplies

[0644] Specific behavior:

[0645] The server calculates and lists the quantities of food, water, and medicine needed based on data on disaster victims gathered at evacuation centers.

[0646] Step 7:

[0647] The server sends instructions to the drone on the route to transport the necessary supplies.

[0648] Input: List of required supplies and destination coordinates

[0649] Data processing / calculation: The server calculates the optimal route for transporting supplies and sends those instructions to the drone.

[0650] Output: Delivery route instructions for drone

[0651] Specific behavior:

[0652] The server indicates to the drone the specific flight route to carry the necessary supplies, and the drone then transports the supplies along that route.

[0653] Step 8:

[0654] If communication infrastructure is destroyed, drones equipped with communication capabilities will move to designated locations and function as communication relay points.

[0655] Input: Communication status data for affected areas

[0656] Data processing / calculation: The server identifies the area where communication has been lost and instructs the communication drone to move to that area.

[0657] Output: Communication infrastructure restored

[0658] Specific behavior:

[0659] Based on instructions from the server, drones equipped with communication capabilities will provide communication relay points over the affected area, temporarily restoring the communication network.

[0660] Step 9:

[0661] Based on the analysis results of the generated AI model, the server identifies unrescue locations and instructs a group of drones to carry out rescue operations.

[0662] Input: Analysis results of the generative AI model

[0663] Data processing / calculation: The server identifies unrescue locations that require rescue operations and issues instructions to the drones.

[0664] Output: Rescue operation instructions

[0665] Specific behavior:

[0666] The drones will fly to unrescue locations, remotely measure the temperature and heart rate of victims, and provide necessary medical assistance.

[0667] The above are the specific processing steps and detailed operations in the system program.

[0668] (Application example 1)

[0669] 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."

[0670] Conventional disaster relief systems have had difficulty quickly and efficiently grasping the situation in disaster-stricken areas and taking appropriate action. They also have issues with delays in sharing information and issuing instructions for rescue operations when communication infrastructure is destroyed. Furthermore, even with standard security monitoring, anomaly detection is not performed in real time, making it difficult to respond quickly.

[0671] 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.

[0672] In this invention, the server includes a means for flying the autonomous flight device to a designated disaster area and collecting video data in real time, a generating artificial intelligence means for analyzing the collected video data, and a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions. This makes it possible to quickly collect and analyze information in the event of a disaster and provide optimal rescue routes.

[0673] Furthermore, it includes a means for temporarily securing communication infrastructure in disaster-stricken areas using autonomous flight devices, and a means for identifying unrescue locations, maintaining public order, checking the health of disaster victims, and guiding them to evacuation sites. This allows for the continuation of information sharing and instructions for rescue operations even if communication infrastructure is destroyed.

[0674] In addition, it includes a means for collecting security monitoring data in real time during operation, detecting anomalies using a generative AI model, and a means for securing communication relay points even in areas with unstable communication infrastructure based on the detection results, which enables rapid anomaly detection and response even in normal security monitoring.

[0675] An "autonomous flight device" is an unmanned aerial vehicle that flies autonomously according to pre-programmed instructions and collects video and sensor data.

[0676] "Generative AI" is an artificial intelligence technology that analyzes collected data and generates and provides necessary information.

[0677] A "rescue route" is a route optimized for safe and rapid rescue operations.

[0678] "Sensor data" refers to physical data such as temperature, humidity, vibration, and pressure obtained from drones and other sensor devices.

[0679] "Anomaly detection" is the process of detecting abnormal situations or behaviors that deviate from normal conditions.

[0680] "Telecommunications infrastructure" refers to the physical and software systems that create telecommunications networks and enable the transmission and reception of data.

[0681] A "communication relay point" is an intermediate point that temporarily relays communications in an area where communications have been cut off, ensuring network connectivity.

[0682] A "generative AI model" is a type of artificial intelligence that generates new information and data patterns based on large amounts of data.

[0683] A "prompt sentence" is an input sentence used to give instructions to a generative AI model.

[0684] "Security surveillance data" refers to video, audio, sensor, and other data collected in real time to ensure the safety of a specific area.

[0685] "Disaster situation" refers to the state of damage in the area where the disaster occurred, including the number of collapsed buildings, the location of victims, and the presence or absence of fires or heat sources.

[0686] An "embodiment" is a form showing how the invention is specifically carried out.

[0687] This invention is a system that combines autonomous flight devices (drones) and generative AI technology to realize rapid and efficient rescue operations in the event of a disaster. The main components of this system are as follows:

[0688] System configuration

[0689] 1. Autonomous flying devices (drones)

[0690] 2. Generative artificial intelligence (AI) means

[0691] 3. Rescue route calculation method

[0692] 4. Measures to secure communications infrastructure

[0693] 5. Anomaly detection and notification methods

[0694] System Operation

[0695] Drone launch and information gathering

[0696] When a disaster occurs, the server immediately activates an autonomous flying device (drone) and has it fly toward the designated disaster area. The drone collects video and sensor data in real time and transmits the data to the server. In particular, the drone uses advanced sensor technology (temperature sensors, humidity sensors, etc.) to collect detailed data.

[0697] Real-time data analysis and rescue route calculation

[0698] The server passes the real-time video and sensor data transmitted from the drone to a generative AI model for analysis. Examples of generative AI models include OpenAI's GPT-4. This AI analyzes the collected data and identifies the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. It then calculates the optimal rescue points and safe rescue routes and provides this information to rescue organizations and medical institutions.

[0699] Calculation and instructions for necessary supplies

[0700] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drones for delivering the supplies. Selecting the appropriate route enables the rapid and efficient delivery of supplies.

[0701] Securing communication infrastructure

[0702] If communications infrastructure is destroyed, drones equipped with communications capabilities will move to designated locations and establish temporary communications relay points. Specifically, the drones will maintain altitude and transmit communications signals to support communications at the scene. This will restore data communications within the disaster area and maintain communication with servers and relief organizations.

[0703] Security monitoring and anomaly detection

[0704] Under normal circumstances, drones collect security monitoring data and use generative AI models to detect anomalies in real time. The analysis results are then immediately communicated to security personnel. Even in areas with unstable communications infrastructure, drones can function as communication relay points, ensuring stable data communication.

[0705] Specific examples

[0706] During nighttime security surveillance at a large commercial facility, if a drone detects a suspicious person entering the facility in real time, by inputting the prompt "Anomaly detection: Analyze video data, detect and report any anomalies" into the generative AI model, details of the anomaly will be immediately sent to the server. As a result, security personnel will receive an immediate notification of the anomaly via their smartphone or smart glasses, enabling them to respond promptly.

[0707] As described above, this system can be applied not only during disasters but also to normal security monitoring, enabling rapid and efficient responses through real-time data collection and analysis using generative AI.

[0708] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0709] Step 1:

[0710] When a disaster occurs, the server immediately activates an autonomous flying device (drone) and sends it off to the designated disaster area. The drone collects video and sensor data in real time. The input is coordinate information of the disaster area, and the output is real-time video and sensor data.

[0711] Step 2:

[0712] The collected video and sensor data is sent to a server, which receives the data and passes it to a generative AI model. The input is real-time video and sensor data, and the output is data that is analyzed by the generative AI model.

[0713] Step 3:

[0714] The server analyzes the collected data using a generative AI model. Specifically, the AI ​​model receives prompts to "analyze the damage situation, identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources," and obtains analysis results. This analysis includes pattern recognition in video and anomaly detection in sensor data. The inputs are prompts and raw data for the AI ​​model, and the output is the analysis results.

[0715] Step 4:

[0716] Based on the analysis results, the server calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions. The input is the analysis results, and the output is optimized rescue route information. Specifically, a route search algorithm is used to calculate the shortest and safest route.

[0717] Step 5:

[0718] The server calculates the type and amount of medical supplies and relief supplies needed and sends route instructions to the drones for delivering the supplies. The input is the number of people in the disaster area and health data, and the output is the delivery route and a list of supplies. A supply supply algorithm determines the amount of supplies needed at each location.

[0719] Step 6:

[0720] If communications infrastructure is destroyed, drones act as communication relay points to establish a temporary communications infrastructure. The input is the coordinate information of the communication-disrupted area, and the output is the area where a constant communication connection is ensured. Communications are stabilized using LoRa networks and other mesh network technologies.

[0721] Step 7:

[0722] Under normal circumstances, drones collect security surveillance data and use generative AI models to detect anomalies in real time. The results are then notified to security personnel. The input is real-time surveillance data, and the output is anomaly detection results and notification information. A specific prompt, "Anomaly detection: Analyze video data, detect anomalies, and report them," is used to prompt the AI ​​to perform analysis.

[0723] By combining these processing steps, this system enables multifunctional and highly efficient operations during disasters and normal security activities.

[0724] 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.

[0725] This invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones), generative AI technology, and an emotion engine to carry out disaster relief activities quickly and efficiently. The system of this invention collects and analyzes information when a disaster occurs, optimizes rescue routes, secures communication infrastructure, and provides psychological support through emotion analysis. The following describes the overall configuration of the system and the operation of each component.

[0726] System configuration

[0727] The system consists of five main parts:

[0728] 1. Information gathering devices (drones)

[0729] 2. Data analysis device (server)

[0730] 3. Emotion Engine

[0731] 4. Server for linking with rescue and medical institutions

[0732] 5. Communication infrastructure securing device (drone)

[0733] Program for carrying out the invention

[0734] Drone launch and information gathering

[0735] When a disaster occurs, the server immediately sends instructions to launch a fleet of drones. The drones begin flying toward the designated disaster area and collect video and sensor data in real time. This data is then sent from the drones to the server. For example, if a major earthquake occurs, the server sends the coordinates of the disaster area to the drones, who then depart for that location.

[0736] Real-time data analysis and rescue route calculation

[0737] The server receives real-time video data sent from the drone and passes it to the generation AI for analysis. The generation AI analyzes the damage situation in detail and extracts important information such as the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions. As a specific example, the server identifies the building with the most damage among multiple collapsed buildings and provides rescue teams with safe routes around it.

[0738] Calculating necessary supplies

[0739] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drone for delivering the supplies. For example, it calculates the amount of food, water, and medicine needed based on the number and health condition of the victims gathered at evacuation centers and sends this information to the delivery drone.

[0740] Securing communications infrastructure and relief efforts

[0741] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points. This will restore data communications within the affected area and maintain connections with servers and relief organizations. As a specific example, a communications relay drone will fly over a disaster-stricken area where communications have been cut off, maintaining its altitude to provide communications signals.

[0742] Emotion analysis and psychological support using an emotion engine

[0743] The server uses an emotion engine to analyze the facial expression data of victims collected by the drone and identify their emotional state. Based on the emotion engine's analysis results, it notifies rescue organizations and medical institutions of locations where psychological support is needed. In addition, even after communication infrastructure is restored, it continues to monitor the emotional state of victims in evacuation centers in real time, and notifies medical institutions if it detects abnormal stress or anxiety. For example, if a victim in an evacuation center becomes extremely anxious or panics, this information is quickly conveyed to the medical team, and the necessary support is provided.

[0744] With such a system configuration and operation, the present invention can realize rapid and effective relief activities in disaster areas and psychological care for disaster victims.

[0745] The processing flow will be explained below.

[0746] Step 1:

[0747] Server: Upon receiving information about a disaster, it immediately launches multiple drones and sends them commands to fly towards the designated disaster area.

[0748] Example: An earthquake occurs and the server sends a departure command to each drone.

[0749] Step 2:

[0750] Drones: Fly to designated disaster areas and collect real-time video and sensor data. Drones follow pre-set flight patterns to collect data over a wide area.

[0751] Example: Drones can capture images of debris and road damage from the sky, and temperature sensors can detect fires.

[0752] Step 3:

[0753] Drone: Collected video and sensor data is sent to a server via 4G / 5G networks or dedicated wireless communication protocols.

[0754] Example: A drone uploads data to a server in real time.

[0755] Step 4:

[0756] Server: Passes the received data to the generation AI, which analyzes the damage situation in detail. The generation AI uses image recognition technology to identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources, and extracts important information.

[0757] Example: Generative AI analyzes video footage and displays the coordinates of collapsed buildings and fire sites on a map.

[0758] Step 5:

[0759] Server: Based on the analysis results of the generation AI, it calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions.

[0760] Example: The server identifies the most affected areas and sends their coordinates and rescue routes to rescue teams.

[0761] Step 6:

[0762] Server: Analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to drones delivering supplies.

[0763] Example: Calculate the amount of food, water, and medicine needed at a shelter and communicate that information to a delivery drone.

[0764] Step 7:

[0765] Drones: Drones equipped with communication capabilities will fly to designated locations and establish temporary communication relay points, thereby temporarily restoring communication infrastructure in the affected areas.

[0766] Example: A communications drone hovers over the affected area and provides a communications signal.

[0767] Step 8:

[0768] Server: The emotion engine analyzes the facial expression data collected by the drone and identifies the emotional state of the victim. The emotion engine reads emotions such as anxiety, fear, and sadness from facial expressions.

[0769] Example: The emotion engine analyzes the facial expression data of a victim and determines that the victim is in a "high stress state."

[0770] Step 9:

[0771] Server: Based on the analysis results of the emotion engine, it notifies rescue organizations of locations where psychological assistance is needed, allowing psychological counseling and emergency psychological assistance to be provided promptly.

[0772] Example: The server sends an instruction to dispatch a psychological counselor to an evacuation site determined to be in a "high stress state."

[0773] Step 10:

[0774] Server: Even after the communication infrastructure is restored, the server monitors the emotional state of disaster victims in evacuation shelters in real time, and notifies medical institutions if it detects abnormal stress or anxiety.

[0775] Example: A server continuously monitors the emotional state of disaster victims in evacuation centers and sends an alert to medical teams if any abnormalities are detected.

[0776] Each processing step of this system enables rapid information gathering in disaster areas, ensuring the safety of victims, efficiently distributing relief supplies, and providing psychological care to victims.

[0777] Example 2

[0778] 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."

[0779] Conventional disaster relief systems have had problems with the collection and analysis of information, securing communication infrastructure, and providing psychological support to victims in a timely and efficient manner. Furthermore, the calculation and transportation of necessary supplies was ineffective, resulting in delayed responses to disaster victims.

[0780] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for flying multiple autonomous flight devices to a designated disaster area when a disaster occurs and collecting video data and sensor data in real time; a generating artificial intelligence means for analyzing the collected video data and sensor data; means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions; means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices; means for analyzing situation data in the disaster area to calculate the type and amount of supplies needed and sending route instructions to an autonomous flight device for delivery; and means for analyzing facial expression data of victims collected by the autonomous flight devices, identifying their emotional states, and providing psychological support. This enables rapid and efficient information collection and analysis, securing communication infrastructure, calculating and delivering needed supplies, and providing psychological support to victims.

[0781] A "disaster" is an abnormal phenomenon caused by natural phenomena or human factors that results in human injury or property damage.

[0782] An "autonomous flying device" is a device that performs a designated mission while flying itself based on pre-programmed instructions or instructions received in real time.

[0783] "Real-time" refers to situations in which data is collected and processed virtually immediately.

[0784] "Video data" refers to visual information acquired by a camera or other optical means.

[0785] "Sensor data" refers to data collected by a sensor that represents changes in physical quantities. Specifically, it includes information on temperature, humidity, air pressure, gas concentration, etc.

[0786] "Generative AI means" refers to a method or device that uses generative AI technology to analyze input data and extract and generate useful information.

[0787] "Rescue point" refers to a specific location within a disaster area where rescue operations should be carried out.

[0788] A "rescue route" refers to the optimal route for rescue teams to reach the rescue point safely and quickly.

[0789] "Communications infrastructure" refers to the hardware and software infrastructure required to conduct data communications.

[0790] "Supplies" refers to basic necessities and relief supplies such as food, medicine, and clothing needed to support disaster victims.

[0791] "Facial expression data" is data that captures a person's facial expressions and records their features and changes.

[0792] "Emotional state" refers to the results of analyzing and identifying the psychological reactions and emotional state of victims.

[0793] "Psychological support" refers to interventions and support activities aimed at reducing psychological stress and anxiety among disaster victims and supporting their mental health.

[0794] The system of the present invention combines multiple autonomous flying devices (hereinafter referred to as drones), generative artificial intelligence technology (generative AI model), and an emotion engine to realize rapid and efficient rescue operations in the event of a disaster. The system operates based on the following main components and their interactions:

[0795] System configuration

[0796] The system consists of five main parts:

[0797] 1. Information gathering devices (drones)

[0798] 2. Data analysis device (server)

[0799] 3. Emotion Engine

[0800] 4. Server for linking with rescue and medical institutions

[0801] 5. Communication infrastructure securing device (drone)

[0802] Information gathering device

[0803] In the event of a disaster, the server launches a fleet of drones and sends them to the affected area. The drones collect video and sensor data in real time and transmit that data to the server. For example, in the event of a major earthquake, the server sends coordinate information of the affected area to the drones, which then fly to that location and transmit the collected video and sensor data in real time.

[0804] Data analysis equipment

[0805] The server passes the received drone footage and sensor data to the generation AI for detailed analysis. The generation AI analyzes the damage situation and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fire or heat sources. This allows rescue points and routes to be optimized, and the information is provided to rescue organizations and medical institutions. For example, the server could identify the building with the most damage among multiple collapsed buildings and provide rescue teams with safe routes around it.

[0806] Calculating necessary supplies

[0807] The server uses the results of the analysis to analyze the situation in the affected area and calculate the type and amount of medical supplies and relief supplies needed. Based on this information, the server sends route instructions to the drone for delivering supplies. For example, the server calculates the necessary supplies and issues instructions, taking into account the number and health status of victims gathered at evacuation centers.

[0808] Securing communication infrastructure

[0809] In areas where communications have been cut off due to a disaster, the server will move drones equipped with communications capabilities to designated locations to establish temporary communications relay points. This will restore data communications within the affected area and maintain coordination with the server and relief organizations. For example, a communications relay drone will fly over a disaster area where communications have been cut off and provide communications signals.

[0810] Emotion Engine

[0811] The server uses an emotion engine to analyze the facial expression data of disaster victims collected by the drone and identify their emotional state. Based on this, it notifies rescue organizations and medical institutions of locations where psychological support is needed. It also monitors the emotional state of disaster victims in evacuation centers in real time and notifies medical institutions if it detects any abnormalities. For example, if a disaster victim in an evacuation center becomes extremely anxious or panicked, it will quickly convey that information to the medical team.

[0812] Prompt Sentence Examples

[0813] Below are some example prompts for each process in the event of a disaster:

[0814] "An earthquake has occurred. Fly a drone based on the coordinate information of the center of City A and collect video and sensor data."

[0815] "Use AI to analyze real-time video data from the disaster area, calculate the optimal rescue route, and provide it to rescue teams."

[0816] "Calculate the necessary medical supplies and relief supplies based on the situation at the evacuation center, and have delivery drones deliver them along the designated route."

[0817] "Send communications relay drones to areas where communications have been cut off and secure communications infrastructure."

[0818] "Analyze the emotional state of the victims and notify medical institutions so that necessary psychological care can be provided."

[0819] In this way, the present invention allows disaster relief efforts to be carried out quickly and efficiently, providing comprehensive assistance to victims.

[0820] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0821] Program processing flow

[0822] Step 1: Detecting a disaster and issuing a command to launch a drone

[0823] Description: When a user confirms that a disaster has occurred, the server immediately sends activation commands to multiple autonomous flying devices (drones).

[0824] Input: Disaster occurrence detection data (obtained from sensor networks or external APIs)

[0825] Data processing and calculation: Receiving and analyzing disaster information

[0826] Output: Start command to drone

[0827] Specific operation: The user confirms the occurrence of a disaster on the system, and the server sends a start-up command to the drone, including coordinate information of the affected area. For example, when the server confirms the occurrence of a disaster, it issues a start-up command to the drone, including coordinate information (center of City A).

[0828] Step 2: Collecting information using drones

[0829] Description: The device (drone) heads to the designated disaster area and collects video and sensor data in real time.

[0830] Input: Drone launch command and coordinate information of the affected area

[0831] Data processing and computation: Autonomous flight control and sensor data collection

[0832] Output: Collected video and sensor data

[0833] Specific operation: Once the drone reaches the designated disaster area, it uses its onboard camera and sensor devices to collect video footage and data such as temperature, humidity, and gas concentration in real time, and transmits the data to a server.

[0834] Step 3: Data analysis and rescue route calculation

[0835] Description: The server passes the data received from the drone to the generative AI model, which analyzes the damage situation.

[0836] Input: Video data and sensor data transmitted from the drone

[0837] Data Processing and Computation: Disaster Situation Analysis Using Generative AI Models

[0838] Output: Analysis results (number of collapsed buildings, location of victims, presence or absence of fire or heat source, etc.)

[0839] Specific operation: The server inputs the received data into the generative AI model and analyzes the damage situation (e.g., the collapsed status of multiple buildings, the location of victims, the location of the fire, etc.). Based on the analysis results, the server calculates the optimal rescue point and safe rescue route.

[0840] Step 4: Provide information to relief agencies and medical institutions

[0841] Description: The server provides rescue routes calculated based on the analysis results to rescue organizations and medical institutions.

[0842] Input: Analysis results of the generative AI model (optimal rescue location and route)

[0843] Data processing and calculation: Optimization and notification of rescue routes

[0844] Output: Providing information to relief agencies and medical institutions

[0845] Specific operation: The server uses the analysis results to calculate the optimal rescue route and transmits that information to rescue teams and hospitals in real time. For example, the server transmits the optimal rescue route and rescue location information to the rescue team's tablet device.

[0846] Step 5: Calculate and order supplies

[0847] Description: The server calculates the type and amount of supplies needed based on situational data from the disaster area and sends route instructions to the transport drone.

[0848] Input: Situation data of the affected area and analysis results

[0849] Data processing and calculation: Calculation of the type and amount of supplies needed

[0850] Output: Route instructions for the transport drone

[0851] Specific operation: Based on the analysis results, the server calculates the amount of food, water, and medical supplies needed, and transmits this information to a delivery drone to transport the supplies along a specified route. For example, the server calculates the amount of supplies needed based on the number of disaster victims in an evacuation shelter and transmits this information to the delivery drone.

[0852] Step 6: Securing communications infrastructure

[0853] Description: The server will move a drone with communication capabilities to a specific location to secure a temporary communication relay point.

[0854] Input: Communication infrastructure status data

[0855] Data processing and calculation: Calculation to secure communication relay points

[0856] Output: Position instructions to communication drone

[0857] Specific operation: To cover areas where communication has been cut off, the server sends instructions to communication relay drones to move to specific locations and secure communication relay points. For example, the server analyzes the communication situation in the affected area and transmits location information to drones that provide communication signals at high altitudes.

[0858] Step 7: Emotional analysis and psychological support

[0859] Description: The server uses an emotion engine to analyze the facial expression data of the victim and identify their emotional state.

[0860] Input: Facial expression data (collected by drone)

[0861] Data Processing and Computation: Emotion Analysis with Emotion Engine

[0862] Output: Identification of locations where psychological support is needed

[0863] Specific operation: The server inputs facial expression data into the emotion engine and analyzes the emotional state of the victim. Based on the results, it notifies medical institutions where psychological support is needed. For example, it identifies victims who are anxious or panicked and conveys that information to the medical team.

[0864] This enables the system to quickly and efficiently collect and analyze information, secure communication infrastructure, calculate and transport necessary supplies, and provide psychological support to disaster victims.

[0865] (Application example 2)

[0866] 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."

[0867] When it comes to fast and efficient rescue operations and support for victims in the event of a disaster, as well as efficient inventory management at logistics centers, conventional systems have faced challenges such as delays in information collection and analysis, difficulty in securing communication infrastructure, and a lack of mental care for workers.

[0868] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for flying an autonomous flight device to a designated disaster area and collecting video data and environmental data in real time; a generative artificial intelligence means for analyzing the collected video data and environmental data; means for calculating optimal material transportation routes and efficient inventory management means based on the analysis results and providing them to management agencies and rescue agencies; means for temporarily securing communication infrastructure using the autonomous flight device and restoring data communication; and means for capturing facial expressions of workers using the autonomous flight device or a fixed camera and providing psychological support using an emotion analysis engine. This enables fast and efficient information collection and analysis at disaster sites and logistics centers, enabling optimal rescue operations, inventory management, and psychological care for workers.

[0869] An "autonomous flying device" is an unmanned aerial vehicle that flies autonomously to a designated location and collects data in real time.

[0870] "Video data" refers to real-time video information acquired by an autonomous flying device or a fixed camera.

[0871] "Environmental data" refers to environmental information such as temperature, humidity, and air pressure collected by sensors on an autonomous flight device.

[0872] The "generative artificial intelligence means" is an artificial intelligence system that analyzes collected image data and environmental data and determines the situation and necessary response.

[0873] The "emotion analysis engine" is an analysis system that analyzes facial expression data of workers and disaster victims to identify their emotional state.

[0874] "Communications infrastructure" refers to network equipment that enables data exchange.

[0875] "Disaster area" means an area that has been affected by a disaster.

[0876] A "logistics center" is a facility that stores, manages, and distributes goods.

[0877] A "relief organization" is an organization or group that carries out relief activities in the event of a disaster.

[0878] "Management agency" means the organization or body that operates and manages the logistics center.

[0879] A "materials transport route" is a route for efficiently transporting materials.

[0880] "Inventory management means" refers to a system and method for efficiently managing inventory within a distribution center.

[0881] The present invention provides a system that enables prompt and efficient information collection and analysis in the event of a disaster or at a logistics center, enabling optimal responses. The detailed configuration and operation of the system are described below.

[0882] System configuration

[0883] The system consists of the following main components:

[0884] 1. Autonomous flying devices (drones)

[0885] 2. Server (for data analysis)

[0886] 3. Sentiment Analysis Engine

[0887] 4. Linkage device with rescue / medical institutions and logistics management organizations

[0888] 5. Communication infrastructure securing equipment

[0889] Hardware and software used

[0890] Drone: An unmanned aerial vehicle that flies autonomously to a designated location and collects video and environmental data in real time.

[0891] Server: AWS EC2 instance used for data analysis

[0892] Generative AI method: Uses a generative AI model (e.g., OpenAI GPT-4)

[0893] Sentiment analysis engine: Affectiva

[0894] Collaborative software: Python, TensorFlow, Flask

[0895] How it works

[0896] 1. Information gathering

[0897] The drones fly to designated locations in disaster situations or within logistics centers, using cameras and sensors to collect real-time video and environmental data, which is then sent to a server in real time.

[0898] 2. Data Analysis

[0899] The server inputs the received video data and environmental data into a generative AI model for analysis. The generative AI performs a detailed analysis of the damage situation and the inventory status of the logistics center, extracting important information such as the number of collapsed buildings, the location of victims, the presence or absence of fires or heat sources, and the location and quantity of inventory. Based on the results of this analysis, it calculates the optimal rescue points and supply transport routes.

[0900] 3. Securing communication infrastructure

[0901] Drones equipped with communication capabilities will set up communication relay points in disaster-stricken areas and logistics centers, securing temporary communication infrastructure, which will restore data communication and enable collaboration with servers and information sharing.

[0902] 4. Emotion analysis and psychological support

[0903] Drones or fixed cameras capture the facial expressions of workers and victims, which are then analyzed using an emotion analysis engine. Based on the results of this analysis, necessary psychological support is provided. If a worker is in a state of high stress, a notification is sent to the manager, urging them to take appropriate action.

[0904] Specific examples

[0905] When a disaster occurs: Drones fly over the affected area and collect information on the damage in real time. This information is analyzed by a generative AI model to determine rescue routes and routes for transporting supplies. If necessary, communication relay drones fly to secure the communications infrastructure.

[0906] Logistics Center: Drones monitor inventory in logistics centers, and generative AI identifies shortages and areas that need restocking. In addition, an emotion analysis engine monitors the psychological state of workers and notifies managers if they are feeling stressed.

[0907] Example prompt sentence:

[0908] Get a real-time view of your inventory and calculate the best route.

[0909] Analyze the emotional state of workers based on facial expression data and notify them if there are any abnormalities.

[0910] In this way, this system aims to solve comprehensive problems by enabling rapid response in the event of a disaster, efficient management at logistics centers, and also providing psychological care for workers.

[0911] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0912] Step 1:

[0913] Drone launch and information gathering

[0914] The server activates an autonomous flight device (drone) to collect information on disasters and within the logistics center. The server transmits coordinate information of a specified location (a specific point in the disaster area or logistics center) to the drone. The drone begins flying and collects video data and environmental data (temperature, humidity, air pressure, etc.) in real time. This data is then transmitted to the server in real time.

[0915] Input: Coordinate information of the disaster site and logistics center

[0916] Output: Real-time video and environmental data

[0917] Specific operations: Data collection using drone cameras and sensors, real-time flight control of drones

[0918] Step 2:

[0919] Receiving and storing data

[0920] The server receives the video and environmental data transmitted from the drone and stores it in a database, where it is temporarily saved for analysis.

[0921] Input: Real-time video and environmental data transmitted from the drone

[0922] Output: Video and environmental data stored in a database

[0923] Specific operation: Receiving data on the server side and writing it to the database

[0924] Step 3:

[0925] Data analysis

[0926] The server inputs the stored video data and environmental data into a generative AI model, which then performs a detailed analysis of the damage and inventory status and extracts important information (e.g., the number of collapsed buildings, the locations of victims, the presence or absence of fires or heat sources, and the location and quantity of inventory).

[0927] Input: Video and environmental data stored in a database

[0928] Output: Important parsed information

[0929] Specific behavior: Data analysis and extraction of important information using generative AI

[0930] Step 4:

[0931] Rescue and transport route calculations

[0932] The server calculates optimal rescue locations and routes for transporting supplies based on the analysis results obtained from the generative AI model. This route information is provided to rescue organizations and logistics management organizations, enabling rapid response.

[0933] Input: Analysis results obtained from the generative AI model

[0934] Output: Optimal rescue and supply routes

[0935] Specific operations: Applying route calculation algorithms, notifying rescue and logistics agencies

[0936] Step 5:

[0937] Securing communication infrastructure

[0938] To secure the communications infrastructure, the server activates drones equipped with communications capabilities and flies them to designated locations, establishing temporary communications relay points that enable data communication within disaster-stricken areas and logistics centers.

[0939] Input: Drone flight instructions and coordinate information of the specified point

[0940] Output: Secured communications infrastructure

[0941] Specific operations: Starting and flying a drone with communication capabilities, setting up a communication relay point

[0942] Step 6:

[0943] Emotion analysis and psychological support

[0944] The server receives facial expression data of workers and disaster victims sent from drones or fixed cameras and inputs it into an emotion analysis engine. The emotion analysis engine identifies their emotional state and identifies individuals who need psychological support. The server notifies administrators of this information and encourages appropriate psychological care.

[0945] Input: Facial expression data of workers and victims

[0946] Output: Identified emotional state and necessary support information

[0947] Specific actions: Data analysis using sentiment analysis engine, notification to administrator

[0948] As a result, the system of the present invention realizes a rapid response in the event of a disaster and efficient management at the logistics center. Furthermore, it aims to provide comprehensive problem-solving by providing psychological care for workers and disaster victims.

[0949] 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.

[0950] 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.

[0951] 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.

[0952] [Third embodiment]

[0953] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0954] 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.

[0955] 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).

[0956] 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.

[0957] 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.

[0958] 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).

[0959] 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.

[0960] 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.

[0961] 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.

[0962] 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.

[0963] 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.

[0964] 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."

[0965] The present invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones) with generative AI technology to carry out disaster relief activities quickly and efficiently. The system of the present invention mainly collects and analyzes information when a disaster occurs, optimizes rescue routes, secures communication infrastructure, and carries out rescue activities. The following describes the overall configuration of the system and the operation of each part.

[0966] System configuration

[0967] The system consists of four main parts:

[0968] 1. Information gathering devices (drones)

[0969] 2. Data analysis device (server)

[0970] 3. Server for linking with rescue and medical institutions

[0971] 4. Communication infrastructure securing device (drone)

[0972] Program for carrying out the invention

[0973] Drone launch and information gathering

[0974] When a disaster occurs, the server immediately sends instructions to launch a fleet of drones. The drones begin flying toward the designated disaster area and collect video and sensor data in real time. This data is then sent from the drones to the server. For example, if a major earthquake occurs, the server sends the coordinates of the disaster area to the drones, who then depart for that location.

[0975] Real-time data analysis and rescue route calculation

[0976] The server receives real-time video data sent from the drone and passes it to the generation AI for analysis. The generation AI analyzes the damage situation in detail and extracts important information such as the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions. As a specific example, the server identifies the building with the most damage among multiple collapsed buildings and provides rescue teams with safe routes around it.

[0977] Calculating necessary supplies

[0978] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drone for delivering the supplies. For example, it calculates the amount of food, water, and medicine needed based on the number and health condition of the victims gathered at evacuation centers and sends this information to the delivery drone.

[0979] Securing communications infrastructure and relief efforts

[0980] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points. This will restore data communications within the affected area and maintain connections with servers and relief organizations. As a specific example, a communications relay drone will fly over a disaster-stricken area where communications have been cut off, maintaining its altitude to provide communications signals.

[0981] Implementing and following up on relief efforts

[0982] Identifying unrescue locations, checking the health of victims, and maintaining public order are also important functions of this system. Based on the analysis results of the generated AI, the server identifies unrescue locations and directs a group of drones to carry out rescue operations. It also checks the health of victims and provides necessary medical assistance. As a specific example, drones fly over the affected area, remotely measuring the body temperature and heart rate of victims, and immediately dispatching rescue teams to victims in urgent need.

[0983] With such a system configuration and operation, the present invention can realize rapid and effective rescue operations in the event of a disaster.

[0984] The processing flow will be explained below.

[0985] Step 1:

[0986] Server: Upon receiving information about a disaster, it immediately launches multiple drones and sends them commands to fly towards the designated disaster area.

[0987] Example: An earthquake occurs and the server sends a departure command to each drone.

[0988] Step 2:

[0989] Drones: Fly to designated disaster areas to collect real-time video and sensor data. The drones perform a series of flight patterns to ensure comprehensive coverage of the disaster area.

[0990] Example: Drones can capture images of debris and road damage from the sky, and temperature sensors can detect fires.

[0991] Step 3:

[0992] Drone: Collected video and sensor data is sent to a server via 4G / 5G networks or dedicated wireless communication protocols.

[0993] Example: A drone uploads data to a server in real time.

[0994] Step 4:

[0995] Server: Passes the received data to the generation AI, which analyzes the damage situation in detail. The generation AI uses image recognition technology to identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources, and extracts important information.

[0996] Example: Generative AI analyzes video footage and displays the coordinates of collapsed buildings and fire sites on a map.

[0997] Step 5:

[0998] Server: Based on the analysis results of the generation AI, it calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions.

[0999] Example: The server identifies the most affected areas and sends their coordinates and rescue routes to rescue teams.

[1000] Step 6:

[1001] Server: Analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to drones delivering supplies.

[1002] Example: Calculate the amount of food, water, and medicine needed at a shelter and communicate that information to a delivery drone.

[1003] Step 7:

[1004] Drones: Drones equipped with communication capabilities will fly to designated locations and establish temporary communication relay points, thereby temporarily restoring communication infrastructure in the affected areas.

[1005] Example: A communications drone hovers over the affected area and provides a communications signal.

[1006] Step 8:

[1007] Server: Based on the analysis results of the generated AI and real-time data, it identifies unrescue locations and directs a group of drones to carry out rescue operations.

[1008] Example: A drone continuously collects images of unrescue areas identified by the server and updates the information.

[1009] Step 9:

[1010] Drones: Guide victims to safe evacuation sites and deliver necessary emergency supplies. They may also use voice guidance and LED displays to show the route.

[1011] Example: The drone will provide voice guidance to indicate evacuation routes and use LED lights to show evacuation routes even at night.

[1012] This will enable the system to carry out rapid and effective disaster relief efforts in affected areas.

[1013] Example 1

[1014] 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."

[1015] Conventional disaster relief systems had the problem of making it difficult to carry out relief activities quickly and efficiently, resulting in the time it took to rescue victims. Furthermore, due to insufficient understanding of the situation in the affected areas and insufficient communication infrastructure, the transmission of information regarding relief activities was often delayed. Furthermore, due to a lack of means to accurately grasp the amount and type of supplies needed, the supply of supplies was delayed, and in some cases appropriate support was not provided in line with the needs of the victims.

[1016] 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.

[1017] In this invention, the server includes means for flying multiple autonomous flight devices to designated disaster areas and collecting video data and environmental data in real time, a generating artificial intelligence means for analyzing the collected video data and environmental data, a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions, a means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices, and a means for identifying unrescue points, maintaining public order, checking the health of victims, guiding them to evacuation sites, and calculating and issuing transport instructions for necessary supplies. This enables rapid and efficient rescue operations, understanding the situation in the disaster area, securing communication infrastructure, and supplying appropriate supplies.

[1018] An "autonomous flying device" is an unmanned aerial vehicle that can fly by remote control or automatic control.

[1019] "Video data" refers to visual information collected by a video capture device such as a camera or video recorder.

[1020] "Environmental data" is data obtained from sensors that measure environmental parameters such as temperature, humidity, gas concentration, and radiation levels.

[1021] "Generative artificial intelligence means" refers to an artificial intelligence system that has the ability to analyze large amounts of data and automatically generate specific patterns or information.

[1022] "Rescue point" refers to a location within a disaster area where rescue is particularly needed.

[1023] A "rescue route" refers to a route that can be traveled safely and efficiently when carrying out rescue operations.

[1024] "Communications infrastructure" refers to the entire hardware and software that make up a communications network.

[1025] A "communication relay point" is a base that relays communication signals, and is a point that is installed to expand the communication range or to deal with sudden communication interruptions.

[1026] "Unrescue points" refer to locations within the disaster area where rescue efforts have not yet begun.

[1027] "Maintaining public order" refers to activities to ensure safety and maintain order at the scene of a disaster.

[1028] "Health assessment of disaster victims" is the process of assessing the physical condition and medical condition of disaster victims and determining the medical assistance they require.

[1029] An "evacuation site" refers to a safe place designated for temporary evacuation of disaster victims in the event of a disaster.

[1030] "Necessary supplies" refers to basic necessities such as food, water, and medicine that disaster victims need during relief efforts.

[1031] A "materials transport order" is an order to transport needed materials to a specific location.

[1032] "Real-time" refers to data being processed and used as soon as it is generated.

[1033] This invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones) with generative AI technology to carry out disaster relief activities quickly and efficiently. The system of this invention mainly collects and analyzes information when a disaster occurs, calculates rescue routes, secures communication infrastructure, and carries out relief activities.

[1034] System configuration

[1035] The system consists of four main parts:

[1036] 1. Information gathering devices (drones)

[1037] 2. Data analysis device (server)

[1038] 3. Server for linking with rescue and medical institutions

[1039] 4. Communication infrastructure securing device (drone)

[1040] Drone launch and information gathering

[1041] When a disaster occurs, the server immediately sends instructions to activate a fleet of drones, which begin flying toward the designated disaster area and collecting real-time video and sensor data, which is then transmitted from the drones to the server.

[1042] Examples:

[1043] In the event of a major earthquake, the server will send coordinate information of the affected area to the drone, and the drone will then depart for that location.

[1044] Real-time data analysis and rescue route calculation

[1045] The server receives real-time video data sent from the drone and passes it to the AI ​​generator for analysis. The AI ​​generator performs a detailed analysis of the damage situation and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions.

[1046] Examples:

[1047] The server identifies the building that suffered the most damage among several collapsed buildings and provides rescue teams with safe routes around it.

[1048] Calculating necessary supplies

[1049] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drones for delivering the supplies.

[1050] Examples:

[1051] Taking into account the number of disaster victims gathered at the evacuation center and their health condition, the system calculates the amount of food, water, and medicine needed and transmits this information to the transport drone.

[1052] Securing communications infrastructure and relief efforts

[1053] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points, restoring data communications within the affected area and maintaining connections with servers and relief organizations.

[1054] Examples:

[1055] Communication relay drones fly over disaster-stricken areas where communications have been cut off, maintaining altitude to provide communication signals.

[1056] Implementing and following up on relief efforts

[1057] Identifying unrescue locations, checking the health of victims, and maintaining public order are also important functions of this system. Based on the analysis results of the generated AI, the server identifies unrescue locations and directs drones to carry out rescue operations. It also checks the health of victims and provides necessary medical assistance.

[1058] Examples:

[1059] The drones fly over the affected areas, remotely measuring the body temperature and heart rate of victims, and rescue teams are immediately dispatched to those in urgent need.

[1060] Prompt Sentence Examples

[1061] Here are some examples of specific prompts for a generative AI model:

[1062] 1. Prompt for analyzing video data from the disaster area:

[1063] Next, analyze the video data provided to determine the number of collapsed buildings, the location of victims, and whether there were any fires or heat sources.

[1064] 2. Prompt to assess the victim's health:

[1065] Please use the following sensor data to measure the victim's body temperature and heart rate and identify those in need of emergency assistance.

[1066] With this system configuration and specific operation, the present invention can realize rapid and effective rescue operations in the event of a disaster.

[1067] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1068] Step 1:

[1069] The server that detects the occurrence of a disaster sends an instruction to activate the drones.

[1070] Input: Disaster occurrence detection data (e.g., earthquake occurrence notification)

[1071] Data processing / calculation: The server obtains coordinate data of the disaster site and executes the drone activation protocol.

[1072] Output: Commands to launch drones and coordinates of the affected area

[1073] Specific behavior:

[1074] The server automatically receives notification of a disaster and sends the coordinates of the affected area to the drone, which then prepares to fly to the specified location.

[1075] Step 2:

[1076] Based on the transmitted coordinate information, the drone begins flying toward the affected area and collects video and sensor data in real time.

[1077] Input: Coordinate information of affected area

[1078] Data processing / computation: The drone activates its cameras and sensors to collect video and environmental data of the designated area.

[1079] Output: Collected video and sensor data

[1080] Specific behavior:

[1081] The drone flies to specified coordinates, captures real-time footage with a high-resolution camera, and uses sensors to measure environmental data such as temperature and gas concentrations.

[1082] Step 3:

[1083] The collected data is sent to the server in real time.

[1084] Input: Video and sensor data

[1085] Data processing / calculation: The drone transmits the collected data to a server via wireless communication.

[1086] Output: Video data and sensor data uploaded to the server

[1087] Specific behavior:

[1088] The drone wirelessly transmits real-time video and sensor data to a server, which then receives the data.

[1089] Step 4:

[1090] The server passes the received data to the generative AI model for analysis.

[1091] Input: Video data and sensor data sent to the server

[1092] Data processing / calculation: A generative AI model analyzes the data and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fire or heat sources.

[1093] Output: Analysis results of the damage situation

[1094] Specific behavior:

[1095] The server inputs the received data into a generative AI model, and the AI ​​analyzes the data to gain a detailed understanding of the situation in the affected areas.

[1096] Step 5:

[1097] The server calculates the optimal rescue point and safe rescue route based on the analysis results of the generated AI model.

[1098] Input: Analysis results of the damage situation

[1099] Data processing / calculation: The server runs an algorithm based on the analysis results to calculate the optimal rescue point and safe route.

[1100] Output: Rescue location and rescue route information

[1101] Specific behavior:

[1102] The server calculates safe and efficient rescue routes based on the locations of collapsed buildings and victims, and provides them to rescue agencies.

[1103] Step 6:

[1104] The server analyzes detailed data on the affected area and calculates the types and quantities of medical supplies and relief goods needed.

[1105] Input: Detailed data of the affected area

[1106] Data processing / calculation: The server analyzes the number of people, their health status, and the damage situation, and determines the type and amount of supplies needed.

[1107] Output: List of required supplies

[1108] Specific behavior:

[1109] The server calculates and lists the quantities of food, water, and medicine needed based on data on disaster victims gathered at evacuation centers.

[1110] Step 7:

[1111] The server sends instructions to the drone on the route to transport the necessary supplies.

[1112] Input: List of required supplies and destination coordinates

[1113] Data processing / calculation: The server calculates the optimal route for transporting supplies and sends those instructions to the drone.

[1114] Output: Delivery route instructions for drone

[1115] Specific behavior:

[1116] The server indicates to the drone the specific flight route to carry the necessary supplies, and the drone then transports the supplies along that route.

[1117] Step 8:

[1118] If communication infrastructure is destroyed, drones equipped with communication capabilities will move to designated locations and function as communication relay points.

[1119] Input: Communication status data for affected areas

[1120] Data processing / calculation: The server identifies the area where communication has been lost and instructs the communication drone to move to that area.

[1121] Output: Communication infrastructure restored

[1122] Specific behavior:

[1123] Based on instructions from the server, drones equipped with communication capabilities will provide communication relay points over the affected area, temporarily restoring the communication network.

[1124] Step 9:

[1125] Based on the analysis results of the generated AI model, the server identifies unrescue locations and instructs a group of drones to carry out rescue operations.

[1126] Input: Analysis results of the generative AI model

[1127] Data processing / calculation: The server identifies unrescue locations that require rescue operations and issues instructions to the drones.

[1128] Output: Rescue operation instructions

[1129] Specific behavior:

[1130] The drones will fly to unrescue locations, remotely measure the temperature and heart rate of victims, and provide necessary medical assistance.

[1131] The above are the specific processing steps and detailed operations in the system program.

[1132] (Application example 1)

[1133] 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."

[1134] Conventional disaster relief systems have had difficulty quickly and efficiently grasping the situation in disaster-stricken areas and taking appropriate action. They also have issues with delays in sharing information and issuing instructions for rescue operations when communication infrastructure is destroyed. Furthermore, even with standard security monitoring, anomaly detection is not performed in real time, making it difficult to respond quickly.

[1135] 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.

[1136] In this invention, the server includes a means for flying the autonomous flight device to a designated disaster area and collecting video data in real time, a generating artificial intelligence means for analyzing the collected video data, and a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions. This makes it possible to quickly collect and analyze information in the event of a disaster and provide optimal rescue routes.

[1137] Furthermore, it includes a means for temporarily securing communication infrastructure in disaster-stricken areas using autonomous flight devices, and a means for identifying unrescue locations, maintaining public order, checking the health of disaster victims, and guiding them to evacuation sites. This allows for the continuation of information sharing and instructions for rescue operations even if communication infrastructure is destroyed.

[1138] In addition, it includes a means for collecting security monitoring data in real time during operation, detecting anomalies using a generative AI model, and a means for securing communication relay points even in areas with unstable communication infrastructure based on the detection results, which enables rapid anomaly detection and response even in normal security monitoring.

[1139] An "autonomous flight device" is an unmanned aerial vehicle that flies autonomously according to pre-programmed instructions and collects video and sensor data.

[1140] "Generative AI" is an artificial intelligence technology that analyzes collected data and generates and provides necessary information.

[1141] A "rescue route" is a route optimized for safe and rapid rescue operations.

[1142] "Sensor data" refers to physical data such as temperature, humidity, vibration, and pressure obtained from drones and other sensor devices.

[1143] "Anomaly detection" is the process of detecting abnormal situations or behaviors that deviate from normal conditions.

[1144] "Telecommunications infrastructure" refers to the physical and software systems that create telecommunications networks and enable the transmission and reception of data.

[1145] A "communication relay point" is an intermediate point that temporarily relays communications in an area where communications have been cut off, ensuring network connectivity.

[1146] A "generative AI model" is a type of artificial intelligence that generates new information and data patterns based on large amounts of data.

[1147] A "prompt sentence" is an input sentence used to give instructions to a generative AI model.

[1148] "Security surveillance data" refers to video, audio, sensor, and other data collected in real time to ensure the safety of a specific area.

[1149] "Disaster situation" refers to the state of damage in the area where the disaster occurred, including the number of collapsed buildings, the location of victims, and the presence or absence of fires or heat sources.

[1150] An "embodiment" is a form showing how the invention is specifically carried out.

[1151] This invention is a system that combines autonomous flight devices (drones) and generative AI technology to realize rapid and efficient rescue operations in the event of a disaster. The main components of this system are as follows:

[1152] System configuration

[1153] 1. Autonomous flying devices (drones)

[1154] 2. Generative artificial intelligence (AI) means

[1155] 3. Rescue route calculation method

[1156] 4. Measures to secure communications infrastructure

[1157] 5. Anomaly detection and notification methods

[1158] System Operation

[1159] Drone launch and information gathering

[1160] When a disaster occurs, the server immediately activates an autonomous flying device (drone) and has it fly toward the designated disaster area. The drone collects video and sensor data in real time and transmits the data to the server. In particular, the drone uses advanced sensor technology (temperature sensors, humidity sensors, etc.) to collect detailed data.

[1161] Real-time data analysis and rescue route calculation

[1162] The server passes the real-time video and sensor data transmitted from the drone to a generative AI model for analysis. Examples of generative AI models include OpenAI's GPT-4. This AI analyzes the collected data and identifies the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. It then calculates the optimal rescue points and safe rescue routes and provides this information to rescue organizations and medical institutions.

[1163] Calculation and instructions for necessary supplies

[1164] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drones for delivering the supplies. Selecting the appropriate route enables the rapid and efficient delivery of supplies.

[1165] Securing communication infrastructure

[1166] If communications infrastructure is destroyed, drones equipped with communications capabilities will move to designated locations and establish temporary communications relay points. Specifically, the drones will maintain altitude and transmit communications signals to support communications at the scene. This will restore data communications within the disaster area and maintain communication with servers and relief organizations.

[1167] Security monitoring and anomaly detection

[1168] Under normal circumstances, drones collect security monitoring data and use generative AI models to detect anomalies in real time. The analysis results are then immediately communicated to security personnel. Even in areas with unstable communications infrastructure, drones can function as communication relay points, ensuring stable data communication.

[1169] Specific examples

[1170] During nighttime security surveillance at a large commercial facility, if a drone detects a suspicious person entering the facility in real time, by inputting the prompt "Anomaly detection: Analyze video data, detect and report any anomalies" into the generative AI model, details of the anomaly will be immediately sent to the server. As a result, security personnel will receive an immediate notification of the anomaly via their smartphone or smart glasses, enabling them to respond promptly.

[1171] As described above, this system can be applied not only during disasters but also to normal security monitoring, enabling rapid and efficient responses through real-time data collection and analysis using generative AI.

[1172] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1173] Step 1:

[1174] When a disaster occurs, the server immediately activates an autonomous flying device (drone) and sends it off to the designated disaster area. The drone collects video and sensor data in real time. The input is coordinate information of the disaster area, and the output is real-time video and sensor data.

[1175] Step 2:

[1176] The collected video and sensor data is sent to a server, which receives the data and passes it to a generative AI model. The input is real-time video and sensor data, and the output is data that is analyzed by the generative AI model.

[1177] Step 3:

[1178] The server analyzes the collected data using a generative AI model. Specifically, the AI ​​model receives prompts to "analyze the damage situation, identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources," and obtains analysis results. This analysis includes pattern recognition in video and anomaly detection in sensor data. The inputs are prompts and raw data for the AI ​​model, and the output is the analysis results.

[1179] Step 4:

[1180] Based on the analysis results, the server calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions. The input is the analysis results, and the output is optimized rescue route information. Specifically, a route search algorithm is used to calculate the shortest and safest route.

[1181] Step 5:

[1182] The server calculates the type and amount of medical supplies and relief supplies needed and sends route instructions to the drones for delivering the supplies. The input is the number of people in the disaster area and health data, and the output is the delivery route and a list of supplies. A supply supply algorithm determines the amount of supplies needed at each location.

[1183] Step 6:

[1184] If communications infrastructure is destroyed, drones act as communication relay points to establish a temporary communications infrastructure. The input is the coordinate information of the communication-disrupted area, and the output is the area where a constant communication connection is ensured. Communications are stabilized using LoRa networks and other mesh network technologies.

[1185] Step 7:

[1186] Under normal circumstances, drones collect security surveillance data and use generative AI models to detect anomalies in real time. The results are then notified to security personnel. The input is real-time surveillance data, and the output is anomaly detection results and notification information. A specific prompt, "Anomaly detection: Analyze video data, detect anomalies, and report them," is used to prompt the AI ​​to perform analysis.

[1187] By combining these processing steps, this system enables multifunctional and highly efficient operations during disasters and normal security activities.

[1188] 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.

[1189] This invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones), generative AI technology, and an emotion engine to carry out disaster relief activities quickly and efficiently. The system of this invention collects and analyzes information when a disaster occurs, optimizes rescue routes, secures communication infrastructure, and provides psychological support through emotion analysis. The following describes the overall configuration of the system and the operation of each component.

[1190] System configuration

[1191] The system consists of five main parts:

[1192] 1. Information gathering devices (drones)

[1193] 2. Data analysis device (server)

[1194] 3. Emotion Engine

[1195] 4. Server for linking with rescue and medical institutions

[1196] 5. Communication infrastructure securing device (drone)

[1197] Program for carrying out the invention

[1198] Drone launch and information gathering

[1199] When a disaster occurs, the server immediately sends instructions to launch a fleet of drones. The drones begin flying toward the designated disaster area and collect video and sensor data in real time. This data is then sent from the drones to the server. For example, if a major earthquake occurs, the server sends the coordinates of the disaster area to the drones, who then depart for that location.

[1200] Real-time data analysis and rescue route calculation

[1201] The server receives real-time video data sent from the drone and passes it to the generation AI for analysis. The generation AI analyzes the damage situation in detail and extracts important information such as the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions. As a specific example, the server identifies the building with the most damage among multiple collapsed buildings and provides rescue teams with safe routes around it.

[1202] Calculating necessary supplies

[1203] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drone for delivering the supplies. For example, it calculates the amount of food, water, and medicine needed based on the number and health condition of the victims gathered at evacuation centers and sends this information to the delivery drone.

[1204] Securing communications infrastructure and relief efforts

[1205] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points. This will restore data communications within the affected area and maintain connections with servers and relief organizations. As a specific example, a communications relay drone will fly over a disaster-stricken area where communications have been cut off, maintaining its altitude to provide communications signals.

[1206] Emotion analysis and psychological support using an emotion engine

[1207] The server uses an emotion engine to analyze the facial expression data of victims collected by the drone and identify their emotional state. Based on the emotion engine's analysis results, it notifies rescue organizations and medical institutions of locations where psychological support is needed. In addition, even after communication infrastructure is restored, it continues to monitor the emotional state of victims in evacuation centers in real time, and notifies medical institutions if it detects abnormal stress or anxiety. For example, if a victim in an evacuation center becomes extremely anxious or panics, this information is quickly conveyed to the medical team, and the necessary support is provided.

[1208] With such a system configuration and operation, the present invention can realize rapid and effective relief activities in disaster areas and psychological care for disaster victims.

[1209] The processing flow will be explained below.

[1210] Step 1:

[1211] Server: Upon receiving information about a disaster, it immediately launches multiple drones and sends them commands to fly towards the designated disaster area.

[1212] Example: An earthquake occurs and the server sends a departure command to each drone.

[1213] Step 2:

[1214] Drones: Fly to designated disaster areas and collect real-time video and sensor data. Drones follow pre-set flight patterns to collect data over a wide area.

[1215] Example: Drones can capture images of debris and road damage from the sky, and temperature sensors can detect fires.

[1216] Step 3:

[1217] Drone: Collected video and sensor data is sent to a server via 4G / 5G networks or dedicated wireless communication protocols.

[1218] Example: A drone uploads data to a server in real time.

[1219] Step 4:

[1220] Server: Passes the received data to the generation AI, which analyzes the damage situation in detail. The generation AI uses image recognition technology to identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources, and extracts important information.

[1221] Example: Generative AI analyzes video footage and displays the coordinates of collapsed buildings and fire sites on a map.

[1222] Step 5:

[1223] Server: Based on the analysis results of the generation AI, it calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions.

[1224] Example: The server identifies the most affected areas and sends their coordinates and rescue routes to rescue teams.

[1225] Step 6:

[1226] Server: Analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to drones delivering supplies.

[1227] Example: Calculate the amount of food, water, and medicine needed at a shelter and communicate that information to a delivery drone.

[1228] Step 7:

[1229] Drones: Drones equipped with communication capabilities will fly to designated locations and establish temporary communication relay points, thereby temporarily restoring communication infrastructure in the affected areas.

[1230] Example: A communications drone hovers over the affected area and provides a communications signal.

[1231] Step 8:

[1232] Server: The emotion engine analyzes the facial expression data collected by the drone and identifies the emotional state of the victim. The emotion engine reads emotions such as anxiety, fear, and sadness from facial expressions.

[1233] Example: The emotion engine analyzes the facial expression data of a victim and determines that the victim is in a "high stress state."

[1234] Step 9:

[1235] Server: Based on the analysis results of the emotion engine, it notifies rescue organizations of locations where psychological assistance is needed, allowing psychological counseling and emergency psychological assistance to be provided promptly.

[1236] Example: The server sends an instruction to dispatch a psychological counselor to an evacuation site determined to be in a "high stress state."

[1237] Step 10:

[1238] Server: Even after the communication infrastructure is restored, the server monitors the emotional state of disaster victims in evacuation shelters in real time, and notifies medical institutions if it detects abnormal stress or anxiety.

[1239] Example: A server continuously monitors the emotional state of disaster victims in evacuation centers and sends an alert to medical teams if any abnormalities are detected.

[1240] Each processing step of this system enables rapid information gathering in disaster areas, ensuring the safety of victims, efficiently distributing relief supplies, and providing psychological care to victims.

[1241] Example 2

[1242] 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."

[1243] Conventional disaster relief systems have had problems with the collection and analysis of information, securing communication infrastructure, and providing psychological support to victims in a timely and efficient manner. Furthermore, the calculation and transportation of necessary supplies was ineffective, resulting in delayed responses to disaster victims.

[1244] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for flying multiple autonomous flight devices to a designated disaster area when a disaster occurs and collecting video data and sensor data in real time; a generating artificial intelligence means for analyzing the collected video data and sensor data; means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions; means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices; means for analyzing situation data in the disaster area to calculate the type and amount of supplies needed and sending route instructions to an autonomous flight device for delivery; and means for analyzing facial expression data of victims collected by the autonomous flight devices, identifying their emotional states, and providing psychological support. This enables rapid and efficient information collection and analysis, securing communication infrastructure, calculating and delivering needed supplies, and providing psychological support to victims.

[1245] A "disaster" is an abnormal phenomenon caused by natural phenomena or human factors that results in human injury or property damage.

[1246] An "autonomous flying device" is a device that performs a designated mission while flying itself based on pre-programmed instructions or instructions received in real time.

[1247] "Real-time" refers to situations in which data is collected and processed virtually immediately.

[1248] "Video data" refers to visual information acquired by a camera or other optical means.

[1249] "Sensor data" refers to data collected by a sensor that represents changes in physical quantities. Specifically, it includes information on temperature, humidity, air pressure, gas concentration, etc.

[1250] "Generative AI means" refers to a method or device that uses generative AI technology to analyze input data and extract and generate useful information.

[1251] "Rescue point" refers to a specific location within a disaster area where rescue operations should be carried out.

[1252] A "rescue route" refers to the optimal route for rescue teams to reach the rescue point safely and quickly.

[1253] "Communications infrastructure" refers to the hardware and software infrastructure required to conduct data communications.

[1254] "Supplies" refers to basic necessities and relief supplies such as food, medicine, and clothing needed to support disaster victims.

[1255] "Facial expression data" is data that captures a person's facial expressions and records their features and changes.

[1256] "Emotional state" refers to the results of analyzing and identifying the psychological reactions and emotional state of victims.

[1257] "Psychological support" refers to interventions and support activities aimed at reducing psychological stress and anxiety among disaster victims and supporting their mental health.

[1258] The system of the present invention combines multiple autonomous flying devices (hereinafter referred to as drones), generative artificial intelligence technology (generative AI model), and an emotion engine to realize rapid and efficient rescue operations in the event of a disaster. The system operates based on the following main components and their interactions:

[1259] System configuration

[1260] The system consists of five main parts:

[1261] 1. Information gathering devices (drones)

[1262] 2. Data analysis device (server)

[1263] 3. Emotion Engine

[1264] 4. Server for linking with rescue and medical institutions

[1265] 5. Communication infrastructure securing device (drone)

[1266] Information gathering device

[1267] In the event of a disaster, the server launches a fleet of drones and sends them to the affected area. The drones collect video and sensor data in real time and transmit that data to the server. For example, in the event of a major earthquake, the server sends coordinate information of the affected area to the drones, which then fly to that location and transmit the collected video and sensor data in real time.

[1268] Data analysis equipment

[1269] The server passes the received drone footage and sensor data to the generation AI for detailed analysis. The generation AI analyzes the damage situation and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fire or heat sources. This allows rescue points and routes to be optimized, and the information is provided to rescue organizations and medical institutions. For example, the server could identify the building with the most damage among multiple collapsed buildings and provide rescue teams with safe routes around it.

[1270] Calculating necessary supplies

[1271] The server uses the results of the analysis to analyze the situation in the affected area and calculate the type and amount of medical supplies and relief supplies needed. Based on this information, the server sends route instructions to the drone for delivering supplies. For example, the server calculates the necessary supplies and issues instructions, taking into account the number and health status of victims gathered at evacuation centers.

[1272] Securing communication infrastructure

[1273] In areas where communications have been cut off due to a disaster, the server will move drones equipped with communications capabilities to designated locations to establish temporary communications relay points. This will restore data communications within the affected area and maintain coordination with the server and relief organizations. For example, a communications relay drone will fly over a disaster area where communications have been cut off and provide communications signals.

[1274] Emotion Engine

[1275] The server uses an emotion engine to analyze the facial expression data of disaster victims collected by the drone and identify their emotional state. Based on this, it notifies rescue organizations and medical institutions of locations where psychological support is needed. It also monitors the emotional state of disaster victims in evacuation centers in real time and notifies medical institutions if it detects any abnormalities. For example, if a disaster victim in an evacuation center becomes extremely anxious or panicked, it will quickly convey that information to the medical team.

[1276] Prompt Sentence Examples

[1277] Below are some example prompts for each process in the event of a disaster:

[1278] "An earthquake has occurred. Fly a drone based on the coordinate information of the center of City A and collect video and sensor data."

[1279] "Use AI to analyze real-time video data from the disaster area, calculate the optimal rescue route, and provide it to rescue teams."

[1280] "Calculate the necessary medical supplies and relief supplies based on the situation at the evacuation center, and have delivery drones deliver them along the designated route."

[1281] "Send communications relay drones to areas where communications have been cut off and secure communications infrastructure."

[1282] "Analyze the emotional state of the victims and notify medical institutions so that necessary psychological care can be provided."

[1283] In this way, the present invention allows disaster relief efforts to be carried out quickly and efficiently, providing comprehensive assistance to victims.

[1284] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1285] Program processing flow

[1286] Step 1: Detecting a disaster and issuing a command to launch a drone

[1287] Description: When a user confirms that a disaster has occurred, the server immediately sends activation commands to multiple autonomous flying devices (drones).

[1288] Input: Disaster occurrence detection data (obtained from sensor networks or external APIs)

[1289] Data processing and calculation: Receiving and analyzing disaster information

[1290] Output: Start command to drone

[1291] Specific operation: The user confirms the occurrence of a disaster on the system, and the server sends a start-up command to the drone, including coordinate information of the affected area. For example, when the server confirms the occurrence of a disaster, it issues a start-up command to the drone, including coordinate information (center of City A).

[1292] Step 2: Collecting information using drones

[1293] Description: The device (drone) heads to the designated disaster area and collects video and sensor data in real time.

[1294] Input: Drone launch command and coordinate information of the affected area

[1295] Data processing and computation: Autonomous flight control and sensor data collection

[1296] Output: Collected video and sensor data

[1297] Specific operation: Once the drone reaches the designated disaster area, it uses its onboard camera and sensor devices to collect video footage and data such as temperature, humidity, and gas concentration in real time, and transmits the data to a server.

[1298] Step 3: Data analysis and rescue route calculation

[1299] Description: The server passes the data received from the drone to the generative AI model, which analyzes the damage situation.

[1300] Input: Video data and sensor data transmitted from the drone

[1301] Data Processing and Computation: Disaster Situation Analysis Using Generative AI Models

[1302] Output: Analysis results (number of collapsed buildings, location of victims, presence or absence of fire or heat source, etc.)

[1303] Specific operation: The server inputs the received data into the generative AI model and analyzes the damage situation (e.g., the collapsed status of multiple buildings, the location of victims, the location of the fire, etc.). Based on the analysis results, the server calculates the optimal rescue point and safe rescue route.

[1304] Step 4: Provide information to relief agencies and medical institutions

[1305] Description: The server provides rescue routes calculated based on the analysis results to rescue organizations and medical institutions.

[1306] Input: Analysis results of the generative AI model (optimal rescue location and route)

[1307] Data processing and calculation: Optimization and notification of rescue routes

[1308] Output: Providing information to relief agencies and medical institutions

[1309] Specific operation: The server uses the analysis results to calculate the optimal rescue route and transmits that information to rescue teams and hospitals in real time. For example, the server transmits the optimal rescue route and rescue location information to the rescue team's tablet device.

[1310] Step 5: Calculate and order supplies

[1311] Description: The server calculates the type and amount of supplies needed based on situational data from the disaster area and sends route instructions to the transport drone.

[1312] Input: Situation data of the affected area and analysis results

[1313] Data processing and calculation: Calculation of the type and amount of supplies needed

[1314] Output: Route instructions for the transport drone

[1315] Specific operation: Based on the analysis results, the server calculates the amount of food, water, and medical supplies needed, and transmits this information to a delivery drone to transport the supplies along a specified route. For example, the server calculates the amount of supplies needed based on the number of disaster victims in an evacuation shelter and transmits this information to the delivery drone.

[1316] Step 6: Securing communications infrastructure

[1317] Description: The server will move a drone with communication capabilities to a specific location to secure a temporary communication relay point.

[1318] Input: Communication infrastructure status data

[1319] Data processing and calculation: Calculation to secure communication relay points

[1320] Output: Position instructions to communication drone

[1321] Specific operation: To cover areas where communication has been cut off, the server sends instructions to communication relay drones to move to specific locations and secure communication relay points. For example, the server analyzes the communication situation in the affected area and transmits location information to drones that provide communication signals at high altitudes.

[1322] Step 7: Emotional analysis and psychological support

[1323] Description: The server uses an emotion engine to analyze the facial expression data of the victim and identify their emotional state.

[1324] Input: Facial expression data (collected by drone)

[1325] Data Processing and Computation: Emotion Analysis with Emotion Engine

[1326] Output: Identification of locations where psychological support is needed

[1327] Specific operation: The server inputs facial expression data into the emotion engine and analyzes the emotional state of the victim. Based on the results, it notifies medical institutions where psychological support is needed. For example, it identifies victims who are anxious or panicked and conveys that information to the medical team.

[1328] This enables the system to quickly and efficiently collect and analyze information, secure communication infrastructure, calculate and transport necessary supplies, and provide psychological support to disaster victims.

[1329] (Application example 2)

[1330] 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."

[1331] When it comes to fast and efficient rescue operations and support for victims in the event of a disaster, as well as efficient inventory management at logistics centers, conventional systems have faced challenges such as delays in information collection and analysis, difficulty in securing communication infrastructure, and a lack of mental care for workers.

[1332] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for flying an autonomous flight device to a designated disaster area and collecting video data and environmental data in real time; a generative artificial intelligence means for analyzing the collected video data and environmental data; means for calculating optimal material transportation routes and efficient inventory management means based on the analysis results and providing them to management agencies and rescue agencies; means for temporarily securing communication infrastructure using the autonomous flight device and restoring data communication; and means for capturing facial expressions of workers using the autonomous flight device or a fixed camera and providing psychological support using an emotion analysis engine. This enables fast and efficient information collection and analysis at disaster sites and logistics centers, enabling optimal rescue operations, inventory management, and psychological care for workers.

[1333] An "autonomous flying device" is an unmanned aerial vehicle that flies autonomously to a designated location and collects data in real time.

[1334] "Video data" refers to real-time video information acquired by an autonomous flying device or a fixed camera.

[1335] "Environmental data" refers to environmental information such as temperature, humidity, and air pressure collected by sensors on an autonomous flight device.

[1336] The "generative artificial intelligence means" is an artificial intelligence system that analyzes collected image data and environmental data and determines the situation and necessary response.

[1337] The "emotion analysis engine" is an analysis system that analyzes facial expression data of workers and disaster victims to identify their emotional state.

[1338] "Communications infrastructure" refers to network equipment that enables data exchange.

[1339] "Disaster area" means an area that has been affected by a disaster.

[1340] A "logistics center" is a facility that stores, manages, and distributes goods.

[1341] A "relief organization" is an organization or group that carries out relief activities in the event of a disaster.

[1342] "Management agency" means the organization or body that operates and manages the logistics center.

[1343] A "materials transport route" is a route for efficiently transporting materials.

[1344] "Inventory management means" refers to a system and method for efficiently managing inventory within a distribution center.

[1345] The present invention provides a system that enables prompt and efficient information collection and analysis in the event of a disaster or at a logistics center, enabling optimal responses. The detailed configuration and operation of the system are described below.

[1346] System configuration

[1347] The system consists of the following main components:

[1348] 1. Autonomous flying devices (drones)

[1349] 2. Server (for data analysis)

[1350] 3. Sentiment Analysis Engine

[1351] 4. Linkage device with rescue / medical institutions and logistics management organizations

[1352] 5. Communication infrastructure securing equipment

[1353] Hardware and software used

[1354] Drone: An unmanned aerial vehicle that flies autonomously to a designated location and collects video and environmental data in real time.

[1355] Server: AWS EC2 instance used for data analysis

[1356] Generative AI method: Uses a generative AI model (e.g., OpenAI GPT-4)

[1357] Sentiment analysis engine: Affectiva

[1358] Collaborative software: Python, TensorFlow, Flask

[1359] How it works

[1360] 1. Information gathering

[1361] The drones fly to designated locations in disaster situations or within logistics centers, using cameras and sensors to collect real-time video and environmental data, which is then sent to a server in real time.

[1362] 2. Data Analysis

[1363] The server inputs the received video data and environmental data into a generative AI model for analysis. The generative AI performs a detailed analysis of the damage situation and the inventory status of the logistics center, extracting important information such as the number of collapsed buildings, the location of victims, the presence or absence of fires or heat sources, and the location and quantity of inventory. Based on the results of this analysis, it calculates the optimal rescue points and supply transport routes.

[1364] 3. Securing communication infrastructure

[1365] Drones equipped with communication capabilities will set up communication relay points in disaster-stricken areas and logistics centers, securing temporary communication infrastructure, which will restore data communication and enable collaboration with servers and information sharing.

[1366] 4. Emotion analysis and psychological support

[1367] Drones or fixed cameras capture the facial expressions of workers and victims, which are then analyzed using an emotion analysis engine. Based on the results of this analysis, necessary psychological support is provided. If a worker is in a state of high stress, a notification is sent to the manager, urging them to take appropriate action.

[1368] Specific examples

[1369] When a disaster occurs: Drones fly over the affected area and collect information on the damage in real time. This information is analyzed by a generative AI model to determine rescue routes and routes for transporting supplies. If necessary, communication relay drones fly to secure the communications infrastructure.

[1370] Logistics Center: Drones monitor inventory in logistics centers, and generative AI identifies shortages and areas that need restocking. In addition, an emotion analysis engine monitors the psychological state of workers and notifies managers if they are feeling stressed.

[1371] Example prompt sentence:

[1372] Get a real-time view of your inventory and calculate the best route.

[1373] Analyze the emotional state of workers based on facial expression data and notify them if there are any abnormalities.

[1374] In this way, this system aims to solve comprehensive problems by enabling rapid response in the event of a disaster, efficient management at logistics centers, and also providing psychological care for workers.

[1375] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1376] Step 1:

[1377] Drone launch and information gathering

[1378] The server activates an autonomous flight device (drone) to collect information on disasters and within the logistics center. The server transmits coordinate information of a specified location (a specific point in the disaster area or logistics center) to the drone. The drone begins flying and collects video data and environmental data (temperature, humidity, air pressure, etc.) in real time. This data is then transmitted to the server in real time.

[1379] Input: Coordinate information of the disaster site and logistics center

[1380] Output: Real-time video and environmental data

[1381] Specific operations: Data collection using drone cameras and sensors, real-time flight control of drones

[1382] Step 2:

[1383] Receiving and storing data

[1384] The server receives the video and environmental data transmitted from the drone and stores it in a database, where it is temporarily saved for analysis.

[1385] Input: Real-time video and environmental data transmitted from the drone

[1386] Output: Video and environmental data stored in a database

[1387] Specific operation: Receiving data on the server side and writing it to the database

[1388] Step 3:

[1389] Data analysis

[1390] The server inputs the stored video data and environmental data into a generative AI model, which then performs a detailed analysis of the damage and inventory status and extracts important information (e.g., the number of collapsed buildings, the locations of victims, the presence or absence of fires or heat sources, and the location and quantity of inventory).

[1391] Input: Video and environmental data stored in a database

[1392] Output: Important parsed information

[1393] Specific behavior: Data analysis and extraction of important information using generative AI

[1394] Step 4:

[1395] Rescue and transport route calculations

[1396] The server calculates optimal rescue locations and routes for transporting supplies based on the analysis results obtained from the generative AI model. This route information is provided to rescue organizations and logistics management organizations, enabling rapid response.

[1397] Input: Analysis results obtained from the generative AI model

[1398] Output: Optimal rescue and supply routes

[1399] Specific operations: Applying route calculation algorithms, notifying rescue and logistics agencies

[1400] Step 5:

[1401] Securing communication infrastructure

[1402] To secure the communications infrastructure, the server activates drones equipped with communications capabilities and flies them to designated locations, establishing temporary communications relay points that enable data communication within disaster-stricken areas and logistics centers.

[1403] Input: Drone flight instructions and coordinate information of the specified point

[1404] Output: Secured communications infrastructure

[1405] Specific operations: Starting and flying a drone with communication capabilities, setting up a communication relay point

[1406] Step 6:

[1407] Emotion analysis and psychological support

[1408] The server receives facial expression data of workers and disaster victims sent from drones or fixed cameras and inputs it into an emotion analysis engine. The emotion analysis engine identifies their emotional state and identifies individuals who need psychological support. The server notifies administrators of this information and encourages appropriate psychological care.

[1409] Input: Facial expression data of workers and victims

[1410] Output: Identified emotional state and necessary support information

[1411] Specific actions: Data analysis using sentiment analysis engine, notification to administrator

[1412] As a result, the system of the present invention realizes a rapid response in the event of a disaster and efficient management at the logistics center. Furthermore, it aims to provide comprehensive problem-solving by providing psychological care for workers and disaster victims.

[1413] 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.

[1414] 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.

[1415] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1416] [Fourth embodiment]

[1417] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1418] 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.

[1419] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1420] 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.

[1421] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1422] 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).

[1423] 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.

[1424] 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.

[1425] 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.

[1426] 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.

[1427] 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.

[1428] 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.

[1429] 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."

[1430] The present invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones) with generative AI technology to carry out disaster relief activities quickly and efficiently. The system of the present invention mainly collects and analyzes information when a disaster occurs, optimizes rescue routes, secures communication infrastructure, and carries out rescue activities. The following describes the overall configuration of the system and the operation of each part.

[1431] System configuration

[1432] The system consists of four main parts:

[1433] 1. Information gathering devices (drones)

[1434] 2. Data analysis device (server)

[1435] 3. Server for linking with rescue and medical institutions

[1436] 4. Communication infrastructure securing device (drone)

[1437] Program for carrying out the invention

[1438] Drone launch and information gathering

[1439] When a disaster occurs, the server immediately sends instructions to launch a fleet of drones. The drones begin flying toward the designated disaster area and collect video and sensor data in real time. This data is then sent from the drones to the server. For example, if a major earthquake occurs, the server sends the coordinates of the disaster area to the drones, who then depart for that location.

[1440] Real-time data analysis and rescue route calculation

[1441] The server receives real-time video data sent from the drone and passes it to the generation AI for analysis. The generation AI analyzes the damage situation in detail and extracts important information such as the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions. As a specific example, the server identifies the building with the most damage among multiple collapsed buildings and provides rescue teams with safe routes around it.

[1442] Calculating necessary supplies

[1443] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drone for delivering the supplies. For example, it calculates the amount of food, water, and medicine needed based on the number and health condition of the victims gathered at evacuation centers and sends this information to the delivery drone.

[1444] Securing communications infrastructure and relief efforts

[1445] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points. This will restore data communications within the affected area and maintain connections with servers and relief organizations. As a specific example, a communications relay drone will fly over a disaster-stricken area where communications have been cut off, maintaining its altitude to provide communications signals.

[1446] Implementing and following up on relief efforts

[1447] Identifying unrescue locations, checking the health of victims, and maintaining public order are also important functions of this system. Based on the analysis results of the generated AI, the server identifies unrescue locations and directs a group of drones to carry out rescue operations. It also checks the health of victims and provides necessary medical assistance. As a specific example, drones fly over the affected area, remotely measuring the body temperature and heart rate of victims, and immediately dispatching rescue teams to victims in urgent need.

[1448] With such a system configuration and operation, the present invention can realize rapid and effective rescue operations in the event of a disaster.

[1449] The processing flow will be explained below.

[1450] Step 1:

[1451] Server: Upon receiving information about a disaster, it immediately launches multiple drones and sends them commands to fly towards the designated disaster area.

[1452] Example: An earthquake occurs and the server sends a departure command to each drone.

[1453] Step 2:

[1454] Drones: Fly to designated disaster areas to collect real-time video and sensor data. The drones perform a series of flight patterns to ensure comprehensive coverage of the disaster area.

[1455] Example: Drones can capture images of debris and road damage from the sky, and temperature sensors can detect fires.

[1456] Step 3:

[1457] Drone: Collected video and sensor data is sent to a server via 4G / 5G networks or dedicated wireless communication protocols.

[1458] Example: A drone uploads data to a server in real time.

[1459] Step 4:

[1460] Server: Passes the received data to the generation AI, which analyzes the damage situation in detail. The generation AI uses image recognition technology to identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources, and extracts important information.

[1461] Example: Generative AI analyzes video footage and displays the coordinates of collapsed buildings and fire sites on a map.

[1462] Step 5:

[1463] Server: Based on the analysis results of the generation AI, it calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions.

[1464] Example: The server identifies the most affected areas and sends their coordinates and rescue routes to rescue teams.

[1465] Step 6:

[1466] Server: Analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to drones delivering supplies.

[1467] Example: Calculate the amount of food, water, and medicine needed at a shelter and communicate that information to a delivery drone.

[1468] Step 7:

[1469] Drones: Drones equipped with communication capabilities will fly to designated locations and establish temporary communication relay points, thereby temporarily restoring communication infrastructure in the affected areas.

[1470] Example: A communications drone hovers over the affected area and provides a communications signal.

[1471] Step 8:

[1472] Server: Based on the analysis results of the generated AI and real-time data, it identifies unrescue locations and directs a group of drones to carry out rescue operations.

[1473] Example: A drone continuously collects images of unrescue areas identified by the server and updates the information.

[1474] Step 9:

[1475] Drones: Guide victims to safe evacuation sites and deliver necessary emergency supplies. They may also use voice guidance and LED displays to show the route.

[1476] Example: The drone will provide voice guidance to indicate evacuation routes and use LED lights to show evacuation routes even at night.

[1477] This will enable the system to carry out rapid and effective disaster relief efforts in affected areas.

[1478] Example 1

[1479] 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."

[1480] Conventional disaster relief systems had the problem of making it difficult to carry out relief activities quickly and efficiently, resulting in the time it took to rescue victims. Furthermore, due to insufficient understanding of the situation in the affected areas and insufficient communication infrastructure, the transmission of information regarding relief activities was often delayed. Furthermore, due to a lack of means to accurately grasp the amount and type of supplies needed, the supply of supplies was delayed, and in some cases appropriate support was not provided in line with the needs of the victims.

[1481] 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.

[1482] In this invention, the server includes means for flying multiple autonomous flight devices to designated disaster areas and collecting video data and environmental data in real time, a generating artificial intelligence means for analyzing the collected video data and environmental data, a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions, a means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices, and a means for identifying unrescue points, maintaining public order, checking the health of victims, guiding them to evacuation sites, and calculating and issuing transport instructions for necessary supplies. This enables rapid and efficient rescue operations, understanding the situation in the disaster area, securing communication infrastructure, and supplying appropriate supplies.

[1483] An "autonomous flying device" is an unmanned aerial vehicle that can fly by remote control or automatic control.

[1484] "Video data" refers to visual information collected by a video capture device such as a camera or video recorder.

[1485] "Environmental data" is data obtained from sensors that measure environmental parameters such as temperature, humidity, gas concentration, and radiation levels.

[1486] "Generative artificial intelligence means" refers to an artificial intelligence system that has the ability to analyze large amounts of data and automatically generate specific patterns or information.

[1487] "Rescue point" refers to a location within a disaster area where rescue is particularly needed.

[1488] A "rescue route" refers to a route that can be traveled safely and efficiently when carrying out rescue operations.

[1489] "Communications infrastructure" refers to the entire hardware and software that make up a communications network.

[1490] A "communication relay point" is a base that relays communication signals, and is a point that is installed to expand the communication range or to deal with sudden communication interruptions.

[1491] "Unrescue points" refer to locations within the disaster area where rescue efforts have not yet begun.

[1492] "Maintaining public order" refers to activities to ensure safety and maintain order at the scene of a disaster.

[1493] "Health assessment of disaster victims" is the process of assessing the physical condition and medical condition of disaster victims and determining the medical assistance they require.

[1494] An "evacuation site" refers to a safe place designated for temporary evacuation of disaster victims in the event of a disaster.

[1495] "Necessary supplies" refers to basic necessities such as food, water, and medicine that disaster victims need during relief efforts.

[1496] A "materials transport order" is an order to transport needed materials to a specific location.

[1497] "Real-time" refers to data being processed and used as soon as it is generated.

[1498] This invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones) with generative AI technology to carry out disaster relief activities quickly and efficiently. The system of this invention mainly collects and analyzes information when a disaster occurs, calculates rescue routes, secures communication infrastructure, and carries out relief activities.

[1499] System configuration

[1500] The system consists of four main parts:

[1501] 1. Information gathering devices (drones)

[1502] 2. Data analysis device (server)

[1503] 3. Server for linking with rescue and medical institutions

[1504] 4. Communication infrastructure securing device (drone)

[1505] Drone launch and information gathering

[1506] When a disaster occurs, the server immediately sends instructions to activate a fleet of drones, which begin flying toward the designated disaster area and collecting real-time video and sensor data, which is then transmitted from the drones to the server.

[1507] Examples:

[1508] In the event of a major earthquake, the server will send coordinate information of the affected area to the drone, and the drone will then depart for that location.

[1509] Real-time data analysis and rescue route calculation

[1510] The server receives real-time video data sent from the drone and passes it to the AI ​​generator for analysis. The AI ​​generator performs a detailed analysis of the damage situation and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions.

[1511] Examples:

[1512] The server identifies the building that suffered the most damage among several collapsed buildings and provides rescue teams with safe routes around it.

[1513] Calculating necessary supplies

[1514] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drones for delivering the supplies.

[1515] Examples:

[1516] Taking into account the number of disaster victims gathered at the evacuation center and their health condition, the system calculates the amount of food, water, and medicine needed and transmits this information to the transport drone.

[1517] Securing communications infrastructure and relief efforts

[1518] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points, restoring data communications within the affected area and maintaining connections with servers and relief organizations.

[1519] Examples:

[1520] Communication relay drones fly over disaster-stricken areas where communications have been cut off, maintaining altitude to provide communication signals.

[1521] Implementing and following up on relief efforts

[1522] Identifying unrescue locations, checking the health of victims, and maintaining public order are also important functions of this system. Based on the analysis results of the generated AI, the server identifies unrescue locations and directs drones to carry out rescue operations. It also checks the health of victims and provides necessary medical assistance.

[1523] Examples:

[1524] The drones fly over the affected areas, remotely measuring the body temperature and heart rate of victims, and rescue teams are immediately dispatched to those in urgent need.

[1525] Prompt Sentence Examples

[1526] Here are some examples of specific prompts for a generative AI model:

[1527] 1. Prompt for analyzing video data from the disaster area:

[1528] Next, analyze the video data provided to determine the number of collapsed buildings, the location of victims, and whether there were any fires or heat sources.

[1529] 2. Prompt to assess the victim's health:

[1530] Please use the following sensor data to measure the victim's body temperature and heart rate and identify those in need of emergency assistance.

[1531] With this system configuration and specific operation, the present invention can realize rapid and effective rescue operations in the event of a disaster.

[1532] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1533] Step 1:

[1534] The server that detects the occurrence of a disaster sends an instruction to activate the drones.

[1535] Input: Disaster occurrence detection data (e.g., earthquake occurrence notification)

[1536] Data processing / calculation: The server obtains coordinate data of the disaster site and executes the drone activation protocol.

[1537] Output: Commands to launch drones and coordinates of the affected area

[1538] Specific behavior:

[1539] The server automatically receives notification of a disaster and sends the coordinates of the affected area to the drone, which then prepares to fly to the specified location.

[1540] Step 2:

[1541] Based on the transmitted coordinate information, the drone begins flying toward the affected area and collects video and sensor data in real time.

[1542] Input: Coordinate information of affected area

[1543] Data processing / computation: The drone activates its cameras and sensors to collect video and environmental data of the designated area.

[1544] Output: Collected video and sensor data

[1545] Specific behavior:

[1546] The drone flies to specified coordinates, captures real-time footage with a high-resolution camera, and uses sensors to measure environmental data such as temperature and gas concentrations.

[1547] Step 3:

[1548] The collected data is sent to the server in real time.

[1549] Input: Video and sensor data

[1550] Data processing / calculation: The drone transmits the collected data to a server via wireless communication.

[1551] Output: Video data and sensor data uploaded to the server

[1552] Specific behavior:

[1553] The drone wirelessly transmits real-time video and sensor data to a server, which then receives the data.

[1554] Step 4:

[1555] The server passes the received data to the generative AI model for analysis.

[1556] Input: Video data and sensor data sent to the server

[1557] Data processing / calculation: A generative AI model analyzes the data and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fire or heat sources.

[1558] Output: Analysis results of the damage situation

[1559] Specific behavior:

[1560] The server inputs the received data into a generative AI model, and the AI ​​analyzes the data to gain a detailed understanding of the situation in the affected areas.

[1561] Step 5:

[1562] The server calculates the optimal rescue point and safe rescue route based on the analysis results of the generated AI model.

[1563] Input: Analysis results of the damage situation

[1564] Data processing / calculation: The server runs an algorithm based on the analysis results to calculate the optimal rescue point and safe route.

[1565] Output: Rescue location and rescue route information

[1566] Specific behavior:

[1567] The server calculates safe and efficient rescue routes based on the locations of collapsed buildings and victims, and provides them to rescue agencies.

[1568] Step 6:

[1569] The server analyzes detailed data on the affected area and calculates the types and quantities of medical supplies and relief goods needed.

[1570] Input: Detailed data of the affected area

[1571] Data processing / calculation: The server analyzes the number of people, their health status, and the damage situation, and determines the type and amount of supplies needed.

[1572] Output: List of required supplies

[1573] Specific behavior:

[1574] The server calculates and lists the quantities of food, water, and medicine needed based on data on disaster victims gathered at evacuation centers.

[1575] Step 7:

[1576] The server sends instructions to the drone on the route to transport the necessary supplies.

[1577] Input: List of required supplies and destination coordinates

[1578] Data processing / calculation: The server calculates the optimal route for transporting supplies and sends those instructions to the drone.

[1579] Output: Delivery route instructions for drone

[1580] Specific behavior:

[1581] The server indicates to the drone the specific flight route to carry the necessary supplies, and the drone then transports the supplies along that route.

[1582] Step 8:

[1583] If communication infrastructure is destroyed, drones equipped with communication capabilities will move to designated locations and function as communication relay points.

[1584] Input: Communication status data for affected areas

[1585] Data processing / calculation: The server identifies the area where communication has been lost and instructs the communication drone to move to that area.

[1586] Output: Communication infrastructure restored

[1587] Specific behavior:

[1588] Based on instructions from the server, drones equipped with communication capabilities will provide communication relay points over the affected area, temporarily restoring the communication network.

[1589] Step 9:

[1590] Based on the analysis results of the generated AI model, the server identifies unrescue locations and instructs a group of drones to carry out rescue operations.

[1591] Input: Analysis results of the generative AI model

[1592] Data processing / calculation: The server identifies unrescue locations that require rescue operations and issues instructions to the drones.

[1593] Output: Rescue operation instructions

[1594] Specific behavior:

[1595] The drones will fly to unrescue locations, remotely measure the temperature and heart rate of victims, and provide necessary medical assistance.

[1596] The above are the specific processing steps and detailed operations in the system program.

[1597] (Application example 1)

[1598] 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."

[1599] Conventional disaster relief systems have had difficulty quickly and efficiently grasping the situation in disaster-stricken areas and taking appropriate action. They also have issues with delays in sharing information and issuing instructions for rescue operations when communication infrastructure is destroyed. Furthermore, even with standard security monitoring, anomaly detection is not performed in real time, making it difficult to respond quickly.

[1600] 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.

[1601] In this invention, the server includes a means for flying the autonomous flight device to a designated disaster area and collecting video data in real time, a generating artificial intelligence means for analyzing the collected video data, and a means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions. This makes it possible to quickly collect and analyze information in the event of a disaster and provide optimal rescue routes.

[1602] Furthermore, it includes a means for temporarily securing communication infrastructure in disaster-stricken areas using autonomous flight devices, and a means for identifying unrescue locations, maintaining public order, checking the health of disaster victims, and guiding them to evacuation sites. This allows for the continuation of information sharing and instructions for rescue operations even if communication infrastructure is destroyed.

[1603] In addition, it includes a means for collecting security monitoring data in real time during operation, detecting anomalies using a generative AI model, and a means for securing communication relay points even in areas with unstable communication infrastructure based on the detection results, which enables rapid anomaly detection and response even in normal security monitoring.

[1604] An "autonomous flight device" is an unmanned aerial vehicle that flies autonomously according to pre-programmed instructions and collects video and sensor data.

[1605] "Generative AI" is an artificial intelligence technology that analyzes collected data and generates and provides necessary information.

[1606] A "rescue route" is a route optimized for safe and rapid rescue operations.

[1607] "Sensor data" refers to physical data such as temperature, humidity, vibration, and pressure obtained from drones and other sensor devices.

[1608] "Anomaly detection" is the process of detecting abnormal situations or behaviors that deviate from normal conditions.

[1609] "Telecommunications infrastructure" refers to the physical and software systems that create telecommunications networks and enable the transmission and reception of data.

[1610] A "communication relay point" is an intermediate point that temporarily relays communications in an area where communications have been cut off, ensuring network connectivity.

[1611] A "generative AI model" is a type of artificial intelligence that generates new information and data patterns based on large amounts of data.

[1612] A "prompt sentence" is an input sentence used to give instructions to a generative AI model.

[1613] "Security surveillance data" refers to video, audio, sensor, and other data collected in real time to ensure the safety of a specific area.

[1614] "Disaster situation" refers to the state of damage in the area where the disaster occurred, including the number of collapsed buildings, the location of victims, and the presence or absence of fires or heat sources.

[1615] An "embodiment" is a form showing how the invention is specifically carried out.

[1616] This invention is a system that combines autonomous flight devices (drones) and generative AI technology to realize rapid and efficient rescue operations in the event of a disaster. The main components of this system are as follows:

[1617] System configuration

[1618] 1. Autonomous flying devices (drones)

[1619] 2. Generative artificial intelligence (AI) means

[1620] 3. Rescue route calculation method

[1621] 4. Measures to secure communications infrastructure

[1622] 5. Anomaly detection and notification methods

[1623] System Operation

[1624] Drone launch and information gathering

[1625] When a disaster occurs, the server immediately activates an autonomous flying device (drone) and has it fly toward the designated disaster area. The drone collects video and sensor data in real time and transmits the data to the server. In particular, the drone uses advanced sensor technology (temperature sensors, humidity sensors, etc.) to collect detailed data.

[1626] Real-time data analysis and rescue route calculation

[1627] The server passes the real-time video and sensor data transmitted from the drone to a generative AI model for analysis. Examples of generative AI models include OpenAI's GPT-4. This AI analyzes the collected data and identifies the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. It then calculates the optimal rescue points and safe rescue routes and provides this information to rescue organizations and medical institutions.

[1628] Calculation and instructions for necessary supplies

[1629] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drones for delivering the supplies. Selecting the appropriate route enables the rapid and efficient delivery of supplies.

[1630] Securing communication infrastructure

[1631] If communications infrastructure is destroyed, drones equipped with communications capabilities will move to designated locations and establish temporary communications relay points. Specifically, the drones will maintain altitude and transmit communications signals to support communications at the scene. This will restore data communications within the disaster area and maintain communication with servers and relief organizations.

[1632] Security monitoring and anomaly detection

[1633] Under normal circumstances, drones collect security monitoring data and use generative AI models to detect anomalies in real time. The analysis results are then immediately communicated to security personnel. Even in areas with unstable communications infrastructure, drones can function as communication relay points, ensuring stable data communication.

[1634] Specific examples

[1635] During nighttime security surveillance at a large commercial facility, if a drone detects a suspicious person entering the facility in real time, by inputting the prompt "Anomaly detection: Analyze video data, detect and report any anomalies" into the generative AI model, details of the anomaly will be immediately sent to the server. As a result, security personnel will receive an immediate notification of the anomaly via their smartphone or smart glasses, enabling them to respond promptly.

[1636] As described above, this system can be applied not only during disasters but also to normal security monitoring, enabling rapid and efficient responses through real-time data collection and analysis using generative AI.

[1637] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1638] Step 1:

[1639] When a disaster occurs, the server immediately activates an autonomous flying device (drone) and sends it off to the designated disaster area. The drone collects video and sensor data in real time. The input is coordinate information of the disaster area, and the output is real-time video and sensor data.

[1640] Step 2:

[1641] The collected video and sensor data is sent to a server, which receives the data and passes it to a generative AI model. The input is real-time video and sensor data, and the output is data that is analyzed by the generative AI model.

[1642] Step 3:

[1643] The server analyzes the collected data using a generative AI model. Specifically, the AI ​​model receives prompts to "analyze the damage situation, identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources," and obtains analysis results. This analysis includes pattern recognition in video and anomaly detection in sensor data. The inputs are prompts and raw data for the AI ​​model, and the output is the analysis results.

[1644] Step 4:

[1645] Based on the analysis results, the server calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions. The input is the analysis results, and the output is optimized rescue route information. Specifically, a route search algorithm is used to calculate the shortest and safest route.

[1646] Step 5:

[1647] The server calculates the type and amount of medical supplies and relief supplies needed and sends route instructions to the drones for delivering the supplies. The input is the number of people in the disaster area and health data, and the output is the delivery route and a list of supplies. A supply supply algorithm determines the amount of supplies needed at each location.

[1648] Step 6:

[1649] If communications infrastructure is destroyed, drones act as communication relay points to establish a temporary communications infrastructure. The input is the coordinate information of the communication-disrupted area, and the output is the area where a constant communication connection is ensured. Communications are stabilized using LoRa networks and other mesh network technologies.

[1650] Step 7:

[1651] Under normal circumstances, drones collect security surveillance data and use generative AI models to detect anomalies in real time. The results are then notified to security personnel. The input is real-time surveillance data, and the output is anomaly detection results and notification information. A specific prompt, "Anomaly detection: Analyze video data, detect anomalies, and report them," is used to prompt the AI ​​to perform analysis.

[1652] By combining these processing steps, this system enables multifunctional and highly efficient operations during disasters and normal security activities.

[1653] 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.

[1654] This invention is a system that combines multiple autonomous flying devices (hereinafter referred to as drones), generative AI technology, and an emotion engine to carry out disaster relief activities quickly and efficiently. The system of this invention collects and analyzes information when a disaster occurs, optimizes rescue routes, secures communication infrastructure, and provides psychological support through emotion analysis. The following describes the overall configuration of the system and the operation of each component.

[1655] System configuration

[1656] The system consists of five main parts:

[1657] 1. Information gathering devices (drones)

[1658] 2. Data analysis device (server)

[1659] 3. Emotion Engine

[1660] 4. Server for linking with rescue and medical institutions

[1661] 5. Communication infrastructure securing device (drone)

[1662] Program for carrying out the invention

[1663] Drone launch and information gathering

[1664] When a disaster occurs, the server immediately sends instructions to launch a fleet of drones. The drones begin flying toward the designated disaster area and collect video and sensor data in real time. This data is then sent from the drones to the server. For example, if a major earthquake occurs, the server sends the coordinates of the disaster area to the drones, who then depart for that location.

[1665] Real-time data analysis and rescue route calculation

[1666] The server receives real-time video data sent from the drone and passes it to the generation AI for analysis. The generation AI analyzes the damage situation in detail and extracts important information such as the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources. Based on the results of this analysis, the server determines the optimal rescue points and safe rescue routes and provides them to rescue organizations and medical institutions. As a specific example, the server identifies the building with the most damage among multiple collapsed buildings and provides rescue teams with safe routes around it.

[1667] Calculating necessary supplies

[1668] The server analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to the drone for delivering the supplies. For example, it calculates the amount of food, water, and medicine needed based on the number and health condition of the victims gathered at evacuation centers and sends this information to the delivery drone.

[1669] Securing communications infrastructure and relief efforts

[1670] If a disaster destroys communications infrastructure, drones equipped with communications capabilities will fly to designated locations and establish temporary communications relay points. This will restore data communications within the affected area and maintain connections with servers and relief organizations. As a specific example, a communications relay drone will fly over a disaster-stricken area where communications have been cut off, maintaining its altitude to provide communications signals.

[1671] Emotion analysis and psychological support using an emotion engine

[1672] The server uses an emotion engine to analyze the facial expression data of victims collected by the drone and identify their emotional state. Based on the emotion engine's analysis results, it notifies rescue organizations and medical institutions of locations where psychological support is needed. In addition, even after communication infrastructure is restored, it continues to monitor the emotional state of victims in evacuation centers in real time, and notifies medical institutions if it detects abnormal stress or anxiety. For example, if a victim in an evacuation center becomes extremely anxious or panics, this information is quickly conveyed to the medical team, and the necessary support is provided.

[1673] With such a system configuration and operation, the present invention can realize rapid and effective relief activities in disaster areas and psychological care for disaster victims.

[1674] The processing flow will be explained below.

[1675] Step 1:

[1676] Server: Upon receiving information about a disaster, it immediately launches multiple drones and sends them commands to fly towards the designated disaster area.

[1677] Example: An earthquake occurs and the server sends a departure command to each drone.

[1678] Step 2:

[1679] Drones: Fly to designated disaster areas and collect real-time video and sensor data. Drones follow pre-set flight patterns to collect data over a wide area.

[1680] Example: Drones can capture images of debris and road damage from the sky, and temperature sensors can detect fires.

[1681] Step 3:

[1682] Drone: Collected video and sensor data is sent to a server via 4G / 5G networks or dedicated wireless communication protocols.

[1683] Example: A drone uploads data to a server in real time.

[1684] Step 4:

[1685] Server: Passes the received data to the generation AI, which analyzes the damage situation in detail. The generation AI uses image recognition technology to identify the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources, and extracts important information.

[1686] Example: Generative AI analyzes video footage and displays the coordinates of collapsed buildings and fire sites on a map.

[1687] Step 5:

[1688] Server: Based on the analysis results of the generation AI, it calculates the optimal rescue point and safe rescue route and provides this information to rescue organizations and medical institutions.

[1689] Example: The server identifies the most affected areas and sends their coordinates and rescue routes to rescue teams.

[1690] Step 6:

[1691] Server: Analyzes situational data from the disaster area and calculates the type and amount of medical supplies and relief supplies needed. Based on this information, it sends route instructions to drones delivering supplies.

[1692] Example: Calculate the amount of food, water, and medicine needed at a shelter and communicate that information to a delivery drone.

[1693] Step 7:

[1694] Drones: Drones equipped with communication capabilities will fly to designated locations and establish temporary communication relay points, thereby temporarily restoring communication infrastructure in the affected areas.

[1695] Example: A communications drone hovers over the affected area and provides a communications signal.

[1696] Step 8:

[1697] Server: The emotion engine analyzes the facial expression data collected by the drone and identifies the emotional state of the victim. The emotion engine reads emotions such as anxiety, fear, and sadness from facial expressions.

[1698] Example: The emotion engine analyzes the facial expression data of a victim and determines that the victim is in a "high stress state."

[1699] Step 9:

[1700] Server: Based on the analysis results of the emotion engine, it notifies rescue organizations of locations where psychological assistance is needed, allowing psychological counseling and emergency psychological assistance to be provided promptly.

[1701] Example: The server sends an instruction to dispatch a psychological counselor to an evacuation site determined to be in a "high stress state."

[1702] Step 10:

[1703] Server: Even after the communication infrastructure is restored, the server monitors the emotional state of disaster victims in evacuation shelters in real time, and notifies medical institutions if it detects abnormal stress or anxiety.

[1704] Example: A server continuously monitors the emotional state of disaster victims in evacuation centers and sends an alert to medical teams if any abnormalities are detected.

[1705] Each processing step of this system enables rapid information gathering in disaster areas, ensuring the safety of victims, efficiently distributing relief supplies, and providing psychological care to victims.

[1706] Example 2

[1707] 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."

[1708] Conventional disaster relief systems have had problems with the collection and analysis of information, securing communication infrastructure, and providing psychological support to victims in a timely and efficient manner. Furthermore, the calculation and transportation of necessary supplies was ineffective, resulting in delayed responses to disaster victims.

[1709] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for flying multiple autonomous flight devices to a designated disaster area when a disaster occurs and collecting video data and sensor data in real time; a generating artificial intelligence means for analyzing the collected video data and sensor data; means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions; means for temporarily securing communication infrastructure in the disaster area using the autonomous flight devices; means for analyzing situation data in the disaster area to calculate the type and amount of supplies needed and sending route instructions to an autonomous flight device for delivery; and means for analyzing facial expression data of victims collected by the autonomous flight devices, identifying their emotional states, and providing psychological support. This enables rapid and efficient information collection and analysis, securing communication infrastructure, calculating and delivering needed supplies, and providing psychological support to victims.

[1710] A "disaster" is an abnormal phenomenon caused by natural phenomena or human factors that results in human injury or property damage.

[1711] An "autonomous flying device" is a device that performs a designated mission while flying itself based on pre-programmed instructions or instructions received in real time.

[1712] "Real-time" refers to situations in which data is collected and processed virtually immediately.

[1713] "Video data" refers to visual information acquired by a camera or other optical means.

[1714] "Sensor data" refers to data collected by a sensor that represents changes in physical quantities. Specifically, it includes information on temperature, humidity, air pressure, gas concentration, etc.

[1715] "Generative AI means" refers to a method or device that uses generative AI technology to analyze input data and extract and generate useful information.

[1716] "Rescue point" refers to a specific location within a disaster area where rescue operations should be carried out.

[1717] A "rescue route" refers to the optimal route for rescue teams to reach the rescue point safely and quickly.

[1718] "Communications infrastructure" refers to the hardware and software infrastructure required to conduct data communications.

[1719] "Supplies" refers to basic necessities and relief supplies such as food, medicine, and clothing needed to support disaster victims.

[1720] "Facial expression data" is data that captures a person's facial expressions and records their features and changes.

[1721] "Emotional state" refers to the results of analyzing and identifying the psychological reactions and emotional state of victims.

[1722] "Psychological support" refers to interventions and support activities aimed at reducing psychological stress and anxiety among disaster victims and supporting their mental health.

[1723] The system of the present invention combines multiple autonomous flying devices (hereinafter referred to as drones), generative artificial intelligence technology (generative AI model), and an emotion engine to realize rapid and efficient rescue operations in the event of a disaster. The system operates based on the following main components and their interactions:

[1724] System configuration

[1725] The system consists of five main parts:

[1726] 1. Information gathering devices (drones)

[1727] 2. Data analysis device (server)

[1728] 3. Emotion Engine

[1729] 4. Server for linking with rescue and medical institutions

[1730] 5. Communication infrastructure securing device (drone)

[1731] Information gathering device

[1732] In the event of a disaster, the server launches a fleet of drones and sends them to the affected area. The drones collect video and sensor data in real time and transmit that data to the server. For example, in the event of a major earthquake, the server sends coordinate information of the affected area to the drones, which then fly to that location and transmit the collected video and sensor data in real time.

[1733] Data analysis equipment

[1734] The server passes the received drone footage and sensor data to the generation AI for detailed analysis. The generation AI analyzes the damage situation and extracts important information such as the number of collapsed buildings, the location of victims, and the presence or absence of fire or heat sources. This allows rescue points and routes to be optimized, and the information is provided to rescue organizations and medical institutions. For example, the server could identify the building with the most damage among multiple collapsed buildings and provide rescue teams with safe routes around it.

[1735] Calculating necessary supplies

[1736] The server uses the results of the analysis to analyze the situation in the affected area and calculate the type and amount of medical supplies and relief supplies needed. Based on this information, the server sends route instructions to the drone for delivering supplies. For example, the server calculates the necessary supplies and issues instructions, taking into account the number and health status of victims gathered at evacuation centers.

[1737] Securing communication infrastructure

[1738] In areas where communications have been cut off due to a disaster, the server will move drones equipped with communications capabilities to designated locations to establish temporary communications relay points. This will restore data communications within the affected area and maintain coordination with the server and relief organizations. For example, a communications relay drone will fly over a disaster area where communications have been cut off and provide communications signals.

[1739] Emotion Engine

[1740] The server uses an emotion engine to analyze the facial expression data of disaster victims collected by the drone and identify their emotional state. Based on this, it notifies rescue organizations and medical institutions of locations where psychological support is needed. It also monitors the emotional state of disaster victims in evacuation centers in real time and notifies medical institutions if it detects any abnormalities. For example, if a disaster victim in an evacuation center becomes extremely anxious or panicked, it will quickly convey that information to the medical team.

[1741] Prompt Sentence Examples

[1742] Below are some example prompts for each process in the event of a disaster:

[1743] "An earthquake has occurred. Fly a drone based on the coordinate information of the center of City A and collect video and sensor data."

[1744] "Use AI to analyze real-time video data from the disaster area, calculate the optimal rescue route, and provide it to rescue teams."

[1745] "Calculate the necessary medical supplies and relief supplies based on the situation at the evacuation center, and have delivery drones deliver them along the designated route."

[1746] "Send communications relay drones to areas where communications have been cut off and secure communications infrastructure."

[1747] "Analyze the emotional state of the victims and notify medical institutions so that necessary psychological care can be provided."

[1748] In this way, the present invention allows disaster relief efforts to be carried out quickly and efficiently, providing comprehensive assistance to victims.

[1749] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1750] Program processing flow

[1751] Step 1: Detecting a disaster and issuing a command to launch a drone

[1752] Description: When a user confirms that a disaster has occurred, the server immediately sends activation commands to multiple autonomous flying devices (drones).

[1753] Input: Disaster occurrence detection data (obtained from sensor networks or external APIs)

[1754] Data processing and calculation: Receiving and analyzing disaster information

[1755] Output: Start command to drone

[1756] Specific operation: The user confirms the occurrence of a disaster on the system, and the server sends a start-up command to the drone, including coordinate information of the affected area. For example, when the server confirms the occurrence of a disaster, it issues a start-up command to the drone, including coordinate information (center of City A).

[1757] Step 2: Collecting information using drones

[1758] Description: The device (drone) heads to the designated disaster area and collects video and sensor data in real time.

[1759] Input: Drone launch command and coordinate information of the affected area

[1760] Data processing and computation: Autonomous flight control and sensor data collection

[1761] Output: Collected video and sensor data

[1762] Specific operation: Once the drone reaches the designated disaster area, it uses its onboard camera and sensor devices to collect video footage and data such as temperature, humidity, and gas concentration in real time, and transmits the data to a server.

[1763] Step 3: Data analysis and rescue route calculation

[1764] Description: The server passes the data received from the drone to the generative AI model, which analyzes the damage situation.

[1765] Input: Video data and sensor data transmitted from the drone

[1766] Data Processing and Computation: Disaster Situation Analysis Using Generative AI Models

[1767] Output: Analysis results (number of collapsed buildings, location of victims, presence or absence of fire or heat source, etc.)

[1768] Specific operation: The server inputs the received data into the generative AI model and analyzes the damage situation (e.g., the collapsed status of multiple buildings, the location of victims, the location of the fire, etc.). Based on the analysis results, the server calculates the optimal rescue point and safe rescue route.

[1769] Step 4: Provide information to relief agencies and medical institutions

[1770] Description: The server provides rescue routes calculated based on the analysis results to rescue organizations and medical institutions.

[1771] Input: Analysis results of the generative AI model (optimal rescue location and route)

[1772] Data processing and calculation: Optimization and notification of rescue routes

[1773] Output: Providing information to relief agencies and medical institutions

[1774] Specific operation: The server uses the analysis results to calculate the optimal rescue route and transmits that information to rescue teams and hospitals in real time. For example, the server transmits the optimal rescue route and rescue location information to the rescue team's tablet device.

[1775] Step 5: Calculate and order supplies

[1776] Description: The server calculates the type and amount of supplies needed based on situational data from the disaster area and sends route instructions to the transport drone.

[1777] Input: Situation data of the affected area and analysis results

[1778] Data processing and calculation: Calculation of the type and amount of supplies needed

[1779] Output: Route instructions for the transport drone

[1780] Specific operation: Based on the analysis results, the server calculates the amount of food, water, and medical supplies needed, and transmits this information to a delivery drone to transport the supplies along a specified route. For example, the server calculates the amount of supplies needed based on the number of disaster victims in an evacuation shelter and transmits this information to the delivery drone.

[1781] Step 6: Securing communications infrastructure

[1782] Description: The server will move a drone with communication capabilities to a specific location to secure a temporary communication relay point.

[1783] Input: Communication infrastructure status data

[1784] Data processing and calculation: Calculation to secure communication relay points

[1785] Output: Position instructions to communication drone

[1786] Specific operation: To cover areas where communication has been cut off, the server sends instructions to communication relay drones to move to specific locations and secure communication relay points. For example, the server analyzes the communication situation in the affected area and transmits location information to drones that provide communication signals at high altitudes.

[1787] Step 7: Emotional analysis and psychological support

[1788] Description: The server uses an emotion engine to analyze the facial expression data of the victim and identify their emotional state.

[1789] Input: Facial expression data (collected by drone)

[1790] Data Processing and Computation: Emotion Analysis with Emotion Engine

[1791] Output: Identification of locations where psychological support is needed

[1792] Specific operation: The server inputs facial expression data into the emotion engine and analyzes the emotional state of the victim. Based on the results, it notifies medical institutions where psychological support is needed. For example, it identifies victims who are anxious or panicked and conveys that information to the medical team.

[1793] This enables the system to quickly and efficiently collect and analyze information, secure communication infrastructure, calculate and transport necessary supplies, and provide psychological support to disaster victims.

[1794] (Application example 2)

[1795] 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."

[1796] When it comes to fast and efficient rescue operations and support for victims in the event of a disaster, as well as efficient inventory management at logistics centers, conventional systems have faced challenges such as delays in information collection and analysis, difficulty in securing communication infrastructure, and a lack of mental care for workers.

[1797] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for flying an autonomous flight device to a designated disaster area and collecting video data and environmental data in real time; a generative artificial intelligence means for analyzing the collected video data and environmental data; means for calculating optimal material transportation routes and efficient inventory management means based on the analysis results and providing them to management agencies and rescue agencies; means for temporarily securing communication infrastructure using the autonomous flight device and restoring data communication; and means for capturing facial expressions of workers using the autonomous flight device or a fixed camera and providing psychological support using an emotion analysis engine. This enables fast and efficient information collection and analysis at disaster sites and logistics centers, enabling optimal rescue operations, inventory management, and psychological care for workers.

[1798] An "autonomous flying device" is an unmanned aerial vehicle that flies autonomously to a designated location and collects data in real time.

[1799] "Video data" refers to real-time video information acquired by an autonomous flying device or a fixed camera.

[1800] "Environmental data" refers to environmental information such as temperature, humidity, and air pressure collected by sensors on an autonomous flight device.

[1801] The "generative artificial intelligence means" is an artificial intelligence system that analyzes collected image data and environmental data and determines the situation and necessary response.

[1802] The "emotion analysis engine" is an analysis system that analyzes facial expression data of workers and disaster victims to identify their emotional state.

[1803] "Communications infrastructure" refers to network equipment that enables data exchange.

[1804] "Disaster area" means an area that has been affected by a disaster.

[1805] A "logistics center" is a facility that stores, manages, and distributes goods.

[1806] A "relief organization" is an organization or group that carries out relief activities in the event of a disaster.

[1807] "Management agency" means the organization or body that operates and manages the logistics center.

[1808] A "materials transport route" is a route for efficiently transporting materials.

[1809] "Inventory management means" refers to a system and method for efficiently managing inventory within a distribution center.

[1810] The present invention provides a system that enables prompt and efficient information collection and analysis in the event of a disaster or at a logistics center, enabling optimal responses. The detailed configuration and operation of the system are described below.

[1811] System configuration

[1812] The system consists of the following main components:

[1813] 1. Autonomous flying devices (drones)

[1814] 2. Server (for data analysis)

[1815] 3. Sentiment Analysis Engine

[1816] 4. Linkage device with rescue / medical institutions and logistics management organizations

[1817] 5. Communication infrastructure securing equipment

[1818] Hardware and software used

[1819] Drone: An unmanned aerial vehicle that flies autonomously to a designated location and collects video and environmental data in real time.

[1820] Server: AWS EC2 instance used for data analysis

[1821] Generative AI method: Uses a generative AI model (e.g., OpenAI GPT-4)

[1822] Sentiment analysis engine: Affectiva

[1823] Collaborative software: Python, TensorFlow, Flask

[1824] How it works

[1825] 1. Information gathering

[1826] The drones fly to designated locations in disaster situations or within logistics centers, using cameras and sensors to collect real-time video and environmental data, which is then sent to a server in real time.

[1827] 2. Data Analysis

[1828] The server inputs the received video data and environmental data into a generative AI model for analysis. The generative AI performs a detailed analysis of the damage situation and the inventory status of the logistics center, extracting important information such as the number of collapsed buildings, the location of victims, the presence or absence of fires or heat sources, and the location and quantity of inventory. Based on the results of this analysis, it calculates the optimal rescue points and supply transport routes.

[1829] 3. Securing communication infrastructure

[1830] Drones equipped with communication capabilities will set up communication relay points in disaster-stricken areas and logistics centers, securing temporary communication infrastructure, which will restore data communication and enable collaboration with servers and information sharing.

[1831] 4. Emotion analysis and psychological support

[1832] Drones or fixed cameras capture the facial expressions of workers and victims, which are then analyzed using an emotion analysis engine. Based on the results of this analysis, necessary psychological support is provided. If a worker is in a state of high stress, a notification is sent to the manager, urging them to take appropriate action.

[1833] Specific examples

[1834] When a disaster occurs: Drones fly over the affected area and collect information on the damage in real time. This information is analyzed by a generative AI model to determine rescue routes and routes for transporting supplies...

Claims

1. When a disaster occurs, a means for flying a plurality of autonomous flying devices to a designated disaster area and collecting video data in real time; a generating artificial intelligence means for analyzing the collected video data; A means for calculating rescue points and safe rescue routes based on the analysis results and providing them to rescue organizations and medical institutions; A means for temporarily securing communication infrastructure in the disaster area by the autonomous flight device; A means to identify unrescue locations, maintain public order, check the health of victims, and guide them to evacuation sites. A system including:

2. The system according to claim 1, wherein the generating artificial intelligence means analyzes the damage situation using video data and sensor data, and identifies the number of collapsed buildings, the locations of victims, and the presence or absence of fires or heat sources.

3. The system according to claim 1 , wherein the autonomous flight device has a communication function and secures a communication relay point in a disaster area.

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