system

Abstract

We provide the system. [Solution] Earthquake detection means, A location information means for obtaining the current location of personnel, A calculation means for calculating the optimal evacuation route to at least one emergency exit, A transmission means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits, A means of receiving evacuation instructions via the user's mobile device, A display means that displays the user's location and evacuation route based on location information means and evacuation instructions, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, large-scale natural disasters such as earthquakes have been increasing, and at such times, it is required to quickly and safely evacuate people inside buildings. However, since there is no system that immediately provides an optimal evacuation route at the time of an earthquake, confusion and congestion occur, and evacuation is often delayed. Furthermore, it is difficult to grasp the flow of people within the company at the time of an earthquake and provide appropriate instructions in real time to avoid congestion on the evacuation route. To solve such problems, a system that senses an earthquake in real time and utilizes the flow of people data to quickly provide a safe evacuation route is necessary.

Means for Solving the Problems

[0005] The present invention is a system that includes earthquake sensing means, location information means for acquiring the current location of personnel, calculation means for calculating the optimal evacuation route to at least one emergency exit, transmission means for generating and transmitting evacuation instructions including the evacuation route to the emergency exit, receiving means for receiving evacuation instructions via the user's mobile terminal, and display means for displaying the user's location and evacuation route based on the location information means and evacuation instructions. This makes it possible to immediately calculate and provide the optimal evacuation route to the user when an earthquake occurs, enabling quick and safe evacuation while avoiding confusion and congestion. Furthermore, by monitoring the density of people inside the building using a human flow sensor and having the calculation means calculate the optimal evacuation route based on that data, it is possible to provide the user with an appropriate evacuation route in real time.

[0006] "Earthquake detection means" refers to devices or mechanisms that detect the occurrence of an earthquake and transmit that information to a system.

[0007] "Location information means" refers to devices and technologies for identifying the current location of users or personnel and acquiring and transmitting that location data.

[0008] "Calculation means" refers to devices or software used to calculate the optimal evacuation route based on acquired location information and pedestrian flow data.

[0009] "Transmission means" refers to devices and technologies used to transmit calculated evacuation routes and other important instructional information to a user's mobile device.

[0010] "Receiving means" refers to devices and technologies used to receive evacuation instructions transmitted via a user's mobile device.

[0011] "Display means" refers to devices or technologies that display received evacuation orders or other information in a way that is visible to the user.

[0012] A "human flow sensor" refers to a sensor device or technology used to monitor the movement and density of people inside a building in real time and acquire that data.

[0013] An "evacuation route" refers to the path from a designated point to a safe exit, and is a route optimized by computational means. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] Modes for carrying out the invention

[0036] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, and display means. By coordinating these means, it is possible to provide evacuation routes quickly and safely even in the event of a large-scale disaster.

[0037] Earthquake sensing means

[0038] The server monitors data from earthquake sensors in real time and immediately detects the occurrence of an earthquake. This information is sent to the server, and the process moves on to the next step of notifying the server of the earthquake.

[0039] Sending evacuation alerts

[0040] Once the server detects an earthquake, it sends an evacuation alert to all registered mobile devices. This alert includes a message informing users of the earthquake and urging them to evacuate to a safe place immediately. For example, a message such as "Earthquake! Evacuate immediately!" is sent to each user's mobile device.

[0041] Inquiry about evacuation routes

[0042] After receiving an earthquake alert, users launch a dedicated app on their mobile device and inquire about evacuation routes. For example, if a user types "Please tell me the evacuation route," this request is sent to the server.

[0043] Get current location

[0044] The server receives a user request and obtains location information (such as GPS data) from the mobile device. Based on this information, it determines the user's current location and uses that location data in the next step.

[0045] Collection of pedestrian flow data and calculation of evacuation routes

[0046] The server collects real-time occupancy density data from pedestrian flow sensors installed inside the building. Based on location information and pedestrian flow data, it then uses computational methods to calculate the optimal evacuation route. For example, to avoid congestion, it calculates a route that includes the currently least crowded stairwells and exits.

[0047] Evacuation order notification

[0048] The server sends the calculated optimal evacuation route to the user's mobile device. Specifically, it includes detailed evacuation instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[0049] Evacuation route display

[0050] The user's mobile device displays the received evacuation instructions. The display method allows the user to visually confirm the evacuation route. For example, displaying the route on a map allows the user to easily understand the specific evacuation path.

[0051] Specific example

[0052] Let's consider a specific example of what happens during an earthquake. An earthquake occurs in a company building, and the server immediately receives data from earthquake detection sensors. The server sends an alert to all employees' mobile devices saying, "Earthquake! Evacuate immediately!" User A, upon receiving this alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and identifies their position. Simultaneously, it collects data from pedestrian flow sensors to check the congestion level. Based on the data obtained, the server calculates the optimal evacuation route and notifies User A's mobile device, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." User A can confirm the received instructions on their mobile device screen and evacuate quickly via the designated route. In this way, smooth evacuation is achieved even during an earthquake.

[0053] The following describes the processing flow.

[0054] Step 1:

[0055] The server monitors earthquake detection sensors. When an earthquake is detected by an earthquake detection sensor, data on its speed and intensity is sent to the server.

[0056] Step 2:

[0057] The server analyzes earthquake data and determines the seismic intensity. If the seismic intensity exceeds a certain threshold, it is determined that an earthquake has occurred.

[0058] Step 3:

[0059] The server sends an earthquake alert to all registered mobile devices. The alert message includes content such as "Earthquake! Evacuate immediately!"

[0060] Step 4:

[0061] The user receives an earthquake alert and launches a dedicated app on their mobile device. The user then types "Please tell me the evacuation route" to inquire about evacuation routes.

[0062] Step 5:

[0063] The terminal sends an evacuation route inquiry from the user to the server. This request also includes information about the user's current location.

[0064] Step 6:

[0065] The server uses location information to determine the user's current location. This location information is obtained from sources such as GPS data from a mobile device.

[0066] Step 7:

[0067] The server collects data from pedestrian flow sensors within the building. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server.

[0068] Step 8:

[0069] The server calculates evacuation routes based on the user's current location and density data obtained from pedestrian flow sensors. The calculation method prioritizes less congested routes to determine the optimal evacuation path.

[0070] Step 9:

[0071] The server calculates the optimal evacuation route and sends it to the user's mobile device. For example, it might send instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[0072] Step 10:

[0073] The device displays the evacuation route it received. Depending on the display method, the evacuation route is displayed to the user in a way that is easily visible, such as on a map or in text.

[0074] Step 11:

[0075] The user checks the displayed evacuation route and begins evacuating according to the instructions. By following the instructions on the device, the user can safely evacuate via the optimal route.

[0076] (Example 1)

[0077] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0078] In the event of a large-scale earthquake disaster, an effective information system is needed to ensure rapid and safe evacuation. In particular, when large numbers of people begin evacuating simultaneously, congestion and panic are likely to occur, potentially delaying evacuation. Under these circumstances, the challenge lies in providing real-time situational awareness and accurate guidance on evacuation routes.

[0079] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0080] In this invention, the server includes means for receiving data from earthquake detection sensors in real time, means for acquiring location information of the user's mobile device, means for collecting data from pedestrian flow sensors installed inside the building and calculating the optimal evacuation route, means for generating and transmitting evacuation alerts and evacuation routes, and means for receiving and displaying evacuation routes via the user's mobile device. This enables the provision of rapid and safe evacuation routes and avoidance of congestion even in the event of a large-scale earthquake disaster.

[0081] An "earthquake detection sensor" is a device that detects earthquake vibrations and transmits that information to a server in real time.

[0082] "Real-time" means that data is processed the moment it is generated, and results are obtained almost instantly.

[0083] "Mobile devices" refer to portable information and communication devices such as smartphones and tablets owned by users.

[0084] "Location information" refers to data used to determine one's current location, such as GPS.

[0085] A "people flow sensor" is a device that detects the density and movement of people inside a building and collects the data.

[0086] An "evacuation route" refers to a recommended route for safe evacuation during a disaster.

[0087] A "server" refers to a computer system used for processing, calculating, storing, and managing data.

[0088] An "evacuation alert" is an emergency message sent to prompt immediate evacuation during emergencies such as earthquakes.

[0089] "Calculation means" refers to algorithms and software used to calculate the optimal evacuation route.

[0090] "Receiving means" refers to the mechanism by which a user's mobile device receives data transmitted from a server.

[0091] "Display means" refers to display devices or screens used to visually present received evacuation instructions and evacuation routes to the user.

[0092] An "evacuation order" refers to a message that includes specific instructions for actions to take to ensure the user's safe evacuation.

[0093] Modes for carrying out the invention

[0094] The system of the present invention consists of an earthquake detection sensor, a location information acquisition means, a calculation means, a transmission means, a reception means, and a display means. By coordinating these means, it becomes possible to quickly and safely present evacuation routes even in the event of a large-scale earthquake disaster.

[0095] earthquake sensing

[0096] First, an earthquake detection sensor is connected to the server. When the earthquake detection sensor detects an earthquake, it sends the data to the server in real time. A general-purpose earthquake detection sensor is used for this purpose.

[0097] Sending evacuation alerts

[0098] When the server detects an earthquake, it immediately sends an evacuation alert to the mobile devices of all registered users. This alert includes an urgent message such as, "Earthquake! Evacuate immediately!" The server uses a push notification service (e.g., Firebase Cloud Messaging) to send this message.

[0099] Inquiry about evacuation routes

[0100] When a user receives an evacuation alert on their mobile device, they launch a dedicated application. Through this application, the user sends a request saying, "Please tell me the evacuation route." This request is sent to the server as an HTTP POST request.

[0101] Get current location

[0102] When the server receives a user request, it obtains location information from the mobile device's GPS. The location information obtained by the GPS module is used to determine the user's current location.

[0103] Collection of pedestrian flow data and calculation of evacuation routes

[0104] The server collects data in real time from pedestrian flow sensors installed inside the building to determine the density of people within the building. Based on this pedestrian flow data and location information, the server calculates evacuation routes. Algorithms such as Dijkstra's algorithm are used for this calculation.

[0105] Evacuation order notification

[0106] The server notifies the user's mobile device of the calculated optimal evacuation route. Specifically, it sends detailed evacuation instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." The server then sends this again using a push notification service.

[0107] Evacuation route display

[0108] The user displays the evacuation order notified on their mobile device. The dedicated application uses Google Maps API and other technologies to display the evacuation route on a map from the user's current location. This allows the user to visually confirm the evacuation route and evacuate safely.

[0109] Specific example

[0110] The following is a specific example of how the system works during an earthquake. When an earthquake occurs in a company building, the server immediately receives data from earthquake detection sensors and sends an alert to all employees' mobile devices saying, "Earthquake! Evacuate immediately!" User A, upon receiving the alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and calculates the optimal evacuation route based on data from pedestrian flow sensors. Based on the calculation results, User A's mobile device is notified with the instruction, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." User A can then confirm the evacuation route on their mobile device screen and evacuate quickly via the designated route.

[0111] Example of a prompt

[0112] Please describe in detail the "system for issuing rapid evacuation instructions during an earthquake." Use the subjects of server, terminal, and user, and clearly describe the specific actions, including each sensor, location information, and the process of sending evacuation alerts. For example, "The server, upon confirming the occurrence of an earthquake, sends an evacuation alert to all registered mobile terminals." Please show the specific flow of the process.

[0113] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0114] Program processing flow

[0115] Step 1: Receiving earthquake detection data

[0116] The server receives data from earthquake sensors in real time. It receives vibration data sent from the earthquake sensors as input and analyzes it. If vibrations exceeding a threshold are detected, an earthquake occurrence flag is set. The server also sets the earthquake occurrence flag as output.

[0117] Specific operation: The server polls data from the sensor every 0.1 seconds, and if vibrations exceeding a threshold are detected, it sets an earthquake occurrence flag.

[0118] Step 2: Sending an evacuation alert

[0119] When the server detects an earthquake flag, it sends an evacuation alert to all registered mobile devices. It uses the earthquake flag and user list as input to send push notifications to each user. The output is an evacuation alert sent to each mobile device.

[0120] Specific operation: The server uses a push notification service (e.g., Firebase Cloud Messaging) to send evacuation alert messages to each mobile device.

[0121] Step 3: Request an evacuation route

[0122] When a user receives an evacuation alert, they launch a dedicated app and enter a request for an evacuation route. The user enters "Please tell me the evacuation route" into the app as input, generating a request. The request is then sent to the server as output.

[0123] Specific operation: The user enters a message in the app's text input field and presses the send button. The app sends a request to the server as an HTTP POST request.

[0124] Step 4: Obtain current location

[0125] When the server receives a request from a user, it obtains location information from the mobile device's GPS. It receives the request and location information from the GPS module as input to determine the user's current location. The output is the user's latitude and longitude data.

[0126] Specific operation: The server receives an HTTP request from the terminal, calls a location information acquisition API to obtain latitude and longitude, and saves this information to the database.

[0127] Step 5: Collecting pedestrian flow data and calculating evacuation routes

[0128] The server collects data in real time from pedestrian flow sensors inside the building. It receives data from the pedestrian flow sensors and user location information as input, and uses an algorithm to calculate the optimal evacuation route. The calculated evacuation route is then output.

[0129] Specific operation: The server uses database queries to retrieve the latest human flow data and calculates the optimal evacuation route using algorithms such as Dijkstra's algorithm.

[0130] Step 6: Notification of evacuation order

[0131] The server sends the calculated optimal evacuation route to the user's mobile device. Using the calculated evacuation route and user information as input, it generates and sends a detailed evacuation instruction message. The user's mobile device receives the evacuation instruction as output.

[0132] Specific action: The server will again use the push notification service to send evacuation instructions, including detailed evacuation routes, to the user's mobile device.

[0133] Step 7: Displaying evacuation routes

[0134] The user's mobile device displays received evacuation orders via a dedicated app. The input is the received and displayed evacuation order message. The output is a screen showing the evacuation route, which the user can visually confirm.

[0135] Specific operation: The app uses the Google Maps API to display evacuation routes on a map from the user's current location, allowing for visual confirmation.

[0136] (Application Example 1)

[0137] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0138] In recent years, rapid and safe evacuation during earthquakes in factories has become increasingly important. However, conventional earthquake response systems limit evacuation route guidance to humans, making it difficult to control the appropriate actions of robots within the factory. This can lead to robots becoming obstacles or hindering human evacuation. There is a need to solve this problem and provide a system that allows all personnel and robots in a factory to evacuate safely.

[0139] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0140] In this invention, the server includes earthquake sensing means, location information means for acquiring the current location of personnel, calculation means for calculating the optimal evacuation route to at least one emergency exit, transmission means for generating and transmitting evacuation instructions including the evacuation route to the emergency exit, receiving means for receiving evacuation instructions via the user's mobile terminal, display means for displaying the user's location and evacuation route based on the location information means and evacuation instructions, and means for notifying a robot of the evacuation instructions and having the robot execute the evacuation instructions. This enables personnel and robots in the factory to evacuate quickly and safely.

[0141] An "earthquake detection device" is a device that can detect the occurrence of an earthquake and transmit the vibration information to a server in real time.

[0142] "Location information means" refers to technologies for obtaining the current location of a user or object, and generally involves using GPS or other location detection systems.

[0143] A "calculation means" is a device or system that performs processing to calculate the optimal evacuation route based on multiple data points.

[0144] A "transmission means" is a device that has the function of transmitting calculated evacuation routes and other important information to users or robots.

[0145] A "receiving device" is a device that allows a user's mobile terminal or robot to receive evacuation instructions from a transmitting device.

[0146] "Display means" refers to a device or system for visually displaying evacuation routes received from a transmission means, and usually includes a display device or monitor.

[0147] A "people flow sensor" is a sensor that monitors the density of people inside a building in real time and transmits that data to a server.

[0148] "Seismic intensity" is a measure that indicates the strength of earthquake shaking, and it is the criterion for issuing evacuation orders when the seismic intensity exceeds a specified level.

[0149] A "robot" is an automated mechanical device designed to perform specific tasks in a factory or other work environment.

[0150] "Means for executing evacuation orders" refers to a control system within a robot that recognizes evacuation orders from a receiving means and acts in accordance with those orders.

[0151] This invention is a system that supports rapid and safe evacuation in the event of an earthquake in a factory. The system includes the following means:

[0152] Earthquake sensing means

[0153] The server monitors data from earthquake sensors in real time and immediately detects the occurrence of an earthquake. This detection information is sent to the server, and the process proceeds to the next step.

[0154] Location information means

[0155] To obtain the current location of users and robots, location information systems such as GPS are used. The server acquires location information transmitted from users and robots in real time and uses this information to calculate the optimal evacuation route.

[0156] means of calculation

[0157] The server calculates evacuation routes based on earthquake detection data, location data, and data from pedestrian flow sensors. It uses powerful CPUs and AI algorithms to quickly determine the optimal evacuation route. This calculation process employs algorithms to avoid congestion and methods to find the shortest distance.

[0158] Transmission method

[0159] The server uses a communication module to send the calculated optimal evacuation route to users and robots. Evacuation instructions are sent to users' mobile devices and robots within the factory, providing evacuation routes and action instructions.

[0160] Receiving means

[0161] The user's mobile device or robot receives evacuation instructions transmitted from the server. On the mobile device, launching a dedicated app displays evacuation routes and instructions. Meanwhile, the robot begins its actions based on the received evacuation instructions and safely evacuates along the designated route.

[0162] Display means

[0163] Evacuation instructions sent from the server are displayed on mobile devices and robot displays. On mobile devices, the route is displayed on a map, allowing users to visually confirm the specific evacuation path. On robots, the instructions are displayed through internal displays and interfaces.

[0164] Execution of evacuation orders

[0165] The robot begins its actions based on the evacuation instructions it receives. Following instructions from the server, the robot proceeds along the designated evacuation route. During this process, additional processing is performed using sensors and cameras to avoid obstacles.

[0166] Specific example

[0167] When an earthquake occurs, robot R1, which is working inside the factory, immediately receives earthquake detection information and transmits it to the server. The server confirms robot R1's current location and calculates the optimal evacuation route based on data from the pedestrian flow sensor. The server then sends an evacuation instruction to robot R1: "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." Based on the received instruction, robot R1 proceeds along the evacuation route and begins to safely evacuate to the emergency exit.

[0168] Example of a prompt

[0169] "Retrieve data from the earthquake detection API and analyze that data."

[0170] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0171] Step 1:

[0172] The server monitors data from earthquake detection sensors in real time and detects the occurrence of an earthquake. The server analyzes acceleration data and shaking intensity data transmitted from the sensors and recognizes an earthquake has occurred if they exceed a certain threshold. The input is real-time data from the sensors, and the output is confirmed information that an earthquake has occurred.

[0173] Step 2:

[0174] After confirming the occurrence of an earthquake, the server sends an evacuation alert to all registered mobile devices and robots. This uses a communication module to send the message, "Earthquake! Evacuate immediately!" The input is the confirmed information that an earthquake has occurred, and the output is a notification that the alert message has been successfully sent.

[0175] Step 3:

[0176] After receiving an earthquake alert, users and robots launch a dedicated app on their mobile devices and inquire about evacuation routes. Users might type, "Please tell me the evacuation route." Robots automatically send an evacuation request to the server. Input is the user's request or an automated request from the robot, and output is confirmation of the request's receipt.

[0177] Step 4:

[0178] When the server receives an evacuation route request from a user or robot, it obtains its current location using location information. For users, it obtains GPS data from their mobile device; for robots, it obtains data from their built-in location detection system. The input is data indicating the current location, and the output is the identified location information of the user or robot.

[0179] Step 5:

[0180] The server collects real-time occupancy density data from pedestrian flow sensors installed inside the building and calculates the optimal evacuation route based on location information and pedestrian flow data. It uses algorithms to avoid congestion and shortest distance search algorithms to generate calculation results. The input is the identified location information of users and robots, as well as data from pedestrian flow sensors, and the output is the optimal evacuation route.

[0181] Step 6:

[0182] The server transmits the calculated optimal evacuation route to the user's mobile device and robot, providing specific evacuation instructions. The route is displayed on a map on the user's device, and detailed instructions are conveyed to the robot. The input is information on the optimal evacuation route, and the output is the transmission of sequential evacuation instructions.

[0183] Step 7:

[0184] The user's mobile device and the robot display the received evacuation instructions and begin taking action accordingly. The user evacuates by viewing the map displayed on the device, and the robot moves to a safe location along the evacuation route. The input is the evacuation instruction information, and the output is the execution of the evacuation action.

[0185] Example of a prompt

[0186] "Retrieve data from the earthquake detection API and analyze that data."

[0187] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0188] Modes for carrying out the invention

[0189] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, display means, and emotion engine. This makes it possible to provide a rapid and safe evacuation route in the event of an earthquake, recognize the user's emotional state, and dynamically provide optimal evacuation instructions.

[0190] Earthquake sensing means

[0191] The server monitors earthquake sensors and detects earthquakes in real time. If the earthquake intensity exceeds a certain threshold, that information is immediately sent to the server, and an earthquake alert is issued.

[0192] Location information and evacuation alert transmission

[0193] Upon confirming the occurrence of an earthquake, the server sends an earthquake alert to all registered mobile devices. This alert includes the message, "Earthquake! Evacuate immediately!" Users receive this alert and launch the dedicated app on their mobile devices.

[0194] Inquiry about evacuation routes

[0195] When a user launches the dedicated app and enters "Please tell me the evacuation route," this request is sent to the server. The server retrieves the user's current location information and determines their location.

[0196] Collection of pedestrian flow data and calculation of evacuation routes

[0197] The server collects data from pedestrian flow sensors installed inside the building. These sensors monitor the movement and density of people inside the building in real time and transmit this data to the server. Based on the location information and pedestrian flow data, the server uses computational tools to calculate the optimal evacuation route.

[0198] Emotional analysis and adjustment of evacuation orders using an emotional engine.

[0199] The emotion engine installed on the server analyzes voice data sent by the user and facial expression data captured by the mobile device's camera. Based on this data, the emotion engine determines the user's mental state and whether or not the user is in a state of panic. If the user is in a state of panic, the emotion engine generates gentle instructions to calm them down.

[0200] Evacuation order notification and display

[0201] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. For example, the instructions might include, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." These instructions are dynamically adjusted according to the user's emotional state. The device displays the received evacuation instructions, allowing the user to visually confirm them.

[0202] Specific example

[0203] Let's consider a specific example of what happens during an earthquake. An earthquake occurs in a company building, and the server immediately receives data from earthquake detection sensors. The server sends an alert to all employees' mobile devices saying, "Earthquake!" User A, upon receiving this alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and identifies their position. Simultaneously, it collects data from pedestrian flow sensors within the building to check the congestion level. Based on the obtained data, the server calculates the optimal evacuation route, and the emotion engine analyzes User A's facial expression data. If it is determined that User A is in a state of panic, the server sends a pre-configured instruction to the mobile device saying, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor." User A checks the displayed evacuation route and calmly begins to evacuate. In this way, appropriate evacuation is achieved even during an earthquake, according to the user's emotional state.

[0204] The following describes the processing flow.

[0205] Step 1:

[0206] The server monitors earthquake detection sensors. When an earthquake is detected by an earthquake detection sensor, data on its speed and intensity is sent to the server.

[0207] Step 2:

[0208] The server analyzes earthquake data and determines the seismic intensity. If the seismic intensity exceeds a certain threshold, it is determined that an earthquake has occurred.

[0209] Step 3:

[0210] The server sends an earthquake alert to all registered mobile devices. The alert message includes content such as "Earthquake! Evacuate immediately!"

[0211] Step 4:

[0212] The user receives an earthquake alert and launches a dedicated app on their mobile device. The user then types "Please tell me the evacuation route" to inquire about evacuation routes.

[0213] Step 5:

[0214] The terminal sends an evacuation route inquiry from the user to the server. This request also includes information about the user's current location.

[0215] Step 6:

[0216] The server uses location information to determine the user's current location. This location information is obtained from sources such as GPS data from a mobile device.

[0217] Step 7:

[0218] The server collects data from pedestrian flow sensors within the building. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server.

[0219] Step 8:

[0220] The server calculates evacuation routes based on the user's current location and density data obtained from pedestrian flow sensors. The calculation method prioritizes less congested routes to determine the optimal evacuation path.

[0221] Step 9:

[0222] The server requests data from the device to acquire the user's voice and facial expressions. The device uses its camera and microphone to collect the user's voice and facial expression data and sends it to the server.

[0223] Step 10:

[0224] The emotion engine installed on the server analyzes the transmitted voice and facial expression data to determine the user's emotional state. It analyzes whether the user is in a state of panic.

[0225] Step 11:

[0226] Based on the analysis results of the emotion engine, the server adjusts the content and format of evacuation instructions according to the user's emotional state. For example, if the user is in a panic state, it will generate gentler instructions such as, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor."

[0227] Step 12:

[0228] The server sends coordinated evacuation instructions to the user's mobile device. These instructions include specific routes and evacuation procedures.

[0229] Step 13:

[0230] The device displays the evacuation instructions it has received. Depending on the display method, the evacuation route is shown to the user in a way that is easily visible, such as on a map or in text.

[0231] Step 14:

[0232] The user checks the displayed evacuation route and begins evacuating according to the instructions. Based on the information provided by the server and instructions tailored to their emotional state, the user can safely evacuate via the optimal route.

[0233] (Example 2)

[0234] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0235] While systems exist to provide evacuation routes for rapid and safe evacuation during earthquakes, they face challenges in providing dynamic evacuation instructions that take into account factors such as the density of people in a building and the emotional state of individual users. Furthermore, if users panic, there is a high probability that appropriate evacuation instructions will not be provided, potentially delaying evacuation. As a result, problems arise where evacuations are not carried out efficiently or safely.

[0236] The identification processing performed 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 detecting earthquakes, means for acquiring the current location of personnel, means for measuring the density of personnel inside the building, means for calculating the optimal evacuation route, means for analyzing the emotional state of the user, means for generating and transmitting evacuation instructions including an evacuation route to an emergency exit, means for receiving evacuation instructions via the user's information terminal, and means for displaying the user's location and evacuation route based on location information and evacuation instructions. This enables rapid and safe evacuation even when an earthquake occurs, taking into account the emotional state of the user and the density of personnel inside the building.

[0237] "Means for detecting earthquakes" refers to sensor devices that detect the occurrence of earthquakes in real time and immediately transmit data such as seismic intensity and time of occurrence to a server.

[0238] "Means for obtaining the current location of personnel" refers to technologies that accurately obtain the user's current location information using GPS, Wi-Fi, beacons, etc.

[0239] "Means for measuring the density of people inside a building" refers to a sensor device that monitors the movement and density of people inside a building in real time and transmits that data to a server.

[0240] "Methods for calculating the optimal evacuation route" refers to a technology that uses algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs to calculate a safe and rapid evacuation route based on location information and population density data collected during an earthquake.

[0241] "Methods for analyzing a user's emotional state" refers to technologies that use machine learning algorithms to analyze voice data and facial expression data transmitted by the user to determine the user's mental state.

[0242] "Means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits" refers to a device that dynamically generates evacuation instructions based on the user's current location and the optimal evacuation route, and transmits them to the user's information terminal via communication technology.

[0243] "Means of receiving evacuation instructions via the user's information terminal" refers to technology that allows evacuation instructions transmitted from a server to be received by the user's information terminal, such as a smartphone or tablet.

[0244] "Means for displaying a user's location and evacuation route based on location information and evacuation orders" refers to a technology that visually displays received location information and evacuation orders on the user's information terminal, enabling the user to confirm their evacuation route.

[0245] Modes for carrying out the invention

[0246] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, display means, and emotion engine. Details of how this system specifically operates are described below.

[0247] Earthquake sensing means

[0248] The server constantly monitors earthquake detection sensors. These sensors include, for example, accelerometers and seismometers. When these sensors detect an earthquake and the seismic intensity exceeds a certain threshold, that information is immediately sent to the server.

[0249] Location information and evacuation alert transmission

[0250] Upon confirming the occurrence of an earthquake, the server sends an earthquake alert to all registered mobile devices. This alert includes the message, "Earthquake! Evacuate immediately!" Users receive this alert and launch the dedicated app on their mobile devices.

[0251] Inquiry about evacuation routes

[0252] When a user launches the dedicated app and enters "Please tell me the evacuation route," this request is sent to the server. The server obtains the user's current location information and determines its location. Location information is obtained using GPS, Wi-Fi, beacons, etc.

[0253] Collection of pedestrian flow data and calculation of evacuation routes

[0254] The server collects data from pedestrian flow sensors installed inside the building. These sensors include infrared sensors and laser sensors. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server. Based on the location information and pedestrian flow data, the server calculates the optimal evacuation route using computational methods. Algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs are used.

[0255] Emotional analysis and adjustment of evacuation orders using an emotional engine.

[0256] The emotion engine installed on the server analyzes voice data transmitted by the user and facial expression data captured by the mobile device's camera. The emotion engine uses machine learning algorithms to determine the user's mental state and whether or not the user is in a state of panic. For example, it analyzes changes in voice tone and facial expression.

[0257] Evacuation order notification and display

[0258] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. For example, the instructions might include, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." These instructions are dynamically adjusted according to the user's emotional state. The mobile device displays the received evacuation instructions, allowing the user to visually confirm them.

[0259] Specific example

[0260] The following are specific examples of what happens when an earthquake occurs.

[0261] An earthquake occurs inside a building, and the server immediately receives data from earthquake detection sensors. Next, the server sends an alert to all employees' mobile devices saying "Earthquake!". User A, upon receiving this alert, launches a dedicated app on their mobile device and enters "Please tell me the evacuation route." The server obtains User A's location information and locates their position. Simultaneously, it collects data from pedestrian flow sensors within the building to check the congestion level. Based on the data obtained, the server calculates the optimal evacuation route, and an emotion engine analyzes User A's facial expression data. If it is determined that User A is in a state of panic, the server sends pre-configured instructions to the mobile device saying, "Stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor." User A checks the displayed evacuation route and calmly begins to evacuate.

[0262] Example of a prompt

[0263] "An earthquake has occurred, please tell me the evacuation routes."

[0264] "Please tell me the best evacuation route from my current location."

[0265] "Calculate the optimal evacuation route and provide evacuation instructions that take emotions into consideration."

[0266] By using these prompts, specific and natural evacuation instructions can be obtained.

[0267] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0268] System program processing flow

[0269] Step 1: Earthquake detection

[0270] The server monitors data from earthquake sensors in real time. When a sensor detects an earthquake and the seismic intensity exceeds a certain threshold, that information is immediately sent to the server.

[0271] Input: Data from earthquake detection sensors

[0272] Data processing: Compare with seismic intensity thresholds and generate an alert if the threshold is exceeded.

[0273] Output: Earthquake alert information

[0274] Step 2: Sending an earthquake alert

[0275] When the server receives an alert from an earthquake detection sensor, it immediately sends an earthquake alert to all registered mobile devices. The message includes "Earthquake! Evacuate immediately!"

[0276] Input: Earthquake alert information

[0277] Data processing: Message generation

[0278] Output: Alert notification sent to the user's mobile device.

[0279] Step 3: Accepting requests for evacuation routes

[0280] Users who receive an earthquake alert launch a dedicated app and type "Please tell me the evacuation route." This request is sent to the server.

[0281] Input: User's evacuation route request

[0282] Data processing: Analysis of request content

[0283] Output: Request data to the server

[0284] Step 4: Acquisition of location information

[0285] The server acquires location information data from the user's mobile terminal. This location information is collected using technologies such as GPS, Wi-Fi, and beacons.

[0286] Input: User's location information request

[0287] Data processing: Analysis and identification of location information

[0288] Output: User's current location information

[0289] Step 5: Collection of pedestrian flow data

[0290] The server collects data from the pedestrian flow sensors installed inside the building. The sensors monitor the movement and density of people inside the building in real time and transmit that information to the server.

[0291] Input: Data from pedestrian flow sensors

[0292] Data processing: Measurement of people's movement and density

[0293] Output: Pedestrian flow data inside the building

[0294] Step 6: Calculation of the optimal evacuation route

[0295] The server calculates the optimal evacuation route using calculation means based on the location information and pedestrian flow data. Algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs are used.

[0296] Input: User's current location information, crowd flow data

[0297] Data processing: Calculation of evacuation route

[0298] Output: Optimal evacuation route

[0299] Step 7: Sentiment analysis

[0300] The sentiment engine installed on the server analyzes the voice data transmitted from the user and the facial expression data captured by the mobile terminal camera. It uses machine learning algorithms to determine the user's mental state and judge whether the user is in a panic state.

[0301] Input: User's voice data, facial expression data

[0302] Data processing: Analysis of emotional state

[0303] Output: User's emotional state information

[0304] Step 8: Generation and transmission of evacuation instructions

[0305] Based on the analysis results of the sentiment engine, the server generates evacuation instructions in the optimal format and sends them to the user's mobile terminal. Instructions such as "Please use the central staircase A on the 12th floor and evacuate from Exit C on the 1st floor" are included.

[0306] Input: Optimal evacuation route, user's emotional state information

[0307] Data processing: Generation of evacuation instructions

[0308] Output: Notification of evacuation instructions to the mobile terminal

[0309] Step 9: Display of evacuation instructions

[0310] The terminal visually displays the received evacuation instructions. The user looks at the screen of the mobile terminal and starts evacuating according to the instructed route.

[0311] Input: Evacuation order notification to mobile device

[0312] Data processing: Generating data for display

[0313] Output: Display of evacuation order

[0314] (Application Example 2)

[0315] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0316] While rapid and safe evacuation is crucial during an earthquake, the potential for panic among evacuees makes issuing appropriate evacuation instructions difficult. In such situations, evacuation instructions need to consider the psychological state of evacuees, along with optimizing crowd density and evacuation routes. Furthermore, there is a need for means of providing visually and audibly useful evacuation information.

[0317] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0318] In this invention, the server includes earthquake sensing means, location information means, emotion analysis means, evacuation instruction adjustment means, transmission means, reception means, and display means. This enables the rapid and safe provision of evacuation routes in the event of an earthquake, as well as the recognition of the user's emotional state and the dynamic provision of optimal evacuation instructions. Furthermore, by visually displaying evacuation routes using a head-mounted display and providing personalized prompt messages using a generation AI model, more effective evacuation instructions can be given to the user.

[0319] An "earthquake detection device" is a device or system that detects the occurrence of an earthquake in real time and immediately transmits that information to a server.

[0320] "Location information means" refers to devices and functions such as GPS and indoor location information systems used to obtain the user's current location.

[0321] "Calculation means" refers to algorithms and programs that calculate the optimal evacuation route based on acquired location information and pedestrian flow sensor data.

[0322] "Transmission means" refers to a device or system that transmits calculated evacuation routes and evacuation instructions to the user's mobile terminal.

[0323] "Receiving means" refers to functions or devices that allow a user's mobile device to receive evacuation instructions sent from the transmitting means.

[0324] "Display means" refers to functions or devices for visually displaying received evacuation instructions and route information on the user's mobile device or head-mounted display.

[0325] "Emotional analysis tools" are algorithms and programs that analyze a user's voice data and facial expression data to identify the user's emotional state.

[0326] "Adjustment means" refers to a function or system that dynamically changes the content of evacuation orders according to the user's emotional state obtained from emotion analysis means.

[0327] A "people flow sensor" is a device or system that monitors the density and flow of people within a large building in real time and transmits that data to a server.

[0328] A "head-mounted display" is a display device that a user wears to display information within their field of vision.

[0329] A "generative AI model" is a machine learning model designed to perform a specific task and is used to generate personalized evacuation instructions and prompts for users.

[0330] A "prompt" is a formalized instruction or query text input to a generative AI model, intended to produce appropriate output according to the purpose.

[0331] The system for implementing the present invention comprises earthquake sensing means, location information means, emotion analysis means, evacuation instruction adjustment means, transmission means, reception means, and display means. This system makes it possible to dynamically provide the optimal evacuation route while considering the user's emotional state when an earthquake occurs.

[0332] 1. Earthquake sensing means

[0333] The server monitors earthquake detection sensors (e.g., Shindol, GeoSIG) and detects earthquakes in real time. If the earthquake intensity exceeds a certain threshold, the information is immediately sent to the server, which generates an earthquake alert and sends it to the user's mobile device.

[0334] 2. Location information means

[0335] The server uses the user's mobile device (e.g., iPhone®, Android®) GPS and indoor location systems (e.g., Bluetooth Beacon, Wi-Fi RTT) to obtain the user's current location. This location information is used in combination with data obtained from pedestrian flow sensors inside the building to calculate the optimal evacuation route.

[0336] 3. Emotion analysis means

[0337] The server analyzes the user's voice data and facial expression data captured by the mobile device's camera using an emotion analysis engine (e.g., Microsoft® Azure® Cognitive Services, Google Cloud Emotion API, Amazon Rekognition). This allows the server to determine the user's psychological state, particularly whether they are in a state of panic.

[0338] 4. Evacuation order coordination means

[0339] If the server determines that a user is in a state of panic, the evacuation instruction coordination mechanism generates gradual evacuation instructions to encourage calm action. This allows the user to take appropriate evacuation actions.

[0340] 5. Transmission method

[0341] The server sends evacuation instructions to the user's mobile device, based on the optimal evacuation route calculated by the computational means and the results obtained from the sentiment analysis means.

[0342] 6. Receiving means

[0343] The user's mobile device receives evacuation instructions transmitted from the server. This receiving mechanism functions through a specific, dedicated application.

[0344] 7. Display means

[0345] The user's mobile device or head-mounted display (e.g., HoloLens®, Meta Quest) visually displays received evacuation instructions and route information. Furthermore, it provides voice guidance based on sentiment analysis results.

[0346] Specific example

[0347] When user A, who is inside a building experiencing an earthquake, launches the application, the server immediately receives information from earthquake detection sensors. The server obtains user A's current location and collects data from pedestrian flow sensors inside the building to calculate the optimal evacuation route. Furthermore, it analyzes user A's voice and facial expression data using an emotion analysis engine, and if it determines that user A is in a state of panic, it generates calming instructions. Gentle instructions such as, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor," are provided.

[0348] Example of a prompt

[0349] "When an earthquake is detected by the earthquake detection sensor, quickly obtain the user's current location, calculate the optimal evacuation route considering the congestion level within the building, and provide evacuation instructions based on the user's psychological state."

[0350] This configuration makes it possible to support swift and appropriate evacuation actions while taking into account the user's emotional state during an earthquake.

[0351] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0352] Step 1:

[0353] The server monitors data from earthquake sensors in real time and detects the occurrence of an earthquake. When the earthquake intensity exceeds a certain threshold, it immediately sends that information to the server (input: earthquake sensor data, output: earthquake occurrence alert). Subsequently, the server sends earthquake occurrence alerts to all registered users (specific actions: reading sensor data, threshold determination, generating and sending alert messages).

[0354] Step 2:

[0355] When the user's device receives an alert, it launches a dedicated app. The app immediately uses location information to send the current location to the server (input: alert message, GPS data; output: current location information). This current location information is used to calculate evacuation routes (specific actions: app launch, location information reading, location information transmission).

[0356] Step 3:

[0357] The server combines the received current location information with real-time data obtained from pedestrian flow sensors inside the building to calculate the optimal evacuation route (input: current location information, pedestrian flow data; output: optimal evacuation route). This calculation is performed using pathfinding algorithms such as Dijkstra's algorithm (specific operation: data collection, path calculation, path information generation).

[0358] Step 4:

[0359] The server receives the user's voice and camera data and uses an emotion analysis engine to analyze the user's emotional state (input: voice data, image data; output: emotion analysis results). This analysis determines whether the user is in a state of panic (specific actions: data collection, application of emotion analysis engine, generation of analysis results).

[0360] Step 5:

[0361] If the emotion analysis results indicate a "panic state," the server uses an evacuation instruction adjustment mechanism to generate a gentle evacuation instruction that will allow the user to act calmly (Input: Emotion analysis result, optimal evacuation route; Output: Adjusted evacuation instruction). This involves generating personalized prompt sentences using a generation AI model (Specific actions: Analysis result determination, instruction adjustment, prompt sentence generation).

[0362] Step 6:

[0363] The server sends a pre-configured evacuation order to the user's terminal (input: pre-configured evacuation order, output: evacuation order to terminal). The user's terminal receives this order, displays it visually on its display device, and also plays an audio guide (specific actions: sending evacuation order, receiving order, visual display, audio playback).

[0364] Step 7:

[0365] The user follows the designated evacuation route and takes appropriate evacuation actions based on sentiment analysis (input: visual display and audio guidance, output: appropriate evacuation actions). This enables the user to evacuate safely while suppressing panic (specific actions: start of evacuation, confirmation of instructions, execution of evacuation actions).

[0366] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0367] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0368] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0369] [Second Embodiment]

[0370] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0371] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0372] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0373] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0374] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0375] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0376] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0377] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0378] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0379] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0380] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0381] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0382] Modes for carrying out the invention

[0383] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, and display means. By coordinating these means, it is possible to provide evacuation routes quickly and safely even in the event of a large-scale disaster.

[0384] Earthquake sensing means

[0385] The server monitors data from earthquake sensors in real time and immediately detects the occurrence of an earthquake. This information is sent to the server, and the process moves on to the next step of notifying the server of the earthquake.

[0386] Sending evacuation alerts

[0387] Once the server detects an earthquake, it sends an evacuation alert to all registered mobile devices. This alert includes a message informing users of the earthquake and urging them to evacuate to a safe place immediately. For example, a message such as "Earthquake! Evacuate immediately!" is sent to each user's mobile device.

[0388] Inquiry about evacuation routes

[0389] After receiving an earthquake alert, users launch a dedicated app on their mobile device and inquire about evacuation routes. For example, if a user types "Please tell me the evacuation route," this request is sent to the server.

[0390] Get current location

[0391] The server receives a user request and obtains location information (such as GPS data) from the mobile device. Based on this information, it determines the user's current location and uses that location data in the next step.

[0392] Collection of pedestrian flow data and calculation of evacuation routes

[0393] The server collects real-time occupancy density data from pedestrian flow sensors installed inside the building. Based on location information and pedestrian flow data, it then uses computational methods to calculate the optimal evacuation route. For example, to avoid congestion, it calculates a route that includes the currently least crowded stairwells and exits.

[0394] Evacuation order notification

[0395] The server sends the calculated optimal evacuation route to the user's mobile device. Specifically, it includes detailed evacuation instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[0396] Evacuation route display

[0397] The user's mobile device displays the received evacuation instructions. The display method allows the user to visually confirm the evacuation route. For example, displaying the route on a map allows the user to easily understand the specific evacuation path.

[0398] Specific example

[0399] Let's consider a specific example of what happens during an earthquake. An earthquake occurs in a company building, and the server immediately receives data from earthquake detection sensors. The server sends an alert to all employees' mobile devices saying, "Earthquake! Evacuate immediately!" User A, upon receiving this alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and identifies their position. Simultaneously, it collects data from pedestrian flow sensors to check the congestion level. Based on the data obtained, the server calculates the optimal evacuation route and notifies User A's mobile device, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." User A can confirm the received instructions on their mobile device screen and evacuate quickly via the designated route. In this way, smooth evacuation is achieved even during an earthquake.

[0400] The following describes the processing flow.

[0401] Step 1:

[0402] The server monitors earthquake detection sensors. When an earthquake is detected by an earthquake detection sensor, data on its speed and intensity is sent to the server.

[0403] Step 2:

[0404] The server analyzes earthquake data and determines the seismic intensity. If the seismic intensity exceeds a certain threshold, it is determined that an earthquake has occurred.

[0405] Step 3:

[0406] The server sends an earthquake alert to all registered mobile devices. The alert message includes content such as "Earthquake! Evacuate immediately!"

[0407] Step 4:

[0408] The user receives an earthquake alert and launches a dedicated app on their mobile device. The user then types "Please tell me the evacuation route" to inquire about evacuation routes.

[0409] Step 5:

[0410] The terminal sends an evacuation route inquiry from the user to the server. This request also includes information about the user's current location.

[0411] Step 6:

[0412] The server uses location information to determine the user's current location. This location information is obtained from sources such as GPS data from a mobile device.

[0413] Step 7:

[0414] The server collects data from pedestrian flow sensors within the building. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server.

[0415] Step 8:

[0416] The server calculates evacuation routes based on the user's current location and density data obtained from pedestrian flow sensors. The calculation method prioritizes less congested routes to determine the optimal evacuation path.

[0417] Step 9:

[0418] The server calculates the optimal evacuation route and sends it to the user's mobile device. For example, it might send instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[0419] Step 10:

[0420] The device displays the evacuation route it received. Depending on the display method, the evacuation route is displayed to the user in a way that is easily visible, such as on a map or in text.

[0421] Step 11:

[0422] The user checks the displayed evacuation route and begins evacuating according to the instructions. By following the instructions on the device, the user can safely evacuate via the optimal route.

[0423] (Example 1)

[0424] Next, we will describe Example 1. 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."

[0425] In the event of a large-scale earthquake disaster, an effective information system is needed to ensure rapid and safe evacuation. In particular, when large numbers of people begin evacuating simultaneously, congestion and panic are likely to occur, potentially delaying evacuation. Under these circumstances, the challenge lies in providing real-time situational awareness and accurate guidance on evacuation routes.

[0426] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0427] In this invention, the server includes means for receiving data from earthquake detection sensors in real time, means for acquiring location information of the user's mobile device, means for collecting data from pedestrian flow sensors installed inside the building and calculating the optimal evacuation route, means for generating and transmitting evacuation alerts and evacuation routes, and means for receiving and displaying evacuation routes via the user's mobile device. This enables the provision of rapid and safe evacuation routes and avoidance of congestion even in the event of a large-scale earthquake disaster.

[0428] An "earthquake detection sensor" is a device that detects earthquake vibrations and transmits that information to a server in real time.

[0429] "Real-time" means that data is processed the moment it is generated, and results are obtained almost instantly.

[0430] "Mobile devices" refer to portable information and communication devices such as smartphones and tablets owned by users.

[0431] "Location information" refers to data used to determine one's current location, such as GPS.

[0432] A "people flow sensor" is a device that detects the density and movement of people inside a building and collects the data.

[0433] An "evacuation route" refers to a recommended route for safe evacuation during a disaster.

[0434] A "server" refers to a computer system used for processing, calculating, storing, and managing data.

[0435] An "evacuation alert" is an emergency message sent to prompt immediate evacuation during emergencies such as earthquakes.

[0436] "Calculation means" refers to algorithms and software used to calculate the optimal evacuation route.

[0437] "Receiving means" refers to the mechanism by which a user's mobile device receives data transmitted from a server.

[0438] "Display means" refers to display devices or screens used to visually present received evacuation instructions and evacuation routes to the user.

[0439] An "evacuation order" refers to a message that includes specific instructions for actions to take to ensure the user's safe evacuation.

[0440] Modes for carrying out the invention

[0441] The system of the present invention consists of an earthquake detection sensor, a location information acquisition means, a calculation means, a transmission means, a reception means, and a display means. By coordinating these means, it becomes possible to quickly and safely present evacuation routes even in the event of a large-scale earthquake disaster.

[0442] earthquake sensing

[0443] First, an earthquake detection sensor is connected to the server. When the earthquake detection sensor detects an earthquake, it sends the data to the server in real time. A general-purpose earthquake detection sensor is used for this purpose.

[0444] Sending evacuation alerts

[0445] When the server detects an earthquake, it immediately sends an evacuation alert to the mobile devices of all registered users. This alert includes an urgent message such as, "Earthquake! Evacuate immediately!" The server uses a push notification service (e.g., Firebase Cloud Messaging) to send this message.

[0446] Inquiry about evacuation routes

[0447] When a user receives an evacuation alert on their mobile device, they launch a dedicated application. Through this application, the user sends a request saying, "Please tell me the evacuation route." This request is sent to the server as an HTTP POST request.

[0448] Get current location

[0449] When the server receives a user request, it obtains location information from the mobile device's GPS. The location information obtained by the GPS module is used to determine the user's current location.

[0450] Collection of pedestrian flow data and calculation of evacuation routes

[0451] The server collects data in real time from pedestrian flow sensors installed inside the building to determine the density of people within the building. Based on this pedestrian flow data and location information, the server calculates evacuation routes. Algorithms such as Dijkstra's algorithm are used for this calculation.

[0452] Evacuation order notification

[0453] The server notifies the user's mobile device of the calculated optimal evacuation route. Specifically, it sends detailed evacuation instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." The server then sends this again using a push notification service.

[0454] Evacuation route display

[0455] The user displays the evacuation order notified on their mobile device. A dedicated application uses the Google Maps API and other tools to display the evacuation route on a map from the user's current location. This allows the user to visually confirm the evacuation route and evacuate safely.

[0456] Specific example

[0457] The following is a specific example of how the system works during an earthquake. When an earthquake occurs in a company building, the server immediately receives data from earthquake detection sensors and sends an alert to all employees' mobile devices saying, "Earthquake! Evacuate immediately!" User A, upon receiving the alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and calculates the optimal evacuation route based on data from pedestrian flow sensors. Based on the calculation results, User A's mobile device is notified with the instruction, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." User A can then confirm the evacuation route on their mobile device screen and evacuate quickly via the designated route.

[0458] Example of a prompt

[0459] Please describe in detail the "system for issuing rapid evacuation instructions during an earthquake." Use the subjects of server, terminal, and user, and clearly describe the specific actions, including each sensor, location information, and the process of sending evacuation alerts. For example, "The server, upon confirming the occurrence of an earthquake, sends an evacuation alert to all registered mobile terminals." Please show the specific flow of the process.

[0460] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0461] Program processing flow

[0462] Step 1: Receiving earthquake detection data

[0463] The server receives data from earthquake sensors in real time. It receives vibration data sent from the earthquake sensors as input and analyzes it. If vibrations exceeding a threshold are detected, an earthquake occurrence flag is set. The server also sets the earthquake occurrence flag as output.

[0464] Specific operation: The server polls data from the sensor every 0.1 seconds, and if vibrations exceeding a threshold are detected, it sets an earthquake occurrence flag.

[0465] Step 2: Sending an evacuation alert

[0466] When the server detects an earthquake flag, it sends an evacuation alert to all registered mobile devices. It uses the earthquake flag and user list as input to send push notifications to each user. The output is an evacuation alert sent to each mobile device.

[0467] Specific operation: The server uses a push notification service (e.g., Firebase Cloud Messaging) to send evacuation alert messages to each mobile device.

[0468] Step 3: Request an evacuation route

[0469] When a user receives an evacuation alert, they launch a dedicated app and enter a request for an evacuation route. The user enters "Please tell me the evacuation route" into the app as input, generating a request. The request is then sent to the server as output.

[0470] Specific operation: The user enters a message in the app's text input field and presses the send button. The app sends a request to the server as an HTTP POST request.

[0471] Step 4: Obtain current location

[0472] When the server receives a request from a user, it obtains location information from the mobile device's GPS. It receives the request and location information from the GPS module as input to determine the user's current location. The output is the user's latitude and longitude data.

[0473] Specific operation: The server receives an HTTP request from the terminal, calls a location information acquisition API to obtain latitude and longitude, and saves this information to the database.

[0474] Step 5: Collecting pedestrian flow data and calculating evacuation routes

[0475] The server collects data in real time from pedestrian flow sensors inside the building. It receives data from the pedestrian flow sensors and user location information as input, and uses an algorithm to calculate the optimal evacuation route. The calculated evacuation route is then output.

[0476] Specific operation: The server uses database queries to retrieve the latest human flow data and calculates the optimal evacuation route using algorithms such as Dijkstra's algorithm.

[0477] Step 6: Notification of evacuation order

[0478] The server sends the calculated optimal evacuation route to the user's mobile device. Using the calculated evacuation route and user information as input, it generates and sends a detailed evacuation instruction message. The user's mobile device receives the evacuation instruction as output.

[0479] Specific action: The server will again use the push notification service to send evacuation instructions, including detailed evacuation routes, to the user's mobile device.

[0480] Step 7: Displaying evacuation routes

[0481] The user's mobile device displays received evacuation orders via a dedicated app. The input is the received and displayed evacuation order message. The output is a screen showing the evacuation route, which the user can visually confirm.

[0482] Specific operation: The app uses the Google Maps API to display evacuation routes on a map from the user's current location, allowing for visual confirmation.

[0483] (Application Example 1)

[0484] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0485] In recent years, rapid and safe evacuation during earthquakes in factories has become increasingly important. However, conventional earthquake response systems limit evacuation route guidance to humans, making it difficult to control the appropriate actions of robots within the factory. This can lead to robots becoming obstacles or hindering human evacuation. There is a need to solve this problem and provide a system that allows all personnel and robots in a factory to evacuate safely.

[0486] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0487] In this invention, the server includes earthquake sensing means, location information means for acquiring the current location of personnel, calculation means for calculating the optimal evacuation route to at least one emergency exit, transmission means for generating and transmitting evacuation instructions including the evacuation route to the emergency exit, receiving means for receiving evacuation instructions via the user's mobile terminal, display means for displaying the user's location and evacuation route based on the location information means and evacuation instructions, and means for notifying a robot of the evacuation instructions and having the robot execute the evacuation instructions. This enables personnel and robots in the factory to evacuate quickly and safely.

[0488] An "earthquake detection device" is a device that can detect the occurrence of an earthquake and transmit the vibration information to a server in real time.

[0489] "Location information means" refers to technologies for obtaining the current location of a user or object, and generally involves using GPS or other location detection systems.

[0490] A "calculation means" is a device or system that performs processing to calculate the optimal evacuation route based on multiple data points.

[0491] A "transmission means" is a device that has the function of transmitting calculated evacuation routes and other important information to users or robots.

[0492] A "receiving device" is a device that allows a user's mobile terminal or robot to receive evacuation instructions from a transmitting device.

[0493] "Display means" refers to a device or system for visually displaying evacuation routes received from a transmission means, and usually includes a display device or monitor.

[0494] A "people flow sensor" is a sensor that monitors the density of people inside a building in real time and transmits that data to a server.

[0495] "Seismic intensity" is a measure that indicates the strength of earthquake shaking, and it is the criterion for issuing evacuation orders when the seismic intensity exceeds a specified level.

[0496] A "robot" is an automated mechanical device designed to perform specific tasks in a factory or other work environment.

[0497] "Means for executing evacuation orders" refers to a control system within a robot that recognizes evacuation orders from a receiving means and acts in accordance with those orders.

[0498] This invention is a system that supports rapid and safe evacuation in the event of an earthquake in a factory. The system includes the following means:

[0499] Earthquake sensing means

[0500] The server monitors data from earthquake sensors in real time and immediately detects the occurrence of an earthquake. This detection information is sent to the server, and the process proceeds to the next step.

[0501] Location information means

[0502] To obtain the current location of users and robots, location information systems such as GPS are used. The server acquires location information transmitted from users and robots in real time and uses this information to calculate the optimal evacuation route.

[0503] means of calculation

[0504] The server calculates evacuation routes based on earthquake detection data, location data, and data from pedestrian flow sensors. It uses powerful CPUs and AI algorithms to quickly determine the optimal evacuation route. This calculation process employs algorithms to avoid congestion and methods to find the shortest distance.

[0505] Transmission method

[0506] The server uses a communication module to send the calculated optimal evacuation route to users and robots. Evacuation instructions are sent to users' mobile devices and robots within the factory, providing evacuation routes and action instructions.

[0507] Receiving means

[0508] The user's mobile device or robot receives evacuation instructions transmitted from the server. On the mobile device, launching a dedicated app displays evacuation routes and instructions. Meanwhile, the robot begins its actions based on the received evacuation instructions and safely evacuates along the designated route.

[0509] Display means

[0510] Evacuation instructions sent from the server are displayed on mobile devices and robot displays. On mobile devices, the route is displayed on a map, allowing users to visually confirm the specific evacuation path. On robots, the instructions are displayed through internal displays and interfaces.

[0511] Execution of evacuation orders

[0512] The robot begins its actions based on the evacuation instructions it receives. Following instructions from the server, the robot proceeds along the designated evacuation route. During this process, additional processing is performed using sensors and cameras to avoid obstacles.

[0513] Specific example

[0514] When an earthquake occurs, robot R1, which is working inside the factory, immediately receives earthquake detection information and transmits it to the server. The server confirms robot R1's current location and calculates the optimal evacuation route based on data from the pedestrian flow sensor. The server then sends an evacuation instruction to robot R1: "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." Based on the received instruction, robot R1 proceeds along the evacuation route and begins to safely evacuate to the emergency exit.

[0515] Example of a prompt

[0516] "Retrieve data from the earthquake detection API and analyze that data."

[0517] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0518] Step 1:

[0519] The server monitors data from earthquake detection sensors in real time and detects the occurrence of an earthquake. The server analyzes acceleration data and shaking intensity data transmitted from the sensors and recognizes an earthquake has occurred if they exceed a certain threshold. The input is real-time data from the sensors, and the output is confirmed information that an earthquake has occurred.

[0520] Step 2:

[0521] After confirming the occurrence of an earthquake, the server sends an evacuation alert to all registered mobile devices and robots. This uses a communication module to send the message, "Earthquake! Evacuate immediately!" The input is the confirmed information that an earthquake has occurred, and the output is a notification that the alert message has been successfully sent.

[0522] Step 3:

[0523] After receiving an earthquake alert, users and robots launch a dedicated app on their mobile devices and inquire about evacuation routes. Users might type, "Please tell me the evacuation route." Robots automatically send an evacuation request to the server. Input is the user's request or an automated request from the robot, and output is confirmation of the request's receipt.

[0524] Step 4:

[0525] When the server receives an evacuation route request from a user or robot, it obtains its current location using location information. For users, it obtains GPS data from their mobile device; for robots, it obtains data from their built-in location detection system. The input is data indicating the current location, and the output is the identified location information of the user or robot.

[0526] Step 5:

[0527] The server collects real-time occupancy density data from pedestrian flow sensors installed inside the building and calculates the optimal evacuation route based on location information and pedestrian flow data. It uses algorithms to avoid congestion and shortest distance search algorithms to generate calculation results. The input is the identified location information of users and robots, as well as data from pedestrian flow sensors, and the output is the optimal evacuation route.

[0528] Step 6:

[0529] The server transmits the calculated optimal evacuation route to the user's mobile device and robot, providing specific evacuation instructions. The route is displayed on a map on the user's device, and detailed instructions are conveyed to the robot. The input is information on the optimal evacuation route, and the output is the transmission of sequential evacuation instructions.

[0530] Step 7:

[0531] The user's mobile device and the robot display the received evacuation instructions and begin taking action accordingly. The user evacuates by viewing the map displayed on the device, and the robot moves to a safe location along the evacuation route. The input is the evacuation instruction information, and the output is the execution of the evacuation action.

[0532] Example of a prompt

[0533] "Retrieve data from the earthquake detection API and analyze that data."

[0534] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0535] Modes for carrying out the invention

[0536] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, display means, and emotion engine. This makes it possible to provide a rapid and safe evacuation route in the event of an earthquake, recognize the user's emotional state, and dynamically provide optimal evacuation instructions.

[0537] Earthquake sensing means

[0538] The server monitors earthquake sensors and detects earthquakes in real time. If the earthquake intensity exceeds a certain threshold, that information is immediately sent to the server, and an earthquake alert is issued.

[0539] Location information and evacuation alert transmission

[0540] Upon confirming the occurrence of an earthquake, the server sends an earthquake alert to all registered mobile devices. This alert includes the message, "Earthquake! Evacuate immediately!" Users receive this alert and launch the dedicated app on their mobile devices.

[0541] Inquiry about evacuation routes

[0542] When a user launches the dedicated app and enters "Please tell me the evacuation route," this request is sent to the server. The server retrieves the user's current location information and determines their location.

[0543] Collection of pedestrian flow data and calculation of evacuation routes

[0544] The server collects data from pedestrian flow sensors installed inside the building. These sensors monitor the movement and density of people inside the building in real time and transmit this data to the server. Based on the location information and pedestrian flow data, the server uses computational tools to calculate the optimal evacuation route.

[0545] Emotional analysis and adjustment of evacuation orders using an emotional engine.

[0546] The emotion engine installed on the server analyzes voice data sent by the user and facial expression data captured by the mobile device's camera. Based on this data, the emotion engine determines the user's mental state and whether or not the user is in a state of panic. If the user is in a state of panic, the emotion engine generates gentle instructions to calm them down.

[0547] Evacuation order notification and display

[0548] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. For example, the instructions might include, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." These instructions are dynamically adjusted according to the user's emotional state. The device displays the received evacuation instructions, allowing the user to visually confirm them.

[0549] Specific example

[0550] Let's consider a specific example of what happens during an earthquake. An earthquake occurs in a company building, and the server immediately receives data from earthquake detection sensors. The server sends an alert to all employees' mobile devices saying, "Earthquake!" User A, upon receiving this alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and identifies their position. Simultaneously, it collects data from pedestrian flow sensors within the building to check the congestion level. Based on the obtained data, the server calculates the optimal evacuation route, and the emotion engine analyzes User A's facial expression data. If it is determined that User A is in a state of panic, the server sends a pre-configured instruction to the mobile device saying, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor." User A checks the displayed evacuation route and calmly begins to evacuate. In this way, appropriate evacuation is achieved even during an earthquake, according to the user's emotional state.

[0551] The following describes the processing flow.

[0552] Step 1:

[0553] The server monitors earthquake detection sensors. When an earthquake is detected by an earthquake detection sensor, data on its speed and intensity is sent to the server.

[0554] Step 2:

[0555] The server analyzes earthquake data and determines the seismic intensity. If the seismic intensity exceeds a certain threshold, it is determined that an earthquake has occurred.

[0556] Step 3:

[0557] The server sends an earthquake alert to all registered mobile devices. The alert message includes content such as "Earthquake! Evacuate immediately!"

[0558] Step 4:

[0559] The user receives an earthquake alert and launches a dedicated app on their mobile device. The user then types "Please tell me the evacuation route" to inquire about evacuation routes.

[0560] Step 5:

[0561] The terminal sends an evacuation route inquiry from the user to the server. This request also includes information about the user's current location.

[0562] Step 6:

[0563] The server uses location information to determine the user's current location. This location information is obtained from sources such as GPS data from a mobile device.

[0564] Step 7:

[0565] The server collects data from pedestrian flow sensors within the building. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server.

[0566] Step 8:

[0567] The server calculates evacuation routes based on the user's current location and density data obtained from pedestrian flow sensors. The calculation method prioritizes less congested routes to determine the optimal evacuation path.

[0568] Step 9:

[0569] The server requests data from the device to acquire the user's voice and facial expressions. The device uses its camera and microphone to collect the user's voice and facial expression data and sends it to the server.

[0570] Step 10:

[0571] The emotion engine installed on the server analyzes the transmitted voice and facial expression data to determine the user's emotional state. It analyzes whether the user is in a state of panic.

[0572] Step 11:

[0573] Based on the analysis results of the emotion engine, the server adjusts the content and format of evacuation instructions according to the user's emotional state. For example, if the user is in a panic state, it will generate gentler instructions such as, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor."

[0574] Step 12:

[0575] The server sends coordinated evacuation instructions to the user's mobile device. These instructions include specific routes and evacuation procedures.

[0576] Step 13:

[0577] The device displays the evacuation instructions it has received. Depending on the display method, the evacuation route is shown to the user in a way that is easily visible, such as on a map or in text.

[0578] Step 14:

[0579] The user checks the displayed evacuation route and begins evacuating according to the instructions. Based on the information provided by the server and instructions tailored to their emotional state, the user can safely evacuate via the optimal route.

[0580] (Example 2)

[0581] Next, we will describe Example 2. 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".

[0582] While systems exist to provide evacuation routes for rapid and safe evacuation during earthquakes, they face challenges in providing dynamic evacuation instructions that take into account factors such as the density of people in a building and the emotional state of individual users. Furthermore, if users panic, there is a high probability that appropriate evacuation instructions will not be provided, potentially delaying evacuation. As a result, problems arise where evacuations are not carried out efficiently or safely.

[0583] The identification processing performed 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 detecting earthquakes, means for acquiring the current location of personnel, means for measuring the density of personnel inside the building, means for calculating the optimal evacuation route, means for analyzing the emotional state of the user, means for generating and transmitting evacuation instructions including an evacuation route to an emergency exit, means for receiving evacuation instructions via the user's information terminal, and means for displaying the user's location and evacuation route based on location information and evacuation instructions. This enables rapid and safe evacuation even when an earthquake occurs, taking into account the emotional state of the user and the density of personnel inside the building.

[0584] "Means for detecting earthquakes" refers to sensor devices that detect the occurrence of earthquakes in real time and immediately transmit data such as seismic intensity and time of occurrence to a server.

[0585] "Means for obtaining the current location of personnel" refers to technologies that accurately obtain the user's current location information using GPS, Wi-Fi, beacons, etc.

[0586] "Means for measuring the density of people inside a building" refers to a sensor device that monitors the movement and density of people inside a building in real time and transmits that data to a server.

[0587] "Methods for calculating the optimal evacuation route" refers to a technology that uses algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs to calculate a safe and rapid evacuation route based on location information and population density data collected during an earthquake.

[0588] "Methods for analyzing a user's emotional state" refers to technologies that use machine learning algorithms to analyze voice data and facial expression data transmitted by the user to determine the user's mental state.

[0589] "Means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits" refers to a device that dynamically generates evacuation instructions based on the user's current location and the optimal evacuation route, and transmits them to the user's information terminal via communication technology.

[0590] "Means of receiving evacuation instructions via the user's information terminal" refers to technology that allows evacuation instructions transmitted from a server to be received by the user's information terminal, such as a smartphone or tablet.

[0591] "Means for displaying a user's location and evacuation route based on location information and evacuation orders" refers to a technology that visually displays received location information and evacuation orders on the user's information terminal, enabling the user to confirm their evacuation route.

[0592] Modes for carrying out the invention

[0593] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, display means, and emotion engine. Details of how this system specifically operates are described below.

[0594] Earthquake sensing means

[0595] The server constantly monitors earthquake detection sensors. These sensors include, for example, accelerometers and seismometers. When these sensors detect an earthquake and the seismic intensity exceeds a certain threshold, that information is immediately sent to the server.

[0596] Location information and evacuation alert transmission

[0597] Upon confirming the occurrence of an earthquake, the server sends an earthquake alert to all registered mobile devices. This alert includes the message, "Earthquake! Evacuate immediately!" Users receive this alert and launch the dedicated app on their mobile devices.

[0598] Inquiry about evacuation routes

[0599] When a user launches the dedicated app and enters "Please tell me the evacuation route," this request is sent to the server. The server obtains the user's current location information and determines its location. Location information is obtained using GPS, Wi-Fi, beacons, etc.

[0600] Collection of pedestrian flow data and calculation of evacuation routes

[0601] The server collects data from pedestrian flow sensors installed inside the building. These sensors include infrared sensors and laser sensors. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server. Based on the location information and pedestrian flow data, the server calculates the optimal evacuation route using computational methods. Algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs are used.

[0602] Emotional analysis and adjustment of evacuation orders using an emotional engine.

[0603] The emotion engine installed on the server analyzes voice data transmitted by the user and facial expression data captured by the mobile device's camera. The emotion engine uses machine learning algorithms to determine the user's mental state and whether or not the user is in a state of panic. For example, it analyzes changes in voice tone and facial expression.

[0604] Evacuation order notification and display

[0605] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. For example, the instructions might include, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." These instructions are dynamically adjusted according to the user's emotional state. The mobile device displays the received evacuation instructions, allowing the user to visually confirm them.

[0606] Specific example

[0607] The following are specific examples of what happens when an earthquake occurs.

[0608] An earthquake occurs inside a building, and the server immediately receives data from earthquake detection sensors. Next, the server sends an alert to all employees' mobile devices saying "Earthquake!". User A, upon receiving this alert, launches a dedicated app on their mobile device and enters "Please tell me the evacuation route." The server obtains User A's location information and locates their position. Simultaneously, it collects data from pedestrian flow sensors within the building to check the congestion level. Based on the data obtained, the server calculates the optimal evacuation route, and an emotion engine analyzes User A's facial expression data. If it is determined that User A is in a state of panic, the server sends pre-configured instructions to the mobile device saying, "Stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor." User A checks the displayed evacuation route and calmly begins to evacuate.

[0609] Example of a prompt

[0610] "An earthquake has occurred, please tell me the evacuation routes."

[0611] "Please tell me the best evacuation route from my current location."

[0612] "Calculate the optimal evacuation route and provide evacuation instructions that take emotions into consideration."

[0613] By using these prompts, specific and natural evacuation instructions can be obtained.

[0614] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0615] System program processing flow

[0616] Step 1: Earthquake detection

[0617] The server monitors data from earthquake sensors in real time. When a sensor detects an earthquake and the seismic intensity exceeds a certain threshold, that information is immediately sent to the server.

[0618] Input: Data from earthquake detection sensors

[0619] Data processing: Compare with seismic intensity thresholds and generate an alert if the threshold is exceeded.

[0620] Output: Earthquake alert information

[0621] Step 2: Sending an earthquake alert

[0622] When the server receives an alert from an earthquake detection sensor, it immediately sends an earthquake alert to all registered mobile devices. The message includes "Earthquake! Evacuate immediately!"

[0623] Input: Earthquake alert information

[0624] Data processing: Message generation

[0625] Output: Alert notification sent to the user's mobile device.

[0626] Step 3: Accepting requests for evacuation routes

[0627] Users who receive an earthquake alert launch a dedicated app and type "Please tell me the evacuation route." This request is sent to the server.

[0628] Input: User evacuation route request

[0629] Data processing: Analysis of request content

[0630] Output: Request data to the server

[0631] Step 4: Obtaining location information

[0632] The server obtains location data from the user's mobile device. This location information is collected using technologies such as GPS, Wi-Fi, and beacons.

[0633] Input: User location request

[0634] Data processing: Analysis and identification of location information

[0635] Output: User's current location information

[0636] Step 5: Collecting pedestrian flow data

[0637] The server collects data from pedestrian flow sensors installed inside the building. The sensors monitor the movement and density of people inside the building in real time and transmit that information to the server.

[0638] Input: Data from human flow sensors

[0639] Data processing: Measurement of human movement and density

[0640] Output: Foot traffic data within the building

[0641] Step 6: Calculating the optimal evacuation route

[0642] The server uses location information and human flow data to calculate the optimal evacuation route using computational methods. Algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs are used.

[0643] Input: User's current location information, pedestrian flow data

[0644] Data processing: Calculation of evacuation routes

[0645] Output: Optimal evacuation route

[0646] Step 7: Emotion Analysis

[0647] The emotion engine installed on the server analyzes voice data sent by the user and facial expression data captured by the mobile device's camera. It uses machine learning algorithms to determine the user's mental state and whether or not they are in a state of panic.

[0648] Input: User voice data, facial expression data

[0649] Data processing: Analysis of emotional states

[0650] Output: User's emotional state information

[0651] Step 8: Generate and send evacuation orders

[0652] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. These instructions may include phrases such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[0653] Input: Optimal evacuation route, user emotional state information

[0654] Data processing: Generation of evacuation orders

[0655] Output: Evacuation order notification to mobile devices

[0656] Step 9: Displaying evacuation instructions

[0657] The terminal visually displays the received evacuation instructions. The user looks at the screen of their mobile device and begins evacuating according to the instructed route.

[0658] Input: Evacuation order notification to mobile device

[0659] Data processing: Generating data for display

[0660] Output: Display of evacuation order

[0661] (Application Example 2)

[0662] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0663] While rapid and safe evacuation is crucial during an earthquake, the potential for panic among evacuees makes issuing appropriate evacuation instructions difficult. In such situations, evacuation instructions need to consider the psychological state of evacuees, along with optimizing crowd density and evacuation routes. Furthermore, there is a need for means of providing visually and audibly useful evacuation information.

[0664] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0665] In this invention, the server includes earthquake sensing means, location information means, emotion analysis means, evacuation instruction adjustment means, transmission means, reception means, and display means. This enables the rapid and safe provision of evacuation routes in the event of an earthquake, as well as the recognition of the user's emotional state and the dynamic provision of optimal evacuation instructions. Furthermore, by visually displaying evacuation routes using a head-mounted display and providing personalized prompt messages using a generation AI model, more effective evacuation instructions can be given to the user.

[0666] An "earthquake detection device" is a device or system that detects the occurrence of an earthquake in real time and immediately transmits that information to a server.

[0667] "Location information means" refers to devices and functions such as GPS and indoor location information systems used to obtain the user's current location.

[0668] "Calculation means" refers to algorithms and programs that calculate the optimal evacuation route based on acquired location information and pedestrian flow sensor data.

[0669] "Transmission means" refers to a device or system that transmits calculated evacuation routes and evacuation instructions to the user's mobile terminal.

[0670] "Receiving means" refers to functions or devices that allow a user's mobile device to receive evacuation instructions sent from the transmitting means.

[0671] "Display means" refers to functions or devices for visually displaying received evacuation instructions and route information on the user's mobile device or head-mounted display.

[0672] "Emotional analysis tools" are algorithms and programs that analyze a user's voice data and facial expression data to identify the user's emotional state.

[0673] "Adjustment means" refers to a function or system that dynamically changes the content of evacuation orders according to the user's emotional state obtained from emotion analysis means.

[0674] A "people flow sensor" is a device or system that monitors the density and flow of people within a large building in real time and transmits that data to a server.

[0675] A "head-mounted display" is a display device that a user wears to display information within their field of vision.

[0676] A "generative AI model" is a machine learning model designed to perform a specific task and is used to generate personalized evacuation instructions and prompts for users.

[0677] A "prompt" is a formalized instruction or query text input to a generative AI model, intended to produce appropriate output according to the purpose.

[0678] The system for implementing the present invention comprises earthquake sensing means, location information means, emotion analysis means, evacuation instruction adjustment means, transmission means, reception means, and display means. This system makes it possible to dynamically provide the optimal evacuation route while considering the user's emotional state when an earthquake occurs.

[0679] 1. Earthquake sensing means

[0680] The server monitors earthquake detection sensors (e.g., Shindol, GeoSIG) and detects earthquakes in real time. If the earthquake intensity exceeds a certain threshold, the information is immediately sent to the server, which generates an earthquake alert and sends it to the user's mobile device.

[0681] 2. Location information means

[0682] The server uses the user's mobile device (e.g., iPhone, Android) GPS and indoor location systems (e.g., Bluetooth Beacon, Wi-Fi RTT) to obtain the user's current location. This location information is used in combination with data obtained from pedestrian flow sensors inside the building to calculate the optimal evacuation route.

[0683] 3. Emotion analysis means

[0684] The server analyzes the user's voice data and facial expression data captured by the mobile device's camera using an emotion analysis engine (e.g., Microsoft Azure Cognitive Services, Google Cloud Emotion API, Amazon Rekognition). This allows the server to determine the user's psychological state, particularly whether they are in a state of panic.

[0685] 4. Evacuation order coordination means

[0686] If the server determines that a user is in a state of panic, the evacuation instruction coordination mechanism generates gradual evacuation instructions to encourage calm action. This allows the user to take appropriate evacuation actions.

[0687] 5. Transmission method

[0688] The server sends evacuation instructions to the user's mobile device, based on the optimal evacuation route calculated by the computational means and the results obtained from the sentiment analysis means.

[0689] 6. Receiving means

[0690] The user's mobile device receives evacuation instructions transmitted from the server. This receiving mechanism functions through a specific, dedicated application.

[0691] 7. Display means

[0692] The user's mobile device or head-mounted display (e.g., HoloLens, Meta Quest) visually displays received evacuation instructions and route information. Furthermore, it provides voice guidance based on sentiment analysis results.

[0693] Specific example

[0694] When user A, who is inside a building experiencing an earthquake, launches the application, the server immediately receives information from earthquake detection sensors. The server obtains user A's current location and collects data from pedestrian flow sensors inside the building to calculate the optimal evacuation route. Furthermore, it analyzes user A's voice and facial expression data using an emotion analysis engine, and if it determines that user A is in a state of panic, it generates calming instructions. Gentle instructions such as, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor," are provided.

[0695] Example of a prompt

[0696] "When an earthquake is detected by the earthquake detection sensor, quickly obtain the user's current location, calculate the optimal evacuation route considering the congestion level within the building, and provide evacuation instructions based on the user's psychological state."

[0697] This configuration makes it possible to support swift and appropriate evacuation actions while taking into account the user's emotional state during an earthquake.

[0698] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0699] Step 1:

[0700] The server monitors data from earthquake sensors in real time and detects the occurrence of an earthquake. When the earthquake intensity exceeds a certain threshold, it immediately sends that information to the server (input: earthquake sensor data, output: earthquake occurrence alert). Subsequently, the server sends earthquake occurrence alerts to all registered users (specific actions: reading sensor data, threshold determination, generating and sending alert messages).

[0701] Step 2:

[0702] When the user's device receives an alert, it launches a dedicated app. The app immediately uses location information to send the current location to the server (input: alert message, GPS data; output: current location information). This current location information is used to calculate evacuation routes (specific actions: app launch, location information reading, location information transmission).

[0703] Step 3:

[0704] The server combines the received current location information with real-time data obtained from pedestrian flow sensors inside the building to calculate the optimal evacuation route (input: current location information, pedestrian flow data; output: optimal evacuation route). This calculation is performed using pathfinding algorithms such as Dijkstra's algorithm (specific operation: data collection, path calculation, path information generation).

[0705] Step 4:

[0706] The server receives the user's voice and camera data and uses an emotion analysis engine to analyze the user's emotional state (input: voice data, image data; output: emotion analysis results). This analysis determines whether the user is in a state of panic (specific actions: data collection, application of emotion analysis engine, generation of analysis results).

[0707] Step 5:

[0708] If the emotion analysis results indicate a "panic state," the server uses an evacuation instruction adjustment mechanism to generate a gentle evacuation instruction that will allow the user to act calmly (Input: Emotion analysis result, optimal evacuation route; Output: Adjusted evacuation instruction). This involves generating personalized prompt sentences using a generation AI model (Specific actions: Analysis result determination, instruction adjustment, prompt sentence generation).

[0709] Step 6:

[0710] The server sends a pre-configured evacuation order to the user's terminal (input: pre-configured evacuation order, output: evacuation order to terminal). The user's terminal receives this order, displays it visually on its display device, and also plays an audio guide (specific actions: sending evacuation order, receiving order, visual display, audio playback).

[0711] Step 7:

[0712] The user follows the designated evacuation route and takes appropriate evacuation actions based on sentiment analysis (input: visual display and audio guidance, output: appropriate evacuation actions). This enables the user to evacuate safely while suppressing panic (specific actions: start of evacuation, confirmation of instructions, execution of evacuation actions).

[0713] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0714] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0715] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0716] [Third Embodiment]

[0717] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0718] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0719] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0720] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0721] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0722] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0723] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0724] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0725] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0726] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0727] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0728] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0729] Modes for carrying out the invention

[0730] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, and display means. By coordinating these means, it is possible to provide evacuation routes quickly and safely even in the event of a large-scale disaster.

[0731] Earthquake sensing means

[0732] The server monitors data from earthquake sensors in real time and immediately detects the occurrence of an earthquake. This information is sent to the server, and the process moves on to the next step of notifying the server of the earthquake.

[0733] Sending evacuation alerts

[0734] Once the server detects an earthquake, it sends an evacuation alert to all registered mobile devices. This alert includes a message informing users of the earthquake and urging them to evacuate to a safe place immediately. For example, a message such as "Earthquake! Evacuate immediately!" is sent to each user's mobile device.

[0735] Inquiry about evacuation routes

[0736] After receiving an earthquake alert, users launch a dedicated app on their mobile device and inquire about evacuation routes. For example, if a user types "Please tell me the evacuation route," this request is sent to the server.

[0737] Get current location

[0738] The server receives a user request and obtains location information (such as GPS data) from the mobile device. Based on this information, it determines the user's current location and uses that location data in the next step.

[0739] Collection of pedestrian flow data and calculation of evacuation routes

[0740] The server collects real-time occupancy density data from pedestrian flow sensors installed inside the building. Based on location information and pedestrian flow data, it then uses computational methods to calculate the optimal evacuation route. For example, to avoid congestion, it calculates a route that includes the currently least crowded stairwells and exits.

[0741] Evacuation order notification

[0742] The server sends the calculated optimal evacuation route to the user's mobile device. Specifically, it includes detailed evacuation instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[0743] Evacuation route display

[0744] The user's mobile device displays the received evacuation instructions. The display method allows the user to visually confirm the evacuation route. For example, displaying the route on a map allows the user to easily understand the specific evacuation path.

[0745] Specific example

[0746] Let's consider a specific example of what happens during an earthquake. An earthquake occurs in a company building, and the server immediately receives data from earthquake detection sensors. The server sends an alert to all employees' mobile devices saying, "Earthquake! Evacuate immediately!" User A, upon receiving this alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and identifies their position. Simultaneously, it collects data from pedestrian flow sensors to check the congestion level. Based on the data obtained, the server calculates the optimal evacuation route and notifies User A's mobile device, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." User A can confirm the received instructions on their mobile device screen and evacuate quickly via the designated route. In this way, smooth evacuation is achieved even during an earthquake.

[0747] The following describes the processing flow.

[0748] Step 1:

[0749] The server monitors earthquake detection sensors. When an earthquake is detected by an earthquake detection sensor, data on its speed and intensity is sent to the server.

[0750] Step 2:

[0751] The server analyzes earthquake data and determines the seismic intensity. If the seismic intensity exceeds a certain threshold, it is determined that an earthquake has occurred.

[0752] Step 3:

[0753] The server sends an earthquake alert to all registered mobile devices. The alert message includes content such as "Earthquake! Evacuate immediately!"

[0754] Step 4:

[0755] The user receives an earthquake alert and launches a dedicated app on their mobile device. The user then types "Please tell me the evacuation route" to inquire about evacuation routes.

[0756] Step 5:

[0757] The terminal sends an evacuation route inquiry from the user to the server. This request also includes information about the user's current location.

[0758] Step 6:

[0759] The server uses location information to determine the user's current location. This location information is obtained from sources such as GPS data from a mobile device.

[0760] Step 7:

[0761] The server collects data from pedestrian flow sensors within the building. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server.

[0762] Step 8:

[0763] The server calculates evacuation routes based on the user's current location and density data obtained from pedestrian flow sensors. The calculation method prioritizes less congested routes to determine the optimal evacuation path.

[0764] Step 9:

[0765] The server calculates the optimal evacuation route and sends it to the user's mobile device. For example, it might send instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[0766] Step 10:

[0767] The device displays the evacuation route it received. Depending on the display method, the evacuation route is displayed to the user in a way that is easily visible, such as on a map or in text.

[0768] Step 11:

[0769] The user checks the displayed evacuation route and begins evacuating according to the instructions. By following the instructions on the device, the user can safely evacuate via the optimal route.

[0770] (Example 1)

[0771] Next, we will describe Example 1. 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."

[0772] In the event of a large-scale earthquake disaster, an effective information system is needed to ensure rapid and safe evacuation. In particular, when large numbers of people begin evacuating simultaneously, congestion and panic are likely to occur, potentially delaying evacuation. Under these circumstances, the challenge lies in providing real-time situational awareness and accurate guidance on evacuation routes.

[0773] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0774] In this invention, the server includes means for receiving data from earthquake detection sensors in real time, means for acquiring location information of the user's mobile device, means for collecting data from pedestrian flow sensors installed inside the building and calculating the optimal evacuation route, means for generating and transmitting evacuation alerts and evacuation routes, and means for receiving and displaying evacuation routes via the user's mobile device. This enables the provision of rapid and safe evacuation routes and avoidance of congestion even in the event of a large-scale earthquake disaster.

[0775] An "earthquake detection sensor" is a device that detects earthquake vibrations and transmits that information to a server in real time.

[0776] "Real-time" means that data is processed the moment it is generated, and results are obtained almost instantly.

[0777] "Mobile devices" refer to portable information and communication devices such as smartphones and tablets owned by users.

[0778] "Location information" refers to data used to determine one's current location, such as GPS.

[0779] A "people flow sensor" is a device that detects the density and movement of people inside a building and collects the data.

[0780] An "evacuation route" refers to a recommended route for safe evacuation during a disaster.

[0781] A "server" refers to a computer system used for processing, calculating, storing, and managing data.

[0782] An "evacuation alert" is an emergency message sent to prompt immediate evacuation during emergencies such as earthquakes.

[0783] "Calculation means" refers to algorithms and software used to calculate the optimal evacuation route.

[0784] "Receiving means" refers to the mechanism by which a user's mobile device receives data transmitted from a server.

[0785] "Display means" refers to display devices or screens used to visually present received evacuation instructions and evacuation routes to the user.

[0786] An "evacuation order" refers to a message that includes specific instructions for actions to take to ensure the user's safe evacuation.

[0787] Modes for carrying out the invention

[0788] The system of the present invention consists of an earthquake detection sensor, a location information acquisition means, a calculation means, a transmission means, a reception means, and a display means. By coordinating these means, it becomes possible to quickly and safely present evacuation routes even in the event of a large-scale earthquake disaster.

[0789] earthquake sensing

[0790] First, an earthquake detection sensor is connected to the server. When the earthquake detection sensor detects an earthquake, it sends the data to the server in real time. A general-purpose earthquake detection sensor is used for this purpose.

[0791] Sending evacuation alerts

[0792] When the server detects an earthquake, it immediately sends an evacuation alert to the mobile devices of all registered users. This alert includes an urgent message such as, "Earthquake! Evacuate immediately!" The server uses a push notification service (e.g., Firebase Cloud Messaging) to send this message.

[0793] Inquiry about evacuation routes

[0794] When a user receives an evacuation alert on their mobile device, they launch a dedicated application. Through this application, the user sends a request saying, "Please tell me the evacuation route." This request is sent to the server as an HTTP POST request.

[0795] Get current location

[0796] When the server receives a user request, it obtains location information from the mobile device's GPS. The location information obtained by the GPS module is used to determine the user's current location.

[0797] Collection of pedestrian flow data and calculation of evacuation routes

[0798] The server collects data in real time from pedestrian flow sensors installed inside the building to determine the density of people within the building. Based on this pedestrian flow data and location information, the server calculates evacuation routes. Algorithms such as Dijkstra's algorithm are used for this calculation.

[0799] Evacuation order notification

[0800] The server notifies the user's mobile device of the calculated optimal evacuation route. Specifically, it sends detailed evacuation instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." The server then sends this again using a push notification service.

[0801] Evacuation route display

[0802] The user displays the evacuation order notified on their mobile device. A dedicated application uses the Google Maps API and other tools to display the evacuation route on a map from the user's current location. This allows the user to visually confirm the evacuation route and evacuate safely.

[0803] Specific example

[0804] The following is a specific example of how the system works during an earthquake. When an earthquake occurs in a company building, the server immediately receives data from earthquake detection sensors and sends an alert to all employees' mobile devices saying, "Earthquake! Evacuate immediately!" User A, upon receiving the alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and calculates the optimal evacuation route based on data from pedestrian flow sensors. Based on the calculation results, User A's mobile device is notified with the instruction, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." User A can then confirm the evacuation route on their mobile device screen and evacuate quickly via the designated route.

[0805] Example of a prompt

[0806] Please describe in detail the "system for issuing rapid evacuation instructions during an earthquake." Use the subjects of server, terminal, and user, and clearly describe the specific actions, including each sensor, location information, and the process of sending evacuation alerts. For example, "The server, upon confirming the occurrence of an earthquake, sends an evacuation alert to all registered mobile terminals." Please show the specific flow of the process.

[0807] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0808] Program processing flow

[0809] Step 1: Receiving earthquake detection data

[0810] The server receives data from earthquake sensors in real time. It receives vibration data sent from the earthquake sensors as input and analyzes it. If vibrations exceeding a threshold are detected, an earthquake occurrence flag is set. The server also sets the earthquake occurrence flag as output.

[0811] Specific operation: The server polls data from the sensor every 0.1 seconds, and if vibrations exceeding a threshold are detected, it sets an earthquake occurrence flag.

[0812] Step 2: Sending an evacuation alert

[0813] When the server detects an earthquake flag, it sends an evacuation alert to all registered mobile devices. It uses the earthquake flag and user list as input to send push notifications to each user. The output is an evacuation alert sent to each mobile device.

[0814] Specific operation: The server uses a push notification service (e.g., Firebase Cloud Messaging) to send evacuation alert messages to each mobile device.

[0815] Step 3: Request an evacuation route

[0816] When a user receives an evacuation alert, they launch a dedicated app and enter a request for an evacuation route. The user enters "Please tell me the evacuation route" into the app as input, generating a request. The request is then sent to the server as output.

[0817] Specific operation: The user enters a message in the app's text input field and presses the send button. The app sends a request to the server as an HTTP POST request.

[0818] Step 4: Obtain current location

[0819] When the server receives a request from a user, it obtains location information from the mobile device's GPS. It receives the request and location information from the GPS module as input to determine the user's current location. The output is the user's latitude and longitude data.

[0820] Specific operation: The server receives an HTTP request from the terminal, calls a location information acquisition API to obtain latitude and longitude, and saves this information to the database.

[0821] Step 5: Collecting pedestrian flow data and calculating evacuation routes

[0822] The server collects data in real time from pedestrian flow sensors inside the building. It receives data from the pedestrian flow sensors and user location information as input, and uses an algorithm to calculate the optimal evacuation route. The calculated evacuation route is then output.

[0823] Specific operation: The server uses database queries to retrieve the latest human flow data and calculates the optimal evacuation route using algorithms such as Dijkstra's algorithm.

[0824] Step 6: Notification of evacuation order

[0825] The server sends the calculated optimal evacuation route to the user's mobile device. Using the calculated evacuation route and user information as input, it generates and sends a detailed evacuation instruction message. The user's mobile device receives the evacuation instruction as output.

[0826] Specific action: The server will again use the push notification service to send evacuation instructions, including detailed evacuation routes, to the user's mobile device.

[0827] Step 7: Displaying evacuation routes

[0828] The user's mobile device displays received evacuation orders via a dedicated app. The input is the received and displayed evacuation order message. The output is a screen showing the evacuation route, which the user can visually confirm.

[0829] Specific operation: The app uses the Google Maps API to display evacuation routes on a map from the user's current location, allowing for visual confirmation.

[0830] (Application Example 1)

[0831] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0832] In recent years, rapid and safe evacuation during earthquakes in factories has become increasingly important. However, conventional earthquake response systems limit evacuation route guidance to humans, making it difficult to control the appropriate actions of robots within the factory. This can lead to robots becoming obstacles or hindering human evacuation. There is a need to solve this problem and provide a system that allows all personnel and robots in a factory to evacuate safely.

[0833] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0834] In this invention, the server includes earthquake sensing means, location information means for acquiring the current location of personnel, calculation means for calculating the optimal evacuation route to at least one emergency exit, transmission means for generating and transmitting evacuation instructions including the evacuation route to the emergency exit, receiving means for receiving evacuation instructions via the user's mobile terminal, display means for displaying the user's location and evacuation route based on the location information means and evacuation instructions, and means for notifying a robot of the evacuation instructions and having the robot execute the evacuation instructions. This enables personnel and robots in the factory to evacuate quickly and safely.

[0835] An "earthquake detection device" is a device that can detect the occurrence of an earthquake and transmit the vibration information to a server in real time.

[0836] "Location information means" refers to technologies for obtaining the current location of a user or object, and generally involves using GPS or other location detection systems.

[0837] A "calculation means" is a device or system that performs processing to calculate the optimal evacuation route based on multiple data points.

[0838] A "transmission means" is a device that has the function of transmitting calculated evacuation routes and other important information to users or robots.

[0839] A "receiving device" is a device that allows a user's mobile terminal or robot to receive evacuation instructions from a transmitting device.

[0840] "Display means" refers to a device or system for visually displaying evacuation routes received from a transmission means, and usually includes a display device or monitor.

[0841] A "people flow sensor" is a sensor that monitors the density of people inside a building in real time and transmits that data to a server.

[0842] "Seismic intensity" is a measure that indicates the strength of earthquake shaking, and it is the criterion for issuing evacuation orders when the seismic intensity exceeds a specified level.

[0843] A "robot" is an automated mechanical device designed to perform specific tasks in a factory or other work environment.

[0844] "Means for executing evacuation orders" refers to a control system within a robot that recognizes evacuation orders from a receiving means and acts in accordance with those orders.

[0845] This invention is a system that supports rapid and safe evacuation in the event of an earthquake in a factory. The system includes the following means:

[0846] Earthquake sensing means

[0847] The server monitors data from earthquake sensors in real time and immediately detects the occurrence of an earthquake. This detection information is sent to the server, and the process proceeds to the next step.

[0848] Location information means

[0849] To obtain the current location of users and robots, location information systems such as GPS are used. The server acquires location information transmitted from users and robots in real time and uses this information to calculate the optimal evacuation route.

[0850] means of calculation

[0851] The server calculates evacuation routes based on earthquake detection data, location data, and data from pedestrian flow sensors. It uses powerful CPUs and AI algorithms to quickly determine the optimal evacuation route. This calculation process employs algorithms to avoid congestion and methods to find the shortest distance.

[0852] Transmission method

[0853] The server uses a communication module to send the calculated optimal evacuation route to users and robots. Evacuation instructions are sent to users' mobile devices and robots within the factory, providing evacuation routes and action instructions.

[0854] Receiving means

[0855] The user's mobile device or robot receives evacuation instructions transmitted from the server. On the mobile device, launching a dedicated app displays evacuation routes and instructions. Meanwhile, the robot begins its actions based on the received evacuation instructions and safely evacuates along the designated route.

[0856] Display means

[0857] Evacuation instructions sent from the server are displayed on mobile devices and robot displays. On mobile devices, the route is displayed on a map, allowing users to visually confirm the specific evacuation path. On robots, the instructions are displayed through internal displays and interfaces.

[0858] Execution of evacuation orders

[0859] The robot begins its actions based on the evacuation instructions it receives. Following instructions from the server, the robot proceeds along the designated evacuation route. During this process, additional processing is performed using sensors and cameras to avoid obstacles.

[0860] Specific example

[0861] When an earthquake occurs, robot R1, which is working inside the factory, immediately receives earthquake detection information and transmits it to the server. The server confirms robot R1's current location and calculates the optimal evacuation route based on data from the pedestrian flow sensor. The server then sends an evacuation instruction to robot R1: "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." Based on the received instruction, robot R1 proceeds along the evacuation route and begins to safely evacuate to the emergency exit.

[0862] Example of a prompt

[0863] "Retrieve data from the earthquake detection API and analyze that data."

[0864] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0865] Step 1:

[0866] The server monitors data from earthquake detection sensors in real time and detects the occurrence of an earthquake. The server analyzes acceleration data and shaking intensity data transmitted from the sensors and recognizes an earthquake has occurred if they exceed a certain threshold. The input is real-time data from the sensors, and the output is confirmed information that an earthquake has occurred.

[0867] Step 2:

[0868] After confirming the occurrence of an earthquake, the server sends an evacuation alert to all registered mobile devices and robots. This uses a communication module to send the message, "Earthquake! Evacuate immediately!" The input is the confirmed information that an earthquake has occurred, and the output is a notification that the alert message has been successfully sent.

[0869] Step 3:

[0870] After receiving an earthquake alert, users and robots launch a dedicated app on their mobile devices and inquire about evacuation routes. Users might type, "Please tell me the evacuation route." Robots automatically send an evacuation request to the server. Input is the user's request or an automated request from the robot, and output is confirmation of the request's receipt.

[0871] Step 4:

[0872] When the server receives an evacuation route request from a user or robot, it obtains its current location using location information. For users, it obtains GPS data from their mobile device; for robots, it obtains data from their built-in location detection system. The input is data indicating the current location, and the output is the identified location information of the user or robot.

[0873] Step 5:

[0874] The server collects real-time occupancy density data from pedestrian flow sensors installed inside the building and calculates the optimal evacuation route based on location information and pedestrian flow data. It uses algorithms to avoid congestion and shortest distance search algorithms to generate calculation results. The input is the identified location information of users and robots, as well as data from pedestrian flow sensors, and the output is the optimal evacuation route.

[0875] Step 6:

[0876] The server transmits the calculated optimal evacuation route to the user's mobile device and robot, providing specific evacuation instructions. The route is displayed on a map on the user's device, and detailed instructions are conveyed to the robot. The input is information on the optimal evacuation route, and the output is the transmission of sequential evacuation instructions.

[0877] Step 7:

[0878] The user's mobile device and the robot display the received evacuation instructions and begin taking action accordingly. The user evacuates by viewing the map displayed on the device, and the robot moves to a safe location along the evacuation route. The input is the evacuation instruction information, and the output is the execution of the evacuation action.

[0879] Example of a prompt

[0880] "Retrieve data from the earthquake detection API and analyze that data."

[0881] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0882] Modes for carrying out the invention

[0883] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, display means, and emotion engine. This makes it possible to provide a rapid and safe evacuation route in the event of an earthquake, recognize the user's emotional state, and dynamically provide optimal evacuation instructions.

[0884] Earthquake sensing means

[0885] The server monitors earthquake sensors and detects earthquakes in real time. If the earthquake intensity exceeds a certain threshold, that information is immediately sent to the server, and an earthquake alert is issued.

[0886] Location information and evacuation alert transmission

[0887] Upon confirming the occurrence of an earthquake, the server sends an earthquake alert to all registered mobile devices. This alert includes the message, "Earthquake! Evacuate immediately!" Users receive this alert and launch the dedicated app on their mobile devices.

[0888] Inquiry about evacuation routes

[0889] When a user launches the dedicated app and enters "Please tell me the evacuation route," this request is sent to the server. The server retrieves the user's current location information and determines their location.

[0890] Collection of pedestrian flow data and calculation of evacuation routes

[0891] The server collects data from pedestrian flow sensors installed inside the building. These sensors monitor the movement and density of people inside the building in real time and transmit this data to the server. Based on the location information and pedestrian flow data, the server uses computational tools to calculate the optimal evacuation route.

[0892] Emotional analysis and adjustment of evacuation orders using an emotional engine.

[0893] The emotion engine installed on the server analyzes voice data sent by the user and facial expression data captured by the mobile device's camera. Based on this data, the emotion engine determines the user's mental state and whether or not the user is in a state of panic. If the user is in a state of panic, the emotion engine generates gentle instructions to calm them down.

[0894] Evacuation order notification and display

[0895] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. For example, the instructions might include, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." These instructions are dynamically adjusted according to the user's emotional state. The device displays the received evacuation instructions, allowing the user to visually confirm them.

[0896] Specific example

[0897] Let's consider a specific example of what happens during an earthquake. An earthquake occurs in a company building, and the server immediately receives data from earthquake detection sensors. The server sends an alert to all employees' mobile devices saying, "Earthquake!" User A, upon receiving this alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and identifies their position. Simultaneously, it collects data from pedestrian flow sensors within the building to check the congestion level. Based on the obtained data, the server calculates the optimal evacuation route, and the emotion engine analyzes User A's facial expression data. If it is determined that User A is in a state of panic, the server sends a pre-configured instruction to the mobile device saying, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor." User A checks the displayed evacuation route and calmly begins to evacuate. In this way, appropriate evacuation is achieved even during an earthquake, according to the user's emotional state.

[0898] The following describes the processing flow.

[0899] Step 1:

[0900] The server monitors earthquake detection sensors. When an earthquake is detected by an earthquake detection sensor, data on its speed and intensity is sent to the server.

[0901] Step 2:

[0902] The server analyzes earthquake data and determines the seismic intensity. If the seismic intensity exceeds a certain threshold, it is determined that an earthquake has occurred.

[0903] Step 3:

[0904] The server sends an earthquake alert to all registered mobile devices. The alert message includes content such as "Earthquake! Evacuate immediately!"

[0905] Step 4:

[0906] The user receives an earthquake alert and launches a dedicated app on their mobile device. The user then types "Please tell me the evacuation route" to inquire about evacuation routes.

[0907] Step 5:

[0908] The terminal sends an evacuation route inquiry from the user to the server. This request also includes information about the user's current location.

[0909] Step 6:

[0910] The server uses location information to determine the user's current location. This location information is obtained from sources such as GPS data from a mobile device.

[0911] Step 7:

[0912] The server collects data from pedestrian flow sensors within the building. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server.

[0913] Step 8:

[0914] The server calculates evacuation routes based on the user's current location and density data obtained from pedestrian flow sensors. The calculation method prioritizes less congested routes to determine the optimal evacuation path.

[0915] Step 9:

[0916] The server requests data from the device to acquire the user's voice and facial expressions. The device uses its camera and microphone to collect the user's voice and facial expression data and sends it to the server.

[0917] Step 10:

[0918] The emotion engine installed on the server analyzes the transmitted voice and facial expression data to determine the user's emotional state. It analyzes whether the user is in a state of panic.

[0919] Step 11:

[0920] Based on the analysis results of the emotion engine, the server adjusts the content and format of evacuation instructions according to the user's emotional state. For example, if the user is in a panic state, it will generate gentler instructions such as, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor."

[0921] Step 12:

[0922] The server sends coordinated evacuation instructions to the user's mobile device. These instructions include specific routes and evacuation procedures.

[0923] Step 13:

[0924] The device displays the evacuation instructions it has received. Depending on the display method, the evacuation route is shown to the user in a way that is easily visible, such as on a map or in text.

[0925] Step 14:

[0926] The user checks the displayed evacuation route and begins evacuating according to the instructions. Based on the information provided by the server and instructions tailored to their emotional state, the user can safely evacuate via the optimal route.

[0927] (Example 2)

[0928] Next, we will describe Example 2. 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."

[0929] While systems exist to provide evacuation routes for rapid and safe evacuation during earthquakes, they face challenges in providing dynamic evacuation instructions that take into account factors such as the density of people in a building and the emotional state of individual users. Furthermore, if users panic, there is a high probability that appropriate evacuation instructions will not be provided, potentially delaying evacuation. As a result, problems arise where evacuations are not carried out efficiently or safely.

[0930] The identification processing performed 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 detecting earthquakes, means for acquiring the current location of personnel, means for measuring the density of personnel inside the building, means for calculating the optimal evacuation route, means for analyzing the emotional state of the user, means for generating and transmitting evacuation instructions including an evacuation route to an emergency exit, means for receiving evacuation instructions via the user's information terminal, and means for displaying the user's location and evacuation route based on location information and evacuation instructions. This enables rapid and safe evacuation even when an earthquake occurs, taking into account the emotional state of the user and the density of personnel inside the building.

[0931] "Means for detecting earthquakes" refers to sensor devices that detect the occurrence of earthquakes in real time and immediately transmit data such as seismic intensity and time of occurrence to a server.

[0932] "Means for obtaining the current location of personnel" refers to technologies that accurately obtain the user's current location information using GPS, Wi-Fi, beacons, etc.

[0933] "Means for measuring the density of people inside a building" refers to a sensor device that monitors the movement and density of people inside a building in real time and transmits that data to a server.

[0934] "Methods for calculating the optimal evacuation route" refers to a technology that uses algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs to calculate a safe and rapid evacuation route based on location information and population density data collected during an earthquake.

[0935] "Methods for analyzing a user's emotional state" refers to technologies that use machine learning algorithms to analyze voice data and facial expression data transmitted by the user to determine the user's mental state.

[0936] "Means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits" refers to a device that dynamically generates evacuation instructions based on the user's current location and the optimal evacuation route, and transmits them to the user's information terminal via communication technology.

[0937] "Means of receiving evacuation instructions via the user's information terminal" refers to technology that allows evacuation instructions transmitted from a server to be received by the user's information terminal, such as a smartphone or tablet.

[0938] "Means for displaying a user's location and evacuation route based on location information and evacuation orders" refers to a technology that visually displays received location information and evacuation orders on the user's information terminal, enabling the user to confirm their evacuation route.

[0939] Modes for carrying out the invention

[0940] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, display means, and emotion engine. Details of how this system specifically operates are described below.

[0941] Earthquake sensing means

[0942] The server constantly monitors earthquake detection sensors. These sensors include, for example, accelerometers and seismometers. When these sensors detect an earthquake and the seismic intensity exceeds a certain threshold, that information is immediately sent to the server.

[0943] Location information and evacuation alert transmission

[0944] Upon confirming the occurrence of an earthquake, the server sends an earthquake alert to all registered mobile devices. This alert includes the message, "Earthquake! Evacuate immediately!" Users receive this alert and launch the dedicated app on their mobile devices.

[0945] Inquiry about evacuation routes

[0946] When a user launches the dedicated app and enters "Please tell me the evacuation route," this request is sent to the server. The server obtains the user's current location information and determines its location. Location information is obtained using GPS, Wi-Fi, beacons, etc.

[0947] Collection of pedestrian flow data and calculation of evacuation routes

[0948] The server collects data from pedestrian flow sensors installed inside the building. These sensors include infrared sensors and laser sensors. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server. Based on the location information and pedestrian flow data, the server calculates the optimal evacuation route using computational methods. Algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs are used.

[0949] Emotional analysis and adjustment of evacuation orders using an emotional engine.

[0950] The emotion engine installed on the server analyzes voice data transmitted by the user and facial expression data captured by the mobile device's camera. The emotion engine uses machine learning algorithms to determine the user's mental state and whether or not the user is in a state of panic. For example, it analyzes changes in voice tone and facial expression.

[0951] Evacuation order notification and display

[0952] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. For example, the instructions might include, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." These instructions are dynamically adjusted according to the user's emotional state. The mobile device displays the received evacuation instructions, allowing the user to visually confirm them.

[0953] Specific example

[0954] The following are specific examples of what happens when an earthquake occurs.

[0955] An earthquake occurs inside a building, and the server immediately receives data from earthquake detection sensors. Next, the server sends an alert to all employees' mobile devices saying "Earthquake!". User A, upon receiving this alert, launches a dedicated app on their mobile device and enters "Please tell me the evacuation route." The server obtains User A's location information and locates their position. Simultaneously, it collects data from pedestrian flow sensors within the building to check the congestion level. Based on the data obtained, the server calculates the optimal evacuation route, and an emotion engine analyzes User A's facial expression data. If it is determined that User A is in a state of panic, the server sends pre-configured instructions to the mobile device saying, "Stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor." User A checks the displayed evacuation route and calmly begins to evacuate.

[0956] Example of a prompt

[0957] "An earthquake has occurred, please tell me the evacuation routes."

[0958] "Please tell me the best evacuation route from my current location."

[0959] "Calculate the optimal evacuation route and provide evacuation instructions that take emotions into consideration."

[0960] By using these prompts, specific and natural evacuation instructions can be obtained.

[0961] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0962] System program processing flow

[0963] Step 1: Earthquake detection

[0964] The server monitors data from earthquake sensors in real time. When a sensor detects an earthquake and the seismic intensity exceeds a certain threshold, that information is immediately sent to the server.

[0965] Input: Data from earthquake detection sensors

[0966] Data processing: Compare with seismic intensity thresholds and generate an alert if the threshold is exceeded.

[0967] Output: Earthquake alert information

[0968] Step 2: Sending an earthquake alert

[0969] When the server receives an alert from an earthquake detection sensor, it immediately sends an earthquake alert to all registered mobile devices. The message includes "Earthquake! Evacuate immediately!"

[0970] Input: Earthquake alert information

[0971] Data processing: Message generation

[0972] Output: Alert notification sent to the user's mobile device.

[0973] Step 3: Accepting requests for evacuation routes

[0974] Users who receive an earthquake alert launch a dedicated app and type "Please tell me the evacuation route." This request is sent to the server.

[0975] Input: User evacuation route request

[0976] Data processing: Analysis of request content

[0977] Output: Request data to the server

[0978] Step 4: Obtaining location information

[0979] The server obtains location data from the user's mobile device. This location information is collected using technologies such as GPS, Wi-Fi, and beacons.

[0980] Input: User location request

[0981] Data processing: Analysis and identification of location information

[0982] Output: User's current location information

[0983] Step 5: Collecting pedestrian flow data

[0984] The server collects data from pedestrian flow sensors installed inside the building. The sensors monitor the movement and density of people inside the building in real time and transmit that information to the server.

[0985] Input: Data from human flow sensors

[0986] Data processing: Measurement of human movement and density

[0987] Output: Foot traffic data within the building

[0988] Step 6: Calculating the optimal evacuation route

[0989] The server uses location information and human flow data to calculate the optimal evacuation route using computational methods. Algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs are used.

[0990] Input: User's current location information, pedestrian flow data

[0991] Data processing: Calculation of evacuation routes

[0992] Output: Optimal evacuation route

[0993] Step 7: Emotion Analysis

[0994] The emotion engine installed on the server analyzes voice data sent by the user and facial expression data captured by the mobile device's camera. It uses machine learning algorithms to determine the user's mental state and whether or not they are in a state of panic.

[0995] Input: User voice data, facial expression data

[0996] Data processing: Analysis of emotional states

[0997] Output: User's emotional state information

[0998] Step 8: Generate and send evacuation orders

[0999] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. These instructions may include phrases such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[1000] Input: Optimal evacuation route, user emotional state information

[1001] Data processing: Generation of evacuation orders

[1002] Output: Evacuation order notification to mobile devices

[1003] Step 9: Displaying evacuation instructions

[1004] The terminal visually displays the received evacuation instructions. The user looks at the screen of their mobile device and begins evacuating according to the instructed route.

[1005] Input: Evacuation order notification to mobile device

[1006] Data processing: Generating data for display

[1007] Output: Display of evacuation order

[1008] (Application Example 2)

[1009] Next, we will explain application example 2. In the following explanation, 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."

[1010] While rapid and safe evacuation is crucial during an earthquake, the potential for panic among evacuees makes issuing appropriate evacuation instructions difficult. In such situations, evacuation instructions need to consider the psychological state of evacuees, along with optimizing crowd density and evacuation routes. Furthermore, there is a need for means of providing visually and audibly useful evacuation information.

[1011] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1012] In this invention, the server includes earthquake sensing means, location information means, emotion analysis means, evacuation instruction adjustment means, transmission means, reception means, and display means. This enables the rapid and safe provision of evacuation routes in the event of an earthquake, as well as the recognition of the user's emotional state and the dynamic provision of optimal evacuation instructions. Furthermore, by visually displaying evacuation routes using a head-mounted display and providing personalized prompt messages using a generation AI model, more effective evacuation instructions can be given to the user.

[1013] An "earthquake detection device" is a device or system that detects the occurrence of an earthquake in real time and immediately transmits that information to a server.

[1014] "Location information means" refers to devices and functions such as GPS and indoor location information systems used to obtain the user's current location.

[1015] "Calculation means" refers to algorithms and programs that calculate the optimal evacuation route based on acquired location information and pedestrian flow sensor data.

[1016] "Transmission means" refers to a device or system that transmits calculated evacuation routes and evacuation instructions to the user's mobile terminal.

[1017] "Receiving means" refers to functions or devices that allow a user's mobile device to receive evacuation instructions sent from the transmitting means.

[1018] "Display means" refers to functions or devices for visually displaying received evacuation instructions and route information on the user's mobile device or head-mounted display.

[1019] "Emotional analysis tools" are algorithms and programs that analyze a user's voice data and facial expression data to identify the user's emotional state.

[1020] "Adjustment means" refers to a function or system that dynamically changes the content of evacuation orders according to the user's emotional state obtained from emotion analysis means.

[1021] A "people flow sensor" is a device or system that monitors the density and flow of people within a large building in real time and transmits that data to a server.

[1022] A "head-mounted display" is a display device that a user wears to display information within their field of vision.

[1023] A "generative AI model" is a machine learning model designed to perform a specific task and is used to generate personalized evacuation instructions and prompts for users.

[1024] A "prompt" is a formalized instruction or query text input to a generative AI model, intended to produce appropriate output according to the purpose.

[1025] The system for implementing the present invention comprises earthquake sensing means, location information means, emotion analysis means, evacuation instruction adjustment means, transmission means, reception means, and display means. This system makes it possible to dynamically provide the optimal evacuation route while considering the user's emotional state when an earthquake occurs.

[1026] 1. Earthquake sensing means

[1027] The server monitors earthquake detection sensors (e.g., Shindol, GeoSIG) and detects earthquakes in real time. If the earthquake intensity exceeds a certain threshold, the information is immediately sent to the server, which generates an earthquake alert and sends it to the user's mobile device.

[1028] 2. Location information means

[1029] The server uses the user's mobile device (e.g., iPhone, Android) GPS and indoor location systems (e.g., Bluetooth Beacon, Wi-Fi RTT) to obtain the user's current location. This location information is used in combination with data obtained from pedestrian flow sensors inside the building to calculate the optimal evacuation route.

[1030] 3. Emotion analysis means

[1031] The server analyzes the user's voice data and facial expression data captured by the mobile device's camera using an emotion analysis engine (e.g., Microsoft Azure Cognitive Services, Google Cloud Emotion API, Amazon Rekognition). This allows the server to determine the user's psychological state, particularly whether they are in a state of panic.

[1032] 4. Evacuation order coordination means

[1033] If the server determines that a user is in a state of panic, the evacuation instruction coordination mechanism generates gradual evacuation instructions to encourage calm action. This allows the user to take appropriate evacuation actions.

[1034] 5. Transmission method

[1035] The server sends evacuation instructions to the user's mobile device, based on the optimal evacuation route calculated by the computational means and the results obtained from the sentiment analysis means.

[1036] 6. Receiving means

[1037] The user's mobile device receives evacuation instructions transmitted from the server. This receiving mechanism functions through a specific, dedicated application.

[1038] 7. Display means

[1039] The user's mobile device or head-mounted display (e.g., HoloLens, Meta Quest) visually displays received evacuation instructions and route information. Furthermore, it provides voice guidance based on sentiment analysis results.

[1040] Specific example

[1041] When user A, who is inside a building experiencing an earthquake, launches the application, the server immediately receives information from earthquake detection sensors. The server obtains user A's current location and collects data from pedestrian flow sensors inside the building to calculate the optimal evacuation route. Furthermore, it analyzes user A's voice and facial expression data using an emotion analysis engine, and if it determines that user A is in a state of panic, it generates calming instructions. Gentle instructions such as, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor," are provided.

[1042] Example of a prompt

[1043] "When an earthquake is detected by the earthquake detection sensor, quickly obtain the user's current location, calculate the optimal evacuation route considering the congestion level within the building, and provide evacuation instructions based on the user's psychological state."

[1044] This configuration makes it possible to support swift and appropriate evacuation actions while taking into account the user's emotional state during an earthquake.

[1045] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1046] Step 1:

[1047] The server monitors data from earthquake sensors in real time and detects the occurrence of an earthquake. When the earthquake intensity exceeds a certain threshold, it immediately sends that information to the server (input: earthquake sensor data, output: earthquake occurrence alert). Subsequently, the server sends earthquake occurrence alerts to all registered users (specific actions: reading sensor data, threshold determination, generating and sending alert messages).

[1048] Step 2:

[1049] When the user's device receives an alert, it launches a dedicated app. The app immediately uses location information to send the current location to the server (input: alert message, GPS data; output: current location information). This current location information is used to calculate evacuation routes (specific actions: app launch, location information reading, location information transmission).

[1050] Step 3:

[1051] The server combines the received current location information with real-time data obtained from pedestrian flow sensors inside the building to calculate the optimal evacuation route (input: current location information, pedestrian flow data; output: optimal evacuation route). This calculation is performed using pathfinding algorithms such as Dijkstra's algorithm (specific operation: data collection, path calculation, path information generation).

[1052] Step 4:

[1053] The server receives the user's voice and camera data and uses an emotion analysis engine to analyze the user's emotional state (input: voice data, image data; output: emotion analysis results). This analysis determines whether the user is in a state of panic (specific actions: data collection, application of emotion analysis engine, generation of analysis results).

[1054] Step 5:

[1055] If the emotion analysis results indicate a "panic state," the server uses an evacuation instruction adjustment mechanism to generate a gentle evacuation instruction that will allow the user to act calmly (Input: Emotion analysis result, optimal evacuation route; Output: Adjusted evacuation instruction). This involves generating personalized prompt sentences using a generation AI model (Specific actions: Analysis result determination, instruction adjustment, prompt sentence generation).

[1056] Step 6:

[1057] The server sends a pre-configured evacuation order to the user's terminal (input: pre-configured evacuation order, output: evacuation order to terminal). The user's terminal receives this order, displays it visually on its display device, and also plays an audio guide (specific actions: sending evacuation order, receiving order, visual display, audio playback).

[1058] Step 7:

[1059] The user follows the designated evacuation route and takes appropriate evacuation actions based on sentiment analysis (input: visual display and audio guidance, output: appropriate evacuation actions). This enables the user to evacuate safely while suppressing panic (specific actions: start of evacuation, confirmation of instructions, execution of evacuation actions).

[1060] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1061] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1062] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1063] [Fourth Embodiment]

[1064] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1065] As shown in Figure 7, the 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.

[1066] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1067] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1068] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1069] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1070] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1071] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1072] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1073] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1074] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1075] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1076] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1077] Modes for carrying out the invention

[1078] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, and display means. By coordinating these means, it is possible to provide evacuation routes quickly and safely even in the event of a large-scale disaster.

[1079] Earthquake sensing means

[1080] The server monitors data from earthquake sensors in real time and immediately detects the occurrence of an earthquake. This information is sent to the server, and the process moves on to the next step of notifying the server of the earthquake.

[1081] Sending evacuation alerts

[1082] Once the server detects an earthquake, it sends an evacuation alert to all registered mobile devices. This alert includes a message informing users of the earthquake and urging them to evacuate to a safe place immediately. For example, a message such as "Earthquake! Evacuate immediately!" is sent to each user's mobile device.

[1083] Inquiry about evacuation routes

[1084] After receiving an earthquake alert, users launch a dedicated app on their mobile device and inquire about evacuation routes. For example, if a user types "Please tell me the evacuation route," this request is sent to the server.

[1085] Get current location

[1086] The server receives a user request and obtains location information (such as GPS data) from the mobile device. Based on this information, it determines the user's current location and uses that location data in the next step.

[1087] Collection of pedestrian flow data and calculation of evacuation routes

[1088] The server collects real-time occupancy density data from pedestrian flow sensors installed inside the building. Based on location information and pedestrian flow data, it then uses computational methods to calculate the optimal evacuation route. For example, to avoid congestion, it calculates a route that includes the currently least crowded stairwells and exits.

[1089] Evacuation order notification

[1090] The server sends the calculated optimal evacuation route to the user's mobile device. Specifically, it includes detailed evacuation instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[1091] Evacuation route display

[1092] The user's mobile device displays the received evacuation instructions. The display method allows the user to visually confirm the evacuation route. For example, displaying the route on a map allows the user to easily understand the specific evacuation path.

[1093] Specific example

[1094] Let's consider a specific example of what happens during an earthquake. An earthquake occurs in a company building, and the server immediately receives data from earthquake detection sensors. The server sends an alert to all employees' mobile devices saying, "Earthquake! Evacuate immediately!" User A, upon receiving this alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and identifies their position. Simultaneously, it collects data from pedestrian flow sensors to check the congestion level. Based on the data obtained, the server calculates the optimal evacuation route and notifies User A's mobile device, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." User A can confirm the received instructions on their mobile device screen and evacuate quickly via the designated route. In this way, smooth evacuation is achieved even during an earthquake.

[1095] The following describes the processing flow.

[1096] Step 1:

[1097] The server monitors earthquake detection sensors. When an earthquake is detected by an earthquake detection sensor, data on its speed and intensity is sent to the server.

[1098] Step 2:

[1099] The server analyzes earthquake data and determines the seismic intensity. If the seismic intensity exceeds a certain threshold, it is determined that an earthquake has occurred.

[1100] Step 3:

[1101] The server sends an earthquake alert to all registered mobile devices. The alert message includes content such as "Earthquake! Evacuate immediately!"

[1102] Step 4:

[1103] The user receives an earthquake alert and launches a dedicated app on their mobile device. The user then types "Please tell me the evacuation route" to inquire about evacuation routes.

[1104] Step 5:

[1105] The terminal sends an evacuation route inquiry from the user to the server. This request also includes information about the user's current location.

[1106] Step 6:

[1107] The server uses location information to determine the user's current location. This location information is obtained from sources such as GPS data from a mobile device.

[1108] Step 7:

[1109] The server collects data from pedestrian flow sensors within the building. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server.

[1110] Step 8:

[1111] The server calculates evacuation routes based on the user's current location and density data obtained from pedestrian flow sensors. The calculation method prioritizes less congested routes to determine the optimal evacuation path.

[1112] Step 9:

[1113] The server calculates the optimal evacuation route and sends it to the user's mobile device. For example, it might send instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[1114] Step 10:

[1115] The device displays the evacuation route it received. Depending on the display method, the evacuation route is displayed to the user in a way that is easily visible, such as on a map or in text.

[1116] Step 11:

[1117] The user checks the displayed evacuation route and begins evacuating according to the instructions. By following the instructions on the device, the user can safely evacuate via the optimal route.

[1118] (Example 1)

[1119] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1120] In the event of a large-scale earthquake disaster, an effective information system is needed to ensure rapid and safe evacuation. In particular, when large numbers of people begin evacuating simultaneously, congestion and panic are likely to occur, potentially delaying evacuation. Under these circumstances, the challenge lies in providing real-time situational awareness and accurate guidance on evacuation routes.

[1121] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1122] In this invention, the server includes means for receiving data from earthquake detection sensors in real time, means for acquiring location information of the user's mobile device, means for collecting data from pedestrian flow sensors installed inside the building and calculating the optimal evacuation route, means for generating and transmitting evacuation alerts and evacuation routes, and means for receiving and displaying evacuation routes via the user's mobile device. This enables the provision of rapid and safe evacuation routes and avoidance of congestion even in the event of a large-scale earthquake disaster.

[1123] An "earthquake detection sensor" is a device that detects earthquake vibrations and transmits that information to a server in real time.

[1124] "Real-time" means that data is processed the moment it is generated, and results are obtained almost instantly.

[1125] "Mobile devices" refer to portable information and communication devices such as smartphones and tablets owned by users.

[1126] "Location information" refers to data used to determine one's current location, such as GPS.

[1127] A "people flow sensor" is a device that detects the density and movement of people inside a building and collects the data.

[1128] An "evacuation route" refers to a recommended route for safe evacuation during a disaster.

[1129] A "server" refers to a computer system used for processing, calculating, storing, and managing data.

[1130] An "evacuation alert" is an emergency message sent to prompt immediate evacuation during emergencies such as earthquakes.

[1131] "Calculation means" refers to algorithms and software used to calculate the optimal evacuation route.

[1132] "Receiving means" refers to the mechanism by which a user's mobile device receives data transmitted from a server.

[1133] "Display means" refers to display devices or screens used to visually present received evacuation instructions and evacuation routes to the user.

[1134] An "evacuation order" refers to a message that includes specific instructions for actions to take to ensure the user's safe evacuation.

[1135] Modes for carrying out the invention

[1136] The system of the present invention consists of an earthquake detection sensor, a location information acquisition means, a calculation means, a transmission means, a reception means, and a display means. By coordinating these means, it becomes possible to quickly and safely present evacuation routes even in the event of a large-scale earthquake disaster.

[1137] earthquake sensing

[1138] First, an earthquake detection sensor is connected to the server. When the earthquake detection sensor detects an earthquake, it sends the data to the server in real time. A general-purpose earthquake detection sensor is used for this purpose.

[1139] Sending evacuation alerts

[1140] When the server detects an earthquake, it immediately sends an evacuation alert to the mobile devices of all registered users. This alert includes an urgent message such as, "Earthquake! Evacuate immediately!" The server uses a push notification service (e.g., Firebase Cloud Messaging) to send this message.

[1141] Inquiry about evacuation routes

[1142] When a user receives an evacuation alert on their mobile device, they launch a dedicated application. Through this application, the user sends a request saying, "Please tell me the evacuation route." This request is sent to the server as an HTTP POST request.

[1143] Get current location

[1144] When the server receives a user request, it obtains location information from the mobile device's GPS. The location information obtained by the GPS module is used to determine the user's current location.

[1145] Collection of pedestrian flow data and calculation of evacuation routes

[1146] The server collects data in real time from pedestrian flow sensors installed inside the building to determine the density of people within the building. Based on this pedestrian flow data and location information, the server calculates evacuation routes. Algorithms such as Dijkstra's algorithm are used for this calculation.

[1147] Evacuation order notification

[1148] The server notifies the user's mobile device of the calculated optimal evacuation route. Specifically, it sends detailed evacuation instructions such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." The server then sends this again using a push notification service.

[1149] Evacuation route display

[1150] The user displays the evacuation order notified on their mobile device. A dedicated application uses the Google Maps API and other tools to display the evacuation route on a map from the user's current location. This allows the user to visually confirm the evacuation route and evacuate safely.

[1151] Specific example

[1152] The following is a specific example of how the system works during an earthquake. When an earthquake occurs in a company building, the server immediately receives data from earthquake detection sensors and sends an alert to all employees' mobile devices saying, "Earthquake! Evacuate immediately!" User A, upon receiving the alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and calculates the optimal evacuation route based on data from pedestrian flow sensors. Based on the calculation results, User A's mobile device is notified with the instruction, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." User A can then confirm the evacuation route on their mobile device screen and evacuate quickly via the designated route.

[1153] Example of a prompt

[1154] Please describe in detail the "system for issuing rapid evacuation instructions during an earthquake." Use the subjects of server, terminal, and user, and clearly describe the specific actions, including each sensor, location information, and the process of sending evacuation alerts. For example, "The server, upon confirming the occurrence of an earthquake, sends an evacuation alert to all registered mobile terminals." Please show the specific flow of the process.

[1155] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1156] Program processing flow

[1157] Step 1: Receiving earthquake detection data

[1158] The server receives data from earthquake sensors in real time. It receives vibration data sent from the earthquake sensors as input and analyzes it. If vibrations exceeding a threshold are detected, an earthquake occurrence flag is set. The server also sets the earthquake occurrence flag as output.

[1159] Specific operation: The server polls data from the sensor every 0.1 seconds, and if vibrations exceeding a threshold are detected, it sets an earthquake occurrence flag.

[1160] Step 2: Sending an evacuation alert

[1161] When the server detects an earthquake flag, it sends an evacuation alert to all registered mobile devices. It uses the earthquake flag and user list as input to send push notifications to each user. The output is an evacuation alert sent to each mobile device.

[1162] Specific operation: The server uses a push notification service (e.g., Firebase Cloud Messaging) to send evacuation alert messages to each mobile device.

[1163] Step 3: Request an evacuation route

[1164] When a user receives an evacuation alert, they launch a dedicated app and enter a request for an evacuation route. The user enters "Please tell me the evacuation route" into the app as input, generating a request. The request is then sent to the server as output.

[1165] Specific operation: The user enters a message in the app's text input field and presses the send button. The app sends a request to the server as an HTTP POST request.

[1166] Step 4: Obtain current location

[1167] When the server receives a request from a user, it obtains location information from the mobile device's GPS. It receives the request and location information from the GPS module as input to determine the user's current location. The output is the user's latitude and longitude data.

[1168] Specific operation: The server receives an HTTP request from the terminal, calls a location information acquisition API to obtain latitude and longitude, and saves this information to the database.

[1169] Step 5: Collecting pedestrian flow data and calculating evacuation routes

[1170] The server collects data in real time from pedestrian flow sensors inside the building. It receives data from the pedestrian flow sensors and user location information as input, and uses an algorithm to calculate the optimal evacuation route. The calculated evacuation route is then output.

[1171] Specific operation: The server uses database queries to retrieve the latest human flow data and calculates the optimal evacuation route using algorithms such as Dijkstra's algorithm.

[1172] Step 6: Notification of evacuation order

[1173] The server sends the calculated optimal evacuation route to the user's mobile device. Using the calculated evacuation route and user information as input, it generates and sends a detailed evacuation instruction message. The user's mobile device receives the evacuation instruction as output.

[1174] Specific action: The server will again use the push notification service to send evacuation instructions, including detailed evacuation routes, to the user's mobile device.

[1175] Step 7: Displaying evacuation routes

[1176] The user's mobile device displays received evacuation orders via a dedicated app. The input is the received and displayed evacuation order message. The output is a screen showing the evacuation route, which the user can visually confirm.

[1177] Specific operation: The app uses the Google Maps API to display evacuation routes on a map from the user's current location, allowing for visual confirmation.

[1178] (Application Example 1)

[1179] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1180] In recent years, rapid and safe evacuation during earthquakes in factories has become increasingly important. However, conventional earthquake response systems limit evacuation route guidance to humans, making it difficult to control the appropriate actions of robots within the factory. This can lead to robots becoming obstacles or hindering human evacuation. There is a need to solve this problem and provide a system that allows all personnel and robots in a factory to evacuate safely.

[1181] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1182] In this invention, the server includes earthquake sensing means, location information means for acquiring the current location of personnel, calculation means for calculating the optimal evacuation route to at least one emergency exit, transmission means for generating and transmitting evacuation instructions including the evacuation route to the emergency exit, receiving means for receiving evacuation instructions via the user's mobile terminal, display means for displaying the user's location and evacuation route based on the location information means and evacuation instructions, and means for notifying a robot of the evacuation instructions and having the robot execute the evacuation instructions. This enables personnel and robots in the factory to evacuate quickly and safely.

[1183] An "earthquake detection device" is a device that can detect the occurrence of an earthquake and transmit the vibration information to a server in real time.

[1184] "Location information means" refers to technologies for obtaining the current location of a user or object, and generally involves using GPS or other location detection systems.

[1185] A "calculation means" is a device or system that performs processing to calculate the optimal evacuation route based on multiple data points.

[1186] A "transmission means" is a device that has the function of transmitting calculated evacuation routes and other important information to users or robots.

[1187] A "receiving device" is a device that allows a user's mobile terminal or robot to receive evacuation instructions from a transmitting device.

[1188] "Display means" refers to a device or system for visually displaying evacuation routes received from a transmission means, and usually includes a display device or monitor.

[1189] A "people flow sensor" is a sensor that monitors the density of people inside a building in real time and transmits that data to a server.

[1190] "Seismic intensity" is a measure that indicates the strength of earthquake shaking, and it is the criterion for issuing evacuation orders when the seismic intensity exceeds a specified level.

[1191] A "robot" is an automated mechanical device designed to perform specific tasks in a factory or other work environment.

[1192] "Means for executing evacuation orders" refers to a control system within a robot that recognizes evacuation orders from a receiving means and acts in accordance with those orders.

[1193] This invention is a system that supports rapid and safe evacuation in the event of an earthquake in a factory. The system includes the following means:

[1194] Earthquake sensing means

[1195] The server monitors data from earthquake sensors in real time and immediately detects the occurrence of an earthquake. This detection information is sent to the server, and the process proceeds to the next step.

[1196] Location information means

[1197] To obtain the current location of users and robots, location information systems such as GPS are used. The server acquires location information transmitted from users and robots in real time and uses this information to calculate the optimal evacuation route.

[1198] means of calculation

[1199] The server calculates evacuation routes based on earthquake detection data, location data, and data from pedestrian flow sensors. It uses powerful CPUs and AI algorithms to quickly determine the optimal evacuation route. This calculation process employs algorithms to avoid congestion and methods to find the shortest distance.

[1200] Transmission method

[1201] The server uses a communication module to send the calculated optimal evacuation route to users and robots. Evacuation instructions are sent to users' mobile devices and robots within the factory, providing evacuation routes and action instructions.

[1202] Receiving means

[1203] The user's mobile device or robot receives evacuation instructions transmitted from the server. On the mobile device, launching a dedicated app displays evacuation routes and instructions. Meanwhile, the robot begins its actions based on the received evacuation instructions and safely evacuates along the designated route.

[1204] Display means

[1205] Evacuation instructions sent from the server are displayed on mobile devices and robot displays. On mobile devices, the route is displayed on a map, allowing users to visually confirm the specific evacuation path. On robots, the instructions are displayed through internal displays and interfaces.

[1206] Execution of evacuation orders

[1207] The robot begins its actions based on the evacuation instructions it receives. Following instructions from the server, the robot proceeds along the designated evacuation route. During this process, additional processing is performed using sensors and cameras to avoid obstacles.

[1208] Specific example

[1209] When an earthquake occurs, robot R1, which is working inside the factory, immediately receives earthquake detection information and transmits it to the server. The server confirms robot R1's current location and calculates the optimal evacuation route based on data from the pedestrian flow sensor. The server then sends an evacuation instruction to robot R1: "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." Based on the received instruction, robot R1 proceeds along the evacuation route and begins to safely evacuate to the emergency exit.

[1210] Example of a prompt

[1211] "Retrieve data from the earthquake detection API and analyze that data."

[1212] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1213] Step 1:

[1214] The server monitors data from earthquake detection sensors in real time and detects the occurrence of an earthquake. The server analyzes acceleration data and shaking intensity data transmitted from the sensors and recognizes an earthquake has occurred if they exceed a certain threshold. The input is real-time data from the sensors, and the output is confirmed information that an earthquake has occurred.

[1215] Step 2:

[1216] After confirming the occurrence of an earthquake, the server sends an evacuation alert to all registered mobile devices and robots. This uses a communication module to send the message, "Earthquake! Evacuate immediately!" The input is the confirmed information that an earthquake has occurred, and the output is a notification that the alert message has been successfully sent.

[1217] Step 3:

[1218] After receiving an earthquake alert, users and robots launch a dedicated app on their mobile devices and inquire about evacuation routes. Users might type, "Please tell me the evacuation route." Robots automatically send an evacuation request to the server. Input is the user's request or an automated request from the robot, and output is confirmation of the request's receipt.

[1219] Step 4:

[1220] When the server receives an evacuation route request from a user or robot, it obtains its current location using location information. For users, it obtains GPS data from their mobile device; for robots, it obtains data from their built-in location detection system. The input is data indicating the current location, and the output is the identified location information of the user or robot.

[1221] Step 5:

[1222] The server collects real-time occupancy density data from pedestrian flow sensors installed inside the building and calculates the optimal evacuation route based on location information and pedestrian flow data. It uses algorithms to avoid congestion and shortest distance search algorithms to generate calculation results. The input is the identified location information of users and robots, as well as data from pedestrian flow sensors, and the output is the optimal evacuation route.

[1223] Step 6:

[1224] The server transmits the calculated optimal evacuation route to the user's mobile device and robot, providing specific evacuation instructions. The route is displayed on a map on the user's device, and detailed instructions are conveyed to the robot. The input is information on the optimal evacuation route, and the output is the transmission of sequential evacuation instructions.

[1225] Step 7:

[1226] The user's mobile device and the robot display the received evacuation instructions and begin taking action accordingly. The user evacuates by viewing the map displayed on the device, and the robot moves to a safe location along the evacuation route. The input is the evacuation instruction information, and the output is the execution of the evacuation action.

[1227] Example of a prompt

[1228] "Retrieve data from the earthquake detection API and analyze that data."

[1229] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1230] Modes for carrying out the invention

[1231] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, display means, and emotion engine. This makes it possible to provide a rapid and safe evacuation route in the event of an earthquake, recognize the user's emotional state, and dynamically provide optimal evacuation instructions.

[1232] Earthquake sensing means

[1233] The server monitors earthquake sensors and detects earthquakes in real time. If the earthquake intensity exceeds a certain threshold, that information is immediately sent to the server, and an earthquake alert is issued.

[1234] Location information and evacuation alert transmission

[1235] Upon confirming the occurrence of an earthquake, the server sends an earthquake alert to all registered mobile devices. This alert includes the message, "Earthquake! Evacuate immediately!" Users receive this alert and launch the dedicated app on their mobile devices.

[1236] Inquiry about evacuation routes

[1237] When a user launches the dedicated app and enters "Please tell me the evacuation route," this request is sent to the server. The server retrieves the user's current location information and determines their location.

[1238] Collection of pedestrian flow data and calculation of evacuation routes

[1239] The server collects data from pedestrian flow sensors installed inside the building. These sensors monitor the movement and density of people inside the building in real time and transmit this data to the server. Based on the location information and pedestrian flow data, the server uses computational tools to calculate the optimal evacuation route.

[1240] Emotional analysis and adjustment of evacuation orders using an emotional engine.

[1241] The emotion engine installed on the server analyzes voice data sent by the user and facial expression data captured by the mobile device's camera. Based on this data, the emotion engine determines the user's mental state and whether or not the user is in a state of panic. If the user is in a state of panic, the emotion engine generates gentle instructions to calm them down.

[1242] Evacuation order notification and display

[1243] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. For example, the instructions might include, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." These instructions are dynamically adjusted according to the user's emotional state. The device displays the received evacuation instructions, allowing the user to visually confirm them.

[1244] Specific example

[1245] Let's consider a specific example of what happens during an earthquake. An earthquake occurs in a company building, and the server immediately receives data from earthquake detection sensors. The server sends an alert to all employees' mobile devices saying, "Earthquake!" User A, upon receiving this alert, launches a dedicated app on their mobile device and enters, "Please tell me the evacuation route." The server obtains User A's location information and identifies their position. Simultaneously, it collects data from pedestrian flow sensors within the building to check the congestion level. Based on the obtained data, the server calculates the optimal evacuation route, and the emotion engine analyzes User A's facial expression data. If it is determined that User A is in a state of panic, the server sends a pre-configured instruction to the mobile device saying, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor." User A checks the displayed evacuation route and calmly begins to evacuate. In this way, appropriate evacuation is achieved even during an earthquake, according to the user's emotional state.

[1246] The following describes the processing flow.

[1247] Step 1:

[1248] The server monitors earthquake detection sensors. When an earthquake is detected by an earthquake detection sensor, data on its speed and intensity is sent to the server.

[1249] Step 2:

[1250] The server analyzes earthquake data and determines the seismic intensity. If the seismic intensity exceeds a certain threshold, it is determined that an earthquake has occurred.

[1251] Step 3:

[1252] The server sends an earthquake alert to all registered mobile devices. The alert message includes content such as "Earthquake! Evacuate immediately!"

[1253] Step 4:

[1254] The user receives an earthquake alert and launches a dedicated app on their mobile device. The user then types "Please tell me the evacuation route" to inquire about evacuation routes.

[1255] Step 5:

[1256] The terminal sends an evacuation route inquiry from the user to the server. This request also includes information about the user's current location.

[1257] Step 6:

[1258] The server uses location information to determine the user's current location. This location information is obtained from sources such as GPS data from a mobile device.

[1259] Step 7:

[1260] The server collects data from pedestrian flow sensors within the building. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server.

[1261] Step 8:

[1262] The server calculates evacuation routes based on the user's current location and density data obtained from pedestrian flow sensors. The calculation method prioritizes less congested routes to determine the optimal evacuation path.

[1263] Step 9:

[1264] The server requests data from the device to acquire the user's voice and facial expressions. The device uses its camera and microphone to collect the user's voice and facial expression data and sends it to the server.

[1265] Step 10:

[1266] The emotion engine installed on the server analyzes the transmitted voice and facial expression data to determine the user's emotional state. It analyzes whether the user is in a state of panic.

[1267] Step 11:

[1268] Based on the analysis results of the emotion engine, the server adjusts the content and format of evacuation instructions according to the user's emotional state. For example, if the user is in a panic state, it will generate gentler instructions such as, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor."

[1269] Step 12:

[1270] The server sends coordinated evacuation instructions to the user's mobile device. These instructions include specific routes and evacuation procedures.

[1271] Step 13:

[1272] The device displays the evacuation instructions it has received. Depending on the display method, the evacuation route is shown to the user in a way that is easily visible, such as on a map or in text.

[1273] Step 14:

[1274] The user checks the displayed evacuation route and begins evacuating according to the instructions. Based on the information provided by the server and instructions tailored to their emotional state, the user can safely evacuate via the optimal route.

[1275] (Example 2)

[1276] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1277] While systems exist to provide evacuation routes for rapid and safe evacuation during earthquakes, they face challenges in providing dynamic evacuation instructions that take into account factors such as the density of people in a building and the emotional state of individual users. Furthermore, if users panic, there is a high probability that appropriate evacuation instructions will not be provided, potentially delaying evacuation. As a result, problems arise where evacuations are not carried out efficiently or safely.

[1278] The identification processing performed 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 detecting earthquakes, means for acquiring the current location of personnel, means for measuring the density of personnel inside the building, means for calculating the optimal evacuation route, means for analyzing the emotional state of the user, means for generating and transmitting evacuation instructions including an evacuation route to an emergency exit, means for receiving evacuation instructions via the user's information terminal, and means for displaying the user's location and evacuation route based on location information and evacuation instructions. This enables rapid and safe evacuation even when an earthquake occurs, taking into account the emotional state of the user and the density of personnel inside the building.

[1279] "Means for detecting earthquakes" refers to sensor devices that detect the occurrence of earthquakes in real time and immediately transmit data such as seismic intensity and time of occurrence to a server.

[1280] "Means for obtaining the current location of personnel" refers to technologies that accurately obtain the user's current location information using GPS, Wi-Fi, beacons, etc.

[1281] "Means for measuring the density of people inside a building" refers to a sensor device that monitors the movement and density of people inside a building in real time and transmits that data to a server.

[1282] "Methods for calculating the optimal evacuation route" refers to a technology that uses algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs to calculate a safe and rapid evacuation route based on location information and population density data collected during an earthquake.

[1283] "Methods for analyzing a user's emotional state" refers to technologies that use machine learning algorithms to analyze voice data and facial expression data transmitted by the user to determine the user's mental state.

[1284] "Means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits" refers to a device that dynamically generates evacuation instructions based on the user's current location and the optimal evacuation route, and transmits them to the user's information terminal via communication technology.

[1285] "Means of receiving evacuation instructions via the user's information terminal" refers to technology that allows evacuation instructions transmitted from a server to be received by the user's information terminal, such as a smartphone or tablet.

[1286] "Means for displaying a user's location and evacuation route based on location information and evacuation orders" refers to a technology that visually displays received location information and evacuation orders on the user's information terminal, enabling the user to confirm their evacuation route.

[1287] Modes for carrying out the invention

[1288] The system of the present invention consists of earthquake sensing means, location information means, calculation means, transmission means, reception means, display means, and emotion engine. Details of how this system specifically operates are described below.

[1289] Earthquake sensing means

[1290] The server constantly monitors earthquake detection sensors. These sensors include, for example, accelerometers and seismometers. When these sensors detect an earthquake and the seismic intensity exceeds a certain threshold, that information is immediately sent to the server.

[1291] Location information and evacuation alert transmission

[1292] Upon confirming the occurrence of an earthquake, the server sends an earthquake alert to all registered mobile devices. This alert includes the message, "Earthquake! Evacuate immediately!" Users receive this alert and launch the dedicated app on their mobile devices.

[1293] Inquiry about evacuation routes

[1294] When a user launches the dedicated app and enters "Please tell me the evacuation route," this request is sent to the server. The server obtains the user's current location information and determines its location. Location information is obtained using GPS, Wi-Fi, beacons, etc.

[1295] Collection of pedestrian flow data and calculation of evacuation routes

[1296] The server collects data from pedestrian flow sensors installed inside the building. These sensors include infrared sensors and laser sensors. These sensors monitor the movement and density of people inside the building in real time and transmit the data to the server. Based on the location information and pedestrian flow data, the server calculates the optimal evacuation route using computational methods. Algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs are used.

[1297] Emotional analysis and adjustment of evacuation orders using an emotional engine.

[1298] The emotion engine installed on the server analyzes voice data transmitted by the user and facial expression data captured by the mobile device's camera. The emotion engine uses machine learning algorithms to determine the user's mental state and whether or not the user is in a state of panic. For example, it analyzes changes in voice tone and facial expression.

[1299] Evacuation order notification and display

[1300] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. For example, the instructions might include, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor." These instructions are dynamically adjusted according to the user's emotional state. The mobile device displays the received evacuation instructions, allowing the user to visually confirm them.

[1301] Specific example

[1302] The following are specific examples of what happens when an earthquake occurs.

[1303] An earthquake occurs inside a building, and the server immediately receives data from earthquake detection sensors. Next, the server sends an alert to all employees' mobile devices saying "Earthquake!". User A, upon receiving this alert, launches a dedicated app on their mobile device and enters "Please tell me the evacuation route." The server obtains User A's location information and locates their position. Simultaneously, it collects data from pedestrian flow sensors within the building to check the congestion level. Based on the data obtained, the server calculates the optimal evacuation route, and an emotion engine analyzes User A's facial expression data. If it is determined that User A is in a state of panic, the server sends pre-configured instructions to the mobile device saying, "Stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor." User A checks the displayed evacuation route and calmly begins to evacuate.

[1304] Example of a prompt

[1305] "An earthquake has occurred, please tell me the evacuation routes."

[1306] "Please tell me the best evacuation route from my current location."

[1307] "Calculate the optimal evacuation route and provide evacuation instructions that take emotions into consideration."

[1308] By using these prompts, specific and natural evacuation instructions can be obtained.

[1309] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1310] System program processing flow

[1311] Step 1: Earthquake detection

[1312] The server monitors data from earthquake sensors in real time. When a sensor detects an earthquake and the seismic intensity exceeds a certain threshold, that information is immediately sent to the server.

[1313] Input: Data from earthquake detection sensors

[1314] Data processing: Compare with seismic intensity thresholds and generate an alert if the threshold is exceeded.

[1315] Output: Earthquake alert information

[1316] Step 2: Sending an earthquake alert

[1317] When the server receives an alert from an earthquake detection sensor, it immediately sends an earthquake alert to all registered mobile devices. The message includes "Earthquake! Evacuate immediately!"

[1318] Input: Earthquake alert information

[1319] Data processing: Message generation

[1320] Output: Alert notification sent to the user's mobile device.

[1321] Step 3: Accepting requests for evacuation routes

[1322] Users who receive an earthquake alert launch a dedicated app and type "Please tell me the evacuation route." This request is sent to the server.

[1323] Input: User evacuation route request

[1324] Data processing: Analysis of request content

[1325] Output: Request data to the server

[1326] Step 4: Obtaining location information

[1327] The server obtains location data from the user's mobile device. This location information is collected using technologies such as GPS, Wi-Fi, and beacons.

[1328] Input: User location request

[1329] Data processing: Analysis and identification of location information

[1330] Output: User's current location information

[1331] Step 5: Collecting pedestrian flow data

[1332] The server collects data from pedestrian flow sensors installed inside the building. The sensors monitor the movement and density of people inside the building in real time and transmit that information to the server.

[1333] Input: Data from human flow sensors

[1334] Data processing: Measurement of human movement and density

[1335] Output: Foot traffic data within the building

[1336] Step 6: Calculating the optimal evacuation route

[1337] The server uses location information and human flow data to calculate the optimal evacuation route using computational methods. Algorithms such as Euclidean distance, Manhattan distance, and time-varying graphs are used.

[1338] Input: User's current location information, pedestrian flow data

[1339] Data processing: Calculation of evacuation routes

[1340] Output: Optimal evacuation route

[1341] Step 7: Emotion Analysis

[1342] The emotion engine installed on the server analyzes voice data sent by the user and facial expression data captured by the mobile device's camera. It uses machine learning algorithms to determine the user's mental state and whether or not they are in a state of panic.

[1343] Input: User voice data, facial expression data

[1344] Data processing: Analysis of emotional states

[1345] Output: User's emotional state information

[1346] Step 8: Generate and send evacuation orders

[1347] Based on the analysis results of the emotion engine, the server generates evacuation instructions in the most optimal format and sends them to the user's mobile device. These instructions may include phrases such as, "Use the central staircase A on the 12th floor and evacuate through exit C on the 1st floor."

[1348] Input: Optimal evacuation route, user emotional state information

[1349] Data processing: Generation of evacuation orders

[1350] Output: Evacuation order notification to mobile devices

[1351] Step 9: Displaying evacuation instructions

[1352] The terminal visually displays the received evacuation instructions. The user looks at the screen of their mobile device and begins evacuating according to the instructed route.

[1353] Input: Evacuation order notification to mobile device

[1354] Data processing: Generating data for display

[1355] Output: Display of evacuation order

[1356] (Application Example 2)

[1357] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1358] While rapid and safe evacuation is crucial during an earthquake, the potential for panic among evacuees makes issuing appropriate evacuation instructions difficult. In such situations, evacuation instructions need to consider the psychological state of evacuees, along with optimizing crowd density and evacuation routes. Furthermore, there is a need for means of providing visually and audibly useful evacuation information.

[1359] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1360] In this invention, the server includes earthquake sensing means, location information means, emotion analysis means, evacuation instruction adjustment means, transmission means, reception means, and display means. This enables the rapid and safe provision of evacuation routes in the event of an earthquake, as well as the recognition of the user's emotional state and the dynamic provision of optimal evacuation instructions. Furthermore, by visually displaying evacuation routes using a head-mounted display and providing personalized prompt messages using a generation AI model, more effective evacuation instructions can be given to the user.

[1361] An "earthquake detection device" is a device or system that detects the occurrence of an earthquake in real time and immediately transmits that information to a server.

[1362] "Location information means" refers to devices and functions such as GPS and indoor location information systems used to obtain the user's current location.

[1363] "Calculation means" refers to algorithms and programs that calculate the optimal evacuation route based on acquired location information and pedestrian flow sensor data.

[1364] "Transmission means" refers to a device or system that transmits calculated evacuation routes and evacuation instructions to the user's mobile terminal.

[1365] "Receiving means" refers to functions or devices that allow a user's mobile device to receive evacuation instructions sent from the transmitting means.

[1366] "Display means" refers to functions or devices for visually displaying received evacuation instructions and route information on the user's mobile device or head-mounted display.

[1367] "Emotional analysis tools" are algorithms and programs that analyze a user's voice data and facial expression data to identify the user's emotional state.

[1368] "Adjustment means" refers to a function or system that dynamically changes the content of evacuation orders according to the user's emotional state obtained from emotion analysis means.

[1369] A "people flow sensor" is a device or system that monitors the density and flow of people within a large building in real time and transmits that data to a server.

[1370] A "head-mounted display" is a display device that a user wears to display information within their field of vision.

[1371] A "generative AI model" is a machine learning model designed to perform a specific task and is used to generate personalized evacuation instructions and prompts for users.

[1372] A "prompt" is a formalized instruction or query text input to a generative AI model, intended to produce appropriate output according to the purpose.

[1373] The system for implementing the present invention comprises earthquake sensing means, location information means, emotion analysis means, evacuation instruction adjustment means, transmission means, reception means, and display means. This system makes it possible to dynamically provide the optimal evacuation route while considering the user's emotional state when an earthquake occurs.

[1374] 1. Earthquake sensing means

[1375] The server monitors earthquake detection sensors (e.g., Shindol, GeoSIG) and detects earthquakes in real time. If the earthquake intensity exceeds a certain threshold, the information is immediately sent to the server, which generates an earthquake alert and sends it to the user's mobile device.

[1376] 2. Location information means

[1377] The server uses the user's mobile device (e.g., iPhone, Android) GPS and indoor location systems (e.g., Bluetooth Beacon, Wi-Fi RTT) to obtain the user's current location. This location information is used in combination with data obtained from pedestrian flow sensors inside the building to calculate the optimal evacuation route.

[1378] 3. Emotion analysis means

[1379] The server analyzes the user's voice data and facial expression data captured by the mobile device's camera using an emotion analysis engine (e.g., Microsoft Azure Cognitive Services, Google Cloud Emotion API, Amazon Rekognition). This allows the server to determine the user's psychological state, particularly whether they are in a state of panic.

[1380] 4. Evacuation order coordination means

[1381] If the server determines that a user is in a state of panic, the evacuation instruction coordination mechanism generates gradual evacuation instructions to encourage calm action. This allows the user to take appropriate evacuation actions.

[1382] 5. Transmission method

[1383] The server sends evacuation instructions to the user's mobile device, based on the optimal evacuation route calculated by the computational means and the results obtained from the sentiment analysis means.

[1384] 6. Receiving means

[1385] The user's mobile device receives evacuation instructions transmitted from the server. This receiving mechanism functions through a specific, dedicated application.

[1386] 7. Display means

[1387] The user's mobile device or head-mounted display (e.g., HoloLens, Meta Quest) visually displays received evacuation instructions and route information. Furthermore, it provides voice guidance based on sentiment analysis results.

[1388] Specific example

[1389] When user A, who is inside a building experiencing an earthquake, launches the application, the server immediately receives information from earthquake detection sensors. The server obtains user A's current location and collects data from pedestrian flow sensors inside the building to calculate the optimal evacuation route. Furthermore, it analyzes user A's voice and facial expression data using an emotion analysis engine, and if it determines that user A is in a state of panic, it generates calming instructions. Gentle instructions such as, "Please stay calm, use the central staircase A on the 12th floor, and evacuate through exit C on the 1st floor," are provided.

[1390] Example of a prompt

[1391] "When an earthquake is detected by the earthquake detection sensor, quickly obtain the user's current location, calculate the optimal evacuation route considering the congestion level within the building, and provide evacuation instructions based on the user's psychological state."

[1392] This configuration makes it possible to support swift and appropriate evacuation actions while taking into account the user's emotional state during an earthquake.

[1393] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1394] Step 1:

[1395] The server monitors data from earthquake sensors in real time and detects the occurrence of an earthquake. When the earthquake intensity exceeds a certain threshold, it immediately sends that information to the server (input: earthquake sensor data, output: earthquake occurrence alert). Subsequently, the server sends earthquake occurrence alerts to all registered users (specific actions: reading sensor data, threshold determination, generating and sending alert messages).

[1396] Step 2:

[1397] When the user's device receives an alert, it launches a dedicated app. The app immediately uses location information to send the current location to the server (input: alert message, GPS data; output: current location information). This current location information is used to calculate evacuation routes (specific actions: app launch, location information reading, location information transmission).

[1398] Step 3:

[1399] The server combines the received current location information with real-time data obtained from pedestrian flow sensors inside the building to calculate the optimal evacuation route (input: current location information, pedestrian flow data; output: optimal evacuation route). This calculation is performed using pathfinding algorithms such as Dijkstra's algorithm (specific operation: data collection, path calculation, path information generation).

[1400] Step 4:

[1401] The server receives the user's voice and camera data and uses an emotion analysis engine to analyze the user's emotional state (input: voice data, image data; output: emotion analysis results). This analysis determines whether the user is in a state of panic (specific actions: data collection, application of emotion analysis engine, generation of analysis results).

[1402] Step 5:

[1403] If the emotion analysis results indicate a "panic state," the server uses an evacuation instruction adjustment mechanism to generate a gentle evacuation instruction that will allow the user to act calmly (Input: Emotion analysis result, optimal evacuation route; Output: Adjusted evacuation instruction). This involves generating personalized prompt sentences using a generation AI model (Specific actions: Analysis result determination, instruction adjustment, prompt sentence generation).

[1404] Step 6:

[1405] The server sends a pre-configured evacuation order to the user's terminal (input: pre-configured evacuation order, output: evacuation order to terminal). The user's terminal receives this order, displays it visually on its display device, and also plays an audio guide (specific actions: sending evacuation order, receiving order, visual display, audio playback).

[1406] Step 7:

[1407] The user follows the designated evacuation route and takes appropriate evacuation actions based on sentiment analysis (input: visual display and audio guidance, output: appropriate evacuation actions). This enables the user to evacuate safely while suppressing panic (specific actions: start of evacuation, confirmation of instructions, execution of evacuation actions).

[1408] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1409] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1410] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1411] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1412] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1413] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1414] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1415] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1416] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1417] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1418] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1419] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1420] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1421] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1422] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1423] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1424] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1425] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1426] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1427] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1428] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1429] The following is further disclosed regarding the embodiments described above.

[1430] (Claim 1)

[1431] Earthquake detection means,

[1432] A location information means for obtaining the current location of personnel,

[1433] A calculation means for calculating the optimal evacuation route to at least one emergency exit,

[1434] A transmission means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits,

[1435] A means of receiving evacuation instructions via the user's mobile device,

[1436] A display means that displays the user's location and evacuation route based on location information means and evacuation instructions,

[1437] A system that includes this.

[1438] (Claim 2)

[1439] The system according to claim 1, comprising means for monitoring the density of people inside a building using a human flow sensor, and for a calculation means to calculate the optimal evacuation route based on the data.

[1440] (Claim 3)

[1441] The system according to claim 1, further comprising: an earthquake sensing means for measuring the seismic intensity of an earthquake and a means for transmitting an evacuation order when the seismic intensity exceeds a certain level.

[1442] "Example 1"

[1443] (Claim 1)

[1444] A means of receiving data from earthquake detection sensors in real time,

[1445] A means of obtaining the location information of the user's mobile device,

[1446] A means of collecting data from pedestrian flow sensors installed inside a building and calculating the optimal evacuation route,

[1447] Means for generating and transmitting evacuation alerts and evacuation routes,

[1448] A means of receiving and displaying evacuation routes via the user's mobile device,

[1449] A system that includes this.

[1450] (Claim 2)

[1451] The system according to claim 1, comprising means for a server to send an evacuation alert to all registered mobile devices when an earthquake occurs.

[1452] (Claim 3)

[1453] The system according to claim 1, comprising means for a user's mobile device to request an evacuation route from a server, the server to calculate the optimal evacuation route based on location information and human flow data, and to transmit detailed instructions.

[1454] "Application Example 1"

[1455] (Claim 1)

[1456] Earthquake detection means,

[1457] A location information means for obtaining the current location of personnel,

[1458] A calculation means for calculating the optimal evacuation route to at least one emergency exit,

[1459] A transmission means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits,

[1460] A means of receiving evacuation instructions via the user's mobile device,

[1461] A display means that displays the user's location and evacuation route based on location information means and evacuation instructions,

[1462] A means of notifying a robot of an evacuation order and having the robot execute the evacuation order,

[1463] A system that includes this.

[1464] (Claim 2)

[1465] The system according to claim 1, comprising means for monitoring the density of people inside a building using a human flow sensor, and for a calculation means to calculate the optimal evacuation route based on the data.

[1466] (Claim 3)

[1467] The system according to claim 1, further comprising: an earthquake sensing means for measuring the seismic intensity of an earthquake and a means for transmitting an evacuation order when the seismic intensity exceeds a certain level.

[1468] "Example 2 of combining an emotion engine"

[1469] (Claim 1)

[1470] Means for detecting earthquakes,

[1471] A means of obtaining the current location of personnel,

[1472] A means for measuring the density of people inside a building,

[1473] A means for calculating the optimal evacuation route,

[1474] A means of analyzing the user's emotional state,

[1475] A means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits,

[1476] A means of receiving evacuation instructions via the user's information terminal,

[1477] A means for displaying the user's location and evacuation route based on location information and evacuation orders,

[1478] A system that includes this.

[1479] (Claim 2)

[1480] The system according to claim 1, comprising means for monitoring the density of people inside a building using a human flow sensor and calculating the optimal evacuation route based on the data.

[1481] (Claim 3)

[1482] The system according to claim 1, further comprising: an earthquake sensing means for measuring the seismic intensity of an earthquake and a means for transmitting an evacuation order when the seismic intensity exceeds a certain level.

[1483] "Application example 2 when combining with an emotional engine"

[1484] (Claim 1)

[1485] Earthquake detection means,

[1486] A location information means for obtaining the current location of personnel,

[1487] A calculation means for calculating the optimal evacuation route to at least one emergency exit,

[1488] A transmission means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits,

[1489] A means of receiving evacuation instructions via the user's mobile device,

[1490] A display means that displays the user's location and evacuation route based on location information means and evacuation instructions,

[1491] An emotion analysis means, and an adjustment means that adjusts evacuation orders based on the user's mental state,

[1492] A system that includes this.

[1493] (Claim 2)

[1494] The system according to claim 1, comprising means for monitoring the density of people inside a building using a human flow sensor, and for a calculation means to calculate the optimal evacuation route based on the data.

[1495] (Claim 3)

[1496] The system according to claim 1, further comprising: an earthquake sensing means for measuring the seismic intensity of an earthquake and a means for transmitting an evacuation order when the seismic intensity exceeds a certain level.

[1497] (Claim 4)

[1498] The system according to claim 1, comprising means for displaying evacuation routes using a head-mounted display and providing audio guidance based on information obtained by emotion analysis means.

[1499] (Claim 5)

[1500] The system according to claim 1, comprising means for generating and providing to a user prompt sentences containing evacuation instructions and sentiment analysis results in the event of an earthquake, using a generative AI model. [Explanation of symbols]

[1501] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Earthquake detection means, A location information means for obtaining the current location of personnel, A calculation means for calculating the optimal evacuation route to at least one emergency exit, A transmission means for generating and transmitting evacuation instructions, including evacuation routes to emergency exits, A means of receiving evacuation orders via the user's mobile device, A display means that displays the user's location and evacuation route based on location information means and evacuation instructions, A system that includes this.

2. The system according to claim 1, further comprising means for monitoring the density of people inside a building using a human flow sensor, and for a calculation means to calculate the optimal evacuation route based on the data.

3. The system according to claim 1, further comprising: an earthquake sensing means for measuring the seismic intensity of an earthquake and a means for transmitting an evacuation order when the seismic intensity exceeds a certain level.

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