system

Abstract

We provide the system. [Solution] A means for determining the user's location based on current location information received from a location information acquisition device, A means of integrating disaster-related information, traffic-related information, and weather-related information obtained from multiple data sources to analyze the optimal evacuation route, A means for generating dynamically updateable emergency evacuation routes based on analyzed information using generative artificial intelligence, A means for providing visual and auditory guidance of the evacuation route to the user terminal, and for providing guidance utilizing speech synthesis technology, A method for collecting the support supplies that users need after evacuation through a questionnaire and matching them with support providers based on that information, 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 the event of a disaster, it is difficult for evacuees in the affected area to quickly and safely find a route to an appropriate evacuation location. Particularly when information is scarce or in an unfamiliar area, the difficulty further increases. Also, the information asymmetry in quickly receiving necessary relief supplies and services after evacuation is a major issue. In such a situation, there is a need for a system that can quickly and effectively instruct evacuation actions and efficiently match relief needs with the provided information.

Means for Solving the Problems

[0005] To address this challenge, the present invention provides a system that identifies the user's location based on current location information received from a location information acquisition device, and analyzes the optimal evacuation route by integrating disaster information, traffic information, and weather information collected from multiple data sources. This system utilizes generative artificial intelligence to generate an emergency evacuation route that can be dynamically updated based on the analysis results. Furthermore, it provides a means of comprehensively supporting evacuees by guiding them along the evacuation route visually and audibly to the user's terminal, and after evacuation, matching them with support providers through the collection of relief supplies based on the user's needs.

[0006] A "location information acquisition device" is a device that measures the user's current location and transmits that location information to other devices or systems.

[0007] A "data source" is an external source of information that provides information necessary for a specific purpose, such as disaster information, traffic information, or weather information.

[0008] "Generative artificial intelligence" is a technology that uses machine learning and predictive analytics to generate optimal solutions and recommended paths based on specific conditions and input data.

[0009] An "evacuation route" refers to a series of paths or routes designated for moving to a safe place in the event of a disaster.

[0010] A "user terminal" is a device that a user carries or uses, and is a communication device for receiving and displaying necessary information.

[0011] "Relief supplies" refer to items and services needed by evacuees during a disaster, such as food, water, and medical supplies.

[0012] "Matching" refers to the process of efficiently connecting evacuees with requests and needs with providers who can meet those needs, providing them with the necessary goods and services. [Brief explanation of the drawing]

[0013] [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] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a processor with a reference numeral (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.

[0017] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a storage with a reference numeral 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.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention relates to a system for providing users with the optimal evacuation route in real time during a disaster, thereby streamlining subsequent support activities. The system aims to dynamically generate the optimal evacuation route by integrating information from multiple data sources and utilizing generative artificial intelligence.

[0035] Specifically, the server functions as a central device, receiving emergency information in real time from sources such as the Japan Meteorological Agency and disaster information services. Based on this information, the server assesses the severity of the disaster and quickly activates the entire system.

[0036] The user's device uses its built-in GPS function to obtain its current location. This location information is transmitted to the server in an encrypted state, ensuring the user's privacy is protected. The server integrates the received location information with other data sources (traffic information, weather information, disaster information, etc.) to analyze the safest and most effective evacuation route. As a result, artificial intelligence is used to generate an evacuation route suitable for the user, and this route is updated as needed.

[0037] The generated evacuation route is sent to the user's device, which guides the user through the route in an easy-to-understand manner via a visual map display and voice guidance. This guidance provides specific instructions and precautions for evacuation. For example, it may provide information such as, "This route is optimal given the current traffic conditions. Proceed immediately."

[0038] Furthermore, after the evacuation is complete, the system collects information on the needs for relief supplies from users in the form of a questionnaire and sends it to the server. Based on this information, the server optimally matches the necessary supplies and services with nearby aid providers, enabling rapid relief efforts.

[0039] Thus, the system of the present invention can combine and analyze a large amount of data to support evacuation actions during disasters and streamline support activities, and provide the results to users in an easy-to-understand format.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The server receives emergency information from the disaster information service. This includes the location and magnitude of earthquakes, the path of typhoons, etc., and the server uses this information to assess the severity of the disaster.

[0043] Step 2:

[0044] After the server assesses the severity of the disaster, it starts up the entire system and prepares to begin issuing evacuation orders to users' terminals.

[0045] Step 3:

[0046] The device uses its built-in GPS function to obtain the user's current location. The obtained location information is sent to the server in a privacy-protected manner.

[0047] Step 4:

[0048] The server receives the user's location information and, in addition, retrieves and integrates traffic information, weather information, and disaster information from multiple data sources. This data integration allows for an accurate understanding of the current situation.

[0049] Step 5:

[0050] The server uses artificial intelligence to analyze integrated data and dynamically generate the safest evacuation route for the user. This evacuation route is updated in real time according to the situation.

[0051] Step 6:

[0052] The terminal receives information on the optimal evacuation route from the server and uses it to provide the user with visual and audio guidance. This allows the user to evacuate quickly and safely.

[0053] Step 7:

[0054] After the user has completed their evacuation, the device will conduct a survey to collect information about their needs for relief supplies and send that information to the server.

[0055] Step 8:

[0056] The server analyzes user needs information collected and matches users with nearby support providers. This allows users to quickly receive the necessary supplies and services.

[0057] (Example 1)

[0058] 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."

[0059] During disasters, local infrastructure is disrupted, making it difficult to quickly find appropriate evacuation routes. Furthermore, providing efficient support tailored to the needs of disaster victims after evacuation is challenging. Under these circumstances, there is a need for a system that allows users to evacuate safely and receive necessary support quickly.

[0060] 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.

[0061] In this invention, the server includes means for identifying the user's current location using location information acquisition means, means for integrating disaster-related information, transportation information, and weather information acquired from multiple information sources to analyze a safe evacuation route, and means for generating a dynamically updatable evacuation route based on the analyzed information using generation AI technology. This enables the user to obtain the optimal evacuation route in real time, and further enables the rapid provision of support after evacuation.

[0062] "Location information acquisition means" refers to technical elements for determining the user's current location, and includes the use of GPS and other location information technologies.

[0063] "Information sources" refer to organizations and data systems that provide disaster-related information, transportation information, and weather information, and this information is essential for evacuation route analysis.

[0064] An "evacuation route" refers to the route that users should follow to evacuate safely and efficiently during a disaster, and it can be dynamically updated in real time.

[0065] "Generative AI technology" refers to artificial intelligence technology that has the ability to automatically generate optimal evacuation routes through the analysis and simulation of large-scale data, and to update them as needed.

[0066] "User information devices" refers to devices owned by users that are used for providing evacuation route guidance and gathering information on the needs for relief supplies.

[0067] "Relief supplies" refer to physical resources and services to meet the needs of evacuees, and include drinking water, food, and daily necessities.

[0068] "Matching" refers to the process of selecting and effectively matching support providers who have the necessary supplies to provide, based on the needs of the evacuees.

[0069] This invention aims to realize a system that provides users with the optimal evacuation route in real time during a disaster. This system mainly consists of three components: a server, a terminal, and the user.

[0070] The server functions as a central command center, collecting weather data, transportation information, and disaster information in real time from multiple sources. This data is processed by AI-powered analysis tools to assess the severity of the disaster. Specifically, it can use common web service APIs, such as the Japan Meteorological Agency API and disaster information provision services.

[0071] The device acts as the user interface and obtains current location information using its built-in GPS function. This information is encrypted for privacy protection and sent to the server. Furthermore, the device provides evacuation route information sent from the server to the user through a map display application and voice guidance. In this way, the user can check the optimal route in real time and evacuate.

[0072] Users operate a device to evacuate during a disaster. After evacuation, they can also send their needs for relief supplies to a server via a questionnaire displayed on the device. The server uses this data to appropriately match users with aid providers, enabling rapid relief efforts.

[0073] As a concrete example, when a typhoon approaches, the server immediately acquires weather data and identifies areas requiring evacuation. The terminal determines the user's current location and displays the optimal route provided by the server. The user can then safely head to a shelter while receiving guidance. Afterwards, by selecting and sending necessary supplies, the user can receive support tailored to their needs.

[0074] An example of a prompt message for a generative AI model would be: "We are thinking of a system that provides the optimal evacuation route in real time when a disaster occurs. This system will suggest the optimal evacuation route based on the user's current location and the type of disaster. Please explain the detailed process."

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The server receives disaster information, weather data, traffic information, and other data in real time from multiple sources. Specifically, the server uses APIs to retrieve data from the Japan Meteorological Agency and disaster information provision services. With this single operation, the system obtains multi-source information to be used as foundational data for assessing the severity of disasters. The input is data from each source, and the output is integrated disaster-related information.

[0078] Step 2:

[0079] The device uses its built-in GPS to obtain the user's location information. The device sends this location information to the server, but the data is encrypted for privacy protection. This process provides crucial data for determining the user's current location. The input is the device's location information, and the output is that location information in its encrypted form.

[0080] Step 3:

[0081] The server integrates and analyzes the received user location information with previously acquired disaster-related information. Using a generative AI model, it calculates the optimal evacuation route and generates a travel route that combines safety and efficiency. Here, the AI ​​considers multiple factors such as traffic conditions and weather changes. The input is the integrated disaster-related information and the user's location information, and the output is the generated evacuation route.

[0082] Step 4:

[0083] The terminal receives evacuation route information transmitted from the server and guides the user in an easy-to-understand manner. Using map displays and audio guidance, it visually and audibly guides the user to a safe evacuation location. This allows the user to obtain the latest and most optimal route information in real time. The input is evacuation route data from the server, and the output is route guidance to the user.

[0084] Step 5:

[0085] After evacuation is complete, users input the necessary relief supplies using a questionnaire displayed on their terminal. The terminal sends this information to a server, which matches them with relief providers and arranges efficient assistance. This process uses an algorithm that optimally matches the resources of providers with the needs of users. The input is information about the user's needs for relief supplies, and the output is preparation for providing assistance based on that information.

[0086] (Application Example 1)

[0087] 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."

[0088] This invention aims to provide appropriate evacuation routes in real time during disasters and to improve the efficiency of support activities after evacuation is complete. Conventional systems have difficulty rapidly updating routes in response to changes in disaster conditions and responding immediately to the diversifying needs for relief supplies. Therefore, it is necessary to provide the most suitable evacuation route to users and to achieve effective matching of relief supplies after evacuation through real-time analysis integrating multiple data sets.

[0089] 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.

[0090] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device, means for integrating disaster-related information, traffic-related information, and weather-related information obtained from multiple data sources to analyze the optimal evacuation route, and means for generating an emergency evacuation route that can be dynamically updated based on the analyzed information using generative artificial intelligence. This makes it possible to support the user in taking efficient and safe evacuation actions and to carry out support activities after evacuation quickly and appropriately.

[0091] "Location information acquisition device" refers to hardware or software used to determine the user's current location.

[0092] "Data source" refers to an external information dissemination device or system that provides information necessary for analyzing evacuation routes, such as disaster-related information, traffic-related information, and weather-related information.

[0093] "Analyzing" refers to the process of examining data in detail according to a specific purpose and deriving the optimal evacuation route.

[0094] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to automatically generate the optimal evacuation route from data and dynamically update it in response to changes in the environment.

[0095] "Dynamically updateable emergency evacuation routes" refer to route information that can automatically and continuously update evacuation routes based on real-time changes in disaster and traffic conditions.

[0096] "User terminal" refers to a computing device that a user can directly operate or use, and includes smartphones and tablets.

[0097] "Providing visual and auditory guidance" means providing information to users through screen displays and audio, and indicating directions and actions in a way that is easy for users to understand.

[0098] "Relief supplies" refer to essential goods and other helpful items provided to evacuees after a disaster.

[0099] "Collecting information through questionnaires and matching it with support providers based on that information" means collecting the needs of evacuees through questionnaires and other means, and then selecting and connecting them with those who can provide appropriate support based on that information.

[0100] The system implementing this invention consists of a terminal held by the user and a server that integrates the information. The server is activated quickly in the event of a disaster and identifies the user's current location through a location information acquisition device. A smartphone or tablet equipped with GPS functionality is recommended as the terminal.

[0101] The server receives disaster-related, traffic-related, and weather-related information in real time from multiple external data sources, such as meteorological agencies and disaster information services, and integrates and analyzes the data on a cloud platform. This analysis utilizes a generative AI model to evaluate the relevance and importance of each data point and generate optimal evacuation routes. The generated evacuation routes can be dynamically and flexibly updated.

[0102] The generated evacuation routes are provided to the user's device through visual map displays and audio guidance. The audio guidance is generated in real time using a speech synthesis API, helping users intuitively and effectively carry out evacuation actions. For example, if a road in a certain area is flooded, this information is quickly retrieved from a data source, and the route is automatically updated. The user's device will display instructions, both audibly and visually, such as, "Major roads are currently flooded. We will guide you to an alternative route."

[0103] After evacuation is complete, the terminal displays a questionnaire on the screen regarding the needs for relief supplies, encrypts the user's input, and sends it to the server. The server uses this information to appropriately match relief providers with evacuees. An example of a prompt message generated is, "Calculate the optimal evacuation route based on the current location and real-time disaster information within 5 seconds and guide the user via voice."

[0104] In this way, the system of the present invention supports evacuation actions during disasters and enables efficient support activities.

[0105] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0106] Step 1:

[0107] The server receives the user's current location information from the location information acquisition device. This information is location data obtained by GPS, which is encrypted and sent from the terminal to the server. The server decrypts this data to determine the user's exact location.

[0108] Step 2:

[0109] The server collects disaster-related, traffic-related, and weather-related information in real time from multiple data sources, such as weather agencies and disaster information services. This data is integrated on a cloud platform and used as the basis for predictive analytics.

[0110] Step 3:

[0111] The server inputs various collected data into a generating AI model to analyze the optimal evacuation route. The generating AI model analyzes the characteristics of the data and generates the most appropriate evacuation route, taking into account traffic conditions and the progression of the disaster. The analysis results are dynamically updated within the server.

[0112] Step 4:

[0113] The server sends the evacuation route, generated for each user, to the terminal. At this time, the evacuation route is processed as map data for visual display and converted into a format suitable for display on the terminal.

[0114] Step 5:

[0115] The terminal visually displays evacuation routes received from the server on its screen and provides voice guidance using a speech synthesis API. Users attempt to evacuate safely by following the instructions on the displayed map and voice guidance.

[0116] Step 6:

[0117] After the user completes their evacuation, the device displays a questionnaire to assess their needs for relief supplies. The information entered by the user is encrypted on the device and sent to the server.

[0118] Step 7:

[0119] The server uses information about the supplies received from users to perform optimal matching with support providers. This makes it possible to quickly provide support that is tailored to the user's needs.

[0120] 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.

[0121] This invention is a system that supports users' evacuation during disasters, and is particularly characterized by the combination of an emotion engine that considers the user's psychological state with evacuation route guidance. Based on the user's location information and real-time disaster and traffic information, this system provides safe evacuation routes, recognizes the user's emotional state, and provides guidance appropriate to that state.

[0122] Specifically, the server receives emergency information from a disaster information service and activates the system. The user's terminal uses its built-in GPS to obtain current location information and sends it to the server in an encrypted state. Based on this information, the server integrates the latest information from multiple data sources and intelligently generates a safe evacuation route.

[0123] This system incorporates an emotion engine that recognizes the user's emotions. It analyzes physiological data such as the user's voice tone and speed, and facial expressions, and evaluates their current emotional state. For example, if a user is feeling anxious or tense, the server receives this information and changes the tone of the evacuation route guidance to a calmer one. It also makes the instructions more detailed and guides the user in a way that provides reassurance.

[0124] The user's device provides generated evacuation route information along with voice and visual guidance tailored to their emotional state. For example, it reduces the user's psychological burden by sending instructions such as, "Please proceed calmly. There is a safe place ahead." After the evacuation is complete, a questionnaire regarding relief supplies based on the user's needs is displayed on the device, and the results are sent to the server.

[0125] Based on this needs information, the server quickly matches available relief supplies and services, coordinating with support providers to ensure users receive the necessary assistance promptly. This makes evacuation actions during disasters safer and more effective, enhancing users' psychological and physical safety.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The server receives emergency information in real time from the disaster information provision service via API. This information includes details such as the type of disaster, location, and scale.

[0129] Step 2:

[0130] The device obtains its current location information using its built-in GPS function. The user's location data is encrypted with privacy in mind before being sent to the server.

[0131] Step 3:

[0132] Based on location information received by the server, various traffic, weather, and disaster data are acquired from multiple data sources, integrated, and analyzed. This allows for real-time understanding of the current disaster situation.

[0133] Step 4:

[0134] The server uses an emotion engine to analyze the user's voice data and physiological responses collected from the device to evaluate the user's emotional state. For example, if the tone of voice is high, it might be determined that the user is feeling anxious.

[0135] Step 5:

[0136] The server uses artificial intelligence to generate the most suitable evacuation route based on integrated data and the results of an emotion engine. The tone and content of the guide are also adjusted according to the user's emotional state.

[0137] Step 6:

[0138] The terminal receives evacuation route and guidance information transmitted from the server. Based on the received information, it guides the user through the evacuation route in an easy-to-understand manner using a visual map and emotionally sensitive voice guidance.

[0139] Step 7:

[0140] The user follows the instructions on their device and takes the designated evacuation route. Route instructions are updated in real-time from the server in response to changes in the situation during the evacuation.

[0141] Step 8:

[0142] After the evacuation is complete, the terminal asks the user about their needs for relief supplies in a questionnaire format and sends the results to the server.

[0143] Step 9:

[0144] Based on the needs information collected by the server, a list of available relief supplies and services is generated, and a process is carried out to match the needs of support providers with those of users.

[0145] (Example 2)

[0146] 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".

[0147] In modern society, weather events and natural disasters often have a significant impact on our lives. However, conventional evacuation support systems lack real-time updates and adequate consideration of the psychological state of users, making appropriate evacuation difficult. Therefore, there is a need for more effective evacuation support systems that take into account the psychological state of users in order to enhance safety.

[0148] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0149] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device, means for integrating weather event information, movement status information, and environmental condition information acquired from multiple information sources to analyze the optimal evacuation route, and means for generating a dynamically updateable emergency evacuation route based on the analyzed information using bio-intelligence. This makes it possible to achieve safe and rapid evacuation in the event of weather events or natural disasters, while also reducing the psychological burden on the user.

[0150] A "location information acquisition device" is a device used to measure a user's current location and pinpoint that location.

[0151] "Information source" refers to the medium or device that provides data such as weather events, movement patterns, and environmental conditions.

[0152] "Weather event information" refers to information that includes data on weather and natural disasters, and is a fundamental element for developing evacuation plans.

[0153] "Mobility information" refers to data on traffic flow and road conditions, which influences the selection of evacuation routes.

[0154] "Environmental condition information" refers to data about the surrounding geographical and physical conditions, which is used to assess the safety of evacuation.

[0155] "Integration" is the process of combining multiple different pieces of information and data to derive consistent analytical results.

[0156] "Bio-inventive intelligence" refers to a system that uses artificial intelligence technology to analyze data and has the ability to make adaptive decisions and generate information according to the situation.

[0157] An "evacuation route" is a path that indicates how people can safely evacuate in an emergency.

[0158] An "emotion recognition device" is a technology or device that analyzes physiological data such as a user's voice and facial expressions to determine their psychological state.

[0159] "Mediation" is a process that connects the needs of users with support providers, enabling the efficient delivery of necessary support.

[0160] This invention is a system that supports the safe evacuation of users during natural disasters, and is particularly characterized by providing evacuation guidance that takes into account the user's psychological state. The server collects data from various sources of information regarding weather events, traffic conditions, and environmental conditions, and uses a location information acquisition device to determine the user's current location. Specifically, the server acquires this data in real time using an API of a disaster information provision service and dynamically generates the optimal evacuation route through a generative AI model.

[0161] The user's device utilizes a built-in GPS module to acquire real-time location information and transmit it to the server. This information is encrypted and transmitted securely. Furthermore, the device is equipped with a microphone and camera, and has a function to analyze the user's voice tone and facial expressions using an emotion recognition device to evaluate their psychological state. The generated evacuation route information is provided to the user through the device as visual and auditory guidance.

[0162] Once the evacuation is complete, the terminal displays a questionnaire to the user regarding items they need. The information entered by the user is encrypted again and sent to the server. Based on this data, the server acts as an intermediary with support providers and coordinates the provision of necessary assistance as quickly as possible.

[0163] For example, if the system determines that a user is feeling anxious during an evacuation, the voice assistant can provide a calming message such as, "Please proceed with confidence; there is a safe place ahead."

[0164] An example of a prompt for a generative AI model is as follows: "To provide evacuation guidance tailored to the user's psychological state during a disaster, please suggest appropriate voice tones and message content."

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The server collects data on weather events, traffic conditions, and environmental conditions through the API of the disaster information provision service. This input data is formatted as information necessary for risk assessment during disasters and used for subsequent processing. Specifically, the information obtained from the API is parsed into JSON format, the necessary information is extracted, and stored in the database.

[0168] Step 2:

[0169] The user's device obtains its current location using its built-in GPS module. This location information is sent to the server in an encrypted format. The input data is location coordinates, and the output is encrypted GPS data. During this process, encryption algorithms such as AES are used to securely convert the data.

[0170] Step 3:

[0171] The server integrates user location information with data from external sources to generate a safe and optimal evacuation route. Inputs include user location information and various disaster data, while output is recommended evacuation route information. This includes processes that optimize the shortest distance and safety of the route using various algorithms.

[0172] Step 4:

[0173] The user's device uses a microphone and camera to analyze the user's voice tone and facial expressions, and an emotion recognition device to evaluate their psychological state. Input is audio and visual data, and output is the evaluation result of the user's emotional state. The device utilizes machine learning models to analyze emotions in real time.

[0174] Step 5:

[0175] The server considers the generated evacuation route and the user's emotional information to provide the user with audio and visual guidance. The input is the evacuation route and emotional assessment, and the output is the adjusted guidance message. In this step, speech synthesis software is used to generate user-adapted audio instructions.

[0176] Step 6:

[0177] After evacuation is complete, the user's device displays a questionnaire regarding relief supplies and collects the user's responses. Input is the user's answers, and output is encrypted questionnaire data. The device has a user-friendly interface to guide data entry.

[0178] Step 7:

[0179] The server analyzes collected survey data and acts as an intermediary with support providers. The input is survey data, and the output is a support plan. It uses a database and matching algorithms to ensure prompt and appropriate support delivery.

[0180] (Application Example 2)

[0181] 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".

[0182] During a disaster, many people are required to evacuate quickly and safely. However, the psychological state of users is often not adequately considered, which can amplify anxiety and confusion and hinder evacuation. Furthermore, after evacuation, the provision of relief supplies may not be timely. Conventional technologies lack evacuation support systems that consider both real-time information updates and psychological support, and this needs to be addressed.

[0183] 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.

[0184] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device; means for integrating disaster information, traffic information, and weather information obtained from multiple information sources to analyze the optimal evacuation route; means for generating an emergency evacuation route that can be dynamically updated based on the analyzed information using generative artificial intelligence; means for visually and audibly guiding the user terminal along the evacuation route; means for collecting the support supplies needed by the user after evacuation and matching them with support providers based on that; and means for evaluating the user's psychological state through voice and facial expression analysis and adjusting the tone and information of the guidance based on that. This makes it possible to provide reassuring guidance that takes the user's psychological state into consideration, and to provide support supplies quickly and effectively.

[0185] A "location information acquisition device" is a device that determines the user's current location in real time, and uses GPS or other positioning technologies.

[0186] "Multiple information sources" refers to sources that provide various data, such as disaster information, traffic information, and weather information. Integrating this information makes it possible to generate the optimal evacuation route.

[0187] "Generative artificial intelligence" is an artificial intelligence technology that automatically analyzes information based on accumulated data and responds to dynamic changes in events.

[0188] An "evacuation route" is a path that allows users to safely evacuate to their destination during a disaster, and it is constantly updated based on disaster information and traffic information.

[0189] A "user terminal" is a device used to receive evacuation route guidance and various other information, and usually refers to a smartphone or tablet.

[0190] "Relief supplies" refer to food, beverages, medicines, and daily necessities that evacuees will need after a disaster, and should be provided promptly as needed.

[0191] "Voice and facial expression analysis" is a technology that evaluates a user's psychological state based on their voice tone, speed, and facial expressions, and obtains information to alleviate the user's anxiety and tension.

[0192] The system of this invention provides comprehensive evacuation support to ensure the safe evacuation of users during disasters. The server uses location information received via a location information acquisition device to pinpoint the user's exact location. It also integrates disaster information, traffic information, and weather information obtained from multiple sources in real time and analyzes this information. Based on the analysis results, the server uses artificial intelligence to generate an optimal evacuation route that can be dynamically updated, taking into account the progress of the disaster and traffic congestion.

[0193] The generated evacuation routes are provided to the user's device as visual and auditory guidance. This includes smartphones and tablets, allowing users to receive real-time, reassuring route guidance. This guidance is designed to enhance user confidence by adjusting tone and information based on the results of evaluating the user's psychological state using voice and facial expression analysis technology. Specifically, tools such as the Affectiva SDK are used for voice analysis.

[0194] After the evacuation is complete, the system collects the necessary relief supplies from users via their terminals and sends them to a server. Based on this information, the server matches them with relief providers and can quickly provide the necessary supplies.

[0195] As a concrete example, imagine a scenario where an earthquake occurs while a user is in a shopping mall, and the user's terminal provides a gentle voice instructing, "Please proceed calmly. It is safe to go up these stairs." This system plays a role in alleviating user anxiety by providing dynamic evacuation instructions using a generative AI model. The system generates optimal instructions for the user based on a prompt such as, "Analyze the voice tone and speed, and generate instructions that will calm the user."

[0196] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0197] Step 1:

[0198] The server acquires the user's current location information received from a location information acquisition device. The input is location data transmitted from the user's smartphone, which the server receives. The output is data that precisely identifies the user's location. This makes it possible to track the user's location in real time.

[0199] Step 2:

[0200] The server integrates disaster information, traffic information, and weather information obtained from multiple sources. The input consists of the latest information from various databases. The server analyzes this data and generates detailed information on disaster situations, traffic congestion, and weather conditions as output. Data processing includes accessing databases and cross-referencing information.

[0201] Step 3:

[0202] The server uses generative artificial intelligence to generate dynamically updateable evacuation routes, taking into account disaster conditions and traffic information. The input is pre-analyzed integrated information. The server uses a generative AI model to calculate the optimal evacuation route. The output provides users with safe and timely evacuation route information.

[0203] Step 4:

[0204] The terminal visually and audibly guides the user with evacuation route information received from the server. The input is route data transmitted from the server. The terminal uses this data to launch map applications and voice guides to direct the user. The output is route guidance provided to the user.

[0205] Step 5:

[0206] The terminal uses voice and facial expression analysis to assess the user's psychological state and adjusts the tone and details of the guidance accordingly. Input consists of audio and video data acquired by the microphone and camera. The terminal uses an analysis engine to analyze the user's tone and facial expressions based on the prompt message, "Analyze the voice tone and speed, and generate guidance that will calm the user." The output is customized route guidance.

[0207] Step 6:

[0208] After evacuation, the terminal collects information about the relief supplies the user needs and sends it to the server. Inputs include questionnaires and selected needs information from the user. The terminal aggregates this information, creates a list of relief supplies, and sends it to the server. The output is information about the support needs.

[0209] Step 7:

[0210] The server matches users with aid providers based on collected information about the necessary supplies. The input is user-submitted information about their aid needs. The server searches its database for available supplies and services to identify appropriate providers. The output is instructions sent to aid providers to ensure the supplies and services are delivered quickly.

[0211] 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.

[0212] 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.

[0213] 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.

[0214] [Second Embodiment]

[0215] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0216] 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.

[0217] 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).

[0218] 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.

[0219] 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.

[0220] 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).

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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".

[0227] This invention relates to a system for providing users with the optimal evacuation route in real time during a disaster, thereby streamlining subsequent support activities. The system aims to dynamically generate the optimal evacuation route by integrating information from multiple data sources and utilizing generative artificial intelligence.

[0228] Specifically, the server functions as a central device, receiving emergency information in real time from sources such as the Japan Meteorological Agency and disaster information services. Based on this information, the server assesses the severity of the disaster and quickly activates the entire system.

[0229] The user's device uses its built-in GPS function to obtain its current location. This location information is transmitted to the server in an encrypted state, ensuring the user's privacy is protected. The server integrates the received location information with other data sources (traffic information, weather information, disaster information, etc.) to analyze the safest and most effective evacuation route. As a result, artificial intelligence is used to generate an evacuation route suitable for the user, and this route is updated as needed.

[0230] The generated evacuation route is sent to the user's device, which guides the user through the route in an easy-to-understand manner via a visual map display and voice guidance. This guidance provides specific instructions and precautions for evacuation. For example, it may provide information such as, "This route is optimal given the current traffic conditions. Proceed immediately."

[0231] Furthermore, after the evacuation is complete, the system collects information on the needs for relief supplies from users in the form of a questionnaire and sends it to the server. Based on this information, the server optimally matches the necessary supplies and services with nearby aid providers, enabling rapid relief efforts.

[0232] Thus, the system of the present invention can combine and analyze a large amount of data to support evacuation actions during disasters and streamline support activities, and provide the results to users in an easy-to-understand format.

[0233] The following describes the processing flow.

[0234] Step 1:

[0235] The server receives emergency information from the disaster information service. This includes the location and magnitude of earthquakes, the path of typhoons, etc., and the server uses this information to assess the severity of the disaster.

[0236] Step 2:

[0237] After the server assesses the severity of the disaster, it starts up the entire system and prepares to begin issuing evacuation orders to users' terminals.

[0238] Step 3:

[0239] The device uses its built-in GPS function to obtain the user's current location. The obtained location information is sent to the server in a privacy-protected manner.

[0240] Step 4:

[0241] The server receives the user's location information and, in addition, retrieves and integrates traffic information, weather information, and disaster information from multiple data sources. This data integration allows for an accurate understanding of the current situation.

[0242] Step 5:

[0243] The server uses artificial intelligence to analyze integrated data and dynamically generate the safest evacuation route for the user. This evacuation route is updated in real time according to the situation.

[0244] Step 6:

[0245] The terminal receives information on the optimal evacuation route from the server and uses it to provide the user with visual and audio guidance. This allows the user to evacuate quickly and safely.

[0246] Step 7:

[0247] After the user has completed their evacuation, the device will conduct a survey to collect information about their needs for relief supplies and send that information to the server.

[0248] Step 8:

[0249] The server analyzes user needs information collected and matches users with nearby support providers. This allows users to quickly receive the necessary supplies and services.

[0250] (Example 1)

[0251] 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."

[0252] During disasters, local infrastructure is disrupted, making it difficult to quickly find appropriate evacuation routes. Furthermore, providing efficient support tailored to the needs of disaster victims after evacuation is challenging. Under these circumstances, there is a need for a system that allows users to evacuate safely and receive necessary support quickly.

[0253] 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.

[0254] In this invention, the server includes means for identifying the user's current location using location information acquisition means, means for integrating disaster-related information, transportation information, and weather information acquired from multiple information sources to analyze a safe evacuation route, and means for generating a dynamically updatable evacuation route based on the analyzed information using generation AI technology. This enables the user to obtain the optimal evacuation route in real time, and further enables the rapid provision of support after evacuation.

[0255] "Location information acquisition means" refers to technical elements for determining the user's current location, and includes the use of GPS and other location information technologies.

[0256] "Information sources" refer to organizations and data systems that provide disaster-related information, transportation information, and weather information, and this information is essential for evacuation route analysis.

[0257] An "evacuation route" refers to the route that users should follow to evacuate safely and efficiently during a disaster, and it can be dynamically updated in real time.

[0258] "Generative AI technology" refers to artificial intelligence technology that has the ability to automatically generate optimal evacuation routes through the analysis and simulation of large-scale data, and to update them as needed.

[0259] "User information devices" refers to devices owned by users that are used for providing evacuation route guidance and gathering information on the needs for relief supplies.

[0260] "Relief supplies" refer to physical resources and services to meet the needs of evacuees, and include drinking water, food, and daily necessities.

[0261] "Matching" refers to the process of selecting and effectively matching support providers who have the necessary supplies to provide, based on the needs of the evacuees.

[0262] This invention aims to realize a system that provides users with the optimal evacuation route in real time during a disaster. This system mainly consists of three components: a server, a terminal, and the user.

[0263] The server functions as a central command center, collecting weather data, transportation information, and disaster information in real time from multiple sources. This data is processed by AI-powered analysis tools to assess the severity of the disaster. Specifically, it can use common web service APIs, such as the Japan Meteorological Agency API and disaster information provision services.

[0264] The device acts as the user interface and obtains current location information using its built-in GPS function. This information is encrypted for privacy protection and sent to the server. Furthermore, the device provides evacuation route information sent from the server to the user through a map display application and voice guidance. In this way, the user can check the optimal route in real time and evacuate.

[0265] Users operate a device to evacuate during a disaster. After evacuation, they can also send their needs for relief supplies to a server via a questionnaire displayed on the device. The server uses this data to appropriately match users with aid providers, enabling rapid relief efforts.

[0266] As a concrete example, when a typhoon approaches, the server immediately acquires weather data and identifies areas requiring evacuation. The terminal determines the user's current location and displays the optimal route provided by the server. The user can then safely head to a shelter while receiving guidance. Afterwards, by selecting and sending necessary supplies, the user can receive support tailored to their needs.

[0267] An example of a prompt message for a generative AI model would be: "We are thinking of a system that provides the optimal evacuation route in real time when a disaster occurs. This system will suggest the optimal evacuation route based on the user's current location and the type of disaster. Please explain the detailed process."

[0268] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0269] Step 1:

[0270] The server receives disaster information, weather data, traffic information, and other data in real time from multiple sources. Specifically, the server uses APIs to retrieve data from the Japan Meteorological Agency and disaster information provision services. With this single operation, the system obtains multi-source information to be used as foundational data for assessing the severity of disasters. The input is data from each source, and the output is integrated disaster-related information.

[0271] Step 2:

[0272] The device uses its built-in GPS to obtain the user's location information. The device sends this location information to the server, but the data is encrypted for privacy protection. This process provides crucial data for determining the user's current location. The input is the device's location information, and the output is that location information in its encrypted form.

[0273] Step 3:

[0274] The server integrates and analyzes the received user location information with previously acquired disaster-related information. Using a generative AI model, it calculates the optimal evacuation route and generates a travel route that combines safety and efficiency. Here, the AI ​​considers multiple factors such as traffic conditions and weather changes. The input is the integrated disaster-related information and the user's location information, and the output is the generated evacuation route.

[0275] Step 4:

[0276] The terminal receives evacuation route information transmitted from the server and guides the user in an easy-to-understand manner. Using map displays and audio guidance, it visually and audibly guides the user to a safe evacuation location. This allows the user to obtain the latest and most optimal route information in real time. The input is evacuation route data from the server, and the output is route guidance to the user.

[0277] Step 5:

[0278] After evacuation is complete, users input the necessary relief supplies using a questionnaire displayed on their terminal. The terminal sends this information to a server, which matches them with relief providers and arranges efficient assistance. This process uses an algorithm that optimally matches the resources of providers with the needs of users. The input is information about the user's needs for relief supplies, and the output is preparation for providing assistance based on that information.

[0279] (Application Example 1)

[0280] 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."

[0281] This invention aims to provide appropriate evacuation routes in real time during disasters and to improve the efficiency of support activities after evacuation is complete. Conventional systems have difficulty rapidly updating routes in response to changes in disaster conditions and responding immediately to the diversifying needs for relief supplies. Therefore, it is necessary to provide the most suitable evacuation route to users and to achieve effective matching of relief supplies after evacuation through real-time analysis integrating multiple data sets.

[0282] 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.

[0283] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device, means for integrating disaster-related information, traffic-related information, and weather-related information obtained from multiple data sources to analyze the optimal evacuation route, and means for generating an emergency evacuation route that can be dynamically updated based on the analyzed information using generative artificial intelligence. This makes it possible to support the user in taking efficient and safe evacuation actions and to carry out support activities after evacuation quickly and appropriately.

[0284] The "location information acquisition device" refers to the hardware or software used to identify the user's current location.

[0285] The "data source" refers to an external information transmitting device or system that provides information necessary for analyzing evacuation routes, such as disaster-related information, traffic-related information, and weather-related information.

[0286] "Analyze" refers to the process of examining data in detail according to a specific purpose and deriving an optimal evacuation route.

[0287] The "generative artificial intelligence" refers to an artificial intelligence technology that can automatically generate an optimal evacuation route from data and dynamically update it according to changes in the environment.

[0288] The "dynamically updatable emergency evacuation route" refers to route information that can continuously update the evacuation route automatically based on the disaster situation and traffic conditions that change in real time.

[0289] The "user terminal" refers to a computing device that a user can directly operate or use, including smartphones and tablets.

[0290] "Visually and auditorily guide" means providing information to the user through screen display and voice, and indicating directions and actions in a form that is easy for the user to understand.

[0291] "Relief supplies" refer to daily necessities and other assisting supplies provided to evacuees after a disaster occurs.

[0292] "Collect in the form of a questionnaire and conduct matching with support providers" means collecting the needs from evacuees through questionnaires and selecting and linking appropriate support providers based on the information.

[0293] The system implementing this invention consists of a terminal held by the user and a server that integrates the information. The server is activated quickly in the event of a disaster and identifies the user's current location through a location information acquisition device. A smartphone or tablet equipped with GPS functionality is recommended as the terminal.

[0294] The server receives disaster-related, traffic-related, and weather-related information in real time from multiple external data sources, such as meteorological agencies and disaster information services, and integrates and analyzes the data on a cloud platform. This analysis utilizes a generative AI model to evaluate the relevance and importance of each data point and generate optimal evacuation routes. The generated evacuation routes can be dynamically and flexibly updated.

[0295] The generated evacuation routes are provided to the user's device through visual map displays and audio guidance. The audio guidance is generated in real time using a speech synthesis API, helping users intuitively and effectively carry out evacuation actions. For example, if a road in a certain area is flooded, this information is quickly retrieved from a data source, and the route is automatically updated. The user's device will display instructions, both audibly and visually, such as, "Major roads are currently flooded. We will guide you to an alternative route."

[0296] After evacuation is complete, the terminal displays a questionnaire on the screen regarding the needs for relief supplies, encrypts the user's input, and sends it to the server. The server uses this information to appropriately match relief providers with evacuees. An example of a prompt message generated is, "Calculate the optimal evacuation route based on the current location and real-time disaster information within 5 seconds and guide the user via voice."

[0297] In this way, the system of the present invention supports evacuation actions during disasters and enables efficient support activities.

[0298] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0299] Step 1:

[0300] The server receives the user's current location information from the location information acquisition device. This information is position data obtained by GPS, encrypted from the terminal, and sent to the server. The server decrypts this data to identify the user's exact location.

[0301] Step 2:

[0302] The server collects disaster-related information, traffic-related information, and weather-related information in real time from multiple data sources such as meteorological agencies and disaster information providers. These data are integrated on the cloud platform and used as a basis for performing predictive analysis.

[0303] Step 3:

[0304] The server inputs the collected various data into the generated AI model to analyze the optimal evacuation route. The generated AI model analyzes the characteristics of the data and generates the most appropriate evacuation route considering the traffic situation and the progress of the disaster. The analysis results are dynamically updated within the server.

[0305] Step 4:

[0306] The server sends the evacuation route generated for each user to the terminal. At this time, the evacuation route is processed as map data for visual display and converted into a format suitable for display on the terminal.

[0307] Step 5:

[0308] The terminal visually displays the evacuation route received from the server on the screen and provides voice guidance by utilizing the text-to-speech API. The user attempts safe evacuation following the instructions through the displayed map and voice guidance.

[0309] Step 6:

[0310] After the user completes their evacuation, the device displays a questionnaire to assess their needs for relief supplies. The information entered by the user is encrypted on the device and sent to the server.

[0311] Step 7:

[0312] The server uses information about the supplies received from users to perform optimal matching with support providers. This makes it possible to quickly provide support that is tailored to the user's needs.

[0313] 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.

[0314] This invention is a system that supports users' evacuation during disasters, and is particularly characterized by the combination of an emotion engine that considers the user's psychological state with evacuation route guidance. Based on the user's location information and real-time disaster and traffic information, this system provides safe evacuation routes, recognizes the user's emotional state, and provides guidance appropriate to that state.

[0315] Specifically, the server receives emergency information from a disaster information service and activates the system. The user's terminal uses its built-in GPS to obtain current location information and sends it to the server in an encrypted state. Based on this information, the server integrates the latest information from multiple data sources and intelligently generates a safe evacuation route.

[0316] This system incorporates an emotion engine that recognizes the user's emotions. It analyzes physiological data such as the user's voice tone and speed, and facial expressions, and evaluates their current emotional state. For example, if a user is feeling anxious or tense, the server receives this information and changes the tone of the evacuation route guidance to a calmer one. It also makes the instructions more detailed and guides the user in a way that provides reassurance.

[0317] The user's device provides generated evacuation route information along with voice and visual guidance tailored to their emotional state. For example, it reduces the user's psychological burden by sending instructions such as, "Please proceed calmly. There is a safe place ahead." After the evacuation is complete, a questionnaire regarding relief supplies based on the user's needs is displayed on the device, and the results are sent to the server.

[0318] Based on this needs information, the server quickly matches available relief supplies and services, coordinating with support providers to ensure users receive the necessary assistance promptly. This makes evacuation actions during disasters safer and more effective, enhancing users' psychological and physical safety.

[0319] The following describes the processing flow.

[0320] Step 1:

[0321] The server receives emergency information in real time from the disaster information provision service via API. This information includes details such as the type of disaster, location, and scale.

[0322] Step 2:

[0323] The device obtains its current location information using its built-in GPS function. The user's location data is encrypted with privacy in mind before being sent to the server.

[0324] Step 3:

[0325] Based on location information received by the server, various traffic, weather, and disaster data are acquired from multiple data sources, integrated, and analyzed. This allows for real-time understanding of the current disaster situation.

[0326] Step 4:

[0327] The server uses an emotion engine to analyze the user's voice data and physiological responses collected from the device to evaluate the user's emotional state. For example, if the tone of voice is high, it might be determined that the user is feeling anxious.

[0328] Step 5:

[0329] The server uses artificial intelligence to generate the most suitable evacuation route based on integrated data and the results of an emotion engine. The tone and content of the guide are also adjusted according to the user's emotional state.

[0330] Step 6:

[0331] The terminal receives evacuation route and guidance information transmitted from the server. Based on the received information, it guides the user through the evacuation route in an easy-to-understand manner using a visual map and emotionally sensitive voice guidance.

[0332] Step 7:

[0333] The user follows the instructions on their device and takes the designated evacuation route. Route instructions are updated in real-time from the server in response to changes in the situation during the evacuation.

[0334] Step 8:

[0335] After the evacuation is complete, the terminal asks the user about their needs for relief supplies in a questionnaire format and sends the results to the server.

[0336] Step 9:

[0337] Based on the needs information collected by the server, a list of available relief supplies and services is generated, and a process is carried out to match the needs of support providers with those of users.

[0338] (Example 2)

[0339] 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".

[0340] In modern society, weather events and natural disasters often have a significant impact on our lives. However, conventional evacuation support systems lack real-time updates and adequate consideration of the psychological state of users, making appropriate evacuation difficult. Therefore, there is a need for more effective evacuation support systems that take into account the psychological state of users in order to enhance safety.

[0341] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0342] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device, means for integrating weather event information, movement status information, and environmental condition information acquired from multiple information sources to analyze the optimal evacuation route, and means for generating a dynamically updateable emergency evacuation route based on the analyzed information using bio-intelligence. This makes it possible to achieve safe and rapid evacuation in the event of weather events or natural disasters, while also reducing the psychological burden on the user.

[0343] A "location information acquisition device" is a device used to measure a user's current location and pinpoint that location.

[0344] "Information source" refers to the medium or device that provides data such as weather events, movement patterns, and environmental conditions.

[0345] "Weather event information" refers to information that includes data on weather and natural disasters, and is a fundamental element for developing evacuation plans.

[0346] "Mobility information" refers to data on traffic flow and road conditions, which influences the selection of evacuation routes.

[0347] "Environmental condition information" refers to data about the surrounding geographical and physical conditions, which is used to assess the safety of evacuation.

[0348] "Integration" is the process of combining multiple different pieces of information and data to derive consistent analytical results.

[0349] "Bio-inventive intelligence" refers to a system that uses artificial intelligence technology to analyze data and has the ability to make adaptive decisions and generate information according to the situation.

[0350] An "evacuation route" is a path that indicates how people can safely evacuate in an emergency.

[0351] An "emotion recognition device" is a technology or device that analyzes physiological data such as a user's voice and facial expressions to determine their psychological state.

[0352] "Mediation" is a process that connects the needs of users with support providers, enabling the efficient delivery of necessary support.

[0353] This invention is a system that supports the safe evacuation of users during natural disasters, and is particularly characterized by providing evacuation guidance that takes into account the user's psychological state. The server collects data from various sources of information regarding weather events, traffic conditions, and environmental conditions, and uses a location information acquisition device to determine the user's current location. Specifically, the server acquires this data in real time using an API of a disaster information provision service and dynamically generates the optimal evacuation route through a generative AI model.

[0354] The user's device utilizes a built-in GPS module to acquire real-time location information and transmit it to the server. This information is encrypted and transmitted securely. Furthermore, the device is equipped with a microphone and camera, and has a function to analyze the user's voice tone and facial expressions using an emotion recognition device to evaluate their psychological state. The generated evacuation route information is provided to the user through the device as visual and auditory guidance.

[0355] Once the evacuation is complete, the terminal displays a questionnaire to the user regarding items they need. The information entered by the user is encrypted again and sent to the server. Based on this data, the server acts as an intermediary with support providers and coordinates the provision of necessary assistance as quickly as possible.

[0356] For example, if the system determines that a user is feeling anxious during an evacuation, the voice assistant can provide a calming message such as, "Please proceed with confidence; there is a safe place ahead."

[0357] An example of a prompt for a generative AI model is as follows: "To provide evacuation guidance tailored to the user's psychological state during a disaster, please suggest appropriate voice tones and message content."

[0358] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0359] Step 1:

[0360] The server collects data on weather events, traffic conditions, and environmental conditions through the API of the disaster information provision service. This input data is formatted as information necessary for risk assessment during disasters and used for subsequent processing. Specifically, the information obtained from the API is parsed into JSON format, the necessary information is extracted, and stored in the database.

[0361] Step 2:

[0362] The user's device obtains its current location using its built-in GPS module. This location information is sent to the server in an encrypted format. The input data is location coordinates, and the output is encrypted GPS data. During this process, encryption algorithms such as AES are used to securely convert the data.

[0363] Step 3:

[0364] The server integrates user location information with data from external sources to generate a safe and optimal evacuation route. Inputs include user location information and various disaster data, while output is recommended evacuation route information. This includes processes that optimize the shortest distance and safety of the route using various algorithms.

[0365] Step 4:

[0366] The user's device uses a microphone and camera to analyze the user's voice tone and facial expressions, and an emotion recognition device to evaluate their psychological state. Input is audio and visual data, and output is the evaluation result of the user's emotional state. The device utilizes machine learning models to analyze emotions in real time.

[0367] Step 5:

[0368] The server considers the generated evacuation route and the user's emotional information to provide the user with audio and visual guidance. The input is the evacuation route and emotional assessment, and the output is the adjusted guidance message. In this step, speech synthesis software is used to generate user-adapted audio instructions.

[0369] Step 6:

[0370] After evacuation is complete, the user's device displays a questionnaire regarding relief supplies and collects the user's responses. Input is the user's answers, and output is encrypted questionnaire data. The device has a user-friendly interface to guide data entry.

[0371] Step 7:

[0372] The server analyzes collected survey data and acts as an intermediary with support providers. The input is survey data, and the output is a support plan. It uses a database and matching algorithms to ensure prompt and appropriate support delivery.

[0373] (Application Example 2)

[0374] 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 as the "terminal".

[0375] During a disaster, many people are required to evacuate quickly and safely. However, the psychological state of users is often not adequately considered, which can amplify anxiety and confusion and hinder evacuation. Furthermore, after evacuation, the provision of relief supplies may not be timely. Conventional technologies lack evacuation support systems that consider both real-time information updates and psychological support, and this needs to be addressed.

[0376] 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.

[0377] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device; means for integrating disaster information, traffic information, and weather information obtained from multiple information sources to analyze the optimal evacuation route; means for generating an emergency evacuation route that can be dynamically updated based on the analyzed information using generative artificial intelligence; means for visually and audibly guiding the user terminal along the evacuation route; means for collecting the support supplies needed by the user after evacuation and matching them with support providers based on that; and means for evaluating the user's psychological state through voice and facial expression analysis and adjusting the tone and information of the guidance based on that. This makes it possible to provide reassuring guidance that takes the user's psychological state into consideration, and to provide support supplies quickly and effectively.

[0378] A "location information acquisition device" is a device that determines the user's current location in real time, and uses GPS or other positioning technologies.

[0379] "Multiple information sources" refers to sources that provide various data, such as disaster information, traffic information, and weather information. Integrating this information makes it possible to generate the optimal evacuation route.

[0380] "Generative artificial intelligence" is an artificial intelligence technology that automatically analyzes information based on accumulated data and responds to dynamic changes in events.

[0381] An "evacuation route" is a path that allows users to safely evacuate to their destination during a disaster, and it is constantly updated based on disaster information and traffic information.

[0382] A "user terminal" is a device used to receive evacuation route guidance and various other information, and usually refers to a smartphone or tablet.

[0383] "Relief supplies" refer to food, beverages, medicines, and daily necessities that evacuees will need after a disaster, and should be provided promptly as needed.

[0384] "Voice and facial expression analysis" is a technology that evaluates a user's psychological state based on their voice tone, speed, and facial expressions, and obtains information to alleviate the user's anxiety and tension.

[0385] The system of this invention provides comprehensive evacuation support to ensure the safe evacuation of users during disasters. The server uses location information received via a location information acquisition device to pinpoint the user's exact location. It also integrates disaster information, traffic information, and weather information obtained from multiple sources in real time and analyzes this information. Based on the analysis results, the server uses artificial intelligence to generate an optimal evacuation route that can be dynamically updated, taking into account the progress of the disaster and traffic congestion.

[0386] The generated evacuation routes are provided to the user's device as visual and auditory guidance. This includes smartphones and tablets, allowing users to receive real-time, reassuring route guidance. This guidance is designed to enhance user confidence by adjusting tone and information based on the results of evaluating the user's psychological state using voice and facial expression analysis technology. Specifically, tools such as the Affectiva SDK are used for voice analysis.

[0387] After the evacuation is complete, the system collects the necessary relief supplies from users via their terminals and sends them to a server. Based on this information, the server matches them with relief providers and can quickly provide the necessary supplies.

[0388] As a concrete example, imagine a scenario where an earthquake occurs while a user is in a shopping mall, and the user's terminal provides a gentle voice instructing, "Please proceed calmly. It is safe to go up these stairs." This system plays a role in alleviating user anxiety by providing dynamic evacuation instructions using a generative AI model. The system generates optimal instructions for the user based on a prompt such as, "Analyze the voice tone and speed, and generate instructions that will calm the user."

[0389] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0390] Step 1:

[0391] The server acquires the user's current location information received from a location information acquisition device. The input is location data transmitted from the user's smartphone, which the server receives. The output is data that precisely identifies the user's location. This makes it possible to track the user's location in real time.

[0392] Step 2:

[0393] The server integrates disaster information, traffic information, and weather information obtained from multiple sources. The input consists of the latest information from various databases. The server analyzes this data and generates detailed information on disaster situations, traffic congestion, and weather conditions as output. Data processing includes accessing databases and cross-referencing information.

[0394] Step 3:

[0395] The server uses generative artificial intelligence to generate dynamically updateable evacuation routes, taking into account disaster conditions and traffic information. The input is pre-analyzed integrated information. The server uses a generative AI model to calculate the optimal evacuation route. The output provides users with safe and timely evacuation route information.

[0396] Step 4:

[0397] The terminal visually and audibly guides the user with evacuation route information received from the server. The input is route data transmitted from the server. The terminal uses this data to launch map applications and voice guides to direct the user. The output is route guidance provided to the user.

[0398] Step 5:

[0399] The terminal uses voice and facial expression analysis to assess the user's psychological state and adjusts the tone and details of the guidance accordingly. Input consists of audio and video data acquired by the microphone and camera. The terminal uses an analysis engine to analyze the user's tone and facial expressions based on the prompt message, "Analyze the voice tone and speed, and generate guidance that will calm the user." The output is customized route guidance.

[0400] Step 6:

[0401] After evacuation, the terminal collects information about the relief supplies the user needs and sends it to the server. Inputs include questionnaires and selected needs information from the user. The terminal aggregates this information, creates a list of relief supplies, and sends it to the server. The output is information about the support needs.

[0402] Step 7:

[0403] The server matches users with aid providers based on collected information about the necessary supplies. The input is user-submitted information about their aid needs. The server searches its database for available supplies and services to identify appropriate providers. The output is instructions sent to aid providers to ensure the supplies and services are delivered quickly.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] [Third Embodiment]

[0408] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0409] 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.

[0410] 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).

[0411] 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.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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".

[0420] This invention relates to a system for providing users with the optimal evacuation route in real time during a disaster, thereby streamlining subsequent support activities. The system aims to dynamically generate the optimal evacuation route by integrating information from multiple data sources and utilizing generative artificial intelligence.

[0421] Specifically, the server functions as a central device, receiving emergency information in real time from sources such as the Japan Meteorological Agency and disaster information services. Based on this information, the server assesses the severity of the disaster and quickly activates the entire system.

[0422] The user's device uses its built-in GPS function to obtain its current location. This location information is transmitted to the server in an encrypted state, ensuring the user's privacy is protected. The server integrates the received location information with other data sources (traffic information, weather information, disaster information, etc.) to analyze the safest and most effective evacuation route. As a result, artificial intelligence is used to generate an evacuation route suitable for the user, and this route is updated as needed.

[0423] The generated evacuation route is sent to the user's device, which guides the user through the route in an easy-to-understand manner via a visual map display and voice guidance. This guidance provides specific instructions and precautions for evacuation. For example, it may provide information such as, "This route is optimal given the current traffic conditions. Proceed immediately."

[0424] Furthermore, after the evacuation is complete, the system collects information on the needs for relief supplies from users in the form of a questionnaire and sends it to the server. Based on this information, the server optimally matches the necessary supplies and services with nearby aid providers, enabling rapid relief efforts.

[0425] Thus, the system of the present invention can combine and analyze a large amount of data to support evacuation actions during disasters and streamline support activities, and provide the results to users in an easy-to-understand format.

[0426] The following describes the processing flow.

[0427] Step 1:

[0428] The server receives emergency information from the disaster information service. This includes the location and magnitude of earthquakes, the path of typhoons, etc., and the server uses this information to assess the severity of the disaster.

[0429] Step 2:

[0430] After the server assesses the severity of the disaster, it starts up the entire system and prepares to begin issuing evacuation orders to users' terminals.

[0431] Step 3:

[0432] The device uses its built-in GPS function to obtain the user's current location. The obtained location information is sent to the server in a privacy-protected manner.

[0433] Step 4:

[0434] The server receives the user's location information and, in addition, retrieves and integrates traffic information, weather information, and disaster information from multiple data sources. This data integration allows for an accurate understanding of the current situation.

[0435] Step 5:

[0436] The server uses artificial intelligence to analyze integrated data and dynamically generate the safest evacuation route for the user. This evacuation route is updated in real time according to the situation.

[0437] Step 6:

[0438] The terminal receives information on the optimal evacuation route from the server and uses it to provide the user with visual and audio guidance. This allows the user to evacuate quickly and safely.

[0439] Step 7:

[0440] After the user has completed their evacuation, the device will conduct a survey to collect information about their needs for relief supplies and send that information to the server.

[0441] Step 8:

[0442] The server analyzes user needs information collected and matches users with nearby support providers. This allows users to quickly receive the necessary supplies and services.

[0443] (Example 1)

[0444] 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."

[0445] During disasters, local infrastructure is disrupted, making it difficult to quickly find appropriate evacuation routes. Furthermore, providing efficient support tailored to the needs of disaster victims after evacuation is challenging. Under these circumstances, there is a need for a system that allows users to evacuate safely and receive necessary support quickly.

[0446] 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.

[0447] In this invention, the server includes means for identifying the user's current location using location information acquisition means, means for integrating disaster-related information, transportation information, and weather information acquired from multiple information sources to analyze a safe evacuation route, and means for generating a dynamically updatable evacuation route based on the analyzed information using generation AI technology. This enables the user to obtain the optimal evacuation route in real time, and further enables the rapid provision of support after evacuation.

[0448] "Location information acquisition means" refers to technical elements for determining the user's current location, and includes the use of GPS and other location information technologies.

[0449] "Information sources" refer to organizations and data systems that provide disaster-related information, transportation information, and weather information, and this information is essential for evacuation route analysis.

[0450] An "evacuation route" refers to the route that users should follow to evacuate safely and efficiently during a disaster, and it can be dynamically updated in real time.

[0451] "Generative AI technology" refers to artificial intelligence technology that has the ability to automatically generate optimal evacuation routes through the analysis and simulation of large-scale data, and to update them as needed.

[0452] "User information devices" refers to devices owned by users that are used for providing evacuation route guidance and gathering information on the needs for relief supplies.

[0453] "Relief supplies" refer to physical resources and services to meet the needs of evacuees, and include drinking water, food, and daily necessities.

[0454] "Matching" refers to the process of selecting and effectively matching support providers who have the necessary supplies to provide, based on the needs of the evacuees.

[0455] This invention aims to realize a system that provides users with the optimal evacuation route in real time during a disaster. This system mainly consists of three components: a server, a terminal, and the user.

[0456] The server functions as a central command center, collecting weather data, transportation information, and disaster information in real time from multiple sources. This data is processed by AI-powered analysis tools to assess the severity of the disaster. Specifically, it can use common web service APIs, such as the Japan Meteorological Agency API and disaster information provision services.

[0457] The device acts as the user interface and obtains current location information using its built-in GPS function. This information is encrypted for privacy protection and sent to the server. Furthermore, the device provides evacuation route information sent from the server to the user through a map display application and voice guidance. In this way, the user can check the optimal route in real time and evacuate.

[0458] Users operate a device to evacuate during a disaster. After evacuation, they can also send their needs for relief supplies to a server via a questionnaire displayed on the device. The server uses this data to appropriately match users with aid providers, enabling rapid relief efforts.

[0459] As a concrete example, when a typhoon approaches, the server immediately acquires weather data and identifies areas requiring evacuation. The terminal determines the user's current location and displays the optimal route provided by the server. The user can then safely head to a shelter while receiving guidance. Afterwards, by selecting and sending necessary supplies, the user can receive support tailored to their needs.

[0460] An example of a prompt message for a generative AI model would be: "We are thinking of a system that provides the optimal evacuation route in real time when a disaster occurs. This system will suggest the optimal evacuation route based on the user's current location and the type of disaster. Please explain the detailed process."

[0461] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0462] Step 1:

[0463] The server receives disaster information, weather data, traffic information, and other data in real time from multiple sources. Specifically, the server uses APIs to retrieve data from the Japan Meteorological Agency and disaster information provision services. With this single operation, the system obtains multi-source information to be used as foundational data for assessing the severity of disasters. The input is data from each source, and the output is integrated disaster-related information.

[0464] Step 2:

[0465] The device uses its built-in GPS to obtain the user's location information. The device sends this location information to the server, but the data is encrypted for privacy protection. This process provides crucial data for determining the user's current location. The input is the device's location information, and the output is that location information in its encrypted form.

[0466] Step 3:

[0467] The server integrates and analyzes the received user location information with previously acquired disaster-related information. Using a generative AI model, it calculates the optimal evacuation route and generates a travel route that combines safety and efficiency. Here, the AI ​​considers multiple factors such as traffic conditions and weather changes. The input is the integrated disaster-related information and the user's location information, and the output is the generated evacuation route.

[0468] Step 4:

[0469] The terminal receives evacuation route information transmitted from the server and guides the user in an easy-to-understand manner. Using map displays and audio guidance, it visually and audibly guides the user to a safe evacuation location. This allows the user to obtain the latest and most optimal route information in real time. The input is evacuation route data from the server, and the output is route guidance to the user.

[0470] Step 5:

[0471] After evacuation is complete, users input the necessary relief supplies using a questionnaire displayed on their terminal. The terminal sends this information to a server, which matches them with relief providers and arranges efficient assistance. This process uses an algorithm that optimally matches the resources of providers with the needs of users. The input is information about the user's needs for relief supplies, and the output is preparation for providing assistance based on that information.

[0472] (Application Example 1)

[0473] 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."

[0474] This invention aims to provide appropriate evacuation routes in real time during disasters and to improve the efficiency of support activities after evacuation is complete. Conventional systems have difficulty rapidly updating routes in response to changes in disaster conditions and responding immediately to the diversifying needs for relief supplies. Therefore, it is necessary to provide the most suitable evacuation route to users and to achieve effective matching of relief supplies after evacuation through real-time analysis integrating multiple data sets.

[0475] 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.

[0476] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device, means for integrating disaster-related information, traffic-related information, and weather-related information obtained from multiple data sources to analyze the optimal evacuation route, and means for generating an emergency evacuation route that can be dynamically updated based on the analyzed information using generative artificial intelligence. This makes it possible to support the user in taking efficient and safe evacuation actions and to carry out support activities after evacuation quickly and appropriately.

[0477] "Location information acquisition device" refers to hardware or software used to determine the user's current location.

[0478] "Data source" refers to an external information dissemination device or system that provides information necessary for analyzing evacuation routes, such as disaster-related information, traffic-related information, and weather-related information.

[0479] "Analyzing" refers to the process of examining data in detail according to a specific purpose and deriving the optimal evacuation route.

[0480] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to automatically generate the optimal evacuation route from data and dynamically update it in response to changes in the environment.

[0481] "Dynamically updateable emergency evacuation routes" refer to route information that can automatically and continuously update evacuation routes based on real-time changes in disaster and traffic conditions.

[0482] "User terminal" refers to a computing device that a user can directly operate or use, and includes smartphones and tablets.

[0483] "Providing visual and auditory guidance" means providing information to users through screen displays and audio, and indicating directions and actions in a way that is easy for users to understand.

[0484] "Relief supplies" refer to essential goods and other helpful items provided to evacuees after a disaster.

[0485] "Collecting information through questionnaires and matching it with support providers based on that information" means collecting the needs of evacuees through questionnaires and other means, and then selecting and connecting them with those who can provide appropriate support based on that information.

[0486] The system implementing this invention consists of a terminal held by the user and a server that integrates the information. The server is activated quickly in the event of a disaster and identifies the user's current location through a location information acquisition device. A smartphone or tablet equipped with GPS functionality is recommended as the terminal.

[0487] The server receives disaster-related, traffic-related, and weather-related information in real time from multiple external data sources, such as meteorological agencies and disaster information services, and integrates and analyzes the data on a cloud platform. This analysis utilizes a generative AI model to evaluate the relevance and importance of each data point and generate optimal evacuation routes. The generated evacuation routes can be dynamically and flexibly updated.

[0488] The generated evacuation routes are provided to the user's device through visual map displays and audio guidance. The audio guidance is generated in real time using a speech synthesis API, helping users intuitively and effectively carry out evacuation actions. For example, if a road in a certain area is flooded, this information is quickly retrieved from a data source, and the route is automatically updated. The user's device will display instructions, both audibly and visually, such as, "Major roads are currently flooded. We will guide you to an alternative route."

[0489] After evacuation is complete, the terminal displays a questionnaire on the screen regarding the needs for relief supplies, encrypts the user's input, and sends it to the server. The server uses this information to appropriately match relief providers with evacuees. An example of a prompt message generated is, "Calculate the optimal evacuation route based on the current location and real-time disaster information within 5 seconds and guide the user via voice."

[0490] In this way, the system of the present invention supports evacuation actions during disasters and enables efficient support activities.

[0491] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0492] Step 1:

[0493] The server receives the user's current location information from the location information acquisition device. This information is location data obtained by GPS, which is encrypted and sent from the terminal to the server. The server decrypts this data to determine the user's exact location.

[0494] Step 2:

[0495] The server collects disaster-related, traffic-related, and weather-related information in real time from multiple data sources, such as weather agencies and disaster information services. This data is integrated on a cloud platform and used as the basis for predictive analytics.

[0496] Step 3:

[0497] The server inputs various collected data into a generating AI model to analyze the optimal evacuation route. The generating AI model analyzes the characteristics of the data and generates the most appropriate evacuation route, taking into account traffic conditions and the progression of the disaster. The analysis results are dynamically updated within the server.

[0498] Step 4:

[0499] The server sends the evacuation route, generated for each user, to the terminal. At this time, the evacuation route is processed as map data for visual display and converted into a format suitable for display on the terminal.

[0500] Step 5:

[0501] The terminal visually displays evacuation routes received from the server on its screen and provides voice guidance using a speech synthesis API. Users attempt to evacuate safely by following the instructions on the displayed map and voice guidance.

[0502] Step 6:

[0503] After the user completes their evacuation, the device displays a questionnaire to assess their needs for relief supplies. The information entered by the user is encrypted on the device and sent to the server.

[0504] Step 7:

[0505] The server uses information about the supplies received from users to perform optimal matching with support providers. This makes it possible to quickly provide support that is tailored to the user's needs.

[0506] 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.

[0507] This invention is a system that supports users' evacuation during disasters, and is particularly characterized by the combination of an emotion engine that considers the user's psychological state with evacuation route guidance. Based on the user's location information and real-time disaster and traffic information, this system provides safe evacuation routes, recognizes the user's emotional state, and provides guidance appropriate to that state.

[0508] Specifically, the server receives emergency information from a disaster information service and activates the system. The user's terminal uses its built-in GPS to obtain current location information and sends it to the server in an encrypted state. Based on this information, the server integrates the latest information from multiple data sources and intelligently generates a safe evacuation route.

[0509] This system incorporates an emotion engine that recognizes the user's emotions. It analyzes physiological data such as the user's voice tone and speed, and facial expressions, and evaluates their current emotional state. For example, if a user is feeling anxious or tense, the server receives this information and changes the tone of the evacuation route guidance to a calmer one. It also makes the instructions more detailed and guides the user in a way that provides reassurance.

[0510] The user's device provides generated evacuation route information along with voice and visual guidance tailored to their emotional state. For example, it reduces the user's psychological burden by sending instructions such as, "Please proceed calmly. There is a safe place ahead." After the evacuation is complete, a questionnaire regarding relief supplies based on the user's needs is displayed on the device, and the results are sent to the server.

[0511] Based on this needs information, the server quickly matches available relief supplies and services, coordinating with support providers to ensure users receive the necessary assistance promptly. This makes evacuation actions during disasters safer and more effective, enhancing users' psychological and physical safety.

[0512] The following describes the processing flow.

[0513] Step 1:

[0514] The server receives emergency information in real time from the disaster information provision service via API. This information includes details such as the type of disaster, location, and scale.

[0515] Step 2:

[0516] The device obtains its current location information using its built-in GPS function. The user's location data is encrypted with privacy in mind before being sent to the server.

[0517] Step 3:

[0518] Based on location information received by the server, various traffic, weather, and disaster data are acquired from multiple data sources, integrated, and analyzed. This allows for real-time understanding of the current disaster situation.

[0519] Step 4:

[0520] The server uses an emotion engine to analyze the user's voice data and physiological responses collected from the device to evaluate the user's emotional state. For example, if the tone of voice is high, it might be determined that the user is feeling anxious.

[0521] Step 5:

[0522] The server uses artificial intelligence to generate the most suitable evacuation route based on integrated data and the results of an emotion engine. The tone and content of the guide are also adjusted according to the user's emotional state.

[0523] Step 6:

[0524] The terminal receives evacuation route and guidance information transmitted from the server. Based on the received information, it guides the user through the evacuation route in an easy-to-understand manner using a visual map and emotionally sensitive voice guidance.

[0525] Step 7:

[0526] The user follows the instructions on their device and takes the designated evacuation route. Route instructions are updated in real-time from the server in response to changes in the situation during the evacuation.

[0527] Step 8:

[0528] After the evacuation is complete, the terminal asks the user about their needs for relief supplies in a questionnaire format and sends the results to the server.

[0529] Step 9:

[0530] Based on the needs information collected by the server, a list of available relief supplies and services is generated, and a process is carried out to match the needs of support providers with those of users.

[0531] (Example 2)

[0532] 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."

[0533] In modern society, weather events and natural disasters often have a significant impact on our lives. However, conventional evacuation support systems lack real-time updates and adequate consideration of the psychological state of users, making appropriate evacuation difficult. Therefore, there is a need for more effective evacuation support systems that take into account the psychological state of users in order to enhance safety.

[0534] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0535] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device, means for integrating weather event information, movement status information, and environmental condition information acquired from multiple information sources to analyze the optimal evacuation route, and means for generating a dynamically updateable emergency evacuation route based on the analyzed information using bio-intelligence. This makes it possible to achieve safe and rapid evacuation in the event of weather events or natural disasters, while also reducing the psychological burden on the user.

[0536] A "location information acquisition device" is a device used to measure a user's current location and pinpoint that location.

[0537] "Information source" refers to the medium or device that provides data such as weather events, movement patterns, and environmental conditions.

[0538] "Weather event information" refers to information that includes data on weather and natural disasters, and is a fundamental element for developing evacuation plans.

[0539] "Mobility information" refers to data on traffic flow and road conditions, which influences the selection of evacuation routes.

[0540] "Environmental condition information" refers to data about the surrounding geographical and physical conditions, which is used to assess the safety of evacuation.

[0541] "Integration" is the process of combining multiple different pieces of information and data to derive consistent analytical results.

[0542] "Bio-inventive intelligence" refers to a system that uses artificial intelligence technology to analyze data and has the ability to make adaptive decisions and generate information according to the situation.

[0543] An "evacuation route" is a path that indicates how people can safely evacuate in an emergency.

[0544] An "emotion recognition device" is a technology or device that analyzes physiological data such as a user's voice and facial expressions to determine their psychological state.

[0545] "Mediation" is a process that connects the needs of users with support providers, enabling the efficient delivery of necessary support.

[0546] This invention is a system that supports the safe evacuation of users during natural disasters, and is particularly characterized by providing evacuation guidance that takes into account the user's psychological state. The server collects data from various sources of information regarding weather events, traffic conditions, and environmental conditions, and uses a location information acquisition device to determine the user's current location. Specifically, the server acquires this data in real time using an API of a disaster information provision service and dynamically generates the optimal evacuation route through a generative AI model.

[0547] The user's device utilizes a built-in GPS module to acquire real-time location information and transmit it to the server. This information is encrypted and transmitted securely. Furthermore, the device is equipped with a microphone and camera, and has a function to analyze the user's voice tone and facial expressions using an emotion recognition device to evaluate their psychological state. The generated evacuation route information is provided to the user through the device as visual and auditory guidance.

[0548] Once the evacuation is complete, the terminal displays a questionnaire to the user regarding items they need. The information entered by the user is encrypted again and sent to the server. Based on this data, the server acts as an intermediary with support providers and coordinates the provision of necessary assistance as quickly as possible.

[0549] For example, if the system determines that a user is feeling anxious during an evacuation, the voice assistant can provide a calming message such as, "Please proceed with confidence; there is a safe place ahead."

[0550] An example of a prompt for a generative AI model is as follows: "To provide evacuation guidance tailored to the user's psychological state during a disaster, please suggest appropriate voice tones and message content."

[0551] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0552] Step 1:

[0553] The server collects data on weather events, traffic conditions, and environmental conditions through the API of the disaster information provision service. This input data is formatted as information necessary for risk assessment during disasters and used for subsequent processing. Specifically, the information obtained from the API is parsed into JSON format, the necessary information is extracted, and stored in the database.

[0554] Step 2:

[0555] The user's device obtains its current location using its built-in GPS module. This location information is sent to the server in an encrypted format. The input data is location coordinates, and the output is encrypted GPS data. During this process, encryption algorithms such as AES are used to securely convert the data.

[0556] Step 3:

[0557] The server integrates user location information with data from external sources to generate a safe and optimal evacuation route. Inputs include user location information and various disaster data, while output is recommended evacuation route information. This includes processes that optimize the shortest distance and safety of the route using various algorithms.

[0558] Step 4:

[0559] The user's device uses a microphone and camera to analyze the user's voice tone and facial expressions, and an emotion recognition device to evaluate their psychological state. Input is audio and visual data, and output is the evaluation result of the user's emotional state. The device utilizes machine learning models to analyze emotions in real time.

[0560] Step 5:

[0561] The server considers the generated evacuation route and the user's emotional information to provide the user with audio and visual guidance. The input is the evacuation route and emotional assessment, and the output is the adjusted guidance message. In this step, speech synthesis software is used to generate user-adapted audio instructions.

[0562] Step 6:

[0563] After evacuation is complete, the user's device displays a questionnaire regarding relief supplies and collects the user's responses. Input is the user's answers, and output is encrypted questionnaire data. The device has a user-friendly interface to guide data entry.

[0564] Step 7:

[0565] The server analyzes collected survey data and acts as an intermediary with support providers. The input is survey data, and the output is a support plan. It uses a database and matching algorithms to ensure prompt and appropriate support delivery.

[0566] (Application Example 2)

[0567] 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."

[0568] During a disaster, many people are required to evacuate quickly and safely. However, the psychological state of users is often not adequately considered, which can amplify anxiety and confusion and hinder evacuation. Furthermore, after evacuation, the provision of relief supplies may not be timely. Conventional technologies lack evacuation support systems that consider both real-time information updates and psychological support, and this needs to be addressed.

[0569] 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.

[0570] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device; means for integrating disaster information, traffic information, and weather information obtained from multiple information sources to analyze the optimal evacuation route; means for generating an emergency evacuation route that can be dynamically updated based on the analyzed information using generative artificial intelligence; means for visually and audibly guiding the user terminal along the evacuation route; means for collecting the support supplies needed by the user after evacuation and matching them with support providers based on that; and means for evaluating the user's psychological state through voice and facial expression analysis and adjusting the tone and information of the guidance based on that. This makes it possible to provide reassuring guidance that takes the user's psychological state into consideration, and to provide support supplies quickly and effectively.

[0571] A "location information acquisition device" is a device that determines the user's current location in real time, and uses GPS or other positioning technologies.

[0572] "Multiple information sources" refers to sources that provide various data, such as disaster information, traffic information, and weather information. Integrating this information makes it possible to generate the optimal evacuation route.

[0573] "Generative artificial intelligence" is an artificial intelligence technology that automatically analyzes information based on accumulated data and responds to dynamic changes in events.

[0574] An "evacuation route" is a path that allows users to safely evacuate to their destination during a disaster, and it is constantly updated based on disaster information and traffic information.

[0575] A "user terminal" is a device used to receive evacuation route guidance and various other information, and usually refers to a smartphone or tablet.

[0576] "Relief supplies" refer to food, beverages, medicines, and daily necessities that evacuees will need after a disaster, and should be provided promptly as needed.

[0577] "Voice and facial expression analysis" is a technology that evaluates a user's psychological state based on their voice tone, speed, and facial expressions, and obtains information to alleviate the user's anxiety and tension.

[0578] The system of this invention provides comprehensive evacuation support to ensure the safe evacuation of users during disasters. The server uses location information received via a location information acquisition device to pinpoint the user's exact location. It also integrates disaster information, traffic information, and weather information obtained from multiple sources in real time and analyzes this information. Based on the analysis results, the server uses artificial intelligence to generate an optimal evacuation route that can be dynamically updated, taking into account the progress of the disaster and traffic congestion.

[0579] The generated evacuation routes are provided to the user's device as visual and auditory guidance. This includes smartphones and tablets, allowing users to receive real-time, reassuring route guidance. This guidance is designed to enhance user confidence by adjusting tone and information based on the results of evaluating the user's psychological state using voice and facial expression analysis technology. Specifically, tools such as the Affectiva SDK are used for voice analysis.

[0580] After the evacuation is complete, the system collects the necessary relief supplies from users via their terminals and sends them to a server. Based on this information, the server matches them with relief providers and can quickly provide the necessary supplies.

[0581] As a concrete example, imagine a scenario where an earthquake occurs while a user is in a shopping mall, and the user's terminal provides a gentle voice instructing, "Please proceed calmly. It is safe to go up these stairs." This system plays a role in alleviating user anxiety by providing dynamic evacuation instructions using a generative AI model. The system generates optimal instructions for the user based on a prompt such as, "Analyze the voice tone and speed, and generate instructions that will calm the user."

[0582] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0583] Step 1:

[0584] The server acquires the user's current location information received from a location information acquisition device. The input is location data transmitted from the user's smartphone, which the server receives. The output is data that precisely identifies the user's location. This makes it possible to track the user's location in real time.

[0585] Step 2:

[0586] The server integrates disaster information, traffic information, and weather information obtained from multiple sources. The input consists of the latest information from various databases. The server analyzes this data and generates detailed information on disaster situations, traffic congestion, and weather conditions as output. Data processing includes accessing databases and cross-referencing information.

[0587] Step 3:

[0588] The server uses generative artificial intelligence to generate dynamically updateable evacuation routes, taking into account disaster conditions and traffic information. The input is pre-analyzed integrated information. The server uses a generative AI model to calculate the optimal evacuation route. The output provides users with safe and timely evacuation route information.

[0589] Step 4:

[0590] The terminal visually and audibly guides the user with evacuation route information received from the server. The input is route data transmitted from the server. The terminal uses this data to launch map applications and voice guides to direct the user. The output is route guidance provided to the user.

[0591] Step 5:

[0592] The terminal uses voice and facial expression analysis to assess the user's psychological state and adjusts the tone and details of the guidance accordingly. Input consists of audio and video data acquired by the microphone and camera. The terminal uses an analysis engine to analyze the user's tone and facial expressions based on the prompt message, "Analyze the voice tone and speed, and generate guidance that will calm the user." The output is customized route guidance.

[0593] Step 6:

[0594] After evacuation, the terminal collects information about the relief supplies the user needs and sends it to the server. Inputs include questionnaires and selected needs information from the user. The terminal aggregates this information, creates a list of relief supplies, and sends it to the server. The output is information about the support needs.

[0595] Step 7:

[0596] The server matches users with aid providers based on collected information about the necessary supplies. The input is user-submitted information about their aid needs. The server searches its database for available supplies and services to identify appropriate providers. The output is instructions sent to aid providers to ensure the supplies and services are delivered quickly.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] [Fourth Embodiment]

[0601] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0602] 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.

[0603] 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).

[0604] 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.

[0605] 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.

[0606] 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).

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] 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".

[0614] This invention relates to a system for providing users with the optimal evacuation route in real time during a disaster, thereby streamlining subsequent support activities. The system aims to dynamically generate the optimal evacuation route by integrating information from multiple data sources and utilizing generative artificial intelligence.

[0615] Specifically, the server functions as a central device, receiving emergency information in real time from sources such as the Japan Meteorological Agency and disaster information services. Based on this information, the server assesses the severity of the disaster and quickly activates the entire system.

[0616] The user's device uses its built-in GPS function to obtain its current location. This location information is transmitted to the server in an encrypted state, ensuring the user's privacy is protected. The server integrates the received location information with other data sources (traffic information, weather information, disaster information, etc.) to analyze the safest and most effective evacuation route. As a result, artificial intelligence is used to generate an evacuation route suitable for the user, and this route is updated as needed.

[0617] The generated evacuation route is sent to the user's device, which guides the user through the route in an easy-to-understand manner via a visual map display and voice guidance. This guidance provides specific instructions and precautions for evacuation. For example, it may provide information such as, "This route is optimal given the current traffic conditions. Proceed immediately."

[0618] Furthermore, after the evacuation is complete, the system collects information on the needs for relief supplies from users in the form of a questionnaire and sends it to the server. Based on this information, the server optimally matches the necessary supplies and services with nearby aid providers, enabling rapid relief efforts.

[0619] Thus, the system of the present invention can combine and analyze a large amount of data to support evacuation actions during disasters and streamline support activities, and provide the results to users in an easy-to-understand format.

[0620] The following describes the processing flow.

[0621] Step 1:

[0622] The server receives emergency information from the disaster information service. This includes the location and magnitude of earthquakes, the path of typhoons, etc., and the server uses this information to assess the severity of the disaster.

[0623] Step 2:

[0624] After the server assesses the severity of the disaster, it starts up the entire system and prepares to begin issuing evacuation orders to users' terminals.

[0625] Step 3:

[0626] The device uses its built-in GPS function to obtain the user's current location. The obtained location information is sent to the server in a privacy-protected manner.

[0627] Step 4:

[0628] The server receives the user's location information and, in addition, retrieves and integrates traffic information, weather information, and disaster information from multiple data sources. This data integration allows for an accurate understanding of the current situation.

[0629] Step 5:

[0630] The server uses artificial intelligence to analyze integrated data and dynamically generate the safest evacuation route for the user. This evacuation route is updated in real time according to the situation.

[0631] Step 6:

[0632] The terminal receives information on the optimal evacuation route from the server and uses it to provide the user with visual and audio guidance. This allows the user to evacuate quickly and safely.

[0633] Step 7:

[0634] After the user has completed their evacuation, the device will conduct a survey to collect information about their needs for relief supplies and send that information to the server.

[0635] Step 8:

[0636] The server analyzes user needs information collected and matches users with nearby support providers. This allows users to quickly receive the necessary supplies and services.

[0637] (Example 1)

[0638] 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".

[0639] During disasters, local infrastructure is disrupted, making it difficult to quickly find appropriate evacuation routes. Furthermore, providing efficient support tailored to the needs of disaster victims after evacuation is challenging. Under these circumstances, there is a need for a system that allows users to evacuate safely and receive necessary support quickly.

[0640] 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.

[0641] In this invention, the server includes means for identifying the user's current location using location information acquisition means, means for integrating disaster-related information, transportation information, and weather information acquired from multiple information sources to analyze a safe evacuation route, and means for generating a dynamically updatable evacuation route based on the analyzed information using generation AI technology. This enables the user to obtain the optimal evacuation route in real time, and further enables the rapid provision of support after evacuation.

[0642] "Location information acquisition means" refers to technical elements for determining the user's current location, and includes the use of GPS and other location information technologies.

[0643] "Information sources" refer to organizations and data systems that provide disaster-related information, transportation information, and weather information, and this information is essential for evacuation route analysis.

[0644] An "evacuation route" refers to the route that users should follow to evacuate safely and efficiently during a disaster, and it can be dynamically updated in real time.

[0645] "Generative AI technology" refers to artificial intelligence technology that has the ability to automatically generate optimal evacuation routes through the analysis and simulation of large-scale data, and to update them as needed.

[0646] "User information devices" refers to devices owned by users that are used for providing evacuation route guidance and gathering information on the needs for relief supplies.

[0647] "Relief supplies" refer to physical resources and services to meet the needs of evacuees, and include drinking water, food, and daily necessities.

[0648] "Matching" refers to the process of selecting and effectively matching support providers who have the necessary supplies to provide, based on the needs of the evacuees.

[0649] This invention aims to realize a system that provides users with the optimal evacuation route in real time during a disaster. This system mainly consists of three components: a server, a terminal, and the user.

[0650] The server functions as a central command center, collecting weather data, transportation information, and disaster information in real time from multiple sources. This data is processed by AI-powered analysis tools to assess the severity of the disaster. Specifically, it can use common web service APIs, such as the Japan Meteorological Agency API and disaster information provision services.

[0651] The device acts as the user interface and obtains current location information using its built-in GPS function. This information is encrypted for privacy protection and sent to the server. Furthermore, the device provides evacuation route information sent from the server to the user through a map display application and voice guidance. In this way, the user can check the optimal route in real time and evacuate.

[0652] Users operate a device to evacuate during a disaster. After evacuation, they can also send their needs for relief supplies to a server via a questionnaire displayed on the device. The server uses this data to appropriately match users with aid providers, enabling rapid relief efforts.

[0653] As a concrete example, when a typhoon approaches, the server immediately acquires weather data and identifies areas requiring evacuation. The terminal determines the user's current location and displays the optimal route provided by the server. The user can then safely head to a shelter while receiving guidance. Afterwards, by selecting and sending necessary supplies, the user can receive support tailored to their needs.

[0654] An example of a prompt message for a generative AI model would be: "We are thinking of a system that provides the optimal evacuation route in real time when a disaster occurs. This system will suggest the optimal evacuation route based on the user's current location and the type of disaster. Please explain the detailed process."

[0655] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0656] Step 1:

[0657] The server receives disaster information, weather data, traffic information, and other data in real time from multiple sources. Specifically, the server uses APIs to retrieve data from the Japan Meteorological Agency and disaster information provision services. With this single operation, the system obtains multi-source information to be used as foundational data for assessing the severity of disasters. The input is data from each source, and the output is integrated disaster-related information.

[0658] Step 2:

[0659] The device uses its built-in GPS to obtain the user's location information. The device sends this location information to the server, but the data is encrypted for privacy protection. This process provides crucial data for determining the user's current location. The input is the device's location information, and the output is that location information in its encrypted form.

[0660] Step 3:

[0661] The server integrates and analyzes the received user location information with previously acquired disaster-related information. Using a generative AI model, it calculates the optimal evacuation route and generates a travel route that combines safety and efficiency. Here, the AI ​​considers multiple factors such as traffic conditions and weather changes. The input is the integrated disaster-related information and the user's location information, and the output is the generated evacuation route.

[0662] Step 4:

[0663] The terminal receives evacuation route information transmitted from the server and guides the user in an easy-to-understand manner. Using map displays and audio guidance, it visually and audibly guides the user to a safe evacuation location. This allows the user to obtain the latest and most optimal route information in real time. The input is evacuation route data from the server, and the output is route guidance to the user.

[0664] Step 5:

[0665] After evacuation is complete, users input the necessary relief supplies using a questionnaire displayed on their terminal. The terminal sends this information to a server, which matches them with relief providers and arranges efficient assistance. This process uses an algorithm that optimally matches the resources of providers with the needs of users. The input is information about the user's needs for relief supplies, and the output is preparation for providing assistance based on that information.

[0666] (Application Example 1)

[0667] 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".

[0668] This invention aims to provide appropriate evacuation routes in real time during disasters and to improve the efficiency of support activities after evacuation is complete. Conventional systems have difficulty rapidly updating routes in response to changes in disaster conditions and responding immediately to the diversifying needs for relief supplies. Therefore, it is necessary to provide the most suitable evacuation route to users and to achieve effective matching of relief supplies after evacuation through real-time analysis integrating multiple data sets.

[0669] 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.

[0670] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device, means for integrating disaster-related information, traffic-related information, and weather-related information obtained from multiple data sources to analyze the optimal evacuation route, and means for generating an emergency evacuation route that can be dynamically updated based on the analyzed information using generative artificial intelligence. This makes it possible to support the user in taking efficient and safe evacuation actions and to carry out support activities after evacuation quickly and appropriately.

[0671] "Location information acquisition device" refers to hardware or software used to determine the user's current location.

[0672] "Data source" refers to an external information dissemination device or system that provides information necessary for analyzing evacuation routes, such as disaster-related information, traffic-related information, and weather-related information.

[0673] "Analyzing" refers to the process of examining data in detail according to a specific purpose and deriving the optimal evacuation route.

[0674] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to automatically generate the optimal evacuation route from data and dynamically update it in response to changes in the environment.

[0675] "Dynamically updateable emergency evacuation routes" refer to route information that can automatically and continuously update evacuation routes based on real-time changes in disaster and traffic conditions.

[0676] "User terminal" refers to a computing device that a user can directly operate or use, and includes smartphones and tablets.

[0677] "Providing visual and auditory guidance" means providing information to users through screen displays and audio, and indicating directions and actions in a way that is easy for users to understand.

[0678] "Relief supplies" refer to essential goods and other helpful items provided to evacuees after a disaster.

[0679] "Collecting information through questionnaires and matching it with support providers based on that information" means collecting the needs of evacuees through questionnaires and other means, and then selecting and connecting them with those who can provide appropriate support based on that information.

[0680] The system implementing this invention consists of a terminal held by the user and a server that integrates the information. The server is activated quickly in the event of a disaster and identifies the user's current location through a location information acquisition device. A smartphone or tablet equipped with GPS functionality is recommended as the terminal.

[0681] The server receives disaster-related, traffic-related, and weather-related information in real time from multiple external data sources, such as meteorological agencies and disaster information services, and integrates and analyzes the data on a cloud platform. This analysis utilizes a generative AI model to evaluate the relevance and importance of each data point and generate optimal evacuation routes. The generated evacuation routes can be dynamically and flexibly updated.

[0682] The generated evacuation routes are provided to the user's device through visual map displays and audio guidance. The audio guidance is generated in real time using a speech synthesis API, helping users intuitively and effectively carry out evacuation actions. For example, if a road in a certain area is flooded, this information is quickly retrieved from a data source, and the route is automatically updated. The user's device will display instructions, both audibly and visually, such as, "Major roads are currently flooded. We will guide you to an alternative route."

[0683] After evacuation is complete, the terminal displays a questionnaire on the screen regarding the needs for relief supplies, encrypts the user's input, and sends it to the server. The server uses this information to appropriately match relief providers with evacuees. An example of a prompt message generated is, "Calculate the optimal evacuation route based on the current location and real-time disaster information within 5 seconds and guide the user via voice."

[0684] In this way, the system of the present invention supports evacuation actions during disasters and enables efficient support activities.

[0685] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0686] Step 1:

[0687] The server receives the user's current location information from the location information acquisition device. This information is location data obtained by GPS, which is encrypted and sent from the terminal to the server. The server decrypts this data to determine the user's exact location.

[0688] Step 2:

[0689] The server collects disaster-related, traffic-related, and weather-related information in real time from multiple data sources, such as weather agencies and disaster information services. This data is integrated on a cloud platform and used as the basis for predictive analytics.

[0690] Step 3:

[0691] The server inputs various collected data into a generating AI model to analyze the optimal evacuation route. The generating AI model analyzes the characteristics of the data and generates the most appropriate evacuation route, taking into account traffic conditions and the progression of the disaster. The analysis results are dynamically updated within the server.

[0692] Step 4:

[0693] The server sends the evacuation route, generated for each user, to the terminal. At this time, the evacuation route is processed as map data for visual display and converted into a format suitable for display on the terminal.

[0694] Step 5:

[0695] The terminal visually displays evacuation routes received from the server on its screen and provides voice guidance using a speech synthesis API. Users attempt to evacuate safely by following the instructions on the displayed map and voice guidance.

[0696] Step 6:

[0697] After the user completes their evacuation, the device displays a questionnaire to assess their needs for relief supplies. The information entered by the user is encrypted on the device and sent to the server.

[0698] Step 7:

[0699] The server uses information about the supplies received from users to perform optimal matching with support providers. This makes it possible to quickly provide support that is tailored to the user's needs.

[0700] 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.

[0701] This invention is a system that supports users' evacuation during disasters, and is particularly characterized by the combination of an emotion engine that considers the user's psychological state with evacuation route guidance. Based on the user's location information and real-time disaster and traffic information, this system provides safe evacuation routes, recognizes the user's emotional state, and provides guidance appropriate to that state.

[0702] Specifically, the server receives emergency information from a disaster information service and activates the system. The user's terminal uses its built-in GPS to obtain current location information and sends it to the server in an encrypted state. Based on this information, the server integrates the latest information from multiple data sources and intelligently generates a safe evacuation route.

[0703] This system incorporates an emotion engine that recognizes the user's emotions. It analyzes physiological data such as the user's voice tone and speed, and facial expressions, and evaluates their current emotional state. For example, if a user is feeling anxious or tense, the server receives this information and changes the tone of the evacuation route guidance to a calmer one. It also makes the instructions more detailed and guides the user in a way that provides reassurance.

[0704] The user's device provides generated evacuation route information along with voice and visual guidance tailored to their emotional state. For example, it reduces the user's psychological burden by sending instructions such as, "Please proceed calmly. There is a safe place ahead." After the evacuation is complete, a questionnaire regarding relief supplies based on the user's needs is displayed on the device, and the results are sent to the server.

[0705] Based on this needs information, the server quickly matches available relief supplies and services, coordinating with support providers to ensure users receive the necessary assistance promptly. This makes evacuation actions during disasters safer and more effective, enhancing users' psychological and physical safety.

[0706] The following describes the processing flow.

[0707] Step 1:

[0708] The server receives emergency information in real time from the disaster information provision service via API. This information includes details such as the type of disaster, location, and scale.

[0709] Step 2:

[0710] The device obtains its current location information using its built-in GPS function. The user's location data is encrypted with privacy in mind before being sent to the server.

[0711] Step 3:

[0712] Based on location information received by the server, various traffic, weather, and disaster data are acquired from multiple data sources, integrated, and analyzed. This allows for real-time understanding of the current disaster situation.

[0713] Step 4:

[0714] The server uses an emotion engine to analyze the user's voice data and physiological responses collected from the device to evaluate the user's emotional state. For example, if the tone of voice is high, it might be determined that the user is feeling anxious.

[0715] Step 5:

[0716] The server uses artificial intelligence to generate the most suitable evacuation route based on integrated data and the results of an emotion engine. The tone and content of the guide are also adjusted according to the user's emotional state.

[0717] Step 6:

[0718] The terminal receives evacuation route and guidance information transmitted from the server. Based on the received information, it guides the user through the evacuation route in an easy-to-understand manner using a visual map and emotionally sensitive voice guidance.

[0719] Step 7:

[0720] The user follows the instructions on their device and takes the designated evacuation route. Route instructions are updated in real-time from the server in response to changes in the situation during the evacuation.

[0721] Step 8:

[0722] After the evacuation is complete, the terminal asks the user about their needs for relief supplies in a questionnaire format and sends the results to the server.

[0723] Step 9:

[0724] Based on the needs information collected by the server, a list of available relief supplies and services is generated, and a process is carried out to match the needs of support providers with those of users.

[0725] (Example 2)

[0726] 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".

[0727] In modern society, weather events and natural disasters often have a significant impact on our lives. However, conventional evacuation support systems lack real-time updates and adequate consideration of the psychological state of users, making appropriate evacuation difficult. Therefore, there is a need for more effective evacuation support systems that take into account the psychological state of users in order to enhance safety.

[0728] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0729] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device, means for integrating weather event information, movement status information, and environmental condition information acquired from multiple information sources to analyze the optimal evacuation route, and means for generating a dynamically updateable emergency evacuation route based on the analyzed information using bio-intelligence. This makes it possible to achieve safe and rapid evacuation in the event of weather events or natural disasters, while also reducing the psychological burden on the user.

[0730] A "location information acquisition device" is a device used to measure a user's current location and pinpoint that location.

[0731] "Information source" refers to the medium or device that provides data such as weather events, movement patterns, and environmental conditions.

[0732] "Weather event information" refers to information that includes data on weather and natural disasters, and is a fundamental element for developing evacuation plans.

[0733] "Mobility information" refers to data on traffic flow and road conditions, which influences the selection of evacuation routes.

[0734] "Environmental condition information" refers to data about the surrounding geographical and physical conditions, which is used to assess the safety of evacuation.

[0735] "Integration" is the process of combining multiple different pieces of information and data to derive consistent analytical results.

[0736] "Bio-inventive intelligence" refers to a system that uses artificial intelligence technology to analyze data and has the ability to make adaptive decisions and generate information according to the situation.

[0737] An "evacuation route" is a path that indicates how people can safely evacuate in an emergency.

[0738] An "emotion recognition device" is a technology or device that analyzes physiological data such as a user's voice and facial expressions to determine their psychological state.

[0739] "Mediation" is a process that connects the needs of users with support providers, enabling the efficient delivery of necessary support.

[0740] This invention is a system that supports the safe evacuation of users during natural disasters, and is particularly characterized by providing evacuation guidance that takes into account the user's psychological state. The server collects data from various sources of information regarding weather events, traffic conditions, and environmental conditions, and uses a location information acquisition device to determine the user's current location. Specifically, the server acquires this data in real time using an API of a disaster information provision service and dynamically generates the optimal evacuation route through a generative AI model.

[0741] The user's device utilizes a built-in GPS module to acquire real-time location information and transmit it to the server. This information is encrypted and transmitted securely. Furthermore, the device is equipped with a microphone and camera, and has a function to analyze the user's voice tone and facial expressions using an emotion recognition device to evaluate their psychological state. The generated evacuation route information is provided to the user through the device as visual and auditory guidance.

[0742] Once the evacuation is complete, the terminal displays a questionnaire to the user regarding items they need. The information entered by the user is encrypted again and sent to the server. Based on this data, the server acts as an intermediary with support providers and coordinates the provision of necessary assistance as quickly as possible.

[0743] For example, if the system determines that a user is feeling anxious during an evacuation, the voice assistant can provide a calming message such as, "Please proceed with confidence; there is a safe place ahead."

[0744] An example of a prompt for a generative AI model is as follows: "To provide evacuation guidance tailored to the user's psychological state during a disaster, please suggest appropriate voice tones and message content."

[0745] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0746] Step 1:

[0747] The server collects data on weather events, traffic conditions, and environmental conditions through the API of the disaster information provision service. This input data is formatted as information necessary for risk assessment during disasters and used for subsequent processing. Specifically, the information obtained from the API is parsed into JSON format, the necessary information is extracted, and stored in the database.

[0748] Step 2:

[0749] The user's device obtains its current location using its built-in GPS module. This location information is sent to the server in an encrypted format. The input data is location coordinates, and the output is encrypted GPS data. During this process, encryption algorithms such as AES are used to securely convert the data.

[0750] Step 3:

[0751] The server integrates user location information with data from external sources to generate a safe and optimal evacuation route. Inputs include user location information and various disaster data, while output is recommended evacuation route information. This includes processes that optimize the shortest distance and safety of the route using various algorithms.

[0752] Step 4:

[0753] The user's device uses a microphone and camera to analyze the user's voice tone and facial expressions, and an emotion recognition device to evaluate their psychological state. Input is audio and visual data, and output is the evaluation result of the user's emotional state. The device utilizes machine learning models to analyze emotions in real time.

[0754] Step 5:

[0755] The server considers the generated evacuation route and the user's emotional information to provide the user with audio and visual guidance. The input is the evacuation route and emotional assessment, and the output is the adjusted guidance message. In this step, speech synthesis software is used to generate user-adapted audio instructions.

[0756] Step 6:

[0757] After evacuation is complete, the user's device displays a questionnaire regarding relief supplies and collects the user's responses. Input is the user's answers, and output is encrypted questionnaire data. The device has a user-friendly interface to guide data entry.

[0758] Step 7:

[0759] The server analyzes collected survey data and acts as an intermediary with support providers. The input is survey data, and the output is a support plan. It uses a database and matching algorithms to ensure prompt and appropriate support delivery.

[0760] (Application Example 2)

[0761] 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".

[0762] During a disaster, many people are required to evacuate quickly and safely. However, the psychological state of users is often not adequately considered, which can amplify anxiety and confusion and hinder evacuation. Furthermore, after evacuation, the provision of relief supplies may not be timely. Conventional technologies lack evacuation support systems that consider both real-time information updates and psychological support, and this needs to be addressed.

[0763] 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.

[0764] In this invention, the server includes means for identifying the user's location based on current location information received from a location information acquisition device; means for integrating disaster information, traffic information, and weather information obtained from multiple information sources to analyze the optimal evacuation route; means for generating an emergency evacuation route that can be dynamically updated based on the analyzed information using generative artificial intelligence; means for visually and audibly guiding the user terminal along the evacuation route; means for collecting the support supplies needed by the user after evacuation and matching them with support providers based on that; and means for evaluating the user's psychological state through voice and facial expression analysis and adjusting the tone and information of the guidance based on that. This makes it possible to provide reassuring guidance that takes the user's psychological state into consideration, and to provide support supplies quickly and effectively.

[0765] A "location information acquisition device" is a device that determines the user's current location in real time, and uses GPS or other positioning technologies.

[0766] "Multiple information sources" refers to sources that provide various data, such as disaster information, traffic information, and weather information. Integrating this information makes it possible to generate the optimal evacuation route.

[0767] "Generative artificial intelligence" is an artificial intelligence technology that automatically analyzes information based on accumulated data and responds to dynamic changes in events.

[0768] An "evacuation route" is a path that allows users to safely evacuate to their destination during a disaster, and it is constantly updated based on disaster information and traffic information.

[0769] A "user terminal" is a device used to receive evacuation route guidance and various other information, and usually refers to a smartphone or tablet.

[0770] "Relief supplies" refer to food, beverages, medicines, and daily necessities that evacuees will need after a disaster, and should be provided promptly as needed.

[0771] "Voice and facial expression analysis" is a technology that evaluates a user's psychological state based on their voice tone, speed, and facial expressions, and obtains information to alleviate the user's anxiety and tension.

[0772] The system of this invention provides comprehensive evacuation support to ensure the safe evacuation of users during disasters. The server uses location information received via a location information acquisition device to pinpoint the user's exact location. It also integrates disaster information, traffic information, and weather information obtained from multiple sources in real time and analyzes this information. Based on the analysis results, the server uses artificial intelligence to generate an optimal evacuation route that can be dynamically updated, taking into account the progress of the disaster and traffic congestion.

[0773] The generated evacuation routes are provided to the user's device as visual and auditory guidance. This includes smartphones and tablets, allowing users to receive real-time, reassuring route guidance. This guidance is designed to enhance user confidence by adjusting tone and information based on the results of evaluating the user's psychological state using voice and facial expression analysis technology. Specifically, tools such as the Affectiva SDK are used for voice analysis.

[0774] After the evacuation is complete, the system collects the necessary relief supplies from users via their terminals and sends them to a server. Based on this information, the server matches them with relief providers and can quickly provide the necessary supplies.

[0775] As a concrete example, imagine a scenario where an earthquake occurs while a user is in a shopping mall, and the user's terminal provides a gentle voice instructing, "Please proceed calmly. It is safe to go up these stairs." This system plays a role in alleviating user anxiety by providing dynamic evacuation instructions using a generative AI model. The system generates optimal instructions for the user based on a prompt such as, "Analyze the voice tone and speed, and generate instructions that will calm the user."

[0776] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0777] Step 1:

[0778] The server acquires the user's current location information received from a location information acquisition device. The input is location data transmitted from the user's smartphone, which the server receives. The output is data that precisely identifies the user's location. This makes it possible to track the user's location in real time.

[0779] Step 2:

[0780] The server integrates disaster information, traffic information, and weather information obtained from multiple sources. The input consists of the latest information from various databases. The server analyzes this data and generates detailed information on disaster situations, traffic congestion, and weather conditions as output. Data processing includes accessing databases and cross-referencing information.

[0781] Step 3:

[0782] The server uses generative artificial intelligence to generate dynamically updateable evacuation routes, taking into account disaster conditions and traffic information. The input is pre-analyzed integrated information. The server uses a generative AI model to calculate the optimal evacuation route. The output provides users with safe and timely evacuation route information.

[0783] Step 4:

[0784] The terminal visually and audibly guides the user with evacuation route information received from the server. The input is route data transmitted from the server. The terminal uses this data to launch map applications and voice guides to direct the user. The output is route guidance provided to the user.

[0785] Step 5:

[0786] The terminal uses voice and facial expression analysis to assess the user's psychological state and adjusts the tone and details of the guidance accordingly. Input consists of audio and video data acquired by the microphone and camera. The terminal uses an analysis engine to analyze the user's tone and facial expressions based on the prompt message, "Analyze the voice tone and speed, and generate guidance that will calm the user." The output is customized route guidance.

[0787] Step 6:

[0788] After evacuation, the terminal collects information about the relief supplies the user needs and sends it to the server. Inputs include questionnaires and selected needs information from the user. The terminal aggregates this information, creates a list of relief supplies, and sends it to the server. The output is information about the support needs.

[0789] Step 7:

[0790] The server matches users with aid providers based on collected information about the necessary supplies. The input is user-submitted information about their aid needs. The server searches its database for available supplies and services to identify appropriate providers. The output is instructions sent to aid providers to ensure the supplies and services are delivered quickly.

[0791] 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.

[0792] 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.

[0793] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0794] 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.

[0795] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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."

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] The following is further disclosed regarding the embodiments described above.

[0813] (Claim 1)

[0814] A means for determining the user's location based on current location information received from a location information acquisition device,

[0815] A means of integrating disaster information, traffic information, and weather information obtained from multiple data sources to analyze the optimal evacuation route,

[0816] A means for generating dynamically updateable emergency evacuation routes based on analyzed information using generative artificial intelligence,

[0817] Means for visually and audibly guiding the user terminal along the evacuation route,

[0818] A means of collecting the necessary relief supplies from users after evacuation and matching them with support providers based on those supplies,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, wherein the collection of the aforementioned relief supplies is carried out based on a guide displayed on the user terminal.

[0822] (Claim 3)

[0823] The system according to claim 1, characterized in that the integration of the aforementioned data is performed based on real-time predictive analysis, and the routes are updated immediately in accordance with the progression of the disaster.

[0824] "Example 1"

[0825] (Claim 1)

[0826] A means of determining the user's current location using a means of acquiring location information,

[0827] A means of integrating disaster-related information, transportation information, and weather information obtained from multiple sources to analyze safe evacuation routes,

[0828] A means for generating dynamically updateable evacuation routes based on analyzed information using generative AI technology,

[0829] Means for visually and audibly guiding the user's information device to the evacuation route,

[0830] A means of collecting the relief supplies requested by users after the evacuation is complete, and matching them with providers based on that data,

[0831] A system that includes this.

[0832] (Claim 2)

[0833] The system according to claim 1, wherein the means for collecting the relief supplies is carried out based on instructions displayed on the user's information device.

[0834] (Claim 3)

[0835] The system according to claim 1, characterized in that the means for integrating the aforementioned information is performed based on real-time predictive analysis, and the routes are updated rapidly in accordance with the development of the disaster.

[0836] "Application Example 1"

[0837] (Claim 1)

[0838] A means for determining the user's location based on current location information received from a location information acquisition device,

[0839] A means of integrating disaster-related information, traffic-related information, and weather-related information obtained from multiple data sources to analyze the optimal evacuation route,

[0840] A means for generating dynamically updateable emergency evacuation routes based on analyzed information using generative artificial intelligence,

[0841] A means for providing visual and auditory guidance of the evacuation route to the user terminal, and for providing guidance utilizing speech synthesis technology,

[0842] A method for collecting the support supplies that users need after evacuation through a questionnaire and matching them with support providers based on that information,

[0843] A system that includes this.

[0844] (Claim 2)

[0845] The system according to claim 1, wherein the collection of the aforementioned relief supplies is carried out based on a visual guide displayed on the user terminal and includes real-time data processing.

[0846] (Claim 3)

[0847] The system according to claim 1, characterized in that the integration of the aforementioned data is performed based on real-time predictive analysis, and routes are updated immediately in accordance with the progression of the disaster, thereby strengthening disaster response in a smart city environment.

[0848] "Example 2 of combining an emotion engine"

[0849] (Claim 1)

[0850] A means for determining the user's location based on current location information received from a location information acquisition device,

[0851] A means of integrating weather event information, movement information, and environmental condition information obtained from multiple sources to analyze the optimal evacuation route,

[0852] A means for generating dynamically updateable emergency evacuation routes based on analyzed information using bio-inventive intelligence,

[0853] A means for adjusting evacuation guidance based on an emotion recognition device that analyzes the user's voice and facial expressions and evaluates their psychological state,

[0854] Means for visually and audibly guiding the user terminal to the evacuation route,

[0855] A means of collecting necessary supplies for users after evacuation and acting as an intermediary between them and support providers,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, wherein the collection of the aforementioned support items is carried out based on guidelines displayed on the user's terminal.

[0859] (Claim 3)

[0860] The system according to claim 1, characterized in that the integration of the aforementioned information is performed based on continuous situation prediction analysis, and the route is updated immediately in accordance with the progression of meteorological events.

[0861] "Application example 2 when combining with an emotional engine"

[0862] (Claim 1)

[0863] A means for determining the user's location based on current location information received from a location information acquisition device,

[0864] A means of integrating disaster information, traffic information, and weather information obtained from multiple sources to analyze the optimal evacuation route,

[0865] A means for generating dynamically updateable emergency evacuation routes based on analyzed information using generative artificial intelligence,

[0866] Means for visually and audibly guiding the user terminal along the evacuation route,

[0867] A means of collecting the necessary relief supplies from users after evacuation and matching them with support providers based on that information,

[0868] A means of evaluating the user's psychological state through voice and facial expression analysis, and adjusting the tone and information of the guidance based on that evaluation,

[0869] A system that includes this.

[0870] (Claim 2)

[0871] The system according to claim 1, wherein the collection of the aforementioned support supplies is carried out based on a support needs survey displayed on the user's terminal.

[0872] (Claim 3)

[0873] The system according to claim 1, characterized in that the integration of the aforementioned data is performed based on real-time predictive analysis, the route is updated immediately in accordance with the progression of the disaster, and guidance is provided that takes into account the psychological state of the user. [Explanation of Symbols]

[0874] 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. A means for determining the user's location based on current location information received from a location information acquisition device, A means of integrating disaster-related information, traffic-related information, and weather-related information obtained from multiple data sources to analyze the optimal evacuation route, A means for generating dynamically updateable emergency evacuation routes based on analyzed information using generative artificial intelligence, A means for providing visual and auditory guidance of the evacuation route to the user terminal, and for providing guidance utilizing speech synthesis technology, A method for collecting the support supplies that users need after evacuation through a questionnaire and matching them with support providers based on that information, A system that includes this.

2. The system according to claim 1, wherein the collection of the aforementioned relief supplies is carried out based on a visual guide displayed on the user terminal, and includes real-time data processing.

3. The system according to claim 1, characterized in that the integration of the aforementioned data is performed based on real-time predictive analysis, and routes are updated immediately in accordance with the progression of the disaster, thereby strengthening disaster response in a smart city environment.

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