system

Abstract

We provide the system. [Solution] Means of acquiring location information, traffic information, weather information, disaster information, etc. An integration method that centrally gathers various acquired information and prepares it in a format that can be analyzed, A generation means for generating the optimal evacuation route based on integrated data, A guidance means that presents the generated evacuation route to the user through audio or visual information, A means of updating the generated routes in real time in response to changes in the environment and circumstances, and making appropriate changes as needed. 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 performed by at least one processor, 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】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 Selecting an evacuation route during a disaster may be difficult due to panic, lack of information, congestion of communication infrastructure, etc. There is also a problem that it is difficult to provide appropriate information to travelers in unfamiliar areas or people who need rapid assistance. In such a situation, it is important to judge and guide a route that allows for rapid and safe evacuation, but the current system does not sufficiently solve this problem. 【Means for Solving the Problems】 【0005】 This invention provides a system that integrates real-time location information, traffic information, weather information, and disaster information collected by an acquisition means using an integration means, and generates a safe and optimal evacuation route using a generation means. Furthermore, it provides a system that guides the user through the generated route in an easy-to-understand manner using voice and visuals by a guidance means, and updates the route based on the latest information at all times using an update means. As a result, the user is always guided to the optimal evacuation route, enabling rapid and safe evacuation during disasters. 【0006】 "Means of acquisition" refers to devices or processes for collecting location information, traffic information, weather information, disaster information, etc. 【0007】 An "integration means" is a device or process that can centrally gather various acquired information and arrange it into an analyzable format. 【0008】 "Generation means" refers to a device or process for generating the optimal evacuation route based on integrated data. 【0009】 "Guidance means" refers to a device or process for presenting a generated evacuation route to a user through audio or visual information. 【0010】 A "renewal mechanism" is a device or process for re-evaluating the generated paths in real time in response to changes in the environment or circumstances, and for making appropriate changes as needed. [Brief explanation of the drawing] 【0011】 [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 the data processing device and 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] 【0012】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0013】 First, let's explain the terminology used in the following explanation. 【0014】 In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0015】 In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0016】 In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0017】 In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F manages communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc. 【0018】 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." 【0019】 [First Embodiment] 【0020】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0021】 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. 【0022】 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). 【0023】 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. 【0024】 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. 【0025】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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. 【0026】 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. 【0027】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0028】 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. 【0029】 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. 【0030】 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. 【0031】 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". 【0032】 The present invention is implemented by a system including acquisition means, integration means, generation means, guidance means, and update means. These means work together to provide users with a safe and efficient evacuation route in the event of a disaster. 【0033】 Program processing and execution 【0034】 Implementation of acquisition methods 【0035】 The server collects real-time location, traffic, weather, and disaster information through external APIs and sensor networks. This information is stored in a database and used for subsequent processing. For example, if an earthquake occurs in a certain area, the server immediately retrieves earthquake information and maps it. 【0036】 Implementation of integration measures 【0037】 The server integrates the diverse information it acquires, organizing all the data points to create a single, unified information set. This integrated information is then used in the optimization process for the next generation method. 【0038】 Implementation of the generation means 【0039】 The server generates the optimal evacuation route from the user's current location based on integrated information. The generated evacuation route takes into account time efficiency, safety of movement, and environmental conditions. For example, if flooding is predicted in an area due to heavy rain, the generation method will prioritize routes that pass through higher ground. 【0040】 Implementation of guidance methods 【0041】 The terminal guides the user along a generated evacuation route. Route guidance is provided using both voice guidance and visual map displays. Users can intuitively follow the instructions and begin their evacuation. 【0042】 Implementation of update methods 【0043】 The server monitors real-time updated information and updates evacuation routes, taking into account the progression of the disaster and changes in public infrastructure. This ensures that users are always provided with evacuation information that reflects the latest situation. 【0044】 Specific example 【0045】 This example illustrates a scenario where an earthquake occurs in a specific area and evacuation becomes necessary. The user launches the app on their smartphone, and the device instantly determines their current location. The server obtains information from the Japan Meteorological Agency and transportation companies, and based on this, generates a safe and rapid evacuation route. The device provides voice guidance along this route, giving specific instructions such as, "It will take 10 minutes to reach the nearest evacuation center. Please proceed along the nearest road that is currently passable." Even if road closure information is updated during the evacuation, the server quickly recalculates the route and guides the user to an appropriate alternative route. This allows the user to complete the evacuation safely without panicking. 【0046】 The following describes the processing flow. 【0047】 Step 1: 【0048】 The server acquires user location information, traffic conditions, weather conditions, and disaster information in real time from external APIs and sensor networks. The acquired data is stored in a database for analysis. 【0049】 Step 2: 【0050】 The device obtains the current location information using the user's GPS function. The location information is automatically updated when the user launches the app. 【0051】 Step 3: 【0052】 The server integrates the acquired data to create a centralized information set that includes information on traffic closures, weather changes, and safe routes. 【0053】 Step 4: 【0054】 The server uses a generation method to calculate the optimal evacuation route based on integrated data. Factors such as safety and travel time are taken into consideration when determining the route. 【0055】 Step 5: 【0056】 The terminal guides the user through the generated evacuation route using both voice and visual aids. Voice guidance allows the user to receive specific instructions for action. 【0057】 Step 6: 【0058】 The server monitors the progress of the disaster and real-time updates of traffic information, re-evaluates routes in response to new risks and changes in information, and updates routes as needed. 【0059】 Step 7: 【0060】 The user receives updated route guidance through the device and continues their safe evacuation by following the instructions. In some cases, the device will recalculate the route and provide a voice-over. 【0061】 Step 8: 【0062】 After evacuation is complete, users report the completion of their evacuation using a terminal and input their needs for necessary relief supplies and medical care. The server records this information and matches it with the necessary support. 【0063】 (Example 1) 【0064】 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." 【0065】 Providing rapid and safe evacuation routes during disasters is a challenge. In particular, there is a need for a system that can always present the optimal route and ensure the safe evacuation of users, especially as information changes in real time. Currently, there is a delay in updating information before it is applied to evacuation routes, which can compromise safety. 【0066】 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. 【0067】 In this invention, the server includes means for acquiring information from external information sources and storing it in a database, means for integrating information acquired from multiple information sources to create a consistent set of information, and means for generating evacuation routes based on the integrated information. This makes it possible to provide a fast and safe evacuation route based on the latest information at all times. 【0068】 "Acquisition means" refers to devices or methods for acquiring information from external sources and storing it in a database. 【0069】 "Integration" refers to the process of organizing information obtained from multiple sources to create a consistent set of information. 【0070】 A "generation means" refers to a device or method that creates new, safe, and efficient evacuation routes based on integrated information. 【0071】 A "guidance means" refers to a device or method that displays the generated evacuation route to the user using audio and visual information, thereby assisting movement. 【0072】 An "update mechanism" is a process that constantly monitors the latest information in situations where information changes in real time, and recalculates and provides the route as needed. 【0073】 This invention aims to construct a system for providing safe and efficient evacuation routes in the event of a disaster. The system comprises five main functions: external information management, integrated analysis, route generation, user guidance, and information updating. 【0074】 The server acquires real-time location, traffic, weather, and disaster information using external APIs and sensor networks. The server manages this data in a database, preparing it for subsequent data processing. The hardware used includes a database server and communication modules. The software used includes libraries for API access and data analysis tools. 【0075】 The server integrates the acquired information to create a consistent set of information. This set of information forms the basis for evacuation route generation, which is described below. The generated evacuation routes take into account user safety and efficiency. This allows users to utilize the optimal route from their current location to their evacuation destination. 【0076】 The device provides the user with generated routes as voice and visual guidance. Users can intuitively receive navigation using a device such as a smartphone. The guidance includes features such as voice guidance and real-time map display. 【0077】 The server constantly monitors for the latest information and updates evacuation routes as needed, including disaster conditions and road closures. This feature ensures that users can always access the safest route. 【0078】 As a concrete example of its use, in the event of an earthquake, the user launches the app on their device. The server immediately generates a safe evacuation route based on the latest weather information and traffic data, and the device provides voice guidance such as, "It will take 10 minutes to reach the nearest evacuation center. Please proceed along the nearest road that is currently passable." Even if roads are blocked along the way, the server immediately calculates a new route and provides instructions to the user. 【0079】 An example of a prompt message is: "Please describe the specific processing steps for the evacuation route guidance system in the event of a disaster. These steps include acquisition, integration, generation, guidance, and update methods." 【0080】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0081】 Step 1: 【0082】 The server collects data from external APIs and sensor networks. Its inputs include location information, traffic information, weather information, and disaster information. This data is received from each information source and stored in a database. Specifically, the server makes API calls, receives information in JSON format, and stores it in a structured database. 【0083】 Step 2: 【0084】 The server integrates the information stored in the database. It uses information from multiple data sources as input. By organizing data points and filtering out unnecessary data, it creates a consistent set of information. Specifically, the server eliminates duplicate location information and prioritizes the integration of the most recent data. 【0085】 Step 3: 【0086】 The server generates evacuation routes based on integrated information. It takes the user's current location and an integrated information set as input. Data processing uses a route generation algorithm to calculate the shortest and safest route. Specifically, it performs optimized route searching, taking into account terrain and traffic information. 【0087】 Step 4: 【0088】 The terminal guides the user along the generated evacuation route. It uses evacuation route information received from the server as input. Output includes voice guidance and real-time map displays. Specifically, the terminal provides voice commands such as "Turn left at the next intersection" and indicates the route with arrows on the screen. 【0089】 Step 5: 【0090】 The server monitors real-time changes in information and recalculates routes as needed. It takes the latest disaster information and traffic conditions as input. Based on this, the server processes the data and generates new routes. Specifically, if road closure information is updated, it calculates a new detour route and sends it to the terminal. 【0091】 (Application Example 1) 【0092】 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." 【0093】 In modern society, rapid and safe evacuation is essential during disasters, but conventional systems struggle to integrate information in real time and generate optimal evacuation routes. Furthermore, they are unable to keep up with rapidly changing disaster information, making it difficult to provide accurate instructions to users. 【0094】 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. 【0095】 In this invention, the server includes data collection means, information integration means, and route generation means. This makes it possible to aggregate diverse data in real time during a disaster and continuously generate the optimal evacuation route. Furthermore, it is possible to support rapid and safe evacuation by providing intuitive instructions to the user using voice and visual information. 【0096】 "Data acquisition means" refers to a device or process for acquiring real-time information from external data sources or sensors. 【0097】 An "information integration tool" is a means for integrating multiple acquired data and creating a single, organized set of information. 【0098】 A "route generation means" is a means for calculating and generating the optimal travel route based on integrated information. 【0099】 "User guidance methods" refer to means of providing information to users using audio and visuals based on generated information. 【0100】 An "information update method" is a means of monitoring acquired information in real time and updating the information and travel routes in accordance with changing circumstances. 【0101】 The system for realizing this invention will be implemented as an application using a smartphone or mobile device. This application will support rapid and safe evacuation during disasters through the processes described below. 【0102】 First, the device obtains the user's current location using GPS functionality through data collection means. It also obtains weather, traffic, and disaster information in real time through external APIs and cloud services. This information is transmitted to a server and integrated using information integration means. 【0103】 Next, the server uses a route generation mechanism to generate the optimal evacuation route for the user based on the information organized by the information integration mechanism. This route generation utilizes an AI algorithm, and by linking with a geographic information system (GIS), for example, it calculates the optimal route according to the type and progression of the disaster. 【0104】 Subsequently, the terminal guides the user along the evacuation route through voice and visual means. A text-to-speech API is used for voice guidance, and a map display API is used for visual guidance. This allows users to intuitively follow the instructions. 【0105】 The server uses an information update mechanism to recalculate evacuation routes in real time based on constantly changing disaster information, providing users with the latest information. In this way, users can evacuate with peace of mind. 【0106】 As a concrete example, consider the use of the app when heavy rain is expected. When a user launches the app, it checks their current location and generates a safe route that avoids areas where flooding is predicted. Detailed instructions are provided via voice guidance, such as "Turn right at the next intersection and go straight," to encourage the user to evacuate appropriately. 【0107】 An example of a prompt statement is: "When evacuation is necessary in a specific area, consider how to provide residents with real-time information and effectively support their evacuation." 【0108】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0109】 Step 1: 【0110】 The device initiates the data collection process. It enables GPS functionality on the device to obtain the user's current location. Simultaneously, it uses external APIs to acquire weather, traffic, and disaster information in real time. Inputs are the device's location information and environmental data from external APIs, and the output is an integrated set of information containing these. 【0111】 Step 2: 【0112】 The server performs the information integration process. It receives sensor information and external API data sent from terminals and stores them in a database. It standardizes various data formats and creates a unified dataset. The input is sensor information and external data, and the output is a dataset that integrates them. 【0113】 Step 3: 【0114】 The server performs the route generation process. Based on the integrated dataset, it uses an AI algorithm to calculate the optimal evacuation route. For example, a generative AI model is used to select a safe and efficient route. The input is the integrated dataset, and the output is the optimized evacuation route. 【0115】 Step 4: 【0116】 The terminal initiates the user guidance process. Based on the generated evacuation route, it guides the user using audio and visual information. The audio guide utilizes text-to-speech functionality, and the route is visually presented using a map display. The input is the optimal evacuation route, and the output is the audio and visual instructions provided to the user. 【0117】 Step 5: 【0118】 The server continuously performs the information update process. It acquires new information in real time and updates the evacuation route if it needs to be recalculated. This ensures that users are always provided with guidance based on the latest information. The input is new environmental data, and the output is the updated evacuation route. 【0119】 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. 【0120】 The present invention is implemented by a system that includes acquisition means, integration means, generation means, guidance means, and update means, as well as an emotion engine that recognizes the user's emotions. These means and the emotion engine work together to reduce the psychological burden on the user during a disaster while supporting safe and effective evacuation. 【0121】 Program processing and execution 【0122】 Implementation of acquisition methods 【0123】 The server collects user location information, traffic conditions, weather information, and disaster information in real time through external APIs and sensor networks. This data serves as foundational information for accurately understanding disaster situations. 【0124】 Identifying user location information 【0125】 The device uses the GPS function of the user's smartphone to accurately obtain their current location, enabling location tracking even during disasters. 【0126】 Implementation of the Emotion Engine 【0127】 The device incorporates an emotion engine that recognizes and analyzes the user's emotions through voice and visual feedback. This allows for real-time monitoring of the user's emotional state, such as fear or anxiety. 【0128】 Implementation of the generation means 【0129】 The server generates an optimal route that takes stress reduction into consideration, based on integrated information and user sentiment data. The generated route takes safety and minimal psychological burden into account. 【0130】 Implementation of guidance methods 【0131】 The device guides the user along a generated evacuation route in a manner adjusted based on emotional data. The voice tone and message content are modified as needed to help the user maintain an emotionally calm state. 【0132】 Implementation of update methods 【0133】 The server recalculates the route in response to changes in circumstances and the acquisition of new information, and provides more refined guidance based on the analysis results from the emotion engine. 【0134】 Specific example 【0135】 Let's take the example of an earthquake occurring and evacuation being necessary. The user launches the app on their smartphone, and the device confirms their current location. At this time, the device's emotion engine recognizes anxiety from the user's voice. Based on the collected data and emotional state, the server prioritizes a route that provides a sense of security and delivers a route mission to the device. The guidance method calms the user by guiding them in a gentle voice, saying, "It is important to act calmly. We will now begin guiding you to the nearest evacuation center." If there is new closure information along the route, the server immediately updates the route and provides guidance again, thereby reducing the user's anxiety and supporting the safe completion of evacuation. 【0136】 The following describes the processing flow. 【0137】 Step 1: 【0138】 The server utilizes external APIs and sensor networks to collect location, traffic, weather, and disaster information in real time. This allows for the accumulation of information based on the latest conditions. 【0139】 Step 2: 【0140】 The terminal obtains GPS information from the user's device to accurately determine their current location. This information is then used to generate evacuation routes. 【0141】 Step 3: 【0142】 The emotion engine built into the device analyzes the user's voice data to recognize their psychological state. The recognition results identify emotions such as anxiety and fear and send them to a database. 【0143】 Step 4: 【0144】 The server uses integration to consolidate all acquired information and constructs a comprehensive dataset that takes into account the user's current location and psychological state. 【0145】 Step 5: 【0146】 The server uses a generation mechanism to create the optimal evacuation route based on integrated data. This route is intended to reduce not only safety but also the emotional burden on the user. 【0147】 Step 6: 【0148】 The device uses guidance to present the user with evacuation routes generated in an appropriate tone and content. Based on emotional data, the voice guide is adjusted to help the user relax. 【0149】 Step 7: 【0150】 The server receives new information in real time and understands changes in the situation. It updates generated routes as needed and adjusts guidance methods based on data from the emotion engine. 【0151】 Step 8: 【0152】 Users feel reassured by receiving the latest route guidance from their devices and safely reach their designated evacuation location. After evacuation is complete, users report any assistance they need, and the server uses this information to match them with appropriate support. 【0153】 (Example 2) 【0154】 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". 【0155】 In the event of a disaster, support is needed to ensure that evacuees can evacuate safely and quickly. This requires a system that can respond to the situation in real time while reducing the psychological burden on evacuees. However, conventional technologies fail to adequately consider the emotional state of individual evacuees when generating and presenting evacuation routes, resulting in a lack of systems that provide safe and psychologically supportive assistance. 【0156】 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. 【0157】 In this invention, the server includes means for acquiring information, means for integrating information, means for generating routes, means for providing guidance, means for updating information, and means for recognizing emotions. This enables the generation of evacuation routes in real time under disaster conditions and provides safe and psychologically less burdensome guidance that takes into account the emotional state of evacuees. 【0158】 "Means of acquiring information" refers to devices or functions that collect data from external sources and make it available for use within a system. 【0159】 "Means for integrating information" refers to devices or functions that analyze various acquired data, correlate them, and compile them into consistent information. 【0160】 "Means for generating routes" refers to devices or functions that calculate and present the optimal travel route to a destination based on integrated information. 【0161】 "Means of providing guidance" refers to devices or functions that communicate generated routes and related information to users via voice or visual means. 【0162】 "Means of updating information" refers to devices or functions that reacquire data in real time and modify its content in order to keep the collected information and calculated paths up-to-date in response to changes in circumstances. 【0163】 "Means of recognizing emotions" refer to devices or functions that analyze emotions from the user's voice, facial expressions, etc., in order to understand the user's psychological state. 【0164】 This invention is a system aimed at providing evacuation support during disasters. Specifically, it has a configuration that acquires and integrates information, generates the optimal evacuation route in real time, and provides guidance to the user, thereby reducing psychological burden. 【0165】 The server integrates information based on location data, traffic conditions, weather conditions, and disaster information obtained from external sources. Specifically, it aggregates data from external APIs such as those of the Japan Meteorological Agency and traffic information centers and stores it in a central database. When integrating the information, a generative AI model is used to perform analysis tailored to the disaster situation. 【0166】 The device uses the user's smartphone's GPS function to obtain their current location. Furthermore, the device is equipped with an emotion recognition engine that analyzes the user's emotional state at that moment based on their voice input and camera footage. This emotional data is sent to a server and used to generate evacuation routes. 【0167】 Using a generative AI model, the server generates the optimal evacuation route in real time based on integrated information and sentiment data. This route ensures the user's safety while minimizing psychological burden, and is then transmitted to the terminal. 【0168】 The user receives instructions from their device. These instructions are presented in both audio and visual formats and are adjusted according to the user's emotional state. This allows the user to evacuate calmly and accurately. 【0169】 As a concrete example, let's consider a situation where a heavy rain warning has been issued for the user's area of ​​residence. The user launches the app and enters a prompt such as, "A heavy rain warning has been issued for my area. Do I need to evacuate?", and receives guidance on appropriate evacuation actions. Based on the information received, the server generates a route to the nearest safe evacuation shelter and provides the user with directions through their device. 【0170】 In this way, this system supports the safe and secure evacuation of users during disasters and aims to reduce their psychological burden. 【0171】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0172】 Step 1: 【0173】 The server obtains location information, traffic conditions, weather information, disaster information, and other data from external sources. This includes sending requests to weather information APIs and traffic information APIs and receiving the data obtained as responses. The input is various real-time data obtained from the APIs, and the output is information converted into a format that is stored in an integrated database. This process involves data format conversion and timely data updates. 【0174】 Step 2: 【0175】 The device obtains its current location using the user's smartphone's GPS function. This involves accessing GPS information through application permissions and obtaining location data with adjusted accuracy. The input is the smartphone's positioning data, and the output is standardized location information sent to the server. This process includes calculating the average value from multiple location detections. 【0176】 Step 3: 【0177】 The device uses an emotion recognition engine to analyze the user's voice data and camera footage to identify their current emotional state. This involves extracting emotional parameters through voice sample acquisition and video analysis. The input is the user's voice and video data, and the output is the identified emotional state data. This process includes voice pattern analysis and emotion determination using an AI learning model. 【0178】 Step 4: 【0179】 The server uses the latest data and sentiment data obtained from an integrated database to generate the optimal evacuation route using a generative AI model. This involves information analysis and calculating the safest and least psychologically stressful route from multiple route options. Inputs include location information, traffic information, weather information, and sentiment data, while output is detailed information about the evacuation route. This process utilizes an optimization algorithm that leverages the learning results of the AI ​​model. 【0180】 Step 5: 【0181】 The terminal provides the user with guidance in the form of audio and visual information based on route information received from the server. Guidance is generated using a speech synthesis engine, and a route map is displayed on the screen. The input is the generated evacuation route information, and the output is a tailored guidance message for the user. This process includes adjusting the voice tone according to the user's emotions. 【0182】 Step 6: 【0183】 The server continuously acquires new information and updates evacuation routes in response to changing circumstances. This includes receiving new data in real time and recalculating existing evacuation routes. The input is the latest information dataset, and the output is updated evacuation route information. This process includes route recalculation for sealed-off areas and newly designated hazard zones. 【0184】 (Application Example 2) 【0185】 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". 【0186】 In times of disaster, flexible guidance that takes into account individual emotional states and real-time changing circumstances is necessary for users to evacuate safely and quickly. However, conventional systems only provide fixed guidance without considering emotional states, which has the problem of failing to alleviate the psychological burden on users. 【0187】 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. 【0188】 In this invention, the server includes emotion recognition means, real-time information acquisition means, and digital map generation means. This makes it possible to generate evacuation routes in real time according to the user's emotional state and provide adaptive guidance. 【0189】 "Acquisition methods" refer to methods for collecting necessary data in real time from external information sources and sensors. 【0190】 An "integration method" is a means of integrating diverse data acquired and transforming it into information that is useful to the user. 【0191】 A "generation method" is used to create appropriate evacuation routes and instructions based on integrated information. 【0192】 "Guidance means" refers to methods of conveying generated information to the user, providing guidance using audio or visual information. 【0193】 "Update mechanisms" refer to methods for revising existing information in response to changes in circumstances or the acquisition of new data, thereby providing the latest instructions. 【0194】 "Emotion recognition means" are devices used to analyze a user's emotional state through audio and visual feedback. 【0195】 A "real-time information acquisition method" is a means of quickly acquiring various types of information at the present time and reflecting them in the system. 【0196】 A "digital map generation method" is a system that generates digital maps using the latest geographic information and uses them for route guidance. 【0197】 "Flexible guidance adjustment methods based on diverse states" refers to methods that change the content of guidance according to the user's emotional state and circumstances, in order to provide optimal information. 【0198】 The system implementing this invention includes means for acquiring information, integrating information, generating information, providing guidance, updating information, recognizing emotions, acquiring real-time information, generating digital maps, and providing flexible guidance adjustment means based on various states. Through cooperation between the server, terminals, and users, it supports safe and effective evacuation. 【0199】 The server obtains weather and traffic information from external APIs and acquires the user's current location information using GPS from their smartphone. Furthermore, it analyzes the user's emotional state from their voice and facial expression data using emotion recognition technology. Voice analysis libraries such as EmotionAPI are used for emotion recognition. 【0200】 Based on the acquired information, the server generates a digital map and calculates appropriate evacuation routes using an AI model. The guidance for these generated routes is adjusted according to the user's emotional state. For example, if the user is deemed anxious, the device provides a reassuring message in a calm voice. The tone and content of the messages can be flexibly changed during the guidance process. 【0201】 Through real-time information acquisition, the server recalculates evacuation routes each time new information is obtained, providing users with the latest guidance. The aim is to make evacuations safer and smoother. 【0202】 Specific example: When a user launches the app on their smartphone during an evacuation drill, the server sends the optimal evacuation route based on their current location and the latest disaster information. Emotion recognition allows the app to display a message such as, "Please calm down, we will now begin guiding you to the nearest evacuation center," if the user appears to be losing their composure. 【0203】 An example of a prompt for a generative AI model would be, "If the user's emotional state is anxious, generate a reassuring guidance message." Based on this prompt, the model will provide an appropriate message. 【0204】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0205】 Step 1: 【0206】 The server uses external APIs to obtain weather and traffic information. This allows it to collect basic data for understanding disaster situations. It sends external API access requests as input and obtains weather and traffic data as output. Based on this data, it analyzes the current situation and proceeds to the next step. 【0207】 Step 2: 【0208】 The device obtains the user's current location using the GPS function of their smartphone. This allows the system to obtain the user's precise location information. The input is the signal from the smartphone's GPS sensor, and the output is the user's location coordinates. Based on this location information, the system proceeds to generate an evacuation route. 【0209】 Step 3: 【0210】 The device analyzes the user's voice data using emotion recognition to identify their emotional state. The user's voice input is fed into a voice analysis library such as EmotionAPI, and emotional state information is obtained as output. This allows for real-time monitoring of the user's psychological state. 【0211】 Step 4: 【0212】 The server integrates collected location information, external data, and the user's emotional state to generate the optimal evacuation route using a generative AI model. By using the integrated data as input and feeding that data into the generative AI model, it obtains a safe and psychologically less stressful evacuation route as output. 【0213】 Step 5: 【0214】 The terminal adjusts the generated evacuation route based on the user's emotional state and provides voice and visual guidance. Inputs are the generated evacuation route and emotional data, which are then used by speech synthesis software to generate messages. Outputs are visual information and voice guidance displayed to the user. 【0215】 Step 6: 【0216】 The server uses real-time information acquisition methods to detect new disaster information and changes in traffic conditions, and recalculates evacuation routes as needed. The input is new data, and existing routes are evaluated based on this data. The output is the updated route. Through this process, users are always guided to the optimal evacuation method. 【0217】 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. 【0218】 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. 【0219】 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. 【0220】 [Second Embodiment] 【0221】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0222】 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. 【0223】 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). 【0224】 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. 【0225】 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. 【0226】 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). 【0227】 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. 【0228】 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. 【0229】 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. 【0230】 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. 【0231】 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. 【0232】 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". 【0233】 The present invention is implemented by a system including acquisition means, integration means, generation means, guidance means, and update means. These means work together to provide users with a safe and efficient evacuation route in the event of a disaster. 【0234】 Program processing and execution 【0235】 Implementation of acquisition methods 【0236】 The server collects real-time location, traffic, weather, and disaster information through external APIs and sensor networks. This information is stored in a database and used for subsequent processing. For example, if an earthquake occurs in a certain area, the server immediately retrieves earthquake information and maps it. 【0237】 Implementation of integration measures 【0238】 The server integrates the diverse information it acquires, organizing all the data points to create a single, unified information set. This integrated information is then used in the optimization process for the next generation method. 【0239】 Implementation of the generation means 【0240】 The server generates the optimal evacuation route from the user's current location based on integrated information. The generated evacuation route takes into account time efficiency, safety of movement, and environmental conditions. For example, if flooding is predicted in an area due to heavy rain, the generation method will prioritize routes that pass through higher ground. 【0241】 Implementation of guidance methods 【0242】 The terminal guides the user along a generated evacuation route. Route guidance is provided using both voice guidance and visual map displays. Users can intuitively follow the instructions and begin their evacuation. 【0243】 Implementation of update methods 【0244】 The server monitors real-time updated information and updates evacuation routes, taking into account the progression of the disaster and changes in public infrastructure. This ensures that users are always provided with evacuation information that reflects the latest situation. 【0245】 Specific example 【0246】 This example illustrates a scenario where an earthquake occurs in a specific area and evacuation becomes necessary. The user launches the app on their smartphone, and the device instantly determines their current location. The server obtains information from the Japan Meteorological Agency and transportation companies, and based on this, generates a safe and rapid evacuation route. The device provides voice guidance along this route, giving specific instructions such as, "It will take 10 minutes to reach the nearest evacuation center. Please proceed along the nearest road that is currently passable." Even if road closure information is updated during the evacuation, the server quickly recalculates the route and guides the user to an appropriate alternative route. This allows the user to complete the evacuation safely without panicking. 【0247】 The following describes the processing flow. 【0248】 Step 1: 【0249】 The server acquires user location information, traffic conditions, weather conditions, and disaster information in real time from external APIs and sensor networks. The acquired data is stored in a database for analysis. 【0250】 Step 2: 【0251】 The device obtains the current location information using the user's GPS function. The location information is automatically updated when the user launches the app. 【0252】 Step 3: 【0253】 The server integrates the acquired data to create a centralized information set that includes information on traffic closures, weather changes, and safe routes. 【0254】 Step 4: 【0255】 The server uses a generation method to calculate the optimal evacuation route based on integrated data. Factors such as safety and travel time are taken into consideration when determining the route. 【0256】 Step 5: 【0257】 The terminal guides the user through the generated evacuation route using both voice and visual aids. Voice guidance allows the user to receive specific instructions for action. 【0258】 Step 6: 【0259】 The server monitors the progress of the disaster and real-time updates of traffic information, re-evaluates routes in response to new risks and changes in information, and updates routes as needed. 【0260】 Step 7: 【0261】 The user receives updated route guidance through the device and continues their safe evacuation by following the instructions. In some cases, the device will recalculate the route and provide a voice-over. 【0262】 Step 8: 【0263】 After evacuation is complete, users report the completion of their evacuation using a terminal and input their needs for necessary relief supplies and medical care. The server records this information and matches it with the necessary support. 【0264】 (Example 1) 【0265】 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". 【0266】 Providing rapid and safe evacuation routes during disasters is a challenge. In particular, there is a need for a system that can always present the optimal route and ensure the safe evacuation of users, especially as information changes in real time. Currently, there is a delay in updating information and applying it to evacuation routes, which can compromise safety. 【0267】 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. 【0268】 In this invention, the server includes means for acquiring information from external information sources and storing it in a database, means for integrating information acquired from multiple information sources to create a consistent set of information, and means for generating evacuation routes based on the integrated information. This makes it possible to provide a fast and safe evacuation route based on the latest information at all times. 【0269】 "Acquisition means" refers to devices or methods for acquiring information from external sources and storing it in a database. 【0270】 "Integration" refers to the process of organizing information obtained from multiple sources to create a consistent set of information. 【0271】 A "generation means" refers to a device or method that creates new, safe, and efficient evacuation routes based on integrated information. 【0272】 A "guidance means" refers to a device or method that displays the generated evacuation route to the user using audio and visual information, thereby assisting them in their movement. 【0273】 An "update mechanism" is a process that constantly monitors the latest information in situations where information changes in real time, and recalculates and provides the route as needed. 【0274】 This invention aims to construct a system for providing safe and efficient evacuation routes in the event of a disaster. The system comprises five main functions: external information management, integrated analysis, route generation, user guidance, and information updating. 【0275】 The server acquires real-time location, traffic, weather, and disaster information using external APIs and sensor networks. The server manages this data in a database, preparing it for subsequent data processing. The hardware used includes a database server and communication modules. The software used includes libraries for API access and data analysis tools. 【0276】 The server integrates the acquired information to create a consistent set of information. This set of information forms the basis for evacuation route generation, which is described below. The generated evacuation routes take into account user safety and efficiency. This allows users to utilize the optimal route from their current location to their evacuation destination. 【0277】 The device provides the user with generated routes as voice and visual guidance. Users can intuitively receive navigation using a device such as a smartphone. The guidance includes features such as voice guidance and real-time map display. 【0278】 The server constantly monitors for the latest information and updates evacuation routes as needed, including disaster conditions and road closures. This feature ensures that users can always access the safest route. 【0279】 As a concrete example of its use, in the event of an earthquake, the user launches the app on their device. The server immediately generates a safe evacuation route based on the latest weather information and traffic data, and the device provides voice guidance such as, "It will take 10 minutes to reach the nearest evacuation center. Please proceed along the nearest road that is currently passable." Even if roads are blocked along the way, the server immediately calculates a new route and provides instructions to the user. 【0280】 An example of a prompt message is: "Please describe the specific processing steps for the evacuation route guidance system in the event of a disaster. These steps include acquisition, integration, generation, guidance, and update methods." 【0281】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0282】 Step 1: 【0283】 The server collects data from external APIs and sensor networks. As input, it targets location information, traffic information, weather information, disaster information, etc. It receives these data from each information source and stores them in a database. As a specific operation, the server makes an API call, receives information in JSON format, and stores it in a structured database. 【0284】 Step 2: 【0285】 The server integrates the information stored in the database. As input, it uses information obtained from multiple data sources. By organizing data points and filtering out unnecessary data, it creates a consistent information set. Specifically, the server performs a process of excluding duplicate location information and prioritizing and integrating the latest data. 【0286】 Step 3: 【0287】 The server generates an evacuation route based on the integrated information. As input, it handles the user's current location and the integrated information set. In data processing, it uses a route generation algorithm to calculate the shortest and safest route. As a specific operation, it performs an optimized route search considering terrain information and traffic information. 【0288】 Step 4: 【0289】 The terminal guides the user through the generated evacuation route. As input, it uses the evacuation route information received from the server. As output, voice guidance and real-time map display are provided. As a specific operation, the terminal gives voice commands such as "Turn left at the next intersection" and shows the route with arrows on the screen. 【0290】 Step 5: 【0291】 The server monitors real-time changes in information and recalculates routes as needed. It takes the latest disaster information and traffic conditions as input. Based on this, the server processes the data and generates new routes. Specifically, if road closure information is updated, it calculates a new detour route and sends it to the terminal. 【0292】 (Application Example 1) 【0293】 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." 【0294】 In modern society, rapid and safe evacuation is essential during disasters, but conventional systems struggle to integrate information in real time and generate optimal evacuation routes. Furthermore, they are unable to keep up with rapidly changing disaster information, making it difficult to provide accurate instructions to users. 【0295】 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. 【0296】 In this invention, the server includes data collection means, information integration means, and route generation means. This makes it possible to aggregate diverse data in real time during a disaster and continuously generate the optimal evacuation route. Furthermore, it is possible to support rapid and safe evacuation by providing intuitive instructions to the user using voice and visual information. 【0297】 "Data acquisition means" refers to a device or process for acquiring real-time information from external data sources or sensors. 【0298】 An "information integration tool" is a means for integrating multiple acquired data and creating a single, organized set of information. 【0299】 A "route generation means" is a means for calculating and generating the optimal travel route based on integrated information. 【0300】 "User guidance methods" refer to means of providing information to users using audio and visuals based on generated information. 【0301】 An "information update method" is a means of monitoring acquired information in real time and updating the information and travel routes in accordance with changing circumstances. 【0302】 The system for realizing this invention will be implemented as an application using a smartphone or mobile device. This application will support rapid and safe evacuation during disasters through the processes described below. 【0303】 First, the device obtains the user's current location using GPS functionality through data collection means. It also obtains weather, traffic, and disaster information in real time through external APIs and cloud services. This information is transmitted to a server and integrated using information integration means. 【0304】 Next, the server uses a route generation mechanism to generate the optimal evacuation route for the user based on the information organized by the information integration mechanism. This route generation utilizes an AI algorithm, and by linking with a geographic information system (GIS), for example, it calculates the optimal route according to the type and progression of the disaster. 【0305】 Subsequently, the terminal guides the user along the evacuation route through voice and visual means. A text-to-speech API is used for voice guidance, and a map display API is used for visual guidance. This allows users to intuitively follow the instructions. 【0306】 The server uses an information update mechanism to recalculate evacuation routes in real time based on constantly changing disaster information, providing users with the latest information. In this way, users can evacuate with peace of mind. 【0307】 As a specific example, consider the use of the app when heavy rain is predicted. When the user launches the app, it checks the current location and generates a safe route that avoids areas where flooding is predicted. By providing detailed instructions such as "Turn right at the next intersection and go straight" through voice guidance, it prompts the user to take appropriate evacuation measures. 【0308】 As an example of a prompt sentence, "When evacuation is necessary in a specific area, consider how to provide real-time information to residents and effectively support evacuation." can be cited. 【0309】 The flow of the specific process in Application Example 1 will be described using FIG. 12. 【0310】 Step 1: 【0311】 The terminal starts the data collection process. It enables the GPS function on the terminal to obtain the user's current location. Additionally, it uses an external API to obtain weather, traffic, and disaster information in real time. The input is the terminal's location information and environmental data from the external API, and the output is an integrated information set including these. 【0312】 Step 2: 【0313】 The server performs the information integration process. It receives the sensor information and external API data sent from the terminal and saves them in the database. It standardizes various data formats to create a unified data set. The input is the sensor information and external data, and the output is the integrated data set. 【0314】 Step 3: 【0315】 The server conducts the route generation process. Based on the integrated data set, it uses an AI algorithm to calculate the optimal evacuation route. For example, it uses a generated AI model to select a safe and efficient route. The input is the integrated data set, and the output is the optimized evacuation route. 【0316】 Step 4: 【0317】 The terminal initiates the user guidance process. Based on the generated evacuation route, it guides the user using audio and visual information. The audio guide utilizes text-to-speech functionality, and the route is visually presented using a map display. The input is the optimal evacuation route, and the output is the audio and visual instructions provided to the user. 【0318】 Step 5: 【0319】 The server continuously performs the information update process. It acquires new information in real time and updates the evacuation route if it needs to be recalculated. This ensures that users are always provided with guidance based on the latest information. The input is new environmental data, and the output is the updated evacuation route. 【0320】 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. 【0321】 The present invention is implemented by a system that includes acquisition means, integration means, generation means, guidance means, and update means, as well as an emotion engine that recognizes the user's emotions. These means and the emotion engine work together to reduce the psychological burden on the user during a disaster while supporting safe and effective evacuation. 【0322】 Program processing and execution 【0323】 Implementation of acquisition methods 【0324】 The server collects user location information, traffic conditions, weather information, and disaster information in real time through external APIs and sensor networks. This data serves as foundational information for accurately understanding disaster situations. 【0325】 Identifying user location information 【0326】 The device uses the GPS function of the user's smartphone to accurately obtain their current location, enabling location tracking even during disasters. 【0327】 Implementation of the Emotion Engine 【0328】 The device incorporates an emotion engine that recognizes and analyzes the user's emotions through voice and visual feedback. This allows for real-time monitoring of the user's emotional state, such as fear or anxiety. 【0329】 Implementation of the generation means 【0330】 The server generates an optimal route that takes stress reduction into consideration, based on integrated information and user sentiment data. The generated route takes safety and minimal psychological burden into account. 【0331】 Implementation of guidance methods 【0332】 The device guides the user along a generated evacuation route in a manner adjusted based on emotional data. The voice tone and message content are modified as needed to help the user maintain an emotionally calm state. 【0333】 Implementation of update methods 【0334】 The server recalculates the route in response to changes in circumstances and the acquisition of new information, and provides more refined guidance based on the analysis results from the emotion engine. 【0335】 Specific example 【0336】 Let's take the example of an earthquake occurring and evacuation being necessary. The user launches the app on their smartphone, and the device confirms their current location. At this time, the device's emotion engine recognizes anxiety from the user's voice. Based on the collected data and emotional state, the server prioritizes a route that provides a sense of security and delivers a route mission to the device. The guidance method calms the user by guiding them in a gentle voice, saying, "It is important to act calmly. We will now begin guiding you to the nearest evacuation center." If there is new closure information along the route, the server immediately updates the route and provides guidance again, thereby reducing the user's anxiety and supporting the safe completion of evacuation. 【0337】 The following describes the processing flow. 【0338】 Step 1: 【0339】 The server utilizes external APIs and sensor networks to collect location, traffic, weather, and disaster information in real time. This allows for the accumulation of information based on the latest conditions. 【0340】 Step 2: 【0341】 The terminal obtains GPS information from the user's device to accurately determine their current location. This information is then used to generate evacuation routes. 【0342】 Step 3: 【0343】 The emotion engine built into the device analyzes the user's voice data to recognize their psychological state. The recognition results identify emotions such as anxiety and fear and send them to a database. 【0344】 Step 4: 【0345】 The server uses integration to consolidate all acquired information and constructs a comprehensive dataset that takes into account the user's current location and psychological state. 【0346】 Step 5: 【0347】 The server uses a generation mechanism to create the optimal evacuation route based on integrated data. This route is intended to reduce not only safety but also the emotional burden on the user. 【0348】 Step 6: 【0349】 The device uses guidance to present the user with evacuation routes generated in an appropriate tone and content. Based on emotional data, the voice guide is adjusted to help the user relax. 【0350】 Step 7: 【0351】 The server receives new information in real time and understands changes in the situation. It updates generated routes as needed and adjusts guidance methods based on data from the emotion engine. 【0352】 Step 8: 【0353】 Users feel reassured by receiving the latest route guidance from their devices and safely reach their designated evacuation location. After evacuation is complete, users report any assistance they need, and the server uses this information to match them with appropriate support. 【0354】 (Example 2) 【0355】 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". 【0356】 In the event of a disaster, support is needed to ensure that evacuees can evacuate safely and quickly. This requires a system that can respond to the situation in real time while reducing the psychological burden on evacuees. However, conventional technologies fail to adequately consider the emotional state of individual evacuees when generating and presenting evacuation routes, resulting in a lack of systems that provide safe and psychologically supportive assistance. 【0357】 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. 【0358】 In this invention, the server includes means for acquiring information, means for integrating information, means for generating routes, means for providing guidance, means for updating information, and means for recognizing emotions. This enables the generation of evacuation routes in real time under disaster conditions and provides safe and psychologically less burdensome guidance that takes into account the emotional state of evacuees. 【0359】 "Means of acquiring information" refers to devices or functions that collect data from external sources and make it available for use within a system. 【0360】 "Means for integrating information" refers to devices or functions that analyze various acquired data, correlate them, and compile them into consistent information. 【0361】 "Means for generating routes" refers to devices or functions that calculate and present the optimal travel route to a destination based on integrated information. 【0362】 "Means of providing guidance" refers to devices or functions that communicate generated routes and related information to users via voice or visual means. 【0363】 "Means of updating information" refers to devices or functions that reacquire data in real time and modify its content in order to keep the collected information and calculated paths up-to-date in response to changes in circumstances. 【0364】 "Means of recognizing emotions" refer to devices or functions that analyze emotions from the user's voice, facial expressions, etc., in order to understand the user's psychological state. 【0365】 This invention is a system aimed at providing evacuation support during disasters. Specifically, it has a configuration that acquires and integrates information, generates the optimal evacuation route in real time, and provides guidance to the user, thereby reducing psychological burden. 【0366】 The server integrates information based on location data, traffic conditions, weather conditions, and disaster information obtained from external sources. Specifically, it aggregates data from external APIs such as those of the Japan Meteorological Agency and traffic information centers and stores it in a central database. When integrating the information, a generative AI model is used to perform analysis tailored to the disaster situation. 【0367】 The device uses the user's smartphone's GPS function to obtain their current location. Furthermore, the device is equipped with an emotion recognition engine that analyzes the user's emotional state at that moment based on their voice input and camera footage. This emotional data is sent to a server and used to generate evacuation routes. 【0368】 Using a generative AI model, the server generates the optimal evacuation route in real time based on integrated information and sentiment data. This route ensures the user's safety while minimizing psychological burden, and is then transmitted to the terminal. 【0369】 The user receives instructions from their device. These instructions are presented in both audio and visual formats and are adjusted according to the user's emotional state. This allows the user to evacuate calmly and accurately. 【0370】 As a concrete example, let's consider a situation where a heavy rain warning has been issued for the user's area of ​​residence. The user launches the app and enters a prompt such as, "A heavy rain warning has been issued for my area. Do I need to evacuate?", and receives guidance on appropriate evacuation actions. Based on the information received, the server generates a route to the nearest safe evacuation shelter and provides the user with directions through their device. 【0371】 In this way, this system supports the safe and secure evacuation of users during disasters and aims to reduce their psychological burden. 【0372】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0373】 Step 1: 【0374】 The server obtains location information, traffic conditions, weather information, disaster information, and other data from external sources. This includes sending requests to weather information APIs and traffic information APIs and receiving the data obtained as responses. The input is various real-time data obtained from the APIs, and the output is information converted into a format that is stored in an integrated database. This process involves data format conversion and timely data updates. 【0375】 Step 2: 【0376】 The device obtains its current location using the user's smartphone's GPS function. This involves accessing GPS information through application permissions and obtaining location data with adjusted accuracy. The input is the smartphone's positioning data, and the output is standardized location information sent to the server. This process includes calculating the average value from multiple location detections. 【0377】 Step 3: 【0378】 The device uses an emotion recognition engine to analyze the user's voice data and camera footage to identify their current emotional state. This involves extracting emotional parameters through voice sample acquisition and video analysis. The input is the user's voice and video data, and the output is the identified emotional state data. This process includes voice pattern analysis and emotion determination using an AI learning model. 【0379】 Step 4: 【0380】 The server uses the latest data and sentiment data obtained from an integrated database to generate the optimal evacuation route using a generative AI model. This involves information analysis and calculating the safest and least psychologically stressful route from multiple route options. Inputs include location information, traffic information, weather information, and sentiment data, while output is detailed information about the evacuation route. This process utilizes an optimization algorithm that leverages the learning results of the AI ​​model. 【0381】 Step 5: 【0382】 The terminal provides the user with guidance in the form of audio and visual information based on route information received from the server. Guidance is generated using a speech synthesis engine, and a route map is displayed on the screen. The input is the generated evacuation route information, and the output is a tailored guidance message for the user. This process includes adjusting the voice tone according to the user's emotions. 【0383】 Step 6: 【0384】 The server continuously acquires new information and updates evacuation routes in response to changing circumstances. This includes receiving new data in real time and recalculating existing evacuation routes. The input is the latest information dataset, and the output is updated evacuation route information. This process includes route recalculation for sealed-off areas and newly designated hazard zones. 【0385】 (Application Example 2) 【0386】 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". 【0387】 In times of disaster, flexible guidance that takes into account individual emotional states and real-time changing circumstances is necessary for users to evacuate safely and quickly. However, conventional systems only provide fixed guidance without considering emotional states, which has the problem of failing to alleviate the psychological burden on users. 【0388】 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. 【0389】 In this invention, the server includes emotion recognition means, real-time information acquisition means, and digital map generation means. This makes it possible to generate evacuation routes in real time according to the user's emotional state and provide adaptive guidance. 【0390】 "Acquisition methods" refer to methods for collecting necessary data in real time from external information sources and sensors. 【0391】 An "integration method" is a means of integrating diverse data acquired and transforming it into information that is useful to the user. 【0392】 A "generation method" is used to create appropriate evacuation routes and instructions based on integrated information. 【0393】 "Guidance means" refers to methods of conveying generated information to the user, providing guidance using audio or visual information. 【0394】 "Update mechanisms" refer to methods for revising existing information in response to changes in circumstances or the acquisition of new data, thereby providing the latest instructions. 【0395】 "Emotion recognition means" are devices used to analyze a user's emotional state through audio and visual feedback. 【0396】 A "real-time information acquisition method" is a means of quickly acquiring various types of information at the present time and reflecting them in the system. 【0397】 A "digital map generation method" is a system that generates digital maps using the latest geographic information and uses them for route guidance. 【0398】 "Flexible guidance adjustment methods based on diverse states" refers to methods that change the content of guidance according to the user's emotional state and circumstances, in order to provide optimal information. 【0399】 The system implementing this invention includes means for acquiring information, integrating information, generating information, providing guidance, updating information, recognizing emotions, acquiring real-time information, generating digital maps, and providing flexible guidance adjustment means based on various states. Through cooperation between the server, terminals, and users, it supports safe and effective evacuation. 【0400】 The server obtains weather and traffic information from external APIs and acquires the user's current location information using GPS from their smartphone. Furthermore, it analyzes the user's emotional state from their voice and facial expression data using emotion recognition technology. Voice analysis libraries such as EmotionAPI are used for emotion recognition. 【0401】 Based on the acquired information, the server generates a digital map and calculates appropriate evacuation routes using an AI model. The guidance for these generated routes is adjusted according to the user's emotional state. For example, if the user is deemed anxious, the device provides a reassuring message in a calm voice. The tone and content of the messages can be flexibly changed during the guidance process. 【0402】 Through real-time information acquisition, the server recalculates evacuation routes each time new information is obtained, providing users with the latest guidance. The aim is to make evacuations safer and smoother. 【0403】 Specific example: When a user launches the app on their smartphone during an evacuation drill, the server sends the optimal evacuation route based on their current location and the latest disaster information. Emotion recognition allows the app to display a message such as, "Please calm down, we will now begin guiding you to the nearest evacuation center," if the user appears to be losing their composure. 【0404】 An example of a prompt for a generative AI model would be, "If the user's emotional state is anxious, generate a reassuring guidance message." Based on this prompt, the model will provide an appropriate message. 【0405】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0406】 Step 1: 【0407】 The server uses external APIs to obtain weather and traffic information. This allows it to collect basic data for understanding disaster situations. It sends external API access requests as input and obtains weather and traffic data as output. Based on this data, it analyzes the current situation and proceeds to the next step. 【0408】 Step 2: 【0409】 The device obtains the user's current location using the GPS function of their smartphone. This allows the system to obtain the user's precise location information. The input is the signal from the smartphone's GPS sensor, and the output is the user's location coordinates. Based on this location information, the system proceeds to generate an evacuation route. 【0410】 Step 3: 【0411】 The device analyzes the user's voice data using emotion recognition to identify their emotional state. The user's voice input is fed into a voice analysis library such as EmotionAPI, and emotional state information is obtained as output. This allows for real-time monitoring of the user's psychological state. 【0412】 Step 4: 【0413】 The server integrates collected location information, external data, and the user's emotional state to generate the optimal evacuation route using a generative AI model. By using the integrated data as input and feeding that data into the generative AI model, it obtains a safe and psychologically less stressful evacuation route as output. 【0414】 Step 5: 【0415】 The terminal adjusts the generated evacuation route based on the user's emotional state and provides voice and visual guidance. Inputs are the generated evacuation route and emotional data, which are then used by speech synthesis software to generate messages. Outputs are visual information and voice guidance displayed to the user. 【0416】 Step 6: 【0417】 The server uses real-time information acquisition methods to detect new disaster information and changes in traffic conditions, and recalculates evacuation routes as needed. The input is new data, and existing routes are evaluated based on this data. The output is the updated route. Through this process, users are always guided to the optimal evacuation method. 【0418】 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. 【0419】 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. 【0420】 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. 【0421】 [Third Embodiment] 【0422】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0423】 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. 【0424】 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). 【0425】 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. 【0426】 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. 【0427】 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). 【0428】 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. 【0429】 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. 【0430】 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. 【0431】 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. 【0432】 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. 【0433】 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". 【0434】 The present invention is implemented by a system including acquisition means, integration means, generation means, guidance means, and update means. These means work together to provide users with a safe and efficient evacuation route in the event of a disaster. 【0435】 Program processing and execution 【0436】 Implementation of acquisition methods 【0437】 The server collects real-time location, traffic, weather, and disaster information through external APIs and sensor networks. This information is stored in a database and used for subsequent processing. For example, if an earthquake occurs in a certain area, the server immediately retrieves earthquake information and maps it. 【0438】 Implementation of integration measures 【0439】 The server integrates the diverse information it acquires, organizing all the data points to create a single, unified information set. This integrated information is then used in the optimization process for the next generation method. 【0440】 Implementation of the generation means 【0441】 The server generates the optimal evacuation route from the user's current location based on integrated information. The generated evacuation route takes into account time efficiency, safety of movement, and environmental conditions. For example, if flooding is predicted in an area due to heavy rain, the generation method will prioritize routes that pass through higher ground. 【0442】 Implementation of guidance methods 【0443】 The terminal guides the user along a generated evacuation route. Route guidance is provided using both voice guidance and visual map displays. Users can intuitively follow the instructions and begin their evacuation. 【0444】 Implementation of update methods 【0445】 The server monitors real-time updated information and updates evacuation routes, taking into account the progression of the disaster and changes in public infrastructure. This ensures that users are always provided with evacuation information that reflects the latest situation. 【0446】 Specific example 【0447】 This example illustrates a scenario where an earthquake occurs in a specific area and evacuation becomes necessary. The user launches the app on their smartphone, and the device instantly determines their current location. The server obtains information from the Japan Meteorological Agency and transportation companies, and based on this, generates a safe and rapid evacuation route. The device provides voice guidance along this route, giving specific instructions such as, "It will take 10 minutes to reach the nearest evacuation center. Please proceed along the nearest road that is currently passable." Even if road closure information is updated during the evacuation, the server quickly recalculates the route and guides the user to an appropriate alternative route. This allows the user to complete the evacuation safely without panicking. 【0448】 The following describes the processing flow. 【0449】 Step 1: 【0450】 The server acquires user location information, traffic conditions, weather conditions, and disaster information in real time from external APIs and sensor networks. The acquired data is stored in a database for analysis. 【0451】 Step 2: 【0452】 The device obtains the current location information using the user's GPS function. The location information is automatically updated when the user launches the app. 【0453】 Step 3: 【0454】 The server integrates the acquired data to create a centralized information set that includes information on traffic closures, weather changes, and safe routes. 【0455】 Step 4: 【0456】 The server uses a generation method to calculate the optimal evacuation route based on integrated data. Factors such as safety and travel time are taken into consideration when determining the route. 【0457】 Step 5: 【0458】 The terminal guides the user through the generated evacuation route using both voice and visual aids. Voice guidance allows the user to receive specific instructions for action. 【0459】 Step 6: 【0460】 The server monitors the progress of the disaster and real-time updates of traffic information, re-evaluates routes in response to new risks and changes in information, and updates routes as needed. 【0461】 Step 7: 【0462】 The user receives updated route guidance through the device and continues their safe evacuation by following the instructions. In some cases, the device will recalculate the route and provide a voice-over. 【0463】 Step 8: 【0464】 After evacuation is complete, users report the completion of their evacuation using a terminal and input their needs for necessary relief supplies and medical care. The server records this information and matches it with the necessary support. 【0465】 (Example 1) 【0466】 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." 【0467】 Providing rapid and safe evacuation routes during disasters is a challenge. In particular, there is a need for a system that can always present the optimal route and ensure the safe evacuation of users, especially as information changes in real time. Currently, there is a delay in updating information and applying it to evacuation routes, which can compromise safety. 【0468】 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. 【0469】 In this invention, the server includes means for acquiring information from external information sources and storing it in a database, means for integrating information acquired from multiple information sources to create a consistent set of information, and means for generating evacuation routes based on the integrated information. This makes it possible to provide a fast and safe evacuation route based on the latest information at all times. 【0470】 "Acquisition means" refers to devices or methods for acquiring information from external sources and storing it in a database. 【0471】 "Integration" refers to the process of organizing information obtained from multiple sources to create a consistent set of information. 【0472】 A "generation means" refers to a device or method that creates new, safe, and efficient evacuation routes based on integrated information. 【0473】 A "guidance means" refers to a device or method that displays the generated evacuation route to the user using audio and visual information, thereby assisting them in their movement. 【0474】 An "update mechanism" is a process that constantly monitors the latest information in situations where information changes in real time, and recalculates and provides the route as needed. 【0475】 This invention aims to construct a system for providing safe and efficient evacuation routes in the event of a disaster. The system comprises five main functions: external information management, integrated analysis, route generation, user guidance, and information updating. 【0476】 The server acquires real-time location, traffic, weather, and disaster information using external APIs and sensor networks. The server manages this data in a database, preparing it for subsequent data processing. The hardware used includes a database server and communication modules. The software used includes libraries for API access and data analysis tools. 【0477】 The server integrates the acquired information to create a consistent set of information. This set of information forms the basis for evacuation route generation, which is described below. The generated evacuation routes take into account user safety and efficiency. This allows users to utilize the optimal route from their current location to their evacuation destination. 【0478】 The device provides the user with generated routes as voice and visual guidance. Users can intuitively receive navigation using a device such as a smartphone. The guidance includes features such as voice guidance and real-time map display. 【0479】 The server constantly monitors for the latest information and updates evacuation routes as needed, including disaster conditions and road closures. This feature ensures that users can always access the safest route. 【0480】 As a concrete example of its use, in the event of an earthquake, the user launches the app on their device. The server immediately generates a safe evacuation route based on the latest weather information and traffic data, and the device provides voice guidance such as, "It will take 10 minutes to reach the nearest evacuation center. Please proceed along the nearest road that is currently passable." Even if roads are blocked along the way, the server immediately calculates a new route and provides instructions to the user. 【0481】 An example of a prompt message is: "Please describe the specific processing steps for the evacuation route guidance system in the event of a disaster. These steps include acquisition, integration, generation, guidance, and update methods." 【0482】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0483】 Step 1: 【0484】 The server collects data from external APIs and sensor networks. Its inputs include location information, traffic information, weather information, and disaster information. This data is received from each information source and stored in a database. Specifically, the server makes API calls, receives information in JSON format, and stores it in a structured database. 【0485】 Step 2: 【0486】 The server integrates the information stored in the database. It uses information from multiple data sources as input. By organizing data points and filtering out unnecessary data, it creates a consistent set of information. Specifically, the server eliminates duplicate location information and prioritizes the integration of the most recent data. 【0487】 Step 3: 【0488】 The server generates evacuation routes based on integrated information. It takes the user's current location and an integrated information set as input. Data processing uses a route generation algorithm to calculate the shortest and safest route. Specifically, it performs optimized route searching, taking into account terrain and traffic information. 【0489】 Step 4: 【0490】 The terminal guides the user along the generated evacuation route. It uses evacuation route information received from the server as input. Output includes voice guidance and real-time map displays. Specifically, the terminal provides voice commands such as "Turn left at the next intersection" and indicates the route with arrows on the screen. 【0491】 Step 5: 【0492】 The server monitors real-time changes in information and recalculates routes as needed. It takes the latest disaster information and traffic conditions as input. Based on this, the server processes the data and generates new routes. Specifically, if road closure information is updated, it calculates a new detour route and sends it to the terminal. 【0493】 (Application Example 1) 【0494】 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." 【0495】 In modern society, rapid and safe evacuation is essential during disasters, but conventional systems struggle to integrate information in real time and generate optimal evacuation routes. Furthermore, they are unable to keep up with rapidly changing disaster information, making it difficult to provide accurate instructions to users. 【0496】 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. 【0497】 In this invention, the server includes data collection means, information integration means, and route generation means. This makes it possible to aggregate diverse data in real time during a disaster and continuously generate the optimal evacuation route. Furthermore, it is possible to support rapid and safe evacuation by providing intuitive instructions to the user using voice and visual information. 【0498】 "Data acquisition means" refers to a device or process for acquiring real-time information from external data sources or sensors. 【0499】 An "information integration tool" is a means for integrating multiple acquired data and creating a single, organized set of information. 【0500】 A "route generation means" is a means for calculating and generating the optimal travel route based on integrated information. 【0501】 "User guidance methods" refer to means of providing information to users using audio and visuals based on generated information. 【0502】 An "information update method" is a means of monitoring acquired information in real time and updating the information and travel routes in accordance with changing circumstances. 【0503】 The system for realizing this invention will be implemented as an application using a smartphone or mobile device. This application will support rapid and safe evacuation during disasters through the processes described below. 【0504】 First, the device obtains the user's current location using GPS functionality through data collection means. It also obtains weather, traffic, and disaster information in real time through external APIs and cloud services. This information is transmitted to a server and integrated using information integration means. 【0505】 Next, the server uses a route generation mechanism to generate the optimal evacuation route for the user based on the information organized by the information integration mechanism. This route generation utilizes an AI algorithm, and by linking with a geographic information system (GIS), for example, it calculates the optimal route according to the type and progression of the disaster. 【0506】 Subsequently, the terminal guides the user along the evacuation route through voice and visual means. A text-to-speech API is used for voice guidance, and a map display API is used for visual guidance. This allows users to intuitively follow the instructions. 【0507】 The server uses an information update mechanism to recalculate evacuation routes in real time based on constantly changing disaster information, providing users with the latest information. In this way, users can evacuate with peace of mind. 【0508】 As a concrete example, consider the use of the app when heavy rain is expected. When a user launches the app, it checks their current location and generates a safe route that avoids areas where flooding is predicted. Detailed instructions are provided via voice guidance, such as "Turn right at the next intersection and go straight," to encourage the user to evacuate appropriately. 【0509】 An example of a prompt statement is: "When evacuation is necessary in a specific area, consider how to provide residents with real-time information and effectively support their evacuation." 【0510】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0511】 Step 1: 【0512】 The device initiates the data collection process. It enables GPS functionality on the device to obtain the user's current location. Simultaneously, it uses external APIs to acquire weather, traffic, and disaster information in real time. The input consists of the device's location information and environmental data from external APIs, while the output is an integrated set of information containing these. 【0513】 Step 2: 【0514】 The server performs the information integration process. It receives sensor information and external API data sent from terminals and stores them in a database. It standardizes various data formats and creates a unified dataset. The input is sensor information and external data, and the output is a dataset that integrates them. 【0515】 Step 3: 【0516】 The server performs the route generation process. Based on the integrated dataset, it uses an AI algorithm to calculate the optimal evacuation route. For example, a generative AI model is used to select a safe and efficient route. The input is the integrated dataset, and the output is the optimized evacuation route. 【0517】 Step 4: 【0518】 The terminal initiates the user guidance process. Based on the generated evacuation route, it guides the user using audio and visual information. The audio guide utilizes text-to-speech functionality, and the route is visually presented using a map display. The input is the optimal evacuation route, and the output is the audio and visual instructions provided to the user. 【0519】 Step 5: 【0520】 The server continuously performs the information update process. It acquires new information in real time and updates the evacuation route if it needs to be recalculated. This ensures that users are always provided with guidance based on the latest information. The input is new environmental data, and the output is the updated evacuation route. 【0521】 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. 【0522】 The present invention is implemented by a system that includes acquisition means, integration means, generation means, guidance means, and update means, as well as an emotion engine that recognizes the user's emotions. These means and the emotion engine work together to reduce the psychological burden on the user during a disaster while supporting safe and effective evacuation. 【0523】 Program processing and execution 【0524】 Implementation of acquisition methods 【0525】 The server collects user location information, traffic conditions, weather information, and disaster information in real time through external APIs and sensor networks. This data serves as foundational information for accurately understanding disaster situations. 【0526】 Identifying user location information 【0527】 The device uses the GPS function of the user's smartphone to accurately obtain their current location, enabling location tracking even during disasters. 【0528】 Implementation of the Emotion Engine 【0529】 The device incorporates an emotion engine that recognizes and analyzes the user's emotions through voice and visual feedback. This allows for real-time monitoring of the user's emotional state, such as fear and anxiety. 【0530】 Implementation of the generation means 【0531】 The server generates an optimal route that takes stress reduction into consideration, based on integrated information and user sentiment data. The generated route takes safety and minimal psychological burden into account. 【0532】 Implementation of guidance methods 【0533】 The device guides the user along a generated evacuation route in a manner adjusted based on emotional data. The voice tone and message content are modified as needed to help the user maintain an emotionally calm state. 【0534】 Implementation of update methods 【0535】 The server recalculates the route in response to changes in circumstances and the acquisition of new information, and provides more refined guidance based on the analysis results from the emotion engine. 【0536】 Specific example 【0537】 Let's take the example of an earthquake occurring and evacuation being necessary. The user launches the app on their smartphone, and the device confirms their current location. At this time, the device's emotion engine recognizes anxiety from the user's voice. Based on the collected data and emotional state, the server prioritizes a route that provides a sense of security and delivers a route mission to the device. The guidance method calms the user by guiding them in a gentle voice, saying, "It is important to act calmly. We will now begin guiding you to the nearest evacuation center." If there is new closure information along the route, the server immediately updates the route and provides guidance again, thereby reducing the user's anxiety and supporting the safe completion of evacuation. 【0538】 The following describes the processing flow. 【0539】 Step 1: 【0540】 The server utilizes external APIs and sensor networks to collect location, traffic, weather, and disaster information in real time. This allows for the accumulation of information based on the latest conditions. 【0541】 Step 2: 【0542】 The terminal obtains GPS information from the user's device to accurately determine their current location. This information is then used to generate evacuation routes. 【0543】 Step 3: 【0544】 The emotion engine built into the device analyzes the user's voice data to recognize their psychological state. The recognition results identify emotions such as anxiety and fear and send them to a database. 【0545】 Step 4: 【0546】 The server uses integration to consolidate all acquired information and constructs a comprehensive dataset that takes into account the user's current location and psychological state. 【0547】 Step 5: 【0548】 The server uses a generation mechanism to generate the optimal evacuation route based on integrated data. This route is intended to reduce not only safety but also the emotional burden on the user. 【0549】 Step 6: 【0550】 The device uses guidance to present the user with evacuation routes generated in an appropriate tone and content. Based on emotional data, the voice guide is adjusted to help the user relax. 【0551】 Step 7: 【0552】 The server receives new information in real time and understands the changing situation. It updates generated routes as needed and adjusts guidance methods based on data from the emotion engine. 【0553】 Step 8: 【0554】 Users feel reassured by receiving the latest route guidance from their devices and safely reach their designated evacuation location. After evacuation is complete, users report any assistance they need, and the server uses this information to match them with appropriate support. 【0555】 (Example 2) 【0556】 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." 【0557】 In the event of a disaster, support is needed to ensure that evacuees can evacuate safely and quickly. This requires a system that can respond to the situation in real time while reducing the psychological burden on evacuees. However, conventional technologies fail to adequately consider the emotional state of individual evacuees when generating and presenting evacuation routes, resulting in a lack of systems that provide safe and psychologically supportive assistance. 【0558】 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. 【0559】 In this invention, the server includes means for acquiring information, means for integrating information, means for generating routes, means for providing guidance, means for updating information, and means for recognizing emotions. This enables the generation of evacuation routes in real time under disaster conditions and provides safe and psychologically less burdensome guidance that takes into account the emotional state of evacuees. 【0560】 "Means of acquiring information" refers to devices or functions that collect data from external sources and make it available for use within a system. 【0561】 "Means for integrating information" refers to devices or functions that analyze various acquired data, correlate them, and compile them into consistent information. 【0562】 "Means for generating routes" refers to devices or functions that calculate and present the optimal travel route to a destination based on integrated information. 【0563】 "Means of providing guidance" refers to devices or functions that communicate generated routes and related information to users via voice or visual means. 【0564】 "Means of updating information" refers to devices or functions that reacquire data in real time and modify its content in order to keep the collected information and calculated paths up-to-date in response to changes in circumstances. 【0565】 "Means of recognizing emotions" refer to devices or functions that analyze emotions from the user's voice, facial expressions, etc., in order to understand the user's psychological state. 【0566】 This invention is a system aimed at providing evacuation support during disasters. Specifically, it has a configuration that acquires and integrates information, generates the optimal evacuation route in real time, and provides guidance to the user, thereby reducing psychological burden. 【0567】 The server integrates information based on location data, traffic conditions, weather conditions, and disaster information obtained from external sources. Specifically, it aggregates data from external APIs such as those of the Japan Meteorological Agency and traffic information centers and stores it in a central database. When integrating the information, a generative AI model is used to perform analysis tailored to the disaster situation. 【0568】 The device uses the user's smartphone's GPS function to obtain their current location. Furthermore, the device is equipped with an emotion recognition engine that analyzes the user's emotional state at that moment based on their voice input and camera footage. This emotional data is sent to a server and used to generate evacuation routes. 【0569】 Using a generative AI model, the server generates the optimal evacuation route in real time based on integrated information and sentiment data. This route ensures user safety while minimizing psychological burden, and is then transmitted to the terminal. 【0570】 The user receives instructions from their device. These instructions are presented in both audio and visual formats and are adjusted according to the user's emotional state. This allows the user to evacuate calmly and accurately. 【0571】 As a concrete example, let's consider a situation where a heavy rain warning has been issued for the user's area of ​​residence. The user launches the app and enters a prompt such as, "A heavy rain warning has been issued for my area. Do I need to evacuate?", and receives guidance on appropriate evacuation actions. Based on the information received, the server generates a route to the nearest safe evacuation shelter and provides the user with directions through their device. 【0572】 In this way, this system supports the safe and secure evacuation of users during disasters and aims to reduce their psychological burden. 【0573】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0574】 Step 1: 【0575】 The server obtains location information, traffic conditions, weather information, disaster information, and other data from external sources. This includes sending requests to weather information APIs and traffic information APIs and receiving the data obtained as responses. The input is various real-time data obtained from the APIs, and the output is information converted into a format that is stored in an integrated database. This process involves data format conversion and timely data updates. 【0576】 Step 2: 【0577】 The device obtains its current location using the user's smartphone's GPS function. This involves accessing GPS information through application permissions and obtaining location data with adjusted accuracy. The input is the smartphone's positioning data, and the output is standardized location information sent to the server. This process includes calculating the average value from multiple location detections. 【0578】 Step 3: 【0579】 The device uses an emotion recognition engine to analyze the user's voice data and camera footage to identify their current emotional state. This involves extracting emotional parameters through voice sample acquisition and video analysis. The input is the user's voice and video data, and the output is the identified emotional state data. This process includes voice pattern analysis and emotion determination using an AI learning model. 【0580】 Step 4: 【0581】 The server uses the latest data and sentiment data obtained from an integrated database to generate the optimal evacuation route using a generative AI model. This involves information analysis and calculating the safest and least psychologically stressful route from multiple route options. Inputs include location information, traffic information, weather information, and sentiment data, while output is detailed information about the evacuation route. This process utilizes an optimization algorithm that leverages the learning results of the AI ​​model. 【0582】 Step 5: 【0583】 The terminal provides the user with guidance in the form of audio and visual information based on route information received from the server. Guidance is generated using a speech synthesis engine, and a route map is displayed on the screen. The input is the generated evacuation route information, and the output is a tailored guidance message for the user. This process includes adjusting the voice tone according to the user's emotions. 【0584】 Step 6: 【0585】 The server continuously acquires new information and updates evacuation routes in response to changing circumstances. This includes receiving new data in real time and recalculating existing evacuation routes. The input is the latest information dataset, and the output is updated evacuation route information. This process includes route recalculation for sealed-off areas and newly designated hazard zones. 【0586】 (Application Example 2) 【0587】 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." 【0588】 In times of disaster, flexible guidance that takes into account individual emotional states and real-time changing circumstances is necessary for users to evacuate safely and quickly. However, conventional systems only provide fixed guidance without considering emotional states, which has the problem of failing to alleviate the psychological burden on users. 【0589】 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. 【0590】 In this invention, the server includes emotion recognition means, real-time information acquisition means, and digital map generation means. This makes it possible to generate evacuation routes in real time according to the user's emotional state and provide adaptive guidance. 【0591】 "Acquisition methods" refer to methods for collecting necessary data in real time from external information sources and sensors. 【0592】 An "integration method" is a means of integrating diverse data acquired and transforming it into information that is useful to the user. 【0593】 A "generation method" is used to create appropriate evacuation routes and instructions based on integrated information. 【0594】 "Guidance means" refers to methods of conveying generated information to the user, providing guidance using audio or visual information. 【0595】 "Update mechanisms" refer to methods for revising existing information in response to changes in circumstances or the acquisition of new data, thereby providing the latest instructions. 【0596】 "Emotion recognition means" are devices used to analyze a user's emotional state through audio and visual feedback. 【0597】 A "real-time information acquisition method" is a means of quickly acquiring various types of information at the present time and reflecting them in the system. 【0598】 A "digital map generation method" is a system that generates digital maps using the latest geographic information and uses them for route guidance. 【0599】 "Flexible guidance adjustment means based on diverse conditions" refers to a system that changes the content of guidance according to the user's emotional state and circumstances, in order to provide optimal information. 【0600】 The system implementing this invention includes means for acquiring information, integrating information, generating information, providing guidance, updating information, recognizing emotions, acquiring real-time information, generating digital maps, and providing flexible guidance adjustment means based on various states. Through cooperation between the server, terminals, and users, it supports safe and effective evacuation. 【0601】 The server obtains weather and traffic information from external APIs and acquires the user's current location information using GPS from their smartphone. Furthermore, it analyzes the user's emotional state from their voice and facial expression data using emotion recognition technology. Voice analysis libraries such as EmotionAPI are used for emotion recognition. 【0602】 Based on the acquired information, the server generates a digital map and calculates appropriate evacuation routes using an AI model. The guidance for these generated routes is adjusted according to the user's emotional state. For example, if the user is deemed anxious, the device provides a reassuring message in a calm voice. The tone and content of the messages can be flexibly changed during the guidance process. 【0603】 Through real-time information acquisition, the server recalculates evacuation routes each time new information is obtained, providing users with the latest guidance. The aim is to make evacuations safer and smoother. 【0604】 Specific example: When a user launches the app on their smartphone during an evacuation drill, the server sends the optimal evacuation route based on their current location and the latest disaster information. Emotion recognition allows the app to display a message such as, "Please calm down, we will now begin guiding you to the nearest evacuation center," if the user appears to be losing their composure. 【0605】 An example of a prompt for a generative AI model would be an instruction such as, "If the user's emotional state is anxious, generate a reassuring guidance message." Based on this prompt, the model will provide an appropriate message. 【0606】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0607】 Step 1: 【0608】 The server uses external APIs to obtain weather and traffic information. This allows it to collect basic data for understanding disaster situations. It sends external API access requests as input and obtains weather and traffic data as output. Based on this data, it analyzes the current situation and proceeds to the next step. 【0609】 Step 2: 【0610】 The device obtains the user's current location using the GPS function of their smartphone. This allows the system to obtain the user's precise location information. The input is the signal from the smartphone's GPS sensor, and the output is the user's location coordinates. Based on this location information, the system proceeds to generate an evacuation route. 【0611】 Step 3: 【0612】 The device analyzes the user's voice data using emotion recognition to identify their emotional state. The user's voice input is fed into a voice analysis library such as EmotionAPI, and emotional state information is obtained as output. This allows for real-time monitoring of the user's psychological state. 【0613】 Step 4: 【0614】 The server integrates collected location information, external data, and the user's emotional state to generate the optimal evacuation route using a generative AI model. By using the integrated data as input and feeding that data into the generative AI model, it obtains a safe and psychologically less stressful evacuation route as output. 【0615】 Step 5: 【0616】 The terminal adjusts the generated evacuation route based on the user's emotional state and provides voice and visual guidance. Inputs are the generated evacuation route and emotional data, which are then used by speech synthesis software to generate messages. Outputs are visual information and voice guidance displayed to the user. 【0617】 Step 6: 【0618】 The server uses real-time information acquisition methods to detect new disaster information and changes in traffic conditions, and recalculates evacuation routes as needed. The input is new data, and existing routes are evaluated based on this data. The output is the updated route. Through this process, users are always guided to the optimal evacuation method. 【0619】 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. 【0620】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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. 【0621】 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. 【0622】 [Fourth Embodiment] 【0623】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0624】 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. 【0625】 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). 【0626】 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. 【0627】 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. 【0628】 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). 【0629】 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. 【0630】 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. 【0631】 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. 【0632】 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. 【0633】 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. 【0634】 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. 【0635】 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". 【0636】 The present invention is implemented by a system including acquisition means, integration means, generation means, guidance means, and update means. These means work together to provide users with a safe and efficient evacuation route in the event of a disaster. 【0637】 Program processing and execution 【0638】 Implementation of acquisition methods 【0639】 The server collects real-time location, traffic, weather, and disaster information through external APIs and sensor networks. This information is stored in a database and used for subsequent processing. For example, if an earthquake occurs in a certain area, the server immediately retrieves earthquake information and maps it. 【0640】 Implementation of integration measures 【0641】 The server integrates the diverse information it acquires, organizing all the data points to create a single, unified information set. This integrated information is then used in the optimization process for the next generation method. 【0642】 Implementation of the generation means 【0643】 The server generates the optimal evacuation route from the user's current location based on integrated information. The generated evacuation route takes into account time efficiency, safety of movement, and environmental conditions. For example, if flooding is predicted in an area due to heavy rain, the generation method will prioritize routes that pass through higher ground. 【0644】 Implementation of guidance methods 【0645】 The terminal guides the user along a generated evacuation route. Route guidance is provided using both voice guidance and visual map displays. Users can intuitively follow the instructions and begin their evacuation. 【0646】 Implementation of update methods 【0647】 The server monitors real-time updated information and updates evacuation routes, taking into account the progression of the disaster and changes in public infrastructure. This ensures that users are always provided with evacuation information that reflects the latest situation. 【0648】 Specific example 【0649】 This example illustrates a scenario where an earthquake occurs in a specific area and evacuation becomes necessary. The user launches the app on their smartphone, and the device instantly determines their current location. The server obtains information from the Japan Meteorological Agency and transportation companies, and based on this, generates a safe and rapid evacuation route. The device provides voice guidance along this route, giving specific instructions such as, "It will take 10 minutes to reach the nearest evacuation center. Please proceed along the nearest road that is currently passable." Even if road closure information is updated during the evacuation, the server quickly recalculates the route and guides the user to an appropriate alternative route. This allows the user to complete the evacuation safely without panicking. 【0650】 The following describes the processing flow. 【0651】 Step 1: 【0652】 The server acquires user location information, traffic conditions, weather conditions, and disaster information in real time from external APIs and sensor networks. The acquired data is stored in a database for analysis. 【0653】 Step 2: 【0654】 The device obtains the current location information using the user's GPS function. The location information is automatically updated when the user launches the app. 【0655】 Step 3: 【0656】 The server integrates the acquired data to create a centralized information set that includes information on traffic closures, weather changes, and safe routes. 【0657】 Step 4: 【0658】 The server uses a generation method to calculate the optimal evacuation route based on integrated data. Factors such as safety and travel time are taken into consideration when determining the route. 【0659】 Step 5: 【0660】 The terminal guides the user through the generated evacuation route using both voice and visual aids. Voice guidance allows the user to receive specific instructions for action. 【0661】 Step 6: 【0662】 The server monitors the progress of the disaster and real-time updates of traffic information, re-evaluates routes in response to new risks and changes in information, and updates routes as needed. 【0663】 Step 7: 【0664】 The user receives updated route guidance through the device and continues their safe evacuation by following the instructions. In some cases, the device will recalculate the route and provide a voice-over. 【0665】 Step 8: 【0666】 After evacuation is complete, users report the completion of their evacuation using a terminal and input their needs for necessary relief supplies and medical care. The server records this information and matches it with the necessary support. 【0667】 (Example 1) 【0668】 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". 【0669】 Providing rapid and safe evacuation routes during disasters is a challenge. In particular, there is a need for a system that can always present the optimal route and ensure the safe evacuation of users, especially as information changes in real time. Currently, there is a delay in updating information and applying it to evacuation routes, which can compromise safety. 【0670】 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. 【0671】 In this invention, the server includes means for acquiring information from external information sources and storing it in a database, means for integrating information acquired from multiple information sources to create a consistent set of information, and means for generating evacuation routes based on the integrated information. This makes it possible to provide a fast and safe evacuation route based on the latest information at all times. 【0672】 "Acquisition means" refers to devices or methods for acquiring information from external sources and storing it in a database. 【0673】 "Integration" refers to the process of organizing information obtained from multiple sources to create a consistent set of information. 【0674】 A "generation means" refers to a device or method that creates new, safe, and efficient evacuation routes based on integrated information. 【0675】 A "guidance means" refers to a device or method that displays the generated evacuation route to the user using audio and visual information, thereby assisting them in their movement. 【0676】 An "update mechanism" is a process that constantly monitors the latest information in situations where information changes in real time, and recalculates and provides the route as needed. 【0677】 This invention aims to construct a system for providing safe and efficient evacuation routes in the event of a disaster. The system comprises five main functions: external information management, integrated analysis, route generation, user guidance, and information updating. 【0678】 The server acquires real-time location, traffic, weather, and disaster information using external APIs and sensor networks. The server manages this data in a database, preparing it for subsequent data processing. The hardware used includes a database server and communication modules. The software used includes libraries for API access and data analysis tools. 【0679】 The server integrates the acquired information to create a consistent set of information. This set of information forms the basis for evacuation route generation, which is described below. The generated evacuation routes take into account user safety and efficiency. This allows users to utilize the optimal route from their current location to their evacuation destination. 【0680】 The device provides the user with generated routes as voice and visual guidance. Users can intuitively receive navigation using a device such as a smartphone. The guidance includes features such as voice guidance and real-time map display. 【0681】 The server constantly monitors for the latest information and updates evacuation routes as needed, including disaster conditions and road closures. This feature ensures that users can always access the safest route. 【0682】 As a concrete example of its use, in the event of an earthquake, the user launches the app on their device. The server immediately generates a safe evacuation route based on the latest weather information and traffic data, and the device provides voice guidance such as, "It will take 10 minutes to reach the nearest evacuation center. Please proceed along the nearest road that is currently passable." Even if roads are blocked along the way, the server immediately calculates a new route and provides instructions to the user. 【0683】 An example of a prompt message is: "Please describe the specific processing steps for the evacuation route guidance system in the event of a disaster. These steps include acquisition, integration, generation, guidance, and update methods." 【0684】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0685】 Step 1: 【0686】 The server collects data from external APIs and sensor networks. Its inputs include location information, traffic information, weather information, and disaster information. This data is received from each information source and stored in a database. Specifically, the server makes API calls, receives information in JSON format, and stores it in a structured database. 【0687】 Step 2: 【0688】 The server integrates the information stored in the database. It uses information from multiple data sources as input. By organizing data points and filtering out unnecessary data, it creates a consistent set of information. Specifically, the server eliminates duplicate location information and prioritizes the integration of the most recent data. 【0689】 Step 3: 【0690】 The server generates evacuation routes based on integrated information. It takes the user's current location and an integrated information set as input. Data processing uses a route generation algorithm to calculate the shortest and safest route. Specifically, it performs optimized route searching, taking into account terrain and traffic information. 【0691】 Step 4: 【0692】 The terminal guides the user along the generated evacuation route. It uses evacuation route information received from the server as input. Output includes voice guidance and real-time map displays. Specifically, the terminal provides voice commands such as "Turn left at the next intersection" and indicates the route with arrows on the screen. 【0693】 Step 5: 【0694】 The server monitors real-time changes in information and recalculates routes as needed. It takes the latest disaster information and traffic conditions as input. Based on this, the server processes the data and generates new routes. Specifically, if road closure information is updated, it calculates a new detour route and sends it to the terminal. 【0695】 (Application Example 1) 【0696】 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". 【0697】 In modern society, rapid and safe evacuation is essential during disasters, but conventional systems struggle to integrate information in real time and generate optimal evacuation routes. Furthermore, they are unable to keep up with rapidly changing disaster information, making it difficult to provide accurate instructions to users. 【0698】 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. 【0699】 In this invention, the server includes data collection means, information integration means, and route generation means. This makes it possible to aggregate diverse data in real time during a disaster and continuously generate the optimal evacuation route. Furthermore, it is possible to support rapid and safe evacuation by providing intuitive instructions to the user using voice and visual information. 【0700】 "Data acquisition means" refers to a device or process for acquiring real-time information from external data sources or sensors. 【0701】 An "information integration tool" is a means for integrating multiple acquired data and creating a single, organized set of information. 【0702】 A "route generation means" is a means for calculating and generating the optimal travel route based on integrated information. 【0703】 "User guidance methods" refer to means of providing information to users using audio and visuals based on generated information. 【0704】 An "information update method" is a means of monitoring acquired information in real time and updating the information and travel routes in accordance with changing circumstances. 【0705】 The system for realizing this invention will be implemented as an application using a smartphone or mobile device. This application will support rapid and safe evacuation during disasters through the processes described below. 【0706】 First, the device obtains the user's current location using GPS functionality through data collection means. It also obtains weather, traffic, and disaster information in real time through external APIs and cloud services. This information is transmitted to a server and integrated using information integration means. 【0707】 Next, the server uses a route generation mechanism to generate the optimal evacuation route for the user based on the information organized by the information integration mechanism. This route generation utilizes an AI algorithm, and by linking with a geographic information system (GIS), for example, it calculates the optimal route according to the type and progression of the disaster. 【0708】 Subsequently, the terminal guides the user along the evacuation route through voice and visual means. A text-to-speech API is used for voice guidance, and a map display API is used for visual guidance. This allows users to intuitively follow the instructions. 【0709】 The server uses an information update mechanism to recalculate evacuation routes in real time based on constantly changing disaster information, providing users with the latest information. In this way, users can evacuate with peace of mind. 【0710】 As a concrete example, consider the use of the app when heavy rain is expected. When a user launches the app, it checks their current location and generates a safe route that avoids areas where flooding is predicted. Detailed instructions are provided via voice guidance, such as "Turn right at the next intersection and go straight," to encourage the user to evacuate appropriately. 【0711】 An example of a prompt statement is: "When evacuation is necessary in a specific area, consider how to provide residents with real-time information and effectively support their evacuation." 【0712】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0713】 Step 1: 【0714】 The device initiates the data collection process. It enables GPS functionality on the device to obtain the user's current location. Simultaneously, it uses external APIs to acquire weather, traffic, and disaster information in real time. The input consists of the device's location information and environmental data from external APIs, while the output is an integrated set of information containing these. 【0715】 Step 2: 【0716】 The server performs the information integration process. It receives sensor information and external API data sent from terminals and stores them in a database. It standardizes various data formats and creates a unified dataset. The input is sensor information and external data, and the output is a dataset that integrates them. 【0717】 Step 3: 【0718】 The server performs the route generation process. Based on the integrated dataset, it uses an AI algorithm to calculate the optimal evacuation route. For example, a generative AI model is used to select a safe and efficient route. The input is the integrated dataset, and the output is the optimized evacuation route. 【0719】 Step 4: 【0720】 The terminal initiates the user guidance process. Based on the generated evacuation route, it guides the user using audio and visual information. The audio guide utilizes text-to-speech functionality, and the route is visually presented using a map display. The input is the optimal evacuation route, and the output is the audio and visual instructions provided to the user. 【0721】 Step 5: 【0722】 The server continuously performs the information update process. It acquires new information in real time and updates the evacuation route if it needs to be recalculated. This ensures that users are always provided with guidance based on the latest information. The input is new environmental data, and the output is the updated evacuation route. 【0723】 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. 【0724】 The present invention is implemented by a system that includes acquisition means, integration means, generation means, guidance means, and update means, as well as an emotion engine that recognizes the user's emotions. These means and the emotion engine work together to reduce the psychological burden on the user during a disaster while supporting safe and effective evacuation. 【0725】 Program processing and execution 【0726】 Implementation of acquisition methods 【0727】 The server collects user location information, traffic conditions, weather information, and disaster information in real time through external APIs and sensor networks. This data serves as foundational information for accurately understanding disaster situations. 【0728】 Identifying user location information 【0729】 The device uses the GPS function of the user's smartphone to accurately obtain their current location, enabling location tracking even during disasters. 【0730】 Implementation of the Emotion Engine 【0731】 The device incorporates an emotion engine that recognizes and analyzes the user's emotions through voice and visual feedback. This allows for real-time monitoring of the user's emotional state, such as fear and anxiety. 【0732】 Implementation of the generation means 【0733】 The server generates an optimal route that takes stress reduction into consideration, based on integrated information and user sentiment data. The generated route takes safety and minimal psychological burden into account. 【0734】 Implementation of guidance methods 【0735】 The device guides the user along a generated evacuation route in a manner adjusted based on emotional data. The voice tone and message content are modified as needed to help the user maintain an emotionally calm state. 【0736】 Implementation of update methods 【0737】 The server recalculates the route in response to changes in circumstances and the acquisition of new information, and provides more refined guidance based on the analysis results from the emotion engine. 【0738】 Specific example 【0739】 Let's take the example of an earthquake occurring and evacuation being necessary. The user launches the app on their smartphone, and the device confirms their current location. At this time, the device's emotion engine recognizes anxiety from the user's voice. Based on the collected data and emotional state, the server prioritizes a route that provides a sense of security and delivers a route mission to the device. The guidance method calms the user by guiding them in a gentle voice, saying, "It is important to act calmly. We will now begin guiding you to the nearest evacuation center." If there is new closure information along the route, the server immediately updates the route and provides guidance again, thereby reducing the user's anxiety and supporting the safe completion of evacuation. 【0740】 The following describes the processing flow. 【0741】 Step 1: 【0742】 The server utilizes external APIs and sensor networks to collect location, traffic, weather, and disaster information in real time. This allows for the accumulation of information based on the latest conditions. 【0743】 Step 2: 【0744】 The terminal obtains GPS information from the user's device to accurately determine their current location. This information is then used to generate evacuation routes. 【0745】 Step 3: 【0746】 The emotion engine built into the device analyzes the user's voice data to recognize their psychological state. The recognition results identify emotions such as anxiety and fear and send them to a database. 【0747】 Step 4: 【0748】 The server uses integration to consolidate all acquired information and constructs a comprehensive dataset that takes into account the user's current location and psychological state. 【0749】 Step 5: 【0750】 The server uses a generation mechanism to generate the optimal evacuation route based on integrated data. This route is intended to reduce not only safety but also the emotional burden on the user. 【0751】 Step 6: 【0752】 The device uses guidance to present the user with evacuation routes generated in an appropriate tone and content. Based on emotional data, the voice guide is adjusted to help the user relax. 【0753】 Step 7: 【0754】 The server receives new information in real time and understands the changing situation. It updates generated routes as needed and adjusts guidance methods based on data from the emotion engine. 【0755】 Step 8: 【0756】 Users feel reassured by receiving the latest route guidance from their devices and safely reach their designated evacuation location. After evacuation is complete, users report any assistance they need, and the server uses this information to match them with appropriate support. 【0757】 (Example 2) 【0758】 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". 【0759】 In the event of a disaster, support is needed to ensure that evacuees can evacuate safely and quickly. This requires a system that can respond to the situation in real time while reducing the psychological burden on evacuees. However, conventional technologies fail to adequately consider the emotional state of individual evacuees when generating and presenting evacuation routes, resulting in a lack of systems that provide safe and psychologically supportive assistance. 【0760】 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. 【0761】 In this invention, the server includes means for acquiring information, means for integrating information, means for generating routes, means for providing guidance, means for updating information, and means for recognizing emotions. This enables the generation of evacuation routes in real time under disaster conditions and provides safe and psychologically less burdensome guidance that takes into account the emotional state of evacuees. 【0762】 "Means of acquiring information" refers to devices or functions that collect data from external sources and make it available for use within a system. 【0763】 "Means for integrating information" refers to devices or functions that analyze various acquired data, correlate them, and compile them into consistent information. 【0764】 "Means for generating routes" refers to devices or functions that calculate and present the optimal travel route to a destination based on integrated information. 【0765】 "Means of providing guidance" refers to devices or functions that communicate generated routes and related information to users via voice or visual means. 【0766】 "Means of updating information" refers to devices or functions that reacquire data in real time and modify its content in order to keep the collected information and calculated paths up-to-date in response to changes in circumstances. 【0767】 "Means of recognizing emotions" refer to devices or functions that analyze emotions from the user's voice, facial expressions, etc., in order to understand the user's psychological state. 【0768】 This invention is a system aimed at providing evacuation support during disasters. Specifically, it has a configuration that acquires and integrates information, generates the optimal evacuation route in real time, and provides guidance to the user, thereby reducing psychological burden. 【0769】 The server integrates information based on location data, traffic conditions, weather conditions, and disaster information obtained from external sources. Specifically, it aggregates data from external APIs such as those of the Japan Meteorological Agency and traffic information centers and stores it in a central database. When integrating the information, a generative AI model is used to perform analysis tailored to the disaster situation. 【0770】 The device uses the user's smartphone's GPS function to obtain their current location. Furthermore, the device is equipped with an emotion recognition engine that analyzes the user's emotional state at that moment based on their voice input and camera footage. This emotional data is sent to a server and used to generate evacuation routes. 【0771】 Using a generative AI model, the server generates the optimal evacuation route in real time based on integrated information and sentiment data. This route ensures user safety while minimizing psychological burden, and is then transmitted to the terminal. 【0772】 The user receives instructions from their device. These instructions are presented in both audio and visual formats and are adjusted according to the user's emotional state. This allows the user to evacuate calmly and accurately. 【0773】 As a concrete example, let's consider a situation where a heavy rain warning has been issued for the user's area of ​​residence. The user launches the app and enters a prompt such as, "A heavy rain warning has been issued for my area. Do I need to evacuate?", and receives guidance on appropriate evacuation actions. Based on the information received, the server generates a route to the nearest safe evacuation shelter and provides the user with directions through their device. 【0774】 In this way, this system supports the safe and secure evacuation of users during disasters and aims to reduce their psychological burden. 【0775】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0776】 Step 1: 【0777】 The server obtains location information, traffic conditions, weather information, disaster information, and other data from external sources. This includes sending requests to weather information APIs and traffic information APIs and receiving the data obtained as responses. The input is various real-time data obtained from the APIs, and the output is information converted into a format that is stored in an integrated database. This process involves data format conversion and timely data updates. 【0778】 Step 2: 【0779】 The device obtains its current location using the user's smartphone's GPS function. This involves accessing GPS information through application permissions and obtaining location data with adjusted accuracy. The input is the smartphone's positioning data, and the output is standardized location information sent to the server. This process includes calculating the average value from multiple location detections. 【0780】 Step 3: 【0781】 The device uses an emotion recognition engine to analyze the user's voice data and camera footage to identify their current emotional state. This involves extracting emotional parameters through voice sample acquisition and video analysis. The input is the user's voice and video data, and the output is the identified emotional state data. This process includes voice pattern analysis and emotion determination using an AI learning model. 【0782】 Step 4: 【0783】 The server uses the latest data and sentiment data obtained from an integrated database to generate the optimal evacuation route using a generative AI model. This involves information analysis and calculating the safest and least psychologically stressful route from multiple route options. Inputs include location information, traffic information, weather information, and sentiment data, while output is detailed information about the evacuation route. This process utilizes an optimization algorithm that leverages the learning results of the AI ​​model. 【0784】 Step 5: 【0785】 The terminal provides the user with guidance in the form of audio and visual information based on route information received from the server. Guidance is generated using a speech synthesis engine, and a route map is displayed on the screen. The input is the generated evacuation route information, and the output is a tailored guidance message for the user. This process includes adjusting the voice tone according to the user's emotions. 【0786】 Step 6: 【0787】 The server continuously acquires new information and updates evacuation routes in response to changing circumstances. This includes receiving new data in real time and recalculating existing evacuation routes. The input is the latest information dataset, and the output is updated evacuation route information. This process includes route recalculation for sealed-off areas and newly designated hazard zones. 【0788】 (Application Example 2) 【0789】 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". 【0790】 In times of disaster, flexible guidance that takes into account individual emotional states and real-time changing circumstances is necessary for users to evacuate safely and quickly. However, conventional systems only provide fixed guidance without considering emotional states, which has the problem of failing to alleviate the psychological burden on users. 【0791】 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. 【0792】 In this invention, the server includes emotion recognition means, real-time information acquisition means, and digital map generation means. This makes it possible to generate evacuation routes in real time according to the user's emotional state and provide adaptive guidance. 【0793】 "Acquisition methods" refer to methods for collecting necessary data in real time from external information sources and sensors. 【0794】 An "integration method" is a means of integrating diverse data acquired and transforming it into information that is useful to the user. 【0795】 A "generation method" is used to create appropriate evacuation routes and instructions based on integrated information. 【0796】 "Guidance means" refers to methods of conveying generated information to the user, providing guidance using audio or visual information. 【0797】 "Update mechanisms" refer to methods for revising existing information in response to changes in circumstances or the acquisition of new data, thereby providing the latest instructions. 【0798】 "Emotion recognition means" are devices used to analyze a user's emotional state through audio and visual feedback. 【0799】 A "real-time information acquisition method" is a means of quickly acquiring various types of information at the present time and reflecting them in the system. 【0800】 A "digital map generation method" is a system that generates digital maps using the latest geographic information and uses them for route guidance. 【0801】 "Flexible guidance adjustment means based on diverse conditions" refers to a system that changes the content of guidance according to the user's emotional state and circumstances, in order to provide optimal information. 【0802】 The system implementing this invention includes means for acquiring information, integrating information, generating information, providing guidance, updating information, recognizing emotions, acquiring real-time information, generating digital maps, and providing flexible guidance adjustment means based on various states. Through cooperation between the server, terminals, and users, it supports safe and effective evacuation. 【0803】 The server obtains weather and traffic information from external APIs and acquires the user's current location information using GPS from their smartphone. Furthermore, it analyzes the user's emotional state from their voice and facial expression data using emotion recognition technology. Voice analysis libraries such as EmotionAPI are used for emotion recognition. 【0804】 Based on the acquired information, the server generates a digital map and calculates appropriate evacuation routes using an AI model. The guidance for these generated routes is adjusted according to the user's emotional state. For example, if the user is deemed anxious, the device provides a reassuring message in a calm voice. The tone and content of the messages can be flexibly changed during the guidance process. 【0805】 Through real-time information acquisition, the server recalculates evacuation routes each time new information is obtained, providing users with the latest guidance. The aim is to make evacuations safer and smoother. 【0806】 Specific example: When a user launches the app on their smartphone during an evacuation drill, the server sends the optimal evacuation route based on their current location and the latest disaster information. Emotion recognition allows the app to display a message such as, "Please calm down, we will now begin guiding you to the nearest evacuation center," if the user appears to be losing their composure. 【0807】 An example of a prompt for a generative AI model would be an instruction such as, "If the user's emotional state is anxious, generate a reassuring guidance message." Based on this prompt, the model will provide an appropriate message. 【0808】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0809】 Step 1: 【0810】 The server uses external APIs to obtain weather and traffic information. This allows it to collect basic data for understanding disaster situations. It sends external API access requests as input and obtains weather and traffic data as output. Based on this data, it analyzes the current situation and proceeds to the next step. 【0811】 Step 2: 【0812】 The device obtains the user's current location using the GPS function of their smartphone. This allows the system to obtain the user's precise location information. The input is the signal from the smartphone's GPS sensor, and the output is the user's location coordinates. Based on this location information, the system proceeds to generate an evacuation route. 【0813】 Step 3: 【0814】 The device analyzes the user's voice data using emotion recognition to identify their emotional state. The user's voice input is fed into a voice analysis library such as EmotionAPI, and emotional state information is obtained as output. This allows for real-time monitoring of the user's psychological state. 【0815】 Step 4: 【0816】 The server integrates collected location information, external data, and the user's emotional state to generate the optimal evacuation route using a generative AI model. By using the integrated data as input and feeding that data into the generative AI model, it obtains a safe and psychologically less stressful evacuation route as output. 【0817】 Step 5: 【0818】 The terminal adjusts the generated evacuation route based on the user's emotional state and provides voice and visual guidance. Inputs are the generated evacuation route and emotional data, which are then used by speech synthesis software to generate messages. Outputs are visual information and voice guidance displayed to the user. 【0819】 Step 6: 【0820】 The server uses real-time information acquisition methods to detect new disaster information and changes in traffic conditions, and recalculates evacuation routes as needed. The input is new data, and existing routes are evaluated based on this data. The output is the updated route. Through this process, users are always guided to the optimal evacuation method. 【0821】 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. 【0822】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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. 【0823】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0824】 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. 【0825】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0826】 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. 【0827】 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. 【0828】 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. 【0829】 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." 【0830】 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. 【0831】 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. 【0832】 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. 【0833】 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. 【0834】 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. 【0835】 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. 【0836】 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. 【0837】 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. 【0838】 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. 【0839】 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. 【0840】 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. 【0841】 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. 【0842】 The following is further disclosed regarding the embodiments described above. 【0843】 (Claim 1) 【0844】 means of acquisition, 【0845】 Integration means, 【0846】 means of generation, 【0847】 Means of guidance, 【0848】 Update methods, 【0849】 A system that includes this. 【0850】 (Claim 2) 【0851】 The system according to claim 1, which determines the current location based on acquired location information. 【0852】 (Claim 3) 【0853】 The system according to claim 1, which presents evacuation routes generated in real time using audio and visual information. 【0854】 "Example 1" 【0855】 (Claim 1) 【0856】 A means of acquiring information from an external source and storing it in a database, 【0857】 An integration means for creating a consistent set of information by combining information obtained from multiple sources, 【0858】 A generation means for generating evacuation routes based on integrated information, 【0859】 A guidance system that guides the user through the generated evacuation route using audio and visual information, 【0860】 An update mechanism that updates information in real time and recalculates the route as needed, 【0861】 A system that includes this. 【0862】 (Claim 2) 【0863】 The system according to claim 1, which determines the current geographical location based on acquired digitized location information. 【0864】 (Claim 3) 【0865】 The system according to claim 1, which presents evacuation routes calculated in real time using voice and visual information and provides movement instructions to the user. 【0866】 "Application Example 1" 【0867】 (Claim 1) 【0868】 Data collection means, 【0869】 Information integration means, 【0870】 Route generation means, 【0871】 User guidance methods, 【0872】 Information update methods, 【0873】 Information systems including 【0874】 (Claim 2) 【0875】 The information system according to claim 1, which determines the location based on data acquired in real time and calculates the optimal route. 【0876】 (Claim 3) 【0877】 The information system according to claim 1, which presents a real-time generated route using audio and visual information, and provides intuitive instructions to the user. 【0878】 "Example 2 of combining an emotion engine" 【0879】 (Claim 1) 【0880】 Means of obtaining information, 【0881】 Means for integrating information, 【0882】 Means for generating a route, 【0883】 Means of providing guidance, 【0884】 Means of updating information, 【0885】 Means of recognizing emotions, 【0886】 A system that includes this. 【0887】 (Claim 2) 【0888】 The system according to claim 1, which identifies the current location based on acquired location information and analyzes the emotional state. 【0889】 (Claim 3) 【0890】 The system according to claim 1, which presents evacuation routes generated in real time using audio and visual information, and adjusts the guidance content according to the emotional state. 【0891】 "Application example 2 of combining emotional engines" 【0892】 (Claim 1) 【0893】 means of acquisition, 【0894】 Integration means, 【0895】 means of generation, 【0896】 Means of guidance, 【0897】 Update methods, 【0898】 Means of recognizing emotions, 【0899】 Means for acquiring real-time information, 【0900】 Digital map generation means and 【0901】 Flexible guidance adjustment means based on diverse conditions, 【0902】 A system that includes this. 【0903】 (Claim 2) 【0904】 The system according to claim 1, which generates an optimized evacuation route based on acquired location information, collected external data, and emotional information. 【0905】 (Claim 3) 【0906】 The system according to claim 1, which adaptively presents evacuation routes generated in real time using audio and visual information, and adjusts them based on the user's emotional state. [Explanation of symbols] 【0907】 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

[Claim 1] Means of acquiring location information, traffic information, weather information, disaster information, etc. An integration method that centrally gathers various acquired information and prepares it in a format that can be analyzed, A generation means for generating the optimal evacuation route based on integrated data, A guidance means that presents the generated evacuation route to the user through audio or visual information, A means of updating the generated routes in real time in response to changes in the environment and circumstances, and making appropriate changes as needed. A system that includes this. [Claim 2] The system according to claim 1, which determines the current location based on acquired location information. [Claim 3] The system according to claim 1, which presents evacuation routes generated in real time using audio and visual information.

Images