system

Abstract

We provide the system. [Solution] A means for obtaining location information to obtain the user's current location, An information gathering method that collects information on disasters, traffic, and weather from an external database and determines the occurrence of an emergency based on the user's current location, A calculation means for calculating the optimal evacuation route or alternative means of transportation to respond to the aforementioned emergency, A notification means for sending emergency notifications to users based on the aforementioned evacuation route or alternative means of transportation, A booking system that automatically arranges evacuation and accommodation reservations 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, which is 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 chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a problem that it is difficult for tourists and local residents to grasp prompt and accurate countermeasures when encountering emergencies such as natural disasters and traffic delays. In particular, information collection for responding to situations that change in real time and the selection of appropriate evacuation routes and alternative means based on it impose a great burden on users. Also, it is necessary to provide information in an easy-to-understand form to international users who speak multiple languages.

Means for Solving the Problems

[0005] <000003This invention includes location information acquisition means for obtaining the user's current location, and information collection means for collecting information on disasters, traffic, and weather from an external database and determining an emergency based on the user's location. Furthermore, it includes calculation means for calculating the optimal evacuation route and alternative means of transportation to deal with the emergency, and notification means for sending emergency notifications to the user. In addition, by providing reservation means for automatically arranging evacuation and accommodation reservations as needed, it enables a quick and accurate response. By using a multilingual display interface, it can accommodate international users and ensure that they can easily understand the information. Moreover, by providing customized instructions that take into account the user's behavioral history, it realizes support that is more tailored to individual needs.

[0006] "Location information acquisition means" refers to technical means for detecting the user's current location.

[0007] "Information gathering means" refers to technical means of collecting information related to disasters, traffic, weather, etc., from external databases.

[0008] "Calculation means" refers to technical means for calculating the optimal evacuation route and alternative means of transportation based on collected data.

[0009] "Notification means" refers to technical means of communicating information and instructions regarding emergencies to users.

[0010] "Reservation methods" refer to technological means for automatically arranging necessary transportation and accommodation for evacuation.

[0011] A "multilingual display interface" is a screen display technology that presents information to users who understand different languages.

[0012] "Customized instructions" refer to providing optimized information and instructions based on the user's behavioral history and individual needs. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

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

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

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is configured as a system that allows users to quickly perform optimal evacuation and response actions appropriate to the situation. It consists of three main components: a server, a terminal, and a user.

[0035] The server retrieves information from multiple external databases. This includes weather data, traffic conditions, and disaster information, which are collected in real time and stored in the database. The server receives location information from users and compares it with the current geographical situation to determine if an emergency has occurred. Based on this determination, it calculates evacuation routes and alternative measures to avoid the impact.

[0036] The device acquires the user's location via GPS and transmits it to the server. Furthermore, based on emergency notifications received from the server, it issues instructions to the user via voice or text. Multilingual support ensures that information is communicated without difficulty to users who speak different languages. In addition, the device tracks the user's movements and sends that information back to the server, enabling the provision of more appropriate countermeasures.

[0037] Users operate this system on a terminal using their regular devices. In the event of an emergency, they follow instructions from the terminal to take evacuation actions or utilize alternative means of transport. Depending on the user's choices, the server can make further arrangements, such as booking a taxi or rebooking a hotel. This allows users to act with peace of mind without experiencing unnecessary stress.

[0038] As a concrete example, consider the case of an earthquake. This system receives earthquake reports, analyzes the affected area in real time, and checks if the user is within the affected area. If they are within the affected area, the server immediately calculates the direction and location of evacuation and sends that information to the terminal. Based on this information, the terminal prompts the user to take safe action in response to the earthquake. By following these instructions, the user can evacuate quickly and safely.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user starts up the device and enables location services. The device uses GPS to obtain the user's current location.

[0042] Step 2:

[0043] The device sends the acquired location information to the server. The server receives this location information and compares it with the latest information in its database.

[0044] Step 3:

[0045] The server analyzes weather, traffic, and disaster information collected from an external database to determine if the user's location is within the area affected by the emergency.

[0046] Step 4:

[0047] If an emergency is detected, the server calculates the optimal evacuation route and alternative transportation options. This calculation takes into account the user's travel history and current traffic conditions.

[0048] Step 5:

[0049] The server sends the calculation results to the terminal. Based on this information, the terminal provides visual and audible notifications to the user.

[0050] Step 6:

[0051] Users check the evacuation route and alternative means of transport information provided on their devices and begin taking action according to the instructions.

[0052] Step 7:

[0053] If necessary, the server automatically makes arrangements such as booking a taxi or re-securing accommodation. The status of these arrangements is notified to the terminal, providing the user with the latest information.

[0054] (Example 1)

[0055] 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."

[0056] In modern society, taking swift and appropriate evacuation actions in the event of a disaster or unforeseen accident is extremely important. However, current technology makes it difficult to provide accurate evacuation routes and alternative means in real time and in multiple languages, and customized information tailored to individual users is also insufficient. This can lead to anxiety and confusion among international travelers and users with diverse backgrounds during emergencies.

[0057] 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.

[0058] In this invention, the server includes means for acquiring the user's location information, means for acquiring information from external sources to determine an emergency situation, and means for generating prompt sentences using a generative AI model to create sentences for instructing a rapid response. This enables rapid and appropriate evacuation guidance and support tailored to the individual needs of the user when they face an emergency.

[0059] "Means of acquiring location information" refers to the technologies and devices necessary to determine the user's current location, and this includes functions that measure location using GPS and Wi-Fi data.

[0060] "Means of obtaining information from information sources" refers to technologies and devices for collecting the latest information on disasters, traffic, and weather from external databases and APIs.

[0061] "Means for determining an emergency situation" refers to technologies and methods for analyzing acquired information and user location data to determine whether a disaster or crisis is occurring.

[0062] "Methods using generative AI models" refer to methods that utilize artificial intelligence technology, such as natural language processing, to automatically generate instruction texts to be provided to the user.

[0063] "Means for creating instructions for rapid response" refers to technologies and methods aimed at promptly providing users with guidance for evacuation and ensuring their safety using generated instructional texts.

[0064] A "multilingual interface" refers to a system that automatically translates and displays information to provide appropriate information to users who speak different languages.

[0065] "Customized instructions that take into account behavioral history" refers to a method of providing information and instructions optimized for each user based on their past behavior and preferences.

[0066] This system is an emergency response system designed to ensure user safety and consists primarily of three elements: servers, terminals, and users.

[0067] The server collects disaster, traffic, and weather information in real time from external sources. These sources include publicly available weather APIs, map APIs, and disaster alert services. Based on the collected information, the server determines whether an emergency has occurred and whether the user may be affected. In the event of an emergency, the server uses a generative artificial intelligence model to generate necessary prompt messages and create instructions that include appropriate evacuation routes and alternative transportation options.

[0068] The device obtains the user's current location via the GPS system and transmits it to the server. It also notifies the user of instructions received from the server in the form of voice or text. A multilingual interface is employed, and information is translated according to the user's language settings for accurate communication. Furthermore, the device considers the user's behavioral history and sends feedback to the server to generate individually customized instructions.

[0069] Users operate the system using their usual devices, such as smartphones or tablets. In the event of an emergency, they receive an alert from their device, allowing them to follow the instructions and take evacuation action. This enables users to evacuate quickly and safely and receive the necessary assistance. For example, in the event of an earthquake, the server immediately analyzes earthquake information, calculates a safe evacuation route, sends it to the device, and provides the user with voice guidance based on the results.

[0070] An example of a prompt message would be, "Calculate the optimal route for the user to safely evacuate from their current location and generate instructions in Japanese." This prompt message allows the server to quickly provide appropriate instructions tailored to the user's situation.

[0071] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0072] Step 1:

[0073] The server collects disaster, traffic, and weather information from external sources. Specifically, the server sends requests to weather APIs, map APIs, and disaster alert services to obtain the latest data. This information is stored in a database on the server and used to determine the status of an emergency. Input requires access to API endpoints and necessary authentication information, while output provides various types of information collected in real time.

[0074] Step 2:

[0075] The device uses GPS to obtain the user's current location and sends this data to the server. Location information is collected through the device's sensors, encrypted according to a protocol, and transmitted. The input is raw data about the user's current location, and the output is location information converted from this data into a format usable by the server.

[0076] Step 3:

[0077] The server uses collected information and the user's location data to determine whether an emergency has occurred. In this process, an AI algorithm compares weather and traffic data with earthquake reports to determine if the user is involved in an emergency. The algorithm's input is information stored in the database and the user's location data, and its output is a flag indicating whether an emergency has occurred.

[0078] Step 4:

[0079] The server uses a generative AI model to generate prompt messages and provide appropriate instructions to the user. These prompt messages suggest the best evacuation route or alternative means based on the user's situation and are sent to the terminal in voice or text format. Inputs include an emergency flag and the user's location information, while output is a customized instruction message.

[0080] Step 5:

[0081] The terminal notifies the user of instructions received from the server. Notifications are delivered via speech synthesis or text messages, and are appropriately translated according to the user's language settings through a multilingual support system. The input is the instruction text from the server, and the output is the notification in a language understandable to the user.

[0082] Step 6:

[0083] The user follows the instructions on the device and moves along the evacuation route. During this process, the device continuously tracks the user's location and sends feedback to the server, which keeps the situation updated in real time. The input is data of the user's actions as they follow the instructions, and the output is updated location information as feedback to the server.

[0084] (Application Example 1)

[0085] 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."

[0086] In recent years, urbanization and the increasing frequency of natural disasters have made ensuring safety in cities a critical issue. Traditional evacuation orders are based on limited information and only provide general guidance, lacking the ability to provide optimal evacuation information tailored to individual circumstances in real time. As a result, it is difficult for residents and visitors to quickly and safely avoid danger.

[0087] 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.

[0088] In this invention, the server includes a device for acquiring location information, a device for collecting information on the environment, means of transportation, and weather from external sources and for evaluating dangerous situations based on the user's location, and a device for calculating the optimal evacuation route or alternative means of transportation to deal with the dangerous situation. This makes it possible for residents and visitors in a city to obtain up-to-date and individualized evacuation routes in real time.

[0089] A "device for acquiring location information" is a device that has the function of identifying the user's current location and transmitting it to a server as digital data.

[0090] A "device for collecting information on the environment, means of transportation, and weather from external sources and evaluating dangerous situations based on the user's location" is a system that analyzes data collected from various databases and sensors to identify and evaluate emergencies related to the user's current location.

[0091] A "device for calculating optimal evacuation routes and alternative means of transportation" is a device that executes an algorithm to calculate the most efficient and safest travel route based on collected data and risk assessment, in order to ensure the safety of the user.

[0092] The system for implementing this invention is formed by three main components: a server, a terminal, and a user.

[0093] The server acquires real-time data on the environment, transportation, and weather from various external sources. Specifically, it connects to diverse databases such as weather data, traffic data, and disaster information, and manages them in an integrated manner. Using this data, the server assesses emergencies and calculates appropriate evacuation routes and alternative transportation options. Advanced algorithms are used in these calculations to provide users with the safest and most efficient evacuation routes.

[0094] The terminal's primary role is to first acquire the user's current location using GPS and transmit that information to the server. As the user moves, the terminal continuously feeds back this location information to the server, enabling a dynamic reassessment of the optimal evacuation route. The terminal also notifies the user of evacuation instructions and warnings sent from the server in multiple languages. This ensures consistent information provision to users of various nationalities.

[0095] Users operate the system using devices such as mobile phones and tablets. In the event of an emergency, they are required to follow instructions from their devices and begin a rapid evacuation. The devices also record the user's activity history and provide a function to individually customize evacuation information based on that history. This customization makes it easy to create an optimal evacuation plan that takes into account the user's past behavior patterns.

[0096] For example, in the event of a sudden flood in a city, this system can instantly analyze the information and present users with safe evacuation routes. Furthermore, when evacuation is necessary, the server can automatically arrange taxis and book accommodations. This minimizes the stress users experience while supporting rapid evacuation.

[0097] To implement this functionality, use the following prompt statements for the model.

[0098] Example input prompts for a generative AI model:

[0099] Development of an app that provides users with real-time information and safe evacuation routes in the event of a disaster in an urban area.

[0100] Required information: User's location, latest weather data, traffic conditions, and location of evacuation shelters.

[0101] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0102] Step 1:

[0103] The device obtains the user's current location using GPS functionality. The input is GPS data, and the output is the user's latitude and longitude information. This ensures accurate location information.

[0104] Step 2:

[0105] The device sends the acquired location information to the server. The input is the latitude and longitude data acquired earlier, and the output is the server receiving this data. This transmission allows the server to determine the user's current location.

[0106] Step 3:

[0107] The server collects environmental, transportation, and weather data from external sources. Input is real-time data from diverse databases, and output is an integrated dataset for analysis. This allows the server to aggregate information for assessing user location-related emergencies.

[0108] Step 4:

[0109] The server uses the user's location information and collected data to assess the likelihood of an emergency. The input is location information and an integrated dataset, and the output is a determination of whether or not an emergency has occurred. This step determines the need for evacuation.

[0110] Step 5:

[0111] The server calculates the optimal evacuation route or alternative mode of transportation in the event of an emergency. Inputs are the determination of the emergency and disaster information, and output is safe and efficient route information. The server can use an algorithm to provide the user with the optimal route.

[0112] Step 6:

[0113] The server sends calculated evacuation routes and alternative transportation information to the terminal. The input is the calculation result, and the output is when the terminal receives it and notifies the user.

[0114] Step 7:

[0115] The terminal displays evacuation instructions to the user based on notifications from the server. Input is evacuation information from the server, and output is a visual or audio notification to the user. This allows the user to take quick and appropriate action.

[0116] Step 8:

[0117] The server makes additional arrangements as needed, including, for example, arranging a taxi or booking accommodation. Input is information based on the user's requests and behavioral patterns, and output is a confirmation of the arrangements. This step allows the user to receive assistance in acting more safely.

[0118] 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.

[0119] This invention is a system that supports users in providing timely and optimal responses, and is characterized by providing personalized support according to the user's emotional state by combining it with an emotion engine. This system consists of four main components: a server, a terminal, an emotion engine, and a user.

[0120] The server collects weather, traffic, and disaster information from multiple external databases and processes it in real time. It receives the user's location information and determines whether an emergency exists based on this. Furthermore, it calculates evacuation routes and alternative transportation options, and determines the most appropriate notification content for the user based on the results of the emotion engine's analysis.

[0121] The device uses GPS to obtain the user's current location and transmits that location information to a server. It also works in conjunction with an emotion engine to analyze the user's emotions in real time based on their voice and actions. This enables support to alleviate the user's tension and anxiety.

[0122] The emotion engine uses sensors to detect the user's facial expressions and voice, and analyzes the resulting emotional data. The analysis results are sent to the terminal and server to adjust the content and method of emergency notifications. This process enables the provision of detailed support tailored to each user's individual situation.

[0123] Users can access this system via their regular devices and receive support tailored to their emotional state. For example, in an emergency, if a user is feeling anxious, the system can provide reassuring instructions.

[0124] As a concrete example, consider the case of a large-scale natural disaster. The server analyzes the extent of the disaster's impact and calculates the optimal evacuation route based on that information. If the emotion engine detects that the user is in a state of confusion, the terminal changes the notification content to something stable and reassuring, and issues instructions to encourage the user to make calm decisions. This enables the user to evacuate appropriately and safely.

[0125] The following describes the processing flow.

[0126] Step 1:

[0127] The user activates the device and enables location services and the emotion engine. The device uses GPS to obtain the user's current location and the emotion engine analyzes the user's voice and facial expressions.

[0128] Step 2:

[0129] The device transmits acquired location and sentiment data to the server. The server receives this information in real time and compares it with weather, traffic, and disaster information in its database.

[0130] Step 3:

[0131] The server determines whether an emergency has occurred based on the user's current location. If an emergency has occurred, it calculates the optimal evacuation route and alternative means of transportation.

[0132] Step 4:

[0133] The emotion engine analyzes the user's emotional state and sends the results to the server. The server adjusts the notification content based on the emotion data. Specifically, if the user is feeling anxious, it generates instructions that provide reassurance.

[0134] Step 5:

[0135] The server sends calculated evacuation routes and notification content to the terminal. The terminal notifies the user of the received information via voice and visual means, prompting them to take emergency action.

[0136] Step 6:

[0137] The user begins evacuation actions and the use of alternative transportation according to instructions from the device. The device continuously monitors the user's location and emotional state and sends additional information to the server as needed.

[0138] Step 7:

[0139] If necessary, the server will devise further support measures for the terminal user, such as booking taxis or rebooking accommodations. This will allow the user to complete their evacuation safely and with peace of mind.

[0140] (Example 2)

[0141] 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".

[0142] While systems already exist to support user actions during disasters and emergencies, these systems are limited in their ability to provide appropriate support because they cannot take into account the user's emotional state. This challenge includes the fact that the information provided may not be sufficiently reassuring to users who are feeling anxious or frightened.

[0143] 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.

[0144] In this invention, the server includes information gathering means that collect information on the environment, movement, and weather from an external database and determine the occurrence of an emergency based on the user's current location; emotion analysis means that perform emotion analysis and adjust the content of emergency notifications according to the user's emotional state based on the analysis results; and notification means that send emergency notifications to the user. As a result, the user can receive information that is appropriate to their emotional state and act appropriately with a sense of security.

[0145] "Location information acquisition means" refers to devices or technologies used to determine a user's current location, and typically involves collecting location data using GPS functionality.

[0146] "Information gathering means" refers to devices and technologies that acquire information on the environment, movement, and weather from external databases and gather information necessary for users to make informed decisions.

[0147] "Calculation means" refers to devices and technologies that calculate the optimal evacuation route or alternative means for the user based on acquired information.

[0148] "Emotional analysis means" refers to devices and technologies that analyze a user's voice and actions to estimate the user's emotional state, and the results are used to adjust notification content.

[0149] "Notification means" refers to devices or technologies used to provide information to users, such as sending notifications via text messages or voice.

[0150] "Reservation methods" refer to devices or technologies that automatically arrange evacuation routes and accommodations as needed.

[0151] This invention is a system for providing appropriate information according to the user's emotional state. The system consists of four main elements: a server, a terminal, an emotion engine, and the user.

[0152] The server collects and processes environmental, movement, and weather information in real time from multiple external databases. This includes databases from the Japan Meteorological Agency, traffic management systems, and disaster information systems. The server combines the collected information with the user's location to determine whether an emergency has occurred. If action is required, it calculates evacuation routes and alternative transportation options, and determines the most appropriate notification content for the user based on the analysis results of the emotion engine.

[0153] The device uses the GPS built into the user's device to obtain the user's current location and transmits that location information to the server. Furthermore, the device works in conjunction with an emotion engine and uses sensors such as microphones and cameras to analyze the user's voice and actions in real time. This allows the device to understand the user's emotional state and provide data to the server to adjust notification content as needed.

[0154] The emotion engine analyzes the user's facial expressions and voice data acquired from sensors to estimate the user's emotional state with high accuracy. The analysis results are sent to the server and terminal and used to adjust the content and method of emergency notifications.

[0155] Users can utilize this system through their everyday devices to receive support tailored to their individual emotional state. Specifically, even in emergencies, they can take calm action based on the reassuring information provided by the system. For example, in the event of a large-scale natural disaster, the server analyzes the extent of the disaster's impact and calculates the optimal evacuation route. When the emotion engine detects that the user is feeling anxious, the device changes the notification content to something reassuring, encouraging the user to make calm decisions.

[0156] A concrete example of a related prompt message would be to input the instruction, "Generate the optimal evacuation instructions based on the user's emotional state," into the AI ​​model. In this way, the system can respond flexibly to a variety of situations and provide a safe environment for the user.

[0157] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0158] Step 1:

[0159] The device uses its built-in GPS module to obtain the user's current location in real time. The acquired location information is sent from the device to the server. Specifically, the location information is updated every 15 seconds.

[0160] Step 2:

[0161] The server collects environmental, movement, and weather information in real time from external databases. The server obtains data from the Japan Meteorological Agency, traffic management systems, and disaster information systems via APIs and analyzes it. The resulting organized information is then combined with user location information and used for subsequent processing.

[0162] Step 3:

[0163] The server determines whether an emergency has occurred based on the user's location information and other collected data. This process uses a Geographic Information System (GIS) to determine if the user's current location is within the disaster's affected area. The result of this determination indicates whether there is an urgent need.

[0164] Step 4:

[0165] The device uses an emotion engine to analyze the user's voice and actions in real time. It uses a combination of speech recognition and image analysis technologies to estimate the user's emotional state. The input for this analysis is the user's voice and facial expression data, and the output is the result of the emotional state assessment.

[0166] Step 5:

[0167] The server uses the sentiment analysis results sent from the sentiment engine to determine the content of the emergency notification. If the user is feeling anxious, it uses a generative AI model to generate a reassuring notification. An example of a prompt is, "Generate a message to alleviate the user's anxiety." The output is the content of the notification to be sent to the user.

[0168] Step 6:

[0169] Users check notifications received from their devices and act according to the instructions. Specifically, this includes actions based on instructions to move to a safe place or to stay calm. Notifications are delivered via text message or voice, and actions are triggered after the user acknowledges them.

[0170] (Application Example 2)

[0171] 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".

[0172] In modern urban environments, it is crucial to provide users with prompt and appropriate evacuation information in the event of sudden emergencies or natural disasters. However, simply issuing uniform notifications without considering users' emotional states is insufficient to adequately alleviate anxiety and confusion. In addition, diverse means of providing information that accommodate linguistic and cultural differences are required. This invention provides a system that enables flexible information provision tailored to users' emotional states in order to solve these problems.

[0173] 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.

[0174] In this invention, the server includes location information acquisition means for obtaining the user's current location, information collection means for collecting information on weather, traffic, and disasters from external information sources and determining the occurrence of an emergency based on the user's location, and calculation means for monitoring the user's emotional state in real time using speech recognition and facial expression analysis and calculating the optimal evacuation route or alternative means of transportation in response to an emergency based on the results. This makes it possible to provide instructions that give the user a sense of security according to their emotional state.

[0175] "Location information acquisition means" is a general term for technologies and devices used to accurately obtain a user's current location.

[0176] "Information gathering means" refers to elements that collect data on weather, traffic, and disasters from external sources and have the function of determining the occurrence of an emergency in relation to the user's location.

[0177] "Emotional state" refers to the user's psychological or emotional state, and is measured through voice and facial expression analysis.

[0178] "Speech recognition" is a technology that analyzes a user's spoken words and converts them into text information, and is used to understand emotions.

[0179] "Facial expression analysis" is a technology that estimates a user's emotions from their facial expressions and is used for real-time emotion monitoring.

[0180] A "computational tool" is a technology that has the function of calculating the optimal evacuation route or alternative means of transportation based on the user's location and emotional state.

[0181] "Notification methods" is a general term for technologies and interfaces used to communicate necessary information and instructions to users in an appropriate format.

[0182] A "procedure management system" is an element that has the function of automatically arranging evacuation and accommodation reservations as needed.

[0183] This invention constructs a system that enables the provision of optimal information based on the user's emotional state. The following describes how this system is implemented.

[0184] The server receives GPS location information transmitted from the user's device and, in conjunction with an external information database, collects weather, traffic, and disaster-related data in real time. Using this data, the server determines whether an emergency has occurred based on the user's location and calculates evacuation routes and alternative transportation options accordingly.

[0185] The device is equipped with voice recognition and facial expression analysis technology, which monitors the user's emotional state in real time. If the user is feeling tense or anxious, the server uses the emotional data obtained from the device to generate a reassuring notification.

[0186] The notification system provides users with optimal instructions that take emotional information into account. For example, if a sudden weather change occurs during a large-scale urban event, the system can send a message to the user's device such as, "We have confirmed the route from your current location to the nearest shelter. Please proceed calmly."

[0187] In this process, a generative AI model is used to automatically generate customized instruction prompts for each user. An example of a prompt might be, "Create guidance to support optimal evacuation actions based on current weather conditions and the user's emotional state." In this way, it is possible to provide flexible and appropriate emergency responses to users.

[0188] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0189] Step 1:

[0190] The server receives GPS data transmitted from the terminal and determines the user's current location. It analyzes the GPS data as input and generates output as geographical information. This allows the server to determine the user's precise location.

[0191] Step 2:

[0192] The server uses location data to connect with external information sources and obtain the latest data on weather, traffic, and disasters. The input is location data, and by making API calls and other actions based on this data, it obtains relevant environmental information as output. This allows the user to understand the situation around them.

[0193] Step 3:

[0194] The device monitors the user's emotional state using voice recognition and facial expression analysis. Audio and video data from sensors are used as input, which is then analyzed to output emotional information. This analysis allows for real-time understanding of the user's current emotional state.

[0195] Step 4:

[0196] The server integrates collected environmental information and emotional information from terminals to determine whether an emergency has occurred. Based on the environmental and emotional information as input, it uses logic to determine if an emergency has occurred and outputs an indicator of the degree of urgency.

[0197] Step 5:

[0198] The server calculates the optimal evacuation route and alternative transportation based on the urgency level. The input consists of an urgency index and location information, which is analyzed to output the most appropriate route for the user. This determines the specific means of transportation needed if an action is required.

[0199] Step 6:

[0200] The device uses a generative AI model to generate notification content as prompts that respond to the user's emotions. Based on emotional information and evacuation routes as input, it outputs notification messages that provide reassurance to the user. By generating prompts, notifications optimized for the user are created.

[0201] Step 7:

[0202] Users receive notifications from their devices and act calmly based on them. The outputted notification message serves as input, and users take appropriate action or move accordingly. This allows them to act safely and with a sense of security.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] [Second Embodiment]

[0207] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0208] 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.

[0209] 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).

[0210] 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.

[0211] 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.

[0212] 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).

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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".

[0219] This invention is configured as a system that allows users to quickly perform optimal evacuation and response actions appropriate to the situation. It consists of three main components: a server, a terminal, and a user.

[0220] The server retrieves information from multiple external databases. This includes weather data, traffic conditions, and disaster information, which are collected in real time and stored in the database. The server receives location information from users and compares it with the current geographical situation to determine if an emergency has occurred. Based on this determination, it calculates evacuation routes and alternative measures to avoid the impact.

[0221] The device acquires the user's location via GPS and transmits it to the server. Furthermore, based on emergency notifications received from the server, it issues instructions to the user via voice or text. Multilingual support ensures that information is communicated without difficulty to users who speak different languages. In addition, the device tracks the user's movements and sends that information back to the server, enabling the provision of more appropriate countermeasures.

[0222] Users operate this system on a terminal using their regular devices. In the event of an emergency, they follow instructions from the terminal to take evacuation actions or utilize alternative means of transport. Depending on the user's choices, the server can make further arrangements, such as booking a taxi or rebooking a hotel. This allows users to act with peace of mind without experiencing unnecessary stress.

[0223] As a concrete example, consider the case of an earthquake. This system receives earthquake reports, analyzes the affected area in real time, and checks if the user is within the affected area. If they are within the affected area, the server immediately calculates the direction and location of evacuation and sends that information to the terminal. Based on this information, the terminal prompts the user to take safe action in response to the earthquake. By following these instructions, the user can evacuate quickly and safely.

[0224] The following describes the processing flow.

[0225] Step 1:

[0226] The user starts up the device and enables location services. The device uses GPS to obtain the user's current location.

[0227] Step 2:

[0228] The device sends the acquired location information to the server. The server receives this location information and compares it with the latest information in its database.

[0229] Step 3:

[0230] The server analyzes weather, traffic, and disaster information collected from an external database to determine if the user's location is within the area affected by the emergency.

[0231] Step 4:

[0232] If an emergency is detected, the server calculates the optimal evacuation route and alternative transportation options. This calculation takes into account the user's travel history and current traffic conditions.

[0233] Step 5:

[0234] The server sends the calculation results to the terminal. Based on this information, the terminal provides visual and audible notifications to the user.

[0235] Step 6:

[0236] Users check the evacuation route and alternative means of transport information provided on their devices and begin taking action according to the instructions.

[0237] Step 7:

[0238] If necessary, the server automatically makes arrangements such as booking a taxi or re-securing accommodation. The status of these arrangements is notified to the terminal, providing the user with the latest information.

[0239] (Example 1)

[0240] 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."

[0241] In modern society, taking swift and appropriate evacuation actions in the event of a disaster or unforeseen accident is extremely important. However, current technology makes it difficult to provide accurate evacuation routes and alternative means in real time and in multiple languages, and customized information tailored to individual users is also insufficient. This can lead to anxiety and confusion among international travelers and users with diverse backgrounds during emergencies.

[0242] 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.

[0243] In this invention, the server includes means for acquiring the user's location information, means for acquiring information from external sources to determine an emergency situation, and means for generating prompt sentences using a generative AI model to create sentences for instructing a rapid response. This enables rapid and appropriate evacuation guidance and support tailored to the individual needs of the user when they face an emergency.

[0244] "Means of acquiring location information" refers to the technologies and devices necessary to determine the user's current location, and this includes functions that measure location using GPS and Wi-Fi data.

[0245] "Means of obtaining information from information sources" refers to technologies and devices for collecting the latest information on disasters, traffic, and weather from external databases and APIs.

[0246] "Means for determining an emergency situation" refers to technologies and methods for analyzing acquired information and user location data to determine whether a disaster or crisis is occurring.

[0247] "Methods using generative AI models" refer to methods that utilize artificial intelligence technology, such as natural language processing, to automatically generate instruction texts to be provided to the user.

[0248] "Means for creating instructions for rapid response" refers to technologies and methods aimed at promptly providing users with guidance for evacuation and ensuring their safety using generated instructional texts.

[0249] A "multilingual interface" refers to a system that automatically translates and displays information to provide appropriate information to users who speak different languages.

[0250] "Customized instructions that take into account behavioral history" refers to a method of providing information and instructions optimized for each user based on their past behavior and preferences.

[0251] This system is an emergency response system designed to ensure user safety and consists primarily of three elements: servers, terminals, and users.

[0252] The server collects disaster, traffic, and weather information in real time from external sources. These sources include publicly available weather APIs, map APIs, and disaster alert services. Based on the collected information, the server determines whether an emergency has occurred and whether the user may be affected. In the event of an emergency, the server uses a generative artificial intelligence model to generate necessary prompt messages and create instructions that include appropriate evacuation routes and alternative transportation options.

[0253] The device obtains the user's current location via the GPS system and transmits it to the server. It also notifies the user of instructions received from the server in the form of voice or text. A multilingual interface is employed, and information is translated according to the user's language settings for accurate communication. Furthermore, the device considers the user's behavioral history and sends feedback to the server to generate individually customized instructions.

[0254] Users operate the system using their usual devices, such as smartphones or tablets. In the event of an emergency, they receive an alert from their device, allowing them to follow the instructions and take evacuation action. This enables users to evacuate quickly and safely and receive the necessary assistance. For example, in the event of an earthquake, the server immediately analyzes earthquake information, calculates a safe evacuation route, sends it to the device, and provides the user with voice guidance based on the results.

[0255] An example of a prompt message would be, "Calculate the optimal route for the user to safely evacuate from their current location and generate instructions in Japanese." This prompt message allows the server to quickly provide appropriate instructions tailored to the user's situation.

[0256] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0257] Step 1:

[0258] The server collects disaster, traffic, and weather information from external sources. Specifically, the server sends requests to weather APIs, map APIs, and disaster alert services to obtain the latest data. This information is stored in a database on the server and used to determine the status of an emergency. Input requires access to API endpoints and necessary authentication information, while output provides various types of information collected in real time.

[0259] Step 2:

[0260] The device uses GPS to obtain the user's current location and sends this data to the server. Location information is collected through the device's sensors, encrypted according to a protocol, and transmitted. The input is raw data about the user's current location, and the output is location information converted from this data into a format usable by the server.

[0261] Step 3:

[0262] The server uses collected information and the user's location data to determine whether an emergency has occurred. In this process, an AI algorithm compares weather and traffic data with earthquake reports to determine if the user is involved in an emergency. The algorithm's input is information stored in the database and the user's location data, and its output is a flag indicating whether an emergency has occurred.

[0263] Step 4:

[0264] The server uses a generative AI model to generate prompt messages and provide appropriate instructions to the user. These prompt messages suggest the best evacuation route or alternative means based on the user's situation and are sent to the terminal in voice or text format. Inputs include an emergency flag and the user's location information, while output is a customized instruction message.

[0265] Step 5:

[0266] The terminal notifies the user of instructions received from the server. Notifications are delivered via speech synthesis or text messages, and are appropriately translated according to the user's language settings through a multilingual support system. The input is the instruction text from the server, and the output is the notification in a language understandable to the user.

[0267] Step 6:

[0268] The user follows the instructions on the device and moves along the evacuation route. During this process, the device continuously tracks the user's location and sends feedback to the server, which keeps the situation updated in real time. The input is data of the user's actions as they follow the instructions, and the output is updated location information as feedback to the server.

[0269] (Application Example 1)

[0270] 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."

[0271] In recent years, urbanization and the increasing frequency of natural disasters have made ensuring safety in cities a critical issue. Traditional evacuation orders are based on limited information and only provide general guidance, lacking the ability to provide optimal evacuation information tailored to individual circumstances in real time. As a result, it is difficult for residents and visitors to quickly and safely avoid danger.

[0272] 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.

[0273] In this invention, the server includes a device for acquiring location information, a device for collecting information on the environment, means of transportation, and weather from external sources and for evaluating dangerous situations based on the user's location, and a device for calculating the optimal evacuation route or alternative means of transportation to deal with the dangerous situation. This makes it possible for residents and visitors in a city to obtain up-to-date and individualized evacuation routes in real time.

[0274] A "device for acquiring location information" is a device that has the function of identifying the user's current location and transmitting it to a server as digital data.

[0275] A "device for collecting information on the environment, means of transportation, and weather from external sources and evaluating dangerous situations based on the user's location" is a system that analyzes data collected from various databases and sensors to identify and evaluate emergencies related to the user's current location.

[0276] A "device for calculating optimal evacuation routes and alternative means of transportation" is a device that executes an algorithm to calculate the most efficient and safest travel route based on collected data and risk assessment, in order to ensure the safety of the user.

[0277] The system for implementing this invention is formed by three main components: a server, a terminal, and a user.

[0278] The server acquires real-time data on the environment, transportation, and weather from various external sources. Specifically, it connects to diverse databases such as weather data, traffic data, and disaster information, and manages them in an integrated manner. Using this data, the server assesses emergencies and calculates appropriate evacuation routes and alternative transportation options. Advanced algorithms are used in these calculations to provide users with the safest and most efficient evacuation routes.

[0279] The terminal's primary role is to first acquire the user's current location using GPS and transmit that information to the server. As the user moves, the terminal continuously feeds back this location information to the server, enabling a dynamic reassessment of the optimal evacuation route. The terminal also notifies the user of evacuation instructions and warnings sent from the server in multiple languages. This ensures consistent information provision to users of various nationalities.

[0280] Users operate the system using devices such as mobile phones and tablets. In the event of an emergency, they are required to follow instructions from their devices and begin a rapid evacuation. The devices also record the user's activity history and provide a function to individually customize evacuation information based on that history. This customization makes it easy to create an optimal evacuation plan that takes into account the user's past behavior patterns.

[0281] For example, in the event of a sudden flood in a city, this system can instantly analyze the information and present users with safe evacuation routes. Furthermore, when evacuation is necessary, the server can automatically arrange taxis and book accommodations. This minimizes the stress users experience while supporting rapid evacuation.

[0282] For a model to achieve such a function, the following prompt sentences are used.

[0283] Example of input prompt to the generative AI model:

[0284] Development of an app that provides real-time routes and information for safe evacuation when a user encounters a disaster within the city.

[0285] Necessary information: User's location, latest weather data, traffic conditions, location of evacuation shelters.

[0286] The flow of specific processing in Application Example 1 will be described using Figure 12.

[0287] Step 1:

[0288] The terminal acquires the user's current location using the GPS function. The input is GPS data, and the output is information on the user's latitude and longitude. This ensures accurate location information.

[0289] Step 2:

[0290] The terminal transmits the acquired location information to the server. The input is the latitude and longitude data acquired earlier, and the output is the server receiving this. Through this transmission, the server can grasp the user's current location.

[0291] Step 3:

[0292] The server collects data on the environment, means of transportation, and weather from external information sources. The input is real-time data from various databases, and the output is an integrated dataset for analysis. This enables the server to aggregate information for evaluating emergencies related to the user's location.

[0293] Step 4:

[0294] The server uses the user's location information and collected data to assess the likelihood of an emergency. The input is location information and an integrated dataset, and the output is a determination of whether or not an emergency has occurred. This step determines the need for evacuation.

[0295] Step 5:

[0296] The server calculates the optimal evacuation route or alternative mode of transportation in the event of an emergency. Inputs are the determination of the emergency and disaster information, and output is safe and efficient route information. The server can use an algorithm to provide the user with the optimal route.

[0297] Step 6:

[0298] The server sends calculated evacuation routes and alternative transportation information to the terminal. The input is the calculation result, and the output is when the terminal receives it and notifies the user.

[0299] Step 7:

[0300] The terminal displays evacuation instructions to the user based on notifications from the server. Input is evacuation information from the server, and output is a visual or audio notification to the user. This allows the user to take quick and appropriate action.

[0301] Step 8:

[0302] The server makes additional arrangements as needed, including, for example, arranging a taxi or booking accommodation. Input is information based on the user's requests and behavioral patterns, and output is a confirmation of the arrangements. This step allows the user to receive assistance in acting more safely.

[0303] 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.

[0304] The present invention is a system that supports users with timely and optimal responses, and is characterized by providing personalized support according to the user's emotional state by combining an emotion engine. This system consists of four main components: a server, a terminal, an emotion engine, and a user.

[0305] The server collects weather, traffic, and disaster information from multiple external databases and processes this in real time. It receives the user's location information and determines the presence or absence of an emergency based on this. Furthermore, it calculates evacuation routes and alternative means of transportation, and determines the optimal notification content for the user based on the analysis results of the emotion engine.

[0306] The terminal acquires the user's current location using GPS and transmits this location information to the server. Also, in cooperation with the emotion engine, it analyzes the emotion from the user's voice and actions in real time. This enables support to relieve the user's tension and anxiety.

[0307] The emotion engine detects the user's expression and voice with sensors and analyzes the obtained emotion data. The analysis results are transmitted to the terminal and the server to adjust the content and method of emergency notifications by the notification means. Through this process, delicate support according to the user's individual situation can be provided.

[0308] The user can utilize this system via a normal device and receive support adapted to their emotional state. For example, in an emergency, when the user is feeling anxious, the system can provide instructions that give a greater sense of security.

[0309] As a concrete example, consider the case of a large-scale natural disaster. The server analyzes the extent of the disaster's impact and calculates the optimal evacuation route based on that information. If the emotion engine detects that the user is in a state of confusion, the terminal changes the notification content to something stable and reassuring, and issues instructions to encourage the user to make calm decisions. This enables the user to evacuate appropriately and safely.

[0310] The following describes the processing flow.

[0311] Step 1:

[0312] The user activates the device and enables location services and the emotion engine. The device uses GPS to obtain the user's current location and the emotion engine analyzes the user's voice and facial expressions.

[0313] Step 2:

[0314] The device transmits acquired location and sentiment data to the server. The server receives this information in real time and compares it with weather, traffic, and disaster information in its database.

[0315] Step 3:

[0316] The server determines whether an emergency has occurred based on the user's current location. If an emergency has occurred, it calculates the optimal evacuation route and alternative means of transportation.

[0317] Step 4:

[0318] The emotion engine analyzes the user's emotional state and sends the results to the server. The server adjusts the notification content based on the emotion data. Specifically, if the user is feeling anxious, it generates instructions that provide reassurance.

[0319] Step 5:

[0320] The server sends calculated evacuation routes and notification content to the terminal. The terminal notifies the user of the received information via voice and visual means, prompting them to take emergency action.

[0321] Step 6:

[0322] The user begins evacuation actions and the use of alternative transportation according to instructions from the device. The device continuously monitors the user's location and emotional state and sends additional information to the server as needed.

[0323] Step 7:

[0324] If necessary, the server will devise further support measures for the terminal user, such as booking taxis or rebooking accommodations. This will allow the user to complete their evacuation safely and with peace of mind.

[0325] (Example 2)

[0326] 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".

[0327] While systems already exist to support user actions during disasters and emergencies, these systems are limited in their ability to provide appropriate support because they cannot take into account the user's emotional state. This challenge includes the fact that the information provided may not be sufficiently reassuring to users who are feeling anxious or frightened.

[0328] 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.

[0329] In this invention, the server includes information gathering means that collect information on the environment, movement, and weather from an external database and determine the occurrence of an emergency based on the user's current location; emotion analysis means that perform emotion analysis and adjust the content of emergency notifications according to the user's emotional state based on the analysis results; and notification means that send emergency notifications to the user. As a result, the user can receive information that is appropriate to their emotional state and act appropriately with a sense of security.

[0330] "Location information acquisition means" refers to devices or technologies used to determine a user's current location, and typically involves collecting location data using GPS functionality.

[0331] "Information gathering means" refers to devices and technologies that acquire information on the environment, movement, and weather from external databases and gather information necessary for users to make informed decisions.

[0332] "Calculation means" refers to devices and technologies that calculate the optimal evacuation route or alternative means for the user based on acquired information.

[0333] "Emotional analysis means" refers to devices and technologies that analyze a user's voice and actions to estimate the user's emotional state, and the results are used to adjust notification content.

[0334] "Notification means" refers to devices or technologies used to provide information to users, such as sending notifications via text messages or voice.

[0335] "Reservation methods" refer to devices or technologies that automatically arrange evacuation routes and accommodations as needed.

[0336] This invention is a system for providing appropriate information according to the user's emotional state. The system consists of four main elements: a server, a terminal, an emotion engine, and the user.

[0337] The server collects and processes environmental, movement, and weather information in real time from multiple external databases. This includes databases from the Japan Meteorological Agency, traffic management systems, and disaster information systems. The server combines the collected information with the user's location to determine whether an emergency has occurred. If action is required, it calculates evacuation routes and alternative transportation options, and determines the most appropriate notification content for the user based on the analysis results of the emotion engine.

[0338] The device uses the GPS built into the user's device to obtain the user's current location and transmits that location information to the server. Furthermore, the device works in conjunction with an emotion engine and uses sensors such as microphones and cameras to analyze the user's voice and actions in real time. This allows the device to understand the user's emotional state and provide data to the server to adjust notification content as needed.

[0339] The emotion engine analyzes the user's facial expressions and voice data acquired from sensors to estimate the user's emotional state with high accuracy. The analysis results are sent to the server and terminal and used to adjust the content and method of emergency notifications.

[0340] Users can utilize this system through their everyday devices to receive support tailored to their individual emotional state. Specifically, even in emergencies, they can take calm action based on the reassuring information provided by the system. For example, in the event of a large-scale natural disaster, the server analyzes the extent of the disaster's impact and calculates the optimal evacuation route. When the emotion engine detects that the user is feeling anxious, the device changes the notification content to something reassuring, encouraging the user to make calm decisions.

[0341] A concrete example of a related prompt message would be to input the instruction, "Generate the optimal evacuation instructions based on the user's emotional state," into the AI ​​model. In this way, the system can respond flexibly to a variety of situations and provide a safe environment for the user.

[0342] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0343] Step 1:

[0344] The device uses its built-in GPS module to obtain the user's current location in real time. The acquired location information is sent from the device to the server. Specifically, the location information is updated every 15 seconds.

[0345] Step 2:

[0346] The server collects environmental, movement, and weather information in real time from external databases. The server obtains data from the Japan Meteorological Agency, traffic management systems, and disaster information systems via APIs and analyzes it. The resulting organized information is then combined with user location information and used for subsequent processing.

[0347] Step 3:

[0348] The server determines whether an emergency has occurred based on the user's location information and other collected data. This process uses a Geographic Information System (GIS) to determine if the user's current location is within the disaster's affected area. The result of this determination indicates whether there is an urgent need.

[0349] Step 4:

[0350] The device uses an emotion engine to analyze the user's voice and actions in real time. It uses a combination of speech recognition and image analysis technologies to estimate the user's emotional state. The input for this analysis is the user's voice and facial expression data, and the output is the result of the emotional state assessment.

[0351] Step 5:

[0352] The server uses the sentiment analysis results sent from the sentiment engine to determine the content of the emergency notification. If the user is feeling anxious, it uses a generative AI model to generate a reassuring notification. An example of a prompt is, "Generate a message to alleviate the user's anxiety." The output is the content of the notification to be sent to the user.

[0353] Step 6:

[0354] Users check notifications received from their devices and act according to the instructions. Specifically, this includes actions based on instructions to move to a safe place or to stay calm. Notifications are delivered via text message or voice, and actions are triggered after the user acknowledges them.

[0355] (Application Example 2)

[0356] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0357] In modern urban environments, it is crucial to provide users with prompt and appropriate evacuation information in the event of sudden emergencies or natural disasters. However, simply issuing uniform notifications without considering users' emotional states is insufficient to adequately alleviate anxiety and confusion. In addition, diverse means of providing information that accommodate linguistic and cultural differences are required. This invention provides a system that enables flexible information provision tailored to users' emotional states in order to solve these problems.

[0358] 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.

[0359] In this invention, the server includes location information acquisition means for obtaining the user's current location, information collection means for collecting information on weather, traffic, and disasters from external information sources and determining the occurrence of an emergency based on the user's location, and calculation means for monitoring the user's emotional state in real time using speech recognition and facial expression analysis and calculating the optimal evacuation route or alternative means of transportation in response to an emergency based on the results. This makes it possible to provide instructions that give the user a sense of security according to their emotional state.

[0360] "Location information acquisition means" is a general term for technologies and devices used to accurately obtain a user's current location.

[0361] "Information gathering means" refers to elements that collect data on weather, traffic, and disasters from external sources and have the function of determining the occurrence of an emergency in relation to the user's location.

[0362] "Emotional state" refers to the user's psychological or emotional state, and is measured through voice and facial expression analysis.

[0363] "Speech recognition" is a technology that analyzes a user's spoken words and converts them into text information, and is used to understand emotions.

[0364] "Facial expression analysis" is a technology that estimates a user's emotions from their facial expressions and is used for real-time emotion monitoring.

[0365] A "computational tool" is a technology that has the function of calculating the optimal evacuation route or alternative means of transportation based on the user's location and emotional state.

[0366] "Notification methods" is a general term for technologies and interfaces used to communicate necessary information and instructions to users in an appropriate format.

[0367] A "procedure management system" is an element that has the function of automatically arranging evacuation and accommodation reservations as needed.

[0368] This invention constructs a system that enables the provision of optimal information based on the user's emotional state. The following describes how this system is implemented.

[0369] The server receives GPS location information transmitted from the user's device and, in conjunction with an external information database, collects weather, traffic, and disaster-related data in real time. Using this data, the server determines whether an emergency has occurred based on the user's location and calculates evacuation routes and alternative transportation options accordingly.

[0370] The device is equipped with voice recognition and facial expression analysis technology, which monitors the user's emotional state in real time. If the user is feeling tense or anxious, the server uses the emotional data obtained from the device to generate a reassuring notification.

[0371] The notification system provides users with optimal instructions that take emotional information into account. For example, if a sudden weather change occurs during a large-scale urban event, the system can send a message to the user's device such as, "We have confirmed the route from your current location to the nearest shelter. Please proceed calmly."

[0372] In this process, a generative AI model is used to automatically generate customized instruction prompts for each user. An example of a prompt might be, "Create guidance to support optimal evacuation actions based on current weather conditions and the user's emotional state." In this way, it is possible to provide flexible and appropriate emergency responses to users.

[0373] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0374] Step 1:

[0375] The server receives GPS data transmitted from the terminal and determines the user's current location. It analyzes the GPS data as input and generates output as geographical information. This allows the server to determine the user's precise location.

[0376] Step 2:

[0377] The server uses location data to connect with external information sources and obtain the latest data on weather, traffic, and disasters. The input is location data, and by making API calls and other actions based on this data, it obtains relevant environmental information as output. This allows the user to understand the situation around them.

[0378] Step 3:

[0379] The device monitors the user's emotional state using voice recognition and facial expression analysis. Audio and video data from sensors are used as input, which is then analyzed to output emotional information. This analysis allows for real-time understanding of the user's current emotional state.

[0380] Step 4:

[0381] The server integrates collected environmental information and emotional information from terminals to determine whether an emergency has occurred. Based on the environmental and emotional information as input, it uses logic to determine if an emergency has occurred and outputs an indicator of the degree of urgency.

[0382] Step 5:

[0383] The server calculates the optimal evacuation route and alternative transportation based on the urgency level. The input consists of an urgency index and location information, which is analyzed to output the most appropriate route for the user. This determines the specific means of transportation needed if an action is required.

[0384] Step 6:

[0385] The device uses a generative AI model to generate notification content as prompts that respond to the user's emotions. Based on emotional information and evacuation routes as input, it outputs notification messages that provide reassurance to the user. By generating prompts, notifications optimized for the user are created.

[0386] Step 7:

[0387] Users receive notifications from their devices and act calmly based on them. The outputted notification message serves as input, and users take appropriate action or move accordingly. This allows them to act safely and with a sense of security.

[0388] 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.

[0389] 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.

[0390] 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.

[0391] [Third Embodiment]

[0392] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0393] 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.

[0394] 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).

[0395] 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.

[0396] 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.

[0397] 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).

[0398] 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.

[0399] 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.

[0400] 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.

[0401] 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.

[0402] 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.

[0403] 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".

[0404] This invention is configured as a system that allows users to quickly perform optimal evacuation and response actions appropriate to the situation. It consists of three main components: a server, a terminal, and a user.

[0405] The server retrieves information from multiple external databases. This includes weather data, traffic conditions, and disaster information, which are collected in real time and stored in the database. The server receives location information from users and compares it with the current geographical situation to determine if an emergency has occurred. Based on this determination, it calculates evacuation routes and alternative measures to avoid the impact.

[0406] The device acquires the user's location via GPS and transmits it to the server. Furthermore, based on emergency notifications received from the server, it issues instructions to the user via voice or text. Multilingual support ensures that information is communicated without difficulty to users who speak different languages. In addition, the device tracks the user's movements and sends that information back to the server, enabling the provision of more appropriate countermeasures.

[0407] Users operate this system on a terminal using their regular devices. In the event of an emergency, they follow instructions from the terminal to take evacuation actions or utilize alternative means of transport. Depending on the user's choices, the server can make further arrangements, such as booking a taxi or rebooking a hotel. This allows users to act with peace of mind without experiencing unnecessary stress.

[0408] As a concrete example, consider the case of an earthquake. This system receives earthquake reports, analyzes the affected area in real time, and checks if the user is within the affected area. If they are within the affected area, the server immediately calculates the direction and location of evacuation and sends that information to the terminal. Based on this information, the terminal prompts the user to take safe action in response to the earthquake. By following these instructions, the user can evacuate quickly and safely.

[0409] The following describes the processing flow.

[0410] Step 1:

[0411] The user starts up the device and enables location services. The device uses GPS to obtain the user's current location.

[0412] Step 2:

[0413] The device sends the acquired location information to the server. The server receives this location information and compares it with the latest information in its database.

[0414] Step 3:

[0415] The server analyzes weather, traffic, and disaster information collected from an external database to determine if the user's location is within the area affected by the emergency.

[0416] Step 4:

[0417] If an emergency is detected, the server calculates the optimal evacuation route and alternative transportation options. This calculation takes into account the user's travel history and current traffic conditions.

[0418] Step 5:

[0419] The server sends the calculation results to the terminal. Based on this information, the terminal provides visual and audible notifications to the user.

[0420] Step 6:

[0421] Users check the evacuation route and alternative means of transport information provided on their devices and begin taking action according to the instructions.

[0422] Step 7:

[0423] If necessary, the server automatically makes arrangements such as booking a taxi or re-securing accommodation. The status of these arrangements is notified to the terminal, providing the user with the latest information.

[0424] (Example 1)

[0425] 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."

[0426] In modern society, taking swift and appropriate evacuation actions in the event of a disaster or unforeseen accident is extremely important. However, current technology makes it difficult to provide accurate evacuation routes and alternative means in real time and in multiple languages, and customized information tailored to individual users is also insufficient. This can lead to anxiety and confusion among international travelers and users with diverse backgrounds during emergencies.

[0427] 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.

[0428] In this invention, the server includes means for acquiring the user's location information, means for acquiring information from external sources to determine an emergency situation, and means for generating prompt sentences using a generative AI model to create sentences for instructing a rapid response. This enables rapid and appropriate evacuation guidance and support tailored to the individual needs of the user when they face an emergency.

[0429] "Means of acquiring location information" refers to the technologies and devices necessary to determine the user's current location, and this includes functions that measure location using GPS and Wi-Fi data.

[0430] "Means of obtaining information from information sources" refers to technologies and devices for collecting the latest information on disasters, traffic, and weather from external databases and APIs.

[0431] "Means for determining an emergency situation" refers to technologies and methods for analyzing acquired information and user location data to determine whether a disaster or crisis is occurring.

[0432] "Methods using generative AI models" refer to methods that utilize artificial intelligence technology, such as natural language processing, to automatically generate instruction texts to be provided to the user.

[0433] "Means for creating instructions for rapid response" refers to technologies and methods aimed at promptly providing users with guidance for evacuation and ensuring their safety using generated instructional texts.

[0434] A "multilingual interface" refers to a system that automatically translates and displays information to provide appropriate information to users who speak different languages.

[0435] "Customized instructions that take into account behavioral history" refers to a method of providing information and instructions optimized for each user based on their past behavior and preferences.

[0436] This system is an emergency response system designed to ensure user safety and consists primarily of three elements: servers, terminals, and users.

[0437] The server collects disaster, traffic, and weather information in real time from external sources. These sources include publicly available weather APIs, map APIs, and disaster alert services. Based on the collected information, the server determines whether an emergency has occurred and whether the user may be affected. In the event of an emergency, the server uses a generative artificial intelligence model to generate necessary prompt messages and create instructions that include appropriate evacuation routes and alternative transportation options.

[0438] The device obtains the user's current location via the GPS system and transmits it to the server. It also notifies the user of instructions received from the server in the form of voice or text. A multilingual interface is employed, and information is translated according to the user's language settings for accurate communication. Furthermore, the device considers the user's behavioral history and sends feedback to the server to generate individually customized instructions.

[0439] Users operate the system using their usual devices, such as smartphones or tablets. In the event of an emergency, they receive an alert from their device, allowing them to follow the instructions and take evacuation action. This enables users to evacuate quickly and safely and receive the necessary assistance. For example, in the event of an earthquake, the server immediately analyzes earthquake information, calculates a safe evacuation route, sends it to the device, and provides the user with voice guidance based on the results.

[0440] An example of a prompt message would be, "Calculate the optimal route for the user to safely evacuate from their current location and generate instructions in Japanese." This prompt message allows the server to quickly provide appropriate instructions tailored to the user's situation.

[0441] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0442] Step 1:

[0443] The server collects disaster, traffic, and weather information from external sources. Specifically, the server sends requests to weather APIs, map APIs, and disaster alert services to obtain the latest data. This information is stored in a database on the server and used to determine the status of an emergency. Input requires access to API endpoints and necessary authentication information, while output provides various types of information collected in real time.

[0444] Step 2:

[0445] The device uses GPS to obtain the user's current location and sends this data to the server. Location information is collected through the device's sensors, encrypted according to a protocol, and transmitted. The input is raw data about the user's current location, and the output is location information converted from this data into a format usable by the server.

[0446] Step 3:

[0447] The server uses collected information and the user's location data to determine whether an emergency has occurred. In this process, an AI algorithm compares weather and traffic data with earthquake reports to determine if the user is involved in an emergency. The algorithm's input is information stored in the database and the user's location data, and its output is a flag indicating whether an emergency has occurred.

[0448] Step 4:

[0449] The server uses a generative AI model to generate prompt messages and provide appropriate instructions to the user. These prompt messages suggest the best evacuation route or alternative means based on the user's situation and are sent to the terminal in voice or text format. Inputs include an emergency flag and the user's location information, while output is a customized instruction message.

[0450] Step 5:

[0451] The terminal notifies the user of instructions received from the server. Notifications are delivered via speech synthesis or text messages, and are appropriately translated according to the user's language settings through a multilingual support system. The input is the instruction text from the server, and the output is the notification in a language understandable to the user.

[0452] Step 6:

[0453] The user follows the instructions on the device and moves along the evacuation route. During this process, the device continuously tracks the user's location and sends feedback to the server, which keeps the situation updated in real time. The input is data of the user's actions as they follow the instructions, and the output is updated location information as feedback to the server.

[0454] (Application Example 1)

[0455] 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."

[0456] In recent years, urbanization and the increasing frequency of natural disasters have made ensuring safety in cities a critical issue. Traditional evacuation orders are based on limited information and only provide general guidance, lacking the ability to provide optimal evacuation information tailored to individual circumstances in real time. As a result, it is difficult for residents and visitors to quickly and safely avoid danger.

[0457] 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.

[0458] In this invention, the server includes a device for acquiring location information, a device for collecting information on the environment, means of transportation, and weather from external sources and for evaluating dangerous situations based on the user's location, and a device for calculating the optimal evacuation route or alternative means of transportation to deal with the dangerous situation. This makes it possible for residents and visitors in a city to obtain up-to-date and individualized evacuation routes in real time.

[0459] A "device for acquiring location information" is a device that has the function of identifying the user's current location and transmitting it to a server as digital data.

[0460] A "device for collecting information on the environment, means of transportation, and weather from external sources and evaluating dangerous situations based on the user's location" is a system that analyzes data collected from various databases and sensors to identify and evaluate emergencies related to the user's current location.

[0461] A "device for calculating optimal evacuation routes and alternative means of transportation" is a device that executes an algorithm to calculate the most efficient and safest travel route based on collected data and risk assessment, in order to ensure the safety of the user.

[0462] The system for implementing this invention is formed by three main components: a server, a terminal, and a user.

[0463] The server acquires real-time data on the environment, transportation, and weather from various external sources. Specifically, it connects to diverse databases such as weather data, traffic data, and disaster information, and manages them in an integrated manner. Using this data, the server assesses emergencies and calculates appropriate evacuation routes and alternative transportation options. Advanced algorithms are used in these calculations to provide users with the safest and most efficient evacuation routes.

[0464] The terminal's primary role is to first acquire the user's current location using GPS and transmit that information to the server. As the user moves, the terminal continuously feeds back this location information to the server, enabling a dynamic reassessment of the optimal evacuation route. The terminal also notifies the user of evacuation instructions and warnings sent from the server in multiple languages. This ensures consistent information provision to users of various nationalities.

[0465] Users operate the system using devices such as mobile phones and tablets. In the event of an emergency, they are required to follow instructions from their devices and begin a rapid evacuation. The devices also record the user's activity history and provide a function to individually customize evacuation information based on that history. This customization makes it easy to create an optimal evacuation plan that takes into account the user's past behavior patterns.

[0466] For example, in the event of a sudden flood in a city, this system can instantly analyze the information and present users with safe evacuation routes. Furthermore, when evacuation is necessary, the server can automatically arrange taxis and book accommodations. This minimizes the stress users experience while supporting rapid evacuation.

[0467] To implement this functionality, use the following prompt statements for the model.

[0468] Example input prompts for a generative AI model:

[0469] Development of an app that provides users with real-time information and safe evacuation routes in the event of a disaster in an urban area.

[0470] Required information: User's location, latest weather data, traffic conditions, and location of evacuation shelters.

[0471] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0472] Step 1:

[0473] The device obtains the user's current location using GPS functionality. The input is GPS data, and the output is the user's latitude and longitude information. This ensures accurate location information.

[0474] Step 2:

[0475] The device sends the acquired location information to the server. The input is the latitude and longitude data acquired earlier, and the output is the server receiving this data. This transmission allows the server to determine the user's current location.

[0476] Step 3:

[0477] The server collects environmental, transportation, and weather data from external sources. Input is real-time data from diverse databases, and output is an integrated dataset for analysis. This allows the server to aggregate information for assessing user location-related emergencies.

[0478] Step 4:

[0479] The server uses the user's location information and collected data to assess the likelihood of an emergency. The input is location information and an integrated dataset, and the output is a determination of whether or not an emergency has occurred. This step determines the need for evacuation.

[0480] Step 5:

[0481] The server calculates the optimal evacuation route or alternative mode of transportation in the event of an emergency. Inputs are the determination of the emergency and disaster information, and output is safe and efficient route information. The server can use an algorithm to provide the user with the optimal route.

[0482] Step 6:

[0483] The server sends calculated evacuation routes and alternative transportation information to the terminal. The input is the calculation result, and the output is when the terminal receives it and notifies the user.

[0484] Step 7:

[0485] The terminal displays evacuation instructions to the user based on notifications from the server. Input is evacuation information from the server, and output is a visual or audio notification to the user. This allows the user to take quick and appropriate action.

[0486] Step 8:

[0487] The server makes additional arrangements as needed, including, for example, arranging a taxi or booking accommodation. Input is information based on the user's requests and behavioral patterns, and output is a confirmation of the arrangements. This step allows the user to receive assistance in acting more safely.

[0488] 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.

[0489] This invention is a system that supports users in providing timely and optimal responses, and is characterized by providing personalized support according to the user's emotional state by combining it with an emotion engine. This system consists of four main components: a server, a terminal, an emotion engine, and a user.

[0490] The server collects weather, traffic, and disaster information from multiple external databases and processes it in real time. It receives the user's location information and determines whether an emergency exists based on this. Furthermore, it calculates evacuation routes and alternative transportation options, and determines the most appropriate notification content for the user based on the results of the emotion engine's analysis.

[0491] The device uses GPS to obtain the user's current location and transmits that location information to a server. It also works in conjunction with an emotion engine to analyze the user's emotions in real time based on their voice and actions. This enables support to alleviate the user's tension and anxiety.

[0492] The emotion engine uses sensors to detect the user's facial expressions and voice, and analyzes the resulting emotional data. The analysis results are sent to the terminal and server to adjust the content and method of emergency notifications. This process enables the provision of detailed support tailored to each user's individual situation.

[0493] Users can access this system via their regular devices and receive support tailored to their emotional state. For example, in an emergency, if a user is feeling anxious, the system can provide reassuring instructions.

[0494] As a concrete example, consider the case of a large-scale natural disaster. The server analyzes the extent of the disaster's impact and calculates the optimal evacuation route based on that information. If the emotion engine detects that the user is in a state of confusion, the terminal changes the notification content to something stable and reassuring, and issues instructions to encourage the user to make calm decisions. This enables the user to evacuate appropriately and safely.

[0495] The following describes the processing flow.

[0496] Step 1:

[0497] The user activates the device and enables location services and the emotion engine. The device uses GPS to obtain the user's current location and the emotion engine analyzes the user's voice and facial expressions.

[0498] Step 2:

[0499] The device transmits acquired location and sentiment data to the server. The server receives this information in real time and compares it with weather, traffic, and disaster information in its database.

[0500] Step 3:

[0501] The server determines whether an emergency has occurred based on the user's current location. If an emergency has occurred, it calculates the optimal evacuation route and alternative means of transportation.

[0502] Step 4:

[0503] The emotion engine analyzes the user's emotional state and sends the results to the server. The server adjusts the notification content based on the emotion data. Specifically, if the user is feeling anxious, it generates instructions that provide reassurance.

[0504] Step 5:

[0505] The server sends calculated evacuation routes and notification content to the terminal. The terminal notifies the user of the received information via voice and visual means, prompting them to take emergency action.

[0506] Step 6:

[0507] The user begins evacuation actions and the use of alternative transportation according to instructions from the device. The device continuously monitors the user's location and emotional state and sends additional information to the server as needed.

[0508] Step 7:

[0509] If necessary, the server will devise further support measures for the terminal user, such as booking taxis or rebooking accommodations. This will allow the user to complete their evacuation safely and with peace of mind.

[0510] (Example 2)

[0511] 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."

[0512] While systems already exist to support user actions during disasters and emergencies, these systems are limited in their ability to provide appropriate support because they cannot take into account the user's emotional state. This challenge includes the fact that the information provided may not be sufficiently reassuring to users who are feeling anxious or frightened.

[0513] 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.

[0514] In this invention, the server includes information gathering means that collect information on the environment, movement, and weather from an external database and determine the occurrence of an emergency based on the user's current location; emotion analysis means that perform emotion analysis and adjust the content of emergency notifications according to the user's emotional state based on the analysis results; and notification means that send emergency notifications to the user. As a result, the user can receive information that is appropriate to their emotional state and act appropriately with a sense of security.

[0515] "Location information acquisition means" refers to devices or technologies used to determine a user's current location, and typically involves collecting location data using GPS functionality.

[0516] "Information gathering means" refers to devices and technologies that acquire information on the environment, movement, and weather from external databases and gather information necessary for users to make informed decisions.

[0517] "Calculation means" refers to devices and technologies that calculate the optimal evacuation route or alternative means for the user based on acquired information.

[0518] "Emotional analysis means" refers to devices and technologies that analyze a user's voice and actions to estimate the user's emotional state, and the results are used to adjust notification content.

[0519] "Notification means" refers to devices or technologies used to provide information to users, such as sending notifications via text messages or voice.

[0520] "Reservation methods" refer to devices or technologies that automatically arrange evacuation routes and accommodations as needed.

[0521] This invention is a system for providing appropriate information according to the user's emotional state. The system consists of four main elements: a server, a terminal, an emotion engine, and the user.

[0522] The server collects and processes environmental, movement, and weather information in real time from multiple external databases. This includes databases from the Japan Meteorological Agency, traffic management systems, and disaster information systems. The server combines the collected information with the user's location to determine whether an emergency has occurred. If action is required, it calculates evacuation routes and alternative transportation options, and determines the most appropriate notification content for the user based on the analysis results of the emotion engine.

[0523] The device uses the GPS built into the user's device to obtain the user's current location and transmits that location information to the server. Furthermore, the device works in conjunction with an emotion engine and uses sensors such as microphones and cameras to analyze the user's voice and actions in real time. This allows the device to understand the user's emotional state and provide data to the server to adjust notification content as needed.

[0524] The emotion engine analyzes the user's facial expressions and voice data acquired from sensors to estimate the user's emotional state with high accuracy. The analysis results are sent to the server and terminal and used to adjust the content and method of emergency notifications.

[0525] Users can utilize this system through their everyday devices to receive support tailored to their individual emotional state. Specifically, even in emergencies, they can take calm action based on the reassuring information provided by the system. For example, in the event of a large-scale natural disaster, the server analyzes the extent of the disaster's impact and calculates the optimal evacuation route. When the emotion engine detects that the user is feeling anxious, the device changes the notification content to something reassuring, encouraging the user to make calm decisions.

[0526] A concrete example of a related prompt message would be to input the instruction, "Generate the optimal evacuation instructions based on the user's emotional state," into the AI ​​model. In this way, the system can respond flexibly to a variety of situations and provide a safe environment for the user.

[0527] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0528] Step 1:

[0529] The device uses its built-in GPS module to obtain the user's current location in real time. The acquired location information is sent from the device to the server. Specifically, the location information is updated every 15 seconds.

[0530] Step 2:

[0531] The server collects environmental, movement, and weather information in real time from external databases. The server obtains data from the Japan Meteorological Agency, traffic management systems, and disaster information systems via APIs and analyzes it. The resulting organized information is then combined with user location information and used for subsequent processing.

[0532] Step 3:

[0533] The server determines whether an emergency has occurred based on the user's location information and other collected data. This process uses a Geographic Information System (GIS) to determine if the user's current location is within the disaster's affected area. The result of this determination indicates whether there is an urgent need.

[0534] Step 4:

[0535] The device uses an emotion engine to analyze the user's voice and actions in real time. It uses a combination of speech recognition and image analysis technologies to estimate the user's emotional state. The input for this analysis is the user's voice and facial expression data, and the output is the result of the emotional state assessment.

[0536] Step 5:

[0537] The server uses the sentiment analysis results sent from the sentiment engine to determine the content of the emergency notification. If the user is feeling anxious, it uses a generative AI model to generate a reassuring notification. An example of a prompt is, "Generate a message to alleviate the user's anxiety." The output is the content of the notification to be sent to the user.

[0538] Step 6:

[0539] Users check notifications received from their devices and act according to the instructions. Specifically, this includes actions based on instructions to move to a safe place or to stay calm. Notifications are delivered via text message or voice, and actions are triggered after the user acknowledges them.

[0540] (Application Example 2)

[0541] 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."

[0542] In modern urban environments, it is crucial to provide users with prompt and appropriate evacuation information in the event of sudden emergencies or natural disasters. However, simply issuing uniform notifications without considering users' emotional states is insufficient to adequately alleviate anxiety and confusion. In addition, diverse means of providing information that accommodate linguistic and cultural differences are required. This invention provides a system that enables flexible information provision tailored to users' emotional states in order to solve these problems.

[0543] 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.

[0544] In this invention, the server includes location information acquisition means for obtaining the user's current location, information collection means for collecting information on weather, traffic, and disasters from external information sources and determining the occurrence of an emergency based on the user's location, and calculation means for monitoring the user's emotional state in real time using speech recognition and facial expression analysis and calculating the optimal evacuation route or alternative means of transportation in response to an emergency based on the results. This makes it possible to provide instructions that give the user a sense of security according to their emotional state.

[0545] "Location information acquisition means" is a general term for technologies and devices used to accurately obtain a user's current location.

[0546] "Information gathering means" refers to elements that collect data on weather, traffic, and disasters from external sources and have the function of determining the occurrence of an emergency in relation to the user's location.

[0547] "Emotional state" refers to the user's psychological or emotional state, and is measured through voice and facial expression analysis.

[0548] "Speech recognition" is a technology that analyzes a user's spoken words and converts them into text information, and is used to understand emotions.

[0549] "Facial expression analysis" is a technology that estimates a user's emotions from their facial expressions and is used for real-time emotion monitoring.

[0550] A "computational tool" is a technology that has the function of calculating the optimal evacuation route or alternative means of transportation based on the user's location and emotional state.

[0551] "Notification methods" is a general term for technologies and interfaces used to communicate necessary information and instructions to users in an appropriate format.

[0552] A "procedure management system" is an element that has the function of automatically arranging evacuation and accommodation reservations as needed.

[0553] This invention constructs a system that enables the provision of optimal information based on the user's emotional state. The following describes how this system is implemented.

[0554] The server receives GPS location information transmitted from the user's device and, in conjunction with an external information database, collects weather, traffic, and disaster-related data in real time. Using this data, the server determines whether an emergency has occurred based on the user's location and calculates evacuation routes and alternative transportation options accordingly.

[0555] The device is equipped with voice recognition and facial expression analysis technology, which monitors the user's emotional state in real time. If the user is feeling tense or anxious, the server uses the emotional data obtained from the device to generate a reassuring notification.

[0556] The notification system provides users with optimal instructions that take emotional information into account. For example, if a sudden weather change occurs during a large-scale urban event, the system can send a message to the user's device such as, "We have confirmed the route from your current location to the nearest shelter. Please proceed calmly."

[0557] In this process, a generative AI model is used to automatically generate customized instruction prompts for each user. An example of a prompt might be, "Create guidance to support optimal evacuation actions based on current weather conditions and the user's emotional state." In this way, it is possible to provide flexible and appropriate emergency responses to users.

[0558] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0559] Step 1:

[0560] The server receives GPS data transmitted from the terminal and determines the user's current location. It analyzes the GPS data as input and generates output as geographical information. This allows the server to determine the user's precise location.

[0561] Step 2:

[0562] The server uses location data to connect with external information sources and obtain the latest data on weather, traffic, and disasters. The input is location data, and by making API calls and other actions based on this data, it obtains relevant environmental information as output. This allows the user to understand the situation around them.

[0563] Step 3:

[0564] The device monitors the user's emotional state using voice recognition and facial expression analysis. Audio and video data from sensors are used as input, which is then analyzed to output emotional information. This analysis allows for real-time understanding of the user's current emotional state.

[0565] Step 4:

[0566] The server integrates collected environmental information and emotional information from terminals to determine whether an emergency has occurred. Based on the environmental and emotional information as input, it uses logic to determine if an emergency has occurred and outputs an indicator of the degree of urgency.

[0567] Step 5:

[0568] The server calculates the optimal evacuation route and alternative transportation based on the urgency level. The input consists of an urgency index and location information, which is analyzed to output the most appropriate route for the user. This determines the specific means of transportation needed if an action is required.

[0569] Step 6:

[0570] The device uses a generative AI model to generate notification content as prompts that respond to the user's emotions. Based on emotional information and evacuation routes as input, it outputs notification messages that provide reassurance to the user. By generating prompts, notifications optimized for the user are created.

[0571] Step 7:

[0572] Users receive notifications from their devices and act calmly based on them. The outputted notification message serves as input, and users take appropriate action or move accordingly. This allows them to act safely and with a sense of security.

[0573] 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.

[0574] 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.

[0575] 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.

[0576] [Fourth Embodiment]

[0577] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0578] 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.

[0579] 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).

[0580] 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.

[0581] 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.

[0582] 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).

[0583] 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.

[0584] 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.

[0585] 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.

[0586] 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.

[0587] 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.

[0588] 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.

[0589] 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".

[0590] This invention is configured as a system that allows users to quickly perform optimal evacuation and response actions appropriate to the situation. It consists of three main components: a server, a terminal, and a user.

[0591] The server retrieves information from multiple external databases. This includes weather data, traffic conditions, and disaster information, which are collected in real time and stored in the database. The server receives location information from users and compares it with the current geographical situation to determine if an emergency has occurred. Based on this determination, it calculates evacuation routes and alternative measures to avoid the impact.

[0592] The device acquires the user's location via GPS and transmits it to the server. Furthermore, based on emergency notifications received from the server, it issues instructions to the user via voice or text. Multilingual support ensures that information is communicated without difficulty to users who speak different languages. In addition, the device tracks the user's movements and sends that information back to the server, enabling the provision of more appropriate countermeasures.

[0593] Users operate this system on a terminal using their regular devices. In the event of an emergency, they follow instructions from the terminal to take evacuation actions or utilize alternative means of transport. Depending on the user's choices, the server can make further arrangements, such as booking a taxi or rebooking a hotel. This allows users to act with peace of mind without experiencing unnecessary stress.

[0594] As a concrete example, consider the case of an earthquake. This system receives earthquake reports, analyzes the affected area in real time, and checks if the user is within the affected area. If they are within the affected area, the server immediately calculates the direction and location of evacuation and sends that information to the terminal. Based on this information, the terminal prompts the user to take safe action in response to the earthquake. By following these instructions, the user can evacuate quickly and safely.

[0595] The following describes the processing flow.

[0596] Step 1:

[0597] The user starts up the device and enables location services. The device uses GPS to obtain the user's current location.

[0598] Step 2:

[0599] The device sends the acquired location information to the server. The server receives this location information and compares it with the latest information in its database.

[0600] Step 3:

[0601] The server analyzes weather, traffic, and disaster information collected from an external database to determine if the user's location is within the area affected by the emergency.

[0602] Step 4:

[0603] If an emergency is detected, the server calculates the optimal evacuation route and alternative transportation options. This calculation takes into account the user's travel history and current traffic conditions.

[0604] Step 5:

[0605] The server sends the calculation results to the terminal. Based on this information, the terminal provides visual and audible notifications to the user.

[0606] Step 6:

[0607] Users check the evacuation route and alternative means of transport information provided on their devices and begin taking action according to the instructions.

[0608] Step 7:

[0609] If necessary, the server automatically makes arrangements such as booking a taxi or re-securing accommodation. The status of these arrangements is notified to the terminal, providing the user with the latest information.

[0610] (Example 1)

[0611] 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".

[0612] In modern society, taking swift and appropriate evacuation actions in the event of a disaster or unforeseen accident is extremely important. However, current technology makes it difficult to provide accurate evacuation routes and alternative means in real time and in multiple languages, and customized information tailored to individual users is also insufficient. This can lead to anxiety and confusion among international travelers and users with diverse backgrounds during emergencies.

[0613] 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.

[0614] In this invention, the server includes means for acquiring the user's location information, means for acquiring information from external sources to determine an emergency situation, and means for generating prompt sentences using a generative AI model to create sentences for instructing a rapid response. This enables rapid and appropriate evacuation guidance and support tailored to the individual needs of the user when they face an emergency.

[0615] "Means of acquiring location information" refers to the technologies and devices necessary to determine the user's current location, and this includes functions that measure location using GPS and Wi-Fi data.

[0616] "Means of obtaining information from information sources" refers to technologies and devices for collecting the latest information on disasters, traffic, and weather from external databases and APIs.

[0617] "Means for determining an emergency situation" refers to technologies and methods for analyzing acquired information and user location data to determine whether a disaster or crisis is occurring.

[0618] "Methods using generative AI models" refer to methods that utilize artificial intelligence technology, such as natural language processing, to automatically generate instruction texts to be provided to the user.

[0619] "Means for creating instructions for rapid response" refers to technologies and methods aimed at promptly providing users with guidance for evacuation and ensuring their safety using generated instructional texts.

[0620] A "multilingual interface" refers to a system that automatically translates and displays information to provide appropriate information to users who speak different languages.

[0621] "Customized instructions that take into account behavioral history" refers to a method of providing information and instructions optimized for each user based on their past behavior and preferences.

[0622] This system is an emergency response system designed to ensure user safety and consists primarily of three elements: servers, terminals, and users.

[0623] The server collects disaster, traffic, and weather information in real time from external sources. These sources include publicly available weather APIs, map APIs, and disaster alert services. Based on the collected information, the server determines whether an emergency has occurred and whether the user may be affected. In the event of an emergency, the server uses a generative artificial intelligence model to generate necessary prompt messages and create instructions that include appropriate evacuation routes and alternative transportation options.

[0624] The device obtains the user's current location via the GPS system and transmits it to the server. It also notifies the user of instructions received from the server in the form of voice or text. A multilingual interface is employed, and information is translated according to the user's language settings for accurate communication. Furthermore, the device considers the user's behavioral history and sends feedback to the server to generate individually customized instructions.

[0625] Users operate the system using their usual devices, such as smartphones or tablets. In the event of an emergency, they receive an alert from their device, allowing them to follow the instructions and take evacuation action. This enables users to evacuate quickly and safely and receive the necessary assistance. For example, in the event of an earthquake, the server immediately analyzes earthquake information, calculates a safe evacuation route, sends it to the device, and provides the user with voice guidance based on the results.

[0626] An example of a prompt message would be, "Calculate the optimal route for the user to safely evacuate from their current location and generate instructions in Japanese." This prompt message allows the server to quickly provide appropriate instructions tailored to the user's situation.

[0627] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0628] Step 1:

[0629] The server collects disaster, traffic, and weather information from external sources. Specifically, the server sends requests to weather APIs, map APIs, and disaster alert services to obtain the latest data. This information is stored in a database on the server and used to determine the status of an emergency. Input requires access to API endpoints and necessary authentication information, while output provides various types of information collected in real time.

[0630] Step 2:

[0631] The device uses GPS to obtain the user's current location and sends this data to the server. Location information is collected through the device's sensors, encrypted according to a protocol, and transmitted. The input is raw data about the user's current location, and the output is location information converted from this data into a format usable by the server.

[0632] Step 3:

[0633] The server uses collected information and the user's location data to determine whether an emergency has occurred. In this process, an AI algorithm compares weather and traffic data with earthquake reports to determine if the user is involved in an emergency. The algorithm's input is information stored in the database and the user's location data, and its output is a flag indicating whether an emergency has occurred.

[0634] Step 4:

[0635] The server uses a generative AI model to generate prompt messages and provide appropriate instructions to the user. These prompt messages suggest the best evacuation route or alternative means based on the user's situation and are sent to the terminal in voice or text format. Inputs include an emergency flag and the user's location information, while output is a customized instruction message.

[0636] Step 5:

[0637] The terminal notifies the user of instructions received from the server. Notifications are delivered via speech synthesis or text messages, and are appropriately translated according to the user's language settings through a multilingual support system. The input is the instruction text from the server, and the output is the notification in a language understandable to the user.

[0638] Step 6:

[0639] The user follows the instructions on the device and moves along the evacuation route. During this process, the device continuously tracks the user's location and sends feedback to the server, which keeps the situation updated in real time. The input is data of the user's actions as they follow the instructions, and the output is updated location information as feedback to the server.

[0640] (Application Example 1)

[0641] 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".

[0642] In recent years, urbanization and the increasing frequency of natural disasters have made ensuring safety in cities a critical issue. Traditional evacuation orders are based on limited information and only provide general guidance, lacking the ability to provide optimal evacuation information tailored to individual circumstances in real time. As a result, it is difficult for residents and visitors to quickly and safely avoid danger.

[0643] 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.

[0644] In this invention, the server includes a device for acquiring location information, a device for collecting information on the environment, means of transportation, and weather from external sources and for evaluating dangerous situations based on the user's location, and a device for calculating the optimal evacuation route or alternative means of transportation to deal with the dangerous situation. This makes it possible for residents and visitors in a city to obtain up-to-date and individualized evacuation routes in real time.

[0645] A "device for acquiring location information" is a device that has the function of identifying the user's current location and transmitting it to a server as digital data.

[0646] A "device for collecting information on the environment, means of transportation, and weather from external sources and evaluating dangerous situations based on the user's location" is a system that analyzes data collected from various databases and sensors to identify and evaluate emergencies related to the user's current location.

[0647] A "device for calculating optimal evacuation routes and alternative means of transportation" is a device that executes an algorithm to calculate the most efficient and safest travel route based on collected data and risk assessment, in order to ensure the safety of the user.

[0648] The system for implementing this invention is formed by three main components: a server, a terminal, and a user.

[0649] The server acquires real-time data on the environment, transportation, and weather from various external sources. Specifically, it connects to diverse databases such as weather data, traffic data, and disaster information, and manages them in an integrated manner. Using this data, the server assesses emergencies and calculates appropriate evacuation routes and alternative transportation options. Advanced algorithms are used in these calculations to provide users with the safest and most efficient evacuation routes.

[0650] The terminal's primary role is to first acquire the user's current location using GPS and transmit that information to the server. As the user moves, the terminal continuously feeds back this location information to the server, enabling a dynamic reassessment of the optimal evacuation route. The terminal also notifies the user of evacuation instructions and warnings sent from the server in multiple languages. This ensures consistent information provision to users of various nationalities.

[0651] Users operate the system using devices such as mobile phones and tablets. In the event of an emergency, they are required to follow instructions from their devices and begin a rapid evacuation. The devices also record the user's activity history and provide a function to individually customize evacuation information based on that history. This customization makes it easy to create an optimal evacuation plan that takes into account the user's past behavior patterns.

[0652] For example, in the event of a sudden flood in a city, this system can instantly analyze the information and present users with safe evacuation routes. Furthermore, when evacuation is necessary, the server can automatically arrange taxis and book accommodations. This minimizes the stress users experience while supporting rapid evacuation.

[0653] To implement this functionality, use the following prompt statements for the model.

[0654] Example input prompts for a generative AI model:

[0655] Development of an app that provides users with real-time information and safe evacuation routes in the event of a disaster in an urban area.

[0656] Required information: User's location, latest weather data, traffic conditions, and location of evacuation shelters.

[0657] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0658] Step 1:

[0659] The device obtains the user's current location using GPS functionality. The input is GPS data, and the output is the user's latitude and longitude information. This ensures accurate location information.

[0660] Step 2:

[0661] The device sends the acquired location information to the server. The input is the latitude and longitude data acquired earlier, and the output is the server receiving this data. This transmission allows the server to determine the user's current location.

[0662] Step 3:

[0663] The server collects environmental, transportation, and weather data from external sources. Input is real-time data from diverse databases, and output is an integrated dataset for analysis. This allows the server to aggregate information for assessing user location-related emergencies.

[0664] Step 4:

[0665] The server uses the user's location information and collected data to assess the likelihood of an emergency. The input is location information and an integrated dataset, and the output is a determination of whether or not an emergency has occurred. This step determines the need for evacuation.

[0666] Step 5:

[0667] The server calculates the optimal evacuation route or alternative mode of transportation in the event of an emergency. Inputs are the determination of the emergency and disaster information, and output is safe and efficient route information. The server can use an algorithm to provide the user with the optimal route.

[0668] Step 6:

[0669] The server sends calculated evacuation routes and alternative transportation information to the terminal. The input is the calculation result, and the output is when the terminal receives it and notifies the user.

[0670] Step 7:

[0671] The terminal displays evacuation instructions to the user based on notifications from the server. Input is evacuation information from the server, and output is a visual or audio notification to the user. This allows the user to take quick and appropriate action.

[0672] Step 8:

[0673] The server makes additional arrangements as needed, including, for example, arranging a taxi or booking accommodation. Input is information based on the user's requests and behavioral patterns, and output is a confirmation of the arrangements. This step allows the user to receive assistance in acting more safely.

[0674] 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.

[0675] This invention is a system that supports users in providing timely and optimal responses, and is characterized by providing personalized support according to the user's emotional state by combining it with an emotion engine. This system consists of four main components: a server, a terminal, an emotion engine, and a user.

[0676] The server collects weather, traffic, and disaster information from multiple external databases and processes it in real time. It receives the user's location information and determines whether an emergency exists based on this. Furthermore, it calculates evacuation routes and alternative transportation options, and determines the most appropriate notification content for the user based on the results of the emotion engine's analysis.

[0677] The device uses GPS to obtain the user's current location and transmits that location information to a server. It also works in conjunction with an emotion engine to analyze the user's emotions in real time based on their voice and actions. This enables support to alleviate the user's tension and anxiety.

[0678] The emotion engine uses sensors to detect the user's facial expressions and voice, and analyzes the resulting emotional data. The analysis results are sent to the terminal and server to adjust the content and method of emergency notifications. This process enables the provision of detailed support tailored to each user's individual situation.

[0679] Users can access this system via their regular devices and receive support tailored to their emotional state. For example, in an emergency, if a user is feeling anxious, the system can provide reassuring instructions.

[0680] As a concrete example, consider the case of a large-scale natural disaster. The server analyzes the extent of the disaster's impact and calculates the optimal evacuation route based on that information. If the emotion engine detects that the user is in a state of confusion, the terminal changes the notification content to something stable and reassuring, and issues instructions to encourage the user to make calm decisions. This enables the user to evacuate appropriately and safely.

[0681] The following describes the processing flow.

[0682] Step 1:

[0683] The user activates the device and enables location services and the emotion engine. The device uses GPS to obtain the user's current location and the emotion engine analyzes the user's voice and facial expressions.

[0684] Step 2:

[0685] The device transmits acquired location and sentiment data to the server. The server receives this information in real time and compares it with weather, traffic, and disaster information in its database.

[0686] Step 3:

[0687] The server determines whether an emergency has occurred based on the user's current location. If an emergency has occurred, it calculates the optimal evacuation route and alternative means of transportation.

[0688] Step 4:

[0689] The emotion engine analyzes the user's emotional state and sends the results to the server. The server adjusts the notification content based on the emotion data. Specifically, if the user is feeling anxious, it generates instructions that provide reassurance.

[0690] Step 5:

[0691] The server sends calculated evacuation routes and notification content to the terminal. The terminal notifies the user of the received information via voice and visual means, prompting them to take emergency action.

[0692] Step 6:

[0693] The user begins evacuation actions and the use of alternative transportation according to instructions from the device. The device continuously monitors the user's location and emotional state and sends additional information to the server as needed.

[0694] Step 7:

[0695] If necessary, the server will devise further support measures for the terminal user, such as booking taxis or rebooking accommodations. This will allow the user to complete their evacuation safely and with peace of mind.

[0696] (Example 2)

[0697] 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".

[0698] While systems already exist to support user actions during disasters and emergencies, these systems are limited in their ability to provide appropriate support because they cannot take into account the user's emotional state. This challenge includes the fact that the information provided may not be sufficiently reassuring to users who are feeling anxious or frightened.

[0699] 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.

[0700] In this invention, the server includes information gathering means that collect information on the environment, movement, and weather from an external database and determine the occurrence of an emergency based on the user's current location; emotion analysis means that perform emotion analysis and adjust the content of emergency notifications according to the user's emotional state based on the analysis results; and notification means that send emergency notifications to the user. As a result, the user can receive information that is appropriate to their emotional state and act appropriately with a sense of security.

[0701] "Location information acquisition means" refers to devices or technologies used to determine a user's current location, and typically involves collecting location data using GPS functionality.

[0702] "Information gathering means" refers to devices and technologies that acquire information on the environment, movement, and weather from external databases and gather information necessary for users to make informed decisions.

[0703] "Calculation means" refers to devices and technologies that calculate the optimal evacuation route or alternative means for the user based on acquired information.

[0704] "Emotional analysis means" refers to devices and technologies that analyze a user's voice and actions to estimate the user's emotional state, and the results are used to adjust notification content.

[0705] "Notification means" refers to devices or technologies used to provide information to users, such as sending notifications via text messages or voice.

[0706] "Reservation methods" refer to devices or technologies that automatically arrange evacuation routes and accommodations as needed.

[0707] This invention is a system for providing appropriate information according to the user's emotional state. The system consists of four main elements: a server, a terminal, an emotion engine, and the user.

[0708] The server collects and processes environmental, movement, and weather information in real time from multiple external databases. This includes databases from the Japan Meteorological Agency, traffic management systems, and disaster information systems. The server combines the collected information with the user's location to determine whether an emergency has occurred. If action is required, it calculates evacuation routes and alternative transportation options, and determines the most appropriate notification content for the user based on the analysis results of the emotion engine.

[0709] The device uses the GPS built into the user's device to obtain the user's current location and transmits that location information to the server. Furthermore, the device works in conjunction with an emotion engine and uses sensors such as microphones and cameras to analyze the user's voice and actions in real time. This allows the device to understand the user's emotional state and provide data to the server to adjust notification content as needed.

[0710] The emotion engine analyzes the user's facial expressions and voice data acquired from sensors to estimate the user's emotional state with high accuracy. The analysis results are sent to the server and terminal and used to adjust the content and method of emergency notifications.

[0711] Users can utilize this system through their everyday devices to receive support tailored to their individual emotional state. Specifically, even in emergencies, they can take calm action based on the reassuring information provided by the system. For example, in the event of a large-scale natural disaster, the server analyzes the extent of the disaster's impact and calculates the optimal evacuation route. When the emotion engine detects that the user is feeling anxious, the device changes the notification content to something reassuring, encouraging the user to make calm decisions.

[0712] A concrete example of a related prompt message would be to input the instruction, "Generate the optimal evacuation instructions based on the user's emotional state," into the AI ​​model. In this way, the system can respond flexibly to a variety of situations and provide a safe environment for the user.

[0713] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0714] Step 1:

[0715] The device uses its built-in GPS module to obtain the user's current location in real time. The acquired location information is sent from the device to the server. Specifically, the location information is updated every 15 seconds.

[0716] Step 2:

[0717] The server collects environmental, movement, and weather information in real time from external databases. The server obtains data from the Japan Meteorological Agency, traffic management systems, and disaster information systems via APIs and analyzes it. The resulting organized information is then combined with user location information and used for subsequent processing.

[0718] Step 3:

[0719] The server determines whether an emergency has occurred based on the user's location information and other collected data. This process uses a Geographic Information System (GIS) to determine if the user's current location is within the disaster's affected area. The result of this determination indicates whether there is an urgent need.

[0720] Step 4:

[0721] The device uses an emotion engine to analyze the user's voice and actions in real time. It uses a combination of speech recognition and image analysis technologies to estimate the user's emotional state. The input for this analysis is the user's voice and facial expression data, and the output is the result of the emotional state assessment.

[0722] Step 5:

[0723] The server uses the sentiment analysis results sent from the sentiment engine to determine the content of the emergency notification. If the user is feeling anxious, it uses a generative AI model to generate a reassuring notification. An example of a prompt is, "Generate a message to alleviate the user's anxiety." The output is the content of the notification to be sent to the user.

[0724] Step 6:

[0725] Users check notifications received from their devices and act according to the instructions. Specifically, this includes actions based on instructions to move to a safe place or to stay calm. Notifications are delivered via text message or voice, and actions are triggered after the user acknowledges them.

[0726] (Application Example 2)

[0727] 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".

[0728] In modern urban environments, it is crucial to provide users with prompt and appropriate evacuation information in the event of sudden emergencies or natural disasters. However, simply issuing uniform notifications without considering users' emotional states is insufficient to adequately alleviate anxiety and confusion. In addition, diverse means of providing information that accommodate linguistic and cultural differences are required. This invention provides a system that enables flexible information provision tailored to users' emotional states in order to solve these problems.

[0729] 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.

[0730] In this invention, the server includes location information acquisition means for obtaining the user's current location, information collection means for collecting information on weather, traffic, and disasters from external information sources and determining the occurrence of an emergency based on the user's location, and calculation means for monitoring the user's emotional state in real time using speech recognition and facial expression analysis and calculating the optimal evacuation route or alternative means of transportation in response to an emergency based on the results. This makes it possible to provide instructions that give the user a sense of security according to their emotional state.

[0731] "Location information acquisition means" is a general term for technologies and devices used to accurately obtain a user's current location.

[0732] "Information gathering means" refers to elements that collect data on weather, traffic, and disasters from external sources and have the function of determining the occurrence of an emergency in relation to the user's location.

[0733] "Emotional state" refers to the user's psychological or emotional state, and is measured through voice and facial expression analysis.

[0734] "Speech recognition" is a technology that analyzes a user's spoken words and converts them into text information, and is used to understand emotions.

[0735] "Facial expression analysis" is a technology that estimates a user's emotions from their facial expressions and is used for real-time emotion monitoring.

[0736] A "computational tool" is a technology that has the function of calculating the optimal evacuation route or alternative means of transportation based on the user's location and emotional state.

[0737] "Notification methods" is a general term for technologies and interfaces used to communicate necessary information and instructions to users in an appropriate format.

[0738] A "procedure management system" is an element that has the function of automatically arranging evacuation and accommodation reservations as needed.

[0739] This invention constructs a system that enables the provision of optimal information based on the user's emotional state. The following describes how this system is implemented.

[0740] The server receives GPS location information transmitted from the user's device and, in conjunction with an external information database, collects weather, traffic, and disaster-related data in real time. Using this data, the server determines whether an emergency has occurred based on the user's location and calculates evacuation routes and alternative transportation options accordingly.

[0741] The device is equipped with voice recognition and facial expression analysis technology, which monitors the user's emotional state in real time. If the user is feeling tense or anxious, the server uses the emotional data obtained from the device to generate a reassuring notification.

[0742] The notification system provides users with optimal instructions that take emotional information into account. For example, if a sudden weather change occurs during a large-scale urban event, the system can send a message to the user's device such as, "We have confirmed the route from your current location to the nearest shelter. Please proceed calmly."

[0743] In this process, a generative AI model is used to automatically generate customized instruction prompts for each user. An example of a prompt might be, "Create guidance to support optimal evacuation actions based on current weather conditions and the user's emotional state." In this way, it is possible to provide flexible and appropriate emergency responses to users.

[0744] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0745] Step 1:

[0746] The server receives GPS data transmitted from the terminal and determines the user's current location. It analyzes the GPS data as input and generates output as geographical information. This allows the server to determine the user's precise location.

[0747] Step 2:

[0748] The server uses location data to connect with external information sources and obtain the latest data on weather, traffic, and disasters. The input is location data, and by making API calls and other actions based on this data, it obtains relevant environmental information as output. This allows the user to understand the situation around them.

[0749] Step 3:

[0750] The device monitors the user's emotional state using voice recognition and facial expression analysis. Audio and video data from sensors are used as input, which is then analyzed to output emotional information. This analysis allows for real-time understanding of the user's current emotional state.

[0751] Step 4:

[0752] The server integrates collected environmental information and emotional information from terminals to determine whether an emergency has occurred. Based on the environmental and emotional information as input, it uses logic to determine if an emergency has occurred and outputs an indicator of the degree of urgency.

[0753] Step 5:

[0754] The server calculates the optimal evacuation route and alternative transportation based on the urgency level. The input consists of an urgency index and location information, which is analyzed to output the most appropriate route for the user. This determines the specific means of transportation needed if an action is required.

[0755] Step 6:

[0756] The device uses a generative AI model to generate notification content as prompts that respond to the user's emotions. Based on emotional information and evacuation routes as input, it outputs notification messages that provide reassurance to the user. By generating prompts, notifications optimized for the user are created.

[0757] Step 7:

[0758] Users receive notifications from their devices and act calmly based on them. The outputted notification message serves as input, and users take appropriate action or move accordingly. This allows them to act safely and with a sense of security.

[0759] 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.

[0760] 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.

[0761] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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."

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] The following is further disclosed regarding the embodiments described above.

[0781] (Claim 1)

[0782] A means for obtaining location information to obtain the user's current location,

[0783] An information gathering method that collects information on disasters, traffic, and weather from an external database and determines the occurrence of an emergency based on the user's current location,

[0784] A calculation means for calculating the optimal evacuation route or alternative means of transportation to respond to the aforementioned emergency,

[0785] A notification means for sending emergency notifications to users based on the aforementioned evacuation route or alternative means of transportation,

[0786] A booking system that automatically arranges evacuation and accommodation reservations as needed,

[0787] A system that includes this.

[0788] (Claim 2)

[0789] The system according to claim 1, having a multilingual display interface to accommodate a diverse range of international users.

[0790] (Claim 3)

[0791] The system according to claim 1, which generates customized instructions taking into account the user's behavioral history when providing the aforementioned evacuation route or alternative means.

[0792] "Example 1"

[0793] (Claim 1)

[0794] A means of obtaining the user's location information,

[0795] A means of obtaining disaster, traffic, and weather information from external sources and determining an emergency based on the user's current location,

[0796] A means for calculating the optimal evacuation route or alternative means to respond to an emergency,

[0797] A means of sending emergency notifications to users,

[0798] A system that automatically arranges evacuation and accommodation as needed,

[0799] A means of tracking user behavior data and coordinating emergency response measures,

[0800] A means for generating prompt sentences using a generative artificial intelligence model and creating sentences to instruct a rapid response,

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, comprising a multilingual interface.

[0804] (Claim 3)

[0805] The system according to claim 1, which takes into account the user's behavioral history and generates customized instructions.

[0806] "Application Example 1"

[0807] (Claim 1)

[0808] A device for acquiring location information,

[0809] A device for collecting environmental, transportation, and weather information from external sources and for assessing hazardous situations based on the user's location,

[0810] A device for calculating the optimal evacuation route or alternative means of transportation to deal with the aforementioned dangerous situation,

[0811] A device for sending warnings to the user based on the aforementioned evacuation routes and alternative means of transportation,

[0812] A device for automatically arranging transportation and accommodation upon request,

[0813] A device with an interface that provides real-time responses to dangerous situations and enhances urban safety,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, which can display diverse languages ​​and enable use by multinational users.

[0817] (Claim 3)

[0818] The system according to claim 1, which, when providing the aforementioned evacuation route or alternative means, creates a guide that is individually tailored to the user's behavioral history.

[0819] "Example 2 of combining an emotion engine"

[0820] (Claim 1)

[0821] A means for obtaining location information to obtain the user's current location,

[0822] An information gathering means that collects information on the environment, movement, and weather from an external database and determines the occurrence of an emergency based on the user's current location,

[0823] A calculation means for calculating the optimal evacuation route or alternative means to respond to the aforementioned emergency,

[0824] An emotion analysis means that performs emotion analysis and adjusts the content of emergency notifications according to the user's emotional state based on the analysis results,

[0825] A notification means for sending an emergency notification to the user based on the aforementioned evacuation route or alternative means,

[0826] A reservation system that automatically arranges evacuation and accommodation reservations as needed,

[0827] A system that includes this.

[0828] (Claim 2)

[0829] The system according to claim 1, having a multilingual display interface to accommodate a diverse range of international users.

[0830] (Claim 3)

[0831] The system according to claim 1, which, when providing the aforementioned evacuation route or alternative means, generates customized instructions that take into account the user's behavioral history and further adjusts them based on the user's emotional state.

[0832] "Application example 2 when combining with an emotional engine"

[0833] (Claim 1)

[0834] A means for obtaining location information to obtain the user's current location,

[0835] Information gathering means that collects information on weather, traffic, and disasters from external information sources and determines the occurrence of an emergency based on the user's location,

[0836] A computational means that monitors the user's emotional state in real time using speech recognition and facial expression analysis, and calculates the optimal evacuation route or alternative means of transportation in an emergency based on the results,

[0837] A notification means that sends an emergency notification to the user based on the aforementioned evacuation route or alternative means of transportation, and provides instructions that give a sense of security according to the user's emotional state,

[0838] A procedural management system that automatically arranges evacuation and accommodation reservations as needed,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, having a multilingual display interface to accommodate a diverse range of international users.

[0842] (Claim 3)

[0843] The system according to claim 1, which generates customized instructions that take into account the user's behavioral history and emotional information when providing the aforementioned evacuation route or alternative means. [Explanation of Symbols]

[0844] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for obtaining location information to obtain the user's current location, An information gathering method that collects information on disasters, traffic, and weather from an external database and determines the occurrence of an emergency based on the user's current location, A calculation means for calculating the optimal evacuation route or alternative means of transportation to respond to the aforementioned emergency, A notification means for sending emergency notifications to users based on the aforementioned evacuation route or alternative means of transportation, A booking system that automatically arranges evacuation and accommodation reservations as needed, A system that includes this.

2. The system according to claim 1, having a multilingual display interface to accommodate a diverse range of international users.

3. The system according to claim 1, which generates customized instructions taking into account the user's behavioral history when providing the aforementioned evacuation route or alternative means.

Images