system

Abstract

We provide the system. [Solution] An information processing device that provides users with information regarding the suspension of public transportation, A means for receiving the user's travel route setting, Means for collecting real-time information related to transportation from multiple sources, A means of analyzing collected information to detect anomalies, Means for calculating an alternative route based on detected anomalies, A means for sending a notification to a medium specified by the user, 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 persona chatbot control method 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 in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When a public transportation stop or delay occurs, it is difficult for visitors, people with hearing impairments, the elderly, and travelers to quickly understand and respond to the situation. In general guidance systems, real-time information provision is insufficient, and there are often deficiencies in foreign language support. This poses a problem of increasing anxiety and confusion during travel.

Means for Solving the Problems

[0005] This invention provides a system that collects and analyzes real-time traffic information from multiple sources based on a travel route set by the user, and calculates an alternative route in the event of an anomaly. It includes means for notifying users of information in multiple languages, and by conveying the situation in real time and accurately, it reduces inconvenience and confusion caused by the suspension of public transportation. This system also provides a link to display map information, helping users easily understand and select alternative means of transport.

[0006] An "information processing device" is a device that collects, analyzes, and outputs data, and has the ability to automatically perform specific tasks.

[0007] "Users" refers to anyone who receives information or services through this system, and includes visitors, people with hearing impairments, the elderly, travelers, and others who particularly need transportation information.

[0008] "Setting a travel route" refers to the act of a user inputting route information into the system to reach their destination, and this information forms the basis for the system's information analysis.

[0009] "Information sources" refer to multiple sources that provide real-time information about traffic, including news media, official website sites, and social media.

[0010] "Real-time information" refers to the latest information on ongoing situations and events, and the collected data is immediately reflected to users.

[0011] "Analysis" refers to the process of processing collected information to identify abnormal situations and make important situational judgments, and is carried out based on a specific methodology.

[0012] An "abnormality" refers to an event that deviates from the normal operation of public transportation, such as accidents, cancellations, or delays.

[0013] An "alternative route" refers to other means of transportation or routes to reach a destination in the event of an anomaly, and is a desirable option that the system provides to the user.

[0014] A "notification" refers to a message sent to the user to convey the analyzed information, and is transmitted through a specific medium.

[0015] "Multilingual generation" refers to the ability to generate information and communicate in the languages ​​that users who speak different languages ​​need.

[0016] A "map information display link" refers to a function that provides a connection to a digital map that users can use to visually understand alternative routes. [Brief explanation of the drawing]

[0017] [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]It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of 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.

[0021] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] The present invention relates to a system comprising an information processing device that provides users with real-time information regarding public transportation and promptly presents alternative routes in the event of an anomaly. This system consists of multiple elements, including a server, terminals, and users.

[0039] First, the user uses their device and downloads a dedicated application. Within the application, they register their language settings and frequently used train and bus routes. This allows the system to build a user profile and personalize the information.

[0040] Based on the aforementioned profile, the server periodically and automatically collects real-time information about public transport from multiple sources. These sources include social media, real-time search services, and the official websites of each railway company. The information collected by the server is stored in a database, and this information is analyzed using natural language processing technology.

[0041] Next, the server detects traffic anomalies (e.g., accidents, delays, cancellations). Based on this analysis, if an anomaly occurs, the server calculates alternative routes related to the affected lines. This calculation takes into account various factors, including travel time to the destination, cost, and operating schedules.

[0042] Once an alternative route is determined, the server creates a notification for the user and sends it to their device. This notification is delivered in the user's preferred language and through their messaging app (e.g., LINE). The notification may include details of the alternative route and links to further transportation options. This allows the user to continue their journey with peace of mind.

[0043] As a concrete example, consider a scenario where a user is using a train in a city during peak hours and the line is suddenly stopped due to a personal injury accident. This system uses a server to collect accident information and, based on the analysis results, calculates alternative routes (e.g., nearby bus routes or other train lines). Then, it notifies the user's terminal of the available alternative routes and the time required in multiple languages. In this way, the user can quickly obtain options to reach their destination without confusion.

[0044] This system will enable visitors, the hearing impaired, the elderly, and travelers to efficiently utilize real-time traffic information and respond flexibly to disruptions in public transport. This implementation will provide a safe and secure means of transportation for all who use public transport.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user installs a dedicated application on their device and registers an account. Here, the user registers their language settings, the train and bus routes they use, and the messaging app they want to receive notifications from. The device sends this information to the server to create a user profile.

[0048] Step 2:

[0049] The server periodically monitors traffic information by collecting real-time data from SNS APIs, search services, and railway company websites. The server accesses each data source, extracts new information, and stores it in the database.

[0050] Step 3:

[0051] The server analyzes the collected data using natural language processing to check the operating status of transportation services. This analysis detects abnormal situations such as accidents and delays. The server identifies the abnormal information and determines whether it will affect users.

[0052] Step 4:

[0053] When an anomaly is detected, the server begins calculating alternative routes for the affected lines. Using an optimized routing algorithm, it evaluates alternative routes to the destination and determines the best alternative, taking into account factors such as travel time and cost.

[0054] Step 5:

[0055] The server generates a notification based on the provided alternative route information. The notification is prepared in multiple languages ​​according to the user's language settings, and the messaging app is ready to send the notification.

[0056] Step 6:

[0057] The device receives notifications sent from the server and displays them to the user as push notifications. The notifications include a description of the current situation, along with suggested alternative modes of transportation and links.

[0058] Step 7:

[0059] The user checks the notifications on their device and selects a mode of transportation to their destination according to the provided alternative route guidance. The device provides maps and additional information as needed to support the user's smooth journey.

[0060] (Example 1)

[0061] 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."

[0062] A challenge for users of public transport is the difficulty in quickly finding appropriate alternative routes in the event of sudden transportation disruptions. Visitors, the hearing impaired, the elderly, and tourists, in particular, may experience confusion and anxiety due to language barriers and unfamiliar transportation environments. Furthermore, the information provided during disruptions may be insufficient, and they may not be able to obtain information that meets their individual needs.

[0063] 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.

[0064] In this invention, the server includes a device for receiving user travel route settings, a device for collecting real-time traffic-related data from multiple information sources, and a device for analyzing the collected data to detect anomalies. This enables the rapid presentation of personalized alternative routes suitable for the user's situation and language when an anomaly occurs.

[0065] "User" refers to an individual or group that uses this system to obtain information about public transportation and uses that information to travel.

[0066] A "device that accepts travel route settings" refers to a device that allows users to input or save information about their planned travel route.

[0067] "Information sources" refer to the sources from which traffic conditions data is disseminated, and these include social media, real-time search services, and official websites of transportation companies.

[0068] "Real-time data" refers to data that shows the current status of transportation services and is continuously and rapidly updated.

[0069] A "data collection device" refers to a device that has the function of acquiring necessary data from multiple sources and storing it within the system.

[0070] A "device for analyzing and detecting anomalies" refers to a device that uses natural language processing technology or other methods to identify unusual situations in transportation systems from collected data.

[0071] A "device for calculating alternative routes" refers to a device that calculates the optimal means of transportation or route in response to detected anomalies in the transportation system.

[0072] A "notification sending device" refers to a device that sends information via messaging apps or other communication methods to deliver calculated alternative route information in a manner chosen by the user.

[0073] "Multiple conditions to consider in the event of an anomaly" refers to various factors used when calculating alternative routes, including travel time, cost, and operating schedule.

[0074] In its embodiment, this system primarily consists of a server and user terminals. Specifically, the server is responsible for collecting real-time traffic-related data from multiple sources and detecting anomalies by analyzing that data. The server uses analysis software developed with programming languages ​​such as Python and employs natural language processing techniques to analyze the collected data. Machine learning algorithms and text mining techniques are used in the analysis, enabling accurate detection of accidents and delays in transportation systems.

[0075] The user interacts with the system through their device. A dedicated application is installed on the device, and the user uses this application to configure their travel route. This application runs on iOS and Android® operating systems.

[0076] The server automatically calculates an alternative route when it detects an anomaly. The calculation takes into account factors such as the travel schedule, travel time, and cost. The calculation results are translated into the user's specified language and notified to the user via a messaging application (e.g., a messaging platform). The notification may include links to map information and travel information.

[0077] As a concrete example, consider a scenario where a user is using a train in a city during peak hours and the line is suddenly stopped due to an accident. This system quickly collects and analyzes accident information and suggests alternative modes of transportation. For example, it would recommend using the nearest bus or other train lines, and also notify the user of necessary transfer times and fares.

[0078] An example of a prompt message generated using an AI model is as follows: "We want to design a system that allows users to individually configure public transport information through a downloaded application and provides alternative routes in real time in case of anomalies. Please provide specific steps regarding the data sources, analysis methods, and notification methods to be used."

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The user downloads a dedicated application to their device and opens it. Within the application, the user registers their frequently used transportation routes and preferred languages ​​to create a profile. The input consists of the user's route and language information, and the output generates user-specific profile data, which is then sent to the server.

[0082] Step 2:

[0083] The server collects real-time transportation-related data from sources such as social media, real-time search services, and official transportation websites, based on the user's profile. The input is transportation data from external sources, and the output is stored in a database as necessary public transportation operation data. This process involves retrieving data using APIs and saving it to a storage system.

[0084] Step 3:

[0085] The server uses natural language processing technology to analyze the collected data and detect anomalies in transportation systems. The input is real-time transportation data stored in a database, and the output is data containing anomaly information as a result of the analysis. Here, predictive analysis using a machine learning model is performed to determine whether or not an anomaly is present.

[0086] Step 4:

[0087] The server calculates alternative routes based on detected anomalies. The calculation takes into account factors such as operating schedules, travel time, and costs. Inputs are anomaly information and available public transport schedules and route data, while output is optimal alternative route information. A route calculation algorithm is used to determine the best route from the available options.

[0088] Step 5:

[0089] The server generates a notification about the calculated alternative route and sends it to the terminal using the method specified by the user. The input is the optimal alternative route information, and the output is the notification message displayed on the user's terminal. A language conversion system is used to translate the information into the user's language and deliver it through the messaging application.

[0090] Step 6:

[0091] The user checks the received notification on their device and follows the provided alternative route. The input is the notification message, and the output is the user's guideline for action. The user follows the map information and instructions provided in the notification and continues their journey appropriately.

[0092] (Application Example 1)

[0093] 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."

[0094] Unexpected stoppages and delays in public transport pose a challenge, particularly for visitors, the hearing impaired, the elderly, and travelers, making it difficult to reach their destinations. Furthermore, with the expected widespread use of autonomous vehicles in the future, efficient route rerouting in the event of disruptions is required. Addressing these issues necessitates the collection of real-time traffic information and the rapid provision of alternative routes tailored to individual travel paths.

[0095] 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.

[0096] In this invention, the server includes means for receiving user travel route settings, means for collecting real-time information related to transportation from multiple information sources, means for analyzing the collected information to detect anomalies, means for calculating alternative routes based on detected anomalies, means for transmitting notifications to a medium specified by the user, means for optimizing the route within the autonomous vehicle, and means for presenting alternative road routes in the event of traffic anomalies. This enables users to quickly obtain options to reach their destination without confusion, even in the event of transportation anomalies.

[0097] A "visitor" is someone who is visiting an unfamiliar place and who wants to understand traffic information more easily.

[0098] A "person with a hearing impairment" is someone who has a hearing loss and needs to receive information through sight.

[0099] "Elderly people" refers to individuals who, due to their age, require special consideration when using public transportation.

[0100] A "traveler" is someone who moves away from their place of residence for the purpose of sightseeing or business.

[0101] An "information processing device" is a computer system that collects and analyzes information and makes decisions automatically.

[0102] "Means for accepting travel route settings" refers to a function that provides an interface for users to set a route to their destination.

[0103] "Means of collecting real-time information related to transportation from multiple sources" refers to the function of obtaining the latest transportation information from various media and databases.

[0104] "Means of analyzing collected information to detect anomalies" refers to a function that analyzes acquired data and identifies unusual conditions or problems.

[0105] "Means for calculating alternative routes" refers to algorithms used to find the optimal alternative route when an anomaly occurs.

[0106] "Means of sending notifications" refers to a function that uses communication technology to deliver information and instructions to users.

[0107] "Means for optimizing the route within an autonomous vehicle" refers to a function that updates and adjusts the optimal route to the destination in real time within an autonomous vehicle.

[0108] "Means of suggesting alternative road routes in the event of traffic abnormalities" refers to a function that suggests alternative road routes that can be used when traffic problems occur.

[0109] This invention details a method for realizing a system that collects traffic information in real time and provides users with the optimal travel route. The system is composed primarily of a server, a terminal, and a user.

[0110] The server uses a computing system designed to collect and analyze real-time data on public transport from multiple sources. The hardware includes server computers with powerful processors and large memory capacities, and the software utilizes high-performance scripting languages ​​such as Python. The geopy library is also used for geographical calculations of the transport data. The server continuously analyzes this data, detects transport anomalies, and calculates alternative routes.

[0111] The terminal is a device in which users register information about their travel routes and receive notifications sent from a server. A dedicated application is installed on the terminal, and users input information about their destinations through this application. Notifications are generated based on the user's pre-configured language and are delivered via a messaging app such as LINE.

[0112] As a concrete example, consider a scenario where a user is traveling using public transportation in a major city and a traffic anomaly occurs. In this system, the server immediately collects and analyzes the information and calculates the optimal alternative route. This information is then notified to the user's terminal in multiple languages. As a result, the user can safely reach their destination using the newly suggested route.

[0113] An example of a prompt to input into a generating AI model would be: "Please tell me the shortest alternative route to the tourist destination. If the train is unavailable, please also suggest which road to take."

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] The user downloads a dedicated application to their device and enters information about their travel route and the modes of transportation they will use. This information is sent to a server by the application and stored as the user's profile. The input is information about the user's selected route and modes of transportation, and the output is individual user profile data on the server.

[0117] Step 2:

[0118] The server collects real-time data on public transport from multiple sources, including social media, search services, and the official websites of each transport provider. The server sends queries to these sources and receives response data. The input is raw data obtained from each source, and the output is real-time transport data integrated into the server.

[0119] Step 3:

[0120] The server analyzes the collected data using natural language processing techniques to detect any anomalies (e.g., delays or cancellations). The input is the real-time traffic data obtained in step 2, and the output is a list of detected traffic anomalies. Specifically, the server uses a keyword detection algorithm to identify information related to the problem.

[0121] Step 4:

[0122] The server calculates alternative routes based on detected anomalies. This calculation takes into account user profile information, as well as factors such as travel time to the destination, cost, and schedule. Inputs are the user profile and anomaly information, while output are multiple alternative route candidates. A route optimization algorithm is used for this specific operation.

[0123] Step 5:

[0124] The server notifies the user's device of the calculated alternative route via the language and media (e.g., a messaging app) specified by the user. The input is the detailed information of the alternative route, and the output is the notification message displayed on the user's device. Specifically, the server generates the notification message in multiple languages ​​and delivers it via the specified media.

[0125] Step 6:

[0126] The device receives a notification, and the user can review the suggested alternative route. At this point, the user can choose the best mode of travel based on the new information. The input is the notification message from the server, and the output is reference information to support the user's decision-making. Specifically, the device visually displays the notification message.

[0127] 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.

[0128] This invention provides a system that offers appropriate information to users during public transportation stoppages or delays, and furthermore, provides information that takes into account the emotional state of the users. This system is implemented by multiple components, including an information processing device, an emotion engine, a terminal, and a user.

[0129] First, the user installs a dedicated application on their device and registers an account. Within the application, the user configures language settings, train and bus route information to use, and messaging apps to receive notifications. The device then sends this user information to the server and sets up the profile.

[0130] The server periodically collects real-time traffic information from multiple sources. These sources include social media, real-time search services, and the official websites of various transportation companies. The collected information is stored in a database on the server and analyzed using natural language processing techniques.

[0131] The server detects transportation anomalies (e.g., accidents, delays) based on the analysis results. If an anomaly is detected, the server calculates a corresponding alternative route using an optimized routing algorithm. This process takes into account factors such as travel time, fare, and departure time.

[0132] Furthermore, the server incorporates an emotion engine. This emotion engine analyzes data obtained from the user via voice or text through the terminal and recognizes the user's emotions in real time. Based on the analysis results, the server adjusts the content and format of notifications according to the user's emotional state.

[0133] Notifications are generated in multiple languages, and the server sends them in an emotionally sensitive manner using the user's specified application. The device receives the notification and displays it to the user as a push notification. This display includes suggested alternative modes of transportation and links to reference map information to help the user easily understand the information.

[0134] As a concrete example, consider a situation where a user is using public transportation in a tourist area and the route is delayed. In this system, the server collects delay information, and an emotion engine detects the user's impatience and anxiety. Subsequently, it generates a reassuring notification, including alternative routes, to help the user quickly choose the appropriate course of action.

[0135] This system will enable visitors, the hearing impaired, the elderly, and travelers to receive real-time, emotionally sensitive traffic information and respond appropriately to any abnormal situations in public transport.

[0136] The following describes the processing flow.

[0137] Step 1:

[0138] The user installs a dedicated application on their device and registers an account. The device sends the user's settings information (language, train lines used, notification apps) to the server to create a user profile.

[0139] Step 2:

[0140] The server regularly collects real-time traffic information from multiple external sources (social media, search engines, and railway company websites). The server stores the information collected this year in a database.

[0141] Step 3:

[0142] The server analyzes the accumulated data using natural language processing technology to detect anomalies in transportation systems (e.g., delays, cancellations). This analysis identifies the nature and scope of the transportation anomaly.

[0143] Step 4:

[0144] If an anomaly is detected, the server begins calculating alternative routes for the affected lines. It applies an algorithm that considers various factors (time, cost, frequency of service) to suggest the best mode of transport for the user.

[0145] Step 5:

[0146] The server uses an emotion engine to analyze voice or text data received from the terminal and identify the user's emotional state. This allows it to tailor notifications to address the user's anxiety and stress levels.

[0147] Step 6:

[0148] The server generates emotionally sensitive notifications in multiple languages ​​and sends them to the user's device via the selected messaging app. The notifications include details about the anomaly, alternative routes, and links to map information.

[0149] Step 7:

[0150] The device receives notifications sent from the server and displays them to the user as push notifications. Based on this information, the user can select an alternative route and continue traveling to their destination.

[0151] (Example 2)

[0152] 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".

[0153] Disruptions and delays in public transportation are particularly stressful for visitors, the hearing impaired, the elderly, and travelers. Furthermore, providing transportation information requires not only conveying information but also considering the emotional state of users. However, conventional systems have been insufficient in providing emotionally sensitive information and multilingual support, meaning users were not always able to utilize the information effectively.

[0154] 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.

[0155] In this invention, the server includes means for setting user route information, means for collecting real-time information related to the traffic network from multiple data sources, means for analyzing the collected data and detecting traffic anomalies, means for calculating alternative routes based on the detected traffic anomalies, means including an emotion engine for analyzing the user's emotional state, means for generating notification content according to the emotional state, and means for transmitting emotionally sensitive notifications to an information medium specified by the user. This makes it possible to acquire traffic information in real time and provide it to the user in a multilingual and emotionally sensitive manner.

[0156] An "information processing system" is a device with multiple functions that provides users with information about the suspension or delay of public transportation.

[0157] "Data sources" refer to various sources of information that provide information about transportation networks, including real-time search services and official websites.

[0158] "Traffic anomaly" refers to any event that disrupts the normal operation of public transportation, including delays, cancellations, and accidents.

[0159] "Route information" refers to information about the route and means of transportation that users use to get to their destination.

[0160] An "emotion engine" is a technology that analyzes a user's emotional state from their voice or text and adjusts the information provided based on that analysis.

[0161] "Notification content" refers to the specific messages and instructions provided to the user, and can be expressed in text, audio, images, etc.

[0162] "Information medium" refers to a means used to send notifications to users, and includes email, messaging apps, and smartphone push notifications.

[0163] This invention is an information processing system that provides users with appropriate and emotionally sensitive information during delays or disruptions in public transportation. This system is implemented through interaction between a server, a terminal, and the user. An overview is provided below.

[0164] The server is responsible for collecting traffic information from multiple data sources and detecting traffic anomalies. These data sources include public transport websites, social media, and real-time search services. The server analyzes the collected data using natural language processing techniques, enabling rapid detection of anomalies such as delays, cancellations, and accidents. When an anomaly is detected, the server calculates alternative routes using an optimized routing algorithm, taking into account factors such as travel time, fare, and available departure times.

[0165] Users install a dedicated application on their device and register an account. Through this application, users can input language settings and transportation route information. The device sends this information to a server to form a user profile. This profile information may include the user's location and settings.

[0166] This system incorporates an emotion engine. The terminal sends voice input and text information from the user to the server, where it is analyzed in real time by the emotion engine. The emotion engine analyzes the tone of the text and the intonation of the voice to recognize the user's emotions. Based on the results, the server generates and customizes notification content according to the emotional state. This is achieved, for example, by sending a reassuring notification to a user who is feeling anxious.

[0167] Notifications are multilingual, with the server generating notifications in the user's chosen language. The server can send these generated notifications through the user's designated messaging app. The device displays the received notification as a push notification, including links to suggested alternative transportation options and map information. This allows the user to efficiently and quickly choose their next course of action.

[0168] As a concrete example, if a user attempts to use a train in a tourist area but the line is delayed, the server analyzes the delay information and detects the user's anxiety using an emotion engine. It then generates a reassuring notification, including alternative routes, and quickly sends it to the user.

[0169] Example of a prompt:

[0170] Please create a description of a system that notifies users when public transportation is delayed. This system will provide appropriate information while taking into account the user's emotional state. As a specific example, please describe how a user in a tourist area might receive delay information.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] User registration and initial setup

[0174] The user installs a dedicated application on their device. Once the installation is complete, the user creates an account and enters information such as language settings and the transportation routes they will use. The device sends this input data to the server to generate a user profile. The input includes the user's personal information and settings, and the output is the user profile stored on the server.

[0175] Step 2:

[0176] Collection of real-time traffic information

[0177] The server periodically collects information about public transportation from multiple data sources. Specifically, it obtains data from social media, real-time search services, and official transportation websites, using APIs to maintain immediacy. The input is transportation information from each data source, which the server stores in a database. The output is raw data used for analysis.

[0178] Step 3:

[0179] Analysis and detection of traffic anomalies

[0180] The server analyzes collected traffic information using natural language processing (NLP) techniques to identify anomalies such as traffic delays and cancellations. The input is raw data stored in a database, and NLP extracts anomaly patterns from the data. The output is the detected traffic anomaly information.

[0181] Step 4:

[0182] Calculation of alternative routes

[0183] The server calculates alternative routes based on identified traffic anomalies. It uses an optimized routing algorithm that considers travel time, fares, and available departure times based on the user profile. Inputs are traffic anomaly information and user profiles, while output is information on alternative routes available to the user.

[0184] Step 5:

[0185] Analysis of emotional states using an emotion engine

[0186] The terminal receives voice or text from the user and sends it to the server. The server's emotion engine analyzes this data to recognize the user's emotional state. The input is voice or text input from the user, and the output is the user's emotional state revealed by the analysis.

[0187] Step 6:

[0188] Generating and sending notification content

[0189] The server generates notification content in an emotionally sensitive manner based on the analyzed emotional state. Notifications are created in multiple languages ​​and include alternative route information and relevant map links. Inputs are emotional state and alternative route information, while output is a customized notification sent to the user.

[0190] Step 7:

[0191] Receiving and displaying notifications

[0192] The device receives notifications sent from the server and displays them to the user as push notifications. This process supports multilingual display and directly provides the user with relevant map and route information. The input is notification data from the server, and the output is the information displayed on the user's device.

[0193] (Application Example 2)

[0194] 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".

[0195] Current autonomous mobility devices can optimize routes based on traffic conditions, but they cannot provide information that takes into account the emotional state of passengers, nor can they adjust routes based on that information. As a result, passengers may experience anxiety and stress. Furthermore, because information provided during emergencies is uniform, there is a need for flexible service provision that can meet the individual needs of each passenger.

[0196] 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.

[0197] In this invention, the server includes means for detecting the user's emotional state, means for adjusting notification content based on the detected emotional state, and means incorporated into an autonomous mobile device for optimizing travel routes in accordance with the passenger's real-time emotional state and traffic conditions. This enables a comfortable travel experience that takes the passenger's emotions into consideration.

[0198] "User" refers to an individual or group that receives services provided by an autonomous mobile device or system.

[0199] "Emotional state" refers to the user's psychological reactions and circumstances, and is data analyzed through voice, facial expressions, and other means.

[0200] "Notification content" refers to the information the system provides to the user, and the message is adjusted according to traffic conditions and the user's mood.

[0201] An "autonomous mobile device" is a means of transportation that operates automatically without external intervention, using artificial intelligence and sensor technology.

[0202] "Real-time" refers to a state with virtually no time delay, meaning that information is processed and provided instantly.

[0203] "Traffic conditions" refers to information indicating the state of congestion, accidents, delays, etc., along a travel route.

[0204] "Route optimization" refers to calculating the best possible route to a destination, taking into account factors such as time, distance, and the user's feelings.

[0205] The system that implements this application has multiple components for collecting and analyzing traffic information and user emotional states in real time. The system utilizes software, including Google Cloud's Natural Language API and Microsoft Azure's Emotion Recognition Services, to enable users to move comfortably within autonomous mobile devices.

[0206] The server uses a traffic information API to collect real-time data on current traffic conditions. This data is analyzed using an AI model. Furthermore, it evaluates the user's emotional state from audio and video data obtained through the terminal's sensors. This emotional data is used to determine the optimal route and notification content based on the passenger's psychological needs.

[0207] As a concrete example, if a passenger using an autonomous mobile device is heading to the airport in rainy weather, the server analyzes the passenger's emotional state and provides the shortest route to alleviate stress. At this time, it automatically generates a message to reduce the passenger's anxiety and notifies the device.

[0208] An example of a prompt to be input to the generating AI model would be: "Design an application that generates reassuring messages and suggests the optimal route in real time when passengers in an autonomous vehicle are in a hurry. Please consider emotion recognition data and traffic information." This would enable a dynamic and emotion-sensitive mobility service.

[0209] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0210] Step 1:

[0211] The user installs a dedicated application on their device and registers an account. As input, they set their preferred traffic information and emotional data, and as output, a profile is created on the server. The device then processes this information and sends it to the server.

[0212] Step 2:

[0213] The server collects data in real time from a traffic information API. It uses traffic data obtained from an external API as input and stores traffic conditions in a database as output. The server then analyzes this information using an AI model to detect anomalies.

[0214] Step 3:

[0215] The device's sensors collect the user's voice and facial expressions, and analyze their emotional state. Using voice and video data as input, the output provides numerical values ​​and classification results that evaluate the user's emotional state. The device uses an emotion recognition API to perform the analysis.

[0216] Step 4:

[0217] The server uses collected traffic and sentiment data to calculate the optimal travel route. It takes current traffic data and the user's sentiment state as input, and generates an optimized route plan tailored to each user as output. Route calculation involves calculations based on time, distance, and sentiment data.

[0218] Step 5:

[0219] The server generates notification messages in multiple languages ​​and adjusts the content based on the user's emotional state. Using generated route suggestions and user emotional data as input, it produces reassuring, adjusted messages as output. The server utilizes a natural language generation model to prepare push notifications.

[0220] Step 6:

[0221] The device pushes notifications to the user, clearly presenting suggested options along with links to map information. It receives notification data and route links from the server as input, and provides the user with visual information as output. The device uses its display to show this information.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] [Second Embodiment]

[0226] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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).

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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".

[0238] The present invention relates to a system comprising an information processing device that provides users with real-time information regarding public transportation and promptly presents alternative routes in the event of an anomaly. This system consists of multiple elements, including a server, terminals, and users.

[0239] First, the user uses their device and downloads a dedicated application. Within the application, they register their language settings and frequently used train and bus routes. This allows the system to build a user profile and personalize the information.

[0240] Based on the aforementioned profile, the server periodically and automatically collects real-time information about public transport from multiple sources. These sources include social media, real-time search services, and the official websites of each railway company. The information collected by the server is stored in a database, and this information is analyzed using natural language processing technology.

[0241] Next, the server detects traffic anomalies (e.g., accidents, delays, cancellations). Based on this analysis, if an anomaly occurs, the server calculates alternative routes related to the affected lines. This calculation takes into account various factors, including travel time to the destination, cost, and operating schedules.

[0242] Once an alternative route is determined, the server creates a notification for the user and sends it to their device. This notification is delivered in the user's preferred language and through their messaging app (e.g., LINE). The notification may include details of the alternative route and links to further transportation options. This allows the user to continue their journey with peace of mind.

[0243] As a concrete example, consider a scenario where a user is using a train in a city during peak hours and the line is suddenly stopped due to a personal injury accident. This system uses a server to collect accident information and, based on the analysis results, calculates alternative routes (e.g., nearby bus routes or other train lines). Then, it notifies the user's terminal of the available alternative routes and the time required in multiple languages. In this way, the user can quickly obtain options to reach their destination without confusion.

[0244] This system will enable visitors, the hearing impaired, the elderly, and travelers to efficiently utilize real-time traffic information and respond flexibly to disruptions in public transport. This implementation will provide a safe and secure means of transportation for all who use public transport.

[0245] The following describes the processing flow.

[0246] Step 1:

[0247] The user installs a dedicated application on their device and registers an account. Here, the user registers their language settings, the train and bus routes they use, and the messaging app they want to receive notifications from. The device sends this information to the server to create a user profile.

[0248] Step 2:

[0249] The server periodically monitors traffic information by collecting real-time data from SNS APIs, search services, and railway company websites. The server accesses each data source, extracts new information, and stores it in the database.

[0250] Step 3:

[0251] The server analyzes the collected data using natural language processing to check the operating status of transportation services. This analysis detects abnormal situations such as accidents and delays. The server identifies the abnormal information and determines whether it will affect users.

[0252] Step 4:

[0253] When an anomaly is detected, the server begins calculating alternative routes for the affected lines. Using an optimized routing algorithm, it evaluates alternative routes to the destination and determines the best alternative, taking into account factors such as travel time and cost.

[0254] Step 5:

[0255] The server generates a notification based on the provided alternative route information. The notification is prepared in multiple languages ​​according to the user's language settings, and the messaging app is ready to send the notification.

[0256] Step 6:

[0257] The device receives notifications sent from the server and displays them to the user as push notifications. The notifications include a description of the current situation, along with suggested alternative modes of transportation and links.

[0258] Step 7:

[0259] The user checks the notifications on their device and selects a mode of transportation to their destination according to the provided alternative route guidance. The device provides maps and additional information as needed to support the user's smooth journey.

[0260] (Example 1)

[0261] 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."

[0262] A challenge for users of public transport is the difficulty in quickly finding appropriate alternative routes in the event of sudden transportation disruptions. Visitors, the hearing impaired, the elderly, and tourists, in particular, may experience confusion and anxiety due to language barriers and unfamiliar transportation environments. Furthermore, the information provided during disruptions may be insufficient, and they may not be able to obtain information that meets their individual needs.

[0263] 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.

[0264] In this invention, the server includes a device for receiving user travel route settings, a device for collecting real-time traffic-related data from multiple information sources, and a device for analyzing the collected data to detect anomalies. This enables the rapid presentation of personalized alternative routes suitable for the user's situation and language when an anomaly occurs.

[0265] "User" refers to an individual or group that uses this system to obtain information about public transportation and uses that information to travel.

[0266] A "device that accepts travel route settings" refers to a device that allows users to input or save information about their planned travel route.

[0267] "Information sources" refer to the sources from which traffic conditions data is disseminated, and these include social media, real-time search services, and official websites of transportation companies.

[0268] "Real-time data" refers to data that shows the current status of transportation services and is continuously and rapidly updated.

[0269] A "data collection device" refers to a device that has the function of acquiring necessary data from multiple sources and storing it within the system.

[0270] A "device for analyzing and detecting anomalies" refers to a device that uses natural language processing technology or other methods to identify unusual situations in transportation systems from collected data.

[0271] A "device for calculating alternative routes" refers to a device that calculates the optimal means of transportation or route in response to detected anomalies in the transportation system.

[0272] A "notification sending device" refers to a device that sends information via messaging apps or other communication methods to deliver calculated alternative route information in a manner chosen by the user.

[0273] "Multiple conditions to consider in the event of an anomaly" refers to various factors used when calculating alternative routes, including travel time, cost, and operating schedule.

[0274] In its embodiment, this system primarily consists of a server and user terminals. Specifically, the server is responsible for collecting real-time traffic-related data from multiple sources and detecting anomalies by analyzing that data. The server uses analysis software developed with programming languages ​​such as Python and employs natural language processing techniques to analyze the collected data. Machine learning algorithms and text mining techniques are used in the analysis, enabling accurate detection of accidents and delays in transportation systems.

[0275] The user interacts with the system through their device. A dedicated application is installed on the device, and the user uses this application to configure their travel route. This application runs on iOS and Android operating systems.

[0276] The server automatically calculates an alternative route when it detects an anomaly. The calculation takes into account factors such as the travel schedule, travel time, and cost. The calculation results are translated into the user's specified language and notified to the user via a messaging application (e.g., a messaging platform). The notification may include links to map information and travel information.

[0277] As a concrete example, consider a scenario where a user is using a train in a city during peak hours and the line is suddenly stopped due to an accident. This system quickly collects and analyzes accident information and suggests alternative modes of transportation. For example, it would recommend using the nearest bus or other train lines, and also notify the user of necessary transfer times and fares.

[0278] An example of a prompt message generated using an AI model is as follows: "We want to design a system that allows users to individually configure public transport information through a downloaded application and provides alternative routes in real time in case of anomalies. Please provide specific steps regarding the data sources, analysis methods, and notification methods to be used."

[0279] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[0280] Step 1:

[0281] The user downloads a dedicated application to the terminal and opens the application. The user registers their frequently used transportation routes and languages in it and creates a profile. The input is the user's route and language information, and as output, user-specific profile data is generated and sent to the server.

[0282] Step 2:

[0283] Based on the user's profile, the server collects real-time traffic-related data from SNS, real-time search services, official websites of transportation agencies, etc. The input is traffic data from external information sources, and the output is stored in the database as the operation data of the necessary public transportation agencies. At this time, the operation of obtaining data using the API and storing it in the storage system is executed.

[0284] Step 3:

[0285] The server analyzes the collected data using natural language processing technology to detect abnormalities in transportation agencies. The input is the real-time traffic data stored in the database, and the output is data containing abnormality information as the analysis result. Here, predictive analysis using a machine learning model is performed, and the operation of determining the presence or absence of abnormalities is performed.

[0286] Step 4:

[0287] The server calculates an alternative route based on the detected abnormality. The calculation takes into account the operation schedule, travel time, cost, etc. The input is the abnormality information and the schedule / route data of available public transportation, and the output is the optimal alternative route information. The operation of determining the optimal route from available options is executed using a route calculation algorithm.

[0288] Step 5:

[0289] The server generates a notification about the calculated alternative route and sends it to the terminal using the method specified by the user. The input is the optimal alternative route information, and the output is the notification message displayed on the user's terminal. A language conversion system is used to translate the information into the user's language and deliver it through the messaging application.

[0290] Step 6:

[0291] The user checks the received notification on their device and follows the provided alternative route. The input is the notification message, and the output is the user's guideline for action. The user follows the map information and instructions provided in the notification and continues their journey appropriately.

[0292] (Application Example 1)

[0293] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0294] Unexpected stoppages and delays in public transport pose a challenge, particularly for visitors, the hearing impaired, the elderly, and travelers, making it difficult to reach their destinations. Furthermore, with the expected widespread use of autonomous vehicles in the future, efficient route rerouting in the event of disruptions is required. Addressing these issues necessitates the collection of real-time traffic information and the rapid provision of alternative routes tailored to individual travel paths.

[0295] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0296] In this invention, the server includes means for receiving user travel route settings, means for collecting real-time information related to transportation from multiple information sources, means for analyzing the collected information to detect anomalies, means for calculating alternative routes based on detected anomalies, means for transmitting notifications to a medium specified by the user, means for optimizing the route within the autonomous vehicle, and means for presenting alternative road routes in the event of traffic anomalies. This enables users to quickly obtain options to reach their destination without confusion, even in the event of transportation anomalies.

[0297] A "visitor" is someone who is visiting an unfamiliar place and who wants to understand traffic information more easily.

[0298] A "person with a hearing impairment" is someone who has a hearing loss and needs to receive information through sight.

[0299] "Elderly people" refers to individuals who, due to their age, require special consideration when using public transportation.

[0300] A "traveler" is someone who moves away from their place of residence for the purpose of sightseeing or business.

[0301] An "information processing device" is a computer system that collects and analyzes information and makes decisions automatically.

[0302] "Means for accepting travel route settings" refers to a function that provides an interface for users to set a route to their destination.

[0303] "Means of collecting real-time information related to transportation from multiple sources" refers to the function of obtaining the latest transportation information from various media and databases.

[0304] "Means of analyzing collected information to detect anomalies" refers to a function that analyzes acquired data and identifies unusual conditions or problems.

[0305] The "means for calculating an alternative route" refers to an algorithm for obtaining an optimal alternative route when an abnormality occurs.

[0306] The "means for sending a notification" refers to the function of delivering information and instructions to the user using communication technology.

[0307] The "means for optimizing a route in an autonomous vehicle" refers to the function of updating and adjusting the optimal route to the destination in real time in an autonomous driving vehicle.

[0308] The "means for presenting an alternative road route during traffic abnormalities" refers to the function of proposing an alternative road route that can be used when a traffic trouble occurs.

[0309] This invention details a method for realizing a system that collects traffic information in real time and provides an optimal travel route for users. It is a system centered around elements such as a server, a terminal, and a user.

[0310] The server uses a computer system designed to collect and analyze real-time data on public transportation from multiple information sources. The hardware used includes a server computer equipped with a powerful processor and a large-capacity memory, and for software, a high-performance scripting language such as Python is used. Also, for geographical calculations of traffic data, the geopy library is utilized. The server continuously analyzes these data, detects traffic abnormalities, and calculates alternative routes.

[0311] The terminal is a device where the user registers information about their travel route and receives notifications sent from the server. A dedicated application is installed on this terminal, and the user inputs destination information through that application. The notifications are generated based on the user's pre-set language and provided through a messaging application such as LINE.

[0312] As a concrete example, consider a scenario where a user is traveling using public transportation in a major city and a traffic anomaly occurs. In this system, the server immediately collects and analyzes the information and calculates the optimal alternative route. This information is then notified to the user's terminal in multiple languages. As a result, the user can safely reach their destination using the newly suggested route.

[0313] An example of a prompt to input into a generating AI model would be: "Please tell me the shortest alternative route to the tourist destination. If the train is unavailable, please also suggest which road to take."

[0314] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0315] Step 1:

[0316] The user downloads a dedicated application to their device and enters information about their travel route and the modes of transportation they will use. This information is sent to a server by the application and stored as the user's profile. The input is information about the user's selected route and modes of transportation, and the output is individual user profile data on the server.

[0317] Step 2:

[0318] The server collects real-time data on public transport from multiple sources, including social media, search services, and the official websites of each transport provider. The server sends queries to these sources and receives response data. The input is raw data obtained from each source, and the output is real-time transport data integrated into the server.

[0319] Step 3:

[0320] The server analyzes the collected data using natural language processing techniques to detect any anomalies (e.g., delays or cancellations). The input is the real-time traffic data obtained in step 2, and the output is a list of detected traffic anomalies. Specifically, the server uses a keyword detection algorithm to identify information related to the problem.

[0321] Step 4:

[0322] The server calculates alternative routes based on detected anomalies. This calculation takes into account user profile information, as well as factors such as travel time to the destination, cost, and schedule. Inputs are the user profile and anomaly information, while output are multiple alternative route candidates. A route optimization algorithm is used for this specific operation.

[0323] Step 5:

[0324] The server notifies the user's device of the calculated alternative route via the language and media (e.g., a messaging app) specified by the user. The input is the detailed information of the alternative route, and the output is the notification message displayed on the user's device. Specifically, the server generates the notification message in multiple languages ​​and delivers it via the specified media.

[0325] Step 6:

[0326] The device receives a notification, and the user can review the suggested alternative route. At this point, the user can choose the best mode of travel based on the new information. The input is the notification message from the server, and the output is reference information to support the user's decision-making. Specifically, the device visually displays the notification message.

[0327] 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.

[0328] This invention provides a system that offers appropriate information to users during public transportation stoppages or delays, and furthermore, provides information that takes into account the emotional state of the users. This system is implemented by multiple components, including an information processing device, an emotion engine, a terminal, and a user.

[0329] First, the user installs a dedicated application on their device and registers an account. Within the application, the user configures language settings, train and bus route information to use, and messaging apps to receive notifications. The device then sends this user information to the server and sets up the profile.

[0330] The server periodically collects real-time traffic information from multiple sources. These sources include social media, real-time search services, and the official websites of various transportation companies. The collected information is stored in a database on the server and analyzed using natural language processing techniques.

[0331] The server detects transportation anomalies (e.g., accidents, delays) based on the analysis results. If an anomaly is detected, the server calculates a corresponding alternative route using an optimized routing algorithm. This process takes into account factors such as travel time, fare, and departure time.

[0332] Furthermore, the server incorporates an emotion engine. This emotion engine analyzes data obtained from the user via voice or text through the terminal and recognizes the user's emotions in real time. Based on the analysis results, the server adjusts the content and format of notifications according to the user's emotional state.

[0333] Notifications are generated in multiple languages, and the server sends them in an emotionally sensitive manner using the user's specified application. The device receives the notification and displays it to the user as a push notification. This display includes suggested alternative modes of transportation and links to reference map information to help the user easily understand the information.

[0334] As a concrete example, consider a situation where a user is using public transportation in a tourist area and the route is delayed. In this system, the server collects delay information, and an emotion engine detects the user's impatience and anxiety. Subsequently, it generates a reassuring notification, including alternative routes, to help the user quickly choose the appropriate course of action.

[0335] This system will enable visitors, the hearing impaired, the elderly, and travelers to receive real-time, emotionally sensitive traffic information and respond appropriately to any abnormal situations in public transport.

[0336] The following describes the processing flow.

[0337] Step 1:

[0338] The user installs a dedicated application on their device and registers an account. The device sends the user's settings information (language, train lines used, notification apps) to the server to create a user profile.

[0339] Step 2:

[0340] The server regularly collects real-time traffic information from multiple external sources (social media, search engines, and railway company websites). The server stores the information collected this year in a database.

[0341] Step 3:

[0342] The server analyzes the accumulated data using natural language processing technology to detect anomalies in transportation systems (e.g., delays, cancellations). This analysis identifies the nature and scope of the transportation anomaly.

[0343] Step 4:

[0344] If an anomaly is detected, the server begins calculating alternative routes for the affected lines. It applies an algorithm that considers various factors (time, cost, frequency of service) to suggest the best mode of transport for the user.

[0345] Step 5:

[0346] The server uses an emotion engine to analyze voice or text data received from the terminal and identify the user's emotional state. This allows it to tailor notifications to address the user's anxiety and stress levels.

[0347] Step 6:

[0348] The server generates emotionally sensitive notifications in multiple languages ​​and sends them to the user's device via the selected messaging app. The notifications include details about the anomaly, alternative routes, and links to map information.

[0349] Step 7:

[0350] The device receives notifications sent from the server and displays them to the user as push notifications. Based on this information, the user can select an alternative route and continue traveling to their destination.

[0351] (Example 2)

[0352] 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".

[0353] Disruptions and delays in public transportation are particularly stressful for visitors, the hearing impaired, the elderly, and travelers. Furthermore, providing transportation information requires not only conveying information but also considering the emotional state of users. However, conventional systems have been insufficient in providing emotionally sensitive information and multilingual support, meaning users were not always able to utilize the information effectively.

[0354] 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.

[0355] In this invention, the server includes means for setting user route information, means for collecting real-time information related to the traffic network from multiple data sources, means for analyzing the collected data and detecting traffic anomalies, means for calculating alternative routes based on the detected traffic anomalies, means including an emotion engine for analyzing the user's emotional state, means for generating notification content according to the emotional state, and means for transmitting emotionally sensitive notifications to an information medium specified by the user. This makes it possible to acquire traffic information in real time and provide it to the user in a multilingual and emotionally sensitive manner.

[0356] An "information processing system" is a device with multiple functions that provides users with information about the suspension or delay of public transportation.

[0357] "Data sources" refer to various sources of information that provide information about transportation networks, including real-time search services and official websites.

[0358] "Traffic anomaly" refers to any event that disrupts the normal operation of public transportation, including delays, cancellations, and accidents.

[0359] "Route information" refers to information about the route and means of transportation that users use to get to their destination.

[0360] An "emotion engine" is a technology that analyzes a user's emotional state from their voice or text and adjusts the information provided based on that analysis.

[0361] "Notification content" refers to the specific messages and instructions provided to the user, and can be expressed in text, audio, images, etc.

[0362] "Information medium" refers to a means used to send notifications to users, and includes email, messaging apps, and smartphone push notifications.

[0363] This invention is an information processing system that provides users with appropriate and emotionally sensitive information during delays or disruptions in public transportation. This system is implemented through interaction between a server, a terminal, and the user. An overview is provided below.

[0364] The server is responsible for collecting traffic information from multiple data sources and detecting traffic anomalies. These data sources include public transport websites, social media, and real-time search services. The server analyzes the collected data using natural language processing techniques, enabling rapid detection of anomalies such as delays, cancellations, and accidents. When an anomaly is detected, the server calculates alternative routes using an optimized routing algorithm, taking into account factors such as travel time, fare, and available departure times.

[0365] Users install a dedicated application on their device and register an account. Through this application, users can input language settings and transportation route information. The device sends this information to a server to form a user profile. This profile information may include the user's location and settings.

[0366] This system incorporates an emotion engine. The terminal sends voice input and text information from the user to the server, where it is analyzed in real time by the emotion engine. The emotion engine analyzes the tone of the text and the intonation of the voice to recognize the user's emotions. Based on the results, the server generates and customizes notification content according to the emotional state. This is achieved, for example, by sending a reassuring notification to a user who is feeling anxious.

[0367] Notifications are multilingual, with the server generating notifications in the user's chosen language. The server can send these generated notifications through the user's designated messaging app. The device displays the received notification as a push notification, including links to suggested alternative transportation options and map information. This allows the user to efficiently and quickly choose their next course of action.

[0368] As a concrete example, if a user attempts to use a train in a tourist area but the line is delayed, the server analyzes the delay information and detects the user's anxiety using an emotion engine. It then generates a reassuring notification, including alternative routes, and quickly sends it to the user.

[0369] Example of a prompt:

[0370] Please create a description of a system that notifies users when public transportation is delayed. This system will provide appropriate information while taking into account the user's emotional state. As a specific example, please describe how a user in a tourist area might receive delay information.

[0371] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0372] Step 1:

[0373] User registration and initial setup

[0374] The user installs a dedicated application on their device. Once the installation is complete, the user creates an account and enters information such as language settings and the transportation routes they will use. The device sends this input data to the server to generate a user profile. The input includes the user's personal information and settings, and the output is the user profile stored on the server.

[0375] Step 2:

[0376] Collection of real-time traffic information

[0377] The server periodically collects information about public transportation from multiple data sources. Specifically, it obtains data from social media, real-time search services, and official transportation websites, using APIs to maintain immediacy. The input is transportation information from each data source, which the server stores in a database. The output is raw data used for analysis.

[0378] Step 3:

[0379] Analysis and detection of traffic anomalies

[0380] The server analyzes collected traffic information using natural language processing (NLP) techniques to identify anomalies such as traffic delays and cancellations. The input is raw data stored in a database, and NLP extracts anomaly patterns from the data. The output is the detected traffic anomaly information.

[0381] Step 4:

[0382] Calculation of alternative routes

[0383] The server calculates alternative routes based on identified traffic anomalies. It uses an optimized routing algorithm that considers travel time, fares, and available departure times based on the user profile. Inputs are traffic anomaly information and user profiles, while output is information on alternative routes available to the user.

[0384] Step 5:

[0385] Analysis of emotional states using an emotion engine

[0386] The terminal receives voice or text from the user and sends it to the server. The server's emotion engine analyzes this data to recognize the user's emotional state. The input is voice or text input from the user, and the output is the user's emotional state revealed by the analysis.

[0387] Step 6:

[0388] Generating and sending notification content

[0389] The server generates notification content in an emotionally sensitive manner based on the analyzed emotional state. Notifications are created in multiple languages ​​and include alternative route information and relevant map links. Inputs are emotional state and alternative route information, while output is a customized notification sent to the user.

[0390] Step 7:

[0391] Receiving and displaying notifications

[0392] The device receives notifications sent from the server and displays them to the user as push notifications. This process supports multilingual display and directly provides the user with relevant map and route information. The input is notification data from the server, and the output is the information displayed on the user's device.

[0393] (Application Example 2)

[0394] 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."

[0395] Current autonomous mobility devices can optimize routes based on traffic conditions, but they cannot provide information that takes into account the emotional state of passengers, nor can they adjust routes based on that information. As a result, passengers may experience anxiety and stress. Furthermore, because information provided during emergencies is uniform, there is a need for flexible service provision that can meet the individual needs of each passenger.

[0396] 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.

[0397] In this invention, the server includes means for detecting the user's emotional state, means for adjusting notification content based on the detected emotional state, and means incorporated into an autonomous mobile device for optimizing travel routes in accordance with the passenger's real-time emotional state and traffic conditions. This enables a comfortable travel experience that takes the passenger's emotions into consideration.

[0398] "User" refers to an individual or group that receives services provided by an autonomous mobile device or system.

[0399] "Emotional state" refers to the user's psychological reactions and circumstances, and is data analyzed through voice, facial expressions, and other means.

[0400] "Notification content" refers to the information the system provides to the user, and the message is adjusted according to traffic conditions and the user's mood.

[0401] An "autonomous mobile device" is a means of transportation that operates automatically without external intervention, using artificial intelligence and sensor technology.

[0402] "Real-time" refers to a state with virtually no time delay, meaning that information is processed and provided instantly.

[0403] "Traffic conditions" refers to information indicating the state of congestion, accidents, delays, etc., along a travel route.

[0404] "Route optimization" refers to calculating the best possible route to a destination, taking into account factors such as time, distance, and the user's feelings.

[0405] The system that implements this application has multiple components for collecting and analyzing traffic information and user emotional states in real time. The system leverages software, including Google Cloud's natural language API and Microsoft Azure's emotion recognition service, to enable users to move comfortably within autonomous mobile devices.

[0406] The server uses a traffic information API to collect real-time data on current traffic conditions. This data is analyzed using an AI model. Furthermore, it evaluates the user's emotional state from audio and video data obtained through the terminal's sensors. This emotional data is used to determine the optimal route and notification content based on the passenger's psychological needs.

[0407] As a concrete example, if a passenger using an autonomous mobile device is heading to the airport in rainy weather, the server analyzes the passenger's emotional state and provides the shortest route to alleviate stress. At this time, it automatically generates a message to reduce the passenger's anxiety and notifies the device.

[0408] An example of a prompt to be input to the generating AI model would be: "Design an application that generates reassuring messages and suggests the optimal route in real time when passengers in an autonomous vehicle are in a hurry. Please consider emotion recognition data and traffic information." This would enable a dynamic and emotion-sensitive mobility service.

[0409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0410] Step 1:

[0411] The user installs a dedicated application on their device and registers an account. As input, they set their preferred traffic information and emotional data, and as output, a profile is created on the server. The device then processes this information and sends it to the server.

[0412] Step 2:

[0413] The server collects data in real time from a traffic information API. It uses traffic data obtained from an external API as input and stores traffic conditions in a database as output. The server then analyzes this information using an AI model to detect anomalies.

[0414] Step 3:

[0415] The device's sensors collect the user's voice and facial expressions, and analyze their emotional state. Using voice and video data as input, the output provides numerical values ​​and classification results that evaluate the user's emotional state. The device uses an emotion recognition API to perform the analysis.

[0416] Step 4:

[0417] The server uses collected traffic and sentiment data to calculate the optimal travel route. It takes current traffic data and the user's sentiment state as input, and generates an optimized route plan tailored to each user as output. Route calculation involves calculations based on time, distance, and sentiment data.

[0418] Step 5:

[0419] The server generates notification messages in multiple languages ​​and adjusts the content based on the user's emotional state. Using generated route suggestions and user emotional data as input, it produces reassuring, adjusted messages as output. The server utilizes a natural language generation model to prepare push notifications.

[0420] Step 6:

[0421] The device pushes notifications to the user, clearly presenting suggested options along with links to map information. It receives notification data and route links from the server as input, and provides the user with visual information as output. The device uses its display to show this information.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] [Third Embodiment]

[0426] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0427] 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.

[0428] 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).

[0429] 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.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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".

[0438] The present invention relates to a system comprising an information processing device that provides users with real-time information regarding public transportation and promptly presents alternative routes in the event of an anomaly. This system consists of multiple elements, including a server, terminals, and users.

[0439] First, the user uses their device and downloads a dedicated application. Within the application, they register their language settings and frequently used train and bus routes. This allows the system to build a user profile and personalize the information.

[0440] Based on the aforementioned profile, the server periodically and automatically collects real-time information about public transport from multiple sources. These sources include social media, real-time search services, and the official websites of each railway company. The information collected by the server is stored in a database, and this information is analyzed using natural language processing technology.

[0441] Next, the server detects traffic anomalies (e.g., accidents, delays, cancellations). Based on this analysis, if an anomaly occurs, the server calculates alternative routes related to the affected lines. This calculation takes into account various factors, including travel time to the destination, cost, and operating schedules.

[0442] Once an alternative route is determined, the server creates a notification for the user and sends it to their device. This notification is delivered in the user's preferred language and through their messaging app (e.g., LINE). The notification may include details of the alternative route and links to further transportation options. This allows the user to continue their journey with peace of mind.

[0443] As a concrete example, consider a scenario where a user is using a train in a city during peak hours and the line is suddenly stopped due to a personal injury accident. This system uses a server to collect accident information and, based on the analysis results, calculates alternative routes (e.g., nearby bus routes or other train lines). Then, it notifies the user's terminal of the available alternative routes and the time required in multiple languages. In this way, the user can quickly obtain options to reach their destination without confusion.

[0444] This system will enable visitors, the hearing impaired, the elderly, and travelers to efficiently utilize real-time traffic information and respond flexibly to disruptions in public transport. This implementation will provide a safe and secure means of transportation for all who use public transport.

[0445] The following describes the processing flow.

[0446] Step 1:

[0447] The user installs a dedicated application on their device and registers an account. Here, the user registers their language settings, the train and bus routes they use, and the messaging app they want to receive notifications from. The device sends this information to the server to create a user profile.

[0448] Step 2:

[0449] The server periodically monitors traffic information by collecting real-time data from SNS APIs, search services, and railway company websites. The server accesses each data source, extracts new information, and stores it in the database.

[0450] Step 3:

[0451] The server analyzes the collected data using natural language processing to check the operating status of transportation services. This analysis detects abnormal situations such as accidents and delays. The server identifies the abnormal information and determines whether it will affect users.

[0452] Step 4:

[0453] When an anomaly is detected, the server begins calculating alternative routes for the affected lines. Using an optimized routing algorithm, it evaluates alternative routes to the destination and determines the best alternative, taking into account factors such as travel time and cost.

[0454] Step 5:

[0455] The server generates a notification based on the provided alternative route information. The notification is prepared in multiple languages ​​according to the user's language settings, and the messaging app is ready to send the notification.

[0456] Step 6:

[0457] The device receives notifications sent from the server and displays them to the user as push notifications. The notifications include a description of the current situation, along with suggested alternative modes of transportation and links.

[0458] Step 7:

[0459] The user checks the notifications on their device and selects a mode of transportation to their destination according to the provided alternative route guidance. The device provides maps and additional information as needed to support the user's smooth journey.

[0460] (Example 1)

[0461] 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."

[0462] A challenge for users of public transport is the difficulty in quickly finding appropriate alternative routes in the event of sudden transportation disruptions. Visitors, the hearing impaired, the elderly, and tourists, in particular, may experience confusion and anxiety due to language barriers and unfamiliar transportation environments. Furthermore, the information provided during disruptions may be insufficient, and they may not be able to obtain information that meets their individual needs.

[0463] 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.

[0464] In this invention, the server includes a device for receiving user travel route settings, a device for collecting real-time traffic-related data from multiple information sources, and a device for analyzing the collected data to detect anomalies. This enables the rapid presentation of personalized alternative routes suitable for the user's situation and language when an anomaly occurs.

[0465] "User" refers to an individual or group that uses this system to obtain information about public transportation and uses that information to travel.

[0466] A "device that accepts travel route settings" refers to a device that allows users to input or save information about their planned travel route.

[0467] "Information sources" refer to the sources from which traffic conditions data is disseminated, and these include social media, real-time search services, and official websites of transportation companies.

[0468] "Real-time data" refers to data that shows the current status of transportation services and is continuously and rapidly updated.

[0469] A "data collection device" refers to a device that has the function of acquiring necessary data from multiple sources and storing it within the system.

[0470] A "device for analyzing and detecting anomalies" refers to a device that uses natural language processing technology or other methods to identify unusual situations in transportation systems from collected data.

[0471] A "device for calculating alternative routes" refers to a device that calculates the optimal means of transportation or route in response to detected anomalies in the transportation system.

[0472] A "notification sending device" refers to a device that sends information via messaging apps or other communication methods to deliver calculated alternative route information in a manner chosen by the user.

[0473] "Multiple conditions to consider in the event of an anomaly" refers to various factors used when calculating alternative routes, including travel time, cost, and operating schedule.

[0474] In its embodiment, this system primarily consists of a server and user terminals. Specifically, the server is responsible for collecting real-time traffic-related data from multiple sources and detecting anomalies by analyzing that data. The server uses analysis software developed with programming languages ​​such as Python and employs natural language processing techniques to analyze the collected data. Machine learning algorithms and text mining techniques are used in the analysis, enabling accurate detection of accidents and delays in transportation systems.

[0475] The user interacts with the system through their device. A dedicated application is installed on the device, and the user uses this application to configure their travel route. This application runs on iOS and Android operating systems.

[0476] The server automatically calculates an alternative route when it detects an anomaly. The calculation takes into account factors such as the travel schedule, travel time, and cost. The calculation results are translated into the user's specified language and notified to the user via a messaging application (e.g., a messaging platform). The notification may include links to map information and travel information.

[0477] As a concrete example, consider a scenario where a user is using a train in a city during peak hours and the line is suddenly stopped due to an accident. This system quickly collects and analyzes accident information and suggests alternative modes of transportation. For example, it would recommend using the nearest bus or other train lines, and also notify the user of necessary transfer times and fares.

[0478] An example of a prompt message generated using an AI model is as follows: "We want to design a system that allows users to individually configure public transport information through a downloaded application and provides alternative routes in real time in case of anomalies. Please provide specific steps regarding the data sources, analysis methods, and notification methods to be used."

[0479] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0480] Step 1:

[0481] The user downloads a dedicated application to their device and opens it. Within the application, the user registers their frequently used transportation routes and preferred languages ​​to create a profile. The input consists of the user's route and language information, and the output generates user-specific profile data, which is then sent to the server.

[0482] Step 2:

[0483] The server collects real-time transportation-related data from sources such as social media, real-time search services, and official transportation websites, based on the user's profile. The input is transportation data from external sources, and the output is stored in a database as necessary public transportation operation data. This process involves retrieving data using APIs and saving it to a storage system.

[0484] Step 3:

[0485] The server uses natural language processing technology to analyze the collected data and detect anomalies in transportation systems. The input is real-time transportation data stored in a database, and the output is data containing anomaly information as a result of the analysis. Here, predictive analysis using a machine learning model is performed to determine whether or not an anomaly is present.

[0486] Step 4:

[0487] The server calculates alternative routes based on detected anomalies. The calculation takes into account factors such as operating schedules, travel time, and costs. Inputs are anomaly information and available public transport schedules and route data, while output is optimal alternative route information. A route calculation algorithm is used to determine the best route from the available options.

[0488] Step 5:

[0489] The server generates a notification about the calculated alternative route and sends it to the terminal using the method specified by the user. The input is the optimal alternative route information, and the output is the notification message displayed on the user's terminal. A language conversion system is used to translate the information into the user's language and deliver it through the messaging application.

[0490] Step 6:

[0491] The user checks the received notification on their device and follows the provided alternative route. The input is the notification message, and the output is the user's guideline for action. The user follows the map information and instructions provided in the notification and continues their journey appropriately.

[0492] (Application Example 1)

[0493] 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."

[0494] Unexpected stoppages and delays in public transport pose a challenge, particularly for visitors, the hearing impaired, the elderly, and travelers, making it difficult to reach their destinations. Furthermore, with the expected widespread use of autonomous vehicles in the future, efficient route rerouting in the event of disruptions is required. Addressing these issues necessitates the collection of real-time traffic information and the rapid provision of alternative routes tailored to individual travel paths.

[0495] 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.

[0496] In this invention, the server includes means for receiving user travel route settings, means for collecting real-time information related to transportation from multiple information sources, means for analyzing the collected information to detect anomalies, means for calculating alternative routes based on detected anomalies, means for transmitting notifications to a medium specified by the user, means for optimizing the route within the autonomous vehicle, and means for presenting alternative road routes in the event of traffic anomalies. This enables users to quickly obtain options to reach their destination without confusion, even in the event of transportation anomalies.

[0497] A "visitor" is someone who is visiting an unfamiliar place and who wants to understand traffic information more easily.

[0498] A "person with a hearing impairment" is someone who has a hearing loss and needs to receive information through sight.

[0499] "Elderly people" refers to individuals who, due to their age, require special consideration when using public transportation.

[0500] A "traveler" is someone who moves away from their place of residence for the purpose of sightseeing or business.

[0501] An "information processing device" is a computer system that collects and analyzes information and makes decisions automatically.

[0502] "Means for accepting travel route settings" refers to a function that provides an interface for users to set a route to their destination.

[0503] "Means of collecting real-time information related to transportation from multiple sources" refers to the function of obtaining the latest transportation information from various media and databases.

[0504] "Means of analyzing collected information to detect anomalies" refers to a function that analyzes acquired data and identifies unusual conditions or problems.

[0505] "Means for calculating alternative routes" refers to algorithms used to find the optimal alternative route when an anomaly occurs.

[0506] "Means of sending notifications" refers to a function that uses communication technology to deliver information and instructions to users.

[0507] "Means for optimizing the route within an autonomous vehicle" refers to a function that updates and adjusts the optimal route to the destination in real time within an autonomous vehicle.

[0508] "Means of suggesting alternative road routes in the event of traffic abnormalities" refers to a function that suggests alternative road routes that can be used when traffic problems occur.

[0509] This invention details a method for realizing a system that collects traffic information in real time and provides users with the optimal travel route. The system is composed primarily of a server, a terminal, and a user.

[0510] The server uses a computing system designed to collect and analyze real-time data on public transport from multiple sources. The hardware includes server computers with powerful processors and large memory capacities, and the software utilizes high-performance scripting languages ​​such as Python. The geopy library is also used for geographical calculations of the transport data. The server continuously analyzes this data, detects transport anomalies, and calculates alternative routes.

[0511] The terminal is a device in which users register information about their travel routes and receive notifications sent from a server. A dedicated application is installed on the terminal, and users input information about their destinations through this application. Notifications are generated based on the user's pre-configured language and are delivered via a messaging app such as LINE.

[0512] As a concrete example, consider a scenario where a user is traveling using public transportation in a major city and a traffic anomaly occurs. In this system, the server immediately collects and analyzes the information and calculates the optimal alternative route. This information is then notified to the user's terminal in multiple languages. As a result, the user can safely reach their destination using the newly suggested route.

[0513] An example of a prompt to input into a generating AI model would be: "Please tell me the shortest alternative route to the tourist destination. If the train is unavailable, please also suggest which road to take."

[0514] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0515] Step 1:

[0516] The user downloads a dedicated application to their device and enters information about their travel route and the modes of transportation they will use. This information is sent to a server by the application and stored as the user's profile. The input is information about the user's selected route and modes of transportation, and the output is individual user profile data on the server.

[0517] Step 2:

[0518] The server collects real-time data on public transport from multiple sources, including social media, search services, and the official websites of each transport provider. The server sends queries to these sources and receives response data. The input is raw data obtained from each source, and the output is real-time transport data integrated into the server.

[0519] Step 3:

[0520] The server analyzes the collected data using natural language processing techniques to detect any anomalies (e.g., delays or cancellations). The input is the real-time traffic data obtained in step 2, and the output is a list of detected traffic anomalies. Specifically, the server uses a keyword detection algorithm to identify information related to the problem.

[0521] Step 4:

[0522] The server calculates alternative routes based on detected anomalies. This calculation takes into account user profile information, as well as factors such as travel time to the destination, cost, and schedule. Inputs are the user profile and anomaly information, while output are multiple alternative route candidates. A route optimization algorithm is used for this specific operation.

[0523] Step 5:

[0524] The server notifies the user's device of the calculated alternative route via the language and media (e.g., a messaging app) specified by the user. The input is the detailed information of the alternative route, and the output is the notification message displayed on the user's device. Specifically, the server generates the notification message in multiple languages ​​and delivers it via the specified media.

[0525] Step 6:

[0526] The device receives a notification, and the user can review the suggested alternative route. At this point, the user can choose the best mode of travel based on the new information. The input is the notification message from the server, and the output is reference information to support the user's decision-making. Specifically, the device visually displays the notification message.

[0527] 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.

[0528] This invention provides a system that offers appropriate information to users during public transportation stoppages or delays, and furthermore, provides information that takes into account the emotional state of the users. This system is implemented by multiple components, including an information processing device, an emotion engine, a terminal, and a user.

[0529] First, the user installs a dedicated application on their device and registers an account. Within the application, the user configures language settings, train and bus route information to use, and messaging apps to receive notifications. The device then sends this user information to the server and sets up the profile.

[0530] The server periodically collects real-time traffic information from multiple sources. These sources include social media, real-time search services, and the official websites of various transportation companies. The collected information is stored in a database on the server and analyzed using natural language processing techniques.

[0531] The server detects transportation anomalies (e.g., accidents, delays) based on the analysis results. If an anomaly is detected, the server calculates a corresponding alternative route using an optimized routing algorithm. This process takes into account factors such as travel time, fare, and departure time.

[0532] Furthermore, the server incorporates an emotion engine. This emotion engine analyzes data obtained from the user via voice or text through the terminal and recognizes the user's emotions in real time. Based on the analysis results, the server adjusts the content and format of notifications according to the user's emotional state.

[0533] Notifications are generated in multiple languages, and the server sends them in an emotionally sensitive manner using the user's specified application. The device receives the notification and displays it to the user as a push notification. This display includes suggested alternative modes of transportation and links to reference map information to help the user easily understand the information.

[0534] As a concrete example, consider a situation where a user is using public transportation in a tourist area and the route is delayed. In this system, the server collects delay information, and an emotion engine detects the user's impatience and anxiety. Subsequently, it generates a reassuring notification, including alternative routes, to help the user quickly choose the appropriate course of action.

[0535] This system will enable visitors, the hearing impaired, the elderly, and travelers to receive real-time, emotionally sensitive traffic information and respond appropriately to any abnormal situations in public transport.

[0536] The following describes the processing flow.

[0537] Step 1:

[0538] The user installs a dedicated application on their device and registers an account. The device sends the user's settings information (language, train lines used, notification apps) to the server to create a user profile.

[0539] Step 2:

[0540] The server regularly collects real-time traffic information from multiple external sources (social media, search engines, and railway company websites). The server stores the information collected this year in a database.

[0541] Step 3:

[0542] The server analyzes the accumulated data using natural language processing technology to detect anomalies in transportation systems (e.g., delays, cancellations). This analysis identifies the nature and scope of the transportation anomaly.

[0543] Step 4:

[0544] If an anomaly is detected, the server begins calculating alternative routes for the affected lines. It applies an algorithm that considers various factors (time, cost, frequency of service) to suggest the best mode of transport for the user.

[0545] Step 5:

[0546] The server uses an emotion engine to analyze voice or text data received from the terminal and identify the user's emotional state. This allows it to tailor notifications to address the user's anxiety and stress levels.

[0547] Step 6:

[0548] The server generates emotionally sensitive notifications in multiple languages ​​and sends them to the user's device via the selected messaging app. The notifications include details about the anomaly, alternative routes, and links to map information.

[0549] Step 7:

[0550] The device receives notifications sent from the server and displays them to the user as push notifications. Based on this information, the user can select an alternative route and continue traveling to their destination.

[0551] (Example 2)

[0552] 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."

[0553] Disruptions and delays in public transportation are particularly stressful for visitors, the hearing impaired, the elderly, and travelers. Furthermore, providing transportation information requires not only conveying information but also considering the emotional state of users. However, conventional systems have been insufficient in providing emotionally sensitive information and multilingual support, meaning users were not always able to utilize the information effectively.

[0554] 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.

[0555] In this invention, the server includes means for setting user route information, means for collecting real-time information related to the traffic network from multiple data sources, means for analyzing the collected data and detecting traffic anomalies, means for calculating alternative routes based on the detected traffic anomalies, means including an emotion engine for analyzing the user's emotional state, means for generating notification content according to the emotional state, and means for transmitting emotionally sensitive notifications to an information medium specified by the user. This makes it possible to acquire traffic information in real time and provide it to the user in a multilingual and emotionally sensitive manner.

[0556] An "information processing system" is a device with multiple functions that provides users with information about the suspension or delay of public transportation.

[0557] "Data sources" refer to various sources of information that provide information about transportation networks, including real-time search services and official websites.

[0558] "Traffic anomaly" refers to any event that disrupts the normal operation of public transportation, including delays, cancellations, and accidents.

[0559] "Route information" refers to information about the route and means of transportation that users use to get to their destination.

[0560] An "emotion engine" is a technology that analyzes a user's emotional state from their voice or text and adjusts the information provided based on that analysis.

[0561] "Notification content" refers to the specific messages and instructions provided to the user, and can be expressed in text, audio, images, etc.

[0562] "Information medium" refers to a means used to send notifications to users, and includes email, messaging apps, and smartphone push notifications.

[0563] This invention is an information processing system that provides users with appropriate and emotionally sensitive information during delays or disruptions in public transportation. This system is implemented through interaction between a server, a terminal, and the user. An overview is provided below.

[0564] The server is responsible for collecting traffic information from multiple data sources and detecting traffic anomalies. These data sources include public transport websites, social media, and real-time search services. The server analyzes the collected data using natural language processing techniques, enabling rapid detection of anomalies such as delays, cancellations, and accidents. When an anomaly is detected, the server calculates alternative routes using an optimized routing algorithm, taking into account factors such as travel time, fare, and available departure times.

[0565] Users install a dedicated application on their device and register an account. Through this application, users can input language settings and transportation route information. The device sends this information to a server to form a user profile. This profile information may include the user's location and settings.

[0566] This system incorporates an emotion engine. The terminal sends voice input and text information from the user to the server, where it is analyzed in real time by the emotion engine. The emotion engine analyzes the tone of the text and the intonation of the voice to recognize the user's emotions. Based on the results, the server generates and customizes notification content according to the emotional state. This is achieved, for example, by sending a reassuring notification to a user who is feeling anxious.

[0567] Notifications are multilingual, with the server generating notifications in the user's chosen language. The server can send these generated notifications through the user's designated messaging app. The device displays the received notification as a push notification, including links to suggested alternative transportation options and map information. This allows the user to efficiently and quickly choose their next course of action.

[0568] As a concrete example, if a user attempts to use a train in a tourist area but the line is delayed, the server analyzes the delay information and detects the user's anxiety using an emotion engine. It then generates a reassuring notification, including alternative routes, and quickly sends it to the user.

[0569] Example of a prompt:

[0570] Please create a description of a system that notifies users when public transportation is delayed. This system will provide appropriate information while taking into account the user's emotional state. As a specific example, please describe how a user in a tourist area might receive delay information.

[0571] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0572] Step 1:

[0573] User registration and initial setup

[0574] The user installs a dedicated application on their device. Once the installation is complete, the user creates an account and enters information such as language settings and the transportation routes they will use. The device sends this input data to the server to generate a user profile. The input includes the user's personal information and settings, and the output is the user profile stored on the server.

[0575] Step 2:

[0576] Collection of real-time traffic information

[0577] The server periodically collects information about public transportation from multiple data sources. Specifically, it obtains data from social media, real-time search services, and official transportation websites, using APIs to maintain immediacy. The input is transportation information from each data source, which the server stores in a database. The output is raw data used for analysis.

[0578] Step 3:

[0579] Analysis and detection of traffic anomalies

[0580] The server analyzes collected traffic information using natural language processing (NLP) techniques to identify anomalies such as traffic delays and cancellations. The input is raw data stored in a database, and NLP extracts anomaly patterns from the data. The output is the detected traffic anomaly information.

[0581] Step 4:

[0582] Calculation of alternative routes

[0583] The server calculates alternative routes based on identified traffic anomalies. It uses an optimized routing algorithm that considers travel time, fares, and available departure times based on the user profile. Inputs are traffic anomaly information and user profiles, while output is information on alternative routes available to the user.

[0584] Step 5:

[0585] Analysis of emotional states using an emotion engine

[0586] The terminal receives voice or text from the user and sends it to the server. The server's emotion engine analyzes this data to recognize the user's emotional state. The input is voice or text input from the user, and the output is the user's emotional state revealed by the analysis.

[0587] Step 6:

[0588] Generating and sending notification content

[0589] The server generates notification content in an emotionally sensitive manner based on the analyzed emotional state. Notifications are created in multiple languages ​​and include alternative route information and relevant map links. Inputs are emotional state and alternative route information, while output is a customized notification sent to the user.

[0590] Step 7:

[0591] Receiving and displaying notifications

[0592] The device receives notifications sent from the server and displays them to the user as push notifications. This process supports multilingual display and directly provides the user with relevant map and route information. The input is notification data from the server, and the output is the information displayed on the user's device.

[0593] (Application Example 2)

[0594] 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."

[0595] Current autonomous mobility devices can optimize routes based on traffic conditions, but they cannot provide information that takes into account the emotional state of passengers, nor can they adjust routes based on that information. As a result, passengers may experience anxiety and stress. Furthermore, because information provided during emergencies is uniform, there is a need for flexible service provision that can meet the individual needs of each passenger.

[0596] 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.

[0597] In this invention, the server includes means for detecting the user's emotional state, means for adjusting notification content based on the detected emotional state, and means incorporated into an autonomous mobile device for optimizing travel routes in accordance with the passenger's real-time emotional state and traffic conditions. This enables a comfortable travel experience that takes the passenger's emotions into consideration.

[0598] "User" refers to an individual or group that receives services provided by an autonomous mobile device or system.

[0599] "Emotional state" refers to the user's psychological reactions and circumstances, and is data analyzed through voice, facial expressions, and other means.

[0600] "Notification content" refers to the information the system provides to the user, and the message is adjusted according to traffic conditions and the user's mood.

[0601] An "autonomous mobile device" is a means of transportation that operates automatically without external intervention, using artificial intelligence and sensor technology.

[0602] "Real-time" refers to a state with virtually no time delay, meaning that information is processed and provided instantly.

[0603] "Traffic conditions" refers to information indicating the state of congestion, accidents, delays, etc., along a travel route.

[0604] "Route optimization" refers to calculating the best possible route to a destination, taking into account factors such as time, distance, and the user's feelings.

[0605] The system that implements this application has multiple components for collecting and analyzing traffic information and user emotional states in real time. The system leverages software, including Google Cloud's natural language API and Microsoft Azure's emotion recognition service, to enable users to move comfortably within autonomous mobile devices.

[0606] The server uses a traffic information API to collect real-time data on current traffic conditions. This data is analyzed using an AI model. Furthermore, it evaluates the user's emotional state from audio and video data obtained through the terminal's sensors. This emotional data is used to determine the optimal route and notification content based on the passenger's psychological needs.

[0607] As a concrete example, if a passenger using an autonomous mobile device is heading to the airport in rainy weather, the server analyzes the passenger's emotional state and provides the shortest route to alleviate stress. At this time, it automatically generates a message to reduce the passenger's anxiety and notifies the device.

[0608] An example of a prompt to be input to the generating AI model would be: "Design an application that generates reassuring messages and suggests the optimal route in real time when passengers in an autonomous vehicle are in a hurry. Please consider emotion recognition data and traffic information." This would enable a dynamic and emotion-sensitive mobility service.

[0609] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0610] Step 1:

[0611] The user installs a dedicated application on their device and registers an account. As input, they set their preferred traffic information and emotional data, and as output, a profile is created on the server. The device then processes this information and sends it to the server.

[0612] Step 2:

[0613] The server collects data in real time from a traffic information API. It uses traffic data obtained from an external API as input and stores traffic conditions in a database as output. The server then analyzes this information using an AI model to detect anomalies.

[0614] Step 3:

[0615] The device's sensors collect the user's voice and facial expressions, and analyze their emotional state. Using voice and video data as input, the output provides numerical values ​​and classification results that evaluate the user's emotional state. The device uses an emotion recognition API to perform the analysis.

[0616] Step 4:

[0617] The server uses collected traffic and sentiment data to calculate the optimal travel route. It takes current traffic data and the user's sentiment state as input, and generates an optimized route plan tailored to each user as output. Route calculation involves calculations based on time, distance, and sentiment data.

[0618] Step 5:

[0619] The server generates notification messages in multiple languages ​​and adjusts the content based on the user's emotional state. Using generated route suggestions and user emotional data as input, it produces reassuring, adjusted messages as output. The server utilizes a natural language generation model to prepare push notifications.

[0620] Step 6:

[0621] The device pushes notifications to the user, clearly presenting suggested options along with links to map information. It receives notification data and route links from the server as input, and provides the user with visual information as output. The device uses its display to show this information.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] [Fourth Embodiment]

[0626] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0627] 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.

[0628] 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).

[0629] 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.

[0630] 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.

[0631] 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).

[0632] 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.

[0633] 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.

[0634] 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.

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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".

[0639] The present invention relates to a system comprising an information processing device that provides users with real-time information regarding public transportation and promptly presents alternative routes in the event of an anomaly. This system consists of multiple elements, including a server, terminals, and users.

[0640] First, the user uses their device and downloads a dedicated application. Within the application, they register their language settings and frequently used train and bus routes. This allows the system to build a user profile and personalize the information.

[0641] Based on the aforementioned profile, the server periodically and automatically collects real-time information about public transport from multiple sources. These sources include social media, real-time search services, and the official websites of each railway company. The information collected by the server is stored in a database, and this information is analyzed using natural language processing technology.

[0642] Next, the server detects traffic anomalies (e.g., accidents, delays, cancellations). Based on this analysis, if an anomaly occurs, the server calculates alternative routes related to the affected lines. This calculation takes into account various factors, including travel time to the destination, cost, and operating schedules.

[0643] Once an alternative route is determined, the server creates a notification for the user and sends it to their device. This notification is delivered in the user's preferred language and through their messaging app (e.g., LINE). The notification may include details of the alternative route and links to further transportation options. This allows the user to continue their journey with peace of mind.

[0644] As a concrete example, consider a scenario where a user is using a train in a city during peak hours and the line is suddenly stopped due to a personal injury accident. This system uses a server to collect accident information and, based on the analysis results, calculates alternative routes (e.g., nearby bus routes or other train lines). Then, it notifies the user's terminal of the available alternative routes and the time required in multiple languages. In this way, the user can quickly obtain options to reach their destination without confusion.

[0645] This system will enable visitors, the hearing impaired, the elderly, and travelers to efficiently utilize real-time traffic information and respond flexibly to disruptions in public transport. This implementation will provide a safe and secure means of transportation for all who use public transport.

[0646] The following describes the processing flow.

[0647] Step 1:

[0648] The user installs a dedicated application on their device and registers an account. Here, the user registers their language settings, the train and bus routes they use, and the messaging app they want to receive notifications from. The device sends this information to the server to create a user profile.

[0649] Step 2:

[0650] The server periodically monitors traffic information by collecting real-time data from SNS APIs, search services, and railway company websites. The server accesses each data source, extracts new information, and stores it in the database.

[0651] Step 3:

[0652] The server analyzes the collected data using natural language processing to check the operating status of transportation services. This analysis detects abnormal situations such as accidents and delays. The server identifies the abnormal information and determines whether it will affect users.

[0653] Step 4:

[0654] When an anomaly is detected, the server begins calculating alternative routes for the affected lines. Using an optimized routing algorithm, it evaluates alternative routes to the destination and determines the best alternative, taking into account factors such as travel time and cost.

[0655] Step 5:

[0656] The server generates a notification based on the provided alternative route information. The notification is prepared in multiple languages ​​according to the user's language settings, and the messaging app is ready to send the notification.

[0657] Step 6:

[0658] The device receives notifications sent from the server and displays them to the user as push notifications. The notifications include a description of the current situation, along with suggested alternative modes of transportation and links.

[0659] Step 7:

[0660] The user checks the notifications on their device and selects a mode of transportation to their destination according to the provided alternative route guidance. The device provides maps and additional information as needed to support the user's smooth journey.

[0661] (Example 1)

[0662] 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".

[0663] A challenge for users of public transport is the difficulty in quickly finding appropriate alternative routes in the event of sudden transportation disruptions. Visitors, the hearing impaired, the elderly, and tourists, in particular, may experience confusion and anxiety due to language barriers and unfamiliar transportation environments. Furthermore, the information provided during disruptions may be insufficient, and they may not be able to obtain information that meets their individual needs.

[0664] 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.

[0665] In this invention, the server includes a device for receiving user travel route settings, a device for collecting real-time traffic-related data from multiple information sources, and a device for analyzing the collected data to detect anomalies. This enables the rapid presentation of personalized alternative routes suitable for the user's situation and language when an anomaly occurs.

[0666] "User" refers to an individual or group that uses this system to obtain information about public transportation and uses that information to travel.

[0667] A "device that accepts travel route settings" refers to a device that allows users to input or save information about their planned travel route.

[0668] "Information sources" refer to the sources from which traffic conditions data is disseminated, and these include social media, real-time search services, and official websites of transportation companies.

[0669] "Real-time data" refers to data that shows the current status of transportation services and is continuously and rapidly updated.

[0670] A "data collection device" refers to a device that has the function of acquiring necessary data from multiple sources and storing it within the system.

[0671] A "device for analyzing and detecting anomalies" refers to a device that uses natural language processing technology or other methods to identify unusual situations in transportation systems from collected data.

[0672] A "device for calculating alternative routes" refers to a device that calculates the optimal means of transportation or route in response to detected anomalies in the transportation system.

[0673] A "notification sending device" refers to a device that sends information via messaging apps or other communication methods to deliver calculated alternative route information in a manner chosen by the user.

[0674] "Multiple conditions to consider in the event of an anomaly" refers to various factors used when calculating alternative routes, including travel time, cost, and operating schedule.

[0675] In its embodiment, this system primarily consists of a server and user terminals. Specifically, the server is responsible for collecting real-time traffic-related data from multiple sources and detecting anomalies by analyzing that data. The server uses analysis software developed with programming languages ​​such as Python and employs natural language processing techniques to analyze the collected data. Machine learning algorithms and text mining techniques are used in the analysis, enabling accurate detection of accidents and delays in transportation systems.

[0676] The user interacts with the system through their device. A dedicated application is installed on the device, and the user uses this application to configure their travel route. This application runs on iOS and Android operating systems.

[0677] The server automatically calculates an alternative route when it detects an anomaly. The calculation takes into account factors such as the travel schedule, travel time, and cost. The calculation results are translated into the user's specified language and notified to the user via a messaging application (e.g., a messaging platform). The notification may include links to map information and travel information.

[0678] As a concrete example, consider a scenario where a user is using a train in a city during peak hours and the line is suddenly stopped due to an accident. This system quickly collects and analyzes accident information and suggests alternative modes of transportation. For example, it would recommend using the nearest bus or other train lines, and also notify the user of necessary transfer times and fares.

[0679] An example of a prompt message generated using an AI model is as follows: "We want to design a system that allows users to individually configure public transport information through a downloaded application and provides alternative routes in real time in case of anomalies. Please provide specific steps regarding the data sources, analysis methods, and notification methods to be used."

[0680] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0681] Step 1:

[0682] The user downloads a dedicated application to their device and opens it. Within the application, the user registers their frequently used transportation routes and preferred languages ​​to create a profile. The input consists of the user's route and language information, and the output generates user-specific profile data, which is then sent to the server.

[0683] Step 2:

[0684] The server collects real-time transportation-related data from sources such as social media, real-time search services, and official transportation websites, based on the user's profile. The input is transportation data from external sources, and the output is stored in a database as necessary public transportation operation data. This process involves retrieving data using APIs and saving it to a storage system.

[0685] Step 3:

[0686] The server uses natural language processing technology to analyze the collected data and detect anomalies in transportation systems. The input is real-time transportation data stored in a database, and the output is data containing anomaly information as a result of the analysis. Here, predictive analysis using a machine learning model is performed to determine whether or not an anomaly is present.

[0687] Step 4:

[0688] The server calculates alternative routes based on detected anomalies. The calculation takes into account factors such as operating schedules, travel time, and costs. Inputs are anomaly information and available public transport schedules and route data, while output is optimal alternative route information. A route calculation algorithm is used to determine the best route from the available options.

[0689] Step 5:

[0690] The server generates a notification about the calculated alternative route and sends it to the terminal using the method specified by the user. The input is the optimal alternative route information, and the output is the notification message displayed on the user's terminal. A language conversion system is used to translate the information into the user's language and deliver it through the messaging application.

[0691] Step 6:

[0692] The user checks the received notification on their device and follows the provided alternative route. The input is the notification message, and the output is the user's guideline for action. The user follows the map information and instructions provided in the notification and continues their journey appropriately.

[0693] (Application Example 1)

[0694] 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".

[0695] Unexpected stoppages and delays in public transport pose a challenge, particularly for visitors, the hearing impaired, the elderly, and travelers, making it difficult to reach their destinations. Furthermore, with the expected widespread use of autonomous vehicles in the future, efficient route rerouting in the event of disruptions is required. Addressing these issues necessitates the collection of real-time traffic information and the rapid provision of alternative routes tailored to individual travel paths.

[0696] 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.

[0697] In this invention, the server includes means for receiving user travel route settings, means for collecting real-time information related to transportation from multiple information sources, means for analyzing the collected information to detect anomalies, means for calculating alternative routes based on detected anomalies, means for transmitting notifications to a medium specified by the user, means for optimizing the route within the autonomous vehicle, and means for presenting alternative road routes in the event of traffic anomalies. This enables users to quickly obtain options to reach their destination without confusion, even in the event of transportation anomalies.

[0698] A "visitor" is someone who is visiting an unfamiliar place and who wants to understand traffic information more easily.

[0699] A "person with a hearing impairment" is someone who has a hearing loss and needs to receive information through sight.

[0700] "Elderly people" refers to individuals who, due to their age, require special consideration when using public transportation.

[0701] A "traveler" is someone who moves away from their place of residence for the purpose of sightseeing or business.

[0702] An "information processing device" is a computer system that collects and analyzes information and makes decisions automatically.

[0703] "Means for accepting travel route settings" refers to a function that provides an interface for users to set a route to their destination.

[0704] "Means of collecting real-time information related to transportation from multiple sources" refers to the function of obtaining the latest transportation information from various media and databases.

[0705] "Means of analyzing collected information to detect anomalies" refers to a function that analyzes acquired data and identifies unusual conditions or problems.

[0706] "Means for calculating alternative routes" refers to algorithms used to find the optimal alternative route when an anomaly occurs.

[0707] "Means of sending notifications" refers to a function that uses communication technology to deliver information and instructions to users.

[0708] "Means for optimizing the route within an autonomous vehicle" refers to a function that updates and adjusts the optimal route to the destination in real time within an autonomous vehicle.

[0709] "Means of suggesting alternative road routes in the event of traffic abnormalities" refers to a function that suggests alternative road routes that can be used when traffic problems occur.

[0710] This invention details a method for realizing a system that collects traffic information in real time and provides users with the optimal travel route. The system is composed primarily of a server, a terminal, and a user.

[0711] The server uses a computing system designed to collect and analyze real-time data on public transport from multiple sources. The hardware includes server computers with powerful processors and large memory capacities, and the software utilizes high-performance scripting languages ​​such as Python. The geopy library is also used for geographical calculations of the transport data. The server continuously analyzes this data, detects transport anomalies, and calculates alternative routes.

[0712] The terminal is a device in which users register information about their travel routes and receive notifications sent from a server. A dedicated application is installed on the terminal, and users input information about their destinations through this application. Notifications are generated based on the user's pre-configured language and are delivered via a messaging app such as LINE.

[0713] As a concrete example, consider a scenario where a user is traveling using public transportation in a major city and a traffic anomaly occurs. In this system, the server immediately collects and analyzes the information and calculates the optimal alternative route. This information is then notified to the user's terminal in multiple languages. As a result, the user can safely reach their destination using the newly suggested route.

[0714] An example of a prompt to input into a generating AI model would be: "Please tell me the shortest alternative route to the tourist destination. If the train is unavailable, please also suggest which road to take."

[0715] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0716] Step 1:

[0717] The user downloads a dedicated application to their device and enters information about their travel route and the modes of transportation they will use. This information is sent to a server by the application and stored as the user's profile. The input is information about the user's selected route and modes of transportation, and the output is individual user profile data on the server.

[0718] Step 2:

[0719] The server collects real-time data on public transport from multiple sources, including social media, search services, and the official websites of each transport provider. The server sends queries to these sources and receives response data. The input is raw data obtained from each source, and the output is real-time transport data integrated into the server.

[0720] Step 3:

[0721] The server analyzes the collected data using natural language processing techniques to detect any anomalies (e.g., delays or cancellations). The input is the real-time traffic data obtained in step 2, and the output is a list of detected traffic anomalies. Specifically, the server uses a keyword detection algorithm to identify information related to the problem.

[0722] Step 4:

[0723] The server calculates alternative routes based on detected anomalies. This calculation takes into account user profile information, as well as factors such as travel time to the destination, cost, and schedule. Inputs are the user profile and anomaly information, while output are multiple alternative route candidates. A route optimization algorithm is used for this specific operation.

[0724] Step 5:

[0725] The server notifies the user's device of the calculated alternative route via the language and media (e.g., a messaging app) specified by the user. The input is the detailed information of the alternative route, and the output is the notification message displayed on the user's device. Specifically, the server generates the notification message in multiple languages ​​and delivers it via the specified media.

[0726] Step 6:

[0727] The device receives a notification, and the user can review the suggested alternative route. At this point, the user can choose the best mode of travel based on the new information. The input is the notification message from the server, and the output is reference information to support the user's decision-making. Specifically, the device visually displays the notification message.

[0728] 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.

[0729] This invention provides a system that offers appropriate information to users during public transportation stoppages or delays, and furthermore, provides information that takes into account the emotional state of the users. This system is implemented by multiple components, including an information processing device, an emotion engine, a terminal, and a user.

[0730] First, the user installs a dedicated application on their device and registers an account. Within the application, the user configures language settings, train and bus route information to use, and messaging apps to receive notifications. The device then sends this user information to the server and sets up the profile.

[0731] The server periodically collects real-time traffic information from multiple sources. These sources include social media, real-time search services, and the official websites of various transportation companies. The collected information is stored in a database on the server and analyzed using natural language processing techniques.

[0732] The server detects transportation anomalies (e.g., accidents, delays) based on the analysis results. If an anomaly is detected, the server calculates a corresponding alternative route using an optimized routing algorithm. This process takes into account factors such as travel time, fare, and departure time.

[0733] Furthermore, the server incorporates an emotion engine. This emotion engine analyzes data obtained from the user via voice or text through the terminal and recognizes the user's emotions in real time. Based on the analysis results, the server adjusts the content and format of notifications according to the user's emotional state.

[0734] Notifications are generated in multiple languages, and the server sends them in an emotionally sensitive manner using the user's specified application. The device receives the notification and displays it to the user as a push notification. This display includes suggested alternative modes of transportation and links to reference map information to help the user easily understand the information.

[0735] As a concrete example, consider a situation where a user is using public transportation in a tourist area and the route is delayed. In this system, the server collects delay information, and an emotion engine detects the user's impatience and anxiety. Subsequently, it generates a reassuring notification, including alternative routes, to help the user quickly choose the appropriate course of action.

[0736] This system will enable visitors, the hearing impaired, the elderly, and travelers to receive real-time, emotionally sensitive traffic information and respond appropriately to any abnormal situations in public transport.

[0737] The following describes the processing flow.

[0738] Step 1:

[0739] The user installs a dedicated application on their device and registers an account. The device sends the user's settings information (language, train lines used, notification apps) to the server to create a user profile.

[0740] Step 2:

[0741] The server regularly collects real-time traffic information from multiple external sources (social media, search engines, and railway company websites). The server stores the information collected this year in a database.

[0742] Step 3:

[0743] The server analyzes the accumulated data using natural language processing technology to detect anomalies in transportation systems (e.g., delays, cancellations). This analysis identifies the nature and scope of the transportation anomaly.

[0744] Step 4:

[0745] If an anomaly is detected, the server begins calculating alternative routes for the affected lines. It applies an algorithm that considers various factors (time, cost, frequency of service) to suggest the best mode of transport for the user.

[0746] Step 5:

[0747] The server uses an emotion engine to analyze voice or text data received from the terminal and identify the user's emotional state. This allows it to tailor notifications to address the user's anxiety and stress levels.

[0748] Step 6:

[0749] The server generates emotionally sensitive notifications in multiple languages ​​and sends them to the user's device via the selected messaging app. The notifications include details about the anomaly, alternative routes, and links to map information.

[0750] Step 7:

[0751] The device receives notifications sent from the server and displays them to the user as push notifications. Based on this information, the user can select an alternative route and continue traveling to their destination.

[0752] (Example 2)

[0753] 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".

[0754] Disruptions and delays in public transportation are particularly stressful for visitors, the hearing impaired, the elderly, and travelers. Furthermore, providing transportation information requires not only conveying information but also considering the emotional state of users. However, conventional systems have been insufficient in providing emotionally sensitive information and multilingual support, meaning users were not always able to utilize the information effectively.

[0755] 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.

[0756] In this invention, the server includes means for setting user route information, means for collecting real-time information related to the traffic network from multiple data sources, means for analyzing the collected data and detecting traffic anomalies, means for calculating alternative routes based on the detected traffic anomalies, means including an emotion engine for analyzing the user's emotional state, means for generating notification content according to the emotional state, and means for transmitting emotionally sensitive notifications to an information medium specified by the user. This makes it possible to acquire traffic information in real time and provide it to the user in a multilingual and emotionally sensitive manner.

[0757] An "information processing system" is a device with multiple functions that provides users with information about the suspension or delay of public transportation.

[0758] "Data sources" refer to various sources of information that provide information about transportation networks, including real-time search services and official websites.

[0759] "Traffic anomaly" refers to any event that disrupts the normal operation of public transportation, including delays, cancellations, and accidents.

[0760] "Route information" refers to information about the route and means of transportation that users use to get to their destination.

[0761] An "emotion engine" is a technology that analyzes a user's emotional state from their voice or text and adjusts the information provided based on that analysis.

[0762] "Notification content" refers to the specific messages and instructions provided to the user, and can be expressed in text, audio, images, etc.

[0763] "Information medium" refers to a means used to send notifications to users, and includes email, messaging apps, and smartphone push notifications.

[0764] This invention is an information processing system that provides users with appropriate and emotionally sensitive information during delays or disruptions in public transportation. This system is implemented through interaction between a server, a terminal, and the user. An overview is provided below.

[0765] The server is responsible for collecting traffic information from multiple data sources and detecting traffic anomalies. These data sources include public transport websites, social media, and real-time search services. The server analyzes the collected data using natural language processing techniques, enabling rapid detection of anomalies such as delays, cancellations, and accidents. When an anomaly is detected, the server calculates alternative routes using an optimized routing algorithm, taking into account factors such as travel time, fare, and available departure times.

[0766] Users install a dedicated application on their device and register an account. Through this application, users can input language settings and transportation route information. The device sends this information to a server to form a user profile. This profile information may include the user's location and settings.

[0767] This system incorporates an emotion engine. The terminal sends voice input and text information from the user to the server, where it is analyzed in real time by the emotion engine. The emotion engine analyzes the tone of the text and the intonation of the voice to recognize the user's emotions. Based on the results, the server generates and customizes notification content according to the emotional state. This is achieved, for example, by sending a reassuring notification to a user who is feeling anxious.

[0768] Notifications are multilingual, with the server generating notifications in the user's chosen language. The server can send these generated notifications through the user's designated messaging app. The device displays the received notification as a push notification, including links to suggested alternative transportation options and map information. This allows the user to efficiently and quickly choose their next course of action.

[0769] As a concrete example, if a user attempts to use a train in a tourist area but the line is delayed, the server analyzes the delay information and detects the user's anxiety using an emotion engine. It then generates a reassuring notification, including alternative routes, and quickly sends it to the user.

[0770] Example of a prompt:

[0771] Please create a description of a system that notifies users when public transportation is delayed. This system will provide appropriate information while taking into account the user's emotional state. As a specific example, please describe how a user in a tourist area might receive delay information.

[0772] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0773] Step 1:

[0774] User registration and initial setup

[0775] The user installs a dedicated application on their device. Once the installation is complete, the user creates an account and enters information such as language settings and the transportation routes they will use. The device sends this input data to the server to generate a user profile. The input includes the user's personal information and settings, and the output is the user profile stored on the server.

[0776] Step 2:

[0777] Collection of real-time traffic information

[0778] The server periodically collects information about public transportation from multiple data sources. Specifically, it obtains data from social media, real-time search services, and official transportation websites, using APIs to maintain immediacy. The input is transportation information from each data source, which the server stores in a database. The output is raw data used for analysis.

[0779] Step 3:

[0780] Analysis and detection of traffic anomalies

[0781] The server analyzes collected traffic information using natural language processing (NLP) techniques to identify anomalies such as traffic delays and cancellations. The input is raw data stored in a database, and NLP extracts anomaly patterns from the data. The output is the detected traffic anomaly information.

[0782] Step 4:

[0783] Calculation of alternative routes

[0784] The server calculates alternative routes based on identified traffic anomalies. It uses an optimized routing algorithm that considers travel time, fares, and available departure times based on the user profile. Inputs are traffic anomaly information and user profiles, while output is information on alternative routes available to the user.

[0785] Step 5:

[0786] Analysis of emotional states using an emotion engine

[0787] The terminal receives voice or text from the user and sends it to the server. The server's emotion engine analyzes this data to recognize the user's emotional state. The input is voice or text input from the user, and the output is the user's emotional state revealed by the analysis.

[0788] Step 6:

[0789] Generating and sending notification content

[0790] The server generates notification content in an emotionally sensitive manner based on the analyzed emotional state. Notifications are created in multiple languages ​​and include alternative route information and relevant map links. Inputs are emotional state and alternative route information, while output is a customized notification sent to the user.

[0791] Step 7:

[0792] Receiving and displaying notifications

[0793] The device receives notifications sent from the server and displays them to the user as push notifications. This process supports multilingual display and directly provides the user with relevant map and route information. The input is notification data from the server, and the output is the information displayed on the user's device.

[0794] (Application Example 2)

[0795] 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".

[0796] Current autonomous mobility devices can optimize routes based on traffic conditions, but they cannot provide information that takes into account the emotional state of passengers, nor can they adjust routes based on that information. As a result, passengers may experience anxiety and stress. Furthermore, because information provided during emergencies is uniform, there is a need for flexible service provision that can meet the individual needs of each passenger.

[0797] 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.

[0798] In this invention, the server includes means for detecting the user's emotional state, means for adjusting notification content based on the detected emotional state, and means incorporated into an autonomous mobile device for optimizing travel routes in accordance with the passenger's real-time emotional state and traffic conditions. This enables a comfortable travel experience that takes the passenger's emotions into consideration.

[0799] "User" refers to an individual or group that receives services provided by an autonomous mobile device or system.

[0800] "Emotional state" refers to the user's psychological reactions and circumstances, and is data analyzed through voice, facial expressions, and other means.

[0801] "Notification content" refers to the information the system provides to the user, and the message is adjusted according to traffic conditions and the user's mood.

[0802] An "autonomous mobile device" is a means of transportation that operates automatically without external intervention, using artificial intelligence and sensor technology.

[0803] "Real-time" refers to a state with virtually no time delay, meaning that information is processed and provided instantly.

[0804] "Traffic conditions" refers to information indicating the state of congestion, accidents, delays, etc., along a travel route.

[0805] "Route optimization" refers to calculating the best possible route to a destination, taking into account factors such as time, distance, and the user's feelings.

[0806] The system that implements this application has multiple components for collecting and analyzing traffic information and user emotional states in real time. The system leverages software, including Google Cloud's natural language API and Microsoft Azure's emotion recognition service, to enable users to move comfortably within autonomous mobile devices.

[0807] The server uses a traffic information API to collect real-time data on current traffic conditions. This data is analyzed using an AI model. Furthermore, it evaluates the user's emotional state from audio and video data obtained through the terminal's sensors. This emotional data is used to determine the optimal route and notification content based on the passenger's psychological needs.

[0808] As a concrete example, if a passenger using an autonomous mobile device is heading to the airport in rainy weather, the server analyzes the passenger's emotional state and provides the shortest route to alleviate stress. At this time, it automatically generates a message to reduce the passenger's anxiety and notifies the device.

[0809] An example of a prompt to be input to the generating AI model would be: "Design an application that generates reassuring messages and suggests the optimal route in real time when passengers in an autonomous vehicle are in a hurry. Please consider emotion recognition data and traffic information." This would enable a dynamic and emotion-sensitive mobility service.

[0810] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0811] Step 1:

[0812] The user installs a dedicated application on their device and registers an account. As input, they set their preferred traffic information and emotional data, and as output, a profile is created on the server. The device then processes this information and sends it to the server.

[0813] Step 2:

[0814] The server collects data in real time from a traffic information API. It uses traffic data obtained from an external API as input and stores traffic conditions in a database as output. The server then analyzes this information using an AI model to detect anomalies.

[0815] Step 3:

[0816] The device's sensors collect the user's voice and facial expressions, and analyze their emotional state. Using voice and video data as input, the output provides numerical values ​​and classification results that evaluate the user's emotional state. The device uses an emotion recognition API to perform the analysis.

[0817] Step 4:

[0818] The server uses collected traffic and sentiment data to calculate the optimal travel route. It takes current traffic data and the user's sentiment state as input, and generates an optimized route plan tailored to each user as output. Route calculation involves calculations based on time, distance, and sentiment data.

[0819] Step 5:

[0820] The server generates notification messages in multiple languages ​​and adjusts the content based on the user's emotional state. Using generated route suggestions and user emotional data as input, it produces reassuring, adjusted messages as output. The server utilizes a natural language generation model to prepare push notifications.

[0821] Step 6:

[0822] The device pushes notifications to the user, clearly presenting suggested options along with links to map information. It receives notification data and route links from the server as input, and provides the user with visual information as output. The device uses its display to show this information.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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."

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] The following is further disclosed regarding the embodiments described above.

[0845] (Claim 1)

[0846] An information processing device that provides information about the suspension of public transport for visitors, the hearing impaired, the elderly, and travelers,

[0847] A means of accepting user travel route settings,

[0848] Means for collecting real-time information related to transportation from multiple sources,

[0849] A means of analyzing collected information to detect anomalies,

[0850] Means for calculating an alternative route based on detected anomalies,

[0851] A means of sending notifications to a medium specified by the user,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, characterized in that the information processing device generates notifications in multiple languages ​​and provides them in the language selected by the user.

[0855] (Claim 3)

[0856] The system according to claim 1, characterized in that the information processing device provides a link to the user's terminal for displaying map information.

[0857] "Example 1"

[0858] (Claim 1)

[0859] A device that accepts user travel route settings,

[0860] A device that collects real-time traffic-related data from multiple sources,

[0861] A device that analyzes collected data to detect anomalies,

[0862] A device that calculates an alternative route based on detected anomalies,

[0863] A device that sends notifications to a medium specified by the user,

[0864] A device that selects the optimal alternative route based on multiple conditions to be considered in the event of an anomaly,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, characterized in that it generates notifications in multiple languages ​​and provides them in the language selected by the user.

[0868] (Claim 3)

[0869] The system according to claim 1, characterized in that it provides a link to display map information to the user's terminal.

[0870] "Application Example 1"

[0871] (Claim 1)

[0872] An information processing device that provides information about the suspension of public transport for visitors, the hearing impaired, the elderly, and travelers,

[0873] A means of accepting user travel route settings,

[0874] Means for collecting real-time information related to transportation from multiple sources,

[0875] A means of analyzing collected information to detect anomalies,

[0876] Means for calculating an alternative route based on detected anomalies,

[0877] A means of sending notifications to a medium specified by the user,

[0878] A means for optimizing the route within an autonomous vehicle,

[0879] A means of presenting alternative road routes in the event of traffic abnormalities,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, characterized in that the information processing device generates notifications in multiple languages ​​and provides them in the language selected by the user.

[0883] (Claim 3)

[0884] The system according to claim 1, characterized in that the information processing device provides a link to the user's terminal for displaying map information.

[0885] "Example 2 of combining an emotion engine"

[0886] (Claim 1)

[0887] An information processing system that provides information on public transport stoppages and delays to visitors, the hearing impaired, the elderly, and travelers,

[0888] A means of setting user route information,

[0889] A means of collecting real-time information related to transportation networks from multiple data sources,

[0890] A means of analyzing collected data to detect traffic anomalies,

[0891] A means for calculating an alternative route based on detected traffic anomalies,

[0892] A means including an emotion engine for analyzing the emotional state of the user,

[0893] A means for generating notification content according to emotional state,

[0894] A means of sending emotionally sensitive notifications to a media designated by the user,

[0895] A system that includes this.

[0896] (Claim 2)

[0897] The system according to claim 1, which generates notifications in multiple languages, provides them in the language selected by the user, and analyzes emotions in real time.

[0898] (Claim 3)

[0899] The system according to claim 1, which provides a link to the user's information terminal for visually providing map data.

[0900] "Application example 2 when combining with an emotional engine"

[0901] (Claim 1)

[0902] A means for detecting the emotional state of the user,

[0903] A means of adjusting notification content based on the detected emotional state,

[0904] A means for optimizing travel routes in response to the passenger's real-time emotional state and traffic conditions, which is incorporated into autonomous mobile devices.

[0905] Means of providing passengers with information that takes into account traffic conditions and passenger sentiment,

[0906] A system that includes this.

[0907] (Claim 2)

[0908] The system according to claim 1, characterized in that it provides notifications in a language and format that is appropriate to the emotional state of the passenger.

[0909] (Claim 3)

[0910] The system according to claim 1, characterized in that it provides map information as a link to an exhibition device or mobile terminal. [Explanation of Symbols]

[0911] 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. An information processing device that provides users with information regarding the suspension of public transportation, A means for receiving the user's travel route setting, Means for collecting real-time information related to transportation from multiple sources, A means of analyzing collected information to detect anomalies, Means for calculating an alternative route based on detected anomalies, A means for sending a notification to a medium specified by the user, A system that includes this.

2. The system according to claim 1, characterized in that the information processing device generates notifications in multiple languages ​​and provides them in the language selected by the user.

3. The system according to claim 1, characterized in that the information processing device provides a link to the user's terminal for displaying map information.

Images