system

Abstract

We provide the system. [Solution] An input means for receiving the starting point, destination, and mode of transport from the user, Information gathering means for collecting barrier-free related information from multiple modes of transportation and facilities, An analysis means that analyzes collected barrier-free information and user input information to calculate the optimal travel route, A display means that visually presents the calculated travel route to the user, A means of updating travel routes based on real-time information, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For mobile people with various physical constraints, such as the elderly, people with physical disabilities, and guardians with children, it is difficult to find a barrier-free moving route in public transportation or facilities. Therefore, not only does it take a long time to reach the destination, but it often hinders the planned usage plan. In addition, there is a problem that it is difficult to quickly respond to real-time changes (e.g., elevator failure) during movement.

Means for Solving the Problems

[0005] This invention provides an input means for receiving the user's starting point, destination, and mode of transport, and includes an information gathering means for collecting barrier-free information from multiple transportation services and facilities based on that information. Furthermore, it includes an analysis means for analyzing the collected information and the user's input information to calculate the optimal travel route. The calculated travel route is communicated to the user through a display means that visually presents it. The system also includes an update means for updating the travel route based on real-time information, enabling it to respond to changes during travel as they occur. This helps the user to safely reach their destination via an efficient and barrier-free route while dealing with unexpected situations.

[0006] A "user" is an individual or group that uses the system and specifies the starting point, destination, and mode of transportation.

[0007] "Input means" refers to a function or device for receiving information about movement from the user.

[0008] "Information gathering means" refers to the functions or processes for collecting accessibility-related data from public transportation and facilities.

[0009] "Analysis means" refers to a function or algorithm for calculating the optimal travel path based on the collected information.

[0010] "Display means" refers to devices or functions, such as monitors, that visually convey the travel route to the user.

[0011] "Update method" refers to a function or process that modifies travel routes based on real-time information and provides users with the latest guidance.

[0012] "Barrier-free" refers to environments and facilities that are designed to be safe and easy to use for people with physical limitations.

[0013] "Travel route" refers to the path or method used when traveling from a designated starting point to a destination.

[0014] "Real-time" refers to a state in which it is possible to respond immediately to rapidly changing situations and information while on the move. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the 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 the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] The system according to the present invention provides support to enable users to use specific travel routes with greater peace of mind. Users can start using the system by inputting their starting point, destination, and mode of transportation using a terminal. The terminal receives this information and transmits it to the server.

[0037] The server collects accessibility information from various transportation services and facilities based on the user information it receives. This includes information such as the presence or absence of elevators and steps at each station and facility. Furthermore, it can update information in real time, allowing for quick identification of maintenance or temporary service disruptions.

[0038] Based on the collected information, the server uses analytical tools to calculate the most efficient and safest travel route for the user. This analysis utilizes AI technology and takes into account the user's preferences (e.g., shortest travel time, elevator priority route selection, etc.). After the optimal travel route is calculated, the information is transmitted to the terminal and presented to the user along with map data and detailed travel guides.

[0039] While viewing this, users can follow the designated route, and if new information reaches the server in real time during their journey, the terminal immediately receives and displays the updated route to the user. This means that even if an elevator malfunctions or an emergency change in the route within the facility is required, alternative options are immediately presented, allowing users to proceed to their destination with peace of mind.

[0040] As a concrete example, when a user travels between stations using a wheelchair, they enter their departure and destination points on a terminal, and the server analyzes the optimal elevator locations and transfer routes for each station based on verified accessibility information. Even if the elevator the user was planning to use breaks down during their journey, the server quickly suggests an alternative route, allowing the user to reach their destination with ample time to spare.

[0041] Thus, the present invention provides effective support to enable users to use public transportation safely and smoothly.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user launches the application using a terminal. They enter their departure point, destination, and mode of transportation (e.g., wheelchair, stroller) into the terminal. They also set their travel preferences (e.g., shortest travel time, elevator priority).

[0045] Step 2:

[0046] The terminal sends the entered information to the server. Here, it verifies that the departure and destination specified by the user are unique, and prompts the user to enter any missing information.

[0047] Step 3:

[0048] The server accesses databases of various public transportation systems and related facilities to retrieve accessibility information. This information includes the location and status of elevators in stations and facilities, as well as the availability of accessibility features.

[0049] Step 4:

[0050] The server uses AI analysis to calculate the optimal travel route based on the acquired information and user input. The analysis generates multiple route options that reflect the user's preferences and the collected real-time situation data.

[0051] Step 5:

[0052] The server transmits the optimal travel route, derived from the analysis, to the terminal. The route information includes the location of elevators to be used and transfer routes, providing detailed directions.

[0053] Step 6:

[0054] The terminal displays the received route information to the user in map or list format. The user begins their journey based on the presented information, and the terminal continuously monitors their progress.

[0055] Step 7:

[0056] While in transit, the server continuously receives real-time operational information and equipment status updates from facilities and railway companies. If a significant change occurs (e.g., elevator malfunction), the server analyzes the situation in real time and calculates a new, optimal route.

[0057] Step 8:

[0058] The server immediately sends the recalculated route to the terminal. The terminal receives this information, updates the route, and notifies the user of the change. The user reviews the new route guidance and corrects the route as needed.

[0059] This allows users to flexibly respond to unexpected obstacles during their journey while safely and smoothly reaching their destination.

[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] One of the problems faced by people with mobility limitations when using public transportation is that insufficient accessibility information along the route prevents them from reaching their destination smoothly and safely. Furthermore, disruptions caused by equipment failures or delays in receiving necessary information also pose a problem.

[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 an information acquisition means for receiving the starting point, destination point, and method of travel from the user; an information aggregation means for collecting fluid obstacle information from multiple transportation methods and facilities; and an analysis means for analyzing the acquired obstacle information and user input information and calculating the optimal travel route using artificial intelligence technology. This enables the user to know the optimal travel route, which is updated in real time, allowing them to reach their destination safely and efficiently.

[0065] "Information acquisition means" refers to a device or method for receiving information from a user regarding the starting point, destination, and method of travel.

[0066] "Information aggregation means" refers to a device or method for collecting and aggregating fluid obstacle information from multiple transportation systems and facilities.

[0067] "Analysis means" refers to a device or method that analyzes acquired obstacle information and user input information and calculates the optimal travel route using artificial intelligence technology.

[0068] "Information display means" refers to a device or method for presenting a calculated travel route to the user visually or audibly.

[0069] A "dynamic update means" is a device or method for recalculating a travel route based on information that changes in real time.

[0070] This invention is a system that assists users with mobility limitations in traveling safely and efficiently using public transportation. The user begins by inputting their departure point, destination, and mode of transport using a terminal. The terminal has a dedicated application installed, allowing for easy input of this information through an intuitive interface.

[0071] The terminal transmits this information to the server via an information acquisition means through an internet connection. The server uses an information aggregation means to collect fluid accessibility information provided by multiple transportation systems and facilities. This information includes elements that change in real time, such as elevator status, presence or absence of steps, and ramp angles. In addition, IoT sensors and publicly available open data APIs are used to ensure the accuracy and timeliness of the information.

[0072] As an analysis method, the server utilizes artificial intelligence technology to calculate the optimal travel route based on the acquired data and the user's desired conditions. This involves using deep learning models and shortest path algorithms, and the analysis takes into account the user's priorities (e.g., speed of travel, ensuring safety).

[0073] The resulting travel route is transmitted to the user's terminal via an information display device. The user can refer to this and travel according to visual map data and audio guidance. Furthermore, through a dynamic update device, even if new information arrives on the server during travel, the plan can be immediately modified and the latest route guidance can be provided.

[0074] For example, when a user travels between stations using a wheelchair, they input their departure and destination points, and the server analyzes the appropriate route based on accessibility information. Dynamic information is reflected, and even if the elevator the user was planning to use malfunctions, an alternative route is immediately suggested, allowing the user to continue their journey with peace of mind.

[0075] An example of a prompt for a generative AI model is: "When a user is traveling from one station to another using a wheelchair, please suggest the optimal route considering accessibility information."

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The user enters their starting point, destination, and mode of transport using a terminal. This data is easily entered using a form in a dedicated application. This information is structured in JSON format and prepared for transmission to the server.

[0079] Step 2:

[0080] The terminal sends the information received from the user to the server. Since this data is transmitted over the internet, the HTTP protocol is typically used. The output is the server receiving the data, indicating that the user's request was successfully delivered to the server.

[0081] Step 3:

[0082] The server uses information aggregation tools to collect real-time accessibility information from various transportation services and facilities. It retrieves information from various data sources using APIs and stores this data in a centralized database. This ensures that elevator operating status and facility accessibility information are always up-to-date. The output is a set of transportation information relevant to the user.

[0083] Step 4:

[0084] The server uses analytical tools to calculate the optimal travel route using AI technology, based on collected accessibility information and user input. The calculation employs shortest path algorithms and machine learning models, which are customized to meet user-specified conditions. The output is optimized travel route data.

[0085] Step 5:

[0086] The server sends the calculated optimal travel route to the terminal. The terminal visually displays this information to the user, drawing the route on a map. Furthermore, it can provide the user with travel instructions accompanied by voice guidance. The output is the route displayed on the user's terminal.

[0087] Step 6:

[0088] During transit, the terminal communicates with the server in real time, updating the screen display whenever new information is received. The server provides the terminal with a recalculated travel route using the latest accessibility information, and presents a new route that takes unexpected obstacles into account. The final output is the presentation of the updated travel route.

[0089] (Application Example 1)

[0090] 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."

[0091] In modern cities, various obstacles and fluctuations in public transportation make it difficult for users to travel smoothly and safely. In particular, when using transportation methods requiring accessibility, optimal route information is often unavailable at the time of travel. As a result, users often experience anxiety about their journey due to unexpected delays and the need for detours. There is a need to provide systems that solve these problems and enable users to reach their destinations efficiently and safely.

[0092] 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.

[0093] In this invention, the server includes data receiving means for receiving the starting point, destination, and means of transportation from the user; information acquisition means for collecting information related to obstacle avoidance from multiple means of transportation and facilities; and calculation means for analyzing the collected obstacle avoidance information and user input information to calculate an efficient travel route. This makes it possible to provide the optimal travel route for the user while responding to unforeseen circumstances in real time.

[0094] A "user" refers to a person who uses a travel route system to receive directions to their destination.

[0095] "Starting point" refers to information about the point from which the user will depart from their current location.

[0096] "Destination" refers to the final location that the user wants to achieve.

[0097] "Transportation" refers to information about the means of transport that a user uses to reach their destination.

[0098] "Data receiving means" refers to the means by which the system receives information about the starting point, destination, and means of transportation entered by the user.

[0099] "Transportation" refers to means that enable geographical movement, and includes a variety of methods of travel, such as trains, buses, and wheelchairs.

[0100] "Facilities" refers to public or private buildings or places that users may potentially use.

[0101] "Information related to obstacle avoidance" includes information about obstacles or malfunctions that may hinder the user's movement.

[0102] "Information acquisition means" refers to means equipped with the function of collecting relevant information in real time from transportation methods and facilities.

[0103] "Analysis" refers to data processing used to derive the optimal travel route based on collected information.

[0104] "Calculation means" refers to a device or program that performs the calculations necessary to determine the best travel path from multiple input pieces of information.

[0105] A "visualization means" is a means that has a display function to present the calculated travel route to the user in an easy-to-understand manner.

[0106] "Information update means" refers to means for updating information in real time and recalculating existing travel routes as needed.

[0107] An "optimization method" is a means of adjusting the travel route to be more efficient or safer in response to changes in circumstances or user requests.

[0108] The system based on this invention is implemented with three main components: a user, a terminal, and a server. The user uses a mobile device or wearable device as a terminal and inputs the starting point, destination, and mode of transportation to be used through the terminal. This information is aggregated by the terminal's data receiving means and transmitted to the server.

[0109] The server operates using a backend system built with Node.js or Python, processing information received from users. The server collects information on transportation methods and obstacle avoidance information from facilities via APIs. This allows for real-time acquisition of traffic conditions and accessibility information. After information collection, the server's computing power uses AI analysis technologies such as TENSORFLOW® and PyTorch to algorithmically calculate the optimal travel route for the user.

[0110] The calculated travel route is transmitted to the user's device through a visualization mechanism. Applications developed using programming languages ​​such as React Native, Swift, and Kotlin are used, allowing users to visually confirm the route through an intuitive interface. Furthermore, an information update mechanism continuously updates the travel route with the latest information collected during the journey, enabling immediate response to unforeseen circumstances.

[0111] A concrete example of its use is when a user is moving around a large commercial facility and is offered the optimal route to efficiently visit each store using the disabled-accessible passageway. In this scenario, the server analyzes the usage status and congestion level of elevators within the facility in real time and provides the user with the shortest and most comfortable travel route.

[0112] An example of a prompt message would be, "Please provide barrier-free navigation that guides wheelchair users to the optimal route from Shinjuku Station to Shibuya Station in a safe and convenient manner." This specific input would then trigger an AI-powered optimized route search.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The user uses a device to input their starting point, destination, and mode of transportation. This input is received by a data receiving device and is the data input sent to the server. The device uses location services to obtain and transmit accurate geographical data.

[0116] Step 2:

[0117] Based on the received information, the server collects real-time obstacle avoidance information from transportation methods and facilities via APIs. Input includes the user's location and desired conditions, and accordingly, relevant accessibility information and transportation data are retrieved from internet resources. Data acquisition and initial processing take place at this stage.

[0118] Step 3:

[0119] The server's computing power uses collected information to calculate the optimal travel path. By combining input location information and obstacle avoidance information, and utilizing AI analysis techniques (TensorFlow and PyTorch), it calculates the travel path that best suits the user's preferences. This outputs data that allows the user to reach their destination efficiently.

[0120] Step 4:

[0121] The server sends the calculated travel route to the terminal. The output route information is presented to the user through the terminal's visualization means. The terminal visually displays map data and detailed travel guides through the application, and the user begins their journey based on this information.

[0122] Step 5:

[0123] During transit, the server collects new information in real time and recalculates the travel route as needed. This includes the latest traffic information and accessibility status, which is used to re-optimize the current route. As a result, any potential changes are immediately transmitted to the user's terminal.

[0124] Step 6:

[0125] The device receives updated route information and presents it to the user quickly. This received data is reflected in the application's UI, allowing the user to smoothly continue their travel planning in accordance with changing circumstances. In other words, the process of continuously providing optimal route guidance in real time is completed.

[0126] 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.

[0127] The system according to the present invention integrates a series of functions to support user mobility, and is particularly aimed at optimizing mobility by taking into account the user's emotional state. This system begins by receiving information from the user via a terminal regarding the origin, destination, and mode of transportation. The user's input information is transmitted from the terminal to a server, which collects accessibility information from transportation companies and facilities.

[0128] The collected information is processed by an analysis system on the server to calculate the optimal travel route. The analysis includes multiple options that take real-time information and user preferences into account. Furthermore, the system is equipped with an emotion engine that can detect the user's stress and tension levels in real time. This emotion engine analyzes emotions from the user's voice tone and biometric information (e.g., heart rate and skin resistance) and adjusts the selection of the travel route and the method of information presentation accordingly.

[0129] The route calculated by the server is sent to the terminal and presented to the user visually and audibly. The terminal adjusts the visual presentation of the guidance information in response to the user's emotional state (e.g., displaying in calming colors or adjusting font size). If the user feels stressed or anxious during the journey, the emotion engine detects this and provides a response message or guidance to help them relax. For example, if the system detects user stress, a message such as "You're on track. Take your time and don't rush" will be displayed.

[0130] For example, if a user feels anxious while traveling through a crowded station, the emotion engine detects this state and suggests escape routes or quiet waiting areas along the way to promote calmness. In addition, when selecting a travel route, routes that prioritize comfort are given priority.

[0131] In this way, the entire system is designed to provide enhanced support, a sense of security, and safety, ensuring that users can travel comfortably.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] The user launches the application using the terminal and enters their departure point, destination, and mode of transportation (e.g., wheelchair, stroller). The terminal assists in easily entering the necessary information through its user interface.

[0135] Step 2:

[0136] Once input is complete, the terminal sends the user's information to the server. The server receives this information and begins preparing for the next processing step.

[0137] Step 3:

[0138] The server collects accessibility-related data from various transportation services and facilities. This includes information such as elevator locations, availability, and the status of accessibility features within facilities. The server then systematically organizes this information.

[0139] Step 4:

[0140] Subsequently, the server uses AI analysis tools to analyze the collected information and user input to calculate the most optimal travel route. The analysis takes into account the user's preferences (shortest travel time, elevator use, etc.), real-time operational data, and equipment usage status.

[0141] Step 5:

[0142] The emotion engine is activated to collect the user's biometric information (e.g., heart rate, voice tone, etc.) in real time and evaluate their emotional state, such as stress and anxiety. At this time, device sensors detect changes in the user's emotions and send the data to the server.

[0143] Step 6:

[0144] Based on information from the emotion engine, the server dynamically readjusts the travel route and the way information is presented. If the server detects that the user is in a high-stress state, it generates guidance that takes into account calmer travel routes and points to avoid.

[0145] Step 7:

[0146] The analyzed information is sent to the device and presented to the user visually and audibly on the device. Here, the presentation method also reflects the feedback from the emotion engine. Specifically, calming colors and encouraging messages are displayed on the screen.

[0147] Step 8:

[0148] As the user begins their journey and heads towards their destination, the server continuously receives real-time operational information and equipment status, recalculating the route as needed and sending updated directions to the device. Throughout this process, feedback from the emotion engine is continuously utilized.

[0149] This helps reduce the psychological burden on users during their journey, enabling them to reach their destination safely and comfortably.

[0150] (Example 2)

[0151] 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".

[0152] While modern mobility systems are well-equipped to meet users' physical travel needs, they face the challenge of optimizing travel by taking into account users' emotional states. As a result, users may experience anxiety due to environmental changes or stress. There is a particular need for services that allow elderly people and people with disabilities to travel with peace of mind.

[0153] 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.

[0154] In this invention, the server includes an input means for receiving the starting position, ending position, and means of transportation from the user; an information gathering means for collecting information to eliminate obstacles from multiple transportation methods and facilities; an analysis means for analyzing the collected information and calculating the optimal travel route; and an emotion analysis means for detecting the user's emotional state from the user's physiological data and adjusting it according to the travel route selection. This enables safe and optimal travel while taking the user's emotional state into consideration.

[0155] "Input means" refers to a device or method for receiving information from the user regarding the starting position, ending position, and means of movement.

[0156] "Information gathering means" refers to a device or method for obtaining information from multiple transportation systems and facilities in order to eliminate obstacles.

[0157] "Analysis means" refers to a device or method for calculating the optimal travel route based on collected obstacle elimination information and user input information.

[0158] "Display means" refers to a device or method for presenting the calculated travel path to the user visually and audibly.

[0159] "Update means" refers to a device or method for updating a travel route using real-time information.

[0160] "Emotional analysis means" refers to a device or method for detecting an emotional state based on the user's physiological data and reflecting this in the selection of a travel route.

[0161] "Adjustment means" refers to a device or method for appropriately adjusting the displayed content according to the user's emotional state.

[0162] This invention provides a system that optimizes a user's movement according to their emotional state. The system begins with the user inputting their starting point, destination, and mode of transportation using a terminal. The terminal collects this data and transmits it to a server. The server uses advanced information gathering means to obtain real-time traffic and accessibility information from databases of external transportation companies and public facilities. Programming interfaces such as APIs may be used for this information gathering.

[0163] After collecting information, the server analyzes the data using a generative AI model to calculate the optimal travel path. This process considers not only user input but also physiological data and emotional state. To detect emotional state, biosensors are used to analyze the user's heart rate and voice tone. As a result, if the user is in a high-stress state, the server selects a more relaxing path.

[0164] The calculated travel route is transmitted from the server to the terminal. The terminal receives this information and presents it to the user in an easy-to-understand manner. Specifically, it provides information to the user using visual maps and voice guidance. The terminal also has a function that automatically adjusts the display's color tone and font size according to the user's emotional state. For example, if the user is feeling stressed, the display will be shown in calming colors to alleviate their tension.

[0165] For example, if a user inputs "Tell me the best route from Shibuya Station to Shinjuku Station," the system might analyze the prompt and recommend a quiet bus route. In this way, the system can respond to the user's different emotional states and provide the most appropriate travel method in real time.

[0166] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0167] Step 1:

[0168] The user uses a terminal to input their starting location, destination location, and preferred mode of transportation. The terminal converts this input data into an internal format and prepares it for transmission to the server. The input data includes geographical information and information about the selected mode of transportation.

[0169] Step 2:

[0170] The terminal sends the converted input data to the server. Upon receiving the data, the server stores it in a database for secure analysis. At this stage, a simple verification process is performed to confirm the integrity and accuracy of the data.

[0171] Step 3:

[0172] The server uses information gathering tools to access external transportation APIs and public facility databases to obtain real-time traffic and accessibility information. This data is an important factor related to user travel and is taken into consideration in the analysis.

[0173] Step 4:

[0174] The server uses a generative AI model to analyze collected real-time information and user input data. The analysis considers available route information, the status of transportation options, and accessibility. Furthermore, an emotion analysis system detects the user's emotional state and incorporates this into the route selection. At this point, an optimized route is calculated within the server.

[0175] Step 5:

[0176] The calculated travel route is transmitted from the server to the terminal. The terminal ensures the user understands the route by providing visual and auditory instructions. Specifically, map displays and audio guidance are used. If necessary, the terminal automatically adjusts the display's color tone and font size to improve user comfort.

[0177] Step 6:

[0178] If a user experiences stress or anxiety while traveling, the device's emotion engine detects this, and the server updates the route or messages accordingly. For example, it might send a voice message to encourage relaxation or suggest a safer route. This allows for a more personalized user experience.

[0179] (Application Example 2)

[0180] 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".

[0181] Conventional travel route optimization systems often fail to adequately consider the user's emotional state, making it difficult to alleviate the tension and anxiety they experience during travel. In particular, they lack the ability to provide flexible information tailored to the user's emotional state, resulting in users not feeling sufficiently secure during their journey.

[0182] 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.

[0183] In this invention, the server includes an input means for receiving the starting point, destination point, and means of transportation from the user; an information gathering means for collecting unobstructed information from multiple means of transportation and facilities; an analysis means for analyzing the collected unobstructed information and user input information to calculate the optimal travel route; a display means for presenting the calculated travel route to the user visually and audibly; an update means for updating the travel route based on real-time information; and an emotion analysis means for detecting the user's emotional state and adjusting the travel route and information presentation method. This enables detailed travel support tailored to the user's emotional state.

[0184] "Input means" refers to a device or method for receiving information from the user regarding the starting point, destination, and means of transportation.

[0185] "Information gathering means" refers to a device or method for collecting unobstructed information from multiple means of transportation or facilities.

[0186] "Analysis means" refers to a device or method for calculating the optimal travel path based on collected unobstructed information and user input information.

[0187] "Display means" refers to a device or method for visually and audibly presenting the calculated travel path to the user.

[0188] "Update means" refers to a device or method for updating a travel route based on real-time information.

[0189] "Emotional analysis means" refers to a device or method for detecting a user's emotional state and adjusting the movement path and information presentation method accordingly.

[0190] The system for carrying out the present invention takes into account the user's emotional state when the user is moving and provides the optimal travel route and information delivery method. This system includes various sensors, processing devices, and output devices.

[0191] As an initial setup, the server receives information from the user regarding the departure point, destination, and mode of transportation via an input device. This input device is implemented through mobile devices such as smartphones and tablets. Next, the server uses an information gathering device to collect unobstructed information from multiple modes of transportation and facilities. This utilizes transportation APIs and public information databases.

[0192] The obtained data is processed by an analysis system to calculate the optimal route for the user's desired travel. The analysis system uses data analysis software such as Python or R, and employs algorithms to evaluate and optimize various conditions. The calculation results are presented to the user via a display system. The display system provides information visually and audibly using a display screen or speech synthesis technology.

[0193] Furthermore, the emotion analysis system monitors the user's biometric data using sensors and detects their emotional state. This is done using heart rate monitors and speech recognition technology. This data is analyzed by a generative AI model to evaluate the user's stress and anxiety levels. Based on this evaluation, the emotion analysis system adjusts the movement path and information presentation method to provide the user with a sense of security.

[0194] For example, if a user feels anxious in a crowded train station, the emotion analysis system will detect this state, and the server will prioritize suggesting a route that passes through a quiet space where the user can relax. In this case, an example of a prompt message to the generating AI model might be, "The user is experiencing high stress. Please suggest a quiet and safe route."

[0195] The entire system is designed to provide flexible support tailored to the user's emotional state, ensuring they can travel with peace of mind.

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

[0197] Step 1:

[0198] The server receives information from the user via the terminal, including the starting point, destination, and mode of transportation. Based on the information collected through the input, it queries the database to determine the user's specific request. As output, the user's travel preferences are finalized as specific parameters.

[0199] Step 2:

[0200] The server uses information gathering methods to collect uninterrupted information from multiple modes of transportation and facilities. This includes processes for obtaining real-time data from transportation APIs and facility information. Inputs are database queries and API requests, and outputs are integrated transportation and facility information.

[0201] Step 3:

[0202] The server analyzes the collected data using analytical tools and calculates the optimal travel route for the user's request. It performs multivariate analysis through a Python algorithm to calculate the optimal route. The input is a vast amount of collected traffic data, and the output is the most efficient travel suggestion.

[0203] Step 4:

[0204] The terminal presents the calculated travel route to the user via a display. The terminal's display graphically shows the route information, and provides detailed explanations using audio guidance as needed. The input is the calculated travel route, and the output is visual and auditory information in a format understandable to the user.

[0205] Step 5:

[0206] The server uses an update mechanism to update the travel route in real time in response to changing conditions. It monitors changes in traffic information and recalculates the travel plan as needed. The input is newly acquired real-time traffic data, and the output is the updated travel route.

[0207] Step 6:

[0208] The server receives biometric data from sensors to analyze the user's emotional state using emotion analysis tools. Data such as heart rate monitor and voice tone are analyzed by a generating AI model. The input is real-time biometric data, and the output is an evaluation of the user's emotional state.

[0209] Step 7:

[0210] The server adjusts the navigation path and information presentation method based on the results of the emotion analysis. If stress is detected, it prepares a calming path and information presentation. Using a generative AI model, it creates specific prompt sentences and notifies the user of reassuring information. The input is the emotion analysis result, and the output is the adjusted information provided to the user.

[0211] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0212] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0213] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0214] [Second Embodiment]

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

[0216] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0217] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0218] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0219] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0220] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0221] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0222] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0223] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0224] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0225] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0226] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0227] The system according to the present invention provides support to enable users to use specific travel routes with greater peace of mind. Users can start using the system by inputting their starting point, destination, and mode of transportation using a terminal. The terminal receives this information and transmits it to the server.

[0228] The server collects accessibility information from various transportation services and facilities based on the user information it receives. This includes information such as the presence or absence of elevators and steps at each station and facility. Furthermore, it can update information in real time, allowing for quick identification of maintenance or temporary service disruptions.

[0229] Based on the collected information, the server uses analytical tools to calculate the most efficient and safest travel route for the user. This analysis utilizes AI technology and takes into account the user's preferences (e.g., shortest travel time, elevator priority route selection, etc.). After the optimal travel route is calculated, the information is transmitted to the terminal and presented to the user along with map data and detailed travel guides.

[0230] While viewing this, users can follow the designated route, and if new information reaches the server in real time during their journey, the terminal immediately receives and displays the updated route to the user. This means that even if an elevator malfunctions or an emergency change in the route within the facility is required, alternative options are immediately presented, allowing users to proceed to their destination with peace of mind.

[0231] As a concrete example, when a user travels between stations using a wheelchair, they enter their departure and destination points on a terminal, and the server analyzes the optimal elevator locations and transfer routes for each station based on verified accessibility information. Even if the elevator the user was planning to use breaks down during their journey, the server quickly suggests an alternative route, allowing the user to reach their destination with ample time to spare.

[0232] Thus, the present invention provides effective support to enable users to use public transportation safely and smoothly.

[0233] The following describes the processing flow.

[0234] Step 1:

[0235] The user launches the application using a terminal. They enter their departure point, destination, and mode of transportation (e.g., wheelchair, stroller) into the terminal. They also set their travel preferences (e.g., shortest travel time, elevator priority).

[0236] Step 2:

[0237] The terminal sends the entered information to the server. Here, it verifies that the departure and destination specified by the user are unique, and prompts the user to enter any missing information.

[0238] Step 3:

[0239] The server accesses databases of various public transportation systems and related facilities to retrieve accessibility information. This information includes the location and status of elevators in stations and facilities, as well as the availability of accessibility features.

[0240] Step 4:

[0241] The server uses AI analysis to calculate the optimal travel route based on the acquired information and user input. The analysis generates multiple route options that reflect the user's preferences and the collected real-time situation data.

[0242] Step 5:

[0243] The server transmits the optimal travel route, derived from the analysis, to the terminal. The route information includes the location of elevators to be used and transfer routes, providing detailed directions.

[0244] Step 6:

[0245] The terminal displays the received route information to the user in map or list format. The user begins their journey based on the presented information, and the terminal continuously monitors their progress.

[0246] Step 7:

[0247] While in transit, the server continuously receives real-time operational information and equipment status updates from facilities and railway companies. If a significant change occurs (e.g., elevator malfunction), the server analyzes the situation in real time and calculates a new, optimal route.

[0248] Step 8:

[0249] The server immediately sends the recalculated route to the terminal. The terminal receives this information, updates the route, and notifies the user of the change. The user reviews the new route guidance and corrects the route as needed.

[0250] This allows users to flexibly respond to unexpected obstacles during their journey while safely and smoothly reaching their destination.

[0251] (Example 1)

[0252] 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."

[0253] One of the problems faced by people with mobility limitations when using public transportation is that insufficient accessibility information along the route prevents them from reaching their destination smoothly and safely. Furthermore, disruptions caused by equipment failures or delays in receiving necessary information also pose a problem.

[0254] 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.

[0255] In this invention, the server includes an information acquisition means for receiving the starting point, destination point, and method of travel from the user; an information aggregation means for collecting fluid obstacle information from multiple transportation methods and facilities; and an analysis means for analyzing the acquired obstacle information and user input information and calculating the optimal travel route using artificial intelligence technology. This enables the user to know the optimal travel route, which is updated in real time, allowing them to reach their destination safely and efficiently.

[0256] "Information acquisition means" refers to a device or method for receiving information from a user regarding the starting point, destination, and method of travel.

[0257] "Information aggregation means" refers to a device or method for collecting and aggregating fluid obstacle information from multiple transportation systems and facilities.

[0258] "Analysis means" refers to a device or method that analyzes acquired obstacle information and user input information and calculates the optimal travel route using artificial intelligence technology.

[0259] "Information display means" refers to a device or method for presenting a calculated travel route to the user visually or audibly.

[0260] A "dynamic update means" is a device or method for recalculating a travel route based on information that changes in real time.

[0261] This invention is a system that assists users with mobility limitations in traveling safely and efficiently using public transportation. The user begins by inputting their departure point, destination, and mode of transport using a terminal. The terminal has a dedicated application installed, allowing for easy input of this information through an intuitive interface.

[0262] The terminal transmits this information to the server via an information acquisition means through an internet connection. The server uses an information aggregation means to collect fluid accessibility information provided by multiple transportation systems and facilities. This information includes elements that change in real time, such as elevator status, presence or absence of steps, and ramp angles. In addition, IoT sensors and publicly available open data APIs are used to ensure the accuracy and timeliness of the information.

[0263] As an analysis method, the server utilizes artificial intelligence technology to calculate the optimal travel route based on the acquired data and the user's desired conditions. This involves using deep learning models and shortest path algorithms, and the analysis takes into account the user's priorities (e.g., speed of travel, ensuring safety).

[0264] The resulting travel route is transmitted to the user's terminal via an information display device. The user can refer to this and travel according to visual map data and audio guidance. Furthermore, through a dynamic update device, even if new information arrives on the server during travel, the plan can be immediately modified and the latest route guidance can be provided.

[0265] For example, when a user travels between stations using a wheelchair, they input their departure and destination points, and the server analyzes the appropriate route based on accessibility information. Dynamic information is reflected, and even if the elevator the user was planning to use malfunctions, an alternative route is immediately suggested, allowing the user to continue their journey with peace of mind.

[0266] An example of a prompt for a generative AI model is: "When a user is traveling from one station to another using a wheelchair, please suggest the optimal route considering accessibility information."

[0267] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0268] Step 1:

[0269] The user enters their starting point, destination, and mode of transport using a terminal. This data is easily entered using a form in a dedicated application. This information is structured in JSON format and prepared for transmission to the server.

[0270] Step 2:

[0271] The terminal sends the information received from the user to the server. Since this data is transmitted over the internet, the HTTP protocol is typically used. The output is the server receiving the data, indicating that the user's request was successfully delivered to the server.

[0272] Step 3:

[0273] The server uses information aggregation tools to collect real-time accessibility information from various transportation services and facilities. It retrieves information from various data sources using APIs and stores this data in a centralized database. This ensures that elevator operating status and facility accessibility information are always up-to-date. The output is a set of transportation information relevant to the user.

[0274] Step 4:

[0275] The server uses analytical tools to calculate the optimal travel route using AI technology, based on collected accessibility information and user input. The calculation employs shortest path algorithms and machine learning models, which are customized to meet user-specified conditions. The output is optimized travel route data.

[0276] Step 5:

[0277] The server sends the calculated optimal travel route to the terminal. The terminal visually displays this information to the user, drawing the route on a map. Furthermore, it can provide the user with travel instructions accompanied by voice guidance. The output is the route displayed on the user's terminal.

[0278] Step 6:

[0279] During transit, the terminal communicates with the server in real time, updating the screen display whenever new information is received. The server provides the terminal with a recalculated travel route using the latest accessibility information, and presents a new route that takes unexpected obstacles into account. The final output is the presentation of the updated travel route.

[0280] (Application Example 1)

[0281] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0282] In modern cities, due to various obstacles and changes in public transportation, it is difficult for users to move smoothly and safely. In particular, when using a means of transportation that requires barrier-free access, it is often impossible to obtain the most optimal route information at that time. For this reason, users often feel anxious about moving due to unexpected delays or the need for detours. There is a demand for a system that can solve such problems and enable users to reach their destinations efficiently and safely.

[0283] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0284] In this invention, the server includes data receiving means for receiving a starting point of movement, a destination, and a means of movement from a user, information acquisition means for collecting information related to obstacle avoidance from a plurality of means of transportation and facilities, and calculation means for analyzing the collected obstacle avoidance information and the user's input information to calculate an efficient movement route. As a result, it becomes possible to provide an optimal movement route for the user while coping with unexpected situations in real time.

[0285] The "user" refers to a person who receives guidance to a destination using the movement route system.

[0286] The "starting point of movement" indicates information on the point from which the user departs from the current position.

[0287] The "destination" means the final position that the user wants to reach.

[0288] "Transportation" refers to information about the means of transport that a user uses to reach their destination.

[0289] "Data receiving means" refers to the means by which the system receives information about the starting point, destination, and means of transportation entered by the user.

[0290] "Transportation" refers to means that enable geographical movement, and includes a variety of methods of travel, such as trains, buses, and wheelchairs.

[0291] "Facilities" refers to public or private buildings or places that users may potentially use.

[0292] "Information related to obstacle avoidance" includes information about obstacles or malfunctions that may hinder the user's movement.

[0293] "Information acquisition means" refers to means equipped with the function of collecting relevant information in real time from transportation methods and facilities.

[0294] "Analysis" refers to data processing used to derive the optimal travel route based on collected information.

[0295] "Calculation means" refers to a device or program that performs the calculations necessary to determine the best travel path from multiple input pieces of information.

[0296] A "visualization means" is a means that has a display function to present the calculated travel route to the user in an easy-to-understand manner.

[0297] "Information update means" refers to means for updating information in real time and recalculating existing travel routes as needed.

[0298] An "optimization method" is a means of adjusting the travel route to be more efficient or safer in response to changes in circumstances or user requests.

[0299] The system based on this invention is implemented with three main components: a user, a terminal, and a server. The user uses a mobile device or wearable device as a terminal and inputs the starting point, destination, and mode of transportation to be used through the terminal. This information is aggregated by the terminal's data receiving means and transmitted to the server.

[0300] The server operates using a backend system built with Node.js or Python, processing information received from users. The server collects information on transportation options and obstacle avoidance information from facilities via APIs. This allows for real-time acquisition of traffic conditions and accessibility information. After information collection, the server's computing power uses AI analysis technologies such as TensorFlow and PyTorch to algorithmically calculate the optimal travel route for the user.

[0301] The calculated travel route is transmitted to the user's device through a visualization mechanism. Applications developed using programming languages ​​such as React Native, Swift, and Kotlin are used, allowing users to visually confirm the route through an intuitive interface. Furthermore, an information update mechanism continuously updates the travel route with the latest information collected during the journey, enabling immediate response to unforeseen circumstances.

[0302] A concrete example of its use is when a user is moving around a large commercial facility and is offered the optimal route to efficiently visit each store using the disabled-accessible passageway. In this scenario, the server analyzes the usage status and congestion level of elevators within the facility in real time and provides the user with the shortest and most comfortable travel route.

[0303] An example of a prompt message would be, "Please provide barrier-free navigation that guides wheelchair users to the optimal route from Shinjuku Station to Shibuya Station in a safe and convenient manner." This specific input would then trigger an AI-powered optimized route search.

[0304] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0305] Step 1:

[0306] The user uses the terminal to input the starting point of movement, the destination, and the means of movement. This input is received by the data receiving means and is the input of the data transmitted to the server. The terminal uses the position information service to obtain accurate geographical data and transmits it.

[0307] Step 2:

[0308] Based on the received information, the server collects real-time obstacle avoidance information from transportation means and facilities via the API. The inputs include the user's position information and desired conditions, and accordingly, relevant barrier-free information and traffic data are obtained from Internet resources. At this point, data acquisition and initial processing are performed.

[0309] Step 3:

[0310] The calculation means of the server calculates the optimal movement route using the collected information. By combining the input position information and obstacle avoidance information and making full use of AI analysis technologies (such as TensorFlow and PyTorch), the movement route most suitable for the user's wishes is calculated. As a result, data for the user to efficiently reach the destination is output.

[0311] Step 4:

[0312] The server transmits the calculated movement route to the terminal. The output route information is presented to the user by the visualization means of the terminal. The terminal visually displays map data and detailed movement guides through the application, and the user starts moving based on it.

[0313] Step 5:

[0314] <During transit, the server collects new information in real time and recalculates the travel route as needed. This includes the latest traffic information and accessibility status, which is used to re-optimize the current route. As a result, any potential changes are immediately transmitted to the user's terminal.

[0315] Step 6:

[0316] The device receives updated route information and presents it to the user quickly. This received data is reflected in the application's UI, allowing the user to smoothly continue their travel planning in accordance with changing circumstances. In other words, the process of continuously providing optimal route guidance in real time is completed.

[0317] 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.

[0318] The system according to the present invention integrates a series of functions to support user mobility, and is particularly aimed at optimizing mobility by taking into account the user's emotional state. This system begins by receiving information from the user via a terminal regarding the origin, destination, and mode of transportation. The user's input information is transmitted from the terminal to a server, which collects accessibility information from transportation companies and facilities.

[0319] The collected information is processed by an analysis system on the server to calculate the optimal travel route. The analysis includes multiple options that take real-time information and user preferences into account. Furthermore, the system is equipped with an emotion engine that can detect the user's stress and tension levels in real time. This emotion engine analyzes emotions from the user's voice tone and biometric information (e.g., heart rate and skin resistance) and adjusts the selection of the travel route and the method of information presentation accordingly.

[0320] The route calculated by the server is sent to the terminal and presented to the user visually and audibly. The terminal adjusts the visual presentation of the guidance information in response to the user's emotional state (e.g., displaying in calming colors or adjusting font size). If the user feels stressed or anxious during the journey, the emotion engine detects this and provides a response message or guidance to help them relax. For example, if the system detects user stress, a message such as "You're on track. Take your time and don't rush" will be displayed.

[0321] For example, if a user feels anxious while traveling through a crowded station, the emotion engine detects this state and suggests escape routes or quiet waiting areas along the way to promote calmness. In addition, when selecting a travel route, routes that prioritize comfort are given priority.

[0322] In this way, the entire system is designed to provide enhanced support, a sense of security, and safety, ensuring that users can travel comfortably.

[0323] The following describes the processing flow.

[0324] Step 1:

[0325] The user launches the application using the terminal and enters their departure point, destination, and mode of transportation (e.g., wheelchair, stroller). The terminal assists in easily entering the necessary information through its user interface.

[0326] Step 2:

[0327] Once input is complete, the terminal sends the user's information to the server. The server receives this information and begins preparing for the next processing step.

[0328] Step 3:

[0329] The server collects accessibility-related data from various transportation services and facilities. This includes information such as elevator locations, availability, and the status of accessibility features within facilities. The server then systematically organizes this information.

[0330] Step 4:

[0331] Subsequently, the server uses AI analysis tools to analyze the collected information and user input to calculate the most optimal travel route. The analysis takes into account the user's preferences (shortest travel time, elevator use, etc.), real-time operational data, and equipment usage status.

[0332] Step 5:

[0333] The emotion engine is activated to collect the user's biometric information (e.g., heart rate, voice tone, etc.) in real time and evaluate their emotional state, such as stress and anxiety. At this time, device sensors detect changes in the user's emotions and send the data to the server.

[0334] Step 6:

[0335] Based on information from the emotion engine, the server dynamically readjusts the travel route and the way information is presented. If the server detects that the user is in a high-stress state, it generates guidance that takes into account calmer travel routes and points to avoid.

[0336] Step 7:

[0337] The analyzed information is sent to the device and presented to the user visually and audibly on the device. Here, the presentation method also reflects the feedback from the emotion engine. Specifically, calming colors and encouraging messages are displayed on the screen.

[0338] Step 8:

[0339] As the user begins their journey and heads towards their destination, the server continuously receives real-time operational information and equipment status, recalculating the route as needed and sending updated directions to the device. Throughout this process, feedback from the emotion engine is continuously utilized.

[0340] This helps reduce the psychological burden on users during their journey, enabling them to reach their destination safely and comfortably.

[0341] (Example 2)

[0342] 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".

[0343] While modern mobility systems are well-equipped to meet users' physical travel needs, they face the challenge of optimizing travel by taking into account users' emotional states. As a result, users may experience anxiety due to environmental changes or stress. There is a particular need for services that allow elderly people and people with disabilities to travel with peace of mind.

[0344] 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.

[0345] In this invention, the server includes an input means for receiving the starting position, ending position, and means of transportation from the user; an information gathering means for collecting information to eliminate obstacles from multiple transportation methods and facilities; an analysis means for analyzing the collected information and calculating the optimal travel route; and an emotion analysis means for detecting the user's emotional state from the user's physiological data and adjusting it according to the travel route selection. This enables safe and optimal travel while taking the user's emotional state into consideration.

[0346] "Input means" refers to a device or method for receiving information from the user regarding the starting position, ending position, and means of movement.

[0347] "Information gathering means" refers to a device or method for obtaining information from multiple transportation systems and facilities in order to eliminate obstacles.

[0348] "Analysis means" refers to a device or method for calculating the optimal travel route based on collected obstacle elimination information and user input information.

[0349] "Display means" refers to a device or method for presenting the calculated travel path to the user visually and audibly.

[0350] "Update means" refers to a device or method for updating a travel route using real-time information.

[0351] "Emotional analysis means" refers to a device or method for detecting an emotional state based on the user's physiological data and reflecting this in the selection of a travel route.

[0352] "Adjustment means" refers to a device or method for appropriately adjusting the displayed content according to the user's emotional state.

[0353] This invention provides a system that optimizes a user's movement according to their emotional state. The system begins with the user inputting their starting point, destination, and mode of transportation using a terminal. The terminal collects this data and transmits it to a server. The server uses advanced information gathering means to obtain real-time traffic and accessibility information from databases of external transportation companies and public facilities. Programming interfaces such as APIs may be used for this information gathering.

[0354] After collecting information, the server analyzes the data using a generative AI model to calculate the optimal travel path. This process considers not only user input but also physiological data and emotional state. To detect emotional state, biosensors are used to analyze the user's heart rate and voice tone. As a result, if the user is in a high-stress state, the server selects a more relaxing path.

[0355] The calculated travel route is transmitted from the server to the terminal. The terminal receives this information and presents it to the user in an easy-to-understand manner. Specifically, it provides information to the user using visual maps and voice guidance. The terminal also has a function that automatically adjusts the display's color tone and font size according to the user's emotional state. For example, if the user is feeling stressed, the display will be shown in calming colors to alleviate their tension.

[0356] For example, if a user inputs "Tell me the best route from Shibuya Station to Shinjuku Station," the system might analyze the prompt and recommend a quiet bus route. In this way, the system can respond to the user's different emotional states and provide the most appropriate travel method in real time.

[0357] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0358] Step 1:

[0359] The user uses a terminal to input their starting location, destination location, and preferred mode of transportation. The terminal converts this input data into an internal format and prepares it for transmission to the server. The input data includes geographical information and information about the selected mode of transportation.

[0360] Step 2:

[0361] The terminal sends the converted input data to the server. Upon receiving the data, the server stores it in a database for secure analysis. At this stage, a simple verification process is performed to confirm the integrity and accuracy of the data.

[0362] Step 3:

[0363] The server uses information gathering tools to access external transportation APIs and public facility databases to obtain real-time traffic and accessibility information. This data is an important factor related to user travel and is taken into consideration in the analysis.

[0364] Step 4:

[0365] The server uses a generative AI model to analyze collected real-time information and user input data. The analysis considers available route information, the status of transportation options, and accessibility. Furthermore, an emotion analysis system detects the user's emotional state and incorporates this into the route selection. At this point, an optimized route is calculated within the server.

[0366] Step 5:

[0367] The calculated travel route is transmitted from the server to the terminal. The terminal ensures the user understands the route by providing visual and auditory instructions. Specifically, map displays and audio guidance are used. If necessary, the terminal automatically adjusts the display's color tone and font size to improve user comfort.

[0368] Step 6:

[0369] If a user experiences stress or anxiety while traveling, the device's emotion engine detects this, and the server updates the route or messages accordingly. For example, it might send a voice message to encourage relaxation or suggest a safer route. This allows for a more personalized user experience.

[0370] (Application Example 2)

[0371] 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."

[0372] Conventional travel route optimization systems often fail to adequately consider the user's emotional state, making it difficult to alleviate the tension and anxiety they experience during travel. In particular, they lack the ability to provide flexible information tailored to the user's emotional state, resulting in users not feeling sufficiently secure during their journey.

[0373] 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.

[0374] In this invention, the server includes an input means for receiving the starting point, destination point, and means of transportation from the user; an information gathering means for collecting unobstructed information from multiple means of transportation and facilities; an analysis means for analyzing the collected unobstructed information and user input information to calculate the optimal travel route; a display means for presenting the calculated travel route to the user visually and audibly; an update means for updating the travel route based on real-time information; and an emotion analysis means for detecting the user's emotional state and adjusting the travel route and information presentation method. This enables detailed travel support tailored to the user's emotional state.

[0375] "Input means" refers to a device or method for receiving information from the user regarding the starting point, destination, and means of transportation.

[0376] "Information gathering means" refers to a device or method for collecting unobstructed information from multiple means of transportation or facilities.

[0377] "Analysis means" refers to a device or method for calculating the optimal travel path based on collected unobstructed information and user input information.

[0378] "Display means" refers to a device or method for visually and audibly presenting the calculated travel path to the user.

[0379] "Update means" refers to a device or method for updating a travel route based on real-time information.

[0380] "Emotional analysis means" refers to a device or method for detecting a user's emotional state and adjusting the movement path and information presentation method accordingly.

[0381] The system for carrying out the present invention takes into account the user's emotional state when the user is moving and provides the optimal travel route and information delivery method. This system includes various sensors, processing devices, and output devices.

[0382] As an initial setup, the server receives information from the user regarding the departure point, destination, and mode of transportation via an input device. This input device is implemented through mobile devices such as smartphones and tablets. Next, the server uses an information gathering device to collect unobstructed information from multiple modes of transportation and facilities. This utilizes transportation APIs and public information databases.

[0383] The obtained data is processed by an analysis system to calculate the optimal route for the user's desired travel. The analysis system uses data analysis software such as Python or R, and employs algorithms to evaluate and optimize various conditions. The calculation results are presented to the user via a display system. The display system provides information visually and audibly using a display screen or speech synthesis technology.

[0384] Furthermore, the emotion analysis system monitors the user's biometric data using sensors and detects their emotional state. This is done using heart rate monitors and speech recognition technology. This data is analyzed by a generative AI model to evaluate the user's stress and anxiety levels. Based on this evaluation, the emotion analysis system adjusts the movement path and information presentation method to provide the user with a sense of security.

[0385] For example, if a user feels anxious in a crowded train station, the emotion analysis system will detect this state, and the server will prioritize suggesting a route that passes through a quiet space where the user can relax. In this case, an example of a prompt message to the generating AI model might be, "The user is experiencing high stress. Please suggest a quiet and safe route."

[0386] The entire system is designed to provide flexible support tailored to the user's emotional state, ensuring they can travel with peace of mind.

[0387] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0388] Step 1:

[0389] The server receives information from the user via the terminal, including the starting point, destination, and mode of transportation. Based on the information collected through the input, it queries the database to determine the user's specific request. As output, the user's travel preferences are finalized as specific parameters.

[0390] Step 2:

[0391] The server uses information gathering methods to collect uninterrupted information from multiple modes of transportation and facilities. This includes processes for obtaining real-time data from transportation APIs and facility information. Inputs are database queries and API requests, and outputs are integrated transportation and facility information.

[0392] Step 3:

[0393] The server analyzes the collected data using analytical tools and calculates the optimal travel route for the user's request. It performs multivariate analysis through a Python algorithm to calculate the optimal route. The input is a vast amount of collected traffic data, and the output is the most efficient travel suggestion.

[0394] Step 4:

[0395] The terminal presents the calculated travel route to the user via a display. The terminal's display graphically shows the route information, and provides detailed explanations using audio guidance as needed. The input is the calculated travel route, and the output is visual and auditory information in a format understandable to the user.

[0396] Step 5:

[0397] The server uses an update mechanism to update the travel route in real time in response to changing conditions. It monitors changes in traffic information and recalculates the travel plan as needed. The input is newly acquired real-time traffic data, and the output is the updated travel route.

[0398] Step 6:

[0399] The server receives biometric data from sensors to analyze the user's emotional state using emotion analysis tools. Data such as heart rate monitor and voice tone are analyzed by a generating AI model. The input is real-time biometric data, and the output is an evaluation of the user's emotional state.

[0400] Step 7:

[0401] The server adjusts the navigation path and information presentation method based on the results of the emotion analysis. If stress is detected, it prepares a calming path and information presentation. Using a generative AI model, it creates specific prompt sentences and notifies the user of reassuring information. The input is the emotion analysis result, and the output is the adjusted information provided to the user.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] [Third Embodiment]

[0406] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0407] 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.

[0408] 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).

[0409] 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.

[0410] 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.

[0411] 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).

[0412] 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.

[0413] 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.

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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".

[0418] The system according to the present invention provides support to enable users to use specific travel routes with greater peace of mind. Users can start using the system by inputting their starting point, destination, and mode of transportation using a terminal. The terminal receives this information and transmits it to the server.

[0419] The server collects accessibility information from various transportation services and facilities based on the user information it receives. This includes information such as the presence or absence of elevators and steps at each station and facility. Furthermore, it can update information in real time, allowing for quick identification of maintenance or temporary service disruptions.

[0420] Based on the collected information, the server uses analytical tools to calculate the most efficient and safest travel route for the user. This analysis utilizes AI technology and takes into account the user's preferences (e.g., shortest travel time, elevator priority route selection, etc.). After the optimal travel route is calculated, the information is transmitted to the terminal and presented to the user along with map data and detailed travel guides.

[0421] While viewing this, users can follow the designated route, and if new information reaches the server in real time during their journey, the terminal immediately receives and displays the updated route to the user. This means that even if an elevator malfunctions or an emergency change in the route within the facility is required, alternative options are immediately presented, allowing users to proceed to their destination with peace of mind.

[0422] As a concrete example, when a user travels between stations using a wheelchair, they enter their departure and destination points on a terminal, and the server analyzes the optimal elevator locations and transfer routes for each station based on verified accessibility information. Even if the elevator the user was planning to use breaks down during their journey, the server quickly suggests an alternative route, allowing the user to reach their destination with ample time to spare.

[0423] Thus, the present invention provides effective support to enable users to use public transportation safely and smoothly.

[0424] The following describes the processing flow.

[0425] Step 1:

[0426] The user launches the application using a terminal. They enter their departure point, destination, and mode of transportation (e.g., wheelchair, stroller) into the terminal. They also set their travel preferences (e.g., shortest travel time, elevator priority).

[0427] Step 2:

[0428] The terminal sends the entered information to the server. Here, it verifies that the departure and destination specified by the user are unique, and prompts the user to enter any missing information.

[0429] Step 3:

[0430] The server accesses databases of various public transportation systems and related facilities to retrieve accessibility information. This information includes the location and status of elevators in stations and facilities, as well as the availability of accessibility features.

[0431] Step 4:

[0432] The server uses AI analysis to calculate the optimal travel route based on the acquired information and user input. The analysis generates multiple route options that reflect the user's preferences and the collected real-time situation data.

[0433] Step 5:

[0434] The server transmits the optimal travel route, derived from the analysis, to the terminal. The route information includes the location of elevators to be used and transfer routes, providing detailed directions.

[0435] Step 6:

[0436] The terminal displays the received route information to the user in map or list format. The user begins their journey based on the presented information, and the terminal continuously monitors their progress.

[0437] Step 7:

[0438] While in transit, the server continuously receives real-time operational information and equipment status updates from facilities and railway companies. If a significant change occurs (e.g., elevator malfunction), the server analyzes the situation in real time and calculates a new, optimal route.

[0439] Step 8:

[0440] The server immediately sends the recalculated route to the terminal. The terminal receives this information, updates the route, and notifies the user of the change. The user reviews the new route guidance and corrects the route as needed.

[0441] This allows users to flexibly respond to unexpected obstacles during their journey while safely and smoothly reaching their destination.

[0442] (Example 1)

[0443] 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."

[0444] One of the problems faced by people with mobility limitations when using public transportation is that insufficient accessibility information along the route prevents them from reaching their destination smoothly and safely. Furthermore, disruptions caused by equipment failures or delays in receiving necessary information also pose a problem.

[0445] 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.

[0446] In this invention, the server includes an information acquisition means for receiving the starting point, destination point, and method of travel from the user; an information aggregation means for collecting fluid obstacle information from multiple transportation methods and facilities; and an analysis means for analyzing the acquired obstacle information and user input information and calculating the optimal travel route using artificial intelligence technology. This enables the user to know the optimal travel route, which is updated in real time, allowing them to reach their destination safely and efficiently.

[0447] "Information acquisition means" refers to a device or method for receiving information from a user regarding the starting point, destination, and method of travel.

[0448] "Information aggregation means" refers to a device or method for collecting and aggregating fluid obstacle information from multiple transportation systems and facilities.

[0449] "Analysis means" refers to a device or method that analyzes acquired obstacle information and user input information and calculates the optimal travel route using artificial intelligence technology.

[0450] "Information display means" refers to a device or method for presenting a calculated travel route to the user visually or audibly.

[0451] A "dynamic update means" is a device or method for recalculating a travel route based on information that changes in real time.

[0452] This invention is a system that assists users with mobility limitations in traveling safely and efficiently using public transportation. The user begins by inputting their departure point, destination, and mode of transport using a terminal. The terminal has a dedicated application installed, allowing for easy input of this information through an intuitive interface.

[0453] The terminal transmits this information to the server via an information acquisition means through an internet connection. The server uses an information aggregation means to collect fluid accessibility information provided by multiple transportation systems and facilities. This information includes elements that change in real time, such as elevator status, presence or absence of steps, and ramp angles. In addition, IoT sensors and publicly available open data APIs are used to ensure the accuracy and timeliness of the information.

[0454] As an analysis method, the server utilizes artificial intelligence technology to calculate the optimal travel route based on the acquired data and the user's desired conditions. This involves using deep learning models and shortest path algorithms, and the analysis takes into account the user's priorities (e.g., speed of travel, ensuring safety).

[0455] The resulting travel route is transmitted to the user's terminal via an information display device. The user can refer to this and travel according to visual map data and audio guidance. Furthermore, through a dynamic update device, even if new information arrives on the server during travel, the plan can be immediately modified and the latest route guidance can be provided.

[0456] For example, when a user travels between stations using a wheelchair, they input their departure and destination points, and the server analyzes the appropriate route based on accessibility information. Dynamic information is reflected, and even if the elevator the user was planning to use malfunctions, an alternative route is immediately suggested, allowing the user to continue their journey with peace of mind.

[0457] An example of a prompt for a generative AI model is: "When a user is traveling from one station to another using a wheelchair, please suggest the optimal route considering accessibility information."

[0458] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0459] Step 1:

[0460] The user enters their starting point, destination, and mode of transport using a terminal. This data is easily entered using a form in a dedicated application. This information is structured in JSON format and prepared for transmission to the server.

[0461] Step 2:

[0462] The terminal sends the information received from the user to the server. Since this data is transmitted over the internet, the HTTP protocol is typically used. The output is the server receiving the data, indicating that the user's request was successfully delivered to the server.

[0463] Step 3:

[0464] The server uses information aggregation tools to collect real-time accessibility information from various transportation services and facilities. It retrieves information from various data sources using APIs and stores this data in a centralized database. This ensures that elevator operating status and facility accessibility information are always up-to-date. The output is a set of transportation information relevant to the user.

[0465] Step 4:

[0466] The server uses analytical tools to calculate the optimal travel route using AI technology, based on collected accessibility information and user input. The calculation employs shortest path algorithms and machine learning models, which are customized to meet user-specified conditions. The output is optimized travel route data.

[0467] Step 5:

[0468] The server sends the calculated optimal travel route to the terminal. The terminal visually displays this information to the user, drawing the route on a map. Furthermore, it can provide the user with travel instructions accompanied by voice guidance. The output is the route displayed on the user's terminal.

[0469] Step 6:

[0470] During transit, the terminal communicates with the server in real time, updating the screen display whenever new information is received. The server provides the terminal with a recalculated travel route using the latest accessibility information, and presents a new route that takes unexpected obstacles into account. The final output is the presentation of the updated travel route.

[0471] (Application Example 1)

[0472] 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."

[0473] In modern cities, various obstacles and fluctuations in public transportation make it difficult for users to travel smoothly and safely. In particular, when using transportation methods requiring accessibility, optimal route information is often unavailable at the time of travel. As a result, users often experience anxiety about their journey due to unexpected delays and the need for detours. There is a need to provide systems that solve these problems and enable users to reach their destinations efficiently and safely.

[0474] 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.

[0475] In this invention, the server includes data receiving means for receiving the starting point, destination, and means of transportation from the user; information acquisition means for collecting information related to obstacle avoidance from multiple means of transportation and facilities; and calculation means for analyzing the collected obstacle avoidance information and user input information to calculate an efficient travel route. This makes it possible to provide the optimal travel route for the user while responding to unforeseen circumstances in real time.

[0476] A "user" refers to a person who uses a travel route system to receive directions to their destination.

[0477] "Starting point" refers to information about the point from which the user will depart from their current location.

[0478] "Destination" refers to the final location that the user wants to achieve.

[0479] "Transportation" refers to information about the means of transport that a user uses to reach their destination.

[0480] "Data receiving means" refers to the means by which the system receives information about the starting point, destination, and means of transportation entered by the user.

[0481] "Transportation" refers to means that enable geographical movement, and includes a variety of methods of travel, such as trains, buses, and wheelchairs.

[0482] "Facilities" refers to public or private buildings or places that users may potentially use.

[0483] "Information related to obstacle avoidance" includes information about obstacles or malfunctions that may hinder the user's movement.

[0484] "Information acquisition means" refers to means equipped with the function of collecting relevant information in real time from transportation methods and facilities.

[0485] "Analysis" refers to data processing used to derive the optimal travel route based on collected information.

[0486] "Calculation means" refers to a device or program that performs the calculations necessary to determine the best travel path from multiple input pieces of information.

[0487] A "visualization means" is a means that has a display function to present the calculated travel route to the user in an easy-to-understand manner.

[0488] "Information update means" refers to means for updating information in real time and recalculating existing travel routes as needed.

[0489] An "optimization method" is a means of adjusting the travel route to be more efficient or safer in response to changes in circumstances or user requests.

[0490] The system based on this invention is implemented with three main components: a user, a terminal, and a server. The user uses a mobile device or wearable device as a terminal and inputs the starting point, destination, and mode of transportation to be used through the terminal. This information is aggregated by the terminal's data receiving means and transmitted to the server.

[0491] The server operates using a backend system built with Node.js or Python, processing information received from users. The server collects information on transportation options and obstacle avoidance information from facilities via APIs. This allows for real-time acquisition of traffic conditions and accessibility information. After information collection, the server's computing power uses AI analysis technologies such as TensorFlow and PyTorch to algorithmically calculate the optimal travel route for the user.

[0492] The calculated travel route is transmitted to the user's device through a visualization mechanism. Applications developed using programming languages ​​such as React Native, Swift, and Kotlin are used, allowing users to visually confirm the route through an intuitive interface. Furthermore, an information update mechanism continuously updates the travel route with the latest information collected during the journey, enabling immediate response to unforeseen circumstances.

[0493] A concrete example of its use is when a user is moving around a large commercial facility and is offered the optimal route to efficiently visit each store using the disabled-accessible passageway. In this scenario, the server analyzes the usage status and congestion level of elevators within the facility in real time and provides the user with the shortest and most comfortable travel route.

[0494] An example of a prompt message would be, "Please provide barrier-free navigation that guides wheelchair users to the optimal route from Shinjuku Station to Shibuya Station in a safe and convenient manner." This specific input would then trigger an AI-powered optimized route search.

[0495] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0496] Step 1:

[0497] The user uses a device to input their starting point, destination, and mode of transportation. This input is received by a data receiving device and is the data input sent to the server. The device uses location services to obtain and transmit accurate geographical data.

[0498] Step 2:

[0499] Based on the received information, the server collects real-time obstacle avoidance information from transportation methods and facilities via APIs. Input includes the user's location and desired conditions, and accordingly, relevant accessibility information and transportation data are retrieved from internet resources. Data acquisition and initial processing take place at this stage.

[0500] Step 3:

[0501] The server's computing power uses collected information to calculate the optimal travel path. By combining input location information and obstacle avoidance information, and utilizing AI analysis techniques (TensorFlow and PyTorch), it calculates the travel path that best suits the user's preferences. This outputs data that allows the user to reach their destination efficiently.

[0502] Step 4:

[0503] The server sends the calculated travel route to the terminal. The output route information is presented to the user through the terminal's visualization means. The terminal visually displays map data and detailed travel guides through the application, and the user begins their journey based on this information.

[0504] Step 5:

[0505] During transit, the server collects new information in real time and recalculates the travel route as needed. This includes the latest traffic information and accessibility status, which is used to re-optimize the current route. As a result, any potential changes are immediately transmitted to the user's terminal.

[0506] Step 6:

[0507] The device receives updated route information and presents it to the user quickly. This received data is reflected in the application's UI, allowing the user to smoothly continue their travel planning in accordance with changing circumstances. In other words, the process of continuously providing optimal route guidance in real time is completed.

[0508] 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.

[0509] The system according to the present invention integrates a series of functions to support user mobility, and is particularly aimed at optimizing mobility by taking into account the user's emotional state. This system begins by receiving information from the user via a terminal regarding the origin, destination, and mode of transportation. The user's input information is transmitted from the terminal to a server, which collects accessibility information from transportation companies and facilities.

[0510] The collected information is processed by an analysis system on the server to calculate the optimal travel route. The analysis includes multiple options that take real-time information and user preferences into account. Furthermore, the system is equipped with an emotion engine that can detect the user's stress and tension levels in real time. This emotion engine analyzes emotions from the user's voice tone and biometric information (e.g., heart rate and skin resistance) and adjusts the selection of the travel route and the method of information presentation accordingly.

[0511] The route calculated by the server is sent to the terminal and presented to the user visually and audibly. The terminal adjusts the visual presentation of the guidance information in response to the user's emotional state (e.g., displaying in calming colors or adjusting font size). If the user feels stressed or anxious during the journey, the emotion engine detects this and provides a response message or guidance to help them relax. For example, if the system detects user stress, a message such as "You're on track. Take your time and don't rush" will be displayed.

[0512] For example, if a user feels anxious while traveling through a crowded station, the emotion engine detects this state and suggests escape routes or quiet waiting areas along the way to promote calmness. In addition, when selecting a travel route, routes that prioritize comfort are given priority.

[0513] In this way, the entire system is designed to provide enhanced support, a sense of security, and safety, ensuring that users can travel comfortably.

[0514] The following describes the processing flow.

[0515] Step 1:

[0516] The user launches the application using the terminal and enters their departure point, destination, and mode of transportation (e.g., wheelchair, stroller). The terminal assists in easily entering the necessary information through its user interface.

[0517] Step 2:

[0518] Once input is complete, the terminal sends the user's information to the server. The server receives this information and begins preparing for the next processing step.

[0519] Step 3:

[0520] The server collects accessibility-related data from various transportation services and facilities. This includes information such as elevator locations, availability, and the status of accessibility features within facilities. The server then systematically organizes this information.

[0521] Step 4:

[0522] Subsequently, the server uses AI analysis tools to analyze the collected information and user input to calculate the most optimal travel route. The analysis takes into account the user's preferences (shortest travel time, elevator use, etc.), real-time operational data, and equipment usage status.

[0523] Step 5:

[0524] The emotion engine is activated to collect the user's biometric information (e.g., heart rate, voice tone, etc.) in real time and evaluate their emotional state, such as stress and anxiety. At this time, device sensors detect changes in the user's emotions and send the data to the server.

[0525] Step 6:

[0526] Based on information from the emotion engine, the server dynamically readjusts the travel route and the way information is presented. If the server detects that the user is in a high-stress state, it generates guidance that takes into account calmer travel routes and points to avoid.

[0527] Step 7:

[0528] The analyzed information is sent to the device and presented to the user visually and audibly on the device. Here, the presentation method also reflects the feedback from the emotion engine. Specifically, calming colors and encouraging messages are displayed on the screen.

[0529] Step 8:

[0530] As the user begins their journey and heads towards their destination, the server continuously receives real-time operational information and equipment status, recalculating the route as needed and sending updated directions to the device. Throughout this process, feedback from the emotion engine is continuously utilized.

[0531] This helps reduce the psychological burden on users during their journey, enabling them to reach their destination safely and comfortably.

[0532] (Example 2)

[0533] 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."

[0534] While modern mobility systems are well-equipped to meet users' physical travel needs, they face the challenge of optimizing travel by taking into account users' emotional states. As a result, users may experience anxiety due to environmental changes or stress. There is a particular need for services that allow elderly people and people with disabilities to travel with peace of mind.

[0535] 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.

[0536] In this invention, the server includes an input means for receiving the starting position, ending position, and means of transportation from the user; an information gathering means for collecting information to eliminate obstacles from multiple transportation methods and facilities; an analysis means for analyzing the collected information and calculating the optimal travel route; and an emotion analysis means for detecting the user's emotional state from the user's physiological data and adjusting it according to the travel route selection. This enables safe and optimal travel while taking the user's emotional state into consideration.

[0537] "Input means" refers to a device or method for receiving information from the user regarding the starting position, ending position, and means of movement.

[0538] "Information gathering means" refers to a device or method for obtaining information from multiple transportation systems and facilities in order to eliminate obstacles.

[0539] "Analysis means" refers to a device or method for calculating the optimal travel route based on collected obstacle elimination information and user input information.

[0540] "Display means" refers to a device or method for presenting the calculated travel path to the user visually and audibly.

[0541] "Update means" refers to a device or method for updating a travel route using real-time information.

[0542] "Emotional analysis means" refers to a device or method for detecting an emotional state based on the user's physiological data and reflecting this in the selection of a travel route.

[0543] "Adjustment means" refers to a device or method for appropriately adjusting the displayed content according to the user's emotional state.

[0544] This invention provides a system that optimizes a user's movement according to their emotional state. The system begins with the user inputting their starting point, destination, and mode of transportation using a terminal. The terminal collects this data and transmits it to a server. The server uses advanced information gathering means to obtain real-time traffic and accessibility information from databases of external transportation companies and public facilities. Programming interfaces such as APIs may be used for this information gathering.

[0545] After collecting information, the server analyzes the data using a generative AI model to calculate the optimal travel path. This process considers not only user input but also physiological data and emotional state. To detect emotional state, biosensors are used to analyze the user's heart rate and voice tone. As a result, if the user is in a high-stress state, the server selects a more relaxing path.

[0546] The calculated travel route is transmitted from the server to the terminal. The terminal receives this information and presents it to the user in an easy-to-understand manner. Specifically, it provides information to the user using visual maps and voice guidance. The terminal also has a function that automatically adjusts the display's color tone and font size according to the user's emotional state. For example, if the user is feeling stressed, the display will be shown in calming colors to alleviate their tension.

[0547] For example, if a user inputs "Tell me the best route from Shibuya Station to Shinjuku Station," the system might analyze the prompt and recommend a quiet bus route. In this way, the system can respond to the user's different emotional states and provide the most appropriate travel method in real time.

[0548] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0549] Step 1:

[0550] The user uses a terminal to input their starting location, destination location, and preferred mode of transportation. The terminal converts this input data into an internal format and prepares it for transmission to the server. The input data includes geographical information and information about the selected mode of transportation.

[0551] Step 2:

[0552] The terminal sends the converted input data to the server. Upon receiving the data, the server stores it in a database for secure analysis. At this stage, a simple verification process is performed to confirm the integrity and accuracy of the data.

[0553] Step 3:

[0554] The server uses information gathering tools to access external transportation APIs and public facility databases to obtain real-time traffic and accessibility information. This data is an important factor related to user travel and is taken into consideration in the analysis.

[0555] Step 4:

[0556] The server uses a generative AI model to analyze collected real-time information and user input data. The analysis considers available route information, the status of transportation options, and accessibility. Furthermore, an emotion analysis system detects the user's emotional state and incorporates this into the route selection. At this point, an optimized route is calculated within the server.

[0557] Step 5:

[0558] The calculated travel route is transmitted from the server to the terminal. The terminal ensures the user understands the route by providing visual and auditory instructions. Specifically, map displays and audio guidance are used. If necessary, the terminal automatically adjusts the display's color tone and font size to improve user comfort.

[0559] Step 6:

[0560] If a user experiences stress or anxiety while traveling, the device's emotion engine detects this, and the server updates the route or messages accordingly. For example, it might send a voice message to encourage relaxation or suggest a safer route. This allows for a more personalized user experience.

[0561] (Application Example 2)

[0562] 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."

[0563] Conventional travel route optimization systems often fail to adequately consider the user's emotional state, making it difficult to alleviate the tension and anxiety they experience during travel. In particular, they lack the ability to provide flexible information tailored to the user's emotional state, resulting in users not feeling sufficiently secure during their journey.

[0564] 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.

[0565] In this invention, the server includes an input means for receiving the starting point, destination point, and means of transportation from the user; an information gathering means for collecting unobstructed information from multiple means of transportation and facilities; an analysis means for analyzing the collected unobstructed information and user input information to calculate the optimal travel route; a display means for presenting the calculated travel route to the user visually and audibly; an update means for updating the travel route based on real-time information; and an emotion analysis means for detecting the user's emotional state and adjusting the travel route and information presentation method. This enables detailed travel support tailored to the user's emotional state.

[0566] "Input means" refers to a device or method for receiving information from the user regarding the starting point, destination, and means of transportation.

[0567] "Information gathering means" refers to a device or method for collecting unobstructed information from multiple means of transportation or facilities.

[0568] "Analysis means" refers to a device or method for calculating the optimal travel path based on collected unobstructed information and user input information.

[0569] "Display means" refers to a device or method for visually and audibly presenting the calculated travel path to the user.

[0570] "Update means" refers to a device or method for updating a travel route based on real-time information.

[0571] "Emotional analysis means" refers to a device or method for detecting a user's emotional state and adjusting the movement path and information presentation method accordingly.

[0572] The system for carrying out the present invention takes into account the user's emotional state when the user is moving and provides the optimal travel route and information delivery method. This system includes various sensors, processing devices, and output devices.

[0573] As an initial setup, the server receives information from the user regarding the departure point, destination, and mode of transportation via an input device. This input device is implemented through mobile devices such as smartphones and tablets. Next, the server uses an information gathering device to collect unobstructed information from multiple modes of transportation and facilities. This utilizes transportation APIs and public information databases.

[0574] The obtained data is processed by an analysis system to calculate the optimal route for the user's desired travel. The analysis system uses data analysis software such as Python or R, and employs algorithms to evaluate and optimize various conditions. The calculation results are presented to the user via a display system. The display system provides information visually and audibly using a display screen or speech synthesis technology.

[0575] Furthermore, the emotion analysis system monitors the user's biometric data using sensors and detects their emotional state. This is done using heart rate monitors and speech recognition technology. This data is analyzed by a generative AI model to evaluate the user's stress and anxiety levels. Based on this evaluation, the emotion analysis system adjusts the movement path and information presentation method to provide the user with a sense of security.

[0576] For example, if a user feels anxious in a crowded train station, the emotion analysis system will detect this state, and the server will prioritize suggesting a route that passes through a quiet space where the user can relax. In this case, an example of a prompt message to the generating AI model might be, "The user is experiencing high stress. Please suggest a quiet and safe route."

[0577] The entire system is designed to provide flexible support tailored to the user's emotional state, ensuring they can travel with peace of mind.

[0578] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0579] Step 1:

[0580] The server receives information from the user via the terminal, including the starting point, destination, and mode of transportation. Based on the information collected through the input, it queries the database to determine the user's specific request. As output, the user's travel preferences are finalized as specific parameters.

[0581] Step 2:

[0582] The server uses information gathering methods to collect uninterrupted information from multiple modes of transportation and facilities. This includes processes for obtaining real-time data from transportation APIs and facility information. Inputs are database queries and API requests, and outputs are integrated transportation and facility information.

[0583] Step 3:

[0584] The server analyzes the collected data using analytical tools and calculates the optimal travel route for the user's request. It performs multivariate analysis through a Python algorithm to calculate the optimal route. The input is a vast amount of collected traffic data, and the output is the most efficient travel suggestion.

[0585] Step 4:

[0586] The terminal presents the calculated travel route to the user via a display. The terminal's display graphically shows the route information, and provides detailed explanations using audio guidance as needed. The input is the calculated travel route, and the output is visual and auditory information in a format understandable to the user.

[0587] Step 5:

[0588] The server uses an update mechanism to update the travel route in real time in response to changing conditions. It monitors changes in traffic information and recalculates the travel plan as needed. The input is newly acquired real-time traffic data, and the output is the updated travel route.

[0589] Step 6:

[0590] The server receives biometric data from sensors to analyze the user's emotional state using emotion analysis tools. Data such as heart rate monitor and voice tone are analyzed by a generating AI model. The input is real-time biometric data, and the output is an evaluation of the user's emotional state.

[0591] Step 7:

[0592] The server adjusts the navigation path and information presentation method based on the results of the emotion analysis. If stress is detected, it prepares a calming path and information presentation. Using a generative AI model, it creates specific prompt sentences and notifies the user of reassuring information. The input is the emotion analysis result, and the output is the adjusted information provided to the user.

[0593] 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.

[0594] 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.

[0595] 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.

[0596] [Fourth Embodiment]

[0597] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0598] 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.

[0599] 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).

[0600] 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.

[0601] 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.

[0602] 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).

[0603] 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.

[0604] 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.

[0605] 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.

[0606] 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.

[0607] 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.

[0608] 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.

[0609] 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".

[0610] The system according to the present invention provides support to enable users to use specific travel routes with greater peace of mind. Users can start using the system by inputting their starting point, destination, and mode of transportation using a terminal. The terminal receives this information and transmits it to the server.

[0611] The server collects accessibility information from various transportation services and facilities based on the user information it receives. This includes information such as the presence or absence of elevators and steps at each station and facility. Furthermore, it can update information in real time, allowing for quick identification of maintenance or temporary service disruptions.

[0612] Based on the collected information, the server uses analytical tools to calculate the most efficient and safest travel route for the user. This analysis utilizes AI technology and takes into account the user's preferences (e.g., shortest travel time, elevator priority route selection, etc.). After the optimal travel route is calculated, the information is transmitted to the terminal and presented to the user along with map data and detailed travel guides.

[0613] While viewing this, users can follow the designated route, and if new information reaches the server in real time during their journey, the terminal immediately receives and displays the updated route to the user. This means that even if an elevator malfunctions or an emergency change in the route within the facility is required, alternative options are immediately presented, allowing users to proceed to their destination with peace of mind.

[0614] As a concrete example, when a user travels between stations using a wheelchair, they enter their departure and destination points on a terminal, and the server analyzes the optimal elevator locations and transfer routes for each station based on verified accessibility information. Even if the elevator the user was planning to use breaks down during their journey, the server quickly suggests an alternative route, allowing the user to reach their destination with ample time to spare.

[0615] Thus, the present invention provides effective support to enable users to use public transportation safely and smoothly.

[0616] The following describes the processing flow.

[0617] Step 1:

[0618] The user launches the application using a terminal. They enter their departure point, destination, and mode of transportation (e.g., wheelchair, stroller) into the terminal. They also set their travel preferences (e.g., shortest travel time, elevator priority).

[0619] Step 2:

[0620] The terminal sends the entered information to the server. Here, it verifies that the departure and destination specified by the user are unique, and prompts the user to enter any missing information.

[0621] Step 3:

[0622] The server accesses databases of various public transportation systems and related facilities to retrieve accessibility information. This information includes the location and status of elevators in stations and facilities, as well as the availability of accessibility features.

[0623] Step 4:

[0624] The server uses AI analysis to calculate the optimal travel route based on the acquired information and user input. The analysis generates multiple route options that reflect the user's preferences and the collected real-time situation data.

[0625] Step 5:

[0626] The server transmits the optimal travel route, derived from the analysis, to the terminal. The route information includes the location of elevators to be used and transfer routes, providing detailed directions.

[0627] Step 6:

[0628] The terminal displays the received route information to the user in map or list format. The user begins their journey based on the presented information, and the terminal continuously monitors their progress.

[0629] Step 7:

[0630] While in transit, the server continuously receives real-time operational information and equipment status updates from facilities and railway companies. If a significant change occurs (e.g., elevator malfunction), the server analyzes the situation in real time and calculates a new, optimal route.

[0631] Step 8:

[0632] The server immediately sends the recalculated route to the terminal. The terminal receives this information, updates the route, and notifies the user of the change. The user reviews the new route guidance and corrects the route as needed.

[0633] This allows users to flexibly respond to unexpected obstacles during their journey while safely and smoothly reaching their destination.

[0634] (Example 1)

[0635] 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".

[0636] One of the problems faced by people with mobility limitations when using public transportation is that insufficient accessibility information along the route prevents them from reaching their destination smoothly and safely. Furthermore, disruptions caused by equipment failures or delays in receiving necessary information also pose a problem.

[0637] 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.

[0638] In this invention, the server includes an information acquisition means for receiving the starting point, destination point, and method of travel from the user; an information aggregation means for collecting fluid obstacle information from multiple transportation methods and facilities; and an analysis means for analyzing the acquired obstacle information and user input information and calculating the optimal travel route using artificial intelligence technology. This enables the user to know the optimal travel route, which is updated in real time, allowing them to reach their destination safely and efficiently.

[0639] "Information acquisition means" refers to a device or method for receiving information from a user regarding the starting point, destination, and method of travel.

[0640] "Information aggregation means" refers to a device or method for collecting and aggregating fluid obstacle information from multiple transportation systems and facilities.

[0641] "Analysis means" refers to a device or method that analyzes acquired obstacle information and user input information and calculates the optimal travel route using artificial intelligence technology.

[0642] "Information display means" refers to a device or method for presenting a calculated travel route to the user visually or audibly.

[0643] A "dynamic update means" is a device or method for recalculating a travel route based on information that changes in real time.

[0644] This invention is a system that assists users with mobility limitations in traveling safely and efficiently using public transportation. The user begins by inputting their departure point, destination, and mode of transport using a terminal. The terminal has a dedicated application installed, allowing for easy input of this information through an intuitive interface.

[0645] The terminal transmits this information to the server via an information acquisition means through an internet connection. The server uses an information aggregation means to collect fluid accessibility information provided by multiple transportation systems and facilities. This information includes elements that change in real time, such as elevator status, presence or absence of steps, and ramp angles. In addition, IoT sensors and publicly available open data APIs are used to ensure the accuracy and timeliness of the information.

[0646] As an analysis method, the server utilizes artificial intelligence technology to calculate the optimal travel route based on the acquired data and the user's desired conditions. This involves using deep learning models and shortest path algorithms, and the analysis takes into account the user's priorities (e.g., speed of travel, ensuring safety).

[0647] The resulting travel route is transmitted to the user's terminal via an information display device. The user can refer to this and travel according to visual map data and audio guidance. Furthermore, through a dynamic update device, even if new information arrives on the server during travel, the plan can be immediately modified and the latest route guidance can be provided.

[0648] For example, when a user travels between stations using a wheelchair, they input their departure and destination points, and the server analyzes the appropriate route based on accessibility information. Dynamic information is reflected, and even if the elevator the user was planning to use malfunctions, an alternative route is immediately suggested, allowing the user to continue their journey with peace of mind.

[0649] An example of a prompt for a generative AI model is: "When a user is traveling from one station to another using a wheelchair, please suggest the optimal route considering accessibility information."

[0650] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0651] Step 1:

[0652] The user enters their starting point, destination, and mode of transport using a terminal. This data is easily entered using a form in a dedicated application. This information is structured in JSON format and prepared for transmission to the server.

[0653] Step 2:

[0654] The terminal sends the information received from the user to the server. Since this data is transmitted over the internet, the HTTP protocol is typically used. The output is the server receiving the data, indicating that the user's request was successfully delivered to the server.

[0655] Step 3:

[0656] The server uses information aggregation tools to collect real-time accessibility information from various transportation services and facilities. It retrieves information from various data sources using APIs and stores this data in a centralized database. This ensures that elevator operating status and facility accessibility information are always up-to-date. The output is a set of transportation information relevant to the user.

[0657] Step 4:

[0658] The server uses analytical tools to calculate the optimal travel route using AI technology, based on collected accessibility information and user input. The calculation employs shortest path algorithms and machine learning models, which are customized to meet user-specified conditions. The output is optimized travel route data.

[0659] Step 5:

[0660] The server sends the calculated optimal travel route to the terminal. The terminal visually displays this information to the user, drawing the route on a map. Furthermore, it can provide the user with travel instructions accompanied by voice guidance. The output is the route displayed on the user's terminal.

[0661] Step 6:

[0662] During transit, the terminal communicates with the server in real time, updating the screen display whenever new information is received. The server provides the terminal with a recalculated travel route using the latest accessibility information, and presents a new route that takes unexpected obstacles into account. The final output is the presentation of the updated travel route.

[0663] (Application Example 1)

[0664] 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".

[0665] In modern cities, various obstacles and fluctuations in public transportation make it difficult for users to travel smoothly and safely. In particular, when using transportation methods requiring accessibility, optimal route information is often unavailable at the time of travel. As a result, users often experience anxiety about their journey due to unexpected delays and the need for detours. There is a need to provide systems that solve these problems and enable users to reach their destinations efficiently and safely.

[0666] 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.

[0667] In this invention, the server includes data receiving means for receiving the starting point, destination, and means of transportation from the user; information acquisition means for collecting information related to obstacle avoidance from multiple means of transportation and facilities; and calculation means for analyzing the collected obstacle avoidance information and user input information to calculate an efficient travel route. This makes it possible to provide the optimal travel route for the user while responding to unforeseen circumstances in real time.

[0668] A "user" refers to a person who uses a travel route system to receive directions to their destination.

[0669] "Starting point" refers to information about the point from which the user will depart from their current location.

[0670] "Destination" refers to the final location that the user wants to achieve.

[0671] "Transportation" refers to information about the means of transport that a user uses to reach their destination.

[0672] "Data receiving means" refers to the means by which the system receives information about the starting point, destination, and means of transportation entered by the user.

[0673] "Transportation" refers to means that enable geographical movement, and includes a variety of methods of travel, such as trains, buses, and wheelchairs.

[0674] "Facilities" refers to public or private buildings or places that users may potentially use.

[0675] "Information related to obstacle avoidance" includes information about obstacles or malfunctions that may hinder the user's movement.

[0676] "Information acquisition means" refers to means equipped with the function of collecting relevant information in real time from transportation methods and facilities.

[0677] "Analysis" refers to data processing used to derive the optimal travel route based on collected information.

[0678] "Calculation means" refers to a device or program that performs the calculations necessary to determine the best travel path from multiple input pieces of information.

[0679] A "visualization means" is a means that has a display function to present the calculated travel route to the user in an easy-to-understand manner.

[0680] "Information update means" refers to means for updating information in real time and recalculating existing travel routes as needed.

[0681] An "optimization method" is a means of adjusting the travel route to be more efficient or safer in response to changes in circumstances or user requests.

[0682] The system based on this invention is implemented with three main components: a user, a terminal, and a server. The user uses a mobile device or wearable device as a terminal and inputs the starting point, destination, and mode of transportation to be used through the terminal. This information is aggregated by the terminal's data receiving means and transmitted to the server.

[0683] The server operates using a backend system built with Node.js or Python, processing information received from users. The server collects information on transportation options and obstacle avoidance information from facilities via APIs. This allows for real-time acquisition of traffic conditions and accessibility information. After information collection, the server's computing power uses AI analysis technologies such as TensorFlow and PyTorch to algorithmically calculate the optimal travel route for the user.

[0684] The calculated travel route is transmitted to the user's device through a visualization mechanism. Applications developed using programming languages ​​such as React Native, Swift, and Kotlin are used, allowing users to visually confirm the route through an intuitive interface. Furthermore, an information update mechanism continuously updates the travel route with the latest information collected during the journey, enabling immediate response to unforeseen circumstances.

[0685] A concrete example of its use is when a user is moving around a large commercial facility and is offered the optimal route to efficiently visit each store using the disabled-accessible passageway. In this scenario, the server analyzes the usage status and congestion level of elevators within the facility in real time and provides the user with the shortest and most comfortable travel route.

[0686] An example of a prompt message would be, "Please provide barrier-free navigation that guides wheelchair users to the optimal route from Shinjuku Station to Shibuya Station in a safe and convenient manner." This specific input would then trigger an AI-powered optimized route search.

[0687] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0688] Step 1:

[0689] The user uses a device to input their starting point, destination, and mode of transportation. This input is received by a data receiving device and is the data input sent to the server. The device uses location services to obtain and transmit accurate geographical data.

[0690] Step 2:

[0691] Based on the received information, the server collects real-time obstacle avoidance information from transportation methods and facilities via APIs. Input includes the user's location and desired conditions, and accordingly, relevant accessibility information and transportation data are retrieved from internet resources. Data acquisition and initial processing take place at this stage.

[0692] Step 3:

[0693] The server's computing power uses collected information to calculate the optimal travel path. By combining input location information and obstacle avoidance information, and utilizing AI analysis techniques (TensorFlow and PyTorch), it calculates the travel path that best suits the user's preferences. This outputs data that allows the user to reach their destination efficiently.

[0694] Step 4:

[0695] The server sends the calculated travel route to the terminal. The output route information is presented to the user through the terminal's visualization means. The terminal visually displays map data and detailed travel guides through the application, and the user begins their journey based on this information.

[0696] Step 5:

[0697] During transit, the server collects new information in real time and recalculates the travel route as needed. This includes the latest traffic information and accessibility status, which is used to re-optimize the current route. As a result, any potential changes are immediately transmitted to the user's terminal.

[0698] Step 6:

[0699] The device receives updated route information and presents it to the user quickly. This received data is reflected in the application's UI, allowing the user to smoothly continue their travel planning in accordance with changing circumstances. In other words, the process of continuously providing optimal route guidance in real time is completed.

[0700] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0701] The system according to the present invention integrates a series of functions to support user mobility, and is particularly aimed at optimizing mobility by taking into account the user's emotional state. This system begins by receiving information from the user via a terminal regarding the origin, destination, and mode of transportation. The user's input information is transmitted from the terminal to a server, which collects accessibility information from transportation companies and facilities.

[0702] The collected information is processed by an analysis system on the server to calculate the optimal travel route. The analysis includes multiple options that take real-time information and user preferences into account. Furthermore, the system is equipped with an emotion engine that can detect the user's stress and tension levels in real time. This emotion engine analyzes emotions from the user's voice tone and biometric information (e.g., heart rate and skin resistance) and adjusts the selection of the travel route and the method of information presentation accordingly.

[0703] The route calculated by the server is sent to the terminal and presented to the user visually and audibly. The terminal adjusts the visual presentation of the guidance information in response to the user's emotional state (e.g., displaying in calming colors or adjusting font size). If the user feels stressed or anxious during the journey, the emotion engine detects this and provides a response message or guidance to help them relax. For example, if the system detects user stress, a message such as "You're on track. Take your time and don't rush" will be displayed.

[0704] For example, if a user feels anxious while traveling through a crowded station, the emotion engine detects this state and suggests escape routes or quiet waiting areas along the way to promote calmness. In addition, when selecting a travel route, routes that prioritize comfort are given priority.

[0705] In this way, the entire system is designed to provide enhanced support, a sense of security, and safety, ensuring that users can travel comfortably.

[0706] The following describes the processing flow.

[0707] Step 1:

[0708] The user launches the application using the terminal and enters their departure point, destination, and mode of transportation (e.g., wheelchair, stroller). The terminal assists in easily entering the necessary information through its user interface.

[0709] Step 2:

[0710] Once input is complete, the terminal sends the user's information to the server. The server receives this information and begins preparing for the next processing step.

[0711] Step 3:

[0712] The server collects accessibility-related data from various transportation services and facilities. This includes information such as elevator locations, availability, and the status of accessibility features within facilities. The server then systematically organizes this information.

[0713] Step 4:

[0714] Subsequently, the server uses AI analysis tools to analyze the collected information and user input to calculate the most optimal travel route. The analysis takes into account the user's preferences (shortest travel time, elevator use, etc.), real-time operational data, and equipment usage status.

[0715] Step 5:

[0716] The emotion engine is activated to collect the user's biometric information (e.g., heart rate, voice tone, etc.) in real time and evaluate their emotional state, such as stress and anxiety. At this time, device sensors detect changes in the user's emotions and send the data to the server.

[0717] Step 6:

[0718] Based on information from the emotion engine, the server dynamically readjusts the travel route and the way information is presented. If the server detects that the user is in a high-stress state, it generates guidance that takes into account calmer travel routes and points to avoid.

[0719] Step 7:

[0720] The analyzed information is sent to the device and presented to the user visually and audibly on the device. Here, the presentation method also reflects the feedback from the emotion engine. Specifically, calming colors and encouraging messages are displayed on the screen.

[0721] Step 8:

[0722] As the user begins their journey and heads towards their destination, the server continuously receives real-time operational information and equipment status, recalculating the route as needed and sending updated directions to the device. Throughout this process, feedback from the emotion engine is continuously utilized.

[0723] This helps reduce the psychological burden on users during their journey, enabling them to reach their destination safely and comfortably.

[0724] (Example 2)

[0725] 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".

[0726] While modern mobility systems are well-equipped to meet users' physical travel needs, they face the challenge of optimizing travel by taking into account users' emotional states. As a result, users may experience anxiety due to environmental changes or stress. There is a particular need for services that allow elderly people and people with disabilities to travel with peace of mind.

[0727] 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.

[0728] In this invention, the server includes an input means for receiving the starting position, ending position, and means of transportation from the user; an information gathering means for collecting information to eliminate obstacles from multiple transportation methods and facilities; an analysis means for analyzing the collected information and calculating the optimal travel route; and an emotion analysis means for detecting the user's emotional state from the user's physiological data and adjusting it according to the travel route selection. This enables safe and optimal travel while taking the user's emotional state into consideration.

[0729] "Input means" refers to a device or method for receiving information from the user regarding the starting position, ending position, and means of movement.

[0730] "Information gathering means" refers to a device or method for obtaining information from multiple transportation systems and facilities in order to eliminate obstacles.

[0731] "Analysis means" refers to a device or method for calculating the optimal travel route based on collected obstacle elimination information and user input information.

[0732] "Display means" refers to a device or method for presenting the calculated travel path to the user visually and audibly.

[0733] "Update means" refers to a device or method for updating a travel route using real-time information.

[0734] "Emotional analysis means" refers to a device or method for detecting an emotional state based on the user's physiological data and reflecting this in the selection of a travel route.

[0735] "Adjustment means" refers to a device or method for appropriately adjusting the displayed content according to the user's emotional state.

[0736] This invention provides a system that optimizes a user's movement according to their emotional state. The system begins with the user inputting their starting point, destination, and mode of transportation using a terminal. The terminal collects this data and transmits it to a server. The server uses advanced information gathering means to obtain real-time traffic and accessibility information from databases of external transportation companies and public facilities. Programming interfaces such as APIs may be used for this information gathering.

[0737] After collecting information, the server analyzes the data using a generative AI model to calculate the optimal travel path. This process considers not only user input but also physiological data and emotional state. To detect emotional state, biosensors are used to analyze the user's heart rate and voice tone. As a result, if the user is in a high-stress state, the server selects a more relaxing path.

[0738] The calculated travel route is transmitted from the server to the terminal. The terminal receives this information and presents it to the user in an easy-to-understand manner. Specifically, it provides information to the user using visual maps and voice guidance. The terminal also has a function that automatically adjusts the display's color tone and font size according to the user's emotional state. For example, if the user is feeling stressed, the display will be shown in calming colors to alleviate their tension.

[0739] For example, if a user inputs "Tell me the best route from Shibuya Station to Shinjuku Station," the system might analyze the prompt and recommend a quiet bus route. In this way, the system can respond to the user's different emotional states and provide the most appropriate travel method in real time.

[0740] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0741] Step 1:

[0742] The user uses a terminal to input their starting location, destination location, and preferred mode of transportation. The terminal converts this input data into an internal format and prepares it for transmission to the server. The input data includes geographical information and information about the selected mode of transportation.

[0743] Step 2:

[0744] The terminal sends the converted input data to the server. Upon receiving the data, the server stores it in a database for secure analysis. At this stage, a simple verification process is performed to confirm the integrity and accuracy of the data.

[0745] Step 3:

[0746] The server uses information gathering tools to access external transportation APIs and public facility databases to obtain real-time traffic and accessibility information. This data is an important factor related to user travel and is taken into consideration in the analysis.

[0747] Step 4:

[0748] The server uses a generative AI model to analyze collected real-time information and user input data. The analysis considers available route information, the status of transportation options, and accessibility. Furthermore, an emotion analysis system detects the user's emotional state and incorporates this into the route selection. At this point, an optimized route is calculated within the server.

[0749] Step 5:

[0750] The calculated travel route is transmitted from the server to the terminal. The terminal ensures the user understands the route by providing visual and auditory instructions. Specifically, map displays and audio guidance are used. If necessary, the terminal automatically adjusts the display's color tone and font size to improve user comfort.

[0751] Step 6:

[0752] If a user experiences stress or anxiety while traveling, the device's emotion engine detects this, and the server updates the route or messages accordingly. For example, it might send a voice message to encourage relaxation or suggest a safer route. This allows for a more personalized user experience.

[0753] (Application Example 2)

[0754] 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".

[0755] Conventional travel route optimization systems often fail to adequately consider the user's emotional state, making it difficult to alleviate the tension and anxiety they experience during travel. In particular, they lack the ability to provide flexible information tailored to the user's emotional state, resulting in users not feeling sufficiently secure during their journey.

[0756] 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.

[0757] In this invention, the server includes an input means for receiving the starting point, destination point, and means of transportation from the user; an information gathering means for collecting unobstructed information from multiple means of transportation and facilities; an analysis means for analyzing the collected unobstructed information and user input information to calculate the optimal travel route; a display means for presenting the calculated travel route to the user visually and audibly; an update means for updating the travel route based on real-time information; and an emotion analysis means for detecting the user's emotional state and adjusting the travel route and information presentation method. This enables detailed travel support tailored to the user's emotional state.

[0758] "Input means" refers to a device or method for receiving information from the user regarding the starting point, destination, and means of transportation.

[0759] "Information gathering means" refers to a device or method for collecting unobstructed information from multiple means of transportation or facilities.

[0760] "Analysis means" refers to a device or method for calculating the optimal travel path based on collected unobstructed information and user input information.

[0761] "Display means" refers to a device or method for visually and audibly presenting the calculated travel path to the user.

[0762] "Update means" refers to a device or method for updating a travel route based on real-time information.

[0763] "Emotional analysis means" refers to a device or method for detecting a user's emotional state and adjusting the movement path and information presentation method accordingly.

[0764] The system for carrying out the present invention takes into account the user's emotional state when the user is moving and provides the optimal travel route and information delivery method. This system includes various sensors, processing devices, and output devices.

[0765] As an initial setup, the server receives information from the user regarding the departure point, destination, and mode of transportation via an input device. This input device is implemented through mobile devices such as smartphones and tablets. Next, the server uses an information gathering device to collect unobstructed information from multiple modes of transportation and facilities. This utilizes transportation APIs and public information databases.

[0766] The obtained data is processed by an analysis system to calculate the optimal route for the user's desired travel. The analysis system uses data analysis software such as Python or R, and employs algorithms to evaluate and optimize various conditions. The calculation results are presented to the user via a display system. The display system provides information visually and audibly using a display screen or speech synthesis technology.

[0767] Furthermore, the emotion analysis system monitors the user's biometric data using sensors and detects their emotional state. This is done using heart rate monitors and speech recognition technology. This data is analyzed by a generative AI model to evaluate the user's stress and anxiety levels. Based on this evaluation, the emotion analysis system adjusts the movement path and information presentation method to provide the user with a sense of security.

[0768] For example, if a user feels anxious in a crowded train station, the emotion analysis system will detect this state, and the server will prioritize suggesting a route that passes through a quiet space where the user can relax. In this case, an example of a prompt message to the generating AI model might be, "The user is experiencing high stress. Please suggest a quiet and safe route."

[0769] The entire system is designed to provide flexible support tailored to the user's emotional state, ensuring they can travel with peace of mind.

[0770] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0771] Step 1:

[0772] The server receives information from the user via the terminal, including the starting point, destination, and mode of transportation. Based on the information collected through the input, it queries the database to determine the user's specific request. As output, the user's travel preferences are finalized as specific parameters.

[0773] Step 2:

[0774] The server uses information gathering methods to collect uninterrupted information from multiple modes of transportation and facilities. This includes processes for obtaining real-time data from transportation APIs and facility information. Inputs are database queries and API requests, and outputs are integrated transportation and facility information.

[0775] Step 3:

[0776] The server analyzes the collected data using analytical tools and calculates the optimal travel route for the user's request. It performs multivariate analysis through a Python algorithm to calculate the optimal route. The input is a vast amount of collected traffic data, and the output is the most efficient travel suggestion.

[0777] Step 4:

[0778] The terminal presents the calculated travel route to the user via a display. The terminal's display graphically shows the route information, and provides detailed explanations using audio guidance as needed. The input is the calculated travel route, and the output is visual and auditory information in a format understandable to the user.

[0779] Step 5:

[0780] The server uses an update mechanism to update the travel route in real time in response to changing conditions. It monitors changes in traffic information and recalculates the travel plan as needed. The input is newly acquired real-time traffic data, and the output is the updated travel route.

[0781] Step 6:

[0782] The server receives biometric data from sensors to analyze the user's emotional state using emotion analysis tools. Data such as heart rate monitor and voice tone are analyzed by a generating AI model. The input is real-time biometric data, and the output is an evaluation of the user's emotional state.

[0783] Step 7:

[0784] The server adjusts the navigation path and information presentation method based on the results of the emotion analysis. If stress is detected, it prepares a calming path and information presentation. Using a generative AI model, it creates specific prompt sentences and notifies the user of reassuring information. The input is the emotion analysis result, and the output is the adjusted information provided to the user.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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."

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] The following is further disclosed regarding the embodiments described above.

[0807] (Claim 1)

[0808] An input means for receiving the starting point, destination, and mode of transport from the user,

[0809] Information gathering means for collecting barrier-free related information from multiple modes of transportation and facilities,

[0810] An analysis means that analyzes collected barrier-free information and user input information to calculate the optimal travel route,

[0811] A display means that visually presents the calculated travel route to the user,

[0812] A means of updating travel routes based on real-time information,

[0813] A system that includes this.

[0814] (Claim 2)

[0815] The system according to claim 1, wherein the analysis means optimizes the travel path based on the user's input preferences.

[0816] (Claim 3)

[0817] The system according to claim 1, wherein the update means recalculates the travel route using information collected in real time and presents the new travel route to the user using the display means.

[0818] "Example 1"

[0819] (Claim 1)

[0820] Information acquisition means for receiving the starting point, destination point, and method of travel from the user,

[0821] Information aggregation means for collecting fluid obstacle information from multiple transportation systems and facilities,

[0822] An analysis means that analyzes acquired obstacle information and user input information and calculates the optimal travel route using artificial intelligence technology,

[0823] Information display means for visually or audibly presenting the calculated travel route to the user,

[0824] A dynamic update mechanism that recalculates the travel route based on real-time change information,

[0825] A system that includes this.

[0826] (Claim 2)

[0827] The system according to claim 1, wherein the analysis means improves the travel route based on the priority conditions entered by the user.

[0828] (Claim 3)

[0829] The system according to claim 1, wherein a dynamic update means recalculates the travel route using real-time acquired change information and provides the new travel route to the user via an information display means.

[0830] "Application Example 1"

[0831] (Claim 1)

[0832] A data receiving means that receives the user's starting point, destination, and mode of transport,

[0833] Information acquisition means for collecting information related to obstacle avoidance from multiple modes of transportation and facilities,

[0834] A calculation means that analyzes collected obstacle avoidance information and user input information to calculate an efficient travel path,

[0835] A visualization means that visually presents the calculated travel path to the user,

[0836] An information update method that updates travel routes based on real-time information,

[0837] An optimization method that presents alternative routes for users to travel safely while using urban areas and public transportation,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, wherein the optimization means adjusts the travel path based on the user's travel status as entered.

[0841] (Claim 3)

[0842] The system according to claim 1, wherein the information update means recalculates the travel route using information collected in real time, and the new travel route is presented to the user by the visualization means.

[0843] "Example 2 of combining an emotion engine"

[0844] (Claim 1)

[0845] An input means for receiving the starting position, ending position, and means of movement from the user,

[0846] Information gathering means for collecting information to eliminate obstacles from multiple transportation systems and facilities,

[0847] An analysis means that analyzes collected obstacle elimination information and user input information to calculate the optimal travel route,

[0848] A display means that presents the calculated travel path to the user visually and audibly,

[0849] A means of updating travel routes based on real-time information,

[0850] An emotion analysis means that detects the emotional state from the user's physiological data and adjusts it according to the selected travel route,

[0851] An adjustment mechanism that adjusts the displayed content according to the user's emotional state,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, wherein the analysis means optimizes the travel path based on the user's input preferences and emotional state.

[0855] (Claim 3)

[0856] The system according to claim 1, wherein the update means recalculates the travel route using information collected in real time and the user's emotional state, and presents the new travel route to the user using the display means.

[0857] "Application example 2 when combining with an emotional engine"

[0858] (Claim 1)

[0859] An input means for receiving the starting point, destination point, and means of transportation from the user,

[0860] Information gathering means for collecting unobstructed information from multiple means of transportation and facilities,

[0861] An analysis means that analyzes collected unobstructed information and user input information to calculate the optimal travel path,

[0862] A display means that visually and audibly presents the calculated travel route to the user,

[0863] A means of updating travel routes based on real-time information,

[0864] An emotion analysis means that detects the user's emotional state and adjusts the movement path and information presentation method,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, wherein, based on a judgment of the user's emotional state, the emotion analysis means presents information to the user to give the user a sense of security.

[0868] (Claim 3)

[0869] The system according to claim 1, wherein the emotion analysis means analyzes the user's emotional state in real time using the user's biometric information and adjusts the movement path accordingly. [Explanation of Symbols]

[0870] 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 input means for receiving the starting point, destination, and mode of transport from the user, Information gathering means for collecting barrier-free related information from multiple modes of transportation and facilities, An analysis means that analyzes collected barrier-free information and user input information to calculate the optimal travel route, A display means that visually presents the calculated travel route to the user, A means of updating travel routes based on real-time information, A system that includes this.

2. The system according to claim 1, wherein the analysis means optimizes the travel path based on the user's input preferences.

3. The system according to claim 1, wherein the update means recalculates the travel route using information collected in real time and presents the new travel route to the user using the display means.

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