system

Abstract

We provide the system. [Solution] An input means for the user to enter the departure point and destination, A means for obtaining transfer information based on the entered departure and destination points, A means for collecting accessibility information for locations related to the acquired transfer information, A means for generating a detour route when non-barrier-free points are included, A system including means for displaying the aforementioned transfer information, accessibility information, and detour route information to the user.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For people with restricted mobility, especially wheelchair users, parents with children, the elderly, and people with physical disabilities, when using public transportation as a means of transportation, the current situation where it is necessary to check barrier-free information at stations and routes one by one is very time-consuming and stressful. Also, when using non-barrier-free facilities, it is difficult to search for alternative routes by oneself, and convenience is reduced. The present invention aims to solve these problems.

Means for Solving the Problems

[0005] The present invention provides a system comprising an input means for the user to input a departure point and destination, a means for acquiring transfer information based on the input departure point and destination, and a means for acquiring barrier-free information for points related to the acquired transfer information. Furthermore, if non-barrier-free points are included, the system adds a means for generating a detour route, and finally has a means for displaying the transfer information, barrier-free information, and detour route information to the user, thereby providing a system that helps the user to smoothly plan their travel.

[0006] A "user" refers to a person who uses the system to search for a travel route.

[0007] "Input means" refers to a device or function that is an interface or device used by a user to input their departure point and destination into the system.

[0008] "Transfer information" refers to data that includes information such as routes, times, and fares for public transportation to be used between the point of origin and the destination.

[0009] "Barrier-free information" refers to data that makes public transportation facilities and routes more accessible to people with physical limitations, such as elevators, multi-purpose restrooms, and priority seating.

[0010] "Non-barrier-free" refers to a state in which public transportation facilities and routes lack or have insufficient barrier-free equipment such as elevators and ramps.

[0011] "Alternative routes" refer to information about travel routes proposed as alternative paths to avoid non-barrier-free locations.

[0012] "Display means" refers to a device or function for visually presenting transfer information, accessibility information, and alternative route information to the user.

[0013] A "machine learning algorithm" refers to a computational method or model that allows a computer to learn from data and automatically derive the optimal solution. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a 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.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is a barrier-free information provision system for improving the convenience of public transportation for people with mobility limitations. The system obtains transfer information and related barrier-free information from the user upon inputting their departure and destination points, and provides alternative routes if non-barrier-free stations are included.

[0036] First, the user accesses a dedicated application or website using a device such as a smartphone or computer and enters their departure and destination points. The device then sends this information to a server. Based on the received data, the server accesses an external transportation information database to obtain the optimal transfer route. This transfer information includes necessary stations, intermediate stops, travel time, and fares.

[0037] The server then accesses a dedicated accessibility information database to check for the availability of barrier-free facilities at each station. It collects information on facilities such as elevators and multi-purpose restrooms. If there are stations without barrier-free facilities along the route, the server uses a generation AI to calculate an alternative route. This alternative route is designed with the user's convenience in mind, providing the shortest and most comfortable route.

[0038] The acquired information is sent back to the device and displayed visually. Users can intuitively check routes on their devices, making it easy to plan their travel. For example, if a wheelchair user wants to use a train station in Tokyo, the server will provide information on available elevators and, if necessary, guide them on a route that bypasses stations without elevators. Similarly, when parents with young children plan to travel with a stroller, convenient routes are provided.

[0039] This system is optimized to meet the diverse needs of users of public transportation and to improve the efficiency of travel.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] Users access a dedicated app or website using their own devices and enter their departure and destination locations. This information is then sent to the server as data collected through the user interface (UI).

[0043] Step 2:

[0044] Based on the received origin and destination data, the server accesses an external traffic information database to retrieve corresponding transfer information. This information includes the travel route, travel time, and fare.

[0045] Step 3:

[0046] Based on the acquired transfer information, the server queries a dedicated accessibility information database to determine the availability of barrier-free facilities at each station. This allows it to collect information such as the presence of elevators and accessible restrooms.

[0047] Step 4:

[0048] The server checks the facilities at each station included in the route, and if there are stations that are not barrier-free, such as those without elevators, it uses a generation AI to calculate an alternative route. The alternative route is optimized with user convenience in mind and designed as an alternative route.

[0049] Step 5:

[0050] The server packages together regular transfer information, accessibility information for each station, and alternative route information as needed, and sends it to the terminal.

[0051] Step 6:

[0052] The terminal analyzes all information retrieved from the server and displays it visually to the user. This allows the user to intuitively understand transfer routes, accessibility information, and alternative routes.

[0053] Step 7:

[0054] Based on the displayed information, users can create an appropriate travel plan. They select their planned route and prepare to depart.

[0055] (Example 1)

[0056] 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."

[0057] When using public transportation, there are challenges in mitigating the inconveniences faced by people with mobility limitations and ensuring safe and comfortable travel. In particular, wheelchair users and those with strollers often struggle to find optimal routes that avoid non-barrier-free locations.

[0058] 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.

[0059] In this invention, the server includes a device means for the user to input a starting point and an ending point; means for acquiring connection information based on the input starting point and ending point; and means for collecting location accessibility information related to the acquired connection information. This makes it possible to provide an appropriate travel route that meets the needs of each user.

[0060] "Users" refer to people who use the system to plan their travel using public transportation.

[0061] "Starting point" refers to the point where a user begins their journey using public transportation.

[0062] "Terminal destination" refers to the point where a user ends their journey using public transportation.

[0063] "Connection information" refers to information about the means of transportation and routes from the starting point to the final destination.

[0064] "Accessibility information" refers to information regarding the availability of facilities and services for users with mobility limitations at each location.

[0065] A "detour route" refers to an alternative route provided to users to reach their destination while avoiding inaccessible points.

[0066] A "generative AI model" refers to a machine learning algorithm that generates new information or routes based on data.

[0067] A "device" refers to an electronic device used by a user to operate a system, and specifically includes smartphones and computers.

[0068] A description of embodiments for carrying out the present invention will be provided.

[0069] Users access the system's dedicated application or website using devices such as smartphones or computers. Through the user interface on their device, users can input their starting and ending locations. The entered information is transmitted to the server via the internet.

[0070] The server accesses an external transportation database based on the received origin and destination data to obtain the most suitable connection information. This process utilizes APIs that interface with transportation schedules and congestion levels. Next, the server retrieves accessibility information for each location from a dedicated database. This information includes the availability of facilities such as elevators and accessible restrooms.

[0071] If an inaccessible location is included in the route, the server uses a generative AI model to generate a new detour route. The generative AI model uses machine learning algorithms to design the optimal detour route tailored to the user's needs. In doing so, the generative AI model takes into account traffic conditions and the characteristics of each user.

[0072] The acquired and generated information is then sent back to the terminal and provided to the user through an intuitive visual display. The user can easily plan their travel based on the displayed information.

[0073] As a concrete example, if a wheelchair user is traveling from one station in a city to another, the server will provide information on elevators and accessible restrooms at that station. Furthermore, by suggesting alternative routes as needed, the server can show the user the most suitable travel route. An example of a prompt message is, "Please provide a barrier-free route from departure point: City A Station to destination: City B Station."

[0074] This system aims to meet the needs of various users with mobility limitations and to make public transportation more accessible.

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

[0076] Step 1:

[0077] The terminal receives the origin and destination locations via a dedicated application or website connected to by the user. The entered data (origin and destination) is temporarily stored on the terminal and prepared to be sent to the server for the next processing step.

[0078] Step 2:

[0079] The terminal sends the origin and destination information it holds to the server. HTTP requests are typically used for this process. The terminal displays the transmission status as output. Error checking is also performed at this step to ensure the data is transmitted correctly.

[0080] Step 3:

[0081] The server uses the received origin and destination data to access an external transportation database and retrieve connection information. It obtains transportation schedules and transfer information via the database API and calculates the optimal route. As a result of this calculation, connection information (route, travel time, and cost) is generated and stored on the server.

[0082] Step 4:

[0083] The server accesses a dedicated database to retrieve accessibility information for each location related to the connection information. It queries the database for accessibility information (availability of facilities, detailed information) and stores it together with the connection information. The output of this step is an information set containing the accessibility status of each location.

[0084] Step 5:

[0085] If the server encounters an inaccessible point along the route, it uses a generative AI model to generate an alternative route. Here, based on the input information (information about inaccessible points), a machine learning algorithm calculates the optimal alternative route and generates alternative route information as output.

[0086] Step 6:

[0087] The server aggregates the acquired and generated connection information, accessibility information, and detour route information, and sends it to the terminal. The output information is converted into a format that can be displayed on the user interface, preparing it for intuitive display.

[0088] Step 7:

[0089] The terminal receives information sent from the server and displays it visually on the user interface. This display includes selectable routes, accessibility information, and alternative routes. Based on this, the user can create the best travel plan.

[0090] (Application Example 1)

[0091] 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."

[0092] When people with mobility limitations use physical stores or public facilities, they often face the challenge of not being able to easily obtain barrier-free route information, making comfortable travel difficult. This invention aims to solve this problem and provide a system that allows users to reach their destinations with peace of mind.

[0093] 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.

[0094] In this invention, the server includes an information terminal means for the user to input a departure point and destination, means for acquiring route information based on the input departure point and destination, and means for collecting barrier-free facility information for points related to the acquired route information. This enables users to easily obtain barrier-free route information and reach their destination comfortably and efficiently.

[0095] An "information terminal" is a device that allows users to input information about their departure and destination locations, and it is equipped with communication capabilities.

[0096] "Route information" refers to information about transfers and travel based on the entered departure and destination points.

[0097] "Barrier-free facilities information" refers to information regarding the availability of facilities that can be used by wheelchair users and people with disabilities.

[0098] "Generative artificial intelligence" is a technology that uses machine learning algorithms to generate the optimal alternative path.

[0099] An "alternative route" is an optimized travel path designed to avoid non-barrier-free locations.

[0100] To implement this invention, the following system will be constructed.

[0101] The server receives origin and destination data entered by the user from an information terminal. This information is entered via a smartphone or tablet device equipped with a communication module. The server first accesses an external geographic information API (e.g., Google® Maps API) based on the input data to obtain optimal route information from the origin to the destination. This route information includes points of passage and transfer information.

[0102] The server then accesses the Accessibility Facilities Information API to check for the presence of barrier-free facilities along the route obtained from the Geographic Information API. Specifically, it retrieves information regarding the presence of elevators and accessible restrooms.

[0103] If there are non-barrier-free points along the route, the server generates an alternative route using a generative AI model (e.g., OpenAI's GPT model). During this process, prompts are input to the generative AI to calculate an optimized alternative route.

[0104] Example prompt: "Please suggest an accessible route to a specific store. Please include information about elevators and ramps."

[0105] The user's device visually displays barrier-free route information and alternative route information transmitted from the server. This allows the user to easily understand the route to their destination and efficiently plan their journey.

[0106] For example, in a shopping mall, if a user wants to visit a specific store, they can input their information into a terminal, which will then display the shortest route that takes accessibility into account. This allows wheelchair users and parents with strollers to enjoy shopping with peace of mind.

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The user enters their departure and destination locations using an information terminal. The departure and destination locations are specified in the user interface, and the terminal sends this information to the server. At this point, the input is the geographical location information selected by the user.

[0110] Step 2:

[0111] Based on the received origin and destination information, the server accesses a geographic information API to obtain optimal route information. The API outputs data related to the travel route. This data includes points of passage, travel time, and possible transfer information. The server organizes the received information and stores it in a format that can be used for the user's travel planning.

[0112] Step 3:

[0113] The server accesses the Accessibility Facilities Information API based on the route information. From this API, it retrieves data regarding the presence or absence of elevators and accessible restrooms at each point along the route. The input is location information along the route, and the output is the presence or absence of accessibility facilities at each point.

[0114] Step 4:

[0115] The server uses generated artificial intelligence to create alternative routes that avoid non-barrier-free points, based on the acquired barrier-free facility information. This process involves providing prompts to the generating AI model to calculate an optimized alternative route. The input is the current route information and barrier-free facility information, and the output is new route information that takes barrier-free access into account. Specifically, the calculated results are adjusted by prompts generated by the AI, and detour routes are suggested if necessary.

[0116] Step 5:

[0117] The server sends alternative routes and related information to the user's terminal. The terminal uses the received data to visually display the route on a map. The input is route data from the server, and the output is a route display that the user can visually confirm. This allows the user to intuitively confirm the suggested travel route and plan for safe travel.

[0118] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0119] This invention is a system designed to enhance convenience for users when using public transportation and to reduce the psychological burden during travel. In particular, it provides barrier-free information to people with mobility limitations, suggests alternative routes when necessary, and not only recognizes the user's emotions but also enables appropriate support.

[0120] The process begins with the user accessing a dedicated application or web platform using a terminal and entering their departure and destination points. The terminal sends this information to a server, which retrieves transfer information from an external transportation database based on the entered data. Simultaneously, accessibility information for each station is also checked, and the status of facilities such as elevators and accessible restrooms is collected.

[0121] Furthermore, the server is equipped with an emotion engine that evaluates the user's emotions and psychological state in real time through voice input and camera. If the system determines that the user's stress level is high, the generating AI will use this emotion data to suggest alternative routes, alternative paths, or relaxing content. This allows users to receive services tailored to their mental state, not just choose a mode of transportation.

[0122] Information is displayed to users in an easy-to-understand format via their devices. Users can review transfer routes, accessibility information, and suggestions from the emotional engine, and then formulate the optimal travel strategy based on this information. For example, if it is determined that a wheelchair user should avoid the afternoon rush hour, the emotional engine can suggest less crowded times or places to relax, such as cafes.

[0123] The aim of this system is to improve convenience and provide a sense of psychological security, thereby creating an environment where users can travel more comfortably.

[0124] The following describes the processing flow.

[0125] Step 1:

[0126] Users access a dedicated application or web platform using a mobile device or computer and enter their departure and destination locations. This initiates the search for travel routes.

[0127] Step 2:

[0128] The terminal sends user input information to the server. This information includes the origin, destination, and current time.

[0129] Step 3:

[0130] Based on the transmitted information, the server accesses an external traffic information database to obtain transfer information, including the optimal transfer route, travel time, and fare.

[0131] Step 4:

[0132] The server uses the acquired transfer information to query its internal database for accessibility information at each location. Key information includes the availability of elevators and accessible restrooms.

[0133] Step 5:

[0134] The emotion engine on the server analyzes voice input and video data from the device to recognize the user's emotional state. This allows for an assessment of the current stress level and other factors.

[0135] Step 6:

[0136] The server uses recognized emotional data to generate AI-powered alternative routes and support information appropriate to the user's state. This includes suggesting alternative routes to reduce stress and places to stop for a change of pace.

[0137] Step 7:

[0138] The server packages transfer information, accessibility information, and emotion-based suggestions and sends them to the terminal.

[0139] Step 8:

[0140] The terminal visually displays the received information to the user. This allows the user to check accessibility information and emotionally tailored suggestions along with their travel route, enabling them to plan the most optimal journey overall.

[0141] Step 9:

[0142] Users make travel decisions based on the information presented and execute travel plans that suit their needs.

[0143] (Example 2)

[0144] 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".

[0145] While there is a wealth of information available regarding accessibility and optimal transfer methods for using public transportation, systems that are easily accessible to people with mobility limitations are scarce. Furthermore, there is a need to reduce the psychological burden during travel. In particular, the lack of systems that can provide appropriate support tailored to the user's emotions and psychological state is a significant challenge.

[0146] 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.

[0147] In this invention, the server includes means for acquiring traffic information based on user input data, means for collecting barrier-free information, and means for using a generative AI model that analyzes the user's emotions and proposes appropriate content. This makes it possible to provide users with mobility limitations with support that reduces their psychological burden, along with presenting them with the optimal barrier-free route.

[0148] A "terminal" is a general term for devices that allow users to input their departure and destination points and that transmit information to a server.

[0149] "External information sources" refer to databases and third-party information systems that provide data such as traffic information and accessibility information.

[0150] "Barrier-free information" refers to information indicating the availability of facilities and equipment relevant to wheelchair users and people with mobility limitations, and includes data on the installation of elevators and multi-purpose restrooms.

[0151] A "detour route" refers to a more accessible alternative travel route proposed when the intended route includes points that are not barrier-free.

[0152] An "emotion analysis engine" is software or an algorithm used to evaluate a user's psychological state and emotions based on their voice and video data.

[0153] A "generative AI model" is a system that uses artificial intelligence technology to suggest appropriate alternative paths and content to users based on the results of analyzing their emotions.

[0154] A "data analysis algorithm" refers to mathematical methods and processes used to calculate the optimal alternative path based on input data.

[0155] This invention is a system designed to enhance convenience for users with mobility limitations when using public transportation. The system begins with the user using a terminal to input their departure and destination points. The terminal can be a general-purpose computer or smartphone, and it is assumed that it is connected to the internet.

[0156] The terminal sends user input data to the server. The server collaborates with external sources that provide traffic information. This allows the server to obtain transfer information based on the entered departure and destination points. The server also collects accessibility information for each station. This information specifically includes the availability of elevators and accessible restrooms.

[0157] Furthermore, the server is equipped with an emotion analysis engine. This engine is software that evaluates the user's psychological state and emotions based on audio data transmitted from the terminal and video data from the camera. If the server determines that the user's stress level is high, it uses a generative AI model to suggest alternative routes or relaxing content based on that data.

[0158] For example, if it is determined that a wheelchair user needs to avoid the afternoon rush hour, the generative AI model can suggest less crowded times or places to rest at cafes. In this way, users can develop optimal travel strategies tailored to their own emotional state.

[0159] An example of a prompt message would be: "Please tell me the best route for my next trip. My departure point is Tokyo Station, and my destination is Shinjuku Station. Please suggest stress-free options, taking into account factors such as the availability of elevators and congestion levels."

[0160] Through this invention, users can improve the convenience of travel and gain a sense of psychological security.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The user uses the terminal to enter their departure and destination points. The terminal stores this data digitally when the user enters "Tokyo Station to Shinjuku Station" into the application's designated input field. This data forms the basis for subsequent retrieval of transportation information.

[0164] Step 2:

[0165] The terminal sends the user-entered departure and destination data to the server. Here, the terminal securely transfers this information to the server via the internet. Upon receiving this input data, the server prepares to begin accessing the database for the next processing step.

[0166] Step 3:

[0167] The server accesses an external traffic information database and obtains the optimal transfer route based on the input data. Specifically, the server queries the database to obtain the calculated fastest route and the simplest transfer path. The results are stored on the server as digital data.

[0168] Step 4:

[0169] The server then collects additional accessibility information for each station related to the acquired traffic information. Here, the server performs another database query to obtain data on the presence of elevators and steps. The obtained information is stored on the server as part of the user's travel plan.

[0170] Step 5:

[0171] The server uses an emotion analysis engine to analyze voice and image data from the user and evaluate their psychological state. This input includes the user's facial expressions and tone of voice. The emotion analysis engine analyzes this data to quantify stress levels and psychological state. The results are stored on the server and used for subsequent processing.

[0172] Step 6:

[0173] The server uses a generative AI model to suggest alternative routes and content based on the user's emotional data. This model generates suggestions such as less crowded routes or relaxing rest areas, depending on the user's stress level. The generated suggestions are customized to be useful to the user.

[0174] Step 7:

[0175] The terminal displays transfer information, accessibility information, and suggestions based on sentiment analysis received from the server to the user. The terminal presents this information in a visually easy-to-understand format, helping the user decide on a travel route based on it. This output allows the user to select the safest and most optimal route and adjust their travel plan accordingly.

[0176] (Application Example 2)

[0177] 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".

[0178] In public transportation and food delivery services, technologies that ensure users can travel or wait comfortably are still not fully established. In particular, optimizing route selection and content suggestions while considering users' emotions and psychological states is difficult with current technology. Therefore, there is a need for systems that reduce stress and improve convenience.

[0179] 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.

[0180] In this invention, the server includes an input device means for the user to input their departure and destination points, a device means for analyzing the user's emotional state and generating suggestions tailored to that state, and a device means for presenting the optimal route and content based on those suggestions. This optimizes transportation and waiting time services based on the user's psychological state, reducing stress and enabling the provision of a comfortable service.

[0181] An "input device" is a device that has the function of allowing the user to specify the origin and destination.

[0182] "Travel information" refers to information about transportation and routes obtained based on the entered departure and destination locations.

[0183] "Convenience information" refers to information about facilities and services that are easily accessible to people with mobility limitations at locations related to their travel information.

[0184] A "detour route" is an alternative route generated when traveling to avoid inconvenient locations.

[0185] "Emotional state" refers to data that indicates the user's psychological or emotional state.

[0186] A "proposal generation device" is a device that analyzes the user's emotional state and generates appropriate travel routes and service content.

[0187] A "content-presenting device" is a device that has the function of presenting suggested travel routes and service details to a user visually or audibly.

[0188] This system includes an input device for the user to enter their departure and destination points. Based on the user's input, the server retrieves travel information from an external database. The server then collects relevant convenience information based on the retrieved travel information and activates emotion assessment software to evaluate the user's emotional state.

[0189] Emotion assessment utilizes data collected via voice input devices and cameras. Based on this data, emotion analysis software analyzes the user's psychological state in real time and determines their stress level. This process employs technologies such as speech recognition libraries and image recognition algorithms.

[0190] If the user's emotional state indicates stress, the server uses a generative AI model to suggest optimal alternative routes and relaxing content. These suggestions are displayed on the user's device through a content-displaying device. The user can confirm the suggested routes and content through visual or audio guidance. This allows the user to receive a service optimized according to their current psychological state.

[0191] A concrete example would be a situation where, when a user is experiencing stress from their commute, this system plays music that is most relaxing for the user and provides an alternative route to avoid congestion.

[0192] Example prompt to input into the generating AI model: "The user is tired and needs to relax. Please suggest the best route and content suitable for this state."

[0193] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0194] Step 1:

[0195] The user enters their departure and destination points using their device. This input data is sent to the server and used as foundational data for extracting travel information. Specifically, the input data is passed to the server via an API, and the server retrieves the desired travel information from an external database based on the input values.

[0196] Step 2:

[0197] The server analyzes the acquired travel information and collects relevant convenience information. At this stage, a data processing algorithm is used to evaluate the degree of convenience regarding the travel route, and information is retrieved from the convenience database. Detailed convenience information is provided as output.

[0198] Step 3:

[0199] The device initiates an emotion assessment process using voice and image data provided by the user. In this step, advanced speech recognition software and image recognition algorithms are used to analyze the user's emotional state. The server outputs the emotional state as numerical data based on the input data, determining the user's current psychological state.

[0200] Step 4:

[0201] The server utilizes a generative AI model to generate optimal suggestions that take into account the user's emotional state. This prompt includes information describing the user's state, and the AI ​​suggests the best route or relaxing content. This output serves as guidance for improving the user's original state.

[0202] Step 5:

[0203] The server transfers the generated suggestions to the terminal and presents them to the user through a content display device. The user can review the suggested routes and content, and select and use them as needed. As a final output, the user can enjoy a stress-free and convenient service.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] [Second Embodiment]

[0208] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0209] 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.

[0210] 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).

[0211] 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.

[0212] 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.

[0213] 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).

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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".

[0220] This invention is a barrier-free information provision system for improving the convenience of public transportation for people with mobility limitations. The system obtains transfer information and related barrier-free information from the user upon inputting their departure and destination points, and provides alternative routes if non-barrier-free stations are included.

[0221] First, the user accesses a dedicated application or website using a device such as a smartphone or computer and enters their departure and destination points. The device then sends this information to a server. Based on the received data, the server accesses an external transportation information database to obtain the optimal transfer route. This transfer information includes necessary stations, intermediate stops, travel time, and fares.

[0222] The server then accesses a dedicated accessibility information database to check for the availability of barrier-free facilities at each station. It collects information on facilities such as elevators and multi-purpose restrooms. If there are stations without barrier-free facilities along the route, the server uses a generation AI to calculate an alternative route. This alternative route is designed with the user's convenience in mind, providing the shortest and most comfortable route.

[0223] The acquired information is sent back to the device and displayed visually. Users can intuitively check routes on their devices, making it easy to plan their travel. For example, if a wheelchair user wants to use a train station in Tokyo, the server will provide information on available elevators and, if necessary, guide them on a route that bypasses stations without elevators. Similarly, when parents with young children plan to travel with a stroller, convenient routes are provided.

[0224] This system is optimized to meet the diverse needs of users of public transportation and to improve the efficiency of travel.

[0225] The following describes the processing flow.

[0226] Step 1:

[0227] Users access a dedicated app or website using their own devices and enter their departure and destination locations. This information is then sent to the server as data collected through the user interface (UI).

[0228] Step 2:

[0229] Based on the received origin and destination data, the server accesses an external traffic information database to retrieve corresponding transfer information. This information includes the travel route, travel time, and fare.

[0230] Step 3:

[0231] Based on the acquired transfer information, the server queries a dedicated accessibility information database to determine the availability of barrier-free facilities at each station. This allows it to collect information such as the presence of elevators and accessible restrooms.

[0232] Step 4:

[0233] The server checks the facilities at each station included in the route, and if there are stations that are not barrier-free, such as those without elevators, it uses a generation AI to calculate an alternative route. The alternative route is optimized with user convenience in mind and designed as an alternative route.

[0234] Step 5:

[0235] The server packages together regular transfer information, accessibility information for each station, and alternative route information as needed, and sends it to the terminal.

[0236] Step 6:

[0237] The terminal analyzes all information retrieved from the server and displays it visually to the user. This allows the user to intuitively understand transfer routes, accessibility information, and alternative routes.

[0238] Step 7:

[0239] Based on the displayed information, users can create an appropriate travel plan. They select their planned route and prepare to depart.

[0240] (Example 1)

[0241] 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."

[0242] When using public transportation, there are challenges in mitigating the inconveniences faced by people with mobility limitations and ensuring safe and comfortable travel. In particular, wheelchair users and those with strollers often struggle to find optimal routes that avoid non-barrier-free locations.

[0243] 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.

[0244] In this invention, the server includes a device means for the user to input a starting point and an ending point; means for acquiring connection information based on the input starting point and ending point; and means for collecting location accessibility information related to the acquired connection information. This makes it possible to provide an appropriate travel route that meets the needs of each user.

[0245] "Users" refer to people who use the system to plan their travel using public transportation.

[0246] "Starting point" refers to the point where a user begins their journey using public transportation.

[0247] "Terminal destination" refers to the point where a user ends their journey using public transportation.

[0248] "Connection information" refers to information about the means of transportation and routes from the starting point to the final destination.

[0249] "Accessibility information" refers to information regarding the availability of facilities and services for users with mobility limitations at each location.

[0250] A "detour route" refers to an alternative route provided to users to reach their destination while avoiding inaccessible points.

[0251] A "generative AI model" refers to a machine learning algorithm that generates new information or routes based on data.

[0252] A "device" refers to an electronic device used by a user to operate a system, and specifically includes smartphones and computers.

[0253] A description of embodiments for carrying out the present invention will be provided.

[0254] Users access the system's dedicated application or website using devices such as smartphones or computers. Through the user interface on their device, users can input their starting and ending locations. The entered information is transmitted to the server via the internet.

[0255] The server accesses an external transportation database based on the received origin and destination data to obtain the most suitable connection information. This process utilizes APIs that interface with transportation schedules and congestion levels. Next, the server retrieves accessibility information for each location from a dedicated database. This information includes the availability of facilities such as elevators and accessible restrooms.

[0256] If an inaccessible location is included in the route, the server uses a generative AI model to generate a new detour route. The generative AI model uses machine learning algorithms to design the optimal detour route tailored to the user's needs. In doing so, the generative AI model takes into account traffic conditions and the characteristics of each user.

[0257] The acquired and generated information is then sent back to the terminal and provided to the user through an intuitive visual display. The user can easily plan their travel based on the displayed information.

[0258] As a concrete example, if a wheelchair user is traveling from one station in a city to another, the server will provide information on elevators and accessible restrooms at that station. Furthermore, by suggesting alternative routes as needed, the server can show the user the most suitable travel route. An example of a prompt message is, "Please provide a barrier-free route from departure point: City A Station to destination: City B Station."

[0259] This system aims to meet the needs of various users with mobility limitations and to make public transportation more accessible.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The terminal receives the origin and destination locations via a dedicated application or website connected to by the user. The entered data (origin and destination) is temporarily stored on the terminal and prepared to be sent to the server for the next processing step.

[0263] Step 2:

[0264] The terminal sends the origin and destination information it holds to the server. HTTP requests are typically used for this process. The terminal displays the transmission status as output. Error checking is also performed at this step to ensure the data is transmitted correctly.

[0265] Step 3:

[0266] The server uses the received origin and destination data to access an external transportation database and retrieve connection information. It obtains transportation schedules and transfer information via the database API and calculates the optimal route. As a result of this calculation, connection information (route, travel time, and cost) is generated and stored on the server.

[0267] Step 4:

[0268] The server accesses a dedicated database to retrieve accessibility information for each location related to the connection information. It queries the database for accessibility information (availability of facilities, detailed information) and stores it together with the connection information. The output of this step is an information set containing the accessibility status of each location.

[0269] Step 5:

[0270] If the server encounters an inaccessible point along the route, it uses a generative AI model to generate an alternative route. Here, based on the input information (information about inaccessible points), a machine learning algorithm calculates the optimal alternative route and generates alternative route information as output.

[0271] Step 6:

[0272] The server aggregates the acquired and generated connection information, accessibility information, and detour route information, and sends it to the terminal. The output information is converted into a format that can be displayed on the user interface, preparing it for intuitive display.

[0273] Step 7:

[0274] The terminal receives information sent from the server and displays it visually on the user interface. This display includes selectable routes, accessibility information, and alternative routes. Based on this, the user can create the best travel plan.

[0275] (Application Example 1)

[0276] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0277] When people with mobility constraints use physical stores or public facilities, there is a problem that they cannot easily obtain barrier-free route information and it is difficult to move comfortably. The purpose of the present invention is to solve such problems and provide a system that allows users to reach their destinations with confidence.

[0278] 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.

[0279] In this invention, the server includes information terminal means for a user to input a departure place and a destination, means for obtaining route information based on the input departure place and destination, and means for collecting barrier-free facility information of locations related to the obtained route information. Thereby, users can easily obtain barrier-free route information and can reach their destinations comfortably and efficiently.

[0280] An "information terminal" is a device for a user to input information on a departure place and a destination and has a communication function.

[0281] "Route information" is information on transfers and movements obtained based on the input departure place and destination.

[0282] "Barrier-free facility information" is information on the presence or absence of facilities that can be used by wheelchair users and people with physical disabilities.

[0283] "Generative artificial intelligence" is a technology that generates an optimal alternative route using machine learning algorithms.

[0284] "Alternative route" is an optimized movement route that avoids non-barrier-free locations.

[0285] To implement this invention, the following system is constructed.

[0286] The server receives the departure and destination data input by the user from the information terminal. This information is input by smartphones or tablet terminals equipped with a communication module. First, based on the input data, the server accesses an external geographic information API (e.g., Google Maps API) to obtain the optimal route information from the departure point to the destination. This route information includes the points to pass through, information regarding transfers, etc.

[0287] The server further accesses the barrier-free facility information API to check the presence or absence of barrier-free facilities existing on the route obtained from the geographic information API. Specifically, it obtains information regarding the presence or absence of elevators and multi-purpose toilets.

[0288] If there are non-barrier-free points on the route, the server uses a generative AI model (e.g., GPT model of OpenAI) to generate an alternative route. At this time, a prompt sentence is input into the generative AI to calculate an optimized alternative route.

[0289] Example of a prompt sentence: "Please propose a barrier-free route to a specific store. Please include information on elevators and slopes."

[0290] The barrier-free route information and alternative route information sent from the server are visually displayed on the user's terminal. As a result, the user can easily grasp the movement route to the destination and efficiently make a travel plan.

[0291] For example, in a shopping mall, when a user wants to visit a specific store, by inputting it into the terminal, the shortest route considering barrier-free facilities is presented, so wheelchair users and parents using strollers can also enjoy shopping with peace of mind.

[0292] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0293] Step 1:

[0294] The user enters their departure and destination locations using an information terminal. The departure and destination locations are specified in the user interface, and the terminal sends this information to the server. At this point, the input is the geographical location information selected by the user.

[0295] Step 2:

[0296] Based on the received origin and destination information, the server accesses a geographic information API to obtain optimal route information. The API outputs data related to the travel route. This data includes points of passage, travel time, and possible transfer information. The server organizes the received information and stores it in a format that can be used for the user's travel planning.

[0297] Step 3:

[0298] The server accesses the Accessibility Facilities Information API based on the route information. From this API, it retrieves data regarding the presence or absence of elevators and accessible restrooms at each point along the route. The input is location information along the route, and the output is the presence or absence of accessibility facilities at each point.

[0299] Step 4:

[0300] The server uses generated artificial intelligence to create alternative routes that avoid non-barrier-free points, based on the acquired barrier-free facility information. This process involves providing prompts to the generating AI model to calculate an optimized alternative route. The input is the current route information and barrier-free facility information, and the output is new route information that takes barrier-free access into account. Specifically, the calculated results are adjusted by prompts generated by the AI, and detour routes are suggested if necessary.

[0301] Step 5:

[0302] The server sends alternative routes and related information to the user's terminal. The terminal uses the received data to visually display the route on a map. The input is route data from the server, and the output is a route display that the user can visually confirm. This allows the user to intuitively confirm the suggested travel route and plan for safe travel.

[0303] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0304] This invention is a system designed to enhance convenience for users when using public transportation and to reduce the psychological burden during travel. In particular, it provides barrier-free information to people with mobility limitations, suggests alternative routes when necessary, and not only recognizes the user's emotions but also enables appropriate support.

[0305] The process begins with the user accessing a dedicated application or web platform using a terminal and entering their departure and destination points. The terminal sends this information to a server, which retrieves transfer information from an external transportation database based on the entered data. Simultaneously, accessibility information for each station is also checked, and the status of facilities such as elevators and accessible restrooms is collected.

[0306] Furthermore, the server is equipped with an emotion engine that evaluates the user's emotions and psychological state in real time through voice input and camera. If the system determines that the user's stress level is high, the generating AI will use this emotion data to suggest alternative routes, alternative paths, or relaxing content. This allows users to receive services tailored to their mental state, not just choose a mode of transportation.

[0307] Information is presented to the user in an easy-to-understand form through the terminal. The user can check the transfer route, barrier-free information, and suggestions from the emotion engine, and formulate an optimal travel strategy based on this. As a specific example, if it is determined that wheelchair users should avoid the afternoon rush hour, the emotion engine can suggest a less congested time period or a break at a café where they can relax.

[0308] The purpose of this system is to provide improved convenience and a sense of psychological security, and to create an environment where users can move more comfortably.

[0309] The following describes the processing flow.

[0310] Step 1:

[0311] The user uses a mobile terminal or a computer to access a dedicated application or a web platform, and enters the departure location and the destination. Thereby, the search for the travel route is started.

[0312] Step 2:

[0313] The terminal transmits the user's input information to the server. This information includes the departure location, the destination, and the current time.

[0314] Step 3:

[0315] The server accesses an external traffic information database based on the transmitted information, and obtains transfer information including the optimal transfer route, travel time, and fare.

[0316] Step 4:

[0317] The server uses the obtained transfer information to query the barrier-free information of each location from the internal database. The main information includes the presence or absence of elevators and multi-purpose toilets.

[0318] Step 5:

[0319] The emotion engine on the server analyzes voice input and video data from the device to recognize the user's emotional state. This allows for an assessment of the current stress level and other factors.

[0320] Step 6:

[0321] The server uses recognized emotional data to generate AI-powered alternative routes and support information appropriate to the user's state. This includes suggesting alternative routes to reduce stress and places to stop for a change of pace.

[0322] Step 7:

[0323] The server packages transfer information, accessibility information, and emotion-based suggestions and sends them to the terminal.

[0324] Step 8:

[0325] The terminal visually displays the received information to the user. This allows the user to check accessibility information and emotionally tailored suggestions along with their travel route, enabling them to plan the most optimal journey overall.

[0326] Step 9:

[0327] Users make travel decisions based on the information presented and execute travel plans that suit their needs.

[0328] (Example 2)

[0329] 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".

[0330] While there is a wealth of information available regarding accessibility and optimal transfer methods for using public transportation, systems that are easily accessible to people with mobility limitations are scarce. Furthermore, there is a need to reduce the psychological burden during travel. In particular, the lack of systems that can provide appropriate support tailored to the user's emotions and psychological state is a significant challenge.

[0331] 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.

[0332] In this invention, the server includes means for acquiring traffic information based on user input data, means for collecting barrier-free information, and means for using a generative AI model that analyzes the user's emotions and proposes appropriate content. This makes it possible to provide users with mobility limitations with support that reduces their psychological burden, along with presenting them with the optimal barrier-free route.

[0333] A "terminal" is a general term for devices that allow users to input their departure and destination points and that transmit information to a server.

[0334] "External information sources" refer to databases and third-party information systems that provide data such as traffic information and accessibility information.

[0335] "Barrier-free information" refers to information indicating the availability of facilities and equipment relevant to wheelchair users and people with mobility limitations, and includes data on the installation of elevators and multi-purpose restrooms.

[0336] A "detour route" refers to a more accessible alternative travel route proposed when the intended route includes points that are not barrier-free.

[0337] An "emotion analysis engine" is software or an algorithm used to evaluate a user's psychological state and emotions based on their voice and video data.

[0338] A "generative AI model" is a system that uses artificial intelligence technology to suggest appropriate alternative paths and content to users based on the results of analyzing their emotions.

[0339] A "data analysis algorithm" refers to mathematical methods and processes used to calculate the optimal alternative path based on input data.

[0340] This invention is a system designed to enhance convenience for users with mobility limitations when using public transportation. The system begins with the user using a terminal to input their departure and destination points. The terminal can be a general-purpose computer or smartphone, and it is assumed that it is connected to the internet.

[0341] The terminal sends user input data to the server. The server collaborates with external sources that provide traffic information. This allows the server to obtain transfer information based on the entered departure and destination points. The server also collects accessibility information for each station. This information specifically includes the availability of elevators and accessible restrooms.

[0342] Furthermore, the server is equipped with an emotion analysis engine. This engine is software that evaluates the user's psychological state and emotions based on audio data transmitted from the terminal and video data from the camera. If the server determines that the user's stress level is high, it uses a generative AI model to suggest alternative routes or relaxing content based on that data.

[0343] For example, if it is determined that a wheelchair user needs to avoid the afternoon rush hour, the generative AI model can suggest less crowded times or places to rest at cafes. In this way, users can develop optimal travel strategies tailored to their own emotional state.

[0344] An example of a prompt message would be: "Please tell me the best route for my next trip. My departure point is Tokyo Station, and my destination is Shinjuku Station. Please suggest stress-free options, taking into account factors such as the availability of elevators and congestion levels."

[0345] Through this invention, users can improve the convenience of travel and gain a sense of psychological security.

[0346] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0347] Step 1:

[0348] The user uses the terminal to enter their departure and destination points. The terminal stores this data digitally when the user enters "Tokyo Station to Shinjuku Station" into the application's designated input field. This data forms the basis for subsequent retrieval of transportation information.

[0349] Step 2:

[0350] The terminal sends the user-entered departure and destination data to the server. Here, the terminal securely transfers this information to the server via the internet. Upon receiving this input data, the server prepares to begin accessing the database for the next processing step.

[0351] Step 3:

[0352] The server accesses an external traffic information database and obtains the optimal transfer route based on the input data. Specifically, the server queries the database to obtain the calculated fastest route and the simplest transfer path. The results are stored on the server as digital data.

[0353] Step 4:

[0354] The server then collects additional accessibility information for each station related to the acquired traffic information. Here, the server performs another database query to obtain data on the presence of elevators and steps. The obtained information is stored on the server as part of the user's travel plan.

[0355] Step 5:

[0356] The server uses an emotion analysis engine to analyze voice and image data from the user and evaluate their psychological state. This input includes the user's facial expressions and tone of voice. The emotion analysis engine analyzes this data to quantify stress levels and psychological state. The results are stored on the server and used for subsequent processing.

[0357] Step 6:

[0358] The server uses a generative AI model to suggest alternative routes and content based on the user's emotional data. This model generates suggestions such as less crowded routes or relaxing rest areas, depending on the user's stress level. The generated suggestions are customized to be useful to the user.

[0359] Step 7:

[0360] The terminal displays transfer information, accessibility information, and suggestions based on sentiment analysis received from the server to the user. The terminal presents this information in a visually easy-to-understand format, helping the user decide on a travel route based on it. This output allows the user to select the safest and most optimal route and adjust their travel plan accordingly.

[0361] (Application Example 2)

[0362] 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."

[0363] In public transportation and food delivery services, technologies that ensure users can travel or wait comfortably are still not fully established. In particular, optimizing route selection and content suggestions while considering users' emotions and psychological states is difficult with current technology. Therefore, there is a need for systems that reduce stress and improve convenience.

[0364] 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.

[0365] In this invention, the server includes an input device means for the user to input their departure and destination points, a device means for analyzing the user's emotional state and generating suggestions tailored to that state, and a device means for presenting the optimal route and content based on those suggestions. This optimizes transportation and waiting time services based on the user's psychological state, reducing stress and enabling the provision of a comfortable service.

[0366] An "input device" is a device that has the function of allowing the user to specify the origin and destination.

[0367] "Travel information" refers to information about transportation and routes obtained based on the entered departure and destination locations.

[0368] "Convenience information" refers to information about facilities and services that are easily accessible to people with mobility limitations at locations related to their travel information.

[0369] A "detour route" is an alternative route generated when traveling to avoid inconvenient locations.

[0370] "Emotional state" refers to data that indicates the user's psychological or emotional state.

[0371] A "proposal generation device" is a device that analyzes the user's emotional state and generates appropriate travel routes and service content.

[0372] A "content-presenting device" is a device that has the function of presenting suggested travel routes and service details to a user visually or audibly.

[0373] This system includes an input device for the user to enter their departure and destination points. Based on the user's input, the server retrieves travel information from an external database. The server then collects relevant convenience information based on the retrieved travel information and activates emotion assessment software to evaluate the user's emotional state.

[0374] Emotion assessment utilizes data collected via voice input devices and cameras. Based on this data, emotion analysis software analyzes the user's psychological state in real time and determines their stress level. This process employs technologies such as speech recognition libraries and image recognition algorithms.

[0375] If the user's emotional state indicates stress, the server uses a generative AI model to suggest optimal alternative routes and relaxing content. These suggestions are displayed on the user's device through a content-displaying device. The user can confirm the suggested routes and content through visual or audio guidance. This allows the user to receive a service optimized according to their current psychological state.

[0376] A concrete example would be a situation where, when a user is experiencing stress from their commute, this system plays music that is most relaxing for the user and provides an alternative route to avoid congestion.

[0377] Example prompt to input into the generating AI model: "The user is tired and needs to relax. Please suggest the best route and content suitable for this state."

[0378] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0379] Step 1:

[0380] The user enters their departure and destination points using their device. This input data is sent to the server and used as foundational data for extracting travel information. Specifically, the input data is passed to the server via an API, and the server retrieves the desired travel information from an external database based on the input values.

[0381] Step 2:

[0382] The server analyzes the acquired travel information and collects relevant convenience information. At this stage, a data processing algorithm is used to evaluate the degree of convenience regarding the travel route, and information is retrieved from the convenience database. Detailed convenience information is provided as output.

[0383] Step 3:

[0384] The device initiates an emotion assessment process using voice and image data provided by the user. In this step, advanced speech recognition software and image recognition algorithms are used to analyze the user's emotional state. The server outputs the emotional state as numerical data based on the input data, determining the user's current psychological state.

[0385] Step 4:

[0386] The server utilizes a generative AI model to generate optimal suggestions that take into account the user's emotional state. This prompt includes information describing the user's state, and the AI ​​suggests the best route or relaxing content. This output serves as guidance for improving the user's original state.

[0387] Step 5:

[0388] The server transfers the generated suggestions to the terminal and presents them to the user through a content display device. The user can review the suggested routes and content, and select and use them as needed. As a final output, the user can enjoy a stress-free and convenient service.

[0389] 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.

[0390] 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.

[0391] 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.

[0392] [Third Embodiment]

[0393] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0394] 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.

[0395] 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).

[0396] 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.

[0397] 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.

[0398] 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).

[0399] 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.

[0400] 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.

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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".

[0405] This invention is a barrier-free information provision system for improving the convenience of public transportation for people with mobility limitations. The system obtains transfer information and related barrier-free information from the user upon inputting their departure and destination points, and provides alternative routes if non-barrier-free stations are included.

[0406] First, the user accesses a dedicated application or website using a device such as a smartphone or computer and enters their departure and destination points. The device then sends this information to a server. Based on the received data, the server accesses an external transportation information database to obtain the optimal transfer route. This transfer information includes necessary stations, intermediate stops, travel time, and fares.

[0407] The server then accesses a dedicated accessibility information database to check for the availability of barrier-free facilities at each station. It collects information on facilities such as elevators and multi-purpose restrooms. If there are stations without barrier-free facilities along the route, the server uses a generation AI to calculate an alternative route. This alternative route is designed with the user's convenience in mind, providing the shortest and most comfortable route.

[0408] The acquired information is sent back to the device and displayed visually. Users can intuitively check routes on their devices, making it easy to plan their travel. For example, if a wheelchair user wants to use a train station in Tokyo, the server will provide information on available elevators and, if necessary, guide them on a route that bypasses stations without elevators. Similarly, when parents with young children plan to travel with a stroller, convenient routes are provided.

[0409] This system is optimized to meet the diverse needs of users of public transportation and to improve the efficiency of travel.

[0410] The following describes the processing flow.

[0411] Step 1:

[0412] Users access a dedicated app or website using their own devices and enter their departure and destination locations. This information is then sent to the server as data collected through the user interface (UI).

[0413] Step 2:

[0414] Based on the received origin and destination data, the server accesses an external traffic information database to retrieve corresponding transfer information. This information includes the travel route, travel time, and fare.

[0415] Step 3:

[0416] Based on the acquired transfer information, the server queries a dedicated accessibility information database to determine the availability of barrier-free facilities at each station. This allows it to collect information such as the presence of elevators and accessible restrooms.

[0417] Step 4:

[0418] The server checks the facilities at each station included in the route, and if there are stations that are not barrier-free, such as those without elevators, it uses a generation AI to calculate an alternative route. The alternative route is optimized with user convenience in mind and designed as an alternative route.

[0419] Step 5:

[0420] The server packages together regular transfer information, accessibility information for each station, and alternative route information as needed, and sends it to the terminal.

[0421] Step 6:

[0422] The terminal analyzes all information retrieved from the server and displays it visually to the user. This allows the user to intuitively understand transfer routes, accessibility information, and alternative routes.

[0423] Step 7:

[0424] Based on the displayed information, users can create an appropriate travel plan. They select their planned route and prepare to depart.

[0425] (Example 1)

[0426] 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."

[0427] When using public transportation, there are challenges in mitigating the inconveniences faced by people with mobility limitations and ensuring safe and comfortable travel. In particular, wheelchair users and those with strollers often struggle to find optimal routes that avoid non-barrier-free locations.

[0428] 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.

[0429] In this invention, the server includes a device means for the user to input a starting point and an ending point; means for acquiring connection information based on the input starting point and ending point; and means for collecting location accessibility information related to the acquired connection information. This makes it possible to provide an appropriate travel route that meets the needs of each user.

[0430] "Users" refer to people who use the system to plan their travel using public transportation.

[0431] "Starting point" refers to the point where a user begins their journey using public transportation.

[0432] "Terminal destination" refers to the point where a user ends their journey using public transportation.

[0433] "Connection information" refers to information about the means of transportation and routes from the starting point to the final destination.

[0434] "Accessibility information" refers to information regarding the availability of facilities and services for users with mobility limitations at each location.

[0435] A "detour route" refers to an alternative route provided to users to reach their destination while avoiding inaccessible points.

[0436] A "generative AI model" refers to a machine learning algorithm that generates new information or routes based on data.

[0437] A "device" refers to an electronic device used by a user to operate a system, and specifically includes smartphones and computers.

[0438] A description of embodiments for carrying out the present invention will be provided.

[0439] Users access the system's dedicated application or website using devices such as smartphones or computers. Through the user interface on their device, users can input their starting and ending locations. The entered information is transmitted to the server via the internet.

[0440] The server accesses an external transportation database based on the received origin and destination data to obtain the most suitable connection information. This process utilizes APIs that interface with transportation schedules and congestion levels. Next, the server retrieves accessibility information for each location from a dedicated database. This information includes the availability of facilities such as elevators and accessible restrooms.

[0441] If an inaccessible location is included in the route, the server uses a generative AI model to generate a new detour route. The generative AI model uses machine learning algorithms to design the optimal detour route tailored to the user's needs. In doing so, the generative AI model takes into account traffic conditions and the characteristics of each user.

[0442] The acquired and generated information is then sent back to the terminal and provided to the user through an intuitive visual display. The user can easily plan their travel based on the displayed information.

[0443] As a concrete example, if a wheelchair user is traveling from one station in a city to another, the server will provide information on elevators and accessible restrooms at that station. Furthermore, by suggesting alternative routes as needed, the server can show the user the most suitable travel route. An example of a prompt message is, "Please provide a barrier-free route from departure point: City A Station to destination: City B Station."

[0444] This system aims to meet the needs of various users with mobility limitations and to make public transportation more accessible.

[0445] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0446] Step 1:

[0447] The terminal receives the origin and destination locations via a dedicated application or website connected to by the user. The entered data (origin and destination) is temporarily stored on the terminal and prepared to be sent to the server for the next processing step.

[0448] Step 2:

[0449] The terminal sends the origin and destination information it holds to the server. HTTP requests are typically used for this process. The terminal displays the transmission status as output. Error checking is also performed at this step to ensure the data is transmitted correctly.

[0450] Step 3:

[0451] The server uses the received origin and destination data to access an external transportation database and retrieve connection information. It obtains transportation schedules and transfer information via the database API and calculates the optimal route. As a result of this calculation, connection information (route, travel time, and cost) is generated and stored on the server.

[0452] Step 4:

[0453] The server accesses a dedicated database to retrieve accessibility information for each location related to the connection information. It queries the database for accessibility information (availability of facilities, detailed information) and stores it together with the connection information. The output of this step is an information set containing the accessibility status of each location.

[0454] Step 5:

[0455] If the server encounters an inaccessible point along the route, it uses a generative AI model to generate an alternative route. Here, based on the input information (information about inaccessible points), a machine learning algorithm calculates the optimal alternative route and generates alternative route information as output.

[0456] Step 6:

[0457] The server aggregates the acquired and generated connection information, accessibility information, and detour route information, and sends it to the terminal. The output information is converted into a format that can be displayed on the user interface, preparing it for intuitive display.

[0458] Step 7:

[0459] The terminal receives information sent from the server and displays it visually on the user interface. This display includes selectable routes, accessibility information, and alternative routes. Based on this, the user can create the best travel plan.

[0460] (Application Example 1)

[0461] 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."

[0462] When people with mobility limitations use physical stores or public facilities, they often face the challenge of not being able to easily obtain barrier-free route information, making comfortable travel difficult. This invention aims to solve this problem and provide a system that allows users to reach their destinations with peace of mind.

[0463] 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.

[0464] In this invention, the server includes an information terminal means for the user to input a departure point and destination, means for acquiring route information based on the input departure point and destination, and means for collecting barrier-free facility information for points related to the acquired route information. This enables users to easily obtain barrier-free route information and reach their destination comfortably and efficiently.

[0465] An "information terminal" is a device that allows users to input information about their departure and destination locations, and it is equipped with communication capabilities.

[0466] "Route information" refers to information about transfers and travel based on the entered departure and destination points.

[0467] "Barrier-free facilities information" refers to information regarding the availability of facilities that can be used by wheelchair users and people with disabilities.

[0468] "Generative artificial intelligence" is a technology that uses machine learning algorithms to generate the optimal alternative path.

[0469] An "alternative route" is an optimized travel path designed to avoid non-barrier-free locations.

[0470] To implement this invention, the following system will be constructed.

[0471] The server receives origin and destination data entered by the user from an information terminal. This information is entered via a smartphone or tablet device equipped with a communication module. The server first accesses an external geographic information API (e.g., Google Maps API) based on the input data to obtain the optimal route information from the origin to the destination. This route information includes points of passage and transfer information.

[0472] The server then accesses the Accessibility Facilities Information API to check for the presence of barrier-free facilities along the route obtained from the Geographic Information API. Specifically, it retrieves information regarding the presence of elevators and accessible restrooms.

[0473] If there are non-barrier-free points along the route, the server generates an alternative route using a generative AI model (e.g., OpenAI's GPT model). In this process, prompts are input to the generative AI to calculate an optimized alternative route.

[0474] Example prompt: "Please suggest an accessible route to a specific store. Please include information about elevators and ramps."

[0475] The user's device visually displays barrier-free route information and alternative route information transmitted from the server. This allows the user to easily understand the route to their destination and efficiently plan their journey.

[0476] For example, in a shopping mall, if a user wants to visit a specific store, they can input their information into a terminal, which will then display the shortest route that takes accessibility into account. This allows wheelchair users and parents with strollers to enjoy shopping with peace of mind.

[0477] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0478] Step 1:

[0479] The user enters their departure and destination locations using an information terminal. The departure and destination locations are specified in the user interface, and the terminal sends this information to the server. At this point, the input is the geographical location information selected by the user.

[0480] Step 2:

[0481] Based on the received origin and destination information, the server accesses a geographic information API to obtain optimal route information. The API outputs data related to the travel route. This data includes points of passage, travel time, and possible transfer information. The server organizes the received information and stores it in a format that can be used for the user's travel planning.

[0482] Step 3:

[0483] The server accesses the Accessibility Facilities Information API based on the route information. From this API, it retrieves data regarding the presence or absence of elevators and accessible restrooms at each point along the route. The input is location information along the route, and the output is the presence or absence of accessibility facilities at each point.

[0484] Step 4:

[0485] The server uses generated artificial intelligence to create alternative routes that avoid non-barrier-free points, based on the acquired barrier-free facility information. This process involves providing prompts to the generating AI model to calculate an optimized alternative route. The input is the current route information and barrier-free facility information, and the output is new route information that takes barrier-free access into account. Specifically, the calculated results are adjusted by prompts generated by the AI, and detour routes are suggested if necessary.

[0486] Step 5:

[0487] The server sends alternative routes and related information to the user's terminal. The terminal uses the received data to visually display the route on a map. The input is route data from the server, and the output is a route display that the user can visually confirm. This allows the user to intuitively confirm the suggested travel route and plan for safe travel.

[0488] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0489] This invention is a system designed to enhance convenience for users when using public transportation and to reduce the psychological burden during travel. In particular, it provides barrier-free information to people with mobility limitations, suggests alternative routes when necessary, and not only recognizes the user's emotions but also enables appropriate support.

[0490] The process begins with the user accessing a dedicated application or web platform using a terminal and entering their departure and destination points. The terminal sends this information to a server, which retrieves transfer information from an external transportation database based on the entered data. Simultaneously, accessibility information for each station is also checked, and the status of facilities such as elevators and accessible restrooms is collected.

[0491] Furthermore, the server is equipped with an emotion engine that evaluates the user's emotions and psychological state in real time through voice input and camera. If the system determines that the user's stress level is high, the generating AI will use this emotion data to suggest alternative routes, alternative paths, or relaxing content. This allows users to receive services tailored to their mental state, not just choose a mode of transportation.

[0492] Information is displayed to users in an easy-to-understand format via their devices. Users can review transfer routes, accessibility information, and suggestions from the emotional engine, and then formulate the optimal travel strategy based on this information. For example, if it is determined that a wheelchair user should avoid the afternoon rush hour, the emotional engine can suggest less crowded times or places to relax, such as cafes.

[0493] The aim of this system is to improve convenience and provide a sense of psychological security, thereby creating an environment where users can travel more comfortably.

[0494] The following describes the processing flow.

[0495] Step 1:

[0496] Users access a dedicated application or web platform using a mobile device or computer and enter their departure and destination locations. This initiates the search for travel routes.

[0497] Step 2:

[0498] The terminal sends user input information to the server. This information includes the origin, destination, and current time.

[0499] Step 3:

[0500] Based on the transmitted information, the server accesses an external traffic information database to obtain transfer information, including the optimal transfer route, travel time, and fare.

[0501] Step 4:

[0502] The server uses the acquired transfer information to query its internal database for accessibility information at each location. Key information includes the availability of elevators and accessible restrooms.

[0503] Step 5:

[0504] The emotion engine on the server analyzes voice input and video data from the device to recognize the user's emotional state. This allows for an assessment of the current stress level and other factors.

[0505] Step 6:

[0506] The server uses recognized emotional data to generate AI-powered alternative routes and support information appropriate to the user's state. This includes suggesting alternative routes to reduce stress and places to stop for a change of pace.

[0507] Step 7:

[0508] The server packages transfer information, accessibility information, and emotion-based suggestions and sends them to the terminal.

[0509] Step 8:

[0510] The terminal visually displays the received information to the user. This allows the user to check accessibility information and emotionally tailored suggestions along with their travel route, enabling them to plan the most optimal journey overall.

[0511] Step 9:

[0512] Users make travel decisions based on the information presented and execute travel plans that suit their needs.

[0513] (Example 2)

[0514] 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."

[0515] While there is a wealth of information available regarding accessibility and optimal transfer methods for using public transportation, systems that are easily accessible to people with mobility limitations are scarce. Furthermore, there is a need to reduce the psychological burden during travel. In particular, the lack of systems that can provide appropriate support tailored to the user's emotions and psychological state is a significant challenge.

[0516] 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.

[0517] In this invention, the server includes means for acquiring traffic information based on user input data, means for collecting barrier-free information, and means for using a generative AI model that analyzes the user's emotions and proposes appropriate content. This makes it possible to provide users with mobility limitations with support that reduces their psychological burden, along with presenting them with the optimal barrier-free route.

[0518] A "terminal" is a general term for devices that allow users to input their departure and destination points and that transmit information to a server.

[0519] "External information sources" refer to databases and third-party information systems that provide data such as traffic information and accessibility information.

[0520] "Barrier-free information" refers to information indicating the availability of facilities and equipment relevant to wheelchair users and people with mobility limitations, and includes data on the installation of elevators and multi-purpose restrooms.

[0521] A "detour route" refers to a more accessible alternative travel route proposed when the intended route includes points that are not barrier-free.

[0522] An "emotion analysis engine" is software or an algorithm used to evaluate a user's psychological state and emotions based on their voice and video data.

[0523] A "generative AI model" is a system that uses artificial intelligence technology to suggest appropriate alternative paths and content to users based on the results of analyzing their emotions.

[0524] A "data analysis algorithm" refers to mathematical methods and processes used to calculate the optimal alternative path based on input data.

[0525] This invention is a system designed to enhance convenience for users with mobility limitations when using public transportation. The system begins with the user using a terminal to input their departure and destination points. The terminal can be a general-purpose computer or smartphone, and it is assumed that it is connected to the internet.

[0526] The terminal sends user input data to the server. The server collaborates with external sources that provide traffic information. This allows the server to obtain transfer information based on the entered departure and destination points. The server also collects accessibility information for each station. This information specifically includes the availability of elevators and accessible restrooms.

[0527] Furthermore, the server is equipped with an emotion analysis engine. This engine is software that evaluates the user's psychological state and emotions based on audio data transmitted from the terminal and video data from the camera. If the server determines that the user's stress level is high, it uses a generative AI model to suggest alternative routes or relaxing content based on that data.

[0528] For example, if it is determined that a wheelchair user needs to avoid the afternoon rush hour, the generative AI model can suggest less crowded times or places to rest at cafes. In this way, users can develop optimal travel strategies tailored to their own emotional state.

[0529] An example of a prompt message would be: "Please tell me the best route for my next trip. My departure point is Tokyo Station, and my destination is Shinjuku Station. Please suggest stress-free options, taking into account factors such as the availability of elevators and congestion levels."

[0530] Through this invention, users can improve the convenience of travel and gain a sense of psychological security.

[0531] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0532] Step 1:

[0533] The user uses the terminal to enter their departure and destination points. The terminal stores this data digitally when the user enters "Tokyo Station to Shinjuku Station" into the application's designated input field. This data forms the basis for subsequent retrieval of transportation information.

[0534] Step 2:

[0535] The terminal sends the user-entered departure and destination data to the server. Here, the terminal securely transfers this information to the server via the internet. Upon receiving this input data, the server prepares to begin accessing the database for the next processing step.

[0536] Step 3:

[0537] The server accesses an external traffic information database and obtains the optimal transfer route based on the input data. Specifically, the server queries the database to obtain the calculated fastest route and the simplest transfer path. The results are stored on the server as digital data.

[0538] Step 4:

[0539] The server then collects additional accessibility information for each station related to the acquired traffic information. Here, the server performs another database query to obtain data on the presence of elevators and steps. The obtained information is stored on the server as part of the user's travel plan.

[0540] Step 5:

[0541] The server uses an emotion analysis engine to analyze voice and image data from the user and evaluate their psychological state. This input includes the user's facial expressions and tone of voice. The emotion analysis engine analyzes this data to quantify stress levels and psychological state. The results are stored on the server and used for subsequent processing.

[0542] Step 6:

[0543] The server uses a generative AI model to suggest alternative routes and content based on the user's emotional data. This model generates suggestions such as less crowded routes or relaxing rest areas, depending on the user's stress level. The generated suggestions are customized to be useful to the user.

[0544] Step 7:

[0545] The terminal displays transfer information, accessibility information, and suggestions based on sentiment analysis received from the server to the user. The terminal presents this information in a visually easy-to-understand format, helping the user decide on a travel route based on it. This output allows the user to select the safest and most optimal route and adjust their travel plan accordingly.

[0546] (Application Example 2)

[0547] 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."

[0548] In public transportation and food delivery services, technologies that ensure users can travel or wait comfortably are still not fully established. In particular, optimizing route selection and content suggestions while considering users' emotions and psychological states is difficult with current technology. Therefore, there is a need for systems that reduce stress and improve convenience.

[0549] 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.

[0550] In this invention, the server includes an input device means for the user to input their departure and destination points, a device means for analyzing the user's emotional state and generating suggestions tailored to that state, and a device means for presenting the optimal route and content based on those suggestions. This optimizes transportation and waiting time services based on the user's psychological state, reducing stress and enabling the provision of a comfortable service.

[0551] An "input device" is a device that has the function of allowing the user to specify the origin and destination.

[0552] "Travel information" refers to information about transportation and routes obtained based on the entered departure and destination locations.

[0553] "Convenience information" refers to information about facilities and services that are easily accessible to people with mobility limitations at locations related to their travel information.

[0554] A "detour route" is an alternative route generated when traveling to avoid inconvenient locations.

[0555] "Emotional state" refers to data that indicates the user's psychological or emotional state.

[0556] A "proposal generation device" is a device that analyzes the user's emotional state and generates appropriate travel routes and service content.

[0557] A "content-presenting device" is a device that has the function of presenting suggested travel routes and service details to a user visually or audibly.

[0558] This system includes an input device for the user to enter their departure and destination points. Based on the user's input, the server retrieves travel information from an external database. The server then collects relevant convenience information based on the retrieved travel information and activates emotion assessment software to evaluate the user's emotional state.

[0559] Emotion assessment utilizes data collected via voice input devices and cameras. Based on this data, emotion analysis software analyzes the user's psychological state in real time and determines their stress level. This process employs technologies such as speech recognition libraries and image recognition algorithms.

[0560] If the user's emotional state indicates stress, the server uses a generative AI model to suggest optimal alternative routes and relaxing content. These suggestions are displayed on the user's device through a content-displaying device. The user can confirm the suggested routes and content through visual or audio guidance. This allows the user to receive a service optimized according to their current psychological state.

[0561] A concrete example would be a situation where, when a user is experiencing stress from their commute, this system plays music that is most relaxing for the user and provides an alternative route to avoid congestion.

[0562] Example prompt to input into the generating AI model: "The user is tired and needs to relax. Please suggest the best route and content suitable for this state."

[0563] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0564] Step 1:

[0565] The user enters their departure and destination points using their device. This input data is sent to the server and used as foundational data for extracting travel information. Specifically, the input data is passed to the server via an API, and the server retrieves the desired travel information from an external database based on the input values.

[0566] Step 2:

[0567] The server analyzes the acquired travel information and collects relevant convenience information. At this stage, a data processing algorithm is used to evaluate the degree of convenience regarding the travel route, and information is retrieved from the convenience database. Detailed convenience information is provided as output.

[0568] Step 3:

[0569] The device initiates an emotion assessment process using voice and image data provided by the user. In this step, advanced speech recognition software and image recognition algorithms are used to analyze the user's emotional state. The server outputs the emotional state as numerical data based on the input data, determining the user's current psychological state.

[0570] Step 4:

[0571] The server utilizes a generative AI model to generate optimal suggestions that take into account the user's emotional state. This prompt includes information describing the user's state, and the AI ​​suggests the best route or relaxing content. This output serves as guidance for improving the user's original state.

[0572] Step 5:

[0573] The server transfers the generated suggestions to the terminal and presents them to the user through a content display device. The user can review the suggested routes and content, and select and use them as needed. As a final output, the user can enjoy a stress-free and convenient service.

[0574] 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.

[0575] 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.

[0576] 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.

[0577] [Fourth Embodiment]

[0578] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0579] 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.

[0580] 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).

[0581] 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.

[0582] 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.

[0583] 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).

[0584] 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.

[0585] 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.

[0586] 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.

[0587] 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.

[0588] 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.

[0589] 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.

[0590] 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".

[0591] This invention is a barrier-free information provision system for improving the convenience of public transportation for people with mobility limitations. The system obtains transfer information and related barrier-free information from the user upon inputting their departure and destination points, and provides alternative routes if non-barrier-free stations are included.

[0592] First, the user accesses a dedicated application or website using a device such as a smartphone or computer and enters their departure and destination points. The device then sends this information to a server. Based on the received data, the server accesses an external transportation information database to obtain the optimal transfer route. This transfer information includes necessary stations, intermediate stops, travel time, and fares.

[0593] The server then accesses a dedicated accessibility information database to check for the availability of barrier-free facilities at each station. It collects information on facilities such as elevators and multi-purpose restrooms. If there are stations without barrier-free facilities along the route, the server uses a generation AI to calculate an alternative route. This alternative route is designed with the user's convenience in mind, providing the shortest and most comfortable route.

[0594] The acquired information is sent back to the device and displayed visually. Users can intuitively check routes on their devices, making it easy to plan their travel. For example, if a wheelchair user wants to use a train station in Tokyo, the server will provide information on available elevators and, if necessary, guide them on a route that bypasses stations without elevators. Similarly, when parents with young children plan to travel with a stroller, convenient routes are provided.

[0595] This system is optimized to meet the diverse needs of users of public transportation and to improve the efficiency of travel.

[0596] The following describes the processing flow.

[0597] Step 1:

[0598] Users access a dedicated app or website using their own devices and enter their departure and destination locations. This information is then sent to the server as data collected through the user interface (UI).

[0599] Step 2:

[0600] Based on the received origin and destination data, the server accesses an external traffic information database to retrieve corresponding transfer information. This information includes the travel route, travel time, and fare.

[0601] Step 3:

[0602] Based on the acquired transfer information, the server queries a dedicated accessibility information database to determine the availability of barrier-free facilities at each station. This allows it to collect information such as the presence of elevators and accessible restrooms.

[0603] Step 4:

[0604] The server checks the facilities at each station included in the route, and if there are stations that are not barrier-free, such as those without elevators, it uses a generation AI to calculate an alternative route. The alternative route is optimized with user convenience in mind and designed as an alternative route.

[0605] Step 5:

[0606] The server packages together regular transfer information, accessibility information for each station, and alternative route information as needed, and sends it to the terminal.

[0607] Step 6:

[0608] The terminal analyzes all information retrieved from the server and displays it visually to the user. This allows the user to intuitively understand transfer routes, accessibility information, and alternative routes.

[0609] Step 7:

[0610] Based on the displayed information, users can create an appropriate travel plan. They select their planned route and prepare to depart.

[0611] (Example 1)

[0612] 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".

[0613] When using public transportation, there are challenges in mitigating the inconveniences faced by people with mobility limitations and ensuring safe and comfortable travel. In particular, wheelchair users and those with strollers often struggle to find optimal routes that avoid non-barrier-free locations.

[0614] 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.

[0615] In this invention, the server includes a device means for the user to input a starting point and an ending point; means for acquiring connection information based on the input starting point and ending point; and means for collecting location accessibility information related to the acquired connection information. This makes it possible to provide an appropriate travel route that meets the needs of each user.

[0616] "Users" refer to people who use the system to plan their travel using public transportation.

[0617] "Starting point" refers to the point where a user begins their journey using public transportation.

[0618] "Terminal destination" refers to the point where a user ends their journey using public transportation.

[0619] "Connection information" refers to information about the means of transportation and routes from the starting point to the final destination.

[0620] "Accessibility information" refers to information regarding the availability of facilities and services for users with mobility limitations at each location.

[0621] A "detour route" refers to an alternative route provided to users to reach their destination while avoiding inaccessible points.

[0622] A "generative AI model" refers to a machine learning algorithm that generates new information or routes based on data.

[0623] A "device" refers to an electronic device used by a user to operate a system, and specifically includes smartphones and computers.

[0624] A description of embodiments for carrying out the present invention will be provided.

[0625] Users access the system's dedicated application or website using devices such as smartphones or computers. Through the user interface on their device, users can input their starting and ending locations. The entered information is transmitted to the server via the internet.

[0626] The server accesses an external transportation database based on the received origin and destination data to obtain the most suitable connection information. This process utilizes APIs that interface with transportation schedules and congestion levels. Next, the server retrieves accessibility information for each location from a dedicated database. This information includes the availability of facilities such as elevators and accessible restrooms.

[0627] If an inaccessible location is included in the route, the server uses a generative AI model to generate a new detour route. The generative AI model uses machine learning algorithms to design the optimal detour route tailored to the user's needs. In doing so, the generative AI model takes into account traffic conditions and the characteristics of each user.

[0628] The acquired and generated information is then sent back to the terminal and provided to the user through an intuitive visual display. The user can easily plan their travel based on the displayed information.

[0629] As a concrete example, if a wheelchair user is traveling from one station in a city to another, the server will provide information on elevators and accessible restrooms at that station. Furthermore, by suggesting alternative routes as needed, the server can show the user the most suitable travel route. An example of a prompt message is, "Please provide a barrier-free route from departure point: City A Station to destination: City B Station."

[0630] This system aims to meet the needs of various users with mobility limitations and to make public transportation more accessible.

[0631] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0632] Step 1:

[0633] The terminal receives the origin and destination locations via a dedicated application or website connected to by the user. The entered data (origin and destination) is temporarily stored on the terminal and prepared to be sent to the server for the next processing step.

[0634] Step 2:

[0635] The terminal sends the origin and destination information it holds to the server. HTTP requests are typically used for this process. The terminal displays the transmission status as output. Error checking is also performed at this step to ensure the data is transmitted correctly.

[0636] Step 3:

[0637] The server uses the received origin and destination data to access an external transportation database and retrieve connection information. It obtains transportation schedules and transfer information via the database API and calculates the optimal route. As a result of this calculation, connection information (route, travel time, and cost) is generated and stored on the server.

[0638] Step 4:

[0639] The server accesses a dedicated database to retrieve accessibility information for each location related to the connection information. It queries the database for accessibility information (availability of facilities, detailed information) and stores it together with the connection information. The output of this step is an information set containing the accessibility status of each location.

[0640] Step 5:

[0641] If the server encounters an inaccessible point along the route, it uses a generative AI model to generate an alternative route. Here, based on the input information (information about inaccessible points), a machine learning algorithm calculates the optimal alternative route and generates alternative route information as output.

[0642] Step 6:

[0643] The server aggregates the acquired and generated connection information, accessibility information, and detour route information, and sends it to the terminal. The output information is converted into a format that can be displayed on the user interface, preparing it for intuitive display.

[0644] Step 7:

[0645] The terminal receives information sent from the server and displays it visually on the user interface. This display includes selectable routes, accessibility information, and alternative routes. Based on this, the user can create the best travel plan.

[0646] (Application Example 1)

[0647] 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".

[0648] When people with mobility limitations use physical stores or public facilities, they often face the challenge of not being able to easily obtain barrier-free route information, making comfortable travel difficult. This invention aims to solve this problem and provide a system that allows users to reach their destinations with peace of mind.

[0649] 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.

[0650] In this invention, the server includes an information terminal means for the user to input a departure point and destination, means for acquiring route information based on the input departure point and destination, and means for collecting barrier-free facility information for points related to the acquired route information. This enables users to easily obtain barrier-free route information and reach their destination comfortably and efficiently.

[0651] An "information terminal" is a device that allows users to input information about their departure and destination locations, and it is equipped with communication capabilities.

[0652] "Route information" refers to information about transfers and travel based on the entered departure and destination points.

[0653] "Barrier-free facilities information" refers to information regarding the availability of facilities that can be used by wheelchair users and people with disabilities.

[0654] "Generative artificial intelligence" is a technology that uses machine learning algorithms to generate the optimal alternative path.

[0655] An "alternative route" is an optimized travel path designed to avoid non-barrier-free locations.

[0656] To implement this invention, the following system will be constructed.

[0657] The server receives origin and destination data entered by the user from an information terminal. This information is entered via a smartphone or tablet device equipped with a communication module. The server first accesses an external geographic information API (e.g., Google Maps API) based on the input data to obtain the optimal route information from the origin to the destination. This route information includes points of passage and transfer information.

[0658] The server then accesses the Accessibility Facilities Information API to check for the presence of barrier-free facilities along the route obtained from the Geographic Information API. Specifically, it retrieves information regarding the presence of elevators and accessible restrooms.

[0659] If there are non-barrier-free points along the route, the server generates an alternative route using a generative AI model (e.g., OpenAI's GPT model). In this process, prompts are input to the generative AI to calculate an optimized alternative route.

[0660] Example prompt: "Please suggest an accessible route to a specific store. Please include information about elevators and ramps."

[0661] The user's device visually displays barrier-free route information and alternative route information transmitted from the server. This allows the user to easily understand the route to their destination and efficiently plan their journey.

[0662] For example, in a shopping mall, if a user wants to visit a specific store, they can input their information into a terminal, which will then display the shortest route that takes accessibility into account. This allows wheelchair users and parents with strollers to enjoy shopping with peace of mind.

[0663] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0664] Step 1:

[0665] The user enters their departure and destination locations using an information terminal. The departure and destination locations are specified in the user interface, and the terminal sends this information to the server. At this point, the input is the geographical location information selected by the user.

[0666] Step 2:

[0667] Based on the received origin and destination information, the server accesses a geographic information API to obtain optimal route information. The API outputs data related to the travel route. This data includes points of passage, travel time, and possible transfer information. The server organizes the received information and stores it in a format that can be used for the user's travel planning.

[0668] Step 3:

[0669] The server accesses the Accessibility Facilities Information API based on the route information. From this API, it retrieves data regarding the presence or absence of elevators and accessible restrooms at each point along the route. The input is location information along the route, and the output is the presence or absence of accessibility facilities at each point.

[0670] Step 4:

[0671] The server uses generated artificial intelligence to create alternative routes that avoid non-barrier-free points, based on the acquired barrier-free facility information. This process involves providing prompts to the generating AI model to calculate an optimized alternative route. The input is the current route information and barrier-free facility information, and the output is new route information that takes barrier-free access into account. Specifically, the calculated results are adjusted by prompts generated by the AI, and detour routes are suggested if necessary.

[0672] Step 5:

[0673] The server sends alternative routes and related information to the user's terminal. The terminal uses the received data to visually display the route on a map. The input is route data from the server, and the output is a route display that the user can visually confirm. This allows the user to intuitively confirm the suggested travel route and plan for safe travel.

[0674] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0675] This invention is a system designed to enhance convenience for users when using public transportation and to reduce the psychological burden during travel. In particular, it provides barrier-free information to people with mobility limitations, suggests alternative routes when necessary, and not only recognizes the user's emotions but also enables appropriate support.

[0676] The process begins with the user accessing a dedicated application or web platform using a terminal and entering their departure and destination points. The terminal sends this information to a server, which retrieves transfer information from an external transportation database based on the entered data. Simultaneously, accessibility information for each station is also checked, and the status of facilities such as elevators and accessible restrooms is collected.

[0677] Furthermore, the server is equipped with an emotion engine that evaluates the user's emotions and psychological state in real time through voice input and camera. If the system determines that the user's stress level is high, the generating AI will use this emotion data to suggest alternative routes, alternative paths, or relaxing content. This allows users to receive services tailored to their mental state, not just choose a mode of transportation.

[0678] Information is displayed to users in an easy-to-understand format via their devices. Users can review transfer routes, accessibility information, and suggestions from the emotional engine, and then formulate the optimal travel strategy based on this information. For example, if it is determined that a wheelchair user should avoid the afternoon rush hour, the emotional engine can suggest less crowded times or places to relax, such as cafes.

[0679] The aim of this system is to improve convenience and provide a sense of psychological security, thereby creating an environment where users can travel more comfortably.

[0680] The following describes the processing flow.

[0681] Step 1:

[0682] Users access a dedicated application or web platform using a mobile device or computer and enter their departure and destination locations. This initiates the search for travel routes.

[0683] Step 2:

[0684] The terminal sends user input information to the server. This information includes the origin, destination, and current time.

[0685] Step 3:

[0686] Based on the transmitted information, the server accesses an external traffic information database to obtain transfer information, including the optimal transfer route, travel time, and fare.

[0687] Step 4:

[0688] The server uses the acquired transfer information to query its internal database for accessibility information at each location. Key information includes the availability of elevators and accessible restrooms.

[0689] Step 5:

[0690] The emotion engine on the server analyzes voice input and video data from the device to recognize the user's emotional state. This allows for an assessment of the current stress level and other factors.

[0691] Step 6:

[0692] The server uses recognized emotional data to generate AI-powered alternative routes and support information appropriate to the user's state. This includes suggesting alternative routes to reduce stress and places to stop for a change of pace.

[0693] Step 7:

[0694] The server packages transfer information, accessibility information, and emotion-based suggestions and sends them to the terminal.

[0695] Step 8:

[0696] The terminal visually displays the received information to the user. This allows the user to check accessibility information and emotionally tailored suggestions along with their travel route, enabling them to plan the most optimal journey overall.

[0697] Step 9:

[0698] Users make travel decisions based on the information presented and execute travel plans that suit their needs.

[0699] (Example 2)

[0700] 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".

[0701] While there is a wealth of information available regarding accessibility and optimal transfer methods for using public transportation, systems that are easily accessible to people with mobility limitations are scarce. Furthermore, there is a need to reduce the psychological burden during travel. In particular, the lack of systems that can provide appropriate support tailored to the user's emotions and psychological state is a significant challenge.

[0702] 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.

[0703] In this invention, the server includes means for acquiring traffic information based on user input data, means for collecting barrier-free information, and means for using a generative AI model that analyzes the user's emotions and proposes appropriate content. This makes it possible to provide users with mobility limitations with support that reduces their psychological burden, along with presenting them with the optimal barrier-free route.

[0704] A "terminal" is a general term for devices that allow users to input their departure and destination points and that transmit information to a server.

[0705] "External information sources" refer to databases and third-party information systems that provide data such as traffic information and accessibility information.

[0706] "Barrier-free information" refers to information indicating the availability of facilities and equipment relevant to wheelchair users and people with mobility limitations, and includes data on the installation of elevators and multi-purpose restrooms.

[0707] A "detour route" refers to a more accessible alternative travel route proposed when the intended route includes points that are not barrier-free.

[0708] An "emotion analysis engine" is software or an algorithm used to evaluate a user's psychological state and emotions based on their voice and video data.

[0709] A "generative AI model" is a system that uses artificial intelligence technology to suggest appropriate alternative paths and content to users based on the results of analyzing their emotions.

[0710] A "data analysis algorithm" refers to mathematical methods and processes used to calculate the optimal alternative path based on input data.

[0711] This invention is a system designed to enhance convenience for users with mobility limitations when using public transportation. The system begins with the user using a terminal to input their departure and destination points. The terminal can be a general-purpose computer or smartphone, and it is assumed that it is connected to the internet.

[0712] The terminal sends user input data to the server. The server collaborates with external sources that provide traffic information. This allows the server to obtain transfer information based on the entered departure and destination points. The server also collects accessibility information for each station. This information specifically includes the availability of elevators and accessible restrooms.

[0713] Furthermore, the server is equipped with an emotion analysis engine. This engine is software that evaluates the user's psychological state and emotions based on audio data transmitted from the terminal and video data from the camera. If the server determines that the user's stress level is high, it uses a generative AI model to suggest alternative routes or relaxing content based on that data.

[0714] For example, if it is determined that a wheelchair user needs to avoid the afternoon rush hour, the generative AI model can suggest less crowded times or places to rest at cafes. In this way, users can develop optimal travel strategies tailored to their own emotional state.

[0715] An example of a prompt message would be: "Please tell me the best route for my next trip. My departure point is Tokyo Station, and my destination is Shinjuku Station. Please suggest stress-free options, taking into account factors such as the availability of elevators and congestion levels."

[0716] Through this invention, users can improve the convenience of travel and gain a sense of psychological security.

[0717] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0718] Step 1:

[0719] The user uses the terminal to enter their departure and destination points. The terminal stores this data digitally when the user enters "Tokyo Station to Shinjuku Station" into the application's designated input field. This data forms the basis for subsequent retrieval of transportation information.

[0720] Step 2:

[0721] The terminal sends the user-entered departure and destination data to the server. Here, the terminal securely transfers this information to the server via the internet. Upon receiving this input data, the server prepares to begin accessing the database for the next processing step.

[0722] Step 3:

[0723] The server accesses an external traffic information database and obtains the optimal transfer route based on the input data. Specifically, the server queries the database to obtain the calculated fastest route and the simplest transfer path. The results are stored on the server as digital data.

[0724] Step 4:

[0725] The server then collects additional accessibility information for each station related to the acquired traffic information. Here, the server performs another database query to obtain data on the presence of elevators and steps. The obtained information is stored on the server as part of the user's travel plan.

[0726] Step 5:

[0727] The server uses an emotion analysis engine to analyze voice and image data from the user and evaluate their psychological state. This input includes the user's facial expressions and tone of voice. The emotion analysis engine analyzes this data to quantify stress levels and psychological state. The results are stored on the server and used for subsequent processing.

[0728] Step 6:

[0729] The server uses a generative AI model to suggest alternative routes and content based on the user's emotional data. This model generates suggestions such as less crowded routes or relaxing rest areas, depending on the user's stress level. The generated suggestions are customized to be useful to the user.

[0730] Step 7:

[0731] The terminal displays transfer information, accessibility information, and suggestions based on sentiment analysis received from the server to the user. The terminal presents this information in a visually easy-to-understand format, helping the user decide on a travel route based on it. This output allows the user to select the safest and most optimal route and adjust their travel plan accordingly.

[0732] (Application Example 2)

[0733] 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".

[0734] In public transportation and food delivery services, technologies that ensure users can travel or wait comfortably are still not fully established. In particular, optimizing route selection and content suggestions while considering users' emotions and psychological states is difficult with current technology. Therefore, there is a need for systems that reduce stress and improve convenience.

[0735] 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.

[0736] In this invention, the server includes an input device means for the user to input their departure and destination points, a device means for analyzing the user's emotional state and generating suggestions tailored to that state, and a device means for presenting the optimal route and content based on those suggestions. This optimizes transportation and waiting time services based on the user's psychological state, reducing stress and enabling the provision of a comfortable service.

[0737] An "input device" is a device that has the function of allowing the user to specify the origin and destination.

[0738] "Travel information" refers to information about transportation and routes obtained based on the entered departure and destination locations.

[0739] "Convenience information" refers to information about facilities and services that are easily accessible to people with mobility limitations at locations related to their travel information.

[0740] A "detour route" is an alternative route generated when traveling to avoid inconvenient locations.

[0741] "Emotional state" refers to data that indicates the user's psychological or emotional state.

[0742] A "proposal generation device" is a device that analyzes the user's emotional state and generates appropriate travel routes and service content.

[0743] A "content-presenting device" is a device that has the function of presenting suggested travel routes and service details to a user visually or audibly.

[0744] This system includes an input device for the user to enter their departure and destination points. Based on the user's input, the server retrieves travel information from an external database. The server then collects relevant convenience information based on the retrieved travel information and activates emotion assessment software to evaluate the user's emotional state.

[0745] Emotion assessment utilizes data collected via voice input devices and cameras. Based on this data, emotion analysis software analyzes the user's psychological state in real time and determines their stress level. This process employs technologies such as speech recognition libraries and image recognition algorithms.

[0746] If the user's emotional state indicates stress, the server uses a generative AI model to suggest optimal alternative routes and relaxing content. These suggestions are displayed on the user's device through a content-displaying device. The user can confirm the suggested routes and content through visual or audio guidance. This allows the user to receive a service optimized according to their current psychological state.

[0747] A concrete example would be a situation where, when a user is experiencing stress from their commute, this system plays music that is most relaxing for the user and provides an alternative route to avoid congestion.

[0748] Example prompt to input into the generating AI model: "The user is tired and needs to relax. Please suggest the best route and content suitable for this state."

[0749] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0750] Step 1:

[0751] The user enters their departure and destination points using their device. This input data is sent to the server and used as foundational data for extracting travel information. Specifically, the input data is passed to the server via an API, and the server retrieves the desired travel information from an external database based on the input values.

[0752] Step 2:

[0753] The server analyzes the acquired travel information and collects relevant convenience information. At this stage, a data processing algorithm is used to evaluate the degree of convenience regarding the travel route, and information is retrieved from the convenience database. Detailed convenience information is provided as output.

[0754] Step 3:

[0755] The device initiates an emotion assessment process using voice and image data provided by the user. In this step, advanced speech recognition software and image recognition algorithms are used to analyze the user's emotional state. The server outputs the emotional state as numerical data based on the input data, determining the user's current psychological state.

[0756] Step 4:

[0757] The server utilizes a generative AI model to generate optimal suggestions that take into account the user's emotional state. This prompt includes information describing the user's state, and the AI ​​suggests the best route or relaxing content. This output serves as guidance for improving the user's original state.

[0758] Step 5:

[0759] The server transfers the generated suggestions to the terminal and presents them to the user through a content display device. The user can review the suggested routes and content, and select and use them as needed. As a final output, the user can enjoy a stress-free and convenient service.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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."

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] The following is further disclosed regarding the embodiments described above.

[0782] (Claim 1)

[0783] An input means for the user to enter the departure point and destination,

[0784] A means for obtaining transfer information based on the entered departure and destination points,

[0785] A means for collecting accessibility information for locations related to the acquired transfer information,

[0786] A means for generating a detour route when non-barrier-free points are included,

[0787] A system including means for displaying the aforementioned transfer information, accessibility information, and detour route information to the user.

[0788] (Claim 2)

[0789] The system according to claim 1, wherein the barrier-free information includes the presence or absence of elevators and multipurpose toilets for wheelchair users.

[0790] (Claim 3)

[0791] The system according to claim 1, wherein the detour route generation means calculates the optimal alternative route using a machine learning algorithm.

[0792] "Example 1"

[0793] (Claim 1)

[0794] A device means for the user to input the starting point and ending point,

[0795] A means for obtaining connection information based on the input origin and destination locations,

[0796] A means for collecting location accessibility information related to acquired connection information,

[0797] Means for generating a detour route when an inaccessible location is included,

[0798] Means for displaying the aforementioned connection information, accessibility information, and detour route information to the user,

[0799] A system that includes means for optimizing detour routes using a generative AI model.

[0800] (Claim 2)

[0801] The system according to claim 1, wherein the accessibility information includes the presence or absence of elevators and multipurpose facilities for wheelchair users.

[0802] (Claim 3)

[0803] The system according to claim 1, wherein the detour route generation means calculates the optimal alternative route using a machine learning method.

[0804] "Application Example 1"

[0805] (Claim 1)

[0806] An information terminal means for the user to input the departure point and destination,

[0807] A means for obtaining route information based on the entered departure and destination points,

[0808] A means for collecting barrier-free facility information at locations related to acquired route information,

[0809] A means for generating alternative routes using artificial intelligence when non-barrier-free locations are included,

[0810] A system including means for displaying the aforementioned route information, barrier-free facility information, and alternative route information to the user.

[0811] (Claim 2)

[0812] The system according to claim 1, wherein the barrier-free facility information includes whether or not there are elevators and multi-purpose sanitary facilities for wheelchair users.

[0813] (Claim 3)

[0814] The system according to claim 1, wherein the alternative route generation means calculates the shortest and most comfortable alternative route using an optimization algorithm.

[0815] "Example 2 of combining an emotion engine"

[0816] (Claim 1)

[0817] A data entry method using a terminal for the user to input the departure point and destination,

[0818] A means of obtaining traffic information from an external source based on the entered origin and destination,

[0819] A means of collecting accessibility information for locations related to acquired traffic information,

[0820] A means for generating a detour route when non-barrier-free points are included,

[0821] A means of using an emotion analysis engine to evaluate the user's emotional state,

[0822] A means of using a generative AI model that generates alternative paths and content to reduce user stress based on the results of emotion analysis,

[0823] Means for displaying the aforementioned traffic information, barrier-free information, detour route information, and suggestions based on sentiment analysis to the user.

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1, wherein the barrier-free information includes whether or not there are mobility support facilities for wheelchair users.

[0827] (Claim 3)

[0828] The system according to claim 1, wherein the detour route generation means calculates the optimal alternative route using a data analysis algorithm.

[0829] "Application example 2 when combining with an emotional engine"

[0830] (Claim 1)

[0831] An input device for the user to enter the departure point and destination,

[0832] A device that acquires travel information based on the input origin and destination,

[0833] A device for collecting convenience information of locations related to acquired travel information,

[0834] A device that generates a detour route when inconvenient locations are included,

[0835] A device that displays the aforementioned travel information, convenience information, and detour route information to the user,

[0836] A device that analyzes the user's emotional state and generates suggestions tailored to that psychological state,

[0837] A system including a device that presents the optimal route and content based on the above proposal.

[0838] (Claim 2)

[0839] The system according to claim 1, wherein the convenience information includes whether or not there are mobility assistance facilities for persons with mobility limitations.

[0840] (Claim 3)

[0841] The system according to claim 1, wherein the detour route generation device calculates the optimal alternative route using a data processing algorithm. [Explanation of Symbols]

[0842] 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 the user to enter the departure point and destination, A means for obtaining transfer information based on the entered departure and destination points, A means for collecting accessibility information for locations related to the acquired transfer information, A means for generating a detour route when non-barrier-free points are included, A system including means for displaying the aforementioned transfer information, accessibility information, and detour route information to the user.

2. The system according to claim 1, wherein the barrier-free information includes the presence or absence of elevators and multipurpose toilets for wheelchair users.

3. The system according to claim 1, wherein the detour route generation means calculates the optimal alternative route using a machine learning algorithm.

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