system

Abstract

We provide the system. [Solution] A means of receiving information about the starting point and destination from the user, Means for obtaining map information and accessibility-related information, A means for calculating the optimal travel route that takes into account steps and steep slopes, Means for providing the calculated travel path to the user, A means of providing real-time direction guidance via voice guidance, Means for displaying and providing facility information to users, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, the needs for various types of mobility support are increasing, such as for the elderly, people with disabilities, and families using baby strollers. However, it has been difficult for conventional route guidance systems to provide an optimal route that avoids barriers for them, such as steep slopes and steps. In addition, there is a lack of information on barrier-free facilities, and it has not been sufficient to support smooth use of facilities at the destination. As a result, there is a problem that the convenience and safety of mobility are not ensured and the free range of movement is restricted.

Means for Solving the Problems

[0005] This invention provides a means for receiving information on the starting point and destination from the user and acquiring map information and barrier-free related information based on this information. Furthermore, it provides a means for calculating the optimal travel route considering steps and steep slopes, and provides the calculated travel route to the user along with real-time direction guidance via voice guidance. In addition, it actively provides information on barrier-free facilities and collects user feedback to reflect in route calculations, thereby enabling a safer and more comfortable travel experience. In this way, it realizes an environment where everyone can travel freely and without stress.

[0006] A "user" is an individual who uses the system to input their origin and destination and receives travel routes and related information.

[0007] A "travel route" refers to the path that a user is expected to take from their starting point to their destination.

[0008] "Map information" refers to data that shows geographical relationships, road shapes, facility layouts, and so on.

[0009] "Barrier-free information" refers to information aimed at eliminating obstacles to movement for users of wheelchairs or strollers, and includes the location of elevators and ramps, and the presence or absence of steps.

[0010] "Voice guidance" is a function that uses machine voice to provide real-time guidance so that users can receive directions to their travel route without using their hands.

[0011] "Facility information" refers to data about shops and public facilities around the destination, including information on whether or not they are barrier-free.

[0012] "Feedback" refers to opinions and evaluations about the user experience provided by users after using the system, and is used to improve the system in the future. [Brief explanation of the drawing]

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

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

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

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

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

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs 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.

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

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

[0021] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0034] This invention is a barrier-free route guidance system designed to enable people to travel safely and comfortably. It is realized through data exchange between a server, a terminal, and a user. The server receives information on the starting point and destination transmitted by the user and calculates the optimal route based on this information. The calculation uses map information and barrier-free related information, prioritizing the selection of routes with fewer steps and steep inclines.

[0035] Users can use their devices to obtain real-time route information provided by the server. This information includes details about barrier-free facilities around the destination and recommended routes tailored to user needs. Furthermore, devices equipped with voice guidance support users to ensure their safe travel and provide directional instructions at specific times.

[0036] As a concrete example, consider a case where a user using a wheelchair visits a tourist destination in an urban area. The user enters their current location as the starting point and the tourist destination as the destination into the terminal. This information is sent to the server, which uses geographical information and accessibility-related information to calculate the safest and most comfortable route. The route calculated by the server includes stations with elevators and sidewalks with ramps, and this information is sent to the user. The terminal uses this information received from the server to guide the user to the appropriate route via voice guidance. After completing their journey, the user can provide feedback, which will be used to improve the accuracy of guidance in the future.

[0037] As described above, this invention aims to provide users with specific needs with freedom of movement and to realize a more comfortable travel experience.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The user launches the application on their device and enters their starting point and destination. They can also optionally select whether they will be using a wheelchair or stroller.

[0041] Step 2:

[0042] The terminal receives input from the user and sends it to the server as a request. The request includes information about the departure point and destination.

[0043] Step 3:

[0044] When the server receives a request from a terminal, it accesses a map information service to retrieve the latest geographic data. At the same time, it also retrieves information on facilities related to accessibility.

[0045] Step 4:

[0046] The server analyzes the acquired map information and prioritizes searching for routes with fewer steps and steep inclines. It also utilizes information on nearby barrier-free facilities during the search process.

[0047] Step 5:

[0048] The server evaluates multiple calculated routes and selects the safest and most comfortable route for the user. Based on the evaluation results, it determines the optimal route.

[0049] Step 6:

[0050] The server sends the selected route information to the user's terminal. The transmitted data includes location information for elevators and ramps.

[0051] Step 7:

[0052] The terminal processes the route information received from the server and displays it visually on the user interface.

[0053] Step 8:

[0054] Once the user starts moving, the device uses its built-in GPS function to constantly track the user's current location.

[0055] Step 9:

[0056] While in motion, the device provides voice guidance at pre-set landmarks and intersections, directing the user in the appropriate direction.

[0057] Step 10:

[0058] After the user reaches their destination, the device displays a prompt for user feedback and collects feedback data.

[0059] Step 11:

[0060] The device sends user feedback to the server.

[0061] Step 12:

[0062] The server stores the received feedback in a database and uses it to improve the accuracy of future route calculations.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] In modern society, freedom of movement is a fundamental right, but physical obstacles such as steps and steep slopes pose significant barriers, especially for those who require barrier-free access. Therefore, route guidance that allows everyone to move safely and comfortably is necessary. Furthermore, conventional route calculation systems have not adequately utilized individual user feedback to improve guidance accuracy. In response, there is a need for a system that prioritizes barrier-free information based on user feedback and improves guidance accuracy.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes a device for receiving information on the starting and destination locations from the user, a device for acquiring spatial information and barrier-free related information, and a device for calculating the optimal travel route considering physical obstacles and steep terrain. This enables safe and comfortable travel guidance, especially for users who require barrier-free access.

[0068] A "user" refers to an individual or legal entity that uses the system to input its starting point and destination and receive guidance regarding travel.

[0069] "Starting location" refers to the geographical point that serves as the starting point for the user's movement.

[0070] "Destination location" refers to the geographical point that the user designates as the end point of their journey.

[0071] "Device" refers to a component of hardware or software designed to perform a specific function.

[0072] "Spatial information" is a general term for information that includes data about geographical location and topography.

[0073] "Barrier-free related information" refers to information related to facilities and equipment that reduce or eliminate physical barriers.

[0074] "Physical obstacles" refer to topographical or structural elements such as steps or steep slopes that hinder movement.

[0075] "Steep terrain" refers to geographical features with steep slopes or dramatic changes in terrain.

[0076] A "travel route" refers to the path a user takes to travel from their starting point to their destination.

[0077] A "generative AI model" refers to an artificial intelligence algorithm that learns from user feedback and improves the accuracy of system guidance.

[0078] This barrier-free route guidance system provides a mechanism to support safe and comfortable travel by exchanging information among three parties: the server, the terminal, and the user.

[0079] The server begins its role by receiving information about the user's starting and destination locations. This information is transmitted from the terminal to the server using a common communication protocol. The server then acquires spatial information related to geographical location and terrain, and further retrieves information about obstacles and facilities from accessibility-related databases. As a specific example, the server utilizes general-purpose map data as an API service when acquiring map information.

[0080] The terminal receives optimal route information calculated from the server based on the information entered by the user. The received data includes information on barrier-free facilities along the user's route, allowing the user to receive real-time voice guidance. This voice direction guidance is automatically generated based on geographical location information and provided to the user at the appropriate time while they are on the move.

[0081] As a concrete example, consider a case where a user using a wheelchair visits a specific tourist destination in an urban area. The user inputs their current location as the starting point and the tourist destination as the destination via a terminal. This information is sent to a server, which calculates the optimal route, including facilities with elevators and paths with minimal steps, based on map information and accessibility-related information. The terminal then provides the user with specific route instructions via voice guidance, such as, "Turn left at the next intersection, proceed 50 meters, and then enter the facility with a ramp on your right."

[0082] Finally, users provide feedback after completing their journey, which helps improve the accuracy of future route guidance. The generative AI model learns from user feedback and uses it to improve future guidance, so the overall system performance improves with continued use.

[0083] Examples of prompt statements include the following:

[0084] "We want to create a system that provides barrier-free and safe route guidance for wheelchair users. Please tell us what kind of data we should use and how we should utilize it."

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The user enters the starting point and destination using the terminal. This input information is formatted by the terminal and output as a request to the server. The terminal can automatically obtain the current location using its GPS function and set it as the starting point. It is also possible to specify the destination using voice input.

[0088] Step 2:

[0089] The terminal sends the entered starting point and destination information to the server. The server receives this data and treats it as input data to begin calculation processing. The received information includes the user's current location and desired destination, and this is used to process the data in the next step.

[0090] Step 3:

[0091] The server acquires spatial information and accessibility-related information based on the received data. It uses a geographic information service API to obtain map data for the starting point and destination. It also collects information on nearby accessibility facilities from reliable public databases. This information is output as input data for route calculation in the next step.

[0092] Step 4:

[0093] The server calculates the optimal travel route to avoid physical obstacles based on acquired map data and accessibility information. This calculation uses algorithms such as Dijkstra's algorithm to select routes that avoid steps and steep slopes. The output of this step is the route information that the user should use for travel.

[0094] Step 5:

[0095] The server sends the calculated travel path information to the terminal. This information includes detailed information such as the locations of elevators and ramps. Upon receiving this information, the terminal prepares to guide the user to the next step.

[0096] Step 6:

[0097] The terminal provides real-time voice guidance to the user based on the received route information. At this stage, it uses speech synthesis to automatically generate and output appropriate directional instructions when approaching important points along the route. For example, it provides specific guidance such as, "Turn right at the intersection 50 meters ahead, then proceed 5 meters and you will find an elevator on your left."

[0098] Step 7:

[0099] After completing their journey, users provide feedback on the comfort and effectiveness of the guided route. The terminal collects this feedback and sends it to the server. This information is used to train a generative AI model and improve the accuracy of route calculation and guidance in the future. User evaluations also contribute to future updates as data for reviewing the entire system.

[0100] (Application Example 1)

[0101] 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."

[0102] In the current urban environment, it is difficult for individuals with physical disabilities to obtain appropriate information that will allow them to move comfortably and safely. This lack of information restricts freedom of movement and hinders users, especially those who require barrier-free facilities, from enjoying the conveniences of the city. Furthermore, the lack of real-time guidance and insufficient system improvements based on user feedback are also challenges.

[0103] 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.

[0104] In this invention, the server includes means for receiving current location information and destination location information, means for acquiring geographic data and barrier-free related data, and means for calculating an appropriate travel route to avoid obstacles. This enables users to use the optimal barrier-free route in real time and move around the city with peace of mind. Furthermore, it allows for guidance using speech synthesis and continuous improvement of the system through the use of feedback.

[0105] "Current location information" is data used to identify the geographical location where the user is currently located.

[0106] "Destination location information" is data that indicates the geographical location of the destination the user is aiming for.

[0107] "Geographic data" refers to data that includes geographical information about a specific area, including topography and infrastructure.

[0108] "Barrier-free related data" refers to data that provides information about routes and facilities that are free from obstacles.

[0109] "Obstacles" refer to physical structures, steps, and other obstacles that hinder the user's movement.

[0110] A "travel route" is route information that shows the optimal path from your current location to your destination.

[0111] "Speech synthesis" is a technology that reads text data and outputs it as a human voice.

[0112] "Guidance" refers to the act of providing users with the information they need to reach their destination.

[0113] "Feedback" refers to opinions and evaluations from users after they have used a system, and is information used to improve the system.

[0114] This invention is a system that supports barrier-free mobility, and is realized through the respective roles of the server, terminal, and user.

[0115] The server receives the user's current location and destination location information and retrieves geographic data using a geographic data API (e.g., Google® Maps API). Furthermore, it obtains necessary accessibility-related data from accessibility databases. Based on this information, the server calculates the optimal accessibility route. The calculated travel path is provided to the user in real time using speech synthesis technology (e.g., Google Text-to-Speech).

[0116] The terminal visualizes route information received from the server and displays it on a map. While the user is moving, it provides real-time direction guidance and additional facility-related data through voice guidance. It also collects user feedback and sends it to the server to help improve the system.

[0117] For example, when a user visits a city park in a wheelchair, the system guides them to the location of barrier-free paths and available ramps along the route. Furthermore, it provides information on barrier-free facilities near the destination, supporting the user's smooth movement.

[0118] As an example of a prompt using a generative AI model, the user is presented with the following instruction: "Please enter your current location and destination. The optimal barrier-free route will be calculated. Do you want to start voice guidance?"

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The terminal sends the user's current location and destination location information to the server. The input consists of the user's current location and destination, and the server prepares to calculate the route based on this information.

[0122] Step 2:

[0123] The server uses the received current location information and destination location information to call a geographic data API to obtain geographic data. This data acquisition process outputs route information on a map from the API, which is then prepared for the next calculation.

[0124] Step 3:

[0125] The server uses acquired geographical data and accessibility-related databases to calculate the optimal travel route to avoid obstacles. This calculation prioritizes barrier-free routes without steps or steep inclines. The output is the route information for the chosen route.

[0126] Step 4:

[0127] The server sends the calculated travel route information to the terminal. This route information includes details such as routes without steps, available elevators, and ramps. This data sent to the terminal is used in the next guide step.

[0128] Step 5:

[0129] Based on the information it receives, the terminal uses speech synthesis technology to provide real-time route guidance to the user. The voice guidance outputs directional instructions to the user, providing appropriate support while they are on the move.

[0130] Step 6:

[0131] After completing a journey, users enter feedback into their terminal, which is then sent to the server and used to improve the system. This feedback helps to improve the accuracy of future route calculations.

[0132] 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.

[0133] This invention is a more advanced barrier-free route guidance system that incorporates an emotion engine to recognize user emotions. It provides mobility assistance through mutual data exchange between the server, terminal, and user. The server receives information on the starting point and destination, and based on this, acquires map information and barrier-free related information. It has means for calculating the optimal travel route, taking into account steps and steep inclines, and providing it to the user along with voice guidance.

[0134] The emotion engine allows the device to recognize the user's emotional state in real time while they are on the move. This emotional data is analyzed using sensor data such as the user's facial expressions and voice tone. For example, if the user is showing positive emotions, the server will suggest recommended sightseeing spots and relaxation spots along the proposed route. On the other hand, if the system detects that the user is feeling stressed, it will suggest a more comfortable and quiet route.

[0135] As a concrete example, consider a case where a user is sightseeing in a city in a wheelchair. The user enters their starting point and destination into the device, and the system calculates the route on the server based on that information. While traveling, the device's emotion engine monitors the user's reactions in real time. For example, if it detects a cheerful expression, the server suggests a nearby park or cafe, providing an opportunity to relax. Furthermore, feedback obtained after use is sent to the server and used to improve the accuracy of emotion analysis.

[0136] Based on the above, this invention aims to provide a safe and comfortable travel experience that responds to the user's emotional state, and to further improve the flexibility and convenience of travel.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The user uses the device to enter their starting point and destination. The device then activates the emotion engine and begins monitoring the user's initial state.

[0140] Step 2:

[0141] The terminal sends the entered information to the server and requests map information and accessibility-related information.

[0142] Step 3:

[0143] The server calculates the optimal travel route based on the received information. In doing so, it prioritizes routes with fewer steps and steep inclines, and takes into account information about barrier-free facilities.

[0144] Step 4:

[0145] The server sends the calculated travel path to the terminal. The terminal receives this, displays it on the user interface, and prepares for voice guidance.

[0146] Step 5:

[0147] As the user begins to move, the device's emotion engine analyzes the user's emotional state in real time. This includes facial recognition using the camera and voice analysis using the microphone.

[0148] Step 6:

[0149] The device sends emotion data detected by the emotion engine to the server. The server receives this data and calculates suggestions based on the user's emotional state.

[0150] Step 7:

[0151] If the user's mood is positive, the server sends options to the device suggesting nearby tourist attractions and relaxation spots.

[0152] Step 8:

[0153] If the user's emotions are negative, the server calculates a more comfortable and calming alternative route and sends it to the terminal.

[0154] Step 9:

[0155] The terminal presents the selected suggestion to the user and continues to provide real-time directional guidance through its voice guidance function.

[0156] Step 10:

[0157] After the user reaches their destination, the device requests feedback on the user's travel experience and provides a function to evaluate the results of the emotion engine's operation.

[0158] Step 11:

[0159] The device sends user feedback and sentiment data to the server.

[0160] Step 12:

[0161] The server stores the received feedback in a database and uses it for future system improvements and training of the emotion engine.

[0162] (Example 2)

[0163] 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".

[0164] Conventional mobility assistance systems have struggled to provide flexible route suggestions that take into account the user's emotions and physical condition, resulting in unsatisfactory travel experiences, particularly for users with physical limitations or those prioritizing comfort. Furthermore, the lack of adaptive route changes in response to real-time emotional changes posed challenges to safety and convenience during travel.

[0165] 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.

[0166] In this invention, the server includes means for receiving information on the starting point and destination from the user, means for acquiring map information and user support-related information, and means for recognizing the user's emotions using an emotion analysis engine. This enables adaptive route suggestions and mobility support based on the user's emotions and physical condition.

[0167] "Means of receiving information" refers to an interface that obtains data such as the starting point and destination from the user and converts it into a format that can be used within the system.

[0168] "Means for acquiring map information and user support-related information" refers to a device or program that acquires geographical information and accessibility information from an external or internal database and processes it for use in route calculation.

[0169] "Means for calculating the optimal travel route" refers to algorithms or software that use received map information and user assistance-related information to calculate the most convenient and safe route for the user.

[0170] "Means of providing users with calculated travel routes" refers to a system that communicates the calculated route to the user via a terminal and provides visual or auditory guidance.

[0171] "Means of providing real-time directional guidance via voice" refers to a device or program that has the function of communicating directions and precautions via voice based on the user's current location.

[0172] "Means of recognizing a user's emotions using an emotion analysis engine" refers to a system that detects the user's voice and facial expressions using sensors, analyzes them with software, and determines their emotional state.

[0173] "Means of adjusting routes and suggestions based on user emotions" refers to a function that improves the travel experience by making optimal route changes or new suggestions based on information obtained through emotion analysis, tailored to the user's state.

[0174] "Means for displaying and providing facility information to users" refers to a display device or software that displays information about facilities along the travel route on the user's terminal and guides them to available services.

[0175] The travel route guidance system in this invention involves the user, terminal, and server cooperating and exchanging information with each other to provide an optimal travel experience tailored to the user's emotional state.

[0176] First, the user enters their starting point and destination into their device. This device is a smartphone or tablet and has the functionality to send the input information to a server through its user interface. The device also has a camera and microphone to sense the user's facial expressions and voice in real time. This hardware works in conjunction with an emotion analysis engine to extract the user's emotional data.

[0177] The server first receives departure and destination information sent from the terminal. Based on this information, the server uses a map API to obtain necessary geographical and accessibility information. The server then calculates the optimal travel route, taking into account obstacles and terrain features, using an algorithm (e.g., Dijkstra's algorithm or A algorithm), and formats the result as voice guidance. The voice guidance is provided to the user through the terminal, using a commonly used voice output service.

[0178] The device's emotion analysis engine analyzes the user's facial expressions and tone of voice in real time while they are on the move to determine their emotional state. The server receives this emotion data from the device, and if the user is showing positive emotions, it suggests new spots along the proposed route, such as tourist attractions or relaxation facilities. On the other hand, if the user is showing stress or discomfort, a more comfortable travel route is suggested.

[0179] As a concrete example, imagine a scenario where a server suggests a nearby park via a device that detects a user's smile while they are sightseeing in a city. This would allow the user to enjoy an unexpected sightseeing spot that wasn't originally in their plan.

[0180] An example of a prompt for the generation AI model would be: "Please generate natural language that recognizes the positive emotions the user is feeling while traveling and suggests spots that align with those emotions." This system would allow users to enjoy a flexible travel experience that responds to their emotional state, significantly improving safety and comfort during travel.

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] The user enters their starting point and destination into the terminal. The entered information is then prepared to be sent to the server via the terminal's interface. The input data is converted into the format necessary to access the map API and used to obtain accurate geographic information. The terminal verifies the user's input and formats the data.

[0184] Step 2:

[0185] The server receives departure and destination information sent from the terminal. Using this information as input, the server performs data calculations to obtain geographical and accessibility information via a map API. The output is detailed map information and user assistance information associated with that location. Here, the server performs specific actions such as managing API keys and configuring communication endpoints.

[0186] Step 3:

[0187] The server uses acquired map information to calculate the optimal travel route. The input consists of map information and accessibility information, and the server applies a route-finding algorithm based on this information. The output is the optimized route data. Algorithms such as Dijkstra's and A are used in the calculation, allowing the server to perform efficient route finding.

[0188] Step 4:

[0189] The server formats the calculated travel path into an audio guidance format and generates a script. This generated script is then prepared to match the audio output service used by the user. The output is audio guidance data that is given to the user in real time. The server performs a process to convert text information into audio data.

[0190] Step 5:

[0191] The device uses its camera and microphone to capture the user's facial expressions and voice in real time. Based on these sensor inputs, the device activates an emotion analysis engine and performs data calculations to analyze the user's emotions. The output is numerical or labeled data of the user's emotional state. The device then proceeds with processing such as facial expression detection and voice analysis.

[0192] Step 6:

[0193] The server adjusts routes and suggestions based on emotion data received from the terminal. This process uses emotion analysis data as input to evaluate routes and create suggestions. For example, it might select new stops based on positive emotions. The output is adjusted route guidance data tailored to the emotions. The server dynamically changes suggestions using conditional branching and other methods.

[0194] This process enables the system to provide flexible guidance and an optimal travel experience tailored to the user's emotional state.

[0195] (Application Example 2)

[0196] 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".

[0197] Existing barrier-free guidance systems do not provide mobility assistance that takes into account the user's emotional state, making it difficult to reduce stress and fatigue during travel. Furthermore, route suggestions are not optimized based on the individual user's emotions, resulting in insufficient support, especially for users who prioritize emotional comfort. This leads to a challenge in that the value of the user's travel experience is not sufficiently enhanced.

[0198] 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.

[0199] In this invention, the server includes means for recognizing the user's emotional state, means for acquiring map information and accessibility-related information, and means for suggesting appropriate facility information based on the emotional state. This makes it possible to provide an optimal travel experience that responds to the user's emotions.

[0200] "Means for receiving departure and destination information from the user" refers to a device or method for acquiring departure and arrival data entered by the user.

[0201] "Means for acquiring map information and barrier-free related information" refers to a device or method for acquiring geographical location data and barrier-free data such as the presence or absence of steps and ramps.

[0202] "Means for calculating the optimal travel route considering steps and steep slopes" refers to a device or method for calculating the most appropriate travel route among routes that include steps and steep slopes that may occur during travel.

[0203] "Means for providing a calculated travel route to a user" refers to a device or method for notifying or presenting a calculated travel route to a user.

[0204] "Means for providing real-time direction guidance via voice guidance" refers to a device or method that generates and transmits real-time voice information indicating direction to the user.

[0205] "Means for displaying and providing facility information to users" means a device or method for displaying information about a facility to users in a visual or other format.

[0206] "Means for recognizing a user's emotional state" refers to a device or method that analyzes data such as a user's facial expressions and tone of voice to evaluate their emotional state.

[0207] "Means for suggesting appropriate facility information based on emotional state" refers to a device or method that suggests information about relevant facilities or locations in accordance with the user's emotions.

[0208] To realize this invention, an advanced barrier-free route guidance system including an emotion recognition engine is used. This system provides mobility assistance to the user by combining multiple terminals and servers. The server receives information about the starting point and destination from the user and acquires map information and barrier-free related information. The terminal recognizes the user's emotional state in real time using sensor data such as facial expressions and voice tone.

[0209] This system uses software that provides real-time directional guidance via voice (e.g., Google Text-to-Speech API) and a map information API (e.g., Google Maps API) to obtain map information. The emotion recognition algorithm is implemented in a programming language such as Python and suggests appropriate facility information based on the user's emotions.

[0210] As a concrete example, a user accesses the system using a smartphone or tablet and enters their starting point and destination. If the device detects the user's cheerful expression during their journey, the server suggests nearby relaxation spots such as parks or cafes based on the emotional data. This allows the user to enjoy a comfortable travel experience that is tailored to their emotional state.

[0211] An example of a prompt message is, "If the user is smiling, generate a route and comments suggesting nearby tourist attractions." This allows the system to use a generative AI model to provide the user with the most relevant information.

[0212] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0213] Step 1:

[0214] The user enters the departure point and destination information into the device.

[0215] The information entered is collected as data transmitted from the terminal to the server. This data is then used as basic information for subsequent mobility assistance.

[0216] Step 2:

[0217] Based on the received departure and destination information, the server retrieves map information and accessibility-related information from an external map API.

[0218] This information is used to calculate the optimal travel route, taking into account factors such as steps and steep inclines. The calculated route becomes the output data for the terminal.

[0219] Step 3:

[0220] The device collects the user's facial expressions and voice tone as sensor data.

[0221] This data is analyzed in real time by a built-in emotion recognition algorithm and used to identify the user's emotional state (e.g., positive, negative).

[0222] Step 4:

[0223] The emotion recognition engine on the device sends emotion data to the server.

[0224] Based on this sentiment data, the server invokes a generative AI model to suggest appropriate facility information along the route (such as tourist attractions or places to relax) and generates prompt messages. The generated information is then provided to the terminal as output data.

[0225] Step 5:

[0226] The terminal provides the user with route information and schedule suggestions received from the server in both voice and display formats.

[0227] The voice guidance system utilizes a speech synthesis API and includes specific actions such as providing directions and recommendations to the user in real time.

[0228] Step 6:

[0229] Once the user's movement is complete, feedback information is sent to the server via the device.

[0230] The server collects this feedback and uses it as data to improve the accuracy of sentiment analysis and path calculation.

[0231] This series of processes makes it possible to provide an optimal travel experience that is tailored to the user's emotions.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] [Second Embodiment]

[0236] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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.

[0247] 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".

[0248] This invention is a barrier-free route guidance system designed to enable people to travel safely and comfortably. It is realized through data exchange between a server, a terminal, and a user. The server receives information on the starting point and destination transmitted by the user and calculates the optimal route based on this information. The calculation uses map information and barrier-free related information, prioritizing the selection of routes with fewer steps and steep inclines.

[0249] Users can use their devices to obtain real-time route information provided by the server. This information includes details about barrier-free facilities around the destination and recommended routes tailored to user needs. Furthermore, devices equipped with voice guidance support users to ensure their safe travel and provide directional instructions at specific times.

[0250] As a concrete example, consider a case where a user using a wheelchair visits a tourist destination in an urban area. The user enters their current location as the starting point and the tourist destination as the destination into the terminal. This information is sent to the server, which uses geographical information and accessibility-related information to calculate the safest and most comfortable route. The route calculated by the server includes stations with elevators and sidewalks with ramps, and this information is sent to the user. The terminal uses this information received from the server to guide the user to the appropriate route via voice guidance. After completing their journey, the user can provide feedback, which will be used to improve the accuracy of guidance in the future.

[0251] As described above, this invention aims to provide users with specific needs with freedom of movement and to realize a more comfortable travel experience.

[0252] The following describes the processing flow.

[0253] Step 1:

[0254] The user launches the application on their device and enters their starting point and destination. They can also optionally select whether they will be using a wheelchair or stroller.

[0255] Step 2:

[0256] The terminal receives input from the user and sends it to the server as a request. The request includes information about the departure point and destination.

[0257] Step 3:

[0258] When the server receives a request from a terminal, it accesses a map information service to retrieve the latest geographic data. At the same time, it also retrieves information on facilities related to accessibility.

[0259] Step 4:

[0260] The server analyzes the acquired map information and prioritizes searching for routes with fewer steps and steep inclines. It also utilizes information on nearby barrier-free facilities during the search process.

[0261] Step 5:

[0262] The server evaluates multiple calculated routes and selects the safest and most comfortable route for the user. Based on the evaluation results, it determines the optimal route.

[0263] Step 6:

[0264] The server sends the selected route information to the user's terminal. The transmitted data includes location information for elevators and ramps.

[0265] Step 7:

[0266] The terminal processes the route information received from the server and displays it visually on the user interface.

[0267] Step 8:

[0268] Once the user starts moving, the device uses its built-in GPS function to constantly track the user's current location.

[0269] Step 9:

[0270] While in motion, the device provides voice guidance at pre-set landmarks and intersections, directing the user in the appropriate direction.

[0271] Step 10:

[0272] After the user reaches their destination, the device displays a prompt for user feedback and collects feedback data.

[0273] Step 11:

[0274] The device sends user feedback to the server.

[0275] Step 12:

[0276] The server stores the received feedback in a database and uses it to improve the accuracy of future route calculations.

[0277] (Example 1)

[0278] 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."

[0279] In modern society, freedom of movement is a fundamental right, but physical obstacles such as steps and steep slopes pose significant barriers, especially for those who require barrier-free access. Therefore, route guidance that allows everyone to move safely and comfortably is necessary. Furthermore, conventional route calculation systems have not adequately utilized individual user feedback to improve guidance accuracy. In response, there is a need for a system that prioritizes barrier-free information based on user feedback and improves guidance accuracy.

[0280] 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.

[0281] In this invention, the server includes a device that receives information on the starting position and the destination position from the user, a device that acquires spatial information and barrier-free related information, and a device that calculates an optimal movement route considering physical obstacles and steep terrain. As a result, it becomes possible to provide a safe and comfortable movement guidance that is also suitable for users who particularly require barrier-free conditions.

[0282] The "user" refers to an individual or a corporation that inputs the starting point and the destination using the system and receives guidance regarding movement.

[0283] The "starting position" refers to the geographical location that is the starting point of the user's movement.

[0284] The "destination position" refers to the geographical location specified by the user as the end point of the movement.

[0285] The "device" refers to a hardware or software component designed to execute a specific function.

[0286] The "spatial information" is a general term for information including data related to geographical locations and terrain.

[0287] The "barrier-free related information" refers to information related to facilities and equipment for reducing or removing physical barriers.

[0288] The "physical obstacle" refers to topographical or structural elements such as steps and steep gradients that impede movement.

[0289] The "steep terrain" refers to geographical terrain with a sharp incline or drastic changes.

[0290] The "movement route" refers to the route that the user passes through to move from the starting point to the destination.

[0291] The "generative AI model" refers to an artificial intelligence algorithm that learns based on feedback from the user and improves the guidance accuracy of the system.

[0292] This barrier-free route guidance system provides a mechanism to support safe and comfortable travel by exchanging information among three parties: the server, the terminal, and the user.

[0293] The server begins its role by receiving information about the user's starting and destination locations. This information is transmitted from the terminal to the server using a common communication protocol. The server then acquires spatial information related to geographical location and terrain, and further retrieves information about obstacles and facilities from accessibility-related databases. As a specific example, the server utilizes general-purpose map data as an API service when acquiring map information.

[0294] The terminal receives optimal route information calculated from the server based on the information entered by the user. The received data includes information on barrier-free facilities along the user's route, allowing the user to receive real-time voice guidance. This voice direction guidance is automatically generated based on geographical location information and provided to the user at the appropriate time while they are on the move.

[0295] As a concrete example, consider a case where a user using a wheelchair visits a specific tourist destination in an urban area. The user inputs their current location as the starting point and the tourist destination as the destination via a terminal. This information is sent to a server, which calculates the optimal route, including facilities with elevators and paths with minimal steps, based on map information and accessibility-related information. The terminal then provides the user with specific route instructions via voice guidance, such as, "Turn left at the next intersection, proceed 50 meters, and then enter the facility with a ramp on your right."

[0296] Finally, users provide feedback after completing their journey, which helps improve the accuracy of future route guidance. The generative AI model learns from user feedback and uses it to improve future guidance, so the overall system performance improves with continued use.

[0297] Examples of prompt statements include the following:

[0298] "We want to create a system that provides barrier-free and safe route guidance for wheelchair users. Please tell us what kind of data we should use and how we should utilize it."

[0299] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0300] Step 1:

[0301] The user enters the starting point and destination using the terminal. This input information is formatted by the terminal and output as a request to the server. The terminal can automatically obtain the current location using its GPS function and set it as the starting point. It is also possible to specify the destination using voice input.

[0302] Step 2:

[0303] The terminal sends the entered starting point and destination information to the server. The server receives this data and treats it as input data to begin calculation processing. The received information includes the user's current location and desired destination, and this is used to process the data in the next step.

[0304] Step 3:

[0305] The server acquires spatial information and accessibility-related information based on the received data. It uses a geographic information service API to obtain map data for the starting point and destination. It also collects information on nearby accessibility facilities from reliable public databases. This information is output as input data for route calculation in the next step.

[0306] Step 4:

[0307] Based on the acquired map data and barrier-free related information, the server calculates the optimal moving route to avoid physical obstacles. In this calculation, an algorithm such as Dijkstra's algorithm is used to select a route that avoids steps and steep slopes. The output of this step is the route information that the user should use for movement.

[0308] Step 5:

[0309] The server transmits the calculated moving route information, which is the result of the calculation, to the terminal. This information also includes detailed information such as the positions of elevators and slopes. By receiving this, the terminal prepares for the guidance in the next step.

[0310] Step 6:

[0311] Based on the received route information, the terminal provides real-time voice guidance to the user. At this stage, the voice synthesis function is used to automatically generate and output appropriate direction instructions when approaching important points on the route. For example, specific guidance such as "Turn right at the intersection 50 meters ahead, and there is an elevator on the left after proceeding 5 meters" is provided.

[0312] Step 7:

[0313] After the user completes the movement, the user provides feedback on the comfort and effectiveness of the guided route. The terminal collects this feedback and transmits it to the server. This information is learned by the generative AI model and used to improve the route calculation and guidance accuracy in subsequent times. The user's evaluation also contributes to future updates as data for reviewing the entire system.

[0314] (Application Example 1)

[0315] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0316] In the current urban environment, it is difficult for individuals with physical disabilities to obtain appropriate information that will allow them to move comfortably and safely. This lack of information restricts freedom of movement and hinders users, especially those who require barrier-free facilities, from enjoying the conveniences of the city. Furthermore, the lack of real-time guidance and insufficient system improvements based on user feedback are also challenges.

[0317] 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.

[0318] In this invention, the server includes means for receiving current location information and destination location information, means for acquiring geographic data and barrier-free related data, and means for calculating an appropriate travel route to avoid obstacles. This enables users to use the optimal barrier-free route in real time and move around the city with peace of mind. Furthermore, it allows for guidance using speech synthesis and continuous improvement of the system through the use of feedback.

[0319] "Current location information" is data used to identify the geographical location where the user is currently located.

[0320] "Destination location information" is data that indicates the geographical location of the destination the user is aiming for.

[0321] "Geographic data" refers to data that includes geographical information about a specific area, including topography and infrastructure.

[0322] "Barrier-free related data" refers to data that provides information about routes and facilities that are free from obstacles.

[0323] "Obstacles" refer to physical structures, steps, and other obstacles that hinder the user's movement.

[0324] A "travel route" is route information that shows the optimal path from your current location to your destination.

[0325] "Speech synthesis" is a technology that reads text data and outputs it as a human voice.

[0326] "Guidance" refers to the act of providing users with the information they need to reach their destination.

[0327] "Feedback" refers to opinions and evaluations from users after they have used a system, and is information used to improve the system.

[0328] This invention is a system that supports barrier-free mobility, and is realized through the respective roles of the server, terminal, and user.

[0329] The server receives the user's current location and destination location information and retrieves geographic data using a geographic data API (e.g., Google Maps API). Furthermore, it obtains necessary accessibility data from accessibility databases. Based on this information, the server calculates the optimal accessibility route. The calculated travel route is provided to the user in real time using speech synthesis technology (e.g., Google Text-to-Speech).

[0330] The terminal visualizes route information received from the server and displays it on a map. While the user is moving, it provides real-time direction guidance and additional facility-related data through voice guidance. It also collects user feedback and sends it to the server to help improve the system.

[0331] For example, when a user visits a city park in a wheelchair, the system guides them to the location of barrier-free paths and available ramps along the route. Furthermore, it provides information on barrier-free facilities near the destination, supporting the user's smooth movement.

[0332] As an example of a prompt using a generative AI model, the user is presented with the following instruction: "Please enter your current location and destination. The optimal barrier-free route will be calculated. Do you want to start voice guidance?"

[0333] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0334] Step 1:

[0335] The terminal sends the user's current location and destination location information to the server. The input consists of the user's current location and destination, and the server prepares to calculate the route based on this information.

[0336] Step 2:

[0337] The server uses the received current location information and destination location information to call a geographic data API to obtain geographic data. This data acquisition process outputs route information on a map from the API, which is then prepared for the next calculation.

[0338] Step 3:

[0339] The server uses acquired geographical data and accessibility-related databases to calculate the optimal travel route to avoid obstacles. This calculation prioritizes barrier-free routes without steps or steep inclines. The output is the route information for the chosen route.

[0340] Step 4:

[0341] The server sends the calculated travel route information to the terminal. This route information includes details such as routes without steps, available elevators, and ramps. This data sent to the terminal is used in the next guide step.

[0342] Step 5:

[0343] Based on the information it receives, the terminal uses speech synthesis technology to provide real-time route guidance to the user. The voice guidance outputs directional instructions to the user, providing appropriate support while they are on the move.

[0344] Step 6:

[0345] After completing a journey, users enter feedback into their terminal, which is then sent to the server and used to improve the system. This feedback helps to improve the accuracy of future route calculations.

[0346] 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.

[0347] This invention is a more advanced barrier-free route guidance system that incorporates an emotion engine to recognize user emotions. It provides mobility assistance through mutual data exchange between the server, terminal, and user. The server receives information on the starting point and destination, and based on this, acquires map information and barrier-free related information. It has means for calculating the optimal travel route, taking into account steps and steep inclines, and providing it to the user along with voice guidance.

[0348] The emotion engine allows the device to recognize the user's emotional state in real time while they are on the move. This emotional data is analyzed using sensor data such as the user's facial expressions and voice tone. For example, if the user is showing positive emotions, the server will suggest recommended sightseeing spots and relaxation spots along the proposed route. On the other hand, if the system detects that the user is feeling stressed, it will suggest a more comfortable and quiet route.

[0349] As a concrete example, consider a case where a user is sightseeing in a city in a wheelchair. The user enters their starting point and destination into the device, and the system calculates the route on the server based on that information. While traveling, the device's emotion engine monitors the user's reactions in real time. For example, if it detects a cheerful expression, the server suggests a nearby park or cafe, providing an opportunity to relax. Furthermore, feedback obtained after use is sent to the server and used to improve the accuracy of emotion analysis.

[0350] Based on the above, this invention aims to provide a safe and comfortable travel experience that responds to the user's emotional state, and to further improve the flexibility and convenience of travel.

[0351] The following describes the processing flow.

[0352] Step 1:

[0353] The user uses the device to enter their starting point and destination. The device then activates the emotion engine and begins monitoring the user's initial state.

[0354] Step 2:

[0355] The terminal sends the entered information to the server and requests map information and accessibility-related information.

[0356] Step 3:

[0357] The server calculates the optimal travel route based on the received information. In doing so, it prioritizes routes with fewer steps and steep inclines, and takes into account information about barrier-free facilities.

[0358] Step 4:

[0359] The server sends the calculated travel path to the terminal. The terminal receives this, displays it on the user interface, and prepares for voice guidance.

[0360] Step 5:

[0361] As the user begins to move, the device's emotion engine analyzes the user's emotional state in real time. This includes facial recognition using the camera and voice analysis using the microphone.

[0362] Step 6:

[0363] The device sends emotion data detected by the emotion engine to the server. The server receives this data and calculates suggestions based on the user's emotional state.

[0364] Step 7:

[0365] If the user's mood is positive, the server sends options to the device suggesting nearby tourist attractions and relaxation spots.

[0366] Step 8:

[0367] If the user's emotions are negative, the server calculates a more comfortable and calming alternative route and sends it to the terminal.

[0368] Step 9:

[0369] The terminal presents the selected suggestion to the user and continues to provide real-time directional guidance through its voice guidance function.

[0370] Step 10:

[0371] After the user reaches their destination, the device requests feedback on the user's travel experience and provides a function to evaluate the results of the emotion engine's operation.

[0372] Step 11:

[0373] The device sends user feedback and sentiment data to the server.

[0374] Step 12:

[0375] The server stores the received feedback in a database and uses it for future system improvements and training of the emotion engine.

[0376] (Example 2)

[0377] 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".

[0378] Conventional mobility assistance systems have struggled to provide flexible route suggestions that take into account the user's emotions and physical condition, resulting in unsatisfactory travel experiences, particularly for users with physical limitations or those prioritizing comfort. Furthermore, the lack of adaptive route changes in response to real-time emotional changes posed challenges to safety and convenience during travel.

[0379] 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.

[0380] In this invention, the server includes means for receiving information on the starting point and destination from the user, means for acquiring map information and user support-related information, and means for recognizing the user's emotions using an emotion analysis engine. This enables adaptive route suggestions and mobility support based on the user's emotions and physical condition.

[0381] "Means of receiving information" refers to an interface that obtains data such as the starting point and destination from the user and converts it into a format that can be used within the system.

[0382] "Means for acquiring map information and user support-related information" refers to a device or program that acquires geographical information and accessibility information from an external or internal database and processes it for use in route calculation.

[0383] "Means for calculating the optimal travel route" refers to algorithms or software that use received map information and user assistance-related information to calculate the most convenient and safe route for the user.

[0384] "Means of providing users with calculated travel routes" refers to a system that communicates the calculated route to the user via a terminal and provides visual or auditory guidance.

[0385] "Means of providing real-time directional guidance via voice" refers to a device or program that has the function of communicating directions and precautions via voice based on the user's current location.

[0386] "Means of recognizing a user's emotions using an emotion analysis engine" refers to a system that detects the user's voice and facial expressions using sensors, analyzes them with software, and determines their emotional state.

[0387] "Means of adjusting routes and suggestions based on user emotions" refers to a function that improves the travel experience by making optimal route changes or new suggestions based on information obtained through emotion analysis, tailored to the user's state.

[0388] "Means for displaying and providing facility information to users" refers to a display device or software that displays information about facilities along the travel route on the user's terminal and guides them to available services.

[0389] The travel route guidance system in this invention involves the user, terminal, and server cooperating and exchanging information with each other to provide an optimal travel experience tailored to the user's emotional state.

[0390] First, the user enters their starting point and destination into their device. This device is a smartphone or tablet and has the functionality to send the input information to a server through its user interface. The device also has a camera and microphone to sense the user's facial expressions and voice in real time. This hardware works in conjunction with an emotion analysis engine to extract the user's emotional data.

[0391] The server first receives departure and destination information sent from the terminal. Based on this information, the server uses a map API to obtain necessary geographical and accessibility information. The server then calculates the optimal travel route, taking into account obstacles and terrain features, using an algorithm (e.g., Dijkstra's algorithm or A algorithm), and formats the result as voice guidance. The voice guidance is provided to the user through the terminal, using a commonly used voice output service.

[0392] The device's emotion analysis engine analyzes the user's facial expressions and tone of voice in real time while they are on the move to determine their emotional state. The server receives this emotion data from the device, and if the user is showing positive emotions, it suggests new spots along the proposed route, such as tourist attractions or relaxation facilities. On the other hand, if the user is showing stress or discomfort, a more comfortable travel route is suggested.

[0393] As a concrete example, imagine a scenario where a server suggests a nearby park via a device that detects a user's smile while they are sightseeing in a city. This would allow the user to enjoy an unexpected sightseeing spot that wasn't originally in their plan.

[0394] An example of a prompt for the generation AI model would be: "Please generate natural language that recognizes the positive emotions the user is feeling while traveling and suggests spots that align with those emotions." This system would allow users to enjoy a flexible travel experience that responds to their emotional state, significantly improving safety and comfort during travel.

[0395] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0396] Step 1:

[0397] The user enters their starting point and destination into the terminal. The entered information is then prepared to be sent to the server via the terminal's interface. The input data is converted into the format necessary to access the map API and used to obtain accurate geographic information. The terminal verifies the user's input and formats the data.

[0398] Step 2:

[0399] The server receives departure and destination information sent from the terminal. Using this information as input, the server performs data calculations to obtain geographical and accessibility information via a map API. The output is detailed map information and user assistance information associated with that location. Here, the server performs specific actions such as managing API keys and configuring communication endpoints.

[0400] Step 3:

[0401] The server uses acquired map information to calculate the optimal travel route. The input consists of map information and accessibility information, and the server applies a route-finding algorithm based on this information. The output is the optimized route data. Algorithms such as Dijkstra's and A are used in the calculation, allowing the server to perform efficient route finding.

[0402] Step 4:

[0403] The server formats the calculated travel path into an audio guidance format and generates a script. This generated script is then prepared to match the audio output service used by the user. The output is audio guidance data that is given to the user in real time. The server performs a process to convert text information into audio data.

[0404] Step 5:

[0405] The device uses its camera and microphone to capture the user's facial expressions and voice in real time. Based on these sensor inputs, the device activates an emotion analysis engine and performs data calculations to analyze the user's emotions. The output is numerical or labeled data of the user's emotional state. The device then proceeds with processing such as facial expression detection and voice analysis.

[0406] Step 6:

[0407] The server adjusts routes and suggestions based on emotion data received from the terminal. This process uses emotion analysis data as input to evaluate routes and create suggestions. For example, it might select new stops based on positive emotions. The output is adjusted route guidance data tailored to the emotions. The server dynamically changes suggestions using conditional branching and other methods.

[0408] This process enables the system to provide flexible guidance and an optimal travel experience tailored to the user's emotional state.

[0409] (Application Example 2)

[0410] 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."

[0411] Existing barrier-free guidance systems do not provide mobility assistance that takes into account the user's emotional state, making it difficult to reduce stress and fatigue during travel. Furthermore, route suggestions are not optimized based on the individual user's emotions, resulting in insufficient support, especially for users who prioritize emotional comfort. This leads to a challenge in that the value of the user's travel experience is not sufficiently enhanced.

[0412] 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.

[0413] In this invention, the server includes means for recognizing the user's emotional state, means for acquiring map information and accessibility-related information, and means for suggesting appropriate facility information based on the emotional state. This makes it possible to provide an optimal travel experience that responds to the user's emotions.

[0414] "Means for receiving departure and destination information from the user" refers to a device or method for acquiring departure and arrival data entered by the user.

[0415] "Means for acquiring map information and barrier-free related information" refers to a device or method for acquiring geographical location data and barrier-free data such as the presence or absence of steps and ramps.

[0416] "Means for calculating the optimal travel route considering steps and steep slopes" refers to a device or method for calculating the most appropriate travel route among routes that include steps and steep slopes that may occur during travel.

[0417] "Means for providing a calculated travel route to a user" refers to a device or method for notifying or presenting a calculated travel route to a user.

[0418] "Means for providing real-time direction guidance via voice guidance" refers to a device or method that generates and transmits real-time voice information indicating direction to the user.

[0419] "Means for displaying and providing facility information to users" means a device or method for displaying information about a facility to users in a visual or other format.

[0420] "Means for recognizing a user's emotional state" refers to a device or method that analyzes data such as a user's facial expressions and tone of voice to evaluate their emotional state.

[0421] "Means for suggesting appropriate facility information based on emotional state" refers to a device or method that suggests information about relevant facilities or locations in accordance with the user's emotions.

[0422] To realize this invention, an advanced barrier-free route guidance system including an emotion recognition engine is used. This system provides mobility assistance to the user by combining multiple terminals and servers. The server receives information about the starting point and destination from the user and acquires map information and barrier-free related information. The terminal recognizes the user's emotional state in real time using sensor data such as facial expressions and voice tone.

[0423] This system uses software that provides real-time directional guidance via voice (e.g., Google Text-to-Speech API) and a map information API (e.g., Google Maps API) to obtain map information. The emotion recognition algorithm is implemented in a programming language such as Python and suggests appropriate facility information based on the user's emotions.

[0424] As a concrete example, a user accesses the system using a smartphone or tablet and enters their starting point and destination. If the device detects the user's cheerful expression during their journey, the server suggests nearby relaxation spots such as parks or cafes based on the emotional data. This allows the user to enjoy a comfortable travel experience that is tailored to their emotional state.

[0425] An example of a prompt message is, "If the user is smiling, generate a route and comments suggesting nearby tourist attractions." This allows the system to use a generative AI model to provide the user with the most relevant information.

[0426] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0427] Step 1:

[0428] The user enters the departure point and destination information into the device.

[0429] The information entered is collected as data transmitted from the terminal to the server. This data is then used as basic information for subsequent mobility assistance.

[0430] Step 2:

[0431] Based on the received departure and destination information, the server retrieves map information and accessibility-related information from an external map API.

[0432] This information is used to calculate the optimal travel route, taking into account factors such as steps and steep inclines. The calculated route becomes the output data for the terminal.

[0433] Step 3:

[0434] The device collects the user's facial expressions and voice tone as sensor data.

[0435] This data is analyzed in real time by a built-in emotion recognition algorithm and used to identify the user's emotional state (e.g., positive, negative).

[0436] Step 4:

[0437] The emotion recognition engine on the device sends emotion data to the server.

[0438] Based on this sentiment data, the server invokes a generative AI model to suggest appropriate facility information along the route (such as tourist attractions or places to relax) and generates prompt messages. The generated information is then provided to the terminal as output data.

[0439] Step 5:

[0440] The terminal provides the user with route information and schedule suggestions received from the server in both voice and display formats.

[0441] The voice guidance system utilizes a speech synthesis API and includes specific actions such as providing directions and recommendations to the user in real time.

[0442] Step 6:

[0443] Once the user's movement is complete, feedback information is sent to the server via the device.

[0444] The server collects this feedback and uses it as data to improve the accuracy of sentiment analysis and path calculation.

[0445] This series of processes makes it possible to provide an optimal travel experience that is tailored to the user's emotions.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] [Third Embodiment]

[0450] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0451] 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.

[0452] 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).

[0453] 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.

[0454] 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.

[0455] 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).

[0456] 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.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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.

[0461] 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".

[0462] This invention is a barrier-free route guidance system designed to enable people to travel safely and comfortably. It is realized through data exchange between a server, a terminal, and a user. The server receives information on the starting point and destination transmitted by the user and calculates the optimal route based on this information. The calculation uses map information and barrier-free related information, prioritizing the selection of routes with fewer steps and steep inclines.

[0463] Users can use their devices to obtain real-time route information provided by the server. This information includes details about barrier-free facilities around the destination and recommended routes tailored to user needs. Furthermore, devices equipped with voice guidance support users to ensure their safe travel and provide directional instructions at specific times.

[0464] As a concrete example, consider a case where a user using a wheelchair visits a tourist destination in an urban area. The user enters their current location as the starting point and the tourist destination as the destination into the terminal. This information is sent to the server, which uses geographical information and accessibility-related information to calculate the safest and most comfortable route. The route calculated by the server includes stations with elevators and sidewalks with ramps, and this information is sent to the user. The terminal uses this information received from the server to guide the user to the appropriate route via voice guidance. After completing their journey, the user can provide feedback, which will be used to improve the accuracy of guidance in the future.

[0465] As described above, this invention aims to provide users with specific needs with freedom of movement and to realize a more comfortable travel experience.

[0466] The following describes the processing flow.

[0467] Step 1:

[0468] The user launches the application on their device and enters their starting point and destination. They can also optionally select whether they will be using a wheelchair or stroller.

[0469] Step 2:

[0470] The terminal receives input from the user and sends it to the server as a request. The request includes information about the departure point and destination.

[0471] Step 3:

[0472] When the server receives a request from a terminal, it accesses a map information service to retrieve the latest geographic data. At the same time, it also retrieves information on facilities related to accessibility.

[0473] Step 4:

[0474] The server analyzes the acquired map information and prioritizes searching for routes with fewer steps and steep inclines. It also utilizes information on nearby barrier-free facilities during the search process.

[0475] Step 5:

[0476] The server evaluates multiple calculated routes and selects the safest and most comfortable route for the user. Based on the evaluation results, it determines the optimal route.

[0477] Step 6:

[0478] The server sends the selected route information to the user's terminal. The transmitted data includes location information for elevators and ramps.

[0479] Step 7:

[0480] The terminal processes the route information received from the server and displays it visually on the user interface.

[0481] Step 8:

[0482] Once the user starts moving, the device uses its built-in GPS function to constantly track the user's current location.

[0483] Step 9:

[0484] While in motion, the device provides voice guidance at pre-set landmarks and intersections, directing the user in the appropriate direction.

[0485] Step 10:

[0486] After the user reaches their destination, the device displays a prompt for user feedback and collects feedback data.

[0487] Step 11:

[0488] The device sends user feedback to the server.

[0489] Step 12:

[0490] The server stores the received feedback in a database and uses it to improve the accuracy of future route calculations.

[0491] (Example 1)

[0492] 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."

[0493] In modern society, freedom of movement is a fundamental right, but physical obstacles such as steps and steep slopes pose significant barriers, especially for those who require barrier-free access. Therefore, route guidance that allows everyone to move safely and comfortably is necessary. Furthermore, conventional route calculation systems have not adequately utilized individual user feedback to improve guidance accuracy. In response, there is a need for a system that prioritizes barrier-free information based on user feedback and improves guidance accuracy.

[0494] 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.

[0495] In this invention, the server includes a device for receiving information on the starting and destination locations from the user, a device for acquiring spatial information and barrier-free related information, and a device for calculating the optimal travel route considering physical obstacles and steep terrain. This enables safe and comfortable travel guidance, especially for users who require barrier-free access.

[0496] A "user" refers to an individual or legal entity that uses the system to input its starting point and destination and receive guidance regarding travel.

[0497] "Starting location" refers to the geographical point that serves as the starting point for the user's movement.

[0498] "Destination location" refers to the geographical point that the user designates as the end point of their journey.

[0499] "Device" refers to a component of hardware or software designed to perform a specific function.

[0500] "Spatial information" is a general term for information that includes data about geographical location and topography.

[0501] "Barrier-free related information" refers to information related to facilities and equipment that reduce or eliminate physical barriers.

[0502] "Physical obstacles" refer to topographical or structural elements such as steps or steep slopes that hinder movement.

[0503] "Steep terrain" refers to geographical features with steep slopes or dramatic changes in terrain.

[0504] A "travel route" refers to the path a user takes to travel from their starting point to their destination.

[0505] A "generative AI model" refers to an artificial intelligence algorithm that learns from user feedback and improves the accuracy of system guidance.

[0506] This barrier-free route guidance system provides a mechanism to support safe and comfortable travel by exchanging information among three parties: the server, the terminal, and the user.

[0507] The server begins its role by receiving information about the user's starting and destination locations. This information is transmitted from the terminal to the server using a common communication protocol. The server then acquires spatial information related to geographical location and terrain, and further retrieves information about obstacles and facilities from accessibility-related databases. As a specific example, the server utilizes general-purpose map data as an API service when acquiring map information.

[0508] The terminal receives optimal route information calculated from the server based on the information entered by the user. The received data includes information on barrier-free facilities along the user's route, allowing the user to receive real-time voice guidance. This voice direction guidance is automatically generated based on geographical location information and provided to the user at the appropriate time while they are on the move.

[0509] As a concrete example, consider a case where a user using a wheelchair visits a specific tourist destination in an urban area. The user inputs their current location as the starting point and the tourist destination as the destination via a terminal. This information is sent to a server, which calculates the optimal route, including facilities with elevators and paths with minimal steps, based on map information and accessibility-related information. The terminal then provides the user with specific route instructions via voice guidance, such as, "Turn left at the next intersection, proceed 50 meters, and then enter the facility with a ramp on your right."

[0510] Finally, users provide feedback after completing their journey, which helps improve the accuracy of future route guidance. The generative AI model learns from user feedback and uses it to improve future guidance, so the overall system performance improves with continued use.

[0511] Examples of prompt statements include the following:

[0512] "We want to create a system that provides barrier-free and safe route guidance for wheelchair users. Please tell us what kind of data we should use and how we should utilize it."

[0513] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0514] Step 1:

[0515] The user enters the starting point and destination using the terminal. This input information is formatted by the terminal and output as a request to the server. The terminal can automatically obtain the current location using its GPS function and set it as the starting point. It is also possible to specify the destination using voice input.

[0516] Step 2:

[0517] The terminal sends the entered starting point and destination information to the server. The server receives this data and treats it as input data to begin calculation processing. The received information includes the user's current location and desired destination, and this is used to process the data in the next step.

[0518] Step 3:

[0519] The server acquires spatial information and accessibility-related information based on the received data. It uses a geographic information service API to obtain map data for the starting point and destination. It also collects information on nearby accessibility facilities from reliable public databases. This information is output as input data for route calculation in the next step.

[0520] Step 4:

[0521] The server calculates the optimal travel route to avoid physical obstacles based on acquired map data and accessibility information. This calculation uses algorithms such as Dijkstra's algorithm to select routes that avoid steps and steep slopes. The output of this step is the route information that the user should use for travel.

[0522] Step 5:

[0523] The server sends the calculated travel path information to the terminal. This information includes detailed information such as the locations of elevators and ramps. Upon receiving this information, the terminal prepares to guide the user to the next step.

[0524] Step 6:

[0525] The terminal provides real-time voice guidance to the user based on the received route information. At this stage, it uses speech synthesis to automatically generate and output appropriate directional instructions when approaching important points along the route. For example, it provides specific guidance such as, "Turn right at the intersection 50 meters ahead, then proceed 5 meters and you will find an elevator on your left."

[0526] Step 7:

[0527] After completing their journey, users provide feedback on the comfort and effectiveness of the guided route. The terminal collects this feedback and sends it to the server. This information is used to train a generative AI model and improve the accuracy of route calculation and guidance in the future. User evaluations also contribute to future updates as data for reviewing the entire system.

[0528] (Application Example 1)

[0529] 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."

[0530] In the current urban environment, it is difficult for individuals with physical disabilities to obtain appropriate information that will allow them to move comfortably and safely. This lack of information restricts freedom of movement and hinders users, especially those who require barrier-free facilities, from enjoying the conveniences of the city. Furthermore, the lack of real-time guidance and insufficient system improvements based on user feedback are also challenges.

[0531] 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.

[0532] In this invention, the server includes means for receiving current location information and destination location information, means for acquiring geographic data and barrier-free related data, and means for calculating an appropriate travel route to avoid obstacles. This enables users to use the optimal barrier-free route in real time and move around the city with peace of mind. Furthermore, it allows for guidance using speech synthesis and continuous improvement of the system through the use of feedback.

[0533] "Current location information" is data used to identify the geographical location where the user is currently located.

[0534] "Destination location information" is data that indicates the geographical location of the destination the user is aiming for.

[0535] "Geographic data" refers to data that includes geographical information about a specific area, including topography and infrastructure.

[0536] "Barrier-free related data" refers to data that provides information about routes and facilities that are free from obstacles.

[0537] "Obstacles" refer to physical structures, steps, and other obstacles that hinder the user's movement.

[0538] A "travel route" is route information that shows the optimal path from your current location to your destination.

[0539] "Speech synthesis" is a technology that reads text data and outputs it as a human voice.

[0540] "Guidance" refers to the act of providing users with the information they need to reach their destination.

[0541] "Feedback" refers to opinions and evaluations from users after they have used a system, and is information used to improve the system.

[0542] This invention is a system that supports barrier-free mobility, and is realized through the respective roles of the server, terminal, and user.

[0543] The server receives the user's current location and destination location information and retrieves geographic data using a geographic data API (e.g., Google Maps API). Furthermore, it obtains necessary accessibility data from accessibility databases. Based on this information, the server calculates the optimal accessibility route. The calculated travel route is provided to the user in real time using speech synthesis technology (e.g., Google Text-to-Speech).

[0544] The terminal visualizes route information received from the server and displays it on a map. While the user is moving, it provides real-time direction guidance and additional facility-related data through voice guidance. It also collects user feedback and sends it to the server to help improve the system.

[0545] For example, when a user visits a city park in a wheelchair, the system guides them to the location of barrier-free paths and available ramps along the route. Furthermore, it provides information on barrier-free facilities near the destination, supporting the user's smooth movement.

[0546] As an example of a prompt using a generative AI model, the user is presented with the following instruction: "Please enter your current location and destination. The optimal barrier-free route will be calculated. Do you want to start voice guidance?"

[0547] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0548] Step 1:

[0549] The terminal sends the user's current location and destination location information to the server. The input consists of the user's current location and destination, and the server prepares to calculate the route based on this information.

[0550] Step 2:

[0551] The server uses the received current location information and destination location information to call a geographic data API to obtain geographic data. This data acquisition process outputs route information on a map from the API, which is then prepared for the next calculation.

[0552] Step 3:

[0553] The server uses acquired geographical data and accessibility-related databases to calculate the optimal travel route to avoid obstacles. This calculation prioritizes barrier-free routes without steps or steep inclines. The output is the route information for the chosen route.

[0554] Step 4:

[0555] The server sends the calculated travel route information to the terminal. This route information includes details such as routes without steps, available elevators, and ramps. This data sent to the terminal is used in the next guide step.

[0556] Step 5:

[0557] Based on the information it receives, the terminal uses speech synthesis technology to provide real-time route guidance to the user. The voice guidance outputs directional instructions to the user, providing appropriate support while they are on the move.

[0558] Step 6:

[0559] After completing a journey, users enter feedback into their terminal, which is then sent to the server and used to improve the system. This feedback helps to improve the accuracy of future route calculations.

[0560] 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.

[0561] This invention is a more advanced barrier-free route guidance system that incorporates an emotion engine to recognize user emotions. It provides mobility assistance through mutual data exchange between the server, terminal, and user. The server receives information on the starting point and destination, and based on this, acquires map information and barrier-free related information. It has means for calculating the optimal travel route, taking into account steps and steep inclines, and providing it to the user along with voice guidance.

[0562] The emotion engine allows the device to recognize the user's emotional state in real time while they are on the move. This emotional data is analyzed using sensor data such as the user's facial expressions and voice tone. For example, if the user is showing positive emotions, the server will suggest recommended sightseeing spots and relaxation spots along the proposed route. On the other hand, if the system detects that the user is feeling stressed, it will suggest a more comfortable and quiet route.

[0563] As a concrete example, consider a case where a user is sightseeing in a city in a wheelchair. The user enters their starting point and destination into the device, and the system calculates the route on the server based on that information. While traveling, the device's emotion engine monitors the user's reactions in real time. For example, if it detects a cheerful expression, the server suggests a nearby park or cafe, providing an opportunity to relax. Furthermore, feedback obtained after use is sent to the server and used to improve the accuracy of emotion analysis.

[0564] Based on the above, this invention aims to provide a safe and comfortable travel experience that responds to the user's emotional state, and to further improve the flexibility and convenience of travel.

[0565] The following describes the processing flow.

[0566] Step 1:

[0567] The user uses the device to enter their starting point and destination. The device then activates the emotion engine and begins monitoring the user's initial state.

[0568] Step 2:

[0569] The terminal sends the entered information to the server and requests map information and accessibility-related information.

[0570] Step 3:

[0571] The server calculates the optimal travel route based on the received information. In doing so, it prioritizes routes with fewer steps and steep inclines, and takes into account information about barrier-free facilities.

[0572] Step 4:

[0573] The server sends the calculated travel path to the terminal. The terminal receives this, displays it on the user interface, and prepares for voice guidance.

[0574] Step 5:

[0575] As the user begins to move, the device's emotion engine analyzes the user's emotional state in real time. This includes facial recognition using the camera and voice analysis using the microphone.

[0576] Step 6:

[0577] The device sends emotion data detected by the emotion engine to the server. The server receives this data and calculates suggestions based on the user's emotional state.

[0578] Step 7:

[0579] If the user's mood is positive, the server sends options to the device suggesting nearby tourist attractions and relaxation spots.

[0580] Step 8:

[0581] If the user's emotions are negative, the server calculates a more comfortable and calming alternative route and sends it to the terminal.

[0582] Step 9:

[0583] The terminal presents the selected suggestion to the user and continues to provide real-time directional guidance through its voice guidance function.

[0584] Step 10:

[0585] After the user reaches their destination, the device requests feedback on the user's travel experience and provides a function to evaluate the results of the emotion engine's operation.

[0586] Step 11:

[0587] The device sends user feedback and sentiment data to the server.

[0588] Step 12:

[0589] The server stores the received feedback in a database and uses it for future system improvements and training of the emotion engine.

[0590] (Example 2)

[0591] 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."

[0592] Conventional mobility assistance systems have struggled to provide flexible route suggestions that take into account the user's emotions and physical condition, resulting in unsatisfactory travel experiences, particularly for users with physical limitations or those prioritizing comfort. Furthermore, the lack of adaptive route changes in response to real-time emotional changes posed challenges to safety and convenience during travel.

[0593] 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.

[0594] In this invention, the server includes means for receiving information on the starting point and destination from the user, means for acquiring map information and user support-related information, and means for recognizing the user's emotions using an emotion analysis engine. This enables adaptive route suggestions and mobility support based on the user's emotions and physical condition.

[0595] "Means of receiving information" refers to an interface that obtains data such as the starting point and destination from the user and converts it into a format that can be used within the system.

[0596] "Means for acquiring map information and user support-related information" refers to a device or program that acquires geographical information and accessibility information from an external or internal database and processes it for use in route calculation.

[0597] "Means for calculating the optimal travel route" refers to algorithms or software that use received map information and user assistance-related information to calculate the most convenient and safe route for the user.

[0598] "Means of providing users with calculated travel routes" refers to a system that communicates the calculated route to the user via a terminal and provides visual or auditory guidance.

[0599] "Means of providing real-time directional guidance via voice" refers to a device or program that has the function of communicating directions and precautions via voice based on the user's current location.

[0600] "Means of recognizing a user's emotions using an emotion analysis engine" refers to a system that detects the user's voice and facial expressions using sensors, analyzes them with software, and determines their emotional state.

[0601] "Means of adjusting routes and suggestions based on user emotions" refers to a function that improves the travel experience by making optimal route changes or new suggestions based on information obtained through emotion analysis, tailored to the user's state.

[0602] "Means for displaying and providing facility information to users" refers to a display device or software that displays information about facilities along the travel route on the user's terminal and guides them to available services.

[0603] The travel route guidance system in this invention involves the user, terminal, and server cooperating and exchanging information with each other to provide an optimal travel experience tailored to the user's emotional state.

[0604] First, the user enters their starting point and destination into their device. This device is a smartphone or tablet and has the functionality to send the input information to a server through its user interface. The device also has a camera and microphone to sense the user's facial expressions and voice in real time. This hardware works in conjunction with an emotion analysis engine to extract the user's emotional data.

[0605] The server first receives departure and destination information sent from the terminal. Based on this information, the server uses a map API to obtain necessary geographical and accessibility information. The server then calculates the optimal travel route, taking into account obstacles and terrain features, using an algorithm (e.g., Dijkstra's algorithm or A algorithm), and formats the result as voice guidance. The voice guidance is provided to the user through the terminal, using a commonly used voice output service.

[0606] The device's emotion analysis engine analyzes the user's facial expressions and tone of voice in real time while they are on the move to determine their emotional state. The server receives this emotion data from the device, and if the user is showing positive emotions, it suggests new spots along the proposed route, such as tourist attractions or relaxation facilities. On the other hand, if the user is showing stress or discomfort, a more comfortable travel route is suggested.

[0607] As a concrete example, imagine a scenario where a server suggests a nearby park via a device that detects a user's smile while they are sightseeing in a city. This would allow the user to enjoy an unexpected sightseeing spot that wasn't originally in their plan.

[0608] An example of a prompt for the generation AI model would be: "Please generate natural language that recognizes the positive emotions the user is feeling while traveling and suggests spots that align with those emotions." This system would allow users to enjoy a flexible travel experience that responds to their emotional state, significantly improving safety and comfort during travel.

[0609] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0610] Step 1:

[0611] The user enters their starting point and destination into the terminal. The entered information is then prepared to be sent to the server via the terminal's interface. The input data is converted into the format necessary to access the map API and used to obtain accurate geographic information. The terminal verifies the user's input and formats the data.

[0612] Step 2:

[0613] The server receives departure and destination information sent from the terminal. Using this information as input, the server performs data calculations to obtain geographical and accessibility information via a map API. The output is detailed map information and user assistance information associated with that location. Here, the server performs specific actions such as managing API keys and configuring communication endpoints.

[0614] Step 3:

[0615] The server uses acquired map information to calculate the optimal travel route. The input consists of map information and accessibility information, and the server applies a route-finding algorithm based on this information. The output is the optimized route data. Algorithms such as Dijkstra's and A are used in the calculation, allowing the server to perform efficient route finding.

[0616] Step 4:

[0617] The server formats the calculated travel path into an audio guidance format and generates a script. This generated script is then prepared to match the audio output service used by the user. The output is audio guidance data that is given to the user in real time. The server performs a process to convert text information into audio data.

[0618] Step 5:

[0619] The device uses its camera and microphone to capture the user's facial expressions and voice in real time. Based on these sensor inputs, the device activates an emotion analysis engine and performs data calculations to analyze the user's emotions. The output is numerical or labeled data of the user's emotional state. The device then proceeds with processing such as facial expression detection and voice analysis.

[0620] Step 6:

[0621] The server adjusts routes and suggestions based on emotion data received from the terminal. This process uses emotion analysis data as input to evaluate routes and create suggestions. For example, it might select new stops based on positive emotions. The output is adjusted route guidance data tailored to the emotions. The server dynamically changes suggestions using conditional branching and other methods.

[0622] This process enables the system to provide flexible guidance and an optimal travel experience tailored to the user's emotional state.

[0623] (Application Example 2)

[0624] 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."

[0625] Existing barrier-free guidance systems do not provide mobility assistance that takes into account the user's emotional state, making it difficult to reduce stress and fatigue during travel. Furthermore, route suggestions are not optimized based on the individual user's emotions, resulting in insufficient support, especially for users who prioritize emotional comfort. This leads to a challenge in that the value of the user's travel experience is not sufficiently enhanced.

[0626] 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.

[0627] In this invention, the server includes means for recognizing the user's emotional state, means for acquiring map information and accessibility-related information, and means for suggesting appropriate facility information based on the emotional state. This makes it possible to provide an optimal travel experience that responds to the user's emotions.

[0628] "Means for receiving departure and destination information from the user" refers to a device or method for acquiring departure and arrival data entered by the user.

[0629] "Means for acquiring map information and barrier-free related information" refers to a device or method for acquiring geographical location data and barrier-free data such as the presence or absence of steps and ramps.

[0630] "Means for calculating the optimal travel route considering steps and steep slopes" refers to a device or method for calculating the most appropriate travel route among routes that include steps and steep slopes that may occur during travel.

[0631] "Means for providing a calculated travel route to a user" refers to a device or method for notifying or presenting a calculated travel route to a user.

[0632] "Means for providing real-time direction guidance via voice guidance" refers to a device or method that generates and transmits real-time voice information indicating direction to the user.

[0633] "Means for displaying and providing facility information to users" means a device or method for displaying information about a facility to users in a visual or other format.

[0634] "Means for recognizing a user's emotional state" refers to a device or method that analyzes data such as a user's facial expressions and tone of voice to evaluate their emotional state.

[0635] "Means for suggesting appropriate facility information based on emotional state" refers to a device or method that suggests information about relevant facilities or locations in accordance with the user's emotions.

[0636] To realize this invention, an advanced barrier-free route guidance system including an emotion recognition engine is used. This system provides mobility assistance to the user by combining multiple terminals and servers. The server receives information about the starting point and destination from the user and acquires map information and barrier-free related information. The terminal recognizes the user's emotional state in real time using sensor data such as facial expressions and voice tone.

[0637] This system uses software that provides real-time directional guidance via voice (e.g., Google Text-to-Speech API) and a map information API (e.g., Google Maps API) to obtain map information. The emotion recognition algorithm is implemented in a programming language such as Python and suggests appropriate facility information based on the user's emotions.

[0638] As a concrete example, a user accesses the system using a smartphone or tablet and enters their starting point and destination. If the device detects the user's cheerful expression during their journey, the server suggests nearby relaxation spots such as parks or cafes based on the emotional data. This allows the user to enjoy a comfortable travel experience that is tailored to their emotional state.

[0639] An example of a prompt message is, "If the user is smiling, generate a route and comments suggesting nearby tourist attractions." This allows the system to use a generative AI model to provide the user with the most relevant information.

[0640] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0641] Step 1:

[0642] The user enters the departure point and destination information into the device.

[0643] The information entered is collected as data transmitted from the terminal to the server. This data is then used as basic information for subsequent mobility assistance.

[0644] Step 2:

[0645] Based on the received departure and destination information, the server retrieves map information and accessibility-related information from an external map API.

[0646] This information is used to calculate the optimal travel route, taking into account factors such as steps and steep inclines. The calculated route becomes the output data for the terminal.

[0647] Step 3:

[0648] The device collects the user's facial expressions and voice tone as sensor data.

[0649] This data is analyzed in real time by a built-in emotion recognition algorithm and used to identify the user's emotional state (e.g., positive, negative).

[0650] Step 4:

[0651] The emotion recognition engine on the device sends emotion data to the server.

[0652] Based on this sentiment data, the server invokes a generative AI model to suggest appropriate facility information along the route (such as tourist attractions or places to relax) and generates prompt messages. The generated information is then provided to the terminal as output data.

[0653] Step 5:

[0654] The terminal provides the user with route information and schedule suggestions received from the server in both voice and display formats.

[0655] The voice guidance system utilizes a speech synthesis API and includes specific actions such as providing directions and recommendations to the user in real time.

[0656] Step 6:

[0657] Once the user's movement is complete, feedback information is sent to the server via the device.

[0658] The server collects this feedback and uses it as data to improve the accuracy of sentiment analysis and path calculation.

[0659] This series of processes makes it possible to provide an optimal travel experience that is tailored to the user's emotions.

[0660] 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.

[0661] 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.

[0662] 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.

[0663] [Fourth Embodiment]

[0664] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0665] 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.

[0666] 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).

[0667] 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.

[0668] 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.

[0669] 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).

[0670] 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.

[0671] 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.

[0672] 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.

[0673] 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.

[0674] 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.

[0675] 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.

[0676] 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".

[0677] This invention is a barrier-free route guidance system designed to enable people to travel safely and comfortably. It is realized through data exchange between a server, a terminal, and a user. The server receives information on the starting point and destination transmitted by the user and calculates the optimal route based on this information. The calculation uses map information and barrier-free related information, prioritizing the selection of routes with fewer steps and steep inclines.

[0678] Users can use their devices to obtain real-time route information provided by the server. This information includes details about barrier-free facilities around the destination and recommended routes tailored to user needs. Furthermore, devices equipped with voice guidance support users to ensure their safe travel and provide directional instructions at specific times.

[0679] As a concrete example, consider a case where a user using a wheelchair visits a tourist destination in an urban area. The user enters their current location as the starting point and the tourist destination as the destination into the terminal. This information is sent to the server, which uses geographical information and accessibility-related information to calculate the safest and most comfortable route. The route calculated by the server includes stations with elevators and sidewalks with ramps, and this information is sent to the user. The terminal uses this information received from the server to guide the user to the appropriate route via voice guidance. After completing their journey, the user can provide feedback, which will be used to improve the accuracy of guidance in the future.

[0680] As described above, this invention aims to provide users with specific needs with freedom of movement and to realize a more comfortable travel experience.

[0681] The following describes the processing flow.

[0682] Step 1:

[0683] The user launches the application on their device and enters their starting point and destination. They can also optionally select whether they will be using a wheelchair or stroller.

[0684] Step 2:

[0685] The terminal receives input from the user and sends it to the server as a request. The request includes information about the departure point and destination.

[0686] Step 3:

[0687] When the server receives a request from a terminal, it accesses a map information service to retrieve the latest geographic data. At the same time, it also retrieves information on facilities related to accessibility.

[0688] Step 4:

[0689] The server analyzes the acquired map information and prioritizes searching for routes with fewer steps and steep inclines. It also utilizes information on nearby barrier-free facilities during the search process.

[0690] Step 5:

[0691] The server evaluates multiple calculated routes and selects the safest and most comfortable route for the user. Based on the evaluation results, it determines the optimal route.

[0692] Step 6:

[0693] The server sends the selected route information to the user's terminal. The transmitted data includes location information for elevators and ramps.

[0694] Step 7:

[0695] The terminal processes the route information received from the server and displays it visually on the user interface.

[0696] Step 8:

[0697] Once the user starts moving, the device uses its built-in GPS function to constantly track the user's current location.

[0698] Step 9:

[0699] While in motion, the device provides voice guidance at pre-set landmarks and intersections, directing the user in the appropriate direction.

[0700] Step 10:

[0701] After the user reaches their destination, the device displays a prompt for user feedback and collects feedback data.

[0702] Step 11:

[0703] The device sends user feedback to the server.

[0704] Step 12:

[0705] The server stores the received feedback in a database and uses it to improve the accuracy of future route calculations.

[0706] (Example 1)

[0707] 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".

[0708] In modern society, freedom of movement is a fundamental right, but physical obstacles such as steps and steep slopes pose significant barriers, especially for those who require barrier-free access. Therefore, route guidance that allows everyone to move safely and comfortably is necessary. Furthermore, conventional route calculation systems have not adequately utilized individual user feedback to improve guidance accuracy. In response, there is a need for a system that prioritizes barrier-free information based on user feedback and improves guidance accuracy.

[0709] 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.

[0710] In this invention, the server includes a device for receiving information on the starting and destination locations from the user, a device for acquiring spatial information and barrier-free related information, and a device for calculating the optimal travel route considering physical obstacles and steep terrain. This enables safe and comfortable travel guidance, especially for users who require barrier-free access.

[0711] A "user" refers to an individual or legal entity that uses the system to input its starting point and destination and receive guidance regarding travel.

[0712] "Starting location" refers to the geographical point that serves as the starting point for the user's movement.

[0713] "Destination location" refers to the geographical point that the user designates as the end point of their journey.

[0714] "Device" refers to a component of hardware or software designed to perform a specific function.

[0715] "Spatial information" is a general term for information that includes data about geographical location and topography.

[0716] "Barrier-free related information" refers to information related to facilities and equipment that reduce or eliminate physical barriers.

[0717] "Physical obstacles" refer to topographical or structural elements such as steps or steep slopes that hinder movement.

[0718] "Steep terrain" refers to geographical features with steep slopes or dramatic changes in terrain.

[0719] A "travel route" refers to the path a user takes to travel from their starting point to their destination.

[0720] A "generative AI model" refers to an artificial intelligence algorithm that learns from user feedback and improves the accuracy of system guidance.

[0721] This barrier-free route guidance system provides a mechanism to support safe and comfortable travel by exchanging information among three parties: the server, the terminal, and the user.

[0722] The server begins its role by receiving information about the user's starting and destination locations. This information is transmitted from the terminal to the server using a common communication protocol. The server then acquires spatial information related to geographical location and terrain, and further retrieves information about obstacles and facilities from accessibility-related databases. As a specific example, the server utilizes general-purpose map data as an API service when acquiring map information.

[0723] The terminal receives optimal route information calculated from the server based on the information entered by the user. The received data includes information on barrier-free facilities along the user's route, allowing the user to receive real-time voice guidance. This voice direction guidance is automatically generated based on geographical location information and provided to the user at the appropriate time while they are on the move.

[0724] As a concrete example, consider a case where a user using a wheelchair visits a specific tourist destination in an urban area. The user inputs their current location as the starting point and the tourist destination as the destination via a terminal. This information is sent to a server, which calculates the optimal route, including facilities with elevators and paths with minimal steps, based on map information and accessibility-related information. The terminal then provides the user with specific route instructions via voice guidance, such as, "Turn left at the next intersection, proceed 50 meters, and then enter the facility with a ramp on your right."

[0725] Finally, users provide feedback after completing their journey, which helps improve the accuracy of future route guidance. The generative AI model learns from user feedback and uses it to improve future guidance, so the overall system performance improves with continued use.

[0726] Examples of prompt statements include the following:

[0727] "We want to create a system that provides barrier-free and safe route guidance for wheelchair users. Please tell us what kind of data we should use and how we should utilize it."

[0728] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0729] Step 1:

[0730] The user enters the starting point and destination using the terminal. This input information is formatted by the terminal and output as a request to the server. The terminal can automatically obtain the current location using its GPS function and set it as the starting point. It is also possible to specify the destination using voice input.

[0731] Step 2:

[0732] The terminal sends the entered starting point and destination information to the server. The server receives this data and treats it as input data to begin calculation processing. The received information includes the user's current location and desired destination, and this is used to process the data in the next step.

[0733] Step 3:

[0734] The server acquires spatial information and accessibility-related information based on the received data. It uses a geographic information service API to obtain map data for the starting point and destination. It also collects information on nearby accessibility facilities from reliable public databases. This information is output as input data for route calculation in the next step.

[0735] Step 4:

[0736] The server calculates the optimal travel route to avoid physical obstacles based on acquired map data and accessibility information. This calculation uses algorithms such as Dijkstra's algorithm to select routes that avoid steps and steep slopes. The output of this step is the route information that the user should use for travel.

[0737] Step 5:

[0738] The server sends the calculated travel path information to the terminal. This information includes detailed information such as the locations of elevators and ramps. Upon receiving this information, the terminal prepares to guide the user to the next step.

[0739] Step 6:

[0740] The terminal provides real-time voice guidance to the user based on the received route information. At this stage, it uses speech synthesis to automatically generate and output appropriate directional instructions when approaching important points along the route. For example, it provides specific guidance such as, "Turn right at the intersection 50 meters ahead, then proceed 5 meters and you will find an elevator on your left."

[0741] Step 7:

[0742] After completing their journey, users provide feedback on the comfort and effectiveness of the guided route. The terminal collects this feedback and sends it to the server. This information is used to train a generative AI model and improve the accuracy of route calculation and guidance in the future. User evaluations also contribute to future updates as data for reviewing the entire system.

[0743] (Application Example 1)

[0744] 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".

[0745] In the current urban environment, it is difficult for individuals with physical disabilities to obtain appropriate information that will allow them to move comfortably and safely. This lack of information restricts freedom of movement and hinders users, especially those who require barrier-free facilities, from enjoying the conveniences of the city. Furthermore, the lack of real-time guidance and insufficient system improvements based on user feedback are also challenges.

[0746] 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.

[0747] In this invention, the server includes means for receiving current location information and destination location information, means for acquiring geographic data and barrier-free related data, and means for calculating an appropriate travel route to avoid obstacles. This enables users to use the optimal barrier-free route in real time and move around the city with peace of mind. Furthermore, it allows for guidance using speech synthesis and continuous improvement of the system through the use of feedback.

[0748] "Current location information" is data used to identify the geographical location where the user is currently located.

[0749] "Destination location information" is data that indicates the geographical location of the destination the user is aiming for.

[0750] "Geographic data" refers to data that includes geographical information about a specific area, including topography and infrastructure.

[0751] "Barrier-free related data" refers to data that provides information about routes and facilities that are free from obstacles.

[0752] "Obstacles" refer to physical structures, steps, and other obstacles that hinder the user's movement.

[0753] A "travel route" is route information that shows the optimal path from your current location to your destination.

[0754] "Speech synthesis" is a technology that reads text data and outputs it as a human voice.

[0755] "Guidance" refers to the act of providing users with the information they need to reach their destination.

[0756] "Feedback" refers to opinions and evaluations from users after they have used a system, and is information used to improve the system.

[0757] This invention is a system that supports barrier-free mobility, and is realized through the respective roles of the server, terminal, and user.

[0758] The server receives the user's current location and destination location information and retrieves geographic data using a geographic data API (e.g., Google Maps API). Furthermore, it obtains necessary accessibility data from accessibility databases. Based on this information, the server calculates the optimal accessibility route. The calculated travel route is provided to the user in real time using speech synthesis technology (e.g., Google Text-to-Speech).

[0759] The terminal visualizes route information received from the server and displays it on a map. While the user is moving, it provides real-time direction guidance and additional facility-related data through voice guidance. It also collects user feedback and sends it to the server to help improve the system.

[0760] For example, when a user visits a city park in a wheelchair, the system guides them to the location of barrier-free paths and available ramps along the route. Furthermore, it provides information on barrier-free facilities near the destination, supporting the user's smooth movement.

[0761] As an example of a prompt using a generative AI model, the user is presented with the following instruction: "Please enter your current location and destination. The optimal barrier-free route will be calculated. Do you want to start voice guidance?"

[0762] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0763] Step 1:

[0764] The terminal sends the user's current location and destination location information to the server. The input consists of the user's current location and destination, and the server prepares to calculate the route based on this information.

[0765] Step 2:

[0766] The server uses the received current location information and destination location information to call a geographic data API to obtain geographic data. This data acquisition process outputs route information on a map from the API, which is then prepared for the next calculation.

[0767] Step 3:

[0768] The server uses acquired geographical data and accessibility-related databases to calculate the optimal travel route to avoid obstacles. This calculation prioritizes barrier-free routes without steps or steep inclines. The output is the route information for the chosen route.

[0769] Step 4:

[0770] The server sends the calculated travel route information to the terminal. This route information includes details such as routes without steps, available elevators, and ramps. This data sent to the terminal is used in the next guide step.

[0771] Step 5:

[0772] Based on the information it receives, the terminal uses speech synthesis technology to provide real-time route guidance to the user. The voice guidance outputs directional instructions to the user, providing appropriate support while they are on the move.

[0773] Step 6:

[0774] After completing a journey, users enter feedback into their terminal, which is then sent to the server and used to improve the system. This feedback helps to improve the accuracy of future route calculations.

[0775] 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.

[0776] This invention is a more advanced barrier-free route guidance system that incorporates an emotion engine to recognize user emotions. It provides mobility assistance through mutual data exchange between the server, terminal, and user. The server receives information on the starting point and destination, and based on this, acquires map information and barrier-free related information. It has means for calculating the optimal travel route, taking into account steps and steep inclines, and providing it to the user along with voice guidance.

[0777] The emotion engine allows the device to recognize the user's emotional state in real time while they are on the move. This emotional data is analyzed using sensor data such as the user's facial expressions and voice tone. For example, if the user is showing positive emotions, the server will suggest recommended sightseeing spots and relaxation spots along the proposed route. On the other hand, if the system detects that the user is feeling stressed, it will suggest a more comfortable and quiet route.

[0778] As a concrete example, consider a case where a user is sightseeing in a city in a wheelchair. The user enters their starting point and destination into the device, and the system calculates the route on the server based on that information. While traveling, the device's emotion engine monitors the user's reactions in real time. For example, if it detects a cheerful expression, the server suggests a nearby park or cafe, providing an opportunity to relax. Furthermore, feedback obtained after use is sent to the server and used to improve the accuracy of emotion analysis.

[0779] Based on the above, this invention aims to provide a safe and comfortable travel experience that responds to the user's emotional state, and to further improve the flexibility and convenience of travel.

[0780] The following describes the processing flow.

[0781] Step 1:

[0782] The user uses the device to enter their starting point and destination. The device then activates the emotion engine and begins monitoring the user's initial state.

[0783] Step 2:

[0784] The terminal sends the entered information to the server and requests map information and accessibility-related information.

[0785] Step 3:

[0786] The server calculates the optimal travel route based on the received information. In doing so, it prioritizes routes with fewer steps and steep inclines, and takes into account information about barrier-free facilities.

[0787] Step 4:

[0788] The server sends the calculated travel path to the terminal. The terminal receives this, displays it on the user interface, and prepares for voice guidance.

[0789] Step 5:

[0790] As the user begins to move, the device's emotion engine analyzes the user's emotional state in real time. This includes facial recognition using the camera and voice analysis using the microphone.

[0791] Step 6:

[0792] The device sends emotion data detected by the emotion engine to the server. The server receives this data and calculates suggestions based on the user's emotional state.

[0793] Step 7:

[0794] If the user's mood is positive, the server sends options to the device suggesting nearby tourist attractions and relaxation spots.

[0795] Step 8:

[0796] If the user's emotions are negative, the server calculates a more comfortable and calming alternative route and sends it to the terminal.

[0797] Step 9:

[0798] The terminal presents the selected suggestion to the user and continues to provide real-time directional guidance through its voice guidance function.

[0799] Step 10:

[0800] After the user reaches their destination, the device requests feedback on the user's travel experience and provides a function to evaluate the results of the emotion engine's operation.

[0801] Step 11:

[0802] The device sends user feedback and sentiment data to the server.

[0803] Step 12:

[0804] The server stores the received feedback in a database and uses it for future system improvements and training of the emotion engine.

[0805] (Example 2)

[0806] 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".

[0807] Conventional mobility assistance systems have struggled to provide flexible route suggestions that take into account the user's emotions and physical condition, resulting in unsatisfactory travel experiences, particularly for users with physical limitations or those prioritizing comfort. Furthermore, the lack of adaptive route changes in response to real-time emotional changes posed challenges to safety and convenience during travel.

[0808] 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.

[0809] In this invention, the server includes means for receiving information on the starting point and destination from the user, means for acquiring map information and user support-related information, and means for recognizing the user's emotions using an emotion analysis engine. This enables adaptive route suggestions and mobility support based on the user's emotions and physical condition.

[0810] "Means of receiving information" refers to an interface that obtains data such as the starting point and destination from the user and converts it into a format that can be used within the system.

[0811] "Means for acquiring map information and user support-related information" refers to a device or program that acquires geographical information and accessibility information from an external or internal database and processes it for use in route calculation.

[0812] "Means for calculating the optimal travel route" refers to algorithms or software that use received map information and user assistance-related information to calculate the most convenient and safe route for the user.

[0813] "Means of providing users with calculated travel routes" refers to a system that communicates the calculated route to the user via a terminal and provides visual or auditory guidance.

[0814] "Means of providing real-time directional guidance via voice" refers to a device or program that has the function of communicating directions and precautions via voice based on the user's current location.

[0815] "Means of recognizing a user's emotions using an emotion analysis engine" refers to a system that detects the user's voice and facial expressions using sensors, analyzes them with software, and determines their emotional state.

[0816] "Means of adjusting routes and suggestions based on user emotions" refers to a function that improves the travel experience by making optimal route changes or new suggestions based on information obtained through emotion analysis, tailored to the user's state.

[0817] "Means for displaying and providing facility information to users" refers to a display device or software that displays information about facilities along the travel route on the user's terminal and guides them to available services.

[0818] The travel route guidance system in this invention involves the user, terminal, and server cooperating and exchanging information with each other to provide an optimal travel experience tailored to the user's emotional state.

[0819] First, the user enters their starting point and destination into their device. This device is a smartphone or tablet and has the functionality to send the input information to a server through its user interface. The device also has a camera and microphone to sense the user's facial expressions and voice in real time. This hardware works in conjunction with an emotion analysis engine to extract the user's emotional data.

[0820] The server first receives departure and destination information sent from the terminal. Based on this information, the server uses a map API to obtain necessary geographical and accessibility information. The server then calculates the optimal travel route, taking into account obstacles and terrain features, using an algorithm (e.g., Dijkstra's algorithm or A algorithm), and formats the result as voice guidance. The voice guidance is provided to the user through the terminal, using a commonly used voice output service.

[0821] The device's emotion analysis engine analyzes the user's facial expressions and tone of voice in real time while they are on the move to determine their emotional state. The server receives this emotion data from the device, and if the user is showing positive emotions, it suggests new spots along the proposed route, such as tourist attractions or relaxation facilities. On the other hand, if the user is showing stress or discomfort, a more comfortable travel route is suggested.

[0822] As a concrete example, imagine a scenario where a server suggests a nearby park via a device that detects a user's smile while they are sightseeing in a city. This would allow the user to enjoy an unexpected sightseeing spot that wasn't originally in their plan.

[0823] An example of a prompt for the generation AI model would be: "Please generate natural language that recognizes the positive emotions the user is feeling while traveling and suggests spots that align with those emotions." This system would allow users to enjoy a flexible travel experience that responds to their emotional state, significantly improving safety and comfort during travel.

[0824] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0825] Step 1:

[0826] The user enters their starting point and destination into the terminal. The entered information is then prepared to be sent to the server via the terminal's interface. The input data is converted into the format necessary to access the map API and used to obtain accurate geographic information. The terminal verifies the user's input and formats the data.

[0827] Step 2:

[0828] The server receives departure and destination information sent from the terminal. Using this information as input, the server performs data calculations to obtain geographical and accessibility information via a map API. The output is detailed map information and user assistance information associated with that location. Here, the server performs specific actions such as managing API keys and configuring communication endpoints.

[0829] Step 3:

[0830] The server uses acquired map information to calculate the optimal travel route. The input consists of map information and accessibility information, and the server applies a route-finding algorithm based on this information. The output is the optimized route data. Algorithms such as Dijkstra's and A are used in the calculation, allowing the server to perform efficient route finding.

[0831] Step 4:

[0832] The server formats the calculated travel path into an audio guidance format and generates a script. This generated script is then prepared to match the audio output service used by the user. The output is audio guidance data that is given to the user in real time. The server performs a process to convert text information into audio data.

[0833] Step 5:

[0834] The device uses its camera and microphone to capture the user's facial expressions and voice in real time. Based on these sensor inputs, the device activates an emotion analysis engine and performs data calculations to analyze the user's emotions. The output is numerical or labeled data of the user's emotional state. The device then proceeds with processing such as facial expression detection and voice analysis.

[0835] Step 6:

[0836] The server adjusts routes and suggestions based on emotion data received from the terminal. This process uses emotion analysis data as input to evaluate routes and create suggestions. For example, it might select new stops based on positive emotions. The output is adjusted route guidance data tailored to the emotions. The server dynamically changes suggestions using conditional branching and other methods.

[0837] This process enables the system to provide flexible guidance and an optimal travel experience tailored to the user's emotional state.

[0838] (Application Example 2)

[0839] 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".

[0840] Existing barrier-free guidance systems do not provide mobility assistance that takes into account the user's emotional state, making it difficult to reduce stress and fatigue during travel. Furthermore, route suggestions are not optimized based on the individual user's emotions, resulting in insufficient support, especially for users who prioritize emotional comfort. This leads to a challenge in that the value of the user's travel experience is not sufficiently enhanced.

[0841] 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.

[0842] In this invention, the server includes means for recognizing the user's emotional state, means for acquiring map information and accessibility-related information, and means for suggesting appropriate facility information based on the emotional state. This makes it possible to provide an optimal travel experience that responds to the user's emotions.

[0843] "Means for receiving departure and destination information from the user" refers to a device or method for acquiring departure and arrival data entered by the user.

[0844] "Means for acquiring map information and barrier-free related information" refers to a device or method for acquiring geographical location data and barrier-free data such as the presence or absence of steps and ramps.

[0845] "Means for calculating the optimal travel route considering steps and steep slopes" refers to a device or method for calculating the most appropriate travel route among routes that include steps and steep slopes that may occur during travel.

[0846] "Means for providing a calculated travel route to a user" refers to a device or method for notifying or presenting a calculated travel route to a user.

[0847] "Means for providing real-time direction guidance via voice guidance" refers to a device or method that generates and transmits real-time voice information indicating direction to the user.

[0848] "Means for displaying and providing facility information to users" means a device or method for displaying information about a facility to users in a visual or other format.

[0849] "Means for recognizing a user's emotional state" refers to a device or method that analyzes data such as a user's facial expressions and tone of voice to evaluate their emotional state.

[0850] "Means for suggesting appropriate facility information based on emotional state" refers to a device or method that suggests information about relevant facilities or locations in accordance with the user's emotions.

[0851] To realize this invention, an advanced barrier-free route guidance system including an emotion recognition engine is used. This system provides mobility assistance to the user by combining multiple terminals and servers. The server receives information about the starting point and destination from the user and acquires map information and barrier-free related information. The terminal recognizes the user's emotional state in real time using sensor data such as facial expressions and voice tone.

[0852] This system uses software that provides real-time directional guidance via voice (e.g., Google Text-to-Speech API) and a map information API (e.g., Google Maps API) to obtain map information. The emotion recognition algorithm is implemented in a programming language such as Python and suggests appropriate facility information based on the user's emotions.

[0853] As a concrete example, a user accesses the system using a smartphone or tablet and enters their starting point and destination. If the device detects the user's cheerful expression during their journey, the server suggests nearby relaxation spots such as parks or cafes based on the emotional data. This allows the user to enjoy a comfortable travel experience that is tailored to their emotional state.

[0854] An example of a prompt message is, "If the user is smiling, generate a route and comments suggesting nearby tourist attractions." This allows the system to use a generative AI model to provide the user with the most relevant information.

[0855] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0856] Step 1:

[0857] The user enters the departure point and destination information into the device.

[0858] The information entered is collected as data transmitted from the terminal to the server. This data is then used as basic information for subsequent mobility assistance.

[0859] Step 2:

[0860] Based on the received departure and destination information, the server retrieves map information and accessibility-related information from an external map API.

[0861] This information is used to calculate the optimal travel route, taking into account factors such as steps and steep inclines. The calculated route becomes the output data for the terminal.

[0862] Step 3:

[0863] The device collects the user's facial expressions and voice tone as sensor data.

[0864] This data is analyzed in real time by a built-in emotion recognition algorithm and used to identify the user's emotional state (e.g., positive, negative).

[0865] Step 4:

[0866] The emotion recognition engine on the device sends emotion data to the server.

[0867] Based on this sentiment data, the server invokes a generative AI model to suggest appropriate facility information along the route (such as tourist attractions or places to relax) and generates prompt messages. The generated information is then provided to the terminal as output data.

[0868] Step 5:

[0869] The terminal provides the user with route information and schedule suggestions received from the server in both voice and display formats.

[0870] The voice guidance system utilizes a speech synthesis API and includes specific actions such as providing directions and recommendations to the user in real time.

[0871] Step 6:

[0872] Once the user's movement is complete, feedback information is sent to the server via the device.

[0873] The server collects this feedback and uses it as data to improve the accuracy of sentiment analysis and path calculation.

[0874] This series of processes makes it possible to provide an optimal travel experience that is tailored to the user's emotions.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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."

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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.

[0896] The following is further disclosed regarding the embodiments described above.

[0897] (Claim 1)

[0898] A means of receiving information about the starting point and destination from the user,

[0899] Means for obtaining map information and accessibility-related information,

[0900] A means for calculating the optimal travel route that takes into account steps and steep slopes,

[0901] Means for providing the calculated travel path to the user,

[0902] A means of providing real-time direction guidance via voice guidance,

[0903] Means for displaying and providing facility information to users,

[0904] A system that includes this.

[0905] (Claim 2)

[0906] The system according to claim 1, further comprising means for collecting user feedback and reflecting it in the calculation of the travel path.

[0907] (Claim 3)

[0908] The system according to claim 1, comprising means for prioritizing the consideration of barrier-free facility information in calculating travel routes.

[0909] "Example 1"

[0910] (Claim 1)

[0911] A device that receives information on the starting position and destination position from the user,

[0912] A device for acquiring spatial information and barrier-free related information,

[0913] A device that calculates the optimal travel route taking into account physical obstacles and steep terrain,

[0914] A device that provides the user with the calculated travel path,

[0915] A device that provides chronological directions via voice guidance,

[0916] A device that displays and provides information about the facility to the user,

[0917] A device for collecting user evaluations and reflecting them in the aforementioned travel path calculation,

[0918] A system that includes this.

[0919] (Claim 2)

[0920] The system according to claim 1, comprising a device that prioritizes the consideration of information on barrier-free facilities in the calculation of travel routes.

[0921] (Claim 3)

[0922] The system according to claim 1, comprising a generative AI model that learns user evaluations and improves the accuracy of the next route guidance.

[0923] "Application Example 1"

[0924] (Claim 1)

[0925] A means for receiving current location information and target location information,

[0926] Means for acquiring geographic data and accessibility-related data,

[0927] A means for calculating an appropriate movement path to avoid obstacles,

[0928] Means for presenting the calculated travel path to the user,

[0929] A means of performing real-time route guidance using speech synthesis,

[0930] Means of providing facility-related data to users,

[0931] A system that includes this.

[0932] (Claim 2)

[0933] The system according to claim 1, further comprising means for collecting user opinions and using them in the calculation of the travel path.

[0934] (Claim 3)

[0935] The system according to claim 1, comprising means for prioritizing the consideration of barrier-free facility-related data in calculating travel routes.

[0936] "Example 2 of combining an emotion engine"

[0937] (Claim 1)

[0938] A means of receiving information about the starting point and destination from the user,

[0939] Means for obtaining map information and user support-related information,

[0940] A means for calculating the optimal travel path considering obstacles and terrain features,

[0941] Means for providing the calculated travel path to the user,

[0942] A means of providing real-time direction guidance via voice guidance,

[0943] A means of recognizing a user's emotions using an emotion analysis engine,

[0944] A means of adjusting routes and suggestions based on user emotions,

[0945] Means for displaying and providing facility information to users,

[0946] A system that includes this.

[0947] (Claim 2)

[0948] The system according to claim 1, further comprising means for collecting user feedback and reflecting it in the calculation of the travel path.

[0949] (Claim 3)

[0950] The system according to claim 1, comprising means for prioritizing user support facility information in calculating travel routes.

[0951] "Application example 2 when combining with an emotional engine"

[0952] (Claim 1)

[0953] A means of receiving information about the starting point and destination from the user,

[0954] Means for obtaining map information and accessibility-related information,

[0955] A means for calculating the optimal travel route that takes into account steps and steep slopes,

[0956] Means for providing the calculated travel path to the user,

[0957] A means of providing real-time direction guidance via voice guidance,

[0958] Means for displaying and providing facility information to users,

[0959] A means of recognizing the user's emotional state,

[0960] A means for suggesting appropriate facility information based on the aforementioned emotional state,

[0961] A system that includes this.

[0962] (Claim 2)

[0963] The system according to claim 1, further comprising means for collecting user feedback and reflecting it in the calculation of the movement path, and means for improving the accuracy of recognizing emotional states.

[0964] (Claim 3)

[0965] The system according to claim 1, comprising means for providing an optimal route that prioritizes the consideration of barrier-free facility information and reflects the user's emotional state in calculating travel routes. [Explanation of symbols]

[0966] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving information about the starting point and destination from the user, Means for obtaining map information and accessibility-related information, A means for calculating the optimal travel route that takes into account steps and steep slopes, Means for providing the calculated travel path to the user, A means of providing real-time direction guidance via voice guidance, Means for displaying and providing facility information to users, A system that includes this.

2. The system according to claim 1, further comprising means for collecting user feedback and reflecting it in the calculation of the travel path.

3. The system according to claim 1, further comprising means for prioritizing the consideration of barrier-free facility information in calculating travel routes.

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