system

Abstract

We provide the system. [Solution] A means of receiving individual traveler information and preference information and learning using machine learning, Based on the learned information, a means of suggesting accessible accommodations, transportation, and destinations, A means of obtaining a traveler's current location during their trip and providing real-time geographic information, A means of providing travelers with audio guidance information while they are on the move and receiving audio instructions from them, A means to transmit traveler status information in emergencies and automatically contact the appropriate agency, A method for collecting traveler visit information and using machine learning to suggest future trips, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For disabled people and the elderly who have difficulty enjoying traveling, the lack of barrier - free information is a major obstacle. Also, although reducing anxiety at the travel destination and prompt response in case of emergency are required, the problem is that these information provisions and supports are not carried out in real time. As a result, there is a problem that it becomes difficult to plan a trip and it is impossible to enjoy traveling with peace of mind.

Means for Solving the Problems

[0005] This invention provides a system that learns a traveler's disability information and travel preference information, and based on that, suggests barrier-free accommodations, transportation, and tourist destinations. Furthermore, it has the function of acquiring the traveler's location information during travel and providing barrier-free information in real time. In emergencies, it can quickly transmit the traveler's location information and health information and contact support organizations to enable a rapid response. The system as a whole supports safe and comfortable travel by collecting traveler experience information and using it to suggest future trips.

[0006] "Traveler" refers to any person, including people with disabilities and the elderly, who plans and carries out a trip using the system.

[0007] "Disability information" refers to detailed information about the physical or mental limitations a traveler may have.

[0008] "Travel preference information" refers to personal preferences regarding a traveler's preferred travel style and destinations.

[0009] "Barrier-free information" refers to information about accommodations, transportation options, and tourist destinations that are easily accessible to people with disabilities and the elderly.

[0010] "Location information" refers to information about a traveler's current geographical location, obtained using technologies such as GPS.

[0011] "Real-time delivery" means providing the information immediately after it is acquired, resulting in minimal delay.

[0012] "Emergency" refers to a situation or problem that arises during a trip that requires immediate attention from the traveler.

[0013] "Health information" refers to data and status information related to a traveler's physical or health condition.

[0014] The "supporting organization" refers to a medical institution where travelers can receive support in case of emergency or an organization that provides other support services.

[0015] "Experience information" refers to information that includes the knowledge and experiences obtained by travelers during their trips.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0020] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a labeled 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a system that provides support to help travelers travel with peace of mind. The system consists of a user terminal, a central server, and an associated database.

[0038] First, the user uses a terminal to input information about their disability and travel preferences. This information includes accessibility features of accommodations, modes of transportation, and desired destinations. The terminal sends this information to a server, which stores the received information in a database and uses an AI algorithm to learn the user's needs. This initial data collection and learning prepares the system to provide travel support optimized for each individual user.

[0039] Next, the server uses the collected information to suggest barrier-free accommodations, transportation options, and tourist destinations. These suggestions are presented as an optimal travel plan based on the latest barrier-free information stored in the database. The terminal displays this travel plan to the user, who can then review and modify it.

[0040] During travel, the device uses GPS technology to determine the user's current location and communicates with a server to obtain real-time accessibility information for the surrounding area. This information is then provided to the user via a voice assistant on the device, allowing the user to obtain necessary information by voice. This ensures that the user always has the latest information at hand, allowing them to enjoy their trip with peace of mind.

[0041] Furthermore, if a user makes an emergency call from their device in an emergency, the server immediately receives the user's location and health information. Based on this information, the server coordinates with the nearest medical facilities and support staff to provide the user with a prompt response.

[0042] For example, if a traveler using a wheelchair visits a tourist destination and is looking for a route without steps, the voice assistant will suggest the optimal route based on the latest accessibility information retrieved from the server by the device. This allows travelers to enjoy sightseeing without stress.

[0043] After a trip, users can post their experiences to the community from their devices. The server collects this experience information and uses it to support future trips. This allows the entire system to continuously learn and evolve.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user uses a terminal to enter their disability information and travel preference information. Once the input is complete, the terminal sends this information to the server.

[0047] Step 2:

[0048] The server creates a user profile based on the received information and stores it in a database. It also utilizes AI algorithms to learn the user's specific needs. This learning process incorporates past travel history and data from other similar users.

[0049] Step 3:

[0050] The server searches the database for the most suitable barrier-free accommodations, transportation options, and tourist attractions for the user. This process takes into account the barrier-free accessibility status of the target area.

[0051] Step 4:

[0052] The server combines the search results to generate multiple travel plans. These plans are optimized to best meet the user's travel preferences.

[0053] Step 5:

[0054] The travel plan generated on the device is displayed to the user. The user can review it and customize the plan as needed.

[0055] Step 6:

[0056] During travel, the device periodically collects the user's location information and sends it to the server. This process is carried out with the traveler's privacy in mind and only to the extent approved by the user.

[0057] Step 7:

[0058] The server updates accessibility information based on location data in real time and sends push notifications to the device. If a voice assistant is active, it provides information instantly via voice in response to user queries.

[0059] Step 8:

[0060] In an emergency, the user activates the emergency contact function from their device. The device immediately sends their current location and health information to the server.

[0061] Step 9:

[0062] Based on the transmitted emergency information, the server automatically sends notifications to the nearest medical facilities and support teams to coordinate. It also notifies the user of necessary instructions and provides follow-up support until their safety is ensured.

[0063] Step 10:

[0064] After their trip, users share their travel experiences with the community using their devices. The server collects this information and uses it as data for planning future trips, helping to improve the system's accuracy.

[0065] (Example 1)

[0066] 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."

[0067] In modern travel, travelers with disabilities, in particular, frequently face situations that compromise their safety and convenience due to a lack of accessibility information at their destinations and inadequate emergency response. In this context, there is a need for optimal travel plans based on disability information and travel preferences, real-time support during travel, and prompt responses in emergencies.

[0068] 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.

[0069] This invention includes a server that receives information on travelers' disabilities and travel preferences and learns using a generative AI model, a server that proposes barrier-free accommodations, transportation options, and tourist destinations, and a server that acquires location information and provides guidance information in real time. This enables optimal planning for travelers with disabilities to travel with peace of mind, as well as real-time and emergency support.

[0070] "Disability information" refers to information about physical or mental limitations that travelers may have, and is a factor that needs to be taken into consideration when traveling.

[0071] "Travel preference information" refers to information that indicates the individual preferences and requirements of travelers regarding their preferred travel style and destinations.

[0072] A "generative AI model" is an algorithm that uses machine learning techniques to analyze input data and then provides personalized suggestions based on that analysis.

[0073] "Barrier-free access" refers to a state where facilities and services are available for use by people with physical limitations without any obstacles.

[0074] "Location information" refers to information indicating the current geographical location of a traveler, identified using GPS technology or similar methods.

[0075] "Guidance information" refers to detailed information about routes and surrounding facilities provided to travelers.

[0076] A "support group" is an organization or agency that coordinates the provision of medical or other assistance to travelers in times of emergency.

[0077] A "voice assistant" is a system that uses voice recognition technology to receive instructions from the user and provides information or performs actions accordingly.

[0078] "Experience information" refers to information that travelers record about the experiences and lessons they learned during their trips. By sharing this information with other travelers, it can serve as a guide for future trips.

[0079] This invention provides a system that allows travelers to obtain an optimal travel plan that takes into account information about their disabilities and travel preferences. The system consists of a user terminal, a central server, and an associated database.

[0080] First, the user uses a terminal to input information about their disability and travel preferences. The terminal sends this input to a server. The server analyzes the received information using a generative AI model to learn the user's preferences. This learning process is performed using software such as Python and Tensorflow®. Based on the information thus obtained, barrier-free accommodations, transportation options, and tourist destinations are identified.

[0081] The server processes accessibility information stored in the database in real time, providing the best possible guidance throughout the trip. The terminal uses a GPS module to determine its current location and communicates with the server. A voice assistant allows users to operate the system by voice. For example, if a user enters the prompt "Tell me some Tokyo tourist spots suitable for wheelchair users" into the terminal, the system can suggest the most suitable locations.

[0082] In an emergency, users can quickly send an SOS from their device, and the server transmits the user's current location and health status information to relevant support organizations. This enables rapid first aid.

[0083] After their trip, travelers can use their devices to post their experiences to the community. The server collects these posts and uses them to plan future trips, allowing the generative AI model to continuously learn and improve the system's accuracy. Through this continuous learning and improvement process, the service provided to travelers is enhanced.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] Users use a device to input information about their disability and travel preferences. This input data is collected through text forms. For example, if a user enters "uses a wheelchair" and "wants accommodation with an ocean view," the device formats this information and sends it to the server. The information obtained as input data is categorized as user profile data.

[0087] Step 2:

[0088] The server stores user information received from the terminal in a database. In this step, the server uses a Python script to preprocess the data and convert it into a format suitable for the generative AI model. By analyzing the received data, separating fault information and preference information, and setting attribute values ​​for each category, it prepares for the next learning phase.

[0089] Step 3:

[0090] The server uses a generative AI model to learn from input user data. Specifically, it trains the model using the TensorFlow library to enhance its ability to recognize patterns and provide optimal suggestions to the user. The model performs data calculations on user profile data as input, using the training data, and generates prediction results as output. This includes information such as the availability of barrier-free facilities and recommended tourist routes.

[0091] Step 4:

[0092] The server creates an optimal travel plan based on the learning results. It references the latest accessibility information in the database and generates a list of suggestions. For example, the list may include specific options such as "easily accessible hotels" or "tourist attractions without steps." The server sends this information to the terminal, allowing the user to view and edit the plan.

[0093] Step 5:

[0094] During travel, the device uses GPS to determine the user's current location. Based on this location information, it communicates with a server to obtain real-time accessibility information for the surrounding area. Based on the acquired data, the voice assistant provides route guidance to the user. For example, if the user prompts, "Tell me a route with few steps from my current location," the voice assistant will provide directions to the destination.

[0095] Step 6:

[0096] In an emergency, the user sends an emergency notification from their device to the server. The server quickly analyzes the location and health status and contacts the nearest support organization according to standard protocols. In this step, information is processed in real time, and the process of contacting medical facilities is automated.

[0097] Step 7:

[0098] After their trip, users post their experiences to the community via their devices. The server collects the posted data and uses it to plan future trips. This updates the community and database information, which is then used as new training data for the AI ​​model.

[0099] (Application Example 1)

[0100] 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."

[0101] For travelers, especially those with disabilities, to enjoy their trips with peace of mind, it is essential to provide travel plans tailored to their individual needs and real-time information during their travels. However, conventional systems lack this kind of individualized support, resulting in a lack of information that travelers need to take appropriate action at their destination. Furthermore, providing information to respond quickly and appropriately in emergencies is also a major challenge.

[0102] 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.

[0103] In this invention, the server includes means for receiving individual information and preference information of travelers and learning using machine learning, means for acquiring the traveler's current location during travel and providing geographic information in real time, and means for presenting guidance information to travelers via voice while they are on the move and receiving voice instructions from travelers. As a result, travelers can create optimal travel plans that suit their needs and obtain useful information in real time while traveling.

[0104] "Personalized information" refers to data such as a traveler's disability information and travel preferences, and is information tailored to individual needs.

[0105] "Machine learning" is the process by which computers learn features from data and improve their ability to make predictions and classifications.

[0106] "Accessibility-friendly accommodations" are accommodations that are designed to be easily accessible to travelers with disabilities, incorporating features such as barrier-free design.

[0107] "Providing real-time geographic information" means instantly providing travelers with the latest geographical data based on their current location.

[0108] "Providing guidance information via audio" means using audio technology to provide information and instructions to travelers.

[0109] "Accepting voice instructions" means analyzing the voice spoken by travelers and obtaining input information so that the system can respond appropriately.

[0110] An "automated communication system" is a function that, in the event of an emergency, allows a computer to automatically contact external organizations without requiring human intervention.

[0111] One embodiment of this invention is a support system that allows travelers to enjoy their trips with peace of mind. This is achieved by using a server, terminals, and associated databases.

[0112] The server receives individual traveler information and preferences, and uses machine learning algorithms to generate information optimized for each traveler. This process makes it possible to suggest accessible accommodations, transportation options, and tourist destinations to travelers.

[0113] The device uses GPS technology to obtain the traveler's current location during their trip and provides geographical information received from a server in real time. The device is equipped with a voice assistant function that can provide traveler guidance information via voice and accept voice instructions from the traveler. This voice technology is often implemented using programming languages ​​such as Java (registered trademark) or Python.

[0114] As a concrete example, a traveler using a wheelchair is given. When this traveler visits a barrier-free tourist destination, the voice assistant guides them to the most suitable route based on the latest barrier-free information retrieved from the server. In this way, the traveler can enjoy sightseeing stress-free.

[0115] An example of a prompt is, "Please suggest the best barrier-free route for a wheelchair user to enjoy sightseeing in Kyoto." By inputting such prompts into the AI ​​model, useful information can be obtained in real time.

[0116] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0117] Step 1:

[0118] The server receives individual information and travel preference information from the user. This includes data such as disability information and desired destinations entered by the user. User profile data is received as input, and registration of this data into the initial database is performed as output. Based on this registered data, the server starts a process of learning the user's needs using a machine learning model.

[0119] Step 2:

[0120] The server applies machine learning algorithms to generate lists of accommodations, transportation, and tourist destinations optimized for the user's preferences. It uses the training data obtained in Step 1 as input and generates a list of travel plans suitable for the user as output. Specifically, it utilizes data analysis and pattern recognition techniques to match user preferences with corresponding facility data and extract the best options.

[0121] Step 3:

[0122] The device uses GPS technology to determine the user's current location while traveling and transmits that location information to the server. The input is geographic location data acquired by the device. The output is the current location information sent to the server. Based on this, the server acquires geographic information in real time and prepares to provide the corresponding information to the device.

[0123] Step 4:

[0124] The server compares the acquired location information with the user's current location and provides the user with the optimal route and accessibility information in real time. The inputs are the location information obtained in step 3 and geographical information from the database. The output is guidance information provided via voice or visual means. Specifically, the server calculates an appropriate route based on the user's current location and transmits the information to the terminal through that route.

[0125] Step 5:

[0126] The device uses a voice assistant to convey guidance information from the server to the user. It can also accept voice commands from the user. Inputs include guidance information sent from the server and voice commands from the user. Outputs include voice guidance to the user and the collection of voice data as feedback. Specifically, speech synthesis technology is used to provide information in a way that is easy for the user to understand, and the device is prepared to recognize and process any further instructions.

[0127] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0128] This invention is a system designed to allow travelers to enjoy their trips with peace of mind. Its key feature is the use of an emotion engine to understand the traveler's emotional state and provide travel support accordingly. The system consists of a user terminal, a central server, an emotion engine, and a related database.

[0129] First, the user inputs information about their disability and travel preferences through their device. The device sends this information to a server, which stores it in a database and uses an AI algorithm to learn the user's needs. Here, the server understands what kind of support and environment the user desires and prepares to provide personalized travel support.

[0130] Based on the transmitted information, the server searches its database for information on barrier-free accommodations, transportation options, and tourist attractions, and generates a travel plan according to the user's learned preferences. The terminal displays this plan to the user, who can review it and customize it as needed.

[0131] During travel, the device continuously acquires the user's location information and monitors the user's emotional state through an emotion engine. Utilizing the device's sensors and microphone, it analyzes the user's emotions from facial expressions, tone of voice, and speech content, and based on this information, the server provides appropriate information. For example, if the emotion engine detects user stress, the server will guide the user to relaxation spots or places where they can rest.

[0132] Furthermore, in emergencies, the device immediately transmits the user's location and health information to the server. The server then contacts the nearest medical facility or support service, enabling a rapid response. This enhances safety and peace of mind.

[0133] The system further collects feedback from users who have completed their travel experiences within the community. The server stores data on travel experiences where users expressed particularly positive emotions and uses this data to suggest travel plans to other users with similar needs. This allows the entire system to be continuously improved by leveraging the information provided by the emotion engine, enabling the delivery of more personalized travel experiences.

[0134] As a concrete example, suppose a user visits a tourist destination and feels anxious due to changes in the weather or other factors. In this case, the emotion engine can detect that emotion, and the server can immediately provide information recommending tourist spots or evacuation locations that are appropriate for the situation, thereby supporting the user's sense of security.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] The user uses a terminal to enter information about their condition and travel preferences. The terminal then sends this information to the server.

[0138] Step 2:

[0139] The server uses an AI algorithm to analyze user needs based on the received user information and stores the results in a database.

[0140] Step 3:

[0141] The server searches the database for barrier-free accommodations, transportation options, and tourist attractions, and generates an optimal travel plan based on the user's preferences.

[0142] Step 4:

[0143] The generated travel plan is sent to the device, which then displays the plan to the user. The user reviews the plan and customizes it as needed.

[0144] Step 5:

[0145] During travel, the device acquires the user's location information in real time and sends it to the server. At the same time, the device's sensors and microphone are used by an emotion engine to analyze the user's facial expressions and tone of voice.

[0146] Step 6:

[0147] The emotion engine analyzes the user's emotional state, and if stress or anxiety is detected, the server immediately sends information about corresponding relaxation spots and safe spaces to the device.

[0148] Step 7:

[0149] The terminal receives information from the server and notifies the user, and provides guidance using a voice assistant, thereby quickly responding to the user's needs.

[0150] Step 8:

[0151] In an emergency, if a user uses the emergency contact function on their device, their location and health information will be sent to the server.

[0152] Step 9:

[0153] The server coordinates with the nearest medical facilities and support teams to provide a rapid response to users. The terminal provides users with appropriate measures and evacuation instructions based on the current situation.

[0154] Step 10:

[0155] After a trip, users share their experiences with the community via their devices. The server learns from this information and incorporates it into future travel suggestions. This improves the system's accuracy and personalization.

[0156] (Example 2)

[0157] 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 will be referred to as the "terminal."

[0158] To ensure travelers can enjoy their trips with peace of mind, it is necessary to provide information tailored to each traveler's individual circumstances and preferences. However, conventional systems have difficulty integrating traveler information such as disability information, preferences, emotional state, and emergency health status, making it challenging to provide optimal information in real time during a trip. This results in travelers being unable to receive the necessary support when they need it.

[0159] 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.

[0160] In this invention, the server includes means for receiving traveler disability information and travel preference information and learning the information using machine learning technology; means for acquiring traveler location information and providing customized support information in real time; and means for monitoring the traveler's emotional state and providing information corresponding to that emotional state. This makes it possible to provide personalized information that meets the traveler's needs.

[0161] A "traveler" refers to an individual who uses the system while traveling, and is the target of support provided based on their disability information and preferences.

[0162] "Disability information" refers to information about a traveler's physical or mental limitations, and is used to optimize support during their trip.

[0163] "Travel preference information" refers to information about travelers' preferred activities, places they want to visit, budgets, etc., and is used to provide personalized travel experiences.

[0164] "Machine learning technology" refers to techniques that enable computers to learn from data and improve their performance in performing specific tasks.

[0165] "Location information" refers to data that indicates a traveler's current geographical location and is used for providing real-time information and responding to emergencies.

[0166] "Emotional state" refers to information that indicates the traveler's psychological or emotional condition, including stress and anxiety.

[0167] "Support information" refers to information about accommodations, tourist attractions, relaxation spots, etc., provided to travelers so that they can enjoy their trip with peace of mind.

[0168] An "emergency" refers to a situation in which a traveler faces a serious health or safety issue during their trip, requiring a swift response.

[0169] "Health information" refers to data about a traveler's physical health status and is used to share information with medical institutions as needed.

[0170] To implement this invention, it is necessary to organically link multiple components. Specifically, a user's terminal, a central server, an emotion engine for sentiment analysis, and an associated database system are required.

[0171] First, users input their travel preferences and disability information using their own devices (such as smartphones or tablets). These devices are equipped with sensor technology and voice assistant functions, allowing for easy input of this information via voice or touch.

[0172] Next, the terminal transmits the collected information to the server via a secure communication method. The server uses high-performance computing equipment and a database system, enabling it to quickly and securely store and manage user information. The database already contains pre-collected information on barrier-free facilities, services, and tourist destinations.

[0173] Based on this information, the server uses a generative AI model to learn the user's preferences and needs. The AI ​​model identifies patterns from a vast amount of data, including the user's past information and the preferences of similar users, and automatically generates the optimal travel plan. The following is an example of a prompt given to the AI ​​model:

[0174] "Please create a list of tourist spots that users would like to see."

[0175] "Please list the data items needed to generate personalized travel plans."

[0176] During travel, the device uses GPS and built-in sensors to acquire the user's location and emotional state in real time. When the emotion engine detects the user's stress or anxiety, it sends this information to a server, which then provides pre-prepared relaxation spots and sightseeing information. This process allows the user to feel more at ease while traveling.

[0177] Furthermore, in the event of an emergency, the device immediately sends data, including the user's health information, to a server, which automatically contacts the nearest medical facility or support service. This ensures a swift and appropriate emergency response.

[0178] This system utilizes advanced, data-driven technology to provide travelers with peace of mind and a fulfilling travel experience.

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] Users input travel preferences and disability information using their own devices. Specific input includes desired destinations, budgets, tourist attractions, and necessary support. The device collects this information, converts it into a digital format, and generates data packets to send to the server. The output data consists of the user's preferences and disability information, ready for transmission to the server.

[0182] Step 2:

[0183] The terminal transmits user preference and fault information to a central server using a secure protocol (e.g., HTTPS). This information is received by the server and stored in a database. The input is encoded user information data, and the output is data storage on the server side.

[0184] Step 3:

[0185] The server uses a generated AI model based on user information retrieved from the database to learn the user's individual needs. The AI ​​model analyzes relevant information and performs data calculations to extract preference patterns. The input consists of existing information from the database and newly received user information, and the output is a travel plan optimized for the user.

[0186] Step 4:

[0187] The server uses the data obtained as a result of training to select barrier-free facilities, transportation options, and recommended tourist destinations, and generates a detailed travel plan. This process employs data filtering and plan generation algorithms. The input is the learned preference patterns, and the output is specific travel plan information.

[0188] Step 5:

[0189] The terminal presents the generated travel plan to the user and provides an interface that allows the user to customize it. The user can review the travel plan here and make changes as needed. The input is travel plan data from the server, and the output is a customizable plan display for the user.

[0190] Step 6:

[0191] During travel, the device continuously monitors the user's location and emotional state in real time using its built-in GPS and sensors. The data collected by the sensors includes geographical location, voice tone, and facial expressions. This monitoring data is fed into an emotion engine, which analyzes it to detect the user's stress and anxiety. The output is an informational notification sent to the server based on the emotional state.

[0192] Step 7:

[0193] The server provides the user with appropriate actions based on information provided by the emotion engine. Here, it presents information on relaxation spots and new tourist destinations tailored to the user's current emotional state. The input is the emotion analysis result, and the output is the information displayed on the terminal.

[0194] Step 8:

[0195] In an emergency, the device will promptly transmit the user's health status data and location information to the server. The server will then receive this information and immediately begin the process of contacting support services. The input is user information in an emergency, and the output is the notification to support services.

[0196] Step 9:

[0197] After the trip ends, the device provides an interface for collecting user feedback on their travel experience. The server analyzes the collected feedback and improves the generated AI model to use in future travel planning. The input is user feedback information, and the output is the improved AI model.

[0198] (Application Example 2)

[0199] 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".

[0200] When travelers navigate different environments, their experience can be diminished if they are unable to cope with potential stressors or emergencies. Furthermore, there is a lack of resources to provide optimal travel experiences tailored to each traveler's emotional state. These challenges need to be addressed to enhance travel safety and satisfaction.

[0201] 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.

[0202] This invention includes a server that receives and learns information on a traveler's disability, travel preferences, and emotional state; a server that, based on the learned information, suggests barrier-free accommodations, transportation options, and tourist destinations, and guides the traveler to relaxation spots and resting places according to their emotional state; and a server that acquires the traveler's location information and emotional state during the trip and provides barrier-free information and emotionally appropriate information in real time. This makes it possible to provide travelers with an individualized and emotionally appropriate travel experience.

[0203] A "traveler" is someone who goes on a trip and needs support tailored to their experiences and emotional state during that trip.

[0204] "Disability information" refers to information about the physical or mental limitations that travelers have, and serves as the basis for providing accessibility considerations.

[0205] "Travel preference information" refers to information about travelers' preferences and tastes, and serves as a reference when creating personalized travel plans.

[0206] "Emotional state information" refers to information that indicates the psychological state of a traveler, and is used to provide emotionally tailored services in order to improve the quality of their travel experience.

[0207] "Means" refer to methods and devices that perform information processing or provide support to achieve an objective, and are elements that constitute a system.

[0208] "Barrier-free accommodations" are accommodations that are designed to be safe and accessible for travelers with disabilities.

[0209] "Transportation" refers to the vehicles and routes that travelers use to get around, and is a factor that directly impacts the comfort of the trip.

[0210] A "tourist destination" is a place that travelers visit and enjoy, and is part of a travel destination.

[0211] A "relaxation spot" is a place where travelers can relax and soothe their mind and body, and is suggested as a way to alleviate stress.

[0212] A "place where you can rest" is a place where travelers can take a temporary rest during their trip.

[0213] "Location information" refers to data that indicates a traveler's current location and is used for real-time guidance and support.

[0214] "Emotional monitoring" is a technology that observes and analyzes the emotional state of travelers in order to optimize their experience.

[0215] This invention provides a system to assist travelers. The system consists of a user terminal, a central server, an emotion engine, and a database associated with them. First, the traveler inputs disability information, travel preference information, and emotional state information through the terminal. The terminal sends this information to the server, which stores the information in a database and learns the traveler's needs using machine learning algorithms. In this process, the system understands what kind of support and environment the user needs and prepares to provide personalized travel support.

[0216] Based on the information it has learned, the server searches its database for information on barrier-free accommodations, transportation, and tourist attractions, and generates a travel plan that suggests relaxation spots and places to rest according to the user's emotional state. The terminal presents this plan to the user, who can then customize it to suit their needs.

[0217] During travel, the device continuously acquires the traveler's location information and monitors the traveler's emotional state through an emotion engine. The device's sensors and microphone analyze emotions based on facial expressions, tone of voice, and speech content, and transmit the results to a server. The server then guides the traveler with appropriate information and relaxation spots based on their emotional state. For example, if the traveler is feeling stressed, the server will immediately suggest a place to relax.

[0218] For example, if a traveler is distressed by rain while sightseeing, the device takes the rain situation into account and sends emotional data to the server. The server immediately provides information recommending nearby shelters or cafes. In this case, a prompt message to the generative AI model such as "Please list tourist spots where the user can relax. The user is currently feeling stressed because of the rain" can be used.

[0219] The hardware used will include mobile devices and personal assistant robots (e.g., Pepper, Nao) carried by travelers, while the software will utilize sentiment analysis libraries (OpenCV, DLib, etc.) and AI platforms (Google Cloud AI, etc.). This will enable the creation of services that meet the personalized needs of travelers and enhance their travel experience.

[0220] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0221] Step 1:

[0222] Users input information about their condition, travel preferences, and emotional state through their terminal. The input data is temporarily stored on the terminal and prepared for transmission to the server. The system is managed to ensure that user input is accurately collected and that necessary information is reliably transmitted to the server.

[0223] Step 2:

[0224] The terminal sends all collected user information to the server. The server analyzes the received data and stores it in the appropriate database. At this point, it builds foundational data for learning user needs and preferences using machine learning algorithms. The server verifies the reliability of the data and prepares it for analysis.

[0225] Step 3:

[0226] The server searches for barrier-free facilities, transportation options, and tourist attractions based on traveler information stored in the database. It also processes data to suggest relaxation spots and places to rest based on the traveler's emotional state. In this step, an AI algorithm is used to filter the information and generate a travel plan.

[0227] Step 4:

[0228] The generated travel plan is sent to the device and presented to the user. The user can review the plan and customize it as needed. At this stage, the user's feelings are reflected in the plan, allowing for personalized choices.

[0229] Step 5:

[0230] During travel, the device continuously acquires the user's location and emotional state. This is done using a GPS module and emotion analysis libraries (e.g., OpenCV, DLib). The acquired information is temporarily processed within the device before being sent to the server. Real-time information updates are performed based on the user's location and emotions.

[0231] Step 6:

[0232] The server analyzes the transmitted location information and emotional state, and generates appropriate suggestions based on the results. For example, if the user is feeling stressed, the server will recommend relaxation spots. In this process, it optimizes the information by utilizing prompts to the generative AI model, such as, "Please list places where the user can calm down. The user is currently feeling stressed because of the rain."

[0233] Step 7:

[0234] In emergencies, the device automatically transmits the user's location, health information, and emotional state to a server. Based on the received data, the server immediately contacts the necessary support organizations. This process ensures the user's safety and security.

[0235] Step 8:

[0236] After the trip ends, the server stores the traveler's feedback in a database, which is used to improve future travel suggestions. This information is used to further enhance and develop suggestions for other users.

[0237] 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.

[0238] 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.

[0239] 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.

[0240] [Second Embodiment]

[0241] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0242] 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.

[0243] 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).

[0244] 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.

[0245] 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.

[0246] 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).

[0247] 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.

[0248] 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.

[0249] 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.

[0250] 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.

[0251] 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.

[0252] 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".

[0253] This invention is a system that provides support to help travelers travel with peace of mind. The system consists of a user terminal, a central server, and an associated database.

[0254] First, the user uses a terminal to input information about their disability and travel preferences. This information includes accessibility features of accommodations, modes of transportation, and desired destinations. The terminal sends this information to a server, which stores the received information in a database and uses an AI algorithm to learn the user's needs. This initial data collection and learning prepares the system to provide travel support optimized for each individual user.

[0255] Next, the server uses the collected information to suggest barrier-free accommodations, transportation options, and tourist destinations. These suggestions are presented as an optimal travel plan based on the latest barrier-free information stored in the database. The terminal displays this travel plan to the user, who can then review and modify it.

[0256] During travel, the device uses GPS technology to determine the user's current location and communicates with a server to obtain real-time accessibility information for the surrounding area. This information is then provided to the user via a voice assistant on the device, allowing the user to obtain necessary information by voice. This ensures that the user always has the latest information at hand, allowing them to enjoy their trip with peace of mind.

[0257] Furthermore, if a user makes an emergency call from their device in an emergency, the server immediately receives the user's location and health information. Based on this information, the server coordinates with the nearest medical facilities and support staff to provide the user with a prompt response.

[0258] For example, if a traveler using a wheelchair visits a tourist destination and is looking for a route without steps, the voice assistant will suggest the optimal route based on the latest accessibility information retrieved from the server by the device. This allows travelers to enjoy sightseeing without stress.

[0259] After a trip, users can post their experiences to the community from their devices. The server collects this experience information and uses it to support future trips. This allows the entire system to continuously learn and evolve.

[0260] The following describes the processing flow.

[0261] Step 1:

[0262] The user uses a terminal to enter their disability information and travel preference information. Once the input is complete, the terminal sends this information to the server.

[0263] Step 2:

[0264] The server creates a user profile based on the received information and stores it in a database. It also utilizes AI algorithms to learn the user's specific needs. This learning process incorporates past travel history and data from other similar users.

[0265] Step 3:

[0266] The server searches the database for the most suitable barrier-free accommodations, transportation options, and tourist attractions for the user. This process takes into account the barrier-free accessibility status of the target area.

[0267] Step 4:

[0268] The server combines the search results to generate multiple travel plans. These plans are optimized to best meet the user's travel preferences.

[0269] Step 5:

[0270] The travel plan generated on the device is displayed to the user. The user can review it and customize the plan as needed.

[0271] Step 6:

[0272] During travel, the device periodically collects the user's location information and sends it to the server. This process is carried out with the traveler's privacy in mind and only to the extent approved by the user.

[0273] Step 7:

[0274] The server updates accessibility information based on location data in real time and sends push notifications to the device. If a voice assistant is active, it provides information instantly via voice in response to user queries.

[0275] Step 8:

[0276] In an emergency, the user activates the emergency contact function from their device. The device immediately sends their current location and health information to the server.

[0277] Step 9:

[0278] Based on the transmitted emergency information, the server automatically sends notifications to the nearest medical facilities and support teams to coordinate. It also notifies the user of necessary instructions and provides follow-up support until their safety is ensured.

[0279] Step 10:

[0280] After their trip, users share their travel experiences with the community using their devices. The server collects this information and uses it as data for planning future trips, helping to improve the system's accuracy.

[0281] (Example 1)

[0282] 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."

[0283] In modern travel, especially for travelers with disabilities, due to the lack of barrier-free information at the destination and insufficient emergency response, situations that undermine the peace of mind and convenience during travel frequently occur. In such circumstances, there is a need for the provision of an optimal travel plan based on disability information and travel preferences, real-time support during travel, and prompt response in case of emergencies.

[0284] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following respective means.

[0285] In this invention, the server includes means for receiving a traveler's disability information and travel preference information, learning using a generative AI model, means for proposing barrier-free accommodation facilities, transportation means, and tourist attractions, and means for acquiring location information and providing guidance information in real time. This enables optimal planning for travelers with disabilities to travel with peace of mind and real-time and emergency support.

[0286] "Disability information" refers to information regarding a traveler's physical or mental limitations, which are elements that need to be considered during travel.

[0287] "Travel preference information" refers to information indicating an individual's wishes and requirements regarding the travel style and destinations preferred by the traveler.

[0288] "Generative AI model" is an algorithm that uses machine learning technology to analyze the input data and make individualized proposals based on it.

[0289] "Barrier-free response" refers to a state where there are facilities and services that people with physical limitations can use without hindrance.

[0290] "Location information" refers to information indicating the current geographical position of the traveler, which is identified using technologies such as GPS technology.

[0291] "Guidance information" refers to detailed information about routes and surrounding facilities provided to travelers.

[0292] A "support group" is an organization or agency that coordinates the provision of medical or other assistance to travelers in times of emergency.

[0293] A "voice assistant" is a system that uses voice recognition technology to receive instructions from the user and provides information or performs actions accordingly.

[0294] "Experience information" refers to information that travelers record about the experiences and lessons they learned during their trips. By sharing this information with other travelers, it can serve as a guide for future trips.

[0295] This invention provides a system that allows travelers to obtain an optimal travel plan that takes into account information about their disabilities and travel preferences. The system consists of a user terminal, a central server, and an associated database.

[0296] First, the user uses a device to input information about their disability and travel preferences. The device sends this input to a server. The server analyzes the received information using a generative AI model to learn the user's preferences. This learning process is performed using software such as Python or TensorFlow. Based on the information obtained in this way, barrier-free accommodations, transportation options, and tourist destinations are identified.

[0297] The server processes accessibility information stored in the database in real time, providing the best possible guidance throughout the trip. The terminal uses a GPS module to determine its current location and communicates with the server. A voice assistant allows users to operate the system by voice. For example, if a user enters the prompt "Tell me some Tokyo tourist spots suitable for wheelchair users" into the terminal, the system can suggest the most suitable locations.

[0298] In an emergency, users can quickly send an SOS from their device, and the server transmits the user's current location and health status information to relevant support organizations. This enables rapid first aid.

[0299] After their trip, travelers can use their devices to post their experiences to the community. The server collects these posts and uses them to plan future trips, allowing the generative AI model to continuously learn and improve the system's accuracy. Through this continuous learning and improvement process, the service provided to travelers is enhanced.

[0300] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0301] Step 1:

[0302] Users use a device to input information about their disability and travel preferences. This input data is collected through text forms. For example, if a user enters "uses a wheelchair" and "wants accommodation with an ocean view," the device formats this information and sends it to the server. The information obtained as input data is categorized as user profile data.

[0303] Step 2:

[0304] The server stores user information received from the terminal in a database. In this step, the server uses a Python script to preprocess the data and convert it into a format suitable for the generative AI model. By analyzing the received data, separating fault information and preference information, and setting attribute values ​​for each category, it prepares for the next learning phase.

[0305] Step 3:

[0306] The server uses a generative AI model to learn the input user data. Specifically, it uses the TensorFlow library to train the model and enhance its ability to recognize patterns and make optimal suggestions to the user. For the user profile data as input, the model performs data operations using the training data and generates prediction results as output. This includes the availability of barrier-free facilities and recommended tourist routes.

[0307] Step 4:

[0308] Based on the learning results, the server creates an optimal travel plan. It refers to the latest barrier-free information in the database and generates a list of suggestions. For example, specific options such as "hotels with good access" and "tourist spots without steps" are included in the list. The server sends this information to the terminal so that the user can view and edit the plan.

[0309] Step 5:

[0310] During the trip, the terminal uses GPS to identify the user's current location. Based on the location information, it communicates with the server to obtain real-time barrier-free information around. Based on the acquired data, the voice assistant provides route guidance to the user. For example, if the user gives a prompt like "Tell me a route with fewer steps from my current location", it provides voice guidance to the destination.

[0311] Step 6:

[0312] In case of an emergency, the user sends an emergency notification from the terminal to the server. The server quickly analyzes the location information and health status and contacts the nearest support organization according to the standard protocol. In this step, information is processed in real-time and the contact procedure to medical facilities is automatically carried out.

[0313] Step 7:

[0314] After their trip, users post their experiences to the community via their devices. The server collects the posted data and uses it to plan future trips. This updates the community and database information, which is then used as new training data for the AI ​​model.

[0315] (Application Example 1)

[0316] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0317] For travelers, especially those with disabilities, to enjoy their trips with peace of mind, it is essential to provide travel plans tailored to their individual needs and real-time information during their travels. However, conventional systems lack this kind of individualized support, resulting in a lack of information that travelers need to take appropriate action at their destination. Furthermore, providing information to respond quickly and appropriately in emergencies is also a major challenge.

[0318] 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.

[0319] In this invention, the server includes means for receiving individual information and preference information of travelers and learning using machine learning, means for acquiring the traveler's current location during travel and providing geographic information in real time, and means for presenting guidance information to travelers via voice while they are on the move and receiving voice instructions from travelers. As a result, travelers can create optimal travel plans that suit their needs and obtain useful information in real time while traveling.

[0320] "Personalized information" refers to data such as a traveler's disability information and travel preferences, and is information tailored to individual needs.

[0321] "Machine learning" is the process by which computers learn features from data and improve their ability to make predictions and classifications.

[0322] "Accessibility-friendly accommodations" are accommodations that are designed to be easily accessible to travelers with disabilities, incorporating features such as barrier-free design.

[0323] "Providing real-time geographic information" means instantly providing travelers with the latest geographical data based on their current location.

[0324] "Providing guidance information via audio" means using audio technology to provide information and instructions to travelers.

[0325] "Accepting voice instructions" means analyzing the voice spoken by travelers and obtaining input information so that the system can respond appropriately.

[0326] An "automated communication system" is a function that, in the event of an emergency, allows a computer to automatically contact external organizations without requiring human intervention.

[0327] One embodiment of this invention is a support system that allows travelers to enjoy their trips with peace of mind. This is achieved by using a server, terminals, and associated databases.

[0328] The server receives individual traveler information and preferences, and uses machine learning algorithms to generate information optimized for each traveler. This process makes it possible to suggest accessible accommodations, transportation options, and tourist destinations to travelers.

[0329] The device uses GPS technology to obtain the traveler's current location during their trip and provides geographical information received from a server in real time. The device is equipped with a voice assistant function that can provide traveler guidance information via voice and accept voice instructions from the traveler. This voice technology is often implemented using programming languages ​​such as Java or Python.

[0330] As a concrete example, a traveler using a wheelchair is given. When this traveler visits a barrier-free tourist destination, the voice assistant guides them to the most suitable route based on the latest barrier-free information retrieved from the server. In this way, the traveler can enjoy sightseeing stress-free.

[0331] An example of a prompt is, "Please suggest the best barrier-free route for a wheelchair user to enjoy sightseeing in Kyoto." By inputting such prompts into the AI ​​model, useful information can be obtained in real time.

[0332] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0333] Step 1:

[0334] The server receives individual information and travel preference information from the user. This includes data such as disability information and desired destinations entered by the user. User profile data is received as input, and registration of this data into the initial database is performed as output. Based on this registered data, the server starts a process of learning the user's needs using a machine learning model.

[0335] Step 2:

[0336] The server applies machine learning algorithms to generate lists of accommodations, transportation, and tourist destinations optimized for the user's preferences. It uses the training data obtained in Step 1 as input and generates a list of travel plans suitable for the user as output. Specifically, it utilizes data analysis and pattern recognition techniques to match user preferences with corresponding facility data and extract the best options.

[0337] Step 3:

[0338] The device uses GPS technology to determine the user's current location while traveling and transmits that location information to the server. The input is geographic location data acquired by the device. The output is the current location information sent to the server. Based on this, the server acquires geographic information in real time and prepares to provide the corresponding information to the device.

[0339] Step 4:

[0340] The server compares the acquired location information with the user's current location and provides the user with the optimal route and accessibility information in real time. The inputs are the location information obtained in step 3 and geographical information from the database. The output is guidance information provided via voice or visual means. Specifically, the server calculates an appropriate route based on the user's current location and transmits the information to the terminal through that route.

[0341] Step 5:

[0342] The device uses a voice assistant to convey guidance information from the server to the user. It can also accept voice commands from the user. Inputs include guidance information sent from the server and voice commands from the user. Outputs include voice guidance to the user and the collection of voice data as feedback. Specifically, speech synthesis technology is used to provide information in a way that is easy for the user to understand, and the device is prepared to recognize and process any further instructions.

[0343] 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.

[0344] This invention is a system designed to allow travelers to enjoy their trips with peace of mind. Its key feature is the use of an emotion engine to understand the traveler's emotional state and provide travel support accordingly. The system consists of a user terminal, a central server, an emotion engine, and a related database.

[0345] First, the user inputs information about their disability and travel preferences through their device. The device sends this information to a server, which stores it in a database and uses an AI algorithm to learn the user's needs. Here, the server understands what kind of support and environment the user desires and prepares to provide personalized travel support.

[0346] Based on the transmitted information, the server searches its database for information on barrier-free accommodations, transportation options, and tourist attractions, and generates a travel plan according to the user's learned preferences. The terminal displays this plan to the user, who can review it and customize it as needed.

[0347] During travel, the device continuously acquires the user's location information and monitors the user's emotional state through an emotion engine. Utilizing the device's sensors and microphone, it analyzes the user's emotions from facial expressions, tone of voice, and speech content, and based on this information, the server provides appropriate information. For example, if the emotion engine detects user stress, the server will guide the user to relaxation spots or places where they can rest.

[0348] Furthermore, in emergencies, the device immediately transmits the user's location and health information to the server. The server then contacts the nearest medical facility or support service, enabling a rapid response. This enhances safety and peace of mind.

[0349] The system further collects feedback from users who have completed their travel experiences within the community. The server stores data on travel experiences where users expressed particularly positive emotions and uses this data to suggest travel plans to other users with similar needs. This allows the entire system to be continuously improved by leveraging the information provided by the emotion engine, enabling the delivery of more personalized travel experiences.

[0350] As a concrete example, suppose a user visits a tourist destination and feels anxious due to changes in the weather or other factors. In this case, the emotion engine can detect that emotion, and the server can immediately provide information recommending tourist spots or evacuation locations that are appropriate for the situation, thereby supporting the user's sense of security.

[0351] The following describes the processing flow.

[0352] Step 1:

[0353] The user uses a terminal to enter information about their condition and travel preferences. The terminal then sends this information to the server.

[0354] Step 2:

[0355] The server uses an AI algorithm to analyze user needs based on the received user information and stores the results in a database.

[0356] Step 3:

[0357] The server searches the database for barrier-free accommodations, transportation options, and tourist attractions, and generates an optimal travel plan based on the user's preferences.

[0358] Step 4:

[0359] The generated travel plan is sent to the device, which then displays the plan to the user. The user reviews the plan and customizes it as needed.

[0360] Step 5:

[0361] During travel, the device acquires the user's location information in real time and sends it to the server. At the same time, the device's sensors and microphone are used by an emotion engine to analyze the user's facial expressions and tone of voice.

[0362] Step 6:

[0363] The emotion engine analyzes the user's emotional state, and if stress or anxiety is detected, the server immediately sends information about corresponding relaxation spots and safe spaces to the device.

[0364] Step 7:

[0365] The terminal receives information from the server and notifies the user, and provides guidance using a voice assistant, thereby quickly responding to the user's needs.

[0366] Step 8:

[0367] In an emergency, if a user uses the emergency contact function on their device, their location and health information will be sent to the server.

[0368] Step 9:

[0369] The server coordinates with the nearest medical facilities and support teams to provide a rapid response to users. The terminal provides users with appropriate measures and evacuation instructions based on the current situation.

[0370] Step 10:

[0371] After a trip, users share their experiences with the community via their devices. The server learns from this information and incorporates it into future travel suggestions. This improves the system's accuracy and personalization.

[0372] (Example 2)

[0373] 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".

[0374] To ensure travelers can enjoy their trips with peace of mind, it is necessary to provide information tailored to each traveler's individual circumstances and preferences. However, conventional systems have difficulty integrating traveler information such as disability information, preferences, emotional state, and emergency health status, making it challenging to provide optimal information in real time during a trip. This results in travelers being unable to receive the necessary support when they need it.

[0375] 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.

[0376] In this invention, the server includes means for receiving traveler disability information and travel preference information and learning the information using machine learning technology; means for acquiring traveler location information and providing customized support information in real time; and means for monitoring the traveler's emotional state and providing information corresponding to that emotional state. This makes it possible to provide personalized information that meets the traveler's needs.

[0377] A "traveler" refers to an individual who uses the system while traveling, and is the target of support provided based on their disability information and preferences.

[0378] "Disability information" refers to information about a traveler's physical or mental limitations, and is used to optimize support during their trip.

[0379] "Travel preference information" refers to information about travelers' preferred activities, places they want to visit, budgets, etc., and is used to provide personalized travel experiences.

[0380] "Machine learning technology" refers to techniques that enable computers to learn from data and improve their performance in performing specific tasks.

[0381] "Location information" refers to data that indicates a traveler's current geographical location and is used for providing real-time information and responding to emergencies.

[0382] "Emotional state" refers to information that indicates the traveler's psychological or emotional condition, including stress and anxiety.

[0383] "Support information" refers to information about accommodations, tourist attractions, relaxation spots, etc., provided to travelers so that they can enjoy their trip with peace of mind.

[0384] An "emergency" refers to a situation in which a traveler faces a serious health or safety issue during their trip, requiring a swift response.

[0385] "Health information" refers to data about a traveler's physical health status and is used to share information with medical institutions as needed.

[0386] To implement this invention, it is necessary to organically link multiple components. Specifically, a user's terminal, a central server, an emotion engine for sentiment analysis, and an associated database system are required.

[0387] First, users input their travel preferences and disability information using their own devices (such as smartphones or tablets). These devices are equipped with sensor technology and voice assistant functions, allowing for easy input of this information via voice or touch.

[0388] Next, the terminal transmits the collected information to the server via a secure communication method. The server uses high-performance computing equipment and a database system, enabling it to quickly and securely store and manage user information. The database already contains pre-collected information on barrier-free facilities, services, and tourist destinations.

[0389] Based on this information, the server uses a generative AI model to learn the user's preferences and needs. The AI ​​model identifies patterns from a vast amount of data, including the user's past information and the preferences of similar users, and automatically generates the optimal travel plan. The following is an example of a prompt given to the AI ​​model:

[0390] "Please create a list of tourist spots that users would like to see."

[0391] "Please list the data items needed to generate personalized travel plans."

[0392] During travel, the device uses GPS and built-in sensors to acquire the user's location and emotional state in real time. When the emotion engine detects the user's stress or anxiety, it sends this information to a server, which then provides pre-prepared relaxation spots and sightseeing information. This process allows the user to feel more at ease while traveling.

[0393] Furthermore, in the event of an emergency, the device immediately sends data, including the user's health information, to a server, which automatically contacts the nearest medical facility or support service. This ensures a swift and appropriate emergency response.

[0394] This system utilizes advanced, data-driven technology to provide travelers with peace of mind and a fulfilling travel experience.

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

[0396] Step 1:

[0397] Users input travel preferences and disability information using their own devices. Specific input includes desired destinations, budgets, tourist attractions, and necessary support. The device collects this information, converts it into a digital format, and generates data packets to send to the server. The output data consists of the user's preferences and disability information, ready for transmission to the server.

[0398] Step 2:

[0399] The terminal transmits user preference and fault information to a central server using a secure protocol (e.g., HTTPS). This information is received by the server and stored in a database. The input is encoded user information data, and the output is data storage on the server side.

[0400] Step 3:

[0401] The server uses a generated AI model based on user information retrieved from the database to learn the user's individual needs. The AI ​​model analyzes relevant information and performs data calculations to extract preference patterns. The input consists of existing information from the database and newly received user information, and the output is a travel plan optimized for the user.

[0402] Step 4:

[0403] The server uses the data obtained as a result of training to select barrier-free facilities, transportation options, and recommended tourist destinations, and generates a detailed travel plan. This process employs data filtering and plan generation algorithms. The input is the learned preference patterns, and the output is specific travel plan information.

[0404] Step 5:

[0405] The terminal presents the generated travel plan to the user and provides an interface that allows the user to customize it. The user can review the travel plan here and make changes as needed. The input is travel plan data from the server, and the output is a customizable plan display for the user.

[0406] Step 6:

[0407] During travel, the device continuously monitors the user's location and emotional state in real time using its built-in GPS and sensors. The data collected by the sensors includes geographical location, voice tone, and facial expressions. This monitoring data is fed into an emotion engine, which analyzes it to detect the user's stress and anxiety. The output is an informational notification sent to the server based on the emotional state.

[0408] Step 7:

[0409] The server provides the user with appropriate actions based on information provided by the emotion engine. Here, it presents information on relaxation spots and new tourist destinations tailored to the user's current emotional state. The input is the emotion analysis result, and the output is the information displayed on the terminal.

[0410] Step 8:

[0411] In an emergency, the device will promptly transmit the user's health status data and location information to the server. The server will then receive this information and immediately begin the process of contacting support services. The input is user information in an emergency, and the output is the notification to support services.

[0412] Step 9:

[0413] After the trip ends, the device provides an interface for collecting user feedback on their travel experience. The server analyzes the collected feedback and improves the generated AI model to use in future travel planning. The input is user feedback information, and the output is the improved AI model.

[0414] (Application Example 2)

[0415] 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."

[0416] When travelers navigate different environments, their experience can be diminished if they are unable to cope with potential stressors or emergencies. Furthermore, there is a lack of resources to provide optimal travel experiences tailored to each traveler's emotional state. These challenges need to be addressed to enhance travel safety and satisfaction.

[0417] 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.

[0418] This invention includes a server that receives and learns information on a traveler's disability, travel preferences, and emotional state; a server that, based on the learned information, suggests barrier-free accommodations, transportation options, and tourist destinations, and guides the traveler to relaxation spots and resting places according to their emotional state; and a server that acquires the traveler's location information and emotional state during the trip and provides barrier-free information and emotionally appropriate information in real time. This makes it possible to provide travelers with an individualized and emotionally appropriate travel experience.

[0419] A "traveler" is someone who goes on a trip and needs support tailored to their experiences and emotional state during that trip.

[0420] "Disability information" refers to information about the physical or mental limitations that travelers have, and serves as the basis for providing accessibility considerations.

[0421] "Travel preference information" refers to information about travelers' preferences and tastes, and serves as a reference when creating personalized travel plans.

[0422] "Emotional state information" refers to information that indicates the psychological state of a traveler, and is used to provide emotionally tailored services in order to improve the quality of their travel experience.

[0423] "Means" refer to methods and devices that perform information processing or provide support to achieve an objective, and are elements that constitute a system.

[0424] "Barrier-free accommodations" are accommodations that are designed to be safe and accessible for travelers with disabilities.

[0425] "Transportation" refers to the vehicles and routes that travelers use to get around, and is a factor that directly impacts the comfort of the trip.

[0426] A "tourist destination" is a place that travelers visit and enjoy, and is part of a travel destination.

[0427] A "relaxation spot" is a place where travelers can relax and soothe their mind and body, and is suggested as a way to alleviate stress.

[0428] A "place where you can rest" is a place where travelers can take a temporary rest during their trip.

[0429] "Location information" refers to data that indicates a traveler's current location and is used for real-time guidance and support.

[0430] "Emotional monitoring" is a technology that observes and analyzes the emotional state of travelers in order to optimize their experience.

[0431] This invention provides a system to assist travelers. The system consists of a user terminal, a central server, an emotion engine, and a database associated with them. First, the traveler inputs disability information, travel preference information, and emotional state information through the terminal. The terminal sends this information to the server, which stores the information in a database and learns the traveler's needs using machine learning algorithms. In this process, the system understands what kind of support and environment the user needs and prepares to provide personalized travel support.

[0432] Based on the information it has learned, the server searches its database for information on barrier-free accommodations, transportation, and tourist attractions, and generates a travel plan that suggests relaxation spots and places to rest according to the user's emotional state. The terminal presents this plan to the user, who can then customize it to suit their needs.

[0433] During travel, the device continuously acquires the traveler's location information and monitors the traveler's emotional state through an emotion engine. The device's sensors and microphone analyze emotions based on facial expressions, tone of voice, and speech content, and transmit the results to a server. The server then guides the traveler with appropriate information and relaxation spots based on their emotional state. For example, if the traveler is feeling stressed, the server will immediately suggest a place to relax.

[0434] For example, if a traveler is distressed by rain while sightseeing, the device takes the rain situation into account and sends emotional data to the server. The server immediately provides information recommending nearby shelters or cafes. In this case, a prompt message to the generative AI model such as "Please list tourist spots where the user can relax. The user is currently feeling stressed because of the rain" can be used.

[0435] The hardware used will include mobile devices and personal assistant robots (e.g., Pepper, Nao) carried by travelers, while the software will consist of sentiment analysis libraries (OpenCV, DLib, etc.) and AI platforms (Google Cloud AI, etc.). This will enable the creation of services that meet the personalized needs of travelers and enhance their travel experience.

[0436] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0437] Step 1:

[0438] Users input information about their condition, travel preferences, and emotional state through their terminal. The input data is temporarily stored on the terminal and prepared for transmission to the server. The system is managed to ensure that user input is accurately collected and that necessary information is reliably transmitted to the server.

[0439] Step 2:

[0440] The terminal sends all collected user information to the server. The server analyzes the received data and stores it in the appropriate database. At this point, it builds foundational data for learning user needs and preferences using machine learning algorithms. The server verifies the reliability of the data and prepares it for analysis.

[0441] Step 3:

[0442] The server searches for barrier-free facilities, transportation options, and tourist attractions based on traveler information stored in the database. It also processes data to suggest relaxation spots and places to rest based on the traveler's emotional state. In this step, an AI algorithm is used to filter the information and generate a travel plan.

[0443] Step 4:

[0444] The generated travel plan is sent to the device and presented to the user. The user can review the plan and customize it as needed. At this stage, the user's feelings are reflected in the plan, allowing for personalized choices.

[0445] Step 5:

[0446] During travel, the device continuously acquires the user's location and emotional state. This is done using a GPS module and emotion analysis libraries (e.g., OpenCV, DLib). The acquired information is temporarily processed within the device before being sent to the server. Real-time information updates are performed based on the user's location and emotions.

[0447] Step 6:

[0448] The server analyzes the transmitted location information and emotional state, and generates appropriate suggestions based on the results. For example, if the user is feeling stressed, the server will recommend relaxation spots. In this process, it optimizes the information by utilizing prompts to the generative AI model, such as, "Please list places where the user can calm down. The user is currently feeling stressed because of the rain."

[0449] Step 7:

[0450] In emergencies, the device automatically transmits the user's location, health information, and emotional state to a server. Based on the received data, the server immediately contacts the necessary support organizations. This process ensures the user's safety and security.

[0451] Step 8:

[0452] After the trip ends, the server stores the traveler's feedback in a database, which is used to improve future travel suggestions. This information is used to further enhance and develop suggestions for other users.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] [Third Embodiment]

[0457] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0458] 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.

[0459] 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).

[0460] 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.

[0461] 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.

[0462] 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).

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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.

[0468] 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".

[0469] This invention is a system that provides support to help travelers travel with peace of mind. The system consists of a user terminal, a central server, and an associated database.

[0470] First, the user uses a terminal to input information about their disability and travel preferences. This information includes accessibility features of accommodations, modes of transportation, and desired destinations. The terminal sends this information to a server, which stores the received information in a database and uses an AI algorithm to learn the user's needs. This initial data collection and learning prepares the system to provide travel support optimized for each individual user.

[0471] Next, the server uses the collected information to suggest barrier-free accommodations, transportation options, and tourist destinations. These suggestions are presented as an optimal travel plan based on the latest barrier-free information stored in the database. The terminal displays this travel plan to the user, who can then review and modify it.

[0472] During travel, the device uses GPS technology to determine the user's current location and communicates with a server to obtain real-time accessibility information for the surrounding area. This information is then provided to the user via a voice assistant on the device, allowing the user to obtain necessary information by voice. This ensures that the user always has the latest information at hand, allowing them to enjoy their trip with peace of mind.

[0473] Furthermore, if a user makes an emergency call from their device in an emergency, the server immediately receives the user's location and health information. Based on this information, the server coordinates with the nearest medical facilities and support staff to provide the user with a prompt response.

[0474] For example, if a traveler using a wheelchair visits a tourist destination and is looking for a route without steps, the voice assistant will suggest the optimal route based on the latest accessibility information retrieved from the server by the device. This allows travelers to enjoy sightseeing without stress.

[0475] After a trip, users can post their experiences to the community from their devices. The server collects this experience information and uses it to support future trips. This allows the entire system to continuously learn and evolve.

[0476] The following describes the processing flow.

[0477] Step 1:

[0478] The user uses a terminal to enter their disability information and travel preference information. Once the input is complete, the terminal sends this information to the server.

[0479] Step 2:

[0480] The server creates a user profile based on the received information and stores it in a database. It also utilizes AI algorithms to learn the user's specific needs. This learning process incorporates past travel history and data from other similar users.

[0481] Step 3:

[0482] The server searches the database for the most suitable barrier-free accommodations, transportation options, and tourist attractions for the user. This process takes into account the barrier-free accessibility status of the target area.

[0483] Step 4:

[0484] The server combines the search results to generate multiple travel plans. These plans are optimized to best meet the user's travel preferences.

[0485] Step 5:

[0486] The travel plan generated on the device is displayed to the user. The user can review it and customize the plan as needed.

[0487] Step 6:

[0488] During travel, the device periodically collects the user's location information and sends it to the server. This process is carried out with the traveler's privacy in mind and only to the extent approved by the user.

[0489] Step 7:

[0490] The server updates accessibility information based on location data in real time and sends push notifications to the device. If a voice assistant is active, it provides information instantly via voice in response to user queries.

[0491] Step 8:

[0492] In an emergency, the user activates the emergency contact function from their device. The device immediately sends their current location and health information to the server.

[0493] Step 9:

[0494] Based on the transmitted emergency information, the server automatically sends notifications to the nearest medical facilities and support teams to coordinate. It also notifies the user of necessary instructions and provides follow-up support until their safety is ensured.

[0495] Step 10:

[0496] After their trip, users share their travel experiences with the community using their devices. The server collects this information and uses it as data for planning future trips, helping to improve the system's accuracy.

[0497] (Example 1)

[0498] 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."

[0499] In modern travel, travelers with disabilities, in particular, frequently face situations that compromise their safety and convenience due to a lack of accessibility information at their destinations and inadequate emergency response. In this context, there is a need for optimal travel plans based on disability information and travel preferences, real-time support during travel, and prompt responses in emergencies.

[0500] 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.

[0501] This invention includes a server that receives information on travelers' disabilities and travel preferences and learns using a generative AI model, a server that proposes barrier-free accommodations, transportation options, and tourist destinations, and a server that acquires location information and provides guidance information in real time. This enables optimal planning for travelers with disabilities to travel with peace of mind, as well as real-time and emergency support.

[0502] "Disability information" refers to information about physical or mental limitations that travelers may have, and is a factor that needs to be taken into consideration when traveling.

[0503] "Travel preference information" refers to information that indicates the individual preferences and requirements of travelers regarding their preferred travel style and destinations.

[0504] A "generative AI model" is an algorithm that uses machine learning techniques to analyze input data and then provides personalized suggestions based on that analysis.

[0505] "Barrier-free access" refers to a state where facilities and services are available for use by people with physical limitations without any obstacles.

[0506] "Location information" refers to information indicating the current geographical location of a traveler, identified using GPS technology or similar methods.

[0507] "Guidance information" refers to detailed information about routes and surrounding facilities provided to travelers.

[0508] A "support group" is an organization or agency that coordinates the provision of medical or other assistance to travelers in times of emergency.

[0509] A "voice assistant" is a system that uses voice recognition technology to receive instructions from the user and provides information or performs actions accordingly.

[0510] "Experience information" refers to information that travelers record about the experiences and lessons they learned during their trips. By sharing this information with other travelers, it can serve as a guide for future trips.

[0511] This invention provides a system that allows travelers to obtain an optimal travel plan that takes into account information about their disabilities and travel preferences. The system consists of a user terminal, a central server, and an associated database.

[0512] First, the user uses a device to input information about their disability and travel preferences. The device sends this input to a server. The server analyzes the received information using a generative AI model to learn the user's preferences. This learning process is performed using software such as Python or TensorFlow. Based on the information obtained in this way, barrier-free accommodations, transportation options, and tourist destinations are identified.

[0513] The server processes accessibility information stored in the database in real time, providing the best possible guidance throughout the trip. The terminal uses a GPS module to determine its current location and communicates with the server. A voice assistant allows users to operate the system by voice. For example, if a user enters the prompt "Tell me some Tokyo tourist spots suitable for wheelchair users" into the terminal, the system can suggest the most suitable locations.

[0514] In an emergency, users can quickly send an SOS from their device, and the server transmits the user's current location and health status information to relevant support organizations. This enables rapid first aid.

[0515] After their trip, travelers can use their devices to post their experiences to the community. The server collects these posts and uses them to plan future trips, allowing the generative AI model to continuously learn and improve the system's accuracy. Through this continuous learning and improvement process, the service provided to travelers is enhanced.

[0516] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0517] Step 1:

[0518] Users use a device to input information about their disability and travel preferences. This input data is collected through text forms. For example, if a user enters "uses a wheelchair" and "wants accommodation with an ocean view," the device formats this information and sends it to the server. The information obtained as input data is categorized as user profile data.

[0519] Step 2:

[0520] The server stores user information received from the terminal in a database. In this step, the server uses a Python script to preprocess the data and convert it into a format suitable for the generative AI model. By analyzing the received data, separating fault information and preference information, and setting attribute values ​​for each category, it prepares for the next learning phase.

[0521] Step 3:

[0522] The server uses a generative AI model to learn from input user data. Specifically, it trains the model using the TensorFlow library to enhance its ability to recognize patterns and provide optimal suggestions to the user. The model performs data calculations on user profile data as input, using the training data, and generates prediction results as output. This includes information such as the availability of barrier-free facilities and recommended tourist routes.

[0523] Step 4:

[0524] The server creates an optimal travel plan based on the learning results. It references the latest accessibility information in the database and generates a list of suggestions. For example, the list may include specific options such as "easily accessible hotels" or "tourist attractions without steps." The server sends this information to the terminal, allowing the user to view and edit the plan.

[0525] Step 5:

[0526] During travel, the device uses GPS to determine the user's current location. Based on this location information, it communicates with a server to obtain real-time accessibility information for the surrounding area. Based on the acquired data, the voice assistant provides route guidance to the user. For example, if the user prompts, "Tell me a route with few steps from my current location," the voice assistant will provide directions to the destination.

[0527] Step 6:

[0528] In an emergency, the user sends an emergency notification from their device to the server. The server quickly analyzes the location and health status and contacts the nearest support organization according to standard protocols. In this step, information is processed in real time, and the process of contacting medical facilities is automated.

[0529] Step 7:

[0530] After their trip, users post their experiences to the community via their devices. The server collects the posted data and uses it to plan future trips. This updates the community and database information, which is then used as new training data for the AI ​​model.

[0531] (Application Example 1)

[0532] 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."

[0533] For travelers, especially those with disabilities, to enjoy their trips with peace of mind, it is essential to provide travel plans tailored to their individual needs and real-time information during their travels. However, conventional systems lack this kind of individualized support, resulting in a lack of information that travelers need to take appropriate action at their destination. Furthermore, providing information to respond quickly and appropriately in emergencies is also a major challenge.

[0534] 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.

[0535] In this invention, the server includes means for receiving individual information and preference information of travelers and learning using machine learning, means for acquiring the traveler's current location during travel and providing geographic information in real time, and means for presenting guidance information to travelers via voice while they are on the move and receiving voice instructions from travelers. As a result, travelers can create optimal travel plans that suit their needs and obtain useful information in real time while traveling.

[0536] "Personalized information" refers to data such as a traveler's disability information and travel preferences, and is information tailored to individual needs.

[0537] "Machine learning" is the process by which computers learn features from data and improve their ability to make predictions and classifications.

[0538] "Accessibility-friendly accommodations" are accommodations that are designed to be easily accessible to travelers with disabilities, incorporating features such as barrier-free design.

[0539] "Providing real-time geographic information" means instantly providing travelers with the latest geographical data based on their current location.

[0540] "Providing guidance information via audio" means using audio technology to provide information and instructions to travelers.

[0541] "Accepting voice instructions" means analyzing the voice spoken by travelers and obtaining input information so that the system can respond appropriately.

[0542] An "automated communication system" is a function that, in the event of an emergency, allows a computer to automatically contact external organizations without requiring human intervention.

[0543] One embodiment of this invention is a support system that allows travelers to enjoy their trips with peace of mind. This is achieved by using a server, terminals, and associated databases.

[0544] The server receives individual traveler information and preferences, and uses machine learning algorithms to generate information optimized for each traveler. This process makes it possible to suggest accessible accommodations, transportation options, and tourist destinations to travelers.

[0545] The device uses GPS technology to obtain the traveler's current location during their trip and provides geographical information received from a server in real time. The device is equipped with a voice assistant function that can provide traveler guidance information via voice and accept voice instructions from the traveler. This voice technology is often implemented using programming languages ​​such as Java or Python.

[0546] As a concrete example, a traveler using a wheelchair is given. When this traveler visits a barrier-free tourist destination, the voice assistant guides them to the most suitable route based on the latest barrier-free information retrieved from the server. In this way, the traveler can enjoy sightseeing stress-free.

[0547] An example of a prompt is, "Please suggest the best barrier-free route for a wheelchair user to enjoy sightseeing in Kyoto." By inputting such prompts into the AI ​​model, useful information can be obtained in real time.

[0548] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0549] Step 1:

[0550] The server receives individual information and travel preference information from the user. This includes data such as disability information and desired destinations entered by the user. User profile data is received as input, and registration of this data into the initial database is performed as output. Based on this registered data, the server starts a process of learning the user's needs using a machine learning model.

[0551] Step 2:

[0552] The server applies machine learning algorithms to generate lists of accommodations, transportation, and tourist destinations optimized for the user's preferences. It uses the training data obtained in Step 1 as input and generates a list of travel plans suitable for the user as output. Specifically, it utilizes data analysis and pattern recognition techniques to match user preferences with corresponding facility data and extract the best options.

[0553] Step 3:

[0554] The device uses GPS technology to determine the user's current location while traveling and transmits that location information to the server. The input is geographic location data acquired by the device. The output is the current location information sent to the server. Based on this, the server acquires geographic information in real time and prepares to provide the corresponding information to the device.

[0555] Step 4:

[0556] The server compares the acquired location information with the user's current location and provides the user with the optimal route and accessibility information in real time. The inputs are the location information obtained in step 3 and geographical information from the database. The output is guidance information provided via voice or visual means. Specifically, the server calculates an appropriate route based on the user's current location and transmits the information to the terminal through that route.

[0557] Step 5:

[0558] The device uses a voice assistant to convey guidance information from the server to the user. It can also accept voice commands from the user. Inputs include guidance information sent from the server and voice commands from the user. Outputs include voice guidance to the user and the collection of voice data as feedback. Specifically, speech synthesis technology is used to provide information in a way that is easy for the user to understand, and the device is prepared to recognize and process any further instructions.

[0559] 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.

[0560] This invention is a system designed to allow travelers to enjoy their trips with peace of mind. Its key feature is the use of an emotion engine to understand the traveler's emotional state and provide travel support accordingly. The system consists of a user terminal, a central server, an emotion engine, and a related database.

[0561] First, the user inputs information about their disability and travel preferences through their device. The device sends this information to a server, which stores it in a database and uses an AI algorithm to learn the user's needs. Here, the server understands what kind of support and environment the user desires and prepares to provide personalized travel support.

[0562] Based on the transmitted information, the server searches its database for information on barrier-free accommodations, transportation options, and tourist attractions, and generates a travel plan according to the user's learned preferences. The terminal displays this plan to the user, who can review it and customize it as needed.

[0563] During travel, the device continuously acquires the user's location information and monitors the user's emotional state through an emotion engine. Utilizing the device's sensors and microphone, it analyzes the user's emotions from facial expressions, tone of voice, and speech content, and based on this information, the server provides appropriate information. For example, if the emotion engine detects user stress, the server will guide the user to relaxation spots or places where they can rest.

[0564] Furthermore, in emergencies, the device immediately transmits the user's location and health information to the server. The server then contacts the nearest medical facility or support service, enabling a rapid response. This enhances safety and peace of mind.

[0565] The system further collects feedback from users who have completed their travel experiences within the community. The server stores data on travel experiences where users expressed particularly positive emotions and uses this data to suggest travel plans to other users with similar needs. This allows the entire system to be continuously improved by leveraging the information provided by the emotion engine, enabling the delivery of more personalized travel experiences.

[0566] As a concrete example, suppose a user visits a tourist destination and feels anxious due to changes in the weather or other factors. In this case, the emotion engine can detect that emotion, and the server can immediately provide information recommending tourist spots or evacuation locations that are appropriate for the situation, thereby supporting the user's sense of security.

[0567] The following describes the processing flow.

[0568] Step 1:

[0569] The user uses a terminal to enter information about their condition and travel preferences. The terminal then sends this information to the server.

[0570] Step 2:

[0571] The server uses an AI algorithm to analyze user needs based on the received user information and stores the results in a database.

[0572] Step 3:

[0573] The server searches the database for barrier-free accommodations, transportation options, and tourist attractions, and generates an optimal travel plan based on the user's preferences.

[0574] Step 4:

[0575] The generated travel plan is sent to the device, which then displays the plan to the user. The user reviews the plan and customizes it as needed.

[0576] Step 5:

[0577] During travel, the device acquires the user's location information in real time and sends it to the server. At the same time, the device's sensors and microphone are used by an emotion engine to analyze the user's facial expressions and tone of voice.

[0578] Step 6:

[0579] The emotion engine analyzes the user's emotional state, and if stress or anxiety is detected, the server immediately sends information about corresponding relaxation spots and safe spaces to the device.

[0580] Step 7:

[0581] The terminal receives information from the server and notifies the user, and provides guidance using a voice assistant, thereby quickly responding to the user's needs.

[0582] Step 8:

[0583] In an emergency, if a user uses the emergency contact function on their device, their location and health information will be sent to the server.

[0584] Step 9:

[0585] The server coordinates with the nearest medical facilities and support teams to provide a rapid response to users. The terminal provides users with appropriate measures and evacuation instructions based on the current situation.

[0586] Step 10:

[0587] After a trip, users share their experiences with the community via their devices. The server learns from this information and incorporates it into future travel suggestions. This improves the system's accuracy and personalization.

[0588] (Example 2)

[0589] 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."

[0590] To ensure travelers can enjoy their trips with peace of mind, it is necessary to provide information tailored to each traveler's individual circumstances and preferences. However, conventional systems have difficulty integrating traveler information such as disability information, preferences, emotional state, and emergency health status, making it challenging to provide optimal information in real time during a trip. This results in travelers being unable to receive the necessary support when they need it.

[0591] 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.

[0592] In this invention, the server includes means for receiving traveler disability information and travel preference information and learning the information using machine learning technology; means for acquiring traveler location information and providing customized support information in real time; and means for monitoring the traveler's emotional state and providing information corresponding to that emotional state. This makes it possible to provide personalized information that meets the traveler's needs.

[0593] A "traveler" refers to an individual who uses the system while traveling, and is the target of support provided based on their disability information and preferences.

[0594] "Disability information" refers to information about a traveler's physical or mental limitations, and is used to optimize support during their trip.

[0595] "Travel preference information" refers to information about travelers' preferred activities, places they want to visit, budgets, etc., and is used to provide personalized travel experiences.

[0596] "Machine learning technology" refers to techniques that enable computers to learn from data and improve their performance in performing specific tasks.

[0597] "Location information" refers to data that indicates a traveler's current geographical location and is used for providing real-time information and responding to emergencies.

[0598] "Emotional state" refers to information that indicates the traveler's psychological or emotional condition, including stress and anxiety.

[0599] "Support information" refers to information about accommodations, tourist attractions, relaxation spots, etc., provided to travelers so that they can enjoy their trip with peace of mind.

[0600] An "emergency" refers to a situation in which a traveler faces a serious health or safety issue during their trip, requiring a swift response.

[0601] "Health information" refers to data about a traveler's physical health status and is used to share information with medical institutions as needed.

[0602] To implement this invention, it is necessary to organically link multiple components. Specifically, a user's terminal, a central server, an emotion engine for sentiment analysis, and an associated database system are required.

[0603] First, users input their travel preferences and disability information using their own devices (such as smartphones or tablets). These devices are equipped with sensor technology and voice assistant functions, allowing for easy input of this information via voice or touch.

[0604] Next, the terminal transmits the collected information to the server via a secure communication method. The server uses high-performance computing equipment and a database system, enabling it to quickly and securely store and manage user information. The database already contains pre-collected information on barrier-free facilities, services, and tourist destinations.

[0605] Based on this information, the server uses a generative AI model to learn the user's preferences and needs. The AI ​​model identifies patterns from a vast amount of data, including the user's past information and the preferences of similar users, and automatically generates the optimal travel plan. The following is an example of a prompt given to the AI ​​model:

[0606] "Please create a list of tourist spots that users would like to see."

[0607] "Please list the data items needed to generate personalized travel plans."

[0608] During travel, the device uses GPS and built-in sensors to acquire the user's location and emotional state in real time. When the emotion engine detects the user's stress or anxiety, it sends this information to a server, which then provides pre-prepared relaxation spots and sightseeing information. This process allows the user to feel more at ease while traveling.

[0609] Furthermore, in the event of an emergency, the device immediately sends data, including the user's health information, to a server, which automatically contacts the nearest medical facility or support service. This ensures a swift and appropriate emergency response.

[0610] This system utilizes advanced, data-driven technology to provide travelers with peace of mind and a fulfilling travel experience.

[0611] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0612] Step 1:

[0613] Users input travel preferences and disability information using their own devices. Specific input includes desired destinations, budgets, tourist attractions, and necessary support. The device collects this information, converts it into a digital format, and generates data packets to send to the server. The output data consists of the user's preferences and disability information, ready for transmission to the server.

[0614] Step 2:

[0615] The terminal transmits user preference and fault information to a central server using a secure protocol (e.g., HTTPS). This information is received by the server and stored in a database. The input is encoded user information data, and the output is data storage on the server side.

[0616] Step 3:

[0617] The server uses a generated AI model based on user information retrieved from the database to learn the user's individual needs. The AI ​​model analyzes relevant information and performs data calculations to extract preference patterns. The input consists of existing information from the database and newly received user information, and the output is a travel plan optimized for the user.

[0618] Step 4:

[0619] The server uses the data obtained as a result of training to select barrier-free facilities, transportation options, and recommended tourist destinations, and generates a detailed travel plan. This process employs data filtering and plan generation algorithms. The input is the learned preference patterns, and the output is specific travel plan information.

[0620] Step 5:

[0621] The terminal presents the generated travel plan to the user and provides an interface that allows the user to customize it. The user can review the travel plan here and make changes as needed. The input is travel plan data from the server, and the output is a customizable plan display for the user.

[0622] Step 6:

[0623] During travel, the device continuously monitors the user's location and emotional state in real time using its built-in GPS and sensors. The data collected by the sensors includes geographical location, voice tone, and facial expressions. This monitoring data is fed into an emotion engine, which analyzes it to detect the user's stress and anxiety. The output is an informational notification sent to the server based on the emotional state.

[0624] Step 7:

[0625] The server provides the user with appropriate actions based on information provided by the emotion engine. Here, it presents information on relaxation spots and new tourist destinations tailored to the user's current emotional state. The input is the emotion analysis result, and the output is the information displayed on the terminal.

[0626] Step 8:

[0627] In an emergency, the device will promptly transmit the user's health status data and location information to the server. The server will then receive this information and immediately begin the process of contacting support services. The input is user information in an emergency, and the output is the notification to support services.

[0628] Step 9:

[0629] After the trip ends, the device provides an interface for collecting user feedback on their travel experience. The server analyzes the collected feedback and improves the generated AI model to use in future travel planning. The input is user feedback information, and the output is the improved AI model.

[0630] (Application Example 2)

[0631] 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."

[0632] When travelers navigate different environments, their experience can be diminished if they are unable to cope with potential stressors or emergencies. Furthermore, there is a lack of resources to provide optimal travel experiences tailored to each traveler's emotional state. These challenges need to be addressed to enhance travel safety and satisfaction.

[0633] 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.

[0634] This invention includes a server that receives and learns information on a traveler's disability, travel preferences, and emotional state; a server that, based on the learned information, suggests barrier-free accommodations, transportation options, and tourist destinations, and guides the traveler to relaxation spots and resting places according to their emotional state; and a server that acquires the traveler's location information and emotional state during the trip and provides barrier-free information and emotionally appropriate information in real time. This makes it possible to provide travelers with an individualized and emotionally appropriate travel experience.

[0635] A "traveler" is someone who goes on a trip and needs support tailored to their experiences and emotional state during that trip.

[0636] "Disability information" refers to information about the physical or mental limitations that travelers have, and serves as the basis for providing accessibility considerations.

[0637] "Travel preference information" refers to information about travelers' preferences and tastes, and serves as a reference when creating personalized travel plans.

[0638] "Emotional state information" refers to information that indicates the psychological state of a traveler, and is used to provide emotionally tailored services in order to improve the quality of their travel experience.

[0639] "Means" refer to methods and devices that perform information processing or provide support to achieve an objective, and are elements that constitute a system.

[0640] "Barrier-free accommodations" are accommodations that are designed to be safe and accessible for travelers with disabilities.

[0641] "Transportation" refers to the vehicles and routes that travelers use to get around, and is a factor that directly impacts the comfort of the trip.

[0642] A "tourist destination" is a place that travelers visit and enjoy, and is part of a travel destination.

[0643] A "relaxation spot" is a place where travelers can relax and soothe their mind and body, and is suggested as a way to alleviate stress.

[0644] A "place where you can rest" is a place where travelers can take a temporary rest during their trip.

[0645] "Location information" refers to data that indicates a traveler's current location and is used for real-time guidance and support.

[0646] "Emotional monitoring" is a technology that observes and analyzes the emotional state of travelers in order to optimize their experience.

[0647] This invention provides a system to assist travelers. The system consists of a user terminal, a central server, an emotion engine, and a database associated with them. First, the traveler inputs disability information, travel preference information, and emotional state information through the terminal. The terminal sends this information to the server, which stores the information in a database and learns the traveler's needs using machine learning algorithms. In this process, the system understands what kind of support and environment the user needs and prepares to provide personalized travel support.

[0648] Based on the information it has learned, the server searches its database for information on barrier-free accommodations, transportation, and tourist attractions, and generates a travel plan that suggests relaxation spots and places to rest according to the user's emotional state. The terminal presents this plan to the user, who can then customize it to suit their needs.

[0649] During travel, the device continuously acquires the traveler's location information and monitors the traveler's emotional state through an emotion engine. The device's sensors and microphone analyze emotions based on facial expressions, tone of voice, and speech content, and transmit the results to a server. The server then guides the traveler with appropriate information and relaxation spots based on their emotional state. For example, if the traveler is feeling stressed, the server will immediately suggest a place to relax.

[0650] For example, if a traveler is distressed by rain while sightseeing, the device takes the rain situation into account and sends emotional data to the server. The server immediately provides information recommending nearby shelters or cafes. In this case, a prompt message to the generative AI model such as "Please list tourist spots where the user can relax. The user is currently feeling stressed because of the rain" can be used.

[0651] The hardware used will include mobile devices and personal assistant robots (e.g., Pepper, Nao) carried by travelers, while the software will consist of sentiment analysis libraries (OpenCV, DLib, etc.) and AI platforms (Google Cloud AI, etc.). This will enable the creation of services that meet the personalized needs of travelers and enhance their travel experience.

[0652] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0653] Step 1:

[0654] Users input information about their condition, travel preferences, and emotional state through their terminal. The input data is temporarily stored on the terminal and prepared for transmission to the server. The system is managed to ensure that user input is accurately collected and that necessary information is reliably transmitted to the server.

[0655] Step 2:

[0656] The terminal sends all collected user information to the server. The server analyzes the received data and stores it in the appropriate database. At this point, it builds foundational data for learning user needs and preferences using machine learning algorithms. The server verifies the reliability of the data and prepares it for analysis.

[0657] Step 3:

[0658] The server searches for barrier-free facilities, transportation options, and tourist attractions based on traveler information stored in the database. It also processes data to suggest relaxation spots and places to rest based on the traveler's emotional state. In this step, an AI algorithm is used to filter the information and generate a travel plan.

[0659] Step 4:

[0660] The generated travel plan is sent to the device and presented to the user. The user can review the plan and customize it as needed. At this stage, the user's feelings are reflected in the plan, allowing for personalized choices.

[0661] Step 5:

[0662] During travel, the device continuously acquires the user's location and emotional state. This is done using a GPS module and emotion analysis libraries (e.g., OpenCV, DLib). The acquired information is temporarily processed within the device before being sent to the server. Real-time information updates are performed based on the user's location and emotions.

[0663] Step 6:

[0664] The server analyzes the transmitted location information and emotional state, and generates appropriate suggestions based on the results. For example, if the user is feeling stressed, the server will recommend relaxation spots. In this process, it optimizes the information by utilizing prompts to the generative AI model, such as, "Please list places where the user can calm down. The user is currently feeling stressed because of the rain."

[0665] Step 7:

[0666] In emergencies, the device automatically transmits the user's location, health information, and emotional state to a server. Based on the received data, the server immediately contacts the necessary support organizations. This process ensures the user's safety and security.

[0667] Step 8:

[0668] After the trip ends, the server stores the traveler's feedback in a database, which is used to improve future travel suggestions. This information is used to further enhance and develop suggestions for other users.

[0669] 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.

[0670] 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.

[0671] 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.

[0672] [Fourth Embodiment]

[0673] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0674] 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.

[0675] 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).

[0676] 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.

[0677] 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.

[0678] 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).

[0679] 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.

[0680] 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.

[0681] 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.

[0682] 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.

[0683] 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.

[0684] 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.

[0685] 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".

[0686] This invention is a system that provides support to help travelers travel with peace of mind. The system consists of a user terminal, a central server, and an associated database.

[0687] First, the user uses a terminal to input information about their disability and travel preferences. This information includes accessibility features of accommodations, modes of transportation, and desired destinations. The terminal sends this information to a server, which stores the received information in a database and uses an AI algorithm to learn the user's needs. This initial data collection and learning prepares the system to provide travel support optimized for each individual user.

[0688] Next, the server uses the collected information to suggest barrier-free accommodations, transportation options, and tourist destinations. These suggestions are presented as an optimal travel plan based on the latest barrier-free information stored in the database. The terminal displays this travel plan to the user, who can then review and modify it.

[0689] During travel, the device uses GPS technology to determine the user's current location and communicates with a server to obtain real-time accessibility information for the surrounding area. This information is then provided to the user via a voice assistant on the device, allowing the user to obtain necessary information by voice. This ensures that the user always has the latest information at hand, allowing them to enjoy their trip with peace of mind.

[0690] Furthermore, if a user makes an emergency call from their device in an emergency, the server immediately receives the user's location and health information. Based on this information, the server coordinates with the nearest medical facilities and support staff to provide the user with a prompt response.

[0691] For example, if a traveler using a wheelchair visits a tourist destination and is looking for a route without steps, the voice assistant will suggest the optimal route based on the latest accessibility information retrieved from the server by the device. This allows travelers to enjoy sightseeing without stress.

[0692] After a trip, users can post their experiences to the community from their devices. The server collects this experience information and uses it to support future trips. This allows the entire system to continuously learn and evolve.

[0693] The following describes the processing flow.

[0694] Step 1:

[0695] The user uses a terminal to enter their disability information and travel preference information. Once the input is complete, the terminal sends this information to the server.

[0696] Step 2:

[0697] The server creates a user profile based on the received information and stores it in a database. It also utilizes AI algorithms to learn the user's specific needs. This learning process incorporates past travel history and data from other similar users.

[0698] Step 3:

[0699] The server searches the database for the most suitable barrier-free accommodations, transportation options, and tourist attractions for the user. This process takes into account the barrier-free accessibility status of the target area.

[0700] Step 4:

[0701] The server combines the search results to generate multiple travel plans. These plans are optimized to best meet the user's travel preferences.

[0702] Step 5:

[0703] The travel plan generated on the device is displayed to the user. The user can review it and customize the plan as needed.

[0704] Step 6:

[0705] During travel, the device periodically collects the user's location information and sends it to the server. This process is carried out with the traveler's privacy in mind and only to the extent approved by the user.

[0706] Step 7:

[0707] The server updates accessibility information based on location data in real time and sends push notifications to the device. If a voice assistant is active, it provides information instantly via voice in response to user queries.

[0708] Step 8:

[0709] In an emergency, the user activates the emergency contact function from their device. The device immediately sends their current location and health information to the server.

[0710] Step 9:

[0711] Based on the transmitted emergency information, the server automatically sends notifications to the nearest medical facilities and support teams to coordinate. It also notifies the user of necessary instructions and provides follow-up support until their safety is ensured.

[0712] Step 10:

[0713] After their trip, users share their travel experiences with the community using their devices. The server collects this information and uses it as data for planning future trips, helping to improve the system's accuracy.

[0714] (Example 1)

[0715] 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".

[0716] In modern travel, travelers with disabilities, in particular, frequently face situations that compromise their safety and convenience due to a lack of accessibility information at their destinations and inadequate emergency response. In this context, there is a need for optimal travel plans based on disability information and travel preferences, real-time support during travel, and prompt responses in emergencies.

[0717] 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.

[0718] This invention includes a server that receives information on travelers' disabilities and travel preferences and learns using a generative AI model, a server that proposes barrier-free accommodations, transportation options, and tourist destinations, and a server that acquires location information and provides guidance information in real time. This enables optimal planning for travelers with disabilities to travel with peace of mind, as well as real-time and emergency support.

[0719] "Disability information" refers to information about physical or mental limitations that travelers may have, and is a factor that needs to be taken into consideration when traveling.

[0720] "Travel preference information" refers to information that indicates the individual preferences and requirements of travelers regarding their preferred travel style and destinations.

[0721] A "generative AI model" is an algorithm that uses machine learning techniques to analyze input data and then provides personalized suggestions based on that analysis.

[0722] "Barrier-free access" refers to a state where facilities and services are available for use by people with physical limitations without any obstacles.

[0723] "Location information" refers to information indicating the current geographical location of a traveler, identified using GPS technology or similar methods.

[0724] "Guidance information" refers to detailed information about routes and surrounding facilities provided to travelers.

[0725] A "support group" is an organization or agency that coordinates the provision of medical or other assistance to travelers in times of emergency.

[0726] A "voice assistant" is a system that uses voice recognition technology to receive instructions from the user and provides information or performs actions accordingly.

[0727] "Experience information" refers to information that travelers record about the experiences and lessons they learned during their trips. By sharing this information with other travelers, it can serve as a guide for future trips.

[0728] This invention provides a system that allows travelers to obtain an optimal travel plan that takes into account information about their disabilities and travel preferences. The system consists of a user terminal, a central server, and an associated database.

[0729] First, the user uses a device to input information about their disability and travel preferences. The device sends this input to a server. The server analyzes the received information using a generative AI model to learn the user's preferences. This learning process is performed using software such as Python or TensorFlow. Based on the information obtained in this way, barrier-free accommodations, transportation options, and tourist destinations are identified.

[0730] The server processes accessibility information stored in the database in real time, providing the best possible guidance throughout the trip. The terminal uses a GPS module to determine its current location and communicates with the server. A voice assistant allows users to operate the system by voice. For example, if a user enters the prompt "Tell me some Tokyo tourist spots suitable for wheelchair users" into the terminal, the system can suggest the most suitable locations.

[0731] In an emergency, users can quickly send an SOS from their device, and the server transmits the user's current location and health status information to relevant support organizations. This enables rapid first aid.

[0732] After their trip, travelers can use their devices to post their experiences to the community. The server collects these posts and uses them to plan future trips, allowing the generative AI model to continuously learn and improve the system's accuracy. Through this continuous learning and improvement process, the service provided to travelers is enhanced.

[0733] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0734] Step 1:

[0735] Users use a device to input information about their disability and travel preferences. This input data is collected through text forms. For example, if a user enters "uses a wheelchair" and "wants accommodation with an ocean view," the device formats this information and sends it to the server. The information obtained as input data is categorized as user profile data.

[0736] Step 2:

[0737] The server stores user information received from the terminal in a database. In this step, the server uses a Python script to preprocess the data and convert it into a format suitable for the generative AI model. By analyzing the received data, separating fault information and preference information, and setting attribute values ​​for each category, it prepares for the next learning phase.

[0738] Step 3:

[0739] The server uses a generative AI model to learn from input user data. Specifically, it trains the model using the TensorFlow library to enhance its ability to recognize patterns and provide optimal suggestions to the user. The model performs data calculations on user profile data as input, using the training data, and generates prediction results as output. This includes information such as the availability of barrier-free facilities and recommended tourist routes.

[0740] Step 4:

[0741] The server creates an optimal travel plan based on the learning results. It references the latest accessibility information in the database and generates a list of suggestions. For example, the list may include specific options such as "easily accessible hotels" or "tourist attractions without steps." The server sends this information to the terminal, allowing the user to view and edit the plan.

[0742] Step 5:

[0743] During travel, the device uses GPS to determine the user's current location. Based on this location information, it communicates with a server to obtain real-time accessibility information for the surrounding area. Based on the acquired data, the voice assistant provides route guidance to the user. For example, if the user prompts, "Tell me a route with few steps from my current location," the voice assistant will provide directions to the destination.

[0744] Step 6:

[0745] In an emergency, the user sends an emergency notification from their device to the server. The server quickly analyzes the location and health status and contacts the nearest support organization according to standard protocols. In this step, information is processed in real time, and the process of contacting medical facilities is automated.

[0746] Step 7:

[0747] After their trip, users post their experiences to the community via their devices. The server collects the posted data and uses it to plan future trips. This updates the community and database information, which is then used as new training data for the AI ​​model.

[0748] (Application Example 1)

[0749] 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".

[0750] For travelers, especially those with disabilities, to enjoy their trips with peace of mind, it is essential to provide travel plans tailored to their individual needs and real-time information during their travels. However, conventional systems lack this kind of individualized support, resulting in a lack of information that travelers need to take appropriate action at their destination. Furthermore, providing information to respond quickly and appropriately in emergencies is also a major challenge.

[0751] 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.

[0752] In this invention, the server includes means for receiving individual information and preference information of travelers and learning using machine learning, means for acquiring the traveler's current location during travel and providing geographic information in real time, and means for presenting guidance information to travelers via voice while they are on the move and receiving voice instructions from travelers. As a result, travelers can create optimal travel plans that suit their needs and obtain useful information in real time while traveling.

[0753] "Personalized information" refers to data such as a traveler's disability information and travel preferences, and is information tailored to individual needs.

[0754] "Machine learning" is the process by which computers learn features from data and improve their ability to make predictions and classifications.

[0755] "Accessibility-friendly accommodations" are accommodations that are designed to be easily accessible to travelers with disabilities, incorporating features such as barrier-free design.

[0756] "Providing real-time geographic information" means instantly providing travelers with the latest geographical data based on their current location.

[0757] "Providing guidance information via audio" means using audio technology to provide information and instructions to travelers.

[0758] "Accepting voice instructions" means analyzing the voice spoken by travelers and obtaining input information so that the system can respond appropriately.

[0759] An "automated communication system" is a function that, in the event of an emergency, allows a computer to automatically contact external organizations without requiring human intervention.

[0760] One embodiment of this invention is a support system that allows travelers to enjoy their trips with peace of mind. This is achieved by using a server, terminals, and associated databases.

[0761] The server receives individual traveler information and preferences, and uses machine learning algorithms to generate information optimized for each traveler. This process makes it possible to suggest accessible accommodations, transportation options, and tourist destinations to travelers.

[0762] The device uses GPS technology to obtain the traveler's current location during their trip and provides geographical information received from a server in real time. The device is equipped with a voice assistant function that can provide traveler guidance information via voice and accept voice instructions from the traveler. This voice technology is often implemented using programming languages ​​such as Java or Python.

[0763] As a concrete example, a traveler using a wheelchair is given. When this traveler visits a barrier-free tourist destination, the voice assistant guides them to the most suitable route based on the latest barrier-free information retrieved from the server. In this way, the traveler can enjoy sightseeing stress-free.

[0764] An example of a prompt is, "Please suggest the best barrier-free route for a wheelchair user to enjoy sightseeing in Kyoto." By inputting such prompts into the AI ​​model, useful information can be obtained in real time.

[0765] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0766] Step 1:

[0767] The server receives individual information and travel preference information from the user. This includes data such as disability information and desired destinations entered by the user. User profile data is received as input, and registration of this data into the initial database is performed as output. Based on this registered data, the server starts a process of learning the user's needs using a machine learning model.

[0768] Step 2:

[0769] The server applies machine learning algorithms to generate lists of accommodations, transportation, and tourist destinations optimized for the user's preferences. It uses the training data obtained in Step 1 as input and generates a list of travel plans suitable for the user as output. Specifically, it utilizes data analysis and pattern recognition techniques to match user preferences with corresponding facility data and extract the best options.

[0770] Step 3:

[0771] The device uses GPS technology to determine the user's current location while traveling and transmits that location information to the server. The input is geographic location data acquired by the device. The output is the current location information sent to the server. Based on this, the server acquires geographic information in real time and prepares to provide the corresponding information to the device.

[0772] Step 4:

[0773] The server compares the acquired location information with the user's current location and provides the user with the optimal route and accessibility information in real time. The inputs are the location information obtained in step 3 and geographical information from the database. The output is guidance information provided via voice or visual means. Specifically, the server calculates an appropriate route based on the user's current location and transmits the information to the terminal through that route.

[0774] Step 5:

[0775] The device uses a voice assistant to convey guidance information from the server to the user. It can also accept voice commands from the user. Inputs include guidance information sent from the server and voice commands from the user. Outputs include voice guidance to the user and the collection of voice data as feedback. Specifically, speech synthesis technology is used to provide information in a way that is easy for the user to understand, and the device is prepared to recognize and process any further instructions.

[0776] 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.

[0777] This invention is a system designed to allow travelers to enjoy their trips with peace of mind. Its key feature is the use of an emotion engine to understand the traveler's emotional state and provide travel support accordingly. The system consists of a user terminal, a central server, an emotion engine, and a related database.

[0778] First, the user inputs information about their disability and travel preferences through their device. The device sends this information to a server, which stores it in a database and uses an AI algorithm to learn the user's needs. Here, the server understands what kind of support and environment the user desires and prepares to provide personalized travel support.

[0779] Based on the transmitted information, the server searches its database for information on barrier-free accommodations, transportation options, and tourist attractions, and generates a travel plan according to the user's learned preferences. The terminal displays this plan to the user, who can review it and customize it as needed.

[0780] During travel, the device continuously acquires the user's location information and monitors the user's emotional state through an emotion engine. Utilizing the device's sensors and microphone, it analyzes the user's emotions from facial expressions, tone of voice, and speech content, and based on this information, the server provides appropriate information. For example, if the emotion engine detects user stress, the server will guide the user to relaxation spots or places where they can rest.

[0781] Furthermore, in emergencies, the device immediately transmits the user's location and health information to the server. The server then contacts the nearest medical facility or support service, enabling a rapid response. This enhances safety and peace of mind.

[0782] The system further collects feedback from users who have completed their travel experiences within the community. The server stores data on travel experiences where users expressed particularly positive emotions and uses this data to suggest travel plans to other users with similar needs. This allows the entire system to be continuously improved by leveraging the information provided by the emotion engine, enabling the delivery of more personalized travel experiences.

[0783] As a concrete example, suppose a user visits a tourist destination and feels anxious due to changes in the weather or other factors. In this case, the emotion engine can detect that emotion, and the server can immediately provide information recommending tourist spots or evacuation locations that are appropriate for the situation, thereby supporting the user's sense of security.

[0784] The following describes the processing flow.

[0785] Step 1:

[0786] The user uses a terminal to enter information about their condition and travel preferences. The terminal then sends this information to the server.

[0787] Step 2:

[0788] The server uses an AI algorithm to analyze user needs based on the received user information and stores the results in a database.

[0789] Step 3:

[0790] The server searches the database for barrier-free accommodations, transportation options, and tourist attractions, and generates an optimal travel plan based on the user's preferences.

[0791] Step 4:

[0792] The generated travel plan is sent to the device, which then displays the plan to the user. The user reviews the plan and customizes it as needed.

[0793] Step 5:

[0794] During travel, the device acquires the user's location information in real time and sends it to the server. At the same time, the device's sensors and microphone are used by an emotion engine to analyze the user's facial expressions and tone of voice.

[0795] Step 6:

[0796] The emotion engine analyzes the user's emotional state, and if stress or anxiety is detected, the server immediately sends information about corresponding relaxation spots and safe spaces to the device.

[0797] Step 7:

[0798] The terminal receives information from the server and notifies the user, and provides guidance using a voice assistant, thereby quickly responding to the user's needs.

[0799] Step 8:

[0800] In an emergency, if a user uses the emergency contact function on their device, their location and health information will be sent to the server.

[0801] Step 9:

[0802] The server coordinates with the nearest medical facilities and support teams to provide a rapid response to users. The terminal provides users with appropriate measures and evacuation instructions based on the current situation.

[0803] Step 10:

[0804] After a trip, users share their experiences with the community via their devices. The server learns from this information and incorporates it into future travel suggestions. This improves the system's accuracy and personalization.

[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] To ensure travelers can enjoy their trips with peace of mind, it is necessary to provide information tailored to each traveler's individual circumstances and preferences. However, conventional systems have difficulty integrating traveler information such as disability information, preferences, emotional state, and emergency health status, making it challenging to provide optimal information in real time during a trip. This results in travelers being unable to receive the necessary support when they need it.

[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 traveler disability information and travel preference information and learning the information using machine learning technology; means for acquiring traveler location information and providing customized support information in real time; and means for monitoring the traveler's emotional state and providing information corresponding to that emotional state. This makes it possible to provide personalized information that meets the traveler's needs.

[0810] A "traveler" refers to an individual who uses the system while traveling, and is the target of support provided based on their disability information and preferences.

[0811] "Disability information" refers to information about a traveler's physical or mental limitations, and is used to optimize support during their trip.

[0812] "Travel preference information" refers to information about travelers' preferred activities, places they want to visit, budgets, etc., and is used to provide personalized travel experiences.

[0813] "Machine learning technology" refers to techniques that enable computers to learn from data and improve their performance in performing specific tasks.

[0814] "Location information" refers to data that indicates a traveler's current geographical location and is used for providing real-time information and responding to emergencies.

[0815] "Emotional state" refers to information that indicates the traveler's psychological or emotional condition, including stress and anxiety.

[0816] "Support information" refers to information about accommodations, tourist attractions, relaxation spots, etc., provided to travelers so that they can enjoy their trip with peace of mind.

[0817] An "emergency" refers to a situation in which a traveler faces a serious health or safety issue during their trip, requiring a swift response.

[0818] "Health information" refers to data about a traveler's physical health status and is used to share information with medical institutions as needed.

[0819] To implement this invention, it is necessary to organically link multiple components. Specifically, a user's terminal, a central server, an emotion engine for sentiment analysis, and an associated database system are required.

[0820] First, users input their travel preferences and disability information using their own devices (such as smartphones or tablets). These devices are equipped with sensor technology and voice assistant functions, allowing for easy input of this information via voice or touch.

[0821] Next, the terminal transmits the collected information to the server via a secure communication method. The server uses high-performance computing equipment and a database system, enabling it to quickly and securely store and manage user information. The database already contains pre-collected information on barrier-free facilities, services, and tourist destinations.

[0822] Based on this information, the server uses a generative AI model to learn the user's preferences and needs. The AI ​​model identifies patterns from a vast amount of data, including the user's past information and the preferences of similar users, and automatically generates the optimal travel plan. The following is an example of a prompt given to the AI ​​model:

[0823] "Please create a list of tourist spots that users would like to see."

[0824] "Please list the data items needed to generate personalized travel plans."

[0825] During travel, the device uses GPS and built-in sensors to acquire the user's location and emotional state in real time. When the emotion engine detects the user's stress or anxiety, it sends this information to a server, which then provides pre-prepared relaxation spots and sightseeing information. This process allows the user to feel more at ease while traveling.

[0826] Furthermore, in the event of an emergency, the device immediately sends data, including the user's health information, to a server, which automatically contacts the nearest medical facility or support service. This ensures a swift and appropriate emergency response.

[0827] This system utilizes advanced, data-driven technology to provide travelers with peace of mind and a fulfilling travel experience.

[0828] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0829] Step 1:

[0830] Users input travel preferences and disability information using their own devices. Specific input includes desired destinations, budgets, tourist attractions, and necessary support. The device collects this information, converts it into a digital format, and generates data packets to send to the server. The output data consists of the user's preferences and disability information, ready for transmission to the server.

[0831] Step 2:

[0832] The terminal transmits user preference and fault information to a central server using a secure protocol (e.g., HTTPS). This information is received by the server and stored in a database. The input is encoded user information data, and the output is data storage on the server side.

[0833] Step 3:

[0834] The server uses a generated AI model based on user information retrieved from the database to learn the user's individual needs. The AI ​​model analyzes relevant information and performs data calculations to extract preference patterns. The input consists of existing information from the database and newly received user information, and the output is a travel plan optimized for the user.

[0835] Step 4:

[0836] The server uses the data obtained as a result of training to select barrier-free facilities, transportation options, and recommended tourist destinations, and generates a detailed travel plan. This process employs data filtering and plan generation algorithms. The input is the learned preference patterns, and the output is specific travel plan information.

[0837] Step 5:

[0838] The terminal presents the generated travel plan to the user and provides an interface that allows the user to customize it. The user can review the travel plan here and make changes as needed. The input is travel plan data from the server, and the output is a customizable plan display for the user.

[0839] Step 6:

[0840] During travel, the device continuously monitors the user's location and emotional state in real time using its built-in GPS and sensors. The data collected by the sensors includes geographical location, voice tone, and facial expressions. This monitoring data is fed into an emotion engine, which analyzes it to detect the user's stress and anxiety. The output is an informational notification sent to the server based on the emotional state.

[0841] Step 7:

[0842] The server provides the user with appropriate actions based on information provided by the emotion engine. Here, it presents information on relaxation spots and new tourist destinations tailored to the user's current emotional state. The input is the emotion analysis result, and the output is the information displayed on the terminal.

[0843] Step 8:

[0844] In an emergency, the device will promptly transmit the user's health status data and location information to the server. The server will then receive this information and immediately begin the process of contacting support services. The input is user information in an emergency, and the output is the notification to support services.

[0845] Step 9:

[0846] After the trip ends, the device provides an interface for collecting user feedback on their travel experience. The server analyzes the collected feedback and improves the generated AI model to use in future travel planning. The input is user feedback information, and the output is the improved AI model.

[0847] (Application Example 2)

[0848] 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".

[0849] When travelers navigate different environments, their experience can be diminished if they are unable to cope with potential stressors or emergencies. Furthermore, there is a lack of resources to provide optimal travel experiences tailored to each traveler's emotional state. These challenges need to be addressed to enhance travel safety and satisfaction.

[0850] 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.

[0851] This invention includes a server that receives and learns information on a traveler's disability, travel preferences, and emotional state; a server that, based on the learned information, suggests barrier-free accommodations, transportation options, and tourist destinations, and guides the traveler to relaxation spots and resting places according to their emotional state; and a server that acquires the traveler's location information and emotional state during the trip and provides barrier-free information and emotionally appropriate information in real time. This makes it possible to provide travelers with an individualized and emotionally appropriate travel experience.

[0852] A "traveler" is someone who goes on a trip and needs support tailored to their experiences and emotional state during that trip.

[0853] "Disability information" refers to information about the physical or mental limitations that travelers have, and serves as the basis for providing accessibility considerations.

[0854] "Travel preference information" refers to information about travelers' preferences and tastes, and serves as a reference when creating personalized travel plans.

[0855] "Emotional state information" refers to information that indicates the psychological state of a traveler, and is used to provide emotionally tailored services in order to improve the quality of their travel experience.

[0856] "Means" refer to methods and devices that perform information processing or provide support to achieve an objective, and are elements that constitute a system.

[0857] "Barrier-free accommodations" are accommodations that are designed to be safe and accessible for travelers with disabilities.

[0858] "Transportation" refers to the vehicles and routes that travelers use to get around, and is a factor that directly impacts the comfort of the trip.

[0859] A "tourist destination" is a place that travelers visit and enjoy, and is part of a travel destination.

[0860] A "relaxation spot" is a place where travelers can relax and soothe their mind and body, and is suggested as a way to alleviate stress.

[0861] A "place where you can rest" is a place where travelers can take a temporary rest during their trip.

[0862] "Location information" refers to data that indicates a traveler's current location and is used for real-time guidance and support.

[0863] "Emotional monitoring" is a technology that observes and analyzes the emotional state of travelers in order to optimize their experience.

[0864] This invention provides a system to assist travelers. The system consists of a user terminal, a central server, an emotion engine, and a database associated with them. First, the traveler inputs disability information, travel preference information, and emotional state information through the terminal. The terminal sends this information to the server, which stores the information in a database and learns the traveler's needs using machine learning algorithms. In this process, the system understands what kind of support and environment the user needs and prepares to provide personalized travel support.

[0865] Based on the information it has learned, the server searches its database for information on barrier-free accommodations, transportation, and tourist attractions, and generates a travel plan that suggests relaxation spots and places to rest according to the user's emotional state. The terminal presents this plan to the user, who can then customize it to suit their needs.

[0866] During travel, the device continuously acquires the traveler's location information and monitors the traveler's emotional state through an emotion engine. The device's sensors and microphone analyze emotions based on facial expressions, tone of voice, and speech content, and transmit the results to a server. The server then guides the traveler with appropriate information and relaxation spots based on their emotional state. For example, if the traveler is feeling stressed, the server will immediately suggest a place to relax.

[0867] For example, if a traveler is distressed by rain while sightseeing, the device takes the rain situation into account and sends emotional data to the server. The server immediately provides information recommending nearby shelters or cafes. In this case, a prompt message to the generative AI model such as "Please list tourist spots where the user can relax. The user is currently feeling stressed because of the rain" can be used.

[0868] The hardware used will include mobile devices and personal assistant robots (e.g., Pepper, Nao) carried by travelers, while the software will consist of sentiment analysis libraries (OpenCV, DLib, etc.) and AI platforms (Google Cloud AI, etc.). This will enable the creation of services that meet the personalized needs of travelers and enhance their travel experience.

[0869] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0870] Step 1:

[0871] Users input information about their condition, travel preferences, and emotional state through their terminal. The input data is temporarily stored on the terminal and prepared for transmission to the server. The system is managed to ensure that user input is accurately collected and that necessary information is reliably transmitted to the server.

[0872] Step 2:

[0873] The terminal sends all collected user information to the server. The server analyzes the received data and stores it in the appropriate database. At this point, it builds foundational data for learning user needs and preferences using machine learning algorithms. The server verifies the reliability of the data and prepares it for analysis.

[0874] Step 3:

[0875] The server searches for barrier-free facilities, transportation options, and tourist attractions based on traveler information stored in the database. It also processes data to suggest relaxation spots and places to rest based on the traveler's emotional state. In this step, an AI algorithm is used to filter the information and generate a travel plan.

[0876] Step 4:

[0877] The generated travel plan is sent to the device and presented to the user. The user can review the plan and customize it as needed. At this stage, the user's feelings are reflected in the plan, allowing for personalized choices.

[0878] Step 5:

[0879] During travel, the device continuously acquires the user's location and emotional state. This is done using a GPS module and emotion analysis libraries (e.g., OpenCV, DLib). The acquired information is temporarily processed within the device before being sent to the server. Real-time information updates are performed based on the user's location and emotions.

[0880] Step 6:

[0881] The server analyzes the transmitted location information and emotional state, and generates appropriate suggestions based on the results. For example, if the user is feeling stressed, the server will recommend relaxation spots. In this process, it optimizes the information by utilizing prompts to the generative AI model, such as, "Please list places where the user can calm down. The user is currently feeling stressed because of the rain."

[0882] Step 7:

[0883] In emergencies, the device automatically transmits the user's location, health information, and emotional state to a server. Based on the received data, the server immediately contacts the necessary support organizations. This process ensures the user's safety and security.

[0884] Step 8:

[0885] After the trip ends, the server stores the traveler's feedback in a database, which is used to improve future travel suggestions. This information is used to further enhance and develop suggestions for other users.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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."

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] The following is further disclosed regarding the embodiments described above.

[0908] (Claim 1)

[0909] A means of receiving and learning about travelers' disability information and travel preferences,

[0910] Based on the learned information, a means of proposing barrier-free accommodations, transportation options, and tourist destinations,

[0911] A means of obtaining travelers' location information during their trip and providing real-time accessibility information,

[0912] In emergencies, a means of transmitting the traveler's location and health information and contacting assistance organizations,

[0913] A means of collecting traveler experience information and learning from it to make suggestions for future trips,

[0914] A system that includes this.

[0915] (Claim 2)

[0916] The system according to claim 1, characterized in that the location information acquisition means provides guidance information to travelers using a voice assistant function and receives voice instructions from travelers.

[0917] (Claim 3)

[0918] The system according to claim 1, characterized in that the emergency information transmission means monitors the health status of travelers and automatically contacts support organizations when an abnormality is detected.

[0919] "Example 1"

[0920] (Claim 1)

[0921] A means of receiving traveler disability information and travel preference information and learning using a generative AI model,

[0922] Based on the learned information, a means of proposing barrier-free accommodations, transportation options, and tourist destinations,

[0923] A means of obtaining travelers' location information during their trip and providing real-time accessibility information,

[0924] A means of providing travelers with information and instructions via voice assistants,

[0925] In an emergency, a means of transmitting the traveler's location and health status information and contacting aid organizations,

[0926] A method for collecting traveler experience information and using a generative AI model to learn for future travel suggestions,

[0927] A system that includes this.

[0928] (Claim 2)

[0929] The system according to claim 1, characterized in that the emergency information transmission means monitors the health status of travelers and automatically contacts support organizations when an abnormality is detected.

[0930] (Claim 3)

[0931] The system according to claim 1, characterized in that the traveler's experience information is posted to the community and reflected in future travel suggestions.

[0932] "Application Example 1"

[0933] (Claim 1)

[0934] A means of receiving individual traveler information and preference information and learning using machine learning,

[0935] Based on the learned information, a means of suggesting accessible accommodations, transportation, and destinations,

[0936] A means of obtaining a traveler's current location during their trip and providing real-time geographic information,

[0937] A means of providing travelers with audio guidance information while they are on the move and receiving audio instructions from them,

[0938] A means to transmit traveler status information in emergencies and automatically contact the appropriate agency,

[0939] A method for collecting traveler visit information and using machine learning to suggest future trips,

[0940] A system that includes this.

[0941] (Claim 2)

[0942] The system according to claim 1, characterized in that the voice guidance means proposes the optimal route for travelers and provides action support based on real-time updated information.

[0943] (Claim 3)

[0944] The system according to claim 1, characterized in that the automatic communication means continuously monitors the traveler's status and immediately notifies the appropriate agency when an abnormal situation is detected.

[0945] "Example 2 of combining an emotion engine"

[0946] (Claim 1)

[0947] A means of receiving traveler disability information and travel preference information, and learning from that information using machine learning technology,

[0948] A means for suggesting available facilities, means of transportation, and places to visit based on the learned information,

[0949] A means of acquiring travelers' location information and providing customized assistance information in real time,

[0950] A means of monitoring travelers' emotional states and providing information tailored to those emotions,

[0951] In emergencies, a means of transmitting the traveler's location and health information and contacting assistance organizations,

[0952] A means of collecting traveler experience information and improving machine learning models for future travel suggestions,

[0953] A system that includes this.

[0954] (Claim 2)

[0955] The system according to claim 1, characterized in that the location information acquisition means provides guidance information to travelers using a voice assistant function and receives voice instructions and feedback based on emotional states from travelers.

[0956] (Claim 3)

[0957] The system according to claim 1, characterized in that the emergency information transmission means monitors the traveler's health condition using sensor technology and automatically contacts a support organization when an abnormality is detected.

[0958] "Application example 2 when combining with an emotional engine"

[0959] (Claim 1)

[0960] A means of receiving and learning information about travelers' disabilities, travel preferences, and emotional states,

[0961] Based on the learned information, a means of suggesting barrier-free accommodations, transportation options, and tourist destinations, and guiding users to relaxation spots and places to rest according to their emotional state,

[0962] A means of acquiring travelers' location information and emotional state during their travels, and providing real-time accessibility information and emotionally-responsive information,

[0963] In emergencies, a means of transmitting the traveler's location, health information, and emotional state, and contacting assistance organizations,

[0964] A means of collecting traveler experience information, learning from it for future travel suggestions, and utilizing information based on emotions,

[0965] A system that includes this.

[0966] (Claim 2)

[0967] The system according to claim 1, characterized in that the location information acquisition means provides guidance information to travelers using a voice assistant function and an emotion monitoring function, receives voice instructions from travelers, and responds according to their emotions.

[0968] (Claim 3)

[0969] The system according to claim 1, characterized in that the emergency information transmission means monitors the health and emotional state of the traveler and automatically contacts a support organization when it detects an abnormality in the health or emotional state. [Explanation of Symbols]

[0970] 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 individual traveler information and preference information and learning using machine learning, Based on the learned information, a means of suggesting accessible accommodations, transportation, and destinations, A means of obtaining a traveler's current location during their trip and providing real-time geographic information, A means of providing travelers with audio guidance information while they are on the move and receiving audio instructions from them, A means to transmit traveler status information in emergencies and automatically contact the appropriate agency, A method for collecting traveler visit information and using machine learning to suggest future trips, A system that includes this.

2. The system according to claim 1, characterized in that the voice guidance means proposes the optimal route for travelers and provides action support based on information updated in real time.

3. The system according to claim 1, characterized in that the automatic communication means continuously monitors the traveler's status and immediately notifies the appropriate agency when it detects an abnormal situation.

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