system

Abstract

We provide the system. [Solution] An input method for the user to enter the purpose of their trip and the degree of their disability, A processing means that receives input data from a user and generates a travel plan that takes accessibility information into consideration, A control means that presents a generated travel plan to the user and performs the booking procedure based on the user's selection, A means of updating the database to collect user feedback after the trip and improve the accuracy of the information, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In order to solve the problems of insufficient information and lack of appropriate barrier-free information faced by travelers with disabilities when creating an appropriate travel plan according to their specific needs, it is necessary to improve the situation where conventional travel plans are not sufficiently considered for disabled people. The purpose of this invention is to provide a customizable travel guide according to the type and degree of disability, and to utilize the feedback after the trip to update information and improve accuracy, so as to provide a more appropriate and reassuring travel experience.

Means for Solving the Problems

[0005] This invention provides a travel plan optimized for the user by including an input means for the user to input the purpose of travel and the degree of their disability, and a processing means that receives data from the user and generates a travel plan that takes accessibility information into consideration. Furthermore, by including a control means that presents the generated travel plan to the user and performs various reservation procedures based on the user's selection, it is possible to carry out the entire process from itinerary construction to reservation in a consistent manner. In addition, by including an update means that collects user feedback after the end of the trip and updates the database to improve the accuracy of the information, the system provides a continuously learning system that reflects this feedback in the creation of the next plan. Moreover, by adjusting the algorithm based on user feedback and improving the accuracy of subsequent generation, it realizes an optimal travel plan tailored to individual disabilities.

[0006] "User" refers to a traveler with a disability who attempts to create a travel plan using the system.

[0007] "Input method" refers to the interface that users use to communicate information to the system regarding their travel purpose and the type and degree of their disability.

[0008] "Receiving means" refers to the function that allows the system to acquire information entered by the user.

[0009] "Accessibility information" refers to information necessary for travelers with disabilities to travel comfortably, and includes the availability and support of transportation, accommodation, and activities.

[0010] "Processing means" refers to an algorithm that analyzes received data and generates an optimal travel plan tailored to the user's needs.

[0011] "Control means" refers to a function that presents the generated travel plan to the user and manages the booking process based on the user's selection.

[0012] "Update mechanism" refers to a function that keeps the system's database up-to-date by reflecting user feedback after the trip has ended.

[0013] "Learning method" refers to the process of analyzing feedback information obtained from users to improve the system's plan generation algorithm. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

[0015] 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.

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

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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.

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

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (for example, hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention relates to a system for providing customized travel plans for travelers with disabilities. The following describes specific embodiments for carrying out the invention.

[0036] First, the user enters information about the degree of their disability, specific travel destinations, and desired activities using the input method on the device. This information includes the travel destination, desired travel dates and times, and any special considerations required.

[0037] The terminal receives information entered by the user and sends it to the server as a dataset. The server has a database containing accessibility information tailored to various types of disabilities, as well as data obtained from past user feedback.

[0038] The server uses AI algorithms to generate the optimal travel plan based on the received information. This takes into account factors such as transportation options, accessibility of accommodations, and activity information at the destination. In particular, it selects accessible spots and services according to the user's disability, creating a plan that best suits individual needs.

[0039] The created plan is sent back to the device and displayed for the user to review and select. After reviewing the plan, the user can choose a satisfactory option. This process ensures that transportation and accommodation bookings are made consistently.

[0040] After their trip, users provide feedback based on their actual experience. This feedback includes information on the actual availability of accessibility features and their satisfaction with the itinerary.

[0041] The device sends this feedback to the server. The server receives the feedback, updates its database, and incorporates it into future suggestions. This allows for continuous improvement of the quality of generated plans. Furthermore, by adjusting the algorithm based on the feedback, it ensures an optimized travel experience for each user.

[0042] For example, if a user using a wheelchair wants to visit a tourist attraction, the server will collect information on wheelchair-accessible transportation, hotels with barrier-free facilities, and accessible tourist spots at the destination, and then provide a plan. In this process, user feedback will be used to generate future plans, resulting in a more personalized travel experience.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user enters information such as their travel destination, desired date and time, and details of any problems into the terminal's input interface.

[0046] Step 2:

[0047] The terminal receives the information entered by the user, converts it into the appropriate data format, and prepares to send it to the server.

[0048] Step 3:

[0049] The server analyzes user information received from the terminal and retrieves relevant accessibility information from the database.

[0050] Step 4:

[0051] The server uses AI algorithms to generate travel plans that best suit the user's needs, taking into account the collected accessibility information.

[0052] Step 5:

[0053] The server sends the generated travel plan to the terminal so that the user can review it.

[0054] Step 6:

[0055] The terminal displays the travel plan received from the server on the user interface, allowing the user to check its contents.

[0056] Step 7:

[0057] The user reviews the displayed travel plans and selects the option they deem best.

[0058] Step 8:

[0059] The device receives the user's plan selection and sends that information back to the server.

[0060] Step 9:

[0061] The server automatically handles the booking process for transportation and accommodation based on the user's selections.

[0062] Step 10:

[0063] After the trip ends, users use their devices to provide feedback about their actual experience.

[0064] Step 11:

[0065] The device sends user feedback to the server.

[0066] Step 12:

[0067] The server saves the received feedback to a database and updates the information for use in future plan generation.

[0068] (Example 1)

[0069] 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."

[0070] For travelers with disabilities, efficiently providing customized travel plans based on available accessibility information is challenging. Furthermore, determining whether the provided plans fully meet individual needs is also a challenge. Additionally, the lack of effective means to incorporate collected feedback into future planning makes it difficult to continuously improve the quality of the travel experience.

[0071] 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.

[0072] In this invention, the server includes input means for the user to input their travel goals and the degree of their disability; calculation means for receiving the input information from the user and constructing a travel plan considering barrier-free information and data corresponding to the user's disability; and control means for generating an optimal travel plan using a generation AI model and presenting it to the user. This makes it possible to efficiently provide travelers with disabilities with personalized travel plans that meet their individual needs and to continuously improve the quality of the plans by utilizing the collected feedback.

[0073] "Input means" refers to a device or method that provides an interface for a user to input their travel goals and the degree of obstacles into the system.

[0074] "Calculation means" refers to a device or method that has the function of constructing a travel plan based on user input information, taking into account accessibility information and data tailored to disabilities.

[0075] "Control means" refers to a device or system that presents a generated travel plan to the user and adjusts and executes the necessary booking procedures based on the user's selection.

[0076] "Update mechanism" refers to a device or method that has the function of updating the database based on feedback collected from users after the end of their trip, thereby continuously improving the accuracy of the information and the quality of the service.

[0077] A "generative AI model" is an artificial intelligence algorithm or system that generates the optimal travel plan based on information provided by the user.

[0078] "Communication methods" refer to the technologies and methods used to send and receive generated travel plans and collected feedback between the user and the server.

[0079] This invention is a system that provides customized travel plans for travelers with disabilities, and its embodiments are described below.

[0080] First, the user uses the terminal to input information such as the degree of their disability, their travel destination, desired dates, and any special considerations they require. This input is primarily done through dedicated application software or a web browser. After inputting the information, the terminal organizes it into a dataset and sends it to the server using a security protocol.

[0081] The server generates the optimal travel plan using an AI model based on the received data. In this process, it references accessibility information stored in the database and past user feedback to perform calculations to create a plan tailored to the user's specific needs. This process is carried out by an AI algorithm implemented in Python. The server temporarily stores the plan provided to the user in JSON format.

[0082] The generated travel plan is sent from the server to the terminal and visually displayed on the terminal's user interface. Based on the displayed plan, the user can make selections and proceed with booking transportation and accommodation.

[0083] After the trip ends, users input feedback based on their actual experience into a device. This feedback includes aspects such as the availability of accessibility features and satisfaction with the plan. The device sends this feedback data to a server, which updates its database based on it, helping to improve the accuracy of the algorithm.

[0084] As a concrete example, if a wheelchair user wants to visit tourist attractions, a possible prompt would be, "Generate a barrier-free travel plan for Tokyo sightseeing for wheelchair users." This prompt is input into the server's AI model and serves as an instruction to generate a travel plan optimized for the user. This makes it possible to provide a more personalized travel experience.

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

[0086] Step 1:

[0087] The user uses the terminal's input interface to enter their travel destination, dates, degree of disability, and any special considerations required.

[0088] The input information is organized as a dataset within the device. The device then sends this organized data to the server via the HTTPS protocol, providing it as input for the initial dataset.

[0089] Step 2:

[0090] The server uses a generative AI model to build a travel plan based on the data received from the terminal.

[0091] Specifically, an AI algorithm implemented in Python compares the received data with accessibility information stored in a database to select the most suitable transportation, accommodation, and activities for the user. This generates a customized travel plan.

[0092] Step 3:

[0093] The server organizes the generated travel plan in JSON format and sends it to the terminal.

[0094] The device parses the received JSON data and displays it on the user interface for the user to visually confirm. Based on the displayed information, the user selects a travel plan and records that selection on the device.

[0095] Step 4:

[0096] After the user completes their trip, they use their device to enter feedback based on their actual travel experience.

[0097] This feedback is recorded as a dataset including the actual level of accessibility measures taken and satisfaction with the itinerary. The device then sends this feedback data to the server.

[0098] Step 5:

[0099] The server receives feedback from users and updates the database.

[0100] Specifically, the collected feedback will be stored in a database so that this new data is taken into consideration when generating future travel plans. The server will also adjust the AI ​​algorithm based on the feedback to improve the next plan, making it more personalized.

[0101] (Application Example 1)

[0102] 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."

[0103] For travelers with disabilities, a lack of accessibility information at their destinations and travel plans that don't suit their needs are major obstacles to enjoying their trips. Furthermore, traditional travel plans lack features to incorporate user feedback and satisfaction into future plans, making it difficult to improve the quality of the travel experience.

[0104] 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.

[0105] In this invention, the server includes input means for the user to input the purpose of the trip and the degree of any obstacles, display means for visually experiencing the travel plan in a virtual environment, and means for learning an algorithm based on user feedback and improving generation accuracy. This allows the user to visually confirm the destination and experience and adjust a more suitable travel plan in advance.

[0106] An "input method" is an interface that allows the user to input information about their travel purpose and the degree of their disability into the system.

[0107] A "processing device" is a device that receives input data from a user and has the function of processing the data in order to generate a travel plan that takes accessibility information into consideration.

[0108] A "control device" is a device that has the function of presenting the generated travel plan to the user and carrying out the booking procedure based on the user's selection.

[0109] "Display means" refers to a device or interface that allows users to visually experience a travel plan within a virtual environment.

[0110] The "update mechanism" refers to a function that collects user feedback after the trip is completed, updates the database based on that feedback, and improves the accuracy of the information.

[0111] A "learning tool" is a function that adjusts the travel plan generation algorithm based on user feedback to improve generation accuracy.

[0112] A "virtual reality device" is a device that provides users with a virtual environment and visually simulates a travel experience.

[0113] This invention realizes a system that generates customized travel plans for travelers with disabilities and delivers them in a virtual reality environment. Details are provided below.

[0114] First, the user enters information on their device, such as their travel destination, preferred dates and times, degree of disability, and any special considerations. The device then sends this information to the server. The hardware used at this stage includes input devices for the user to enter information, such as tablets and smartphones.

[0115] Based on the received information, the server generates an optimal travel plan using a generative AI model. This involves data processing that considers factors such as transportation options, accommodation accessibility, and accessible activities at the destination. The server's software includes a database management system and AI algorithms, which work together to perform data calculations.

[0116] The generated travel plans are provided to the user via a virtual reality device. Using smart glasses or a head-mounted display, the user can visually experience virtual scenery of their travel destination. This allows the user to simulate the trip in advance and select a plan that suits their needs.

[0117] After a trip ends, users provide feedback based on their experience. This feedback is sent back to the server from the device, which updates the database and incorporates it into generating future travel plans. This allows for continuous improvement of service quality. The feedback is used to train the generative AI model's algorithms, ultimately leading to the provision of more suitable travel experiences for users.

[0118] For example, if a wheelchair user wants to visit a specific tourist destination, the server will generate a plan that includes accessibility information suitable for that user and allow them to experience it in virtual reality. An example of a prompt would be, "Generate a travel plan combining information on accessible tourist spots and accommodations for a wheelchair user planning a visit to Kyoto."

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

[0120] Step 1:

[0121] Users enter travel information on their devices. This information includes the travel destination, preferred dates and times, and the degree of any disabilities. This data is then sent from the device to the server as basic data for creating a travel plan.

[0122] Step 2:

[0123] The server searches its database for relevant accessibility information based on input data received from the terminal. Specifically, it uses an AI algorithm to process information on accessible transportation, accommodations, and tourist attractions around the destination to generate an optimal travel plan. This data processing and calculation results in a plan tailored to individual needs.

[0124] Step 3:

[0125] The generated travel plan is converted into a virtual reality-compatible format and sent to the device. The device receives the plan and presents it to the user through a VR display device (e.g., a head-mounted display). This allows the user to have a virtual travel experience in advance and to visually confirm the plan.

[0126] Step 4:

[0127] After the trip ends, users enter feedback about their travel experience via their device. This feedback includes actual accessibility experiences and evaluations of facilities. The feedback data is then sent back to the server.

[0128] Step 5:

[0129] The server analyzes the received feedback and updates the database information. Simultaneously, it uses a generative AI model to train its algorithm and improve the accuracy of future travel plan generation. This data processing enables higher-quality suggestions for subsequent plan generation.

[0130] Step 6:

[0131] As an example of prompt generation, the command "Generate a travel plan combining information on barrier-free tourist attractions and accommodations for a wheelchair user planning a visit to Kyoto" is used. Based on this, the server collects and analyzes the appropriate information.

[0132] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0133] This invention relates to a system that provides more personalized travel plans for travelers with disabilities. In particular, it improves the quality of the travel experience by combining it with an emotion engine that can recognize the user's emotions and respond accordingly.

[0134] First, the user uses the terminal's input method to enter information such as the purpose of their trip, the degree of their disability, the places they want to visit, and their preferred dates and times. This information becomes an important element in plan generation.

[0135] The terminal receives information entered by the user and sends it to the server as structured data. Here, the emotion engine interprets the user's emotions from the input and infers their emotional state.

[0136] The server retrieves the most relevant accessibility information from the database based on the received user information and the emotional state recognized by the emotion engine. This includes feedback from past travelers and the latest facility information.

[0137] Next, the server uses an AI algorithm to create a travel plan. During this process, the user's emotional state is taken into consideration, and adjustments are made to select a more comfortable and satisfying itinerary. The plan includes barrier-free transportation and accommodation, and the activities are also tailored accordingly.

[0138] The created plan is sent to the device and displayed for the user to review. The user can then review the presented plan and choose the option that best suits their needs.

[0139] The terminal receives the user's selection and sends that information back to the server. The server then processes the necessary reservations based on the selection. Even during cancellations or changes, the emotion engine supports appropriate responses, enabling more flexible plan modifications.

[0140] Finally, after completing the trip, the user enters their thoughts and opinions about the experience as feedback into the device. The device sends this data to the server, and the emotion engine also analyzes the emotions included in the feedback. This data is used to improve the plan generation algorithm for future trips, updating the entire system to continuously improve the accuracy of the plans and the ability to respond to emotions.

[0141] For example, if the system recognizes that a user is prone to stress, it can generate a plan that prioritizes activities that help them relax, such as shortening travel time. In this way, the goal is to maximize the user experience by working in conjunction with the emotion engine.

[0142] The following describes the processing flow.

[0143] Step 1:

[0144] Users enter details such as their travel destination, dates, degree of disability, and desired activities using their own devices. This information also includes the purpose of the trip and any individual assistance needed.

[0145] Step 2:

[0146] The terminal collects data entered by the user, organizes that information, and converts it into a format for transmission to the server.

[0147] Step 3:

[0148] The server analyzes user data received from the terminal and uses an emotion engine to process and identify the user's emotional state from the input text.

[0149] Step 4:

[0150] The server searches the database for relevant accessibility information and past feedback information based on the user's emotional state and input information.

[0151] Step 5:

[0152] The server uses AI algorithms to generate customized travel plans that take into account the user's emotional state. This includes available accessibility features, accessible transportation options, and recommended activities.

[0153] Step 6:

[0154] The server sends the generated travel plan to the terminal, allowing the user to review and select it.

[0155] Step 7:

[0156] The terminal displays the plan received from the server to the user, allowing them to view the plan details. The user reviews the plan and selects the one that best suits their needs.

[0157] Step 8:

[0158] Based on their chosen travel plan, users make adjustments as needed to finalize their plan.

[0159] Step 9:

[0160] The device sends the user's confirmed plan to the server and initiates the reservation process based on that information.

[0161] Step 10:

[0162] The server completes the reservation process and gathers the necessary information to execute the entire plan. It also uses an emotion engine to respond flexibly when communication with the user is required.

[0163] Step 11:

[0164] After the trip ends, users provide feedback via their device, including comments about their feelings.

[0165] Step 12:

[0166] The device sends feedback data to the server, and the emotion engine analyzes this feedback to gain insights into the emotional state.

[0167] Step 13:

[0168] The server records the feedback in a database and adjusts the algorithm to use it for future plan generation. Through learning by the emotion engine, its planning capabilities improve for subsequent uses.

[0169] (Example 2)

[0170] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0171] This invention relates to a method for providing personalized travel plans to travelers with disabilities, taking into account their individual emotional states. Conventional travel plans have struggled to adequately reflect the individual needs and emotional states of users, resulting in poor satisfaction. In particular, many plans do not properly incorporate accessibility information that is crucial for travelers with disabilities, making it difficult to provide a safe and satisfying travel experience.

[0172] 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.

[0173] In this invention, the server includes means for receiving information from the user and analyzing the emotional state using machine learning; a processing function for creating a travel schedule that takes accessibility information into consideration using generative AI based on the emotional state and related information; and a control function for presenting the created travel schedule to the user and automatically making reservations, including transportation and accommodation, based on the user's selection. This enables the creation of personalized travel plans that more accurately reflect the user's emotions and individual needs, and allows for flexible responses to changes in plans at any time.

[0174] An "input function" refers to a device or software that allows users to input information about their travel purpose and physical limitations.

[0175] "Information" refers to data provided by the user, including the purpose of travel, the degree of disability, and preferred dates and times.

[0176] "Emotional state" refers to the psychological situation analyzed based on user input information and the emotions reflected in the feedback.

[0177] "Machine learning" is a technology that allows computers to learn patterns and rules from data and improve the algorithms necessary for optimizing travel plans.

[0178] "Generative AI" refers to artificial intelligence that uses machine learning techniques to automatically create personalized travel plans based on emotional states and user information.

[0179] "Accessibility information" refers to data that includes information on the convenience of transportation and facilities necessary for travelers with disabilities to enjoy their trip safely and comfortably.

[0180] "Processing function" refers to the system's ability to automatically generate a travel plan based on the input information and emotional state.

[0181] The "control function" refers to a system feature that automatically handles booking procedures and manages the execution of a travel plan based on the user's selected travel plan.

[0182] The "update function" is a feature that uses user feedback obtained after a trip to update the system's overall information resources and improve the accuracy of the algorithms.

[0183] "Experience feedback" refers to evaluations of opinions and feelings provided by users after a trip, and this data is useful for creating future travel plans.

[0184] The system of the present invention aims to provide personalized travel plans for travelers with disabilities, taking into account the emotional state of each user. Its embodiments are described in detail below.

[0185] The device features an input function for users to enter travel information. This input function allows users to enter details such as the purpose of the trip, the degree of any disabilities, places they wish to visit, and preferred dates and times. This information is crucial data for operating the emotion engine.

[0186] The server uses information received from the terminal to perform sentiment analysis through machine learning. This utilizes natural language processing technology to infer emotions from the user's input. Specifically, it determines the positive or negative nature of the emotion, as well as levels of tension and anticipation, based on the user's expressions and keywords.

[0187] Next, the server uses a generative AI model to generate the optimal travel plan based on the results of the sentiment analysis. This model extracts relevant information from a database that includes accessibility information and personalizes activities, transportation, and accommodations to match the user's emotions.

[0188] The server sends the generated plan back to the terminal, where the user reviews and selects it. Based on the selected plan, the server automatically processes transportation and accommodation reservations, providing an interface that allows for easy modification using drag-and-drop or click operations as needed. This process also integrates with external reservation systems via API connections.

[0189] After the trip is complete, the user enters feedback into their device. This feedback is then sent back to the server and analyzed by the sentiment engine. This information is used as data to improve the algorithm for generating future travel plans.

[0190] For example, if a user inputs an intention such as "I want to relax" or "I want to reduce stress," the AI ​​can be prompted with phrases like "Generate a travel plan that takes the user's emotional state into account" or "How can we use accessibility information and an emotion engine to provide a personalized plan for travelers with disabilities?" This allows the AI ​​to derive more suitable suggestions.

[0191] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0192] Step 1:

[0193] Users use their devices to input information such as the purpose of their trip, the degree of their disability, places they want to visit, and their preferred dates and times. This input information serves as the starting point for data processing throughout the system. The input data is then structured into keywords necessary for personalizing the trip.

[0194] Step 2:

[0195] The terminal sends the data entered by the user to the server as structured data. Specifically, this involves securely and efficiently transmitting information using a data communication protocol. At this stage, the entered information is converted so that it can be stored in a database.

[0196] Step 3:

[0197] The server activates the emotion engine based on the received data. The emotion engine uses natural language processing algorithms to analyze the user's input and infer their emotional state. For example, it extracts emotional keywords such as "excitement" or "anxiety" and identifies the corresponding emotional state. This analysis outputs the emotional state, which is then used in the next process.

[0198] Step 4:

[0199] The server utilizes a generative AI model based on emotional state and user information to generate the optimal travel plan. Here, accessibility information is retrieved from the database, and data processing is performed to select tourist destinations and activities that meet the user's needs. Specifically, plans are generated by referencing past feedback and using plans provided to users with similar emotional states as a reference.

[0200] Step 5:

[0201] The server sends the generated travel plans to the terminal. The terminal visually presents these to the user, allowing them to select their preferred plan. The input here is a list of generated plans, and the output is the specific plan selected by the user. The user-initiated interface is designed to be intuitively understandable.

[0202] Step 6:

[0203] The terminal receives the user's selection and sends that information back to the server. The server, in conjunction with the reservation management system, automatically executes the reservation process based on the selected plan. At this point, the input is the user's selection information, and the output is the confirmed reservation information. This process is carried out via API calls to an external system.

[0204] Step 7:

[0205] After the trip is complete, the user enters feedback about the experience into a terminal. The entered feedback is sent from the terminal to the server. The server uses the emotion engine again to analyze the emotions in the feedback. This analysis result is later stored in a database and used to improve future plan generation algorithms. Through the processing of feedback, the system is constantly updated, enabling it to provide more accurate plans.

[0206] (Application Example 2)

[0207] 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".

[0208] In recent years, there has been a growing demand for technologies that enhance the travel experience for travelers with disabilities. However, conventional systems are insufficient in suggesting personalized travel plans and relevant content that take user emotions into account. As a result, traveler satisfaction is low, and it is difficult to achieve a comfortable travel experience.

[0209] 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.

[0210] In this invention, the server includes an analysis means for receiving input data from the user and analyzing their emotions in real time; a processing means for generating a travel plan that takes accessibility information into consideration based on the emotion analysis results; and a control means for presenting content related to the generated travel plan to the user and performing a reservation procedure based on the user's selection. This makes it possible to provide travelers with disabilities with an optimal travel plan and related content that is tailored to their emotions.

[0211] The "analysis method for analyzing user emotions" is a function that grasps the user's emotional state in real time based on input data and provides information necessary for adjusting travel plans.

[0212] The "processing method for generating travel plans that take accessibility information into consideration" is a function that, based on sentiment analysis and various data, selects transportation methods, accommodations, and tourist facilities that can be comfortably used by travelers with disabilities, and then constructs a travel plan.

[0213] "A control means for presenting content related to the generated travel plan to the user and performing booking procedures" refers to a function that presents the generated travel plan to the user visually or audibly and performs bookings and arrangements based on the user's selections.

[0214] "An update mechanism to collect user feedback and update the database to improve the accuracy of information" refers to a function that collects user feedback and opinions after a trip, updates the information in the database based on this feedback, and improves the accuracy of generating future travel plans.

[0215] This invention aims to construct a system that provides personalized travel plans and content to travelers with disabilities using emotion analysis. The system is primarily based on data processing and communication between three parties: a terminal, a server, and the user.

[0216] The terminal receives input information from the user, such as the purpose of travel, the degree of disability, and desired destinations, through an application installed on a device like a smartphone or head-mounted display. This information is crucial data for real-time sentiment analysis. The terminal uses the Emotion API to read emotions from the user's facial expressions and voice, and sends this data to the server in a structured format.

[0217] On the server, an analysis tool identifies emotions based on the received data, and the analysis results are used to create a travel plan. Past feedback and the latest information on accessibility are retrieved from the database. This information is processed by an AI algorithm (using TENSORFLOW®) to automatically generate a travel plan optimized for the user's emotions and situation. This plan includes transportation, accommodation, and relaxing activities tailored to the user's condition and requests.

[0218] The user visually reviews the suggested travel plan via their device and sends their selected options back to the server. The server then flexibly handles the necessary booking procedures based on this selection. At the end of the trip, user feedback is collected, and emotional information is analyzed again using the Emotion API. This information is used to update the database to improve the accuracy of future plan generation.

[0219] For example, if a user is looking for a relaxing travel destination, the system will recognize the user's emotion as "relaxation" and then provide information about natural tourist destinations. Such a system is designed to allow users to enjoy a more personalized travel experience.

[0220] Example prompt for a generative AI model: "Please advise on what kind of tourist information and content should be provided when a user is feeling stressed."

[0221] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0222] Step 1:

[0223] The user uses a terminal to input the purpose of their trip, the degree of their disability, desired destinations, and preferred dates and times. The terminal receives this user input as structured data and sends it to the server. The input includes text and voice data, resulting in structured data that is sent to the server as output.

[0224] Step 2:

[0225] The server receives structured data sent from the terminal and analyzes the user's emotions in real time using the Emotion API. This analysis determines the user's emotional state, and as a result, data indicating the emotion is generated. The input is structured data, and the output is the analyzed emotional state data.

[0226] Step 3:

[0227] The server retrieves relevant accessibility information from the database based on the sentiment analysis results. Here, SQL queries are used to search the database and extract information suitable for travelers with disabilities. The input is sentiment state data, and the output is accessibility information.

[0228] Step 4:

[0229] The server generates an optimal travel plan using an AI algorithm (TensorFlow) based on the sentiment analysis results and acquired accessibility information. Sentiment data and accessibility information are used for data calculations, and a customized travel plan is obtained as output.

[0230] Step 5:

[0231] The terminal visually displays a travel plan transmitted from the server to the user. The user reviews the presented plan and makes a decision. The input is a customized travel plan, and the output is the user's selection.

[0232] Step 6:

[0233] The terminal, upon receiving the user's selection, sends that information back to the server and requests the reservation process. The server then works in conjunction with the reservation system to proceed with registration and arrangements. The input is the user's selection, and the output is a reservation completion confirmation.

[0234] Step 7:

[0235] After completing their trip, the user enters feedback about their experience into their device. The device sends this information to a server, which then uses the Emotion API again to analyze the emotional information. The input is the user's feedback, and the output is the emotional analysis data.

[0236] Step 8:

[0237] The server updates the database based on feedback information and stores data to be used in future plan generation. Data processing learns from newly acquired information and contributes to improving the algorithm. The input is feedback data, and the output is the updated database.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] [Second Embodiment]

[0242] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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).

[0248] 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.

[0249] 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.

[0250] 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.

[0251] 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.

[0252] 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.

[0253] 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".

[0254] This invention relates to a system for providing customized travel plans for travelers with disabilities. The following describes specific embodiments for carrying out the invention.

[0255] First, the user enters information about the degree of their disability, specific travel destinations, and desired activities using the input method on the device. This information includes the travel destination, desired travel dates and times, and any special considerations required.

[0256] The terminal receives information entered by the user and sends it to the server as a dataset. The server has a database containing accessibility information tailored to various types of disabilities, as well as data obtained from past user feedback.

[0257] The server uses AI algorithms to generate the optimal travel plan based on the received information. This takes into account factors such as transportation options, accessibility of accommodations, and activity information at the destination. In particular, it selects accessible spots and services according to the user's disability, creating a plan that best suits individual needs.

[0258] The created plan is sent back to the device and displayed for the user to review and select. After reviewing the plan, the user can choose a satisfactory option. This process ensures that transportation and accommodation bookings are made consistently.

[0259] After their trip, users provide feedback based on their actual experience. This feedback includes information on the actual availability of accessibility features and their satisfaction with the itinerary.

[0260] The device sends this feedback to the server. The server receives the feedback, updates its database, and incorporates it into future suggestions. This allows for continuous improvement of the quality of generated plans. Furthermore, by adjusting the algorithm based on the feedback, it ensures an optimized travel experience for each user.

[0261] For example, if a user using a wheelchair wants to visit a tourist attraction, the server will collect information on wheelchair-accessible transportation, hotels with barrier-free facilities, and accessible tourist spots at the destination, and then provide a plan. In this process, user feedback will be used to generate future plans, resulting in a more personalized travel experience.

[0262] The following describes the processing flow.

[0263] Step 1:

[0264] The user enters information such as their travel destination, desired date and time, and details of any problems into the terminal's input interface.

[0265] Step 2:

[0266] The terminal receives the information entered by the user, converts it into the appropriate data format, and prepares to send it to the server.

[0267] Step 3:

[0268] The server analyzes user information received from the terminal and retrieves relevant accessibility information from the database.

[0269] Step 4:

[0270] The server uses AI algorithms to generate travel plans that best suit the user's needs, taking into account the collected accessibility information.

[0271] Step 5:

[0272] The server sends the generated travel plan to the terminal so that the user can review it.

[0273] Step 6:

[0274] The terminal displays the travel plan received from the server on the user interface, allowing the user to check its contents.

[0275] Step 7:

[0276] The user reviews the displayed travel plans and selects the option they deem best.

[0277] Step 8:

[0278] The terminal receives the user's plan selection and returns the information to the server.

[0279] Step 9:

[0280] Based on the user's selection, the server automatically performs reservation procedures for transportation means and accommodation facilities.

[0281] Step 10:

[0282] After the trip ends, the user uses the terminal to input feedback about the actual experience.

[0283] Step 11:

[0284] The terminal sends the feedback from the user to the server.

[0285] Step 12:

[0286] The server saves the received feedback in the database and updates the information for utilization during the next plan generation.

[0287] (Example 1)

[0288] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0289] For travelers with disabilities, it is difficult to efficiently provide a customized travel plan based on available barrier-free information. Also, it is an issue to determine whether the provided plan fully meets individual needs. Furthermore, since there is a lack of means to effectively reflect the collected feedback in subsequent trip planning, it is difficult to continuously improve the quality of the travel experience.

[0290] 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.

[0291] In this invention, the server includes input means for the user to input their travel goals and the degree of their disability; calculation means for receiving the input information from the user and constructing a travel plan considering barrier-free information and data corresponding to the user's disability; and control means for generating an optimal travel plan using a generation AI model and presenting it to the user. This makes it possible to efficiently provide travelers with disabilities with personalized travel plans that meet their individual needs and to continuously improve the quality of the plans by utilizing the collected feedback.

[0292] "Input means" refers to a device or method that provides an interface for a user to input their travel goals and the degree of obstacles into the system.

[0293] "Calculation means" refers to a device or method that has the function of constructing a travel plan based on user input information, taking into account accessibility information and data corresponding to disabilities.

[0294] "Control means" refers to a device or system that presents a generated travel plan to the user and adjusts and executes the necessary booking procedures based on the user's selection.

[0295] "Update mechanism" refers to a device or method that has the function of updating the database based on feedback collected from users after the end of their trip, thereby continuously improving the accuracy of the information and the quality of the service.

[0296] A "generative AI model" is an artificial intelligence algorithm or system that generates the optimal travel plan based on information provided by the user.

[0297] "Communication methods" refer to the technologies and methods used to send and receive generated travel plans and collected feedback between the user and the server.

[0298] This invention is a system that provides customized travel plans for travelers with disabilities, and its embodiments are described below.

[0299] First, the user uses the terminal to input information such as the degree of their disability, their travel destination, desired dates, and any special considerations they require. This input is primarily done through dedicated application software or a web browser. After inputting the information, the terminal organizes it into a dataset and sends it to the server using a security protocol.

[0300] The server generates the optimal travel plan using an AI model based on the received data. In this process, it references accessibility information stored in the database and past user feedback to perform calculations to create a plan tailored to the user's specific needs. This process is carried out by an AI algorithm implemented in Python. The server temporarily stores the plan provided to the user in JSON format.

[0301] The generated travel plan is sent from the server to the terminal and visually displayed on the terminal's user interface. Based on the displayed plan, the user can make selections and proceed with booking transportation and accommodation.

[0302] After the trip ends, users input feedback based on their actual experience into a device. This feedback includes aspects such as the availability of accessibility features and satisfaction with the plan. The device sends this feedback data to a server, which updates its database based on it, helping to improve the accuracy of the algorithm.

[0303] As a specific example, when a user using a wheelchair wants to visit a tourist attraction, an example of a prompt sentence is "Please generate a barrier-free travel plan for Tokyo tourism for wheelchair users." This prompt is input into the server's generative AI model and serves as an instruction to generate a travel plan optimized for the user. This makes it possible to provide a more personalized travel experience.

[0304] The flow of the specific process in Example 1 will be described using FIG. 11.

[0305] Step 1:

[0306] The user uses the input interface of the terminal to input the destination of the trip, the schedule, the degree of disability, and items that require special consideration.

[0307] The input information is organized as a dataset in the terminal. The terminal transmits this organized data to the server via the HTTPS protocol, providing the input as an initial dataset.

[0308] Step 2:

[0309] Based on the data received from the terminal, the server utilizes the generative AI model to construct a travel plan.

[0310] Specifically, an AI algorithm implemented in Python compares the received data with the barrier-free information stored in the database and selects the most suitable means of transportation, accommodation, and activities for the user. Thereby, a customized travel plan is generated.

[0311] Step 3:

[0312] The server organizes the generated travel plan in JSON format and transmits it to the terminal.

[0313] The device parses the received JSON data and displays it on the user interface for the user to visually confirm. Based on the displayed information, the user selects a travel plan and records that selection on the device.

[0314] Step 4:

[0315] After the user completes their trip, they use their device to enter feedback based on their actual travel experience.

[0316] This feedback is recorded as a dataset including the actual level of accessibility measures taken and satisfaction with the itinerary. The device sends this feedback data to the server.

[0317] Step 5:

[0318] The server receives feedback from users and updates the database.

[0319] Specifically, the collected feedback will be stored in a database so that this new data is taken into consideration when generating future travel plans. The server will also adjust the AI ​​algorithm based on the feedback to improve the next plan, making it more personalized.

[0320] (Application Example 1)

[0321] 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."

[0322] For travelers with disabilities, a lack of accessibility information at their destinations and travel plans that don't suit their needs are major obstacles to enjoying their trips. Furthermore, traditional travel plans lack features to incorporate user feedback and satisfaction into future plans, making it difficult to improve the quality of the travel experience.

[0323] 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.

[0324] In this invention, the server includes input means for the user to input the purpose of the trip and the degree of any obstacles, display means for visually experiencing the travel plan in a virtual environment, and means for learning an algorithm based on user feedback and improving generation accuracy. This allows the user to visually confirm the destination and experience and adjust a more suitable travel plan in advance.

[0325] An "input method" is an interface that allows the user to input information about their travel purpose and the degree of their disability into the system.

[0326] A "processing means" is a device that receives input data from a user and has the function of processing the data in order to generate a travel plan that takes accessibility information into consideration.

[0327] A "control device" is a device that has the function of presenting the generated travel plan to the user and carrying out the booking procedure based on the user's selection.

[0328] "Display means" refers to a device or interface that allows users to visually experience a travel plan within a virtual environment.

[0329] The "update mechanism" refers to a function that collects user feedback after the trip is completed, updates the database based on that feedback, and improves the accuracy of the information.

[0330] A "learning tool" is a function that adjusts the travel plan generation algorithm based on user feedback to improve generation accuracy.

[0331] A "virtual reality device" is a device that provides users with a virtual environment and visually simulates a travel experience.

[0332] This invention realizes a system that generates customized travel plans for travelers with disabilities and delivers them in a virtual reality environment. The details are as follows.

[0333] First, the user enters information on their device, such as their travel destination, preferred dates and times, degree of disability, and any special considerations. The device then sends this information to the server. The hardware used at this stage includes input devices for the user to enter information, such as tablets and smartphones.

[0334] Based on the received information, the server generates an optimal travel plan using a generative AI model. This involves data processing that considers factors such as transportation options, accommodation accessibility, and accessible activities at the destination. The server's software includes a database management system and AI algorithms, which work together to perform data calculations.

[0335] The generated travel plans are provided to the user via a virtual reality device. Using smart glasses or a head-mounted display, the user can visually experience virtual scenery of their travel destination. This allows the user to simulate the trip in advance and select a plan that suits their needs.

[0336] After a trip ends, users provide feedback based on their experience. This feedback is sent back to the server from the device, which updates the database and incorporates it into generating future travel plans. This allows for continuous improvement of service quality. The feedback is used to train the generative AI model's algorithms, ultimately leading to the provision of more suitable travel experiences for users.

[0337] For example, if a wheelchair user wants to visit a specific tourist destination, the server will generate a plan that includes accessibility information suitable for that user and allow them to experience it in virtual reality. An example of a prompt would be, "Generate a travel plan combining information on accessible tourist spots and accommodations for a wheelchair user planning a visit to Kyoto."

[0338] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0339] Step 1:

[0340] Users enter travel information on their devices. This information includes the travel destination, preferred dates and times, and the degree of any disabilities. This data is then sent from the device to the server as basic data for creating a travel plan.

[0341] Step 2:

[0342] The server searches its database for relevant accessibility information based on input data received from the terminal. Specifically, it uses an AI algorithm to process information on accessible transportation, accommodations, and tourist attractions around the destination to generate an optimal travel plan. This data processing and calculation results in a plan tailored to individual needs.

[0343] Step 3:

[0344] The generated travel plan is converted into a virtual reality-compatible format and sent to the device. The device receives the plan and presents it to the user through a VR display device (e.g., a head-mounted display). This allows the user to have a virtual travel experience in advance and to visually confirm the plan.

[0345] Step 4:

[0346] After the trip ends, users enter feedback about their travel experience via their device. This feedback includes actual accessibility experiences and evaluations of facilities. The feedback data is then sent back to the server.

[0347] Step 5:

[0348] The server analyzes the received feedback and updates the database information. Simultaneously, it uses a generative AI model to train its algorithm and improve the accuracy of future travel plan generation. This data processing enables higher-quality suggestions for subsequent plan generation.

[0349] Step 6:

[0350] As an example of prompt generation, the command "Generate a travel plan combining information on barrier-free tourist attractions and accommodations for a wheelchair user planning a visit to Kyoto" is used. Based on this, the server collects and analyzes the appropriate information.

[0351] 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.

[0352] This invention relates to a system that provides more personalized travel plans for travelers with disabilities. In particular, it improves the quality of the travel experience by combining it with an emotion engine that can recognize the user's emotions and respond accordingly.

[0353] First, the user uses the terminal's input method to enter information such as the purpose of their trip, the degree of their disability, the places they want to visit, and their preferred dates and times. This information becomes an important element in plan generation.

[0354] The terminal receives information entered by the user and sends it to the server as structured data. Here, the emotion engine interprets the user's emotions from the input and infers their emotional state.

[0355] The server retrieves the most relevant accessibility information from the database based on the received user information and the emotional state recognized by the emotion engine. This includes feedback from past travelers and the latest facility information.

[0356] Next, the server uses an AI algorithm to create a travel plan. During this process, the user's emotional state is taken into consideration, and adjustments are made to select a more comfortable and satisfying itinerary. The plan includes barrier-free transportation and accommodation, and the activities are also tailored accordingly.

[0357] The created plan is sent to the device and displayed for the user to review. The user can then review the presented plan and choose the option that best suits their needs.

[0358] The terminal receives the user's selection and sends that information back to the server. The server then processes the necessary reservations based on the selection. Even during cancellations or changes, the emotion engine supports appropriate responses, enabling more flexible plan modifications.

[0359] Finally, after completing the trip, the user enters their thoughts and opinions about the experience as feedback into the device. The device sends this data to the server, and the emotion engine also analyzes the emotions included in the feedback. This data is used to improve the plan generation algorithm for future trips, updating the entire system to continuously improve the accuracy of the plans and the ability to respond to emotions.

[0360] For example, if the system recognizes that a user is prone to stress, it can generate a plan that prioritizes activities that help them relax, such as shortening travel time. In this way, the goal is to maximize the user experience by working in conjunction with the emotion engine.

[0361] The following describes the processing flow.

[0362] Step 1:

[0363] Users enter details such as their travel destination, dates, degree of disability, and desired activities using their own devices. This information also includes the purpose of the trip and any individual assistance needed.

[0364] Step 2:

[0365] The terminal collects data entered by the user, organizes that information, and converts it into a format for transmission to the server.

[0366] Step 3:

[0367] The server analyzes user data received from the terminal and uses an emotion engine to process and identify the user's emotional state from the input text.

[0368] Step 4:

[0369] The server searches the database for relevant accessibility information and past feedback information based on the user's emotional state and input information.

[0370] Step 5:

[0371] The server uses AI algorithms to generate customized travel plans that take into account the user's emotional state. This includes available accessibility features, accessible transportation options, and recommended activities.

[0372] Step 6:

[0373] The server sends the generated travel plan to the terminal, allowing the user to review and select it.

[0374] Step 7:

[0375] The terminal displays the plan received from the server to the user, allowing them to view the plan details. The user reviews the plan and selects the one that best suits their needs.

[0376] Step 8:

[0377] Based on their chosen travel plan, users make adjustments as needed to finalize their plan.

[0378] Step 9:

[0379] The device sends the user's confirmed plan to the server and initiates the reservation process based on that information.

[0380] Step 10:

[0381] The server completes the reservation process and gathers the necessary information to execute the entire plan. It also uses an emotion engine to respond flexibly when communication with the user is required.

[0382] Step 11:

[0383] After the trip ends, users provide feedback via their device, including comments about their feelings.

[0384] Step 12:

[0385] The device sends feedback data to the server, and the emotion engine analyzes this feedback to gain insights into the emotional state.

[0386] Step 13:

[0387] The server records the feedback in a database and adjusts the algorithm to use it for future plan generation. Through learning by the emotion engine, its planning capabilities improve for subsequent uses.

[0388] (Example 2)

[0389] 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".

[0390] This invention relates to a method for providing personalized travel plans to travelers with disabilities, taking into account their individual emotional states. Conventional travel plans have struggled to adequately reflect the individual needs and emotional states of users, resulting in poor satisfaction. In particular, many plans do not properly incorporate accessibility information that is crucial for travelers with disabilities, making it difficult to provide a safe and satisfying travel experience.

[0391] 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.

[0392] In this invention, the server includes means for receiving information from the user and analyzing the emotional state using machine learning; a processing function for creating a travel schedule that takes accessibility information into consideration using generative AI based on the emotional state and related information; and a control function for presenting the created travel schedule to the user and automatically making reservations, including transportation and accommodation, based on the user's selection. This enables the creation of personalized travel plans that more accurately reflect the user's emotions and individual needs, and allows for flexible responses to changes in plans at any time.

[0393] An "input function" refers to a device or software that allows users to input information about their travel purpose and physical limitations.

[0394] "Information" refers to data provided by the user, including the purpose of travel, the degree of disability, and preferred dates and times.

[0395] "Emotional state" refers to the psychological situation analyzed based on user input information and the emotions reflected in the feedback.

[0396] "Machine learning" is a technology that allows computers to learn patterns and rules from data and improve the algorithms necessary for optimizing travel plans.

[0397] "Generative AI" refers to artificial intelligence that uses machine learning techniques to automatically create personalized travel plans based on emotional states and user information.

[0398] "Accessibility information" refers to data that includes information on the convenience of transportation and facilities necessary for travelers with disabilities to enjoy their trip safely and comfortably.

[0399] "Processing function" refers to the system's ability to automatically generate a travel plan based on the input information and emotional state.

[0400] The "control function" refers to a system feature that automatically handles booking procedures and manages the execution of a travel plan based on the user's selected travel plan.

[0401] The "update function" is a feature that uses user feedback obtained after a trip to update the system's overall information resources and improve the accuracy of the algorithms.

[0402] "Experience feedback" refers to evaluations of opinions and feelings provided by users after a trip, and this data is useful for creating future travel plans.

[0403] The system of the present invention aims to provide personalized travel plans for travelers with disabilities, taking into account the emotional state of each user. Its embodiments are described in detail below.

[0404] The device features an input function for users to enter travel information. This input function allows users to enter details such as the purpose of the trip, the degree of any disabilities, places they wish to visit, and preferred dates and times. This information is crucial data for operating the emotion engine.

[0405] The server uses information received from the terminal to perform sentiment analysis through machine learning. This utilizes natural language processing technology to infer emotions from the user's input. Specifically, it determines the positive or negative nature of the emotion, as well as levels of tension and anticipation, based on the user's expressions and keywords.

[0406] Next, the server uses a generative AI model to generate the optimal travel plan based on the results of the sentiment analysis. This model extracts relevant information from a database that includes accessibility information and personalizes activities, transportation, and accommodations to match the user's emotions.

[0407] The server sends the generated plan back to the terminal, where the user reviews and selects it. Based on the selected plan, the server automatically processes transportation and accommodation reservations, providing an interface that allows for easy modification using drag-and-drop or click operations as needed. This process also integrates with external reservation systems via API connections.

[0408] After the trip is complete, the user enters feedback into their device. This feedback is then sent back to the server and analyzed by the sentiment engine. This information is used as data to improve the algorithm for generating future travel plans.

[0409] For example, if a user inputs an intention such as "I want to relax" or "I want to reduce stress," the AI ​​can be prompted with phrases like "Generate a travel plan that takes the user's emotional state into account" or "How can we use accessibility information and an emotion engine to provide a personalized plan for travelers with disabilities?" This allows the AI ​​to derive more suitable suggestions.

[0410] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0411] Step 1:

[0412] Users use their devices to input information such as the purpose of their trip, the degree of their disability, places they want to visit, and their preferred dates and times. This input information serves as the starting point for data processing throughout the system. The input data is then structured into keywords necessary for personalizing the trip.

[0413] Step 2:

[0414] The terminal sends the data entered by the user to the server as structured data. Specifically, this involves securely and efficiently transmitting information using a data communication protocol. At this stage, the entered information is converted so that it can be stored in a database.

[0415] Step 3:

[0416] The server activates the emotion engine based on the received data. The emotion engine uses natural language processing algorithms to analyze the user's input and infer their emotional state. For example, it extracts emotional keywords such as "excitement" or "anxiety" and identifies the corresponding emotional state. This analysis outputs the emotional state, which is then used in the next process.

[0417] Step 4:

[0418] The server utilizes a generative AI model based on emotional state and user information to generate the optimal travel plan. Here, accessibility information is retrieved from the database, and data processing is performed to select tourist destinations and activities that meet the user's needs. Specifically, plans are generated by referencing past feedback and using plans provided to users with similar emotional states as a reference.

[0419] Step 5:

[0420] The server sends the generated travel plans to the terminal. The terminal visually presents these to the user, allowing them to select their preferred plan. The input here is a list of generated plans, and the output is the specific plan selected by the user. The user-initiated interface is designed to be intuitively understandable.

[0421] Step 6:

[0422] The terminal receives the user's selection and sends that information back to the server. The server, in conjunction with the reservation management system, automatically executes the reservation process based on the selected plan. At this point, the input is the user's selection information, and the output is the confirmed reservation information. This process is carried out via API calls to an external system.

[0423] Step 7:

[0424] After the trip is complete, the user enters feedback about the experience into a terminal. The entered feedback is sent from the terminal to the server. The server uses the emotion engine again to analyze the emotions in the feedback. This analysis result is later stored in a database and used to improve future plan generation algorithms. Through the processing of feedback, the system is constantly updated, enabling it to provide more accurate plans.

[0425] (Application Example 2)

[0426] 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."

[0427] In recent years, there has been a growing demand for technologies that enhance the travel experience for travelers with disabilities. However, conventional systems are insufficient in suggesting personalized travel plans and relevant content that take user emotions into account. As a result, traveler satisfaction is low, and it is difficult to achieve a comfortable travel experience.

[0428] 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.

[0429] In this invention, the server includes an analysis means for receiving input data from the user and analyzing their emotions in real time, a processing means for generating a travel plan that takes accessibility information into consideration based on the emotion analysis results, and a control means for presenting content related to the generated travel plan to the user and performing a reservation procedure based on the user's selection. This makes it possible to provide travelers with disabilities with an optimal travel plan and related content that is tailored to their emotions.

[0430] The "analysis method for analyzing user emotions" is a function that grasps the user's emotional state in real time based on input data and provides information necessary for adjusting travel plans.

[0431] The "processing method for generating travel plans that take accessibility information into consideration" is a function that, based on sentiment analysis and various data, selects transportation methods, accommodations, and tourist facilities that can be comfortably used by travelers with disabilities, and then constructs a travel plan.

[0432] "A control means for presenting content related to the generated travel plan to the user and performing booking procedures" refers to a function that presents the generated travel plan to the user visually or audibly and performs bookings and arrangements based on the user's selections.

[0433] "An update mechanism to collect user feedback and update the database to improve information accuracy" refers to a function that collects user feedback and opinions after a trip, updates the information in the database based on this feedback, and improves the accuracy of generating future travel plans.

[0434] This invention aims to build a system that provides personalized travel plans and content to travelers with disabilities using emotion analysis. The system is primarily based on data processing and communication between three parties: a terminal, a server, and the user.

[0435] The terminal receives input information from the user, such as the purpose of travel, the degree of disability, and desired destinations, through an application installed on a device like a smartphone or head-mounted display. This information is crucial data for real-time sentiment analysis. The terminal uses the Emotion API to read emotions from the user's facial expressions and voice, and sends this data to the server in a structured format.

[0436] On the server, an analysis tool identifies emotions based on the received data, and the analysis results are used to create a travel plan. Past feedback and the latest information on accessibility are retrieved from the database. This information is processed by an AI algorithm (using TensorFlow) to automatically generate a travel plan optimized for the user's emotions and situation. This plan includes transportation, accommodation, and relaxing activities tailored to the user's state and requests.

[0437] The user visually reviews the suggested travel plan via their device and sends their selected options back to the server. The server then flexibly handles the necessary booking procedures based on this selection. At the end of the trip, user feedback is collected, and emotional information is analyzed again using the Emotion API. This information is used to update the database to improve the accuracy of future plan generation.

[0438] For example, if a user is looking for a relaxing travel destination, the system will recognize the user's emotion as "relaxation" and then provide information about natural tourist destinations. Such a system is designed to allow users to enjoy a more personalized travel experience.

[0439] Example prompt for a generative AI model: "Please advise on what kind of tourist information and content should be provided when a user is feeling stressed."

[0440] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0441] Step 1:

[0442] The user uses a terminal to input the purpose of their trip, the degree of their disability, desired destinations, and preferred dates and times. The terminal receives this user input as structured data and sends it to the server. The input includes text and voice data, resulting in structured data that is sent to the server as output.

[0443] Step 2:

[0444] The server receives structured data sent from the terminal and analyzes the user's emotions in real time using the Emotion API. This analysis determines the user's emotional state, and as a result, data indicating the emotion is generated. The input is structured data, and the output is the analyzed emotional state data.

[0445] Step 3:

[0446] The server retrieves relevant accessibility information from the database based on the sentiment analysis results. Here, SQL queries are used to search the database and extract information suitable for travelers with disabilities. The input is sentiment state data, and the output is accessibility information.

[0447] Step 4:

[0448] The server generates an optimal travel plan using an AI algorithm (TensorFlow) based on the sentiment analysis results and acquired accessibility information. Sentiment data and accessibility information are used for data calculations, and a customized travel plan is obtained as output.

[0449] Step 5:

[0450] The terminal visually displays a travel plan transmitted from the server to the user. The user reviews the presented plan and makes a decision. The input is a customized travel plan, and the output is the user's selection.

[0451] Step 6:

[0452] The terminal, upon receiving the user's selection, sends that information back to the server and requests the reservation process. The server then works in conjunction with the reservation system to proceed with registration and arrangements. The input is the user's selection, and the output is a reservation completion confirmation.

[0453] Step 7:

[0454] After completing their trip, the user enters feedback about their experience into their device. The device sends this information to a server, which then uses the Emotion API again to analyze the emotional information. The input is the user's feedback, and the output is the emotional analysis data.

[0455] Step 8:

[0456] The server updates the database based on feedback information and stores data to be used in future plan generation. Data processing learns from newly acquired information and contributes to improving the algorithm. The input is feedback data, and the output is the updated database.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] [Third Embodiment]

[0461] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0462] 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.

[0463] 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).

[0464] 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.

[0465] 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.

[0466] 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).

[0467] 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.

[0468] 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.

[0469] 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.

[0470] 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.

[0471] 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.

[0472] 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".

[0473] This invention relates to a system for providing customized travel plans for travelers with disabilities. The following describes specific embodiments for carrying out the invention.

[0474] First, the user enters information about the degree of their disability, specific travel destinations, and desired activities using the input method on the device. This information includes the travel destination, desired travel dates and times, and any special considerations required.

[0475] The terminal receives information entered by the user and sends it to the server as a dataset. The server has a database containing accessibility information tailored to various types of disabilities, as well as data obtained from past user feedback.

[0476] The server uses AI algorithms to generate the optimal travel plan based on the received information. This takes into account factors such as transportation options, accessibility of accommodations, and activity information at the destination. In particular, it selects accessible spots and services according to the user's disability, creating a plan that best suits individual needs.

[0477] The created plan is sent back to the device and displayed for the user to review and select. After reviewing the plan, the user can choose a satisfactory option. This process ensures that transportation and accommodation bookings are made consistently.

[0478] After their trip, users provide feedback based on their actual experience. This feedback includes information on the actual availability of accessibility features and their satisfaction with the itinerary.

[0479] The device sends this feedback to the server. The server receives the feedback, updates its database, and incorporates it into future suggestions. This allows for continuous improvement of the quality of generated plans. Furthermore, by adjusting the algorithm based on the feedback, it ensures an optimized travel experience for each user.

[0480] For example, if a user using a wheelchair wants to visit a tourist attraction, the server will collect information on wheelchair-accessible transportation, hotels with barrier-free facilities, and accessible tourist spots at the destination, and then provide a plan. In this process, user feedback will be used to generate future plans, resulting in a more personalized travel experience.

[0481] The following describes the processing flow.

[0482] Step 1:

[0483] The user enters information such as their travel destination, desired date and time, and details of any problems into the terminal's input interface.

[0484] Step 2:

[0485] The terminal receives the information entered by the user, converts it into the appropriate data format, and prepares to send it to the server.

[0486] Step 3:

[0487] The server analyzes user information received from the terminal and retrieves relevant accessibility information from the database.

[0488] Step 4:

[0489] The server uses AI algorithms to generate travel plans that best suit the user's needs, taking into account the collected accessibility information.

[0490] Step 5:

[0491] The server sends the generated travel plan to the terminal so that the user can review it.

[0492] Step 6:

[0493] The terminal displays the travel plan received from the server on the user interface, allowing the user to check its contents.

[0494] Step 7:

[0495] The user reviews the displayed travel plans and selects the option they deem best.

[0496] Step 8:

[0497] The device receives the user's plan selection and sends that information back to the server.

[0498] Step 9:

[0499] The server automatically handles the booking process for transportation and accommodation based on the user's selections.

[0500] Step 10:

[0501] After the trip ends, users use their devices to provide feedback about their actual experience.

[0502] Step 11:

[0503] The device sends user feedback to the server.

[0504] Step 12:

[0505] The server saves the received feedback to a database and updates the information for use in future plan generation.

[0506] (Example 1)

[0507] 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."

[0508] For travelers with disabilities, efficiently providing customized travel plans based on available accessibility information is challenging. Furthermore, determining whether the provided plans fully meet individual needs is also a challenge. Additionally, the lack of effective means to incorporate collected feedback into future planning makes it difficult to continuously improve the quality of the travel experience.

[0509] 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.

[0510] In this invention, the server includes input means for the user to input their travel goals and the degree of their disability; calculation means for receiving the input information from the user and constructing a travel plan considering barrier-free information and data corresponding to the user's disability; and control means for generating an optimal travel plan using a generation AI model and presenting it to the user. This makes it possible to efficiently provide travelers with disabilities with personalized travel plans that meet their individual needs and to continuously improve the quality of the plans by utilizing the collected feedback.

[0511] "Input means" refers to a device or method that provides an interface for a user to input their travel goals and the degree of obstacles into the system.

[0512] "Calculation means" refers to a device or method that has the function of constructing a travel plan based on user input information, taking into account accessibility information and data corresponding to disabilities.

[0513] "Control means" refers to a device or system that presents a generated travel plan to the user and adjusts and executes the necessary booking procedures based on the user's selection.

[0514] "Update mechanism" refers to a device or method that has the function of updating the database based on feedback collected from users after the end of their trip, thereby continuously improving the accuracy of the information and the quality of the service.

[0515] A "generative AI model" is an artificial intelligence algorithm or system that generates the optimal travel plan based on information provided by the user.

[0516] "Communication methods" refer to the technologies and methods used to send and receive generated travel plans and collected feedback between the user and the server.

[0517] This invention is a system that provides customized travel plans for travelers with disabilities, and its embodiments are described below.

[0518] First, the user uses the terminal to input information such as the degree of their disability, their travel destination, desired dates, and any special considerations they require. This input is primarily done through dedicated application software or a web browser. After inputting the information, the terminal organizes it into a dataset and sends it to the server using a security protocol.

[0519] The server generates the optimal travel plan using an AI model based on the received data. In this process, it references accessibility information stored in the database and past user feedback to perform calculations to create a plan tailored to the user's specific needs. This process is carried out by an AI algorithm implemented in Python. The server temporarily stores the plan provided to the user in JSON format.

[0520] The generated travel plan is sent from the server to the terminal and visually displayed on the terminal's user interface. Based on the displayed plan, the user can make selections and proceed with booking transportation and accommodation.

[0521] After the trip ends, users input feedback based on their actual experience into a device. This feedback includes aspects such as the availability of accessibility features and satisfaction with the plan. The device sends this feedback data to a server, which updates its database based on it, helping to improve the accuracy of the algorithm.

[0522] As a concrete example, if a wheelchair user wants to visit tourist attractions, a possible prompt would be, "Generate a barrier-free travel plan for Tokyo sightseeing for wheelchair users." This prompt is input into the server's AI model and serves as an instruction to generate a travel plan optimized for the user. This makes it possible to provide a more personalized travel experience.

[0523] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0524] Step 1:

[0525] The user uses the terminal's input interface to enter their travel destination, dates, degree of disability, and any special considerations required.

[0526] The input information is organized as a dataset within the device. The device then sends this organized data to the server via the HTTPS protocol, providing it as input for the initial dataset.

[0527] Step 2:

[0528] The server uses a generative AI model to build a travel plan based on the data received from the terminal.

[0529] Specifically, an AI algorithm implemented in Python compares the received data with accessibility information stored in a database to select the most suitable transportation, accommodation, and activities for the user. This generates a customized travel plan.

[0530] Step 3:

[0531] The server organizes the generated travel plan in JSON format and sends it to the terminal.

[0532] The device parses the received JSON data and displays it on the user interface for the user to visually confirm. Based on the displayed information, the user selects a travel plan and records that selection on the device.

[0533] Step 4:

[0534] After the user completes their trip, they use their device to enter feedback based on their actual travel experience.

[0535] This feedback is recorded as a dataset including the actual level of accessibility measures taken and satisfaction with the itinerary. The device sends this feedback data to the server.

[0536] Step 5:

[0537] The server receives feedback from users and updates the database.

[0538] Specifically, the collected feedback will be stored in a database so that this new data is taken into consideration when generating future travel plans. The server will also adjust the AI ​​algorithm based on the feedback to improve the next plan, making it more personalized.

[0539] (Application Example 1)

[0540] 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."

[0541] For travelers with disabilities, a lack of accessibility information at their destinations and travel plans that don't suit their needs are major obstacles to enjoying their trips. Furthermore, traditional travel plans lack features to incorporate user feedback and satisfaction into future plans, making it difficult to improve the quality of the travel experience.

[0542] 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.

[0543] In this invention, the server includes input means for the user to input the purpose of the trip and the degree of any obstacles, display means for visually experiencing the travel plan in a virtual environment, and means for learning an algorithm based on user feedback and improving generation accuracy. This allows the user to visually confirm the destination and experience and adjust a more suitable travel plan in advance.

[0544] An "input method" is an interface that allows the user to input information about their travel purpose and the degree of their disability into the system.

[0545] A "processing device" is a device that receives input data from a user and has the function of processing the data in order to generate a travel plan that takes accessibility information into consideration.

[0546] A "control device" is a device that has the function of presenting the generated travel plan to the user and carrying out the booking procedure based on the user's selection.

[0547] "Display means" refers to a device or interface that allows users to visually experience a travel plan within a virtual environment.

[0548] An "update mechanism" refers to a function that collects user feedback after the trip is completed, updates the database based on that feedback, and improves the accuracy of the information.

[0549] A "learning tool" is a function that adjusts the travel plan generation algorithm based on user feedback to improve generation accuracy.

[0550] A "virtual reality device" is a device that provides users with a virtual environment and visually simulates a travel experience.

[0551] This invention realizes a system that generates customized travel plans for travelers with disabilities and delivers them in a virtual reality environment. The details are as follows.

[0552] First, the user enters information on their device, such as their travel destination, preferred dates and times, degree of disability, and any special considerations. The device then sends this information to the server. The hardware used at this stage includes input devices for the user to enter information, such as tablets and smartphones.

[0553] Based on the received information, the server generates an optimal travel plan using a generative AI model. This involves data processing that considers factors such as transportation options, accommodation accessibility, and accessible activities at the destination. The server's software includes a database management system and AI algorithms, which work together to perform data calculations.

[0554] The generated travel plans are provided to the user via a virtual reality device. Using smart glasses or a head-mounted display, the user can visually experience virtual scenery of their travel destination. This allows the user to simulate the trip in advance and select a plan that suits their needs.

[0555] After a trip ends, users provide feedback based on their experience. This feedback is sent back to the server from the device, which updates the database and incorporates it into generating future travel plans. This allows for continuous improvement of service quality. The feedback is used to train the generative AI model's algorithms, ultimately leading to the provision of more suitable travel experiences for users.

[0556] For example, if a wheelchair user wants to visit a specific tourist destination, the server will generate a plan that includes accessibility information suitable for that user and allow them to experience it in virtual reality. An example of a prompt would be, "Generate a travel plan combining information on accessible tourist spots and accommodations for a wheelchair user planning a visit to Kyoto."

[0557] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0558] Step 1:

[0559] Users enter travel information on their devices. This information includes the travel destination, preferred dates and times, and the degree of any disabilities. This data is then sent from the device to the server as basic data for creating a travel plan.

[0560] Step 2:

[0561] The server searches its database for relevant accessibility information based on input data received from the terminal. Specifically, it uses an AI algorithm to process information on accessible transportation, accommodations, and tourist attractions around the destination to generate an optimal travel plan. This data processing and calculation results in a plan tailored to individual needs.

[0562] Step 3:

[0563] The generated travel plan is converted into a virtual reality-compatible format and sent to the device. The device receives the plan and presents it to the user through a VR display device (e.g., a head-mounted display). This allows the user to have a virtual travel experience in advance and to visually confirm the plan.

[0564] Step 4:

[0565] After the trip ends, users enter feedback about their travel experience via their device. This feedback includes actual accessibility experiences and evaluations of facilities. The feedback data is then sent back to the server.

[0566] Step 5:

[0567] The server analyzes the received feedback and updates the database information. Simultaneously, it uses a generative AI model to train its algorithm and improve the accuracy of future travel plan generation. This data processing enables higher-quality suggestions for subsequent plan generation.

[0568] Step 6:

[0569] As an example of prompt generation, the command "Generate a travel plan combining information on barrier-free tourist attractions and accommodations for a wheelchair user planning a visit to Kyoto" is used. Based on this, the server collects and analyzes the appropriate information.

[0570] 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.

[0571] This invention relates to a system that provides more personalized travel plans for travelers with disabilities. In particular, it improves the quality of the travel experience by combining it with an emotion engine that can recognize the user's emotions and respond accordingly.

[0572] First, the user uses the terminal's input method to enter information such as the purpose of their trip, the degree of their disability, the places they want to visit, and their preferred dates and times. This information becomes an important element in plan generation.

[0573] The terminal receives information entered by the user and sends it to the server as structured data. Here, the emotion engine interprets the user's emotions from the input and infers their emotional state.

[0574] The server retrieves the most relevant accessibility information from the database based on the received user information and the emotional state recognized by the emotion engine. This includes feedback from past travelers and the latest facility information.

[0575] Next, the server uses an AI algorithm to create a travel plan. During this process, the user's emotional state is taken into consideration, and adjustments are made to select a more comfortable and satisfying itinerary. The plan includes barrier-free transportation and accommodation, and the activities are also tailored accordingly.

[0576] The created plan is sent to the device and displayed for the user to review. The user can then review the presented plan and choose the option that best suits their needs.

[0577] The terminal receives the user's selection and sends that information back to the server. The server then processes the necessary reservations based on the selection. Even during cancellations or changes, the emotion engine supports appropriate responses, enabling more flexible plan modifications.

[0578] Finally, after completing the trip, the user enters their thoughts and opinions about the experience as feedback into the device. The device sends this data to the server, and the emotion engine also analyzes the emotions included in the feedback. This data is used to improve the plan generation algorithm for future trips, updating the entire system to continuously improve the accuracy of the plans and the ability to respond to emotions.

[0579] For example, if the system recognizes that a user is prone to stress, it can generate a plan that prioritizes activities that help them relax, such as shortening travel time. In this way, the goal is to maximize the user experience by working in conjunction with the emotion engine.

[0580] The following describes the processing flow.

[0581] Step 1:

[0582] Users enter details such as their travel destination, dates, degree of disability, and desired activities using their own devices. This information also includes the purpose of the trip and any individual assistance needed.

[0583] Step 2:

[0584] The terminal collects data entered by the user, organizes that information, and converts it into a format for transmission to the server.

[0585] Step 3:

[0586] The server analyzes user data received from the terminal and uses an emotion engine to process and identify the user's emotional state from the input text.

[0587] Step 4:

[0588] The server searches the database for relevant accessibility information and past feedback information based on the user's emotional state and input information.

[0589] Step 5:

[0590] The server uses AI algorithms to generate customized travel plans that take into account the user's emotional state. This includes available accessibility features, accessible transportation options, and recommended activities.

[0591] Step 6:

[0592] The server sends the generated travel plan to the terminal, allowing the user to review and select it.

[0593] Step 7:

[0594] The terminal displays the plan received from the server to the user, allowing them to view the plan details. The user reviews the plan and selects the one that best suits their needs.

[0595] Step 8:

[0596] Based on their chosen travel plan, users make adjustments as needed to finalize their itinerary.

[0597] Step 9:

[0598] The device sends the user's confirmed plan to the server and initiates the reservation process based on that information.

[0599] Step 10:

[0600] The server completes the reservation process and gathers the necessary information to execute the entire plan. It also uses an emotion engine to respond flexibly when communication with the user is required.

[0601] Step 11:

[0602] After the trip ends, users provide feedback via their device, including comments about their feelings.

[0603] Step 12:

[0604] The device sends feedback data to the server, and the emotion engine analyzes this feedback to gain insights into the emotional state.

[0605] Step 13:

[0606] The server records the feedback in a database and adjusts the algorithm to use it for future plan generation. Through learning by the emotion engine, its planning capabilities improve for subsequent uses.

[0607] (Example 2)

[0608] 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."

[0609] This invention relates to a method for providing personalized travel plans to travelers with disabilities, taking into account their individual emotional states. Conventional travel plans have struggled to adequately reflect the individual needs and emotional states of users, resulting in poor satisfaction. In particular, many plans do not properly incorporate accessibility information that is crucial for travelers with disabilities, making it difficult to provide a safe and satisfying travel experience.

[0610] 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.

[0611] In this invention, the server includes means for receiving information from the user and analyzing the emotional state using machine learning; a processing function for creating a travel schedule that takes accessibility information into consideration using generative AI based on the emotional state and related information; and a control function for presenting the created travel schedule to the user and automatically making reservations, including transportation and accommodation, based on the user's selection. This enables the creation of personalized travel plans that more accurately reflect the user's emotions and individual needs, and allows for flexible responses to changes in plans at any time.

[0612] An "input function" refers to a device or software that allows users to input information about their travel purpose and physical limitations.

[0613] "Information" refers to data provided by the user, including the purpose of travel, the degree of disability, and preferred dates and times.

[0614] "Emotional state" refers to the psychological situation analyzed based on user input information and the emotions reflected in the feedback.

[0615] "Machine learning" is a technology that allows computers to learn patterns and rules from data and improve the algorithms necessary for optimizing travel plans.

[0616] "Generative AI" refers to artificial intelligence that uses machine learning techniques to automatically create personalized travel plans based on emotional states and user information.

[0617] "Accessibility information" refers to data that includes information on the convenience of transportation and facilities necessary for travelers with disabilities to enjoy their trip safely and comfortably.

[0618] "Processing function" refers to the system's ability to automatically generate a travel plan based on the input information and emotional state.

[0619] The "control function" refers to a system feature that automatically handles booking procedures and manages the execution of a travel plan based on the user's selected travel plan.

[0620] The "update function" is a feature that uses user feedback obtained after a trip to update the system's overall information resources and improve the accuracy of the algorithms.

[0621] "Experience feedback" refers to evaluations of opinions and feelings provided by users after a trip, and this data is useful for creating future travel plans.

[0622] The system of the present invention aims to provide personalized travel plans for travelers with disabilities, taking into account the emotional state of each user. Its embodiments are described in detail below.

[0623] The device features an input function for users to enter travel information. This input function allows users to enter details such as the purpose of the trip, the degree of any disabilities, places they wish to visit, and preferred dates and times. This information is crucial data for operating the emotion engine.

[0624] The server uses information received from the terminal to perform sentiment analysis through machine learning. This utilizes natural language processing technology to infer emotions from the user's input. Specifically, it determines the positive or negative nature of the emotion, as well as levels of tension and anticipation, based on the user's expressions and keywords.

[0625] Next, the server uses a generative AI model to generate the optimal travel plan based on the results of the sentiment analysis. This model extracts relevant information from a database that includes accessibility information and personalizes activities, transportation, and accommodations to match the user's emotions.

[0626] The server sends the generated plan back to the terminal, where the user reviews and selects it. Based on the selected plan, the server automatically processes transportation and accommodation reservations, providing an interface that allows for easy modification using drag-and-drop or click operations as needed. This process also integrates with external reservation systems via API connections.

[0627] After the trip is complete, the user enters feedback into their device. This feedback is then sent back to the server and analyzed by the sentiment engine. This information is used as data to improve the algorithm for generating future travel plans.

[0628] For example, if a user inputs an intention such as "I want to relax" or "I want to reduce stress," the AI ​​can be prompted with phrases like "Generate a travel plan that takes the user's emotional state into account" or "How can we use accessibility information and an emotion engine to provide a personalized plan for travelers with disabilities?" This allows the AI ​​to derive more suitable suggestions.

[0629] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0630] Step 1:

[0631] Users use their devices to input information such as the purpose of their trip, the degree of their disability, places they want to visit, and their preferred dates and times. This input information serves as the starting point for data processing throughout the system. The input data is then structured into keywords necessary for personalizing the trip.

[0632] Step 2:

[0633] The terminal sends the data entered by the user to the server as structured data. Specifically, this involves securely and efficiently transmitting the information using a data communication protocol. At this stage, the entered information is converted so that it can be stored in a database.

[0634] Step 3:

[0635] The server activates the emotion engine based on the received data. The emotion engine uses natural language processing algorithms to analyze the user's input and infer their emotional state. For example, it extracts emotional keywords such as "excitement" or "anxiety" and identifies the corresponding emotional state. This analysis outputs the emotional state, which is then used in the next process.

[0636] Step 4:

[0637] The server utilizes a generative AI model based on emotional state and user information to generate the optimal travel plan. Here, accessibility information is retrieved from the database, and data processing is performed to select tourist destinations and activities that meet the user's needs. Specifically, plans are generated by referencing past feedback and using plans provided to users with similar emotional states as a reference.

[0638] Step 5:

[0639] The server sends the generated travel plans to the terminal. The terminal visually presents these to the user, allowing them to select their preferred plan. The input here is a list of generated plans, and the output is the specific plan selected by the user. The user-initiated interface is designed to be intuitively understandable.

[0640] Step 6:

[0641] The terminal receives the user's selection and sends that information back to the server. The server, in conjunction with the reservation management system, automatically executes the reservation process based on the selected plan. At this point, the input is the user's selection information, and the output is the confirmed reservation information. This process is carried out via API calls to an external system.

[0642] Step 7:

[0643] After the trip is complete, the user enters feedback about the experience into a terminal. The entered feedback is sent from the terminal to the server. The server uses the emotion engine again to analyze the emotions in the feedback. This analysis result is later stored in a database and used to improve future plan generation algorithms. Through the processing of feedback, the system is constantly updated, enabling it to provide more accurate plans.

[0644] (Application Example 2)

[0645] 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."

[0646] In recent years, there has been a growing demand for technologies that enhance the travel experience for travelers with disabilities. However, conventional systems are insufficient in suggesting personalized travel plans and relevant content that take user emotions into account. As a result, traveler satisfaction is low, and it is difficult to achieve a comfortable travel experience.

[0647] 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.

[0648] In this invention, the server includes an analysis means for receiving input data from the user and analyzing their emotions in real time, a processing means for generating a travel plan that takes accessibility information into consideration based on the emotion analysis results, and a control means for presenting content related to the generated travel plan to the user and performing a reservation procedure based on the user's selection. This makes it possible to provide travelers with disabilities with an optimal travel plan and related content that is tailored to their emotions.

[0649] The "analysis method for analyzing user emotions" is a function that grasps the user's emotional state in real time based on input data and provides information necessary for adjusting travel plans.

[0650] The "processing method for generating travel plans that take accessibility information into consideration" is a function that, based on sentiment analysis and various data, selects transportation methods, accommodations, and tourist facilities that can be comfortably used by travelers with disabilities, and then constructs a travel plan.

[0651] "A control means for presenting content related to the generated travel plan to the user and performing booking procedures" refers to a function that presents the generated travel plan to the user visually or audibly and performs bookings and arrangements based on the user's selections.

[0652] "An update mechanism to collect user feedback and update the database to improve the accuracy of information" refers to a function that collects user feedback and opinions after a trip, updates the information in the database based on this feedback, and improves the accuracy of generating future travel plans.

[0653] This invention aims to construct a system that provides personalized travel plans and content to travelers with disabilities using emotion analysis. The system is primarily based on data processing and communication between three parties: a terminal, a server, and the user.

[0654] The terminal receives input information from the user, such as the purpose of travel, the degree of disability, and desired destinations, through an application installed on a device like a smartphone or head-mounted display. This information is crucial data for real-time sentiment analysis. The terminal uses the Emotion API to read emotions from the user's facial expressions and voice, and sends this data to the server in a structured format.

[0655] On the server, an analysis tool identifies emotions based on the received data, and the analysis results are used to create a travel plan. Past feedback and the latest information on accessibility are retrieved from the database. This information is processed by an AI algorithm (using TensorFlow) to automatically generate a travel plan optimized for the user's emotions and situation. This plan includes transportation, accommodation, and relaxing activities tailored to the user's state and requests.

[0656] The user visually reviews the suggested travel plan via their device and sends their selected options back to the server. The server then flexibly handles the necessary booking procedures based on this selection. At the end of the trip, user feedback is collected, and emotional information is analyzed again using the Emotion API. This information is used to update the database to improve the accuracy of future plan generation.

[0657] For example, if a user is looking for a relaxing travel destination, the system will recognize the user's emotion as "relaxation" and then provide information about natural tourist destinations. Such a system is designed to allow users to enjoy a more personalized travel experience.

[0658] Example prompt for a generative AI model: "Please advise on what kind of tourist information and content should be provided when a user is feeling stressed."

[0659] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0660] Step 1:

[0661] The user uses a terminal to input the purpose of their trip, the degree of their disability, desired destinations, and preferred dates and times. The terminal receives this user input as structured data and sends it to the server. The input includes text and voice data, resulting in structured data that is sent to the server as output.

[0662] Step 2:

[0663] The server receives structured data sent from the terminal and analyzes the user's emotions in real time using the Emotion API. This analysis determines the user's emotional state, and as a result, data indicating the emotion is generated. The input is structured data, and the output is the analyzed emotional state data.

[0664] Step 3:

[0665] The server retrieves relevant accessibility information from the database based on the sentiment analysis results. Here, SQL queries are used to search the database and extract information suitable for travelers with disabilities. The input is sentiment state data, and the output is accessibility information.

[0666] Step 4:

[0667] The server generates an optimal travel plan using an AI algorithm (TensorFlow) based on the sentiment analysis results and acquired accessibility information. Sentiment data and accessibility information are used for data calculations, and a customized travel plan is obtained as output.

[0668] Step 5:

[0669] The terminal visually displays a travel plan transmitted from the server to the user. The user reviews the presented plan and makes a decision. The input is a customized travel plan, and the output is the user's selection.

[0670] Step 6:

[0671] The terminal, upon receiving the user's selection, sends that information back to the server and requests the reservation process. The server then works in conjunction with the reservation system to proceed with registration and arrangements. The input is the user's selection, and the output is a reservation completion confirmation.

[0672] Step 7:

[0673] After completing their trip, the user enters feedback about their experience into their device. The device sends this information to a server, which then uses the Emotion API again to analyze the emotional information. The input is the user's feedback, and the output is the emotional analysis data.

[0674] Step 8:

[0675] The server updates the database based on feedback information and stores data to be used in future plan generation. Data processing learns from newly acquired information and contributes to improving the algorithm. The input is feedback data, and the output is the updated database.

[0676] 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.

[0677] 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.

[0678] 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.

[0679] [Fourth Embodiment]

[0680] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0681] 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.

[0682] 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).

[0683] 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.

[0684] 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.

[0685] 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).

[0686] 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.

[0687] 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.

[0688] 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.

[0689] 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.

[0690] 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.

[0691] 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.

[0692] 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".

[0693] This invention relates to a system for providing customized travel plans for travelers with disabilities. The following describes specific embodiments for carrying out the invention.

[0694] First, the user enters information about the degree of their disability, specific travel destinations, and desired activities using the input method on the device. This information includes the travel destination, desired travel dates and times, and any special considerations required.

[0695] The terminal receives information entered by the user and sends it to the server as a dataset. The server has a database containing accessibility information tailored to various types of disabilities, as well as data obtained from past user feedback.

[0696] The server uses AI algorithms to generate the optimal travel plan based on the received information. This takes into account factors such as transportation options, accessibility of accommodations, and activity information at the destination. In particular, it selects accessible spots and services according to the user's disability, creating a plan that best suits individual needs.

[0697] The created plan is sent back to the device and displayed for the user to review and select. After reviewing the plan, the user can choose a satisfactory option. This process ensures that transportation and accommodation bookings are made consistently.

[0698] After their trip, users provide feedback based on their actual experience. This feedback includes information on the actual availability of accessibility features and their satisfaction with the itinerary.

[0699] The device sends this feedback to the server. The server receives the feedback, updates its database, and incorporates it into future suggestions. This allows for continuous improvement of the quality of generated plans. Furthermore, by adjusting the algorithm based on the feedback, it ensures an optimized travel experience for each user.

[0700] For example, if a user using a wheelchair wants to visit a tourist attraction, the server will collect information on wheelchair-accessible transportation, hotels with barrier-free facilities, and accessible tourist spots at the destination, and then provide a plan. In this process, user feedback will be used to generate future plans, resulting in a more personalized travel experience.

[0701] The following describes the processing flow.

[0702] Step 1:

[0703] The user enters information such as their travel destination, desired date and time, and details of any problems into the terminal's input interface.

[0704] Step 2:

[0705] The terminal receives the information entered by the user, converts it into the appropriate data format, and prepares to send it to the server.

[0706] Step 3:

[0707] The server analyzes user information received from the terminal and retrieves relevant accessibility information from the database.

[0708] Step 4:

[0709] The server uses AI algorithms to generate travel plans that best suit the user's needs, taking into account the collected accessibility information.

[0710] Step 5:

[0711] The server sends the generated travel plan to the terminal so that the user can review it.

[0712] Step 6:

[0713] The terminal displays the travel plan received from the server on the user interface, allowing the user to check its contents.

[0714] Step 7:

[0715] The user reviews the displayed travel plans and selects the option they deem best.

[0716] Step 8:

[0717] The device receives the user's plan selection and sends that information back to the server.

[0718] Step 9:

[0719] The server automatically handles the booking process for transportation and accommodation based on the user's selections.

[0720] Step 10:

[0721] After the trip ends, users use their devices to provide feedback about their actual experience.

[0722] Step 11:

[0723] The device sends user feedback to the server.

[0724] Step 12:

[0725] The server saves the received feedback to a database and updates the information for use in future plan generation.

[0726] (Example 1)

[0727] 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".

[0728] For travelers with disabilities, efficiently providing customized travel plans based on available accessibility information is challenging. Furthermore, determining whether the provided plans fully meet individual needs is also a challenge. Additionally, the lack of effective means to incorporate collected feedback into future planning makes it difficult to continuously improve the quality of the travel experience.

[0729] 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.

[0730] In this invention, the server includes input means for the user to input their travel goals and the degree of their disability; calculation means for receiving the input information from the user and constructing a travel plan considering barrier-free information and data corresponding to the user's disability; and control means for generating an optimal travel plan using a generation AI model and presenting it to the user. This makes it possible to efficiently provide travelers with disabilities with personalized travel plans that meet their individual needs and to continuously improve the quality of the plans by utilizing the collected feedback.

[0731] "Input means" refers to a device or method that provides an interface for a user to input their travel goals and the degree of obstacles into the system.

[0732] "Calculation means" refers to a device or method that has the function of constructing a travel plan based on user input information, taking into account accessibility information and data corresponding to disabilities.

[0733] "Control means" refers to a device or system that presents a generated travel plan to the user and adjusts and executes the necessary booking procedures based on the user's selection.

[0734] "Update mechanism" refers to a device or method that has the function of updating the database based on feedback collected from users after the end of their trip, thereby continuously improving the accuracy of the information and the quality of the service.

[0735] A "generative AI model" is an artificial intelligence algorithm or system that generates the optimal travel plan based on information provided by the user.

[0736] "Communication methods" refer to the technologies and methods used to send and receive generated travel plans and collected feedback between the user and the server.

[0737] This invention is a system that provides customized travel plans for travelers with disabilities, and its embodiments are described below.

[0738] First, the user uses the terminal to input information such as the degree of their disability, their travel destination, desired dates, and any special considerations they require. This input is primarily done through dedicated application software or a web browser. After inputting the information, the terminal organizes it into a dataset and sends it to the server using a security protocol.

[0739] The server generates the optimal travel plan using an AI model based on the received data. In this process, it references accessibility information stored in the database and past user feedback to perform calculations to create a plan tailored to the user's specific needs. This process is carried out by an AI algorithm implemented in Python. The server temporarily stores the plan provided to the user in JSON format.

[0740] The generated travel plan is sent from the server to the terminal and visually displayed on the terminal's user interface. Based on the displayed plan, the user can make selections and proceed with booking transportation and accommodation.

[0741] After the trip ends, users input feedback based on their actual experience into a device. This feedback includes aspects such as the availability of accessibility features and satisfaction with the plan. The device sends this feedback data to a server, which updates its database based on it, helping to improve the accuracy of the algorithm.

[0742] As a concrete example, if a wheelchair user wants to visit tourist attractions, a possible prompt would be, "Generate a barrier-free travel plan for Tokyo sightseeing for wheelchair users." This prompt is input into the server's AI model and serves as an instruction to generate a travel plan optimized for the user. This makes it possible to provide a more personalized travel experience.

[0743] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0744] Step 1:

[0745] The user uses the terminal's input interface to enter their travel destination, dates, degree of disability, and any special considerations required.

[0746] The input information is organized as a dataset within the device. The device then sends this organized data to the server via the HTTPS protocol, providing it as input for the initial dataset.

[0747] Step 2:

[0748] The server uses a generative AI model to build a travel plan based on the data received from the terminal.

[0749] Specifically, an AI algorithm implemented in Python compares the received data with accessibility information stored in a database to select the most suitable transportation, accommodation, and activities for the user. This generates a customized travel plan.

[0750] Step 3:

[0751] The server organizes the generated travel plan in JSON format and sends it to the terminal.

[0752] The device parses the received JSON data and displays it on the user interface for the user to visually confirm. Based on the displayed information, the user selects a travel plan and records that selection on the device.

[0753] Step 4:

[0754] After the user completes their trip, they use their device to enter feedback based on their actual travel experience.

[0755] This feedback is recorded as a dataset including the actual level of accessibility measures taken and satisfaction with the itinerary. The device sends this feedback data to the server.

[0756] Step 5:

[0757] The server receives feedback from users and updates the database.

[0758] Specifically, the collected feedback will be stored in a database so that this new data is taken into consideration when generating future travel plans. The server will also adjust the AI ​​algorithm based on the feedback to improve the next plan, making it more personalized.

[0759] (Application Example 1)

[0760] 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".

[0761] For travelers with disabilities, a lack of accessibility information at their destinations and travel plans that don't suit their needs are major obstacles to enjoying their trips. Furthermore, traditional travel plans lack features to incorporate user feedback and satisfaction into future plans, making it difficult to improve the quality of the travel experience.

[0762] 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.

[0763] In this invention, the server includes input means for the user to input the purpose of the trip and the degree of any obstacles, display means for visually experiencing the travel plan in a virtual environment, and means for learning an algorithm based on user feedback and improving generation accuracy. This allows the user to visually confirm the destination and experience and adjust a more suitable travel plan in advance.

[0764] An "input method" is an interface that allows the user to input information about their travel purpose and the degree of their disability into the system.

[0765] A "processing device" is a device that receives input data from a user and has the function of processing the data in order to generate a travel plan that takes accessibility information into consideration.

[0766] A "control device" is a device that has the function of presenting the generated travel plan to the user and carrying out the booking procedure based on the user's selection.

[0767] "Display means" refers to a device or interface that allows users to visually experience a travel plan within a virtual environment.

[0768] An "update mechanism" refers to a function that collects user feedback after the trip is completed, updates the database based on that feedback, and improves the accuracy of the information.

[0769] A "learning tool" is a function that adjusts the travel plan generation algorithm based on user feedback to improve generation accuracy.

[0770] A "virtual reality device" is a device that provides users with a virtual environment and visually simulates a travel experience.

[0771] This invention realizes a system that generates customized travel plans for travelers with disabilities and delivers them in a virtual reality environment. Details are provided below.

[0772] First, the user enters information on their device, such as their travel destination, preferred dates and times, degree of disability, and any special considerations. The device then sends this information to the server. The hardware used at this stage includes input devices for the user to enter information, such as tablets and smartphones.

[0773] Based on the received information, the server generates an optimal travel plan using a generative AI model. This involves data processing that considers factors such as transportation options, accommodation accessibility, and accessible activities at the destination. The server's software includes a database management system and AI algorithms, which work together to perform data calculations.

[0774] The generated travel plans are provided to the user via a virtual reality device. Using smart glasses or a head-mounted display, the user can visually experience virtual scenery of their travel destination. This allows the user to simulate the trip in advance and select a plan that suits their needs.

[0775] After a trip ends, users provide feedback based on their experience. This feedback is sent back to the server from the device, which updates the database and incorporates it into generating future travel plans. This allows for continuous improvement of service quality. The feedback is used to train the generative AI model's algorithms, ultimately leading to the provision of more suitable travel experiences for users.

[0776] For example, if a wheelchair user wants to visit a specific tourist destination, the server will generate a plan that includes accessibility information suitable for that user and allow them to experience it in virtual reality. An example of a prompt would be, "Generate a travel plan combining information on accessible tourist spots and accommodations for a wheelchair user planning a visit to Kyoto."

[0777] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0778] Step 1:

[0779] Users enter travel information on their devices. This information includes the travel destination, preferred dates and times, and the degree of any disabilities. This data is then sent from the device to the server as basic data for creating a travel plan.

[0780] Step 2:

[0781] The server searches its database for relevant accessibility information based on input data received from the terminal. Specifically, it uses an AI algorithm to process information on accessible transportation, accommodations, and tourist attractions around the destination to generate an optimal travel plan. This data processing and calculation results in a plan tailored to individual needs.

[0782] Step 3:

[0783] The generated travel plan is converted into a virtual reality-compatible format and sent to the device. The device receives the plan and presents it to the user through a VR display device (e.g., a head-mounted display). This allows the user to have a virtual travel experience in advance and to visually confirm the plan.

[0784] Step 4:

[0785] After the trip ends, users enter feedback about their travel experience via their device. This feedback includes actual accessibility experiences and evaluations of facilities. The feedback data is then sent back to the server.

[0786] Step 5:

[0787] The server analyzes the received feedback and updates the database information. Simultaneously, it uses a generative AI model to train its algorithm and improve the accuracy of future travel plan generation. This data processing enables higher-quality suggestions for subsequent plan generation.

[0788] Step 6:

[0789] As an example of prompt generation, the command "Generate a travel plan combining information on barrier-free tourist attractions and accommodations for a wheelchair user planning a visit to Kyoto" is used. Based on this, the server collects and analyzes the appropriate information.

[0790] 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.

[0791] This invention relates to a system that provides more personalized travel plans for travelers with disabilities. In particular, it improves the quality of the travel experience by combining it with an emotion engine that can recognize the user's emotions and respond accordingly.

[0792] First, the user uses the terminal's input method to enter information such as the purpose of their trip, the degree of their disability, the places they want to visit, and their preferred dates and times. This information becomes an important element in plan generation.

[0793] The terminal receives information entered by the user and sends it to the server as structured data. Here, the emotion engine interprets the user's emotions from the input and infers their emotional state.

[0794] The server retrieves the most relevant accessibility information from the database based on the received user information and the emotional state recognized by the emotion engine. This includes feedback from past travelers and the latest facility information.

[0795] Next, the server uses an AI algorithm to create a travel plan. During this process, the user's emotional state is taken into consideration, and adjustments are made to select a more comfortable and satisfying itinerary. The plan includes barrier-free transportation and accommodation, and the activities are also tailored accordingly.

[0796] The created plan is sent to the device and displayed for the user to review. The user can then review the presented plan and choose the option that best suits their needs.

[0797] The terminal receives the user's selection and sends that information back to the server. The server then processes the necessary reservations based on the selection. Even during cancellations or changes, the emotion engine supports appropriate responses, enabling more flexible plan modifications.

[0798] Finally, after completing the trip, the user enters their thoughts and opinions about the experience as feedback into the device. The device sends this data to the server, and the emotion engine also analyzes the emotions included in the feedback. This data is used to improve the plan generation algorithm for future trips, updating the entire system to continuously improve the accuracy of the plans and the ability to respond to emotions.

[0799] For example, if the system recognizes that a user is prone to stress, it can generate a plan that prioritizes activities that help them relax, such as shortening travel time. In this way, the goal is to maximize the user experience by working in conjunction with the emotion engine.

[0800] The following describes the processing flow.

[0801] Step 1:

[0802] Users enter details such as their travel destination, dates, degree of disability, and desired activities using their own devices. This information also includes the purpose of the trip and any individual assistance needed.

[0803] Step 2:

[0804] The terminal collects data entered by the user, organizes that information, and converts it into a format for transmission to the server.

[0805] Step 3:

[0806] The server analyzes user data received from the terminal and uses an emotion engine to process and identify the user's emotional state from the input text.

[0807] Step 4:

[0808] The server searches the database for relevant accessibility information and past feedback information based on the user's emotional state and input information.

[0809] Step 5:

[0810] The server uses AI algorithms to generate customized travel plans that take into account the user's emotional state. This includes available accessibility features, accessible transportation options, and recommended activities.

[0811] Step 6:

[0812] The server sends the generated travel plan to the terminal, allowing the user to review and select it.

[0813] Step 7:

[0814] The terminal displays the plan received from the server to the user, allowing them to view the plan details. The user reviews the plan and selects the one that best suits their needs.

[0815] Step 8:

[0816] Based on their chosen travel plan, users make adjustments as needed to finalize their itinerary.

[0817] Step 9:

[0818] The device sends the user's confirmed plan to the server and initiates the reservation process based on that information.

[0819] Step 10:

[0820] The server completes the reservation process and gathers the necessary information to execute the entire plan. It also uses an emotion engine to respond flexibly when communication with the user is required.

[0821] Step 11:

[0822] After the trip ends, users provide feedback via their device, including comments about their feelings.

[0823] Step 12:

[0824] The device sends feedback data to the server, and the emotion engine analyzes this feedback to gain insights into the emotional state.

[0825] Step 13:

[0826] The server records the feedback in a database and adjusts the algorithm to use it for future plan generation. Through learning by the emotion engine, its planning capabilities improve for subsequent uses.

[0827] (Example 2)

[0828] 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".

[0829] This invention relates to a method for providing personalized travel plans to travelers with disabilities, taking into account their individual emotional states. Conventional travel plans have struggled to adequately reflect the individual needs and emotional states of users, resulting in poor satisfaction. In particular, many plans do not properly incorporate accessibility information that is crucial for travelers with disabilities, making it difficult to provide a safe and satisfying travel experience.

[0830] 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.

[0831] In this invention, the server includes means for receiving information from the user and analyzing the emotional state using machine learning; a processing function for creating a travel schedule that takes accessibility information into consideration using generative AI based on the emotional state and related information; and a control function for presenting the created travel schedule to the user and automatically making reservations, including transportation and accommodation, based on the user's selection. This enables the creation of personalized travel plans that more accurately reflect the user's emotions and individual needs, and allows for flexible responses to changes in plans at any time.

[0832] An "input function" refers to a device or software that allows users to input information about their travel purpose and physical limitations.

[0833] "Information" refers to data provided by the user, including the purpose of travel, the degree of disability, and preferred dates and times.

[0834] "Emotional state" refers to the psychological situation analyzed based on user input information and the emotions reflected in the feedback.

[0835] "Machine learning" is a technology that allows computers to learn patterns and rules from data and improve the algorithms necessary for optimizing travel plans.

[0836] "Generative AI" refers to artificial intelligence that uses machine learning techniques to automatically create personalized travel plans based on emotional states and user information.

[0837] "Accessibility information" refers to data that includes information on the convenience of transportation and facilities necessary for travelers with disabilities to enjoy their trip safely and comfortably.

[0838] "Processing function" refers to the system's ability to automatically generate a travel plan based on the input information and emotional state.

[0839] The "control function" refers to a system feature that automatically handles booking procedures and manages the execution of a travel plan based on the user's selected travel plan.

[0840] The "update function" is a feature that uses user feedback obtained after a trip to update the system's overall information resources and improve the accuracy of the algorithms.

[0841] "Experience feedback" refers to evaluations of opinions and feelings provided by users after a trip, and this data is useful for creating future travel plans.

[0842] The system of the present invention aims to provide personalized travel plans for travelers with disabilities, taking into account the emotional state of each user. Its embodiments are described in detail below.

[0843] The device features an input function for users to enter travel information. This input function allows users to enter details such as the purpose of the trip, the degree of any disabilities, places they wish to visit, and preferred dates and times. This information is crucial data for operating the emotion engine.

[0844] The server uses information received from the terminal to perform sentiment analysis through machine learning. This utilizes natural language processing technology to infer emotions from the user's input. Specifically, it determines the positive or negative nature of the emotion, as well as levels of tension and anticipation, based on the user's expressions and keywords.

[0845] Next, the server uses a generative AI model to generate the optimal travel plan based on the results of the sentiment analysis. This model extracts relevant information from a database that includes accessibility information and personalizes activities, transportation, and accommodations to match the user's emotions.

[0846] The server sends the generated plan back to the terminal, where the user reviews and selects it. Based on the selected plan, the server automatically processes transportation and accommodation reservations, providing an interface that allows for easy modification using drag-and-drop or click operations as needed. This process also integrates with external reservation systems via API connections.

[0847] After the trip is complete, the user enters feedback into their device. This feedback is then sent back to the server and analyzed by the sentiment engine. This information is used as data to improve the algorithm for generating future travel plans.

[0848] For example, if a user inputs an intention such as "I want to relax" or "I want to reduce stress," the AI ​​can be prompted with phrases like "Generate a travel plan that takes the user's emotional state into account" or "How can we use accessibility information and an emotion engine to provide a personalized plan for travelers with disabilities?" This allows the AI ​​to derive more suitable suggestions.

[0849] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0850] Step 1:

[0851] Users use their devices to input information such as the purpose of their trip, the degree of their disability, places they want to visit, and their preferred dates and times. This input information serves as the starting point for data processing throughout the system. The input data is then structured into keywords necessary for personalizing the trip.

[0852] Step 2:

[0853] The terminal sends the data entered by the user to the server as structured data. Specifically, this involves securely and efficiently transmitting the information using a data communication protocol. At this stage, the entered information is converted so that it can be stored in a database.

[0854] Step 3:

[0855] The server activates the emotion engine based on the received data. The emotion engine uses natural language processing algorithms to analyze the user's input and infer their emotional state. For example, it extracts emotional keywords such as "excitement" or "anxiety" and identifies the corresponding emotional state. This analysis outputs the emotional state, which is then used in the next process.

[0856] Step 4:

[0857] The server utilizes a generative AI model based on emotional state and user information to generate the optimal travel plan. Here, accessibility information is retrieved from the database, and data processing is performed to select tourist destinations and activities that meet the user's needs. Specifically, plans are generated by referencing past feedback and using plans provided to users with similar emotional states as a reference.

[0858] Step 5:

[0859] The server sends the generated travel plans to the terminal. The terminal visually presents these to the user, allowing them to select their preferred plan. The input here is a list of generated plans, and the output is the specific plan selected by the user. The user-initiated interface is designed to be intuitively understandable.

[0860] Step 6:

[0861] The terminal receives the user's selection and sends that information back to the server. The server, in conjunction with the reservation management system, automatically executes the reservation process based on the selected plan. At this point, the input is the user's selection information, and the output is the confirmed reservation information. This process is carried out via API calls to an external system.

[0862] Step 7:

[0863] After the trip is complete, the user enters feedback about the experience into a terminal. The entered feedback is sent from the terminal to the server. The server uses the emotion engine again to analyze the emotions in the feedback. This analysis result is later stored in a database and used to improve future plan generation algorithms. Through the processing of feedback, the system is constantly updated, enabling it to provide more accurate plans.

[0864] (Application Example 2)

[0865] 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".

[0866] In recent years, there has been a growing demand for technologies that enhance the travel experience for travelers with disabilities. However, conventional systems are insufficient in suggesting personalized travel plans and relevant content that take user emotions into account. As a result, traveler satisfaction is low, and it is difficult to achieve a comfortable travel experience.

[0867] 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.

[0868] In this invention, the server includes an analysis means for receiving input data from the user and analyzing their emotions in real time, a processing means for generating a travel plan that takes accessibility information into consideration based on the emotion analysis results, and a control means for presenting content related to the generated travel plan to the user and performing a reservation procedure based on the user's selection. This makes it possible to provide travelers with disabilities with an optimal travel plan and related content that is tailored to their emotions.

[0869] The "analysis method for analyzing user emotions" is a function that grasps the user's emotional state in real time based on input data and provides information necessary for adjusting travel plans.

[0870] The "processing method for generating travel plans that take accessibility information into consideration" is a function that, based on sentiment analysis and various data, selects transportation methods, accommodations, and tourist facilities that can be comfortably used by travelers with disabilities, and then constructs a travel plan.

[0871] "A control means for presenting content related to the generated travel plan to the user and performing booking procedures" refers to a function that presents the generated travel plan to the user visually or audibly and performs bookings and arrangements based on the user's selections.

[0872] "An update mechanism to collect user feedback and update the database to improve the accuracy of information" refers to a function that collects user feedback and opinions after a trip, updates the information in the database based on this feedback, and improves the accuracy of generating future travel plans.

[0873] This invention aims to construct a system that provides personalized travel plans and content to travelers with disabilities using emotion analysis. The system is primarily based on data processing and communication between three parties: a terminal, a server, and the user.

[0874] The terminal receives input information from the user, such as the purpose of travel, the degree of disability, and desired destinations, through an application installed on a device like a smartphone or head-mounted display. This information is crucial data for real-time sentiment analysis. The terminal uses the Emotion API to read emotions from the user's facial expressions and voice, and sends this data to the server in a structured format.

[0875] On the server, an analysis tool identifies emotions based on the received data, and the analysis results are used to create a travel plan. Past feedback and the latest information on accessibility are retrieved from the database. This information is processed by an AI algorithm (using TensorFlow) to automatically generate a travel plan optimized for the user's emotions and situation. This plan includes transportation, accommodation, and relaxing activities tailored to the user's state and requests.

[0876] The user visually reviews the suggested travel plan via their device and sends their selected options back to the server. The server then flexibly handles the necessary booking procedures based on this selection. At the end of the trip, user feedback is collected, and emotional information is analyzed again using the Emotion API. This information is used to update the database to improve the accuracy of future plan generation.

[0877] For example, if a user is looking for a relaxing travel destination, the system will recognize the user's emotion as "relaxation" and then provide information about natural tourist destinations. Such a system is designed to allow users to enjoy a more personalized travel experience.

[0878] Example prompt for a generative AI model: "Please advise on what kind of tourist information and content should be provided when a user is feeling stressed."

[0879] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0880] Step 1:

[0881] The user uses a terminal to input the purpose of their trip, the degree of their disability, desired destinations, and preferred dates and times. The terminal receives this user input as structured data and sends it to the server. The input includes text and voice data, resulting in structured data that is sent to the server as output.

[0882] Step 2:

[0883] The server receives structured data sent from the terminal and analyzes the user's emotions in real time using the Emotion API. This analysis determines the user's emotional state, and as a result, data indicating the emotion is generated. The input is structured data, and the output is the analyzed emotional state data.

[0884] Step 3:

[0885] The server retrieves relevant accessibility information from the database based on the sentiment analysis results. Here, SQL queries are used to search the database and extract information suitable for travelers with disabilities. The input is sentiment state data, and the output is accessibility information.

[0886] Step 4:

[0887] The server generates an optimal travel plan using an AI algorithm (TensorFlow) based on the sentiment analysis results and acquired accessibility information. Sentiment data and accessibility information are used for data calculations, and a customized travel plan is obtained as output.

[0888] Step 5:

[0889] The terminal visually displays a travel plan transmitted from the server to the user. The user reviews the presented plan and makes a decision. The input is a customized travel plan, and the output is the user's selection.

[0890] Step 6:

[0891] The terminal, upon receiving the user's selection, sends that information back to the server and requests the reservation process. The server then works in conjunction with the reservation system to proceed with registration and arrangements. The input is the user's selection, and the output is a reservation completion confirmation.

[0892] Step 7:

[0893] After completing their trip, the user enters feedback about their experience into their device. The device sends this information to a server, which then uses the Emotion API again to analyze the emotional information. The input is the user's feedback, and the output is the emotional analysis data.

[0894] Step 8:

[0895] The server updates the database based on feedback information and stores data to be used in future plan generation. Data processing learns from newly acquired information and contributes to improving the algorithm. The input is feedback data, and the output is the updated database.

[0896] 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.

[0897] 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.

[0898] 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 robot 414.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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."

[0905] 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.

[0906] 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.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] 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.

[0911] 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.

[0912] 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.

[0913] 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.

[0914] 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.

[0915] 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.

[0916] 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 as being incorporated by reference.

[0917] The following is further disclosed regarding the embodiments described above.

[0918] (Claim 1)

[0919] An input method for the user to enter the purpose of their trip and the degree of their disability,

[0920] A processing means that receives input data from a user and generates a travel plan that takes accessibility information into consideration,

[0921] A control means that presents a generated travel plan to the user and performs the booking procedure based on the user's selection,

[0922] A means of updating the database to collect user feedback after the trip and improve the accuracy of the information,

[0923] A system that includes this.

[0924] (Claim 2)

[0925] The system according to claim 1, further comprising a learning means for adjusting the travel plan generation algorithm based on user feedback and improving generation accuracy.

[0926] (Claim 3)

[0927] The system according to claim 1, comprising an optimization means for analyzing user input data and feedback and optimizing the information to reflect in the next plan proposal.

[0928] "Example 1"

[0929] (Claim 1)

[0930] An input method for users to enter their travel goals and the degree of their obstacles,

[0931] A calculation means that receives input information from the user and constructs a travel plan considering accessibility information and data corresponding to the user's disability,

[0932] A control means for generating an optimal travel plan using a generative AI model and presenting it to the user,

[0933] A means of updating the database based on user feedback and continuously improving the accuracy of the information,

[0934] A means of communication for collecting and transmitting user feedback in order to improve the quality of travel planning,

[0935] A system that includes this.

[0936] (Claim 2)

[0937] The system according to claim 1, further comprising a learning means for adjusting the travel plan generation algorithm based on user feedback and improving generation accuracy.

[0938] (Claim 3)

[0939] The system according to claim 1, comprising optimization means for analyzing user input information and feedback and optimizing the information to reflect in the next plan proposal.

[0940] "Application Example 1"

[0941] (Claim 1)

[0942] An input method for the user to enter the purpose of their trip and the degree of their disability,

[0943] A processing means that receives input data from a user and generates a travel plan that takes accessibility information into consideration,

[0944] A control means that presents a generated travel plan to the user and performs the booking procedure based on the user's selection,

[0945] A display method that allows users to visually experience a travel plan within a virtual environment,

[0946] A means of updating the database to collect user feedback after the trip and improve the accuracy of the information,

[0947] A system that includes this.

[0948] (Claim 2)

[0949] The system according to claim 1, further comprising a learning means for adjusting the travel plan generation algorithm based on user feedback and improving generation accuracy.

[0950] (Claim 3)

[0951] The system according to claim 1, comprising an optimization means for analyzing user input data and feedback and optimizing the information to reflect in the next plan proposal, and a function for simulating a travel experience using a virtual reality device.

[0952] "Example 2 of combining an emotion engine"

[0953] (Claim 1)

[0954] An input function for users to enter information about their travel purpose and physical limitations,

[0955] A function that receives information from users and analyzes their emotional state using machine learning,

[0956] A processing function that uses generative AI to create a travel schedule that takes accessibility information into consideration, based on emotional state and related information.

[0957] A control function that presents the created travel schedule to the user and automatically makes reservations, including transportation and accommodation, based on the user's selections.

[0958] After the trip ends, we collect and analyze user feedback on their experience, along with sentiment data, and update information resources for future improvements.

[0959] A system that includes this.

[0960] (Claim 2)

[0961] The system according to claim 1, having a learning function for adaptively learning the algorithm to improve the accuracy of generating travel schedules based on user feedback and sentiment analysis results.

[0962] (Claim 3)

[0963] The system according to claim 1, comprising a function that analyzes both the initial input information and feedback from the user and optimizes the information to be reflected in the next travel suggestion.

[0964] "Application example 2 of combining emotional engines"

[0965] (Claim 1)

[0966] An input method for the user to enter the purpose of their trip and the degree of their disability,

[0967] An analytical means that receives input data from users and analyzes emotions in real time,

[0968] A processing means for generating a travel plan that takes into account accessibility information based on the results of emotion analysis,

[0969] A control means that presents content related to the generated travel plan to the user and performs the booking procedure based on the user's selection,

[0970] A means of updating the database to collect user feedback after the trip and improve the accuracy of the information,

[0971] A system that includes this.

[0972] (Claim 2)

[0973] The system according to claim 1, further comprising a learning means for adjusting the travel plan generation algorithm based on user feedback and improving generation accuracy.

[0974] (Claim 3)

[0975] The system according to claim 1, comprising an optimization means for analyzing user input data and feedback and optimizing the information using an emotion analysis engine to reflect it in the next plan proposal. [Explanation of Symbols]

[0976] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for the user to enter the purpose of their trip and the degree of their disability, A processing means that receives input data from a user and generates a travel plan that takes accessibility information into consideration, A control means that presents a generated travel plan to the user and performs the booking procedure based on the user's selection, A means of updating the database to collect user feedback after the trip and improve the accuracy of the information, A system that includes this.

2. The system according to claim 1, further comprising a learning means for adjusting the travel plan generation algorithm based on user feedback and improving generation accuracy.

3. The system according to claim 1, comprising an optimization means for analyzing user input data and feedback and optimizing the information to reflect in the next plan proposal.

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