system

Abstract

We provide the system. [Solution] A data collection method for generating an optimized travel plan based on the user's preferences, budget, and travel style, External data acquisition methods for obtaining travel-related information from other travel booking platforms, An artificial intelligence processing system that formulates personalized travel suggestions based on user information, A means of providing real-time local information and information notifications that reflect the latest travel conditions to users, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a 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 conventional travel reservation services, it is difficult to achieve individual optimization according to travelers' preferences, budgets, and travel styles, and real-time information provision during travel is not sufficient. Therefore, there is a problem that it is difficult for travelers to enjoy their trips without stress. In particular, problems such as the time-consuming process of formulating travel plans, lack of local information, and difficulty in real-time information update have emerged. By solving these problems, it is desired to enable users to enjoy a smoother and more fulfilling travel experience.

Means for Solving the Problems

[0005] This invention includes data collection means for generating an optimized travel plan based on the user's preferences, budget, and travel style, and external data acquisition means for obtaining travel-related information from other travel booking platforms. Furthermore, it includes artificial intelligence processing means for formulating personalized travel suggestions based on user information, and implements information notification means for providing local information in real time and reflecting the latest travel conditions to the user, thereby solving the above problems. This resolves the problems that conventional systems had and realizes the provision of an ideal travel experience for the user.

[0006] "User" refers to an individual or group that uses the system to plan their trip.

[0007] "Preferences" refer to the personal tastes and preferences of users, and are factors that influence their travel choices.

[0008] "Budget" refers to the financial limit that a user plans to allocate to their trip.

[0009] "Travel style" refers to a user's attitude towards travel, their methods, and their specific behavioral patterns.

[0010] A "travel plan" refers to a document that includes details about the trip, such as accommodation, transportation, and activities.

[0011] "Data collection methods" refer to the methods and technologies used to collect user information.

[0012] "Travel-related information" refers to all information related to travel, including accommodations, flights, and local activities.

[0013] "Other travel booking platforms" refers to existing online or offline travel booking services.

[0014] "External data acquisition means" refers to a mechanism for collecting data from other systems or services.

[0015] The "artificial intelligence processing means" refers to the AI technology used to process information and generate travel proposals optimized for users.

[0016] The "information notification means" refers to the method or process for providing necessary information to users in real time.

Brief Description of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0021] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] The system according to the present invention enables the suggestion of optimized travel plans based on the user's preferences, budget, and travel style. This system consists of a server, a terminal, and user interaction.

[0039] The server generates a travel plan optimized for the user based on information provided by the user via their device. Specifically, the server collects information such as the user's travel preferences and budget, and uses this to retrieve relevant data from existing travel booking services. Using artificial intelligence processing, it analyzes this data and formulates the optimal travel plan for the user. This process includes selecting accommodations and flights, and recommending activities at the travel destination.

[0040] Meanwhile, the terminal assists users in inputting information through its user interface and displays optimized travel plans sent from the server. Furthermore, the terminal provides real-time information during the trip, informing users of local weather and event information.

[0041] Users can provide feedback on their travel plans to the server via their device. This allows the server to re-optimize the travel plan and dynamically adjust the itinerary to meet the user's needs. This interaction ensures that users always have an ideal travel experience.

[0042] As a concrete example, consider a scenario where a user wants to travel to Europe during their next vacation. The user uses their device to select the countries and cities they want to visit and set a budget. Based on the user's selections, the server retrieves necessary data from major travel booking services and develops a plan suggesting optimal accommodations and sightseeing activities. Furthermore, if any new events occur during the trip, the device provides the user with this information in real time, allowing for corresponding changes to the plan.

[0043] Thus, the present invention is designed to provide users with a smooth and efficient travel experience, enabling flexible planning tailored to individual needs and real-time information notifications.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] Users create an account and log in using their device. Users enter information such as their travel preferences, budget, and purpose.

[0047] Step 2:

[0048] The terminal recognizes the user's input information and sends it to the server. The server receives this information and stores it in its database.

[0049] Step 3:

[0050] The server collects relevant data through APIs of external travel booking services. This includes information on accommodations, transportation, and activities.

[0051] Step 4:

[0052] The server uses AI algorithms to analyze the collected information and generate travel plans optimized for the user's preferences and budget.

[0053] Step 5:

[0054] The server sends the generated travel plan to the user's terminal. The terminal receives it and displays it to the user.

[0055] Step 6:

[0056] Users review the displayed travel plan and provide feedback as needed, such as requesting changes or additions to specific activities.

[0057] Step 7:

[0058] The server receives feedback from the user and readjusts the travel plan. It generates new suggestions and resends them to the user's device.

[0059] Step 8:

[0060] During their trip, users request real-time information through their devices, including local weather and event information.

[0061] Step 9:

[0062] The server collects real-time information and sends it to the user's device. The device then presents this information to the user to assist in decision-making during their trip.

[0063] (Example 1)

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

[0065] Modern travelers spend a lot of time creating appropriate travel plans based on their individual preferences and budgets, and it is also difficult for them to quickly adapt to changing conditions during their trip. Furthermore, there are challenges in dynamically readjusting plans to reflect traveler feedback and providing information that takes into account the diverse cultural backgrounds of the local area.

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

[0067] In this invention, the server includes an information receiving means, an external information acquisition means, and an artificial intelligence analysis means. This allows travelers to obtain individually optimized travel plans based on their preferences and feedback, and enables them to flexibly respond to changes during their trip through the provision of real-time information.

[0068] "Information receiving means" refers to a means of receiving and recording travel-related information provided by users.

[0069] "External information acquisition means" refers to methods for collecting travel-related data from other databases and information sources to obtain necessary information.

[0070] "Artificial intelligence analysis means" refers to a method for analyzing acquired data and creating travel suggestions optimized for the user.

[0071] "Information provision methods" refer to means of providing users with the latest travel-related information in real time and supporting their travel experience.

[0072] "Update mechanisms" refer to methods for dynamically modifying existing travel plans based on user feedback and reconstructing improved plans.

[0073] The system according to the present invention aims to provide optimized travel plans based on the user's travel needs. This system consists of a server, a terminal, and interaction with the user.

[0074] The server collects data provided by users through information receiving means (such as travel destinations, budgets, and travel styles). Based on this information, it uses external information acquisition means to retrieve necessary information from travel-related databases on the internet. This data includes information on flights, accommodations, and tourist attractions. The server uses a generative AI model and artificial intelligence analysis means to process this information and generate the optimal travel plan for the user.

[0075] The terminal provides a user interface, allowing users to easily input information and view optimized travel plans sent from the server. It also features real-time information provision capabilities, providing users with local weather information, event information, and other relevant details during their trip.

[0076] Users can provide feedback on their travel plans to the server via their devices. The server receives this feedback and dynamically adjusts the travel plans using update mechanisms to respond to the user's changing needs.

[0077] For example, if a user wants to travel to various parts of Asia for their next vacation, they select the cities they want to visit (e.g., Tokyo, Seoul, Bangkok) and enter their budget via the device. Based on these conditions, the server collects relevant information from travel booking services and generates a plan suggesting the best flights, accommodations, and activities. Furthermore, if an event matching the user's interests occurs during the trip, the device provides that information in real time, making it easier to adjust the travel plan.

[0078] An example of a prompt sentence to input into a generative AI model might be: "I would like to visit Asia on my next vacation. Planned cities: Tokyo, Seoul, Bangkok. Budget: $1500. Activities of interest: Participating in local festivals, cooking experiences."

[0079] In this way, the combination of functions within this system allows users to always obtain the latest and most optimized travel experience.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] Users use their devices to input their travel preferences. Specifically, they select and enter their destination, budget, and activities of interest. This information about the user's travel preferences is then saved on the device in a list format. This input forms the basis for sending data to the server.

[0083] Step 2:

[0084] The terminal sends the information entered by the user to the server. The server receives this information through an information receiving device. The data received by the server includes the name of the travel destination, the budget, and the type of activity. Based on this information, the server prepares to obtain the basic data necessary to generate a travel plan.

[0085] Step 3:

[0086] The server uses external information acquisition methods to collect information from travel-related databases on the internet. For example, it obtains hotel rates and availability for the selected travel destination, flight schedules, and details of tourist facilities. This acquired data will be used for analysis in the next step.

[0087] Step 4:

[0088] The server processes the acquired information using artificial intelligence analysis methods based on a generation AI model. This process combines the acquired data to generate the optimal travel plan that best matches the conditions specified by the user. For example, when selecting accommodation, the analysis considers price, location, and the user's interests (e.g., a night view). As a result, specific accommodations and activities are suggested.

[0089] Step 5:

[0090] The server sends the generated travel plan to the terminal. The terminal displays this visually to the user. The user can review the suggested accommodations, flights, and activities, and either accept them or request changes if necessary. This output forms the basis of the user's optimal itinerary.

[0091] Step 6:

[0092] Users send feedback on their travel plans to the server via their devices. This feedback includes requests for changes to accommodation dates and additional activities. The server receives the feedback, adjusts the plan using update mechanisms, and generates a revised plan. This re-optimizes the itinerary to suit the user's preferences.

[0093] Step 7:

[0094] Once the trip begins, the device uses real-time information delivery methods to notify the user of local weather and event information. This allows the user to check the latest information at their destination at any time and adjust their schedule as needed. This information enhances the user's travel experience.

[0095] (Application Example 1)

[0096] 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."

[0097] For travelers visiting urban areas, finding efficient and interesting sightseeing routes can be difficult. Furthermore, dynamic route adjustments that adapt to changing traffic conditions and weather are necessary, but current technology struggles to meet these needs. Additionally, there is a lack of multilingual local information and personalized recommendations based on user preferences.

[0098] 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.

[0099] In this invention, the server includes data collection means, external data acquisition means, artificial intelligence processing means, information notification means, and integrated information processing means that integrate urban tourism and traffic information and provide dynamic tourist routes. This allows travelers to obtain individually optimized tourist routes and to flexibly respond to changes in traffic conditions and weather.

[0100] "Data collection means" refers to devices or processes for collecting information such as users' preferences, budgets, and travel styles.

[0101] "External data acquisition means" refers to a device or process for acquiring travel-related information from other travel booking platforms or information sources.

[0102] "Artificial intelligence processing means" refers to a computer program or system that analyzes collected data and formulates personalized travel suggestions for users.

[0103] "Information notification means" refers to a device or process for providing users with the latest travel conditions and local information in real time.

[0104] "Integrated information processing means" refers to a device or process for integrating urban tourism information and traffic information to provide users with dynamic and optimized tourist routes.

[0105] To realize this invention, a system using a server and terminals is constructed. The server collects information about the user's preferences, budget, and travel style using data collection means. This includes data entered by the user into the terminal. The server also obtains travel-related information from other travel booking platforms using external data acquisition means. This process is achieved, for example, by obtaining the necessary data through an external API.

[0106] The server uses artificial intelligence processing to analyze the collected data and formulate personalized travel suggestions for users. For example, it may use AI frameworks such as TENSORFLOW® to analyze the user's past choices and the trends of similar users.

[0107] Furthermore, the server provides users' devices with real-time local information and the latest travel conditions through information notification mechanisms. At this stage, push notifications are used to quickly communicate information about events and traffic changes occurring in the city where the user is traveling.

[0108] Through integrated information processing, the server combines urban tourism and traffic information to provide users with dynamic and optimized sightseeing routes. Real-time route changes are also possible, allowing users to enjoy the most efficient travel experience.

[0109] For example, if a user is visiting Tokyo, they would input their preferences, such as "I like sushi and want to visit interesting spots in Tokyo." Based on this information, the server would create an optimized sightseeing route and immediately notify the user's device. If the weather deteriorates, the plan can be changed to an indoor activity.

[0110] An example of a prompt to input into the generating AI model would be: "A user is planning a sightseeing route in Tokyo. They like sushi and have a budget of 10,000 yen. Please suggest the best route, taking into account alternatives for rainy weather."

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] Users input information about their preferences, budget, and travel style using a terminal. This entered data is sent to the server. The user's input clarifies their travel preferences and budget constraints, serving as the basis for the server to generate subsequent suggestions.

[0114] Step 2:

[0115] The server receives and stores information sent from users using data collection methods. Next, it obtains travel-related information from other travel booking platforms through external data acquisition methods. The server aggregates relevant travel information using APIs, thereby expanding travel options.

[0116] Step 3:

[0117] The server uses artificial intelligence processing to analyze user information and data acquired from external sources to generate personalized travel suggestions. Specifically, data calculations involve analyzing past user data and similar trends, and an optimized travel plan is created using a generative AI model. Suggestions are prepared to match the user's preferences and budget.

[0118] Step 4:

[0119] The server sends travel suggestions generated using an information notification system to the terminal. The user receives this and reviews the suggested plan. Information notifications are provided in real time, allowing users to select or modify their travel schedule.

[0120] Step 5:

[0121] The user reviews the proposed travel plan and provides feedback as needed. The server receives this feedback and dynamically modifies the travel plan. Based on travel conditions and user requests, the plan is recalculated and a new proposal is made.

[0122] Step 6:

[0123] During your trip, the server provides real-time local information through your device. Based on traffic conditions and weather changes, the server uses integrated information processing to dynamically adjust your sightseeing route. This ensures that you always have access to the optimal route.

[0124] Step 7:

[0125] After the trip ends, users provide detailed feedback on their travel experience. The server uses this information to optimize future trips, contributing to overall system accuracy improvements. This cycle enables a better user experience.

[0126] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0127] This invention further enhances the personalized travel experience by integrating an emotion engine that recognizes user emotions, in addition to conventional travel suggestion systems. This system consists of a server, a terminal, and user interaction.

[0128] First, the server receives information from the user, such as preferences, budget, and travel style, and stores it in a database. The terminal collects this information from the user and sends it to the server. The server also retrieves travel-related information from other travel booking platforms based on the user information and generates the optimal plan.

[0129] A distinctive feature of this invention is the incorporation of an emotion engine. The terminal uses a camera, microphone, and sensors to collect and analyze the emotions the user is experiencing during their trip. The server determines the user's current emotional state from the acquired emotion data and adjusts the travel experience provided to be optimized according to changes in emotions.

[0130] For example, if the emotion engine detects that a user is feeling dissatisfied at a certain point during their trip, the server can immediately restructure the plan and suggest alternative activities or sightseeing destinations. Similarly, if the server recognizes that the user is experiencing a very high level of emotion, it can make suggestions to maintain that emotion (e.g., tickets to a special event or recommendations for special interactions).

[0131] This kind of collaboration allows users to always enjoy a travel experience that matches their mood at any given time. The device notifies the user of updates from the server in real time and continuously provides appropriate feedback that reflects their emotional state. Through the collaboration of the server and the emotion engine, users can enjoy their travels with a higher level of satisfaction.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] The user enters travel information using a terminal. This includes various information such as preferences, budget, and travel style. The terminal collects this information and sends it to the server.

[0135] Step 2:

[0136] Based on the information received from the terminal, the server retrieves travel-related data from other travel booking platforms. This includes accommodation, transportation, and activity options.

[0137] Step 3:

[0138] The server uses artificial intelligence processing to analyze the acquired data and generate a travel plan optimized for the user's preferences and budget.

[0139] Step 4:

[0140] The emotion engine uses the device's camera and microphone to collect emotional data such as the user's voice and facial expressions. The device then sends this data to a server.

[0141] Step 5:

[0142] The server analyzes the received emotional data to determine the user's current emotional state. For example, if the user is feeling anxious, it identifies the cause and suggests activities that can help them relax.

[0143] Step 6:

[0144] The server readjusts the travel plan in response to changes in emotions. If necessary, it generates suggestions for new activities and tourist destinations and updates the plan.

[0145] Step 7:

[0146] The device receives update information from the server and notifies the user in real time. Based on this, the user can decide on their next course of action.

[0147] Step 8:

[0148] Users can provide feedback through their devices. The server uses this feedback to further refine the plan and continue to provide the best possible travel experience.

[0149] (Example 2)

[0150] 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".

[0151] Conventional travel suggestion systems could only offer suggestions based on users' fixed preferences and conditions, making it difficult to provide personalized services that could respond immediately to changes in users' emotions and circumstances during their trip. Furthermore, they lacked sufficient real-time information updates, making them unable to adapt to dynamic local conditions.

[0152] 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.

[0153] In this invention, the server includes information gathering means for generating an optimized travel plan based on the user's preferences, budget, and travel style; external information acquisition means for obtaining travel-related information from other booking platforms; and emotion detection means for detecting the user's emotional state and dynamically adjusting the plan accordingly. This makes it possible to provide a personalized travel experience that responds to changes in the user's emotions and circumstances.

[0154] "Information gathering means" refers to technologies or functions for efficiently collecting personal information such as users' preferences, budgets, and travel styles.

[0155] "External information acquisition means" refers to technologies or functions for obtaining travel-related information from other booking platforms or information sources.

[0156] "Artificial intelligence processing means" refers to AI technology or algorithms used to formulate personalized suggestions based on user information.

[0157] "Notification means" refers to technologies or functions that provide users with real-time local information and updates, and that reflect the latest conditions.

[0158] "Emotion detection means" refers to a technology or function that detects the user's emotional state and dynamically adjusts the travel plan based on that information.

[0159] This invention provides technology for a travel suggestion system that offers a personalized travel experience that takes into account the user's emotional state. This system is implemented through interaction between a server, a terminal, and the user.

[0160] First, the device collects information from the user about their preferences, budget, and travel style. This is done using an interface built into the device, which the user enters. This information is then encrypted and sent to the server.

[0161] The server stores the received information in a database and performs analysis. The server uses external information acquisition means to obtain travel-related information from other travel booking platforms. Furthermore, it uses artificial intelligence processing means to generate optimized travel plans based on user information. This system also includes emotion detection means to receive emotion data from the terminal. This allows the system to analyze the user's emotional state and dynamically adjust the travel plan.

[0162] As a concrete example, suppose a user uses a device and receives suggestions for potential tourist destinations and events they might visit while planning a trip. At this point, the device's camera and sensors collect the user's emotional data and send it to a server. The server analyzes this data, and if the user's emotions are heightened, it can suggest special events or activities to maintain those emotions.

[0163] For example, the following prompt could be used with a generative AI model: "The user is dissatisfied with their current trip. As an alternative, suggest a guided tour of a nearby nature park. Also, if they are excited, consider offering them VIP tickets to a local festival currently taking place at their destination."

[0164] Based on this prompt, the AI ​​model generates a new travel plan and notifies the user of the results in real time via their device. This allows users to enjoy the optimal travel experience tailored to their emotions and circumstances at the time.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The user enters information about their travel preferences, budget, and travel style into the device. The device collects, encrypts, and temporarily stores this information. The entered data includes details about the tourist destinations they want to visit and the activities they wish to do. This information is sent directly to the server for later analysis.

[0168] Step 2:

[0169] User information is sent from the terminal to the server. The server receives this data and stores it in a database. Based on the received information, the server begins data analysis and integrates information from external travel booking platforms. This transforms it into a comprehensive dataset that also takes into account the travel history of other users and current trends.

[0170] Step 3:

[0171] The server generates travel plans based on collected data. Using artificial intelligence processing, it analyzes past data and patterns to create optimized travel plans. The generated plans include planned tourist destinations, activities, and accommodations. Here, prompts are input into the AI ​​model to generate new ideas and suggestions.

[0172] Step 4:

[0173] The device collects user emotional data during travel. Using cameras, microphones, and sensors, it analyzes the user's facial expressions, voice, and physical reactions in real time. This data is sent to a server to evaluate the user's emotional state.

[0174] Step 5:

[0175] The server analyzes emotional data sent from the terminal. The server determines the user's emotions during the trip and dynamically reconfigures the travel plan based on the results. For example, if the user expresses dissatisfaction, it suggests alternative tourist destinations or activities. These suggestions are generated using a generative AI model.

[0176] Step 6:

[0177] The device notifies the user in real time of updated plans and suggestions. The user can review these and adjust their travel plans based on the new suggestions. Pop-up notifications appear on the device, and a voice assistant provides explanations, offering user-friendly feedback.

[0178] (Application Example 2)

[0179] 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".

[0180] Traditional travel suggestion systems have optimized travel plans based on user preferences and budgets, but they have a weakness in that they lack personalization that takes user emotions into account. In particular, the inability to dynamically optimize the travel experience in response to changes in emotions during the trip has been an obstacle to increasing user satisfaction.

[0181] 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.

[0182] In this invention, the server includes data collection means for generating an optimized travel plan based on the user's preferences, budget, and travel style; external data acquisition means for obtaining travel-related information from other travel booking platforms; and emotion analysis means for performing emotion recognition. This enables the dynamic optimization of the travel experience in response to the user's emotions.

[0183] "Data collection means" refers to functions for collecting information related to users' preferences, budgets, and travel styles.

[0184] "External data acquisition means" refers to a function that allows you to obtain information necessary for optimizing your travel plan from other travel booking platforms.

[0185] "Artificial intelligence processing means" refers to a function that processes data to formulate personalized travel suggestions based on acquired user information.

[0186] "Information notification means" refers to a function that notifies users of the latest local travel conditions in real time.

[0187] "Emotional analysis means" refers to a function for recognizing and analyzing the user's emotions, using user interfaces and sensor data.

[0188] The "proposal adjustment mechanism" is a function that dynamically adjusts travel plans to provide a travel experience that responds to the user's emotions.

[0189] The implementation of this system requires data collection means, external data acquisition means, artificial intelligence processing means, information notification means, sentiment analysis means, and proposal adjustment means.

[0190] The server collects information such as user preferences, budget, and travel style using data collection methods. This allows the server to understand the user's individualized requests. Subsequently, it obtains travel-related information from other travel booking platforms via external data acquisition methods. This external data includes destination attractions, accommodations, transportation options, and local events.

[0191] The device uses sensors such as cameras and microphones to collect emotions from the user's facial expressions and voice, and analyzes this data using emotion analysis tools. The results of this analysis are sent to a server, where artificial intelligence processing tools construct an optimal travel experience tailored to the user's emotions.

[0192] Based on user sentiment information, the server dynamically adjusts the travel plan and provides real-time feedback to the user through the terminal's information notification system. This makes it possible to provide the user with the most comfortable and satisfying travel experience.

[0193] For example, if the emotion analysis system determines that a user is experiencing stress at a particular tourist destination during a trip, the server can immediately suggest alternative tourist destinations or activities to alleviate the situation. Conversely, if the user is having a great time, suggestions will be made to encourage participation in events that will help maintain that positive feeling.

[0194] Using a generative AI model, an example of a prompt message for this system to function is: "Design a system that senses the user's emotional changes in real time during travel and suggests the most suitable sightseeing activities based on those emotions. Use facial expressions and voice data for emotion recognition."

[0195] This enables personalized travel experiences that cater to a range of emotions during the journey.

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

[0197] Step 1:

[0198] The server collects basic data about the user's preferences, budget, and travel style using data collection methods. At this stage, various information entered by the user through the application is stored in the database. The input data includes the user's preferences, budget, and travel style, and a user profile is formed based on this data.

[0199] Step 2:

[0200] The server collects comprehensive travel information related to the destination from other travel booking platforms via external data acquisition means. This information includes attractions, accommodations, transportation, and event information. This external information is analyzed to create a comprehensive list of travel options, preparing for the next process.

[0201] Step 3:

[0202] The device's sensing capabilities collect real-time emotional data through the user's facial expressions and voice. Using the camera and microphone, it acquires raw emotional data such as changes in the user's facial expressions and tone of voice. The input consists of visual and auditory data, which is processed by emotion analysis tools to identify the emotional state.

[0203] Step 4:

[0204] The server uses artificial intelligence processing to personalize the travel experience based on emotional data obtained through emotion analysis. Here, it combines the user's emotional state and preference profile to generate optimal sightseeing activities and itinerary modifications. The output is a new travel plan best suited to the user's current emotions.

[0205] Step 5:

[0206] The server notifies users in real time of new travel plans and sightseeing activities suggested by the server through the terminal's information notification system. Users receive these suggestions through screen displays and voice guidance and select their next action. In this step, the optimal travel options for the user are specifically presented as output.

[0207] Step 6:

[0208] The system is continuously optimized by collecting user feedback on the device and sending it back to the server. Users input their satisfaction with suggested activities and any new requests, which are then used to process and analyze the data again. This process enables further personalization and optimization of the experience.

[0209] 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.

[0210] 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.

[0211] 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.

[0212] [Second Embodiment]

[0213] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0214] 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.

[0215] 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).

[0216] 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.

[0217] 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.

[0218] 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).

[0219] 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.

[0220] 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.

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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".

[0225] The system according to the present invention enables the suggestion of optimized travel plans based on the user's preferences, budget, and travel style. This system consists of a server, a terminal, and user interaction.

[0226] The server generates a travel plan optimized for the user based on information provided by the user via their device. Specifically, the server collects information such as the user's travel preferences and budget, and uses this to retrieve relevant data from existing travel booking services. Using artificial intelligence processing, it analyzes this data and formulates the optimal travel plan for the user. This process includes selecting accommodations and flights, and recommending activities at the travel destination.

[0227] Meanwhile, the terminal assists users in inputting information through its user interface and displays optimized travel plans sent from the server. Furthermore, the terminal provides real-time information during the trip, informing users of local weather and event information.

[0228] Users can provide feedback on their travel plans to the server via their device. This allows the server to re-optimize the travel plan and dynamically adjust the itinerary to meet the user's needs. This interaction ensures that users always have an ideal travel experience.

[0229] As a concrete example, consider a scenario where a user wants to travel to Europe during their next vacation. The user uses their device to select the countries and cities they want to visit and set a budget. Based on the user's selections, the server retrieves necessary data from major travel booking services and develops a plan suggesting optimal accommodations and sightseeing activities. Furthermore, if any new events occur during the trip, the device provides the user with this information in real time, allowing for corresponding changes to the plan.

[0230] Thus, the present invention is designed to provide users with a smooth and efficient travel experience, enabling flexible planning tailored to individual needs and real-time information notifications.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] Users create an account and log in using their device. Users enter information such as their travel preferences, budget, and purpose.

[0234] Step 2:

[0235] The terminal recognizes the user's input information and sends it to the server. The server receives this information and stores it in its database.

[0236] Step 3:

[0237] The server collects relevant data through APIs of external travel booking services. This includes information on accommodations, transportation, and activities.

[0238] Step 4:

[0239] The server uses AI algorithms to analyze the collected information and generate travel plans optimized for the user's preferences and budget.

[0240] Step 5:

[0241] The server sends the generated travel plan to the user's terminal. The terminal receives it and displays it to the user.

[0242] Step 6:

[0243] Users review the displayed travel plan and provide feedback as needed, such as requesting changes or additions to specific activities.

[0244] Step 7:

[0245] The server receives feedback from the user and readjusts the travel plan. It generates new suggestions and resends them to the user's device.

[0246] Step 8:

[0247] During their trip, users request real-time information through their devices, including local weather and event information.

[0248] Step 9:

[0249] The server collects real-time information and sends it to the user's device. The device then presents this information to the user to assist in decision-making during their trip.

[0250] (Example 1)

[0251] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0252] Modern travelers spend a lot of time creating appropriate travel plans based on their individual preferences and budgets, and it is also difficult for them to quickly adapt to changing conditions during their trip. Furthermore, there are challenges in dynamically readjusting plans to reflect traveler feedback and providing information that takes into account the diverse cultural backgrounds of the local area.

[0253] 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.

[0254] In this invention, the server includes an information receiving means, an external information acquisition means, and an artificial intelligence analysis means. This allows travelers to obtain individually optimized travel plans based on their preferences and feedback, and enables them to flexibly respond to changes during their trip through the provision of real-time information.

[0255] "Information receiving means" refers to a means of receiving and recording travel-related information provided by users.

[0256] "External information acquisition means" refers to methods for collecting travel-related data from other databases and information sources to obtain necessary information.

[0257] "Artificial intelligence analysis means" refers to a method for analyzing acquired data and creating travel suggestions optimized for the user.

[0258] "Information provision methods" refer to means of providing users with the latest travel-related information in real time and supporting their travel experience.

[0259] "Update mechanisms" refer to methods for dynamically modifying existing travel plans based on user feedback and reconstructing improved plans.

[0260] The system according to the present invention aims to provide optimized travel plans based on the user's travel needs. This system consists of a server, a terminal, and interaction with the user.

[0261] The server collects data provided by users through information receiving means (such as travel destinations, budgets, and travel styles). Based on this information, it uses external information acquisition means to retrieve necessary information from travel-related databases on the internet. This data includes information on flights, accommodations, and tourist attractions. The server uses a generative AI model and artificial intelligence analysis means to process this information and generate the optimal travel plan for the user.

[0262] The terminal provides a user interface, allowing users to easily input information and view optimized travel plans sent from the server. It also features real-time information provision capabilities, providing users with local weather information, event information, and other relevant details during their trip.

[0263] Users can provide feedback on their travel plans to the server via their devices. The server receives this feedback and dynamically adjusts the travel plans using update mechanisms to respond to the user's changing needs.

[0264] For example, if a user wants to travel to various parts of Asia for their next vacation, they select the cities they want to visit (e.g., Tokyo, Seoul, Bangkok) and enter their budget via the device. Based on these conditions, the server collects relevant information from travel booking services and generates a plan suggesting the best flights, accommodations, and activities. Furthermore, if an event matching the user's interests occurs during the trip, the device provides that information in real time, making it easier to adjust the travel plan.

[0265] An example of a prompt sentence to input into a generative AI model might be: "I would like to visit Asia on my next vacation. Planned cities: Tokyo, Seoul, Bangkok. Budget: $1500. Activities of interest: Participating in local festivals, cooking experiences."

[0266] In this way, the combination of functions within this system allows users to always obtain the latest and most optimized travel experience.

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

[0268] Step 1:

[0269] Users use their devices to input their travel preferences. Specifically, they select and enter their destination, budget, and activities of interest. This information about the user's travel preferences is then saved on the device in a list format. This input forms the basis for sending data to the server.

[0270] Step 2:

[0271] The terminal sends the information entered by the user to the server. The server receives this information through an information receiving device. The data received by the server includes the name of the travel destination, the budget, and the type of activity. Based on this information, the server prepares to obtain the basic data necessary to generate a travel plan.

[0272] Step 3:

[0273] The server uses external information acquisition methods to collect information from travel-related databases on the internet. For example, it obtains hotel rates and availability for the selected travel destination, flight schedules, and details of tourist facilities. This acquired data will be used for analysis in the next step.

[0274] Step 4:

[0275] The server processes the acquired information using artificial intelligence analysis methods based on a generation AI model. This process combines the acquired data to generate the optimal travel plan that best matches the conditions specified by the user. For example, when selecting accommodation, the analysis considers price, location, and the user's interests (e.g., a night view). As a result, specific accommodations and activities are suggested.

[0276] Step 5:

[0277] The server sends the generated travel plan to the terminal. The terminal displays this visually to the user. The user can review the suggested accommodations, flights, and activities, and either accept them or request changes if necessary. This output forms the basis of the user's optimal itinerary.

[0278] Step 6:

[0279] Users send feedback on their travel plans to the server via their devices. This feedback includes requests for changes to accommodation dates and additional activities. The server receives the feedback, adjusts the plan using update mechanisms, and generates a revised plan. This re-optimizes the itinerary to suit the user's preferences.

[0280] Step 7:

[0281] When the trip starts, the terminal uses the real-time information providing means to notify the user of local weather and event information. Thereby, the user can check the latest information at the travel destination at any time and adjust the schedule as needed. These information are elements that improve the user's travel experience.

[0282] (Application Example 1)

[0283] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0284] For travelers visiting urban areas, it is difficult to find an efficient and interesting sightseeing route. Also, dynamic route adjustment according to traffic conditions and weather changes is necessary, but it is difficult to meet such needs with current technologies. Furthermore, the provision of local information in multiple languages and individualized proposals based on the preferences of users are also lacking.

[0285] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0286] In this invention, the server includes data collection means, external data acquisition means, artificial intelligence processing means, information notification means, and integrated information processing means for integrating urban tourism and traffic information and providing a dynamic sightseeing route. Thereby, travelers can obtain an individually optimized sightseeing route and can also flexibly respond to changes in traffic conditions and weather.

[0287] The "data collection means" is a device or process for collecting information such as the user's preferences, budget, travel style, etc.

[0288] The "external data acquisition means" is a device or process for obtaining travel-related information from other travel reservation platforms or information sources.

[0289] "Artificial intelligence processing means" refers to a computer program or system that analyzes collected data and formulates personalized travel suggestions for users.

[0290] "Information notification means" refers to a device or process for providing users with the latest travel conditions and local information in real time.

[0291] "Integrated information processing means" refers to a device or process for integrating urban tourism information and traffic information to provide users with dynamic and optimized tourist routes.

[0292] To realize this invention, a system using a server and terminals is constructed. The server collects information about the user's preferences, budget, and travel style using data collection means. This includes data entered by the user into the terminal. The server also obtains travel-related information from other travel booking platforms using external data acquisition means. This process is achieved, for example, by obtaining the necessary data through an external API.

[0293] The server uses artificial intelligence processing to analyze the collected data and formulate personalized travel suggestions for users. For example, it might use AI frameworks such as TensorFlow to analyze the user's past choices and the trends of similar users.

[0294] Furthermore, the server provides users' devices with real-time local information and the latest travel conditions through information notification mechanisms. At this stage, push notifications are used to quickly communicate information about events and traffic changes occurring in the city where the user is traveling.

[0295] Through integrated information processing, the server combines urban tourism and traffic information to provide users with dynamic and optimized sightseeing routes. Real-time route changes are also possible, allowing users to enjoy the most efficient travel experience.

[0296] For example, if a user is visiting Tokyo, they would input their preferences, such as "I like sushi and want to visit interesting spots in Tokyo." Based on this information, the server would create an optimized sightseeing route and immediately notify the user's device. If the weather deteriorates, the plan can be changed to an indoor activity.

[0297] An example of a prompt to input into the generating AI model would be: "A user is planning a sightseeing route in Tokyo. They like sushi and have a budget of 10,000 yen. Please suggest the best route, taking into account alternatives for rainy weather."

[0298] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0299] Step 1:

[0300] Users input information about their preferences, budget, and travel style using a terminal. This entered data is sent to the server. The user's input clarifies their travel preferences and budget constraints, serving as the basis for the server to generate subsequent suggestions.

[0301] Step 2:

[0302] The server receives and stores information sent from users using data collection methods. Next, it obtains travel-related information from other travel booking platforms through external data acquisition methods. The server aggregates relevant travel information using APIs, thereby expanding travel options.

[0303] Step 3:

[0304] The server uses artificial intelligence processing to analyze user information and data acquired from external sources to generate personalized travel suggestions. Specifically, data calculations involve analyzing past user data and similar trends, and an optimized travel plan is created using a generative AI model. Suggestions are prepared to match the user's preferences and budget.

[0305] Step 4:

[0306] The server transmits the travel proposal generated using the information notification means to the terminal. The user receives this and checks the proposed plan. The information notification is performed in real time, enabling the selection and change of the travel schedule.

[0307] Step 5:

[0308] The user checks the proposed travel plan and provides feedback if necessary. The server receives this feedback and dynamically modifies the travel plan. The plan is recalculated and a new proposal is made according to the travel conditions and the user's desires.

[0309] Step 6:

[0310] During the trip, the server provides real-time local information through the terminal. Based on traffic conditions and weather changes, the server uses the integrated information processing means to dynamically adjust the sightseeing route. As a result, the user can always use the optimal route.

[0311] Step 7:

[0312] After the trip, the user provides detailed feedback regarding the travel experience. The server utilizes this information in the subsequent optimization process, contributing to the improvement of the overall system accuracy. Through this cycle, a better user experience becomes possible.

[0313] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0314] This invention further enhances the personalized travel experience by integrating an emotion engine that recognizes user emotions, in addition to conventional travel suggestion systems. This system consists of a server, a terminal, and user interaction.

[0315] First, the server receives information from the user, such as preferences, budget, and travel style, and stores it in a database. The terminal collects this information from the user and sends it to the server. The server also retrieves travel-related information from other travel booking platforms based on the user information and generates the optimal plan.

[0316] A distinctive feature of this invention is the incorporation of an emotion engine. The terminal uses a camera, microphone, and sensors to collect and analyze the emotions the user is experiencing during their trip. The server determines the user's current emotional state from the acquired emotion data and adjusts the travel experience provided to be optimized according to changes in emotions.

[0317] For example, if the emotion engine detects that a user is feeling dissatisfied at a certain point during their trip, the server can immediately restructure the plan and suggest alternative activities or sightseeing destinations. Similarly, if the server recognizes that the user is experiencing a very high level of emotion, it can make suggestions to maintain that emotion (e.g., tickets to a special event or recommendations for special interactions).

[0318] This kind of collaboration allows users to always enjoy a travel experience that matches their mood at any given time. The device notifies the user of updates from the server in real time and continuously provides appropriate feedback that reflects their emotional state. Through the collaboration of the server and the emotion engine, users can enjoy their travels with a higher level of satisfaction.

[0319] The following describes the processing flow.

[0320] Step 1:

[0321] The user enters travel information using a terminal. This includes various information such as preferences, budget, and travel style. The terminal collects this information and sends it to the server.

[0322] Step 2:

[0323] Based on the information received from the terminal, the server retrieves travel-related data from other travel booking platforms. This includes accommodation, transportation, and activity options.

[0324] Step 3:

[0325] The server uses artificial intelligence processing to analyze the acquired data and generate a travel plan optimized for the user's preferences and budget.

[0326] Step 4:

[0327] The emotion engine uses the device's camera and microphone to collect emotional data such as the user's voice and facial expressions. The device then sends this data to a server.

[0328] Step 5:

[0329] The server analyzes the received emotional data to determine the user's current emotional state. For example, if the user is feeling anxious, it identifies the cause and suggests activities that can help them relax.

[0330] Step 6:

[0331] The server readjusts the travel plan in response to changes in emotions. If necessary, it generates suggestions for new activities and tourist destinations and updates the plan.

[0332] Step 7:

[0333] The device receives update information from the server and notifies the user in real time. Based on this, the user can decide on their next course of action.

[0334] Step 8:

[0335] Users can provide feedback through their devices. The server uses this feedback to further refine the plan and continue to provide the best possible travel experience.

[0336] (Example 2)

[0337] 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".

[0338] Conventional travel suggestion systems could only offer suggestions based on users' fixed preferences and conditions, making it difficult to provide personalized services that could respond immediately to changes in users' emotions and circumstances during their trip. Furthermore, they lacked sufficient real-time information updates, making them unable to adapt to dynamic local conditions.

[0339] 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.

[0340] In this invention, the server includes information gathering means for generating an optimized travel plan based on the user's preferences, budget, and travel style; external information acquisition means for obtaining travel-related information from other booking platforms; and emotion detection means for detecting the user's emotional state and dynamically adjusting the plan accordingly. This makes it possible to provide a personalized travel experience that responds to changes in the user's emotions and circumstances.

[0341] "Information gathering means" refers to technologies or functions for efficiently collecting personal information such as users' preferences, budgets, and travel styles.

[0342] "External information acquisition means" refers to technologies or functions for obtaining travel-related information from other booking platforms or information sources.

[0343] "Artificial intelligence processing means" refers to AI technology or algorithms used to formulate personalized suggestions based on user information.

[0344] "Notification means" refers to technologies or functions that provide users with real-time local information and updates, and that reflect the latest conditions.

[0345] "Emotion detection means" refers to a technology or function that detects the user's emotional state and dynamically adjusts the travel plan based on that information.

[0346] This invention provides technology for a travel suggestion system that offers a personalized travel experience that takes into account the user's emotional state. This system is implemented through interaction between a server, a terminal, and the user.

[0347] First, the device collects information from the user about their preferences, budget, and travel style. This is done using an interface built into the device, which the user enters. This information is then encrypted and sent to the server.

[0348] The server stores the received information in a database and performs analysis. The server uses external information acquisition means to obtain travel-related information from other travel booking platforms. Furthermore, it uses artificial intelligence processing means to generate optimized travel plans based on user information. This system also includes emotion detection means to receive emotion data from the terminal. This allows the system to analyze the user's emotional state and dynamically adjust the travel plan.

[0349] As a concrete example, suppose a user uses a device and receives suggestions for potential tourist destinations and events they might visit while planning a trip. At this point, the device's camera and sensors collect the user's emotional data and send it to a server. The server analyzes this data, and if the user's emotions are heightened, it can suggest special events or activities to maintain those emotions.

[0350] For example, the following prompt could be used with a generative AI model: "The user is dissatisfied with their current trip. As an alternative, suggest a guided tour of a nearby nature park. Also, if they are excited, consider offering them VIP tickets to a local festival currently taking place at their destination."

[0351] Based on this prompt, the AI ​​model generates a new travel plan and notifies the user of the results in real time via their device. This allows users to enjoy the optimal travel experience tailored to their emotions and circumstances at the time.

[0352] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0353] Step 1:

[0354] The user enters information about their travel preferences, budget, and travel style into the device. The device collects, encrypts, and temporarily stores this information. The entered data includes details about the tourist destinations they want to visit and the activities they wish to do. This information is sent directly to the server for later analysis.

[0355] Step 2:

[0356] User information is sent from the terminal to the server. The server receives this data and stores it in a database. Based on the received information, the server begins data analysis and integrates information from external travel booking platforms. This transforms it into a comprehensive dataset that also takes into account the travel history of other users and current trends.

[0357] Step 3:

[0358] The server generates travel plans based on collected data. Using artificial intelligence processing, it analyzes past data and patterns to create optimized travel plans. The generated plans include planned tourist destinations, activities, and accommodations. Here, prompts are input into the AI ​​model to generate new ideas and suggestions.

[0359] Step 4:

[0360] The device collects user emotional data during travel. Using cameras, microphones, and sensors, it analyzes the user's facial expressions, voice, and physical reactions in real time. This data is sent to a server to evaluate the user's emotional state.

[0361] Step 5:

[0362] The server analyzes emotional data sent from the terminal. The server determines the user's emotions during the trip and dynamically reconfigures the travel plan based on the results. For example, if the user expresses dissatisfaction, it suggests alternative tourist destinations or activities. These suggestions are generated using a generative AI model.

[0363] Step 6:

[0364] The device notifies the user in real time of updated plans and suggestions. The user can review these and adjust their travel plans based on the new suggestions. Pop-up notifications appear on the device, and a voice assistant provides explanations, offering user-friendly feedback.

[0365] (Application Example 2)

[0366] 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 as the "terminal".

[0367] Traditional travel suggestion systems have optimized travel plans based on user preferences and budgets, but they have a weakness in that they lack personalization that takes user emotions into account. In particular, the inability to dynamically optimize the travel experience in response to changes in emotions during the trip has been an obstacle to increasing user satisfaction.

[0368] 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.

[0369] In this invention, the server includes data collection means for generating an optimized travel plan based on the user's preferences, budget, and travel style; external data acquisition means for obtaining travel-related information from other travel booking platforms; and emotion analysis means for performing emotion recognition. This enables the dynamic optimization of the travel experience in response to the user's emotions.

[0370] "Data collection means" refers to functions for collecting information related to users' preferences, budgets, and travel styles.

[0371] "External data acquisition means" refers to a function that allows you to obtain information necessary for optimizing your travel plan from other travel booking platforms.

[0372] "Artificial intelligence processing means" refers to a function that processes data to formulate personalized travel suggestions based on acquired user information.

[0373] "Information notification means" refers to a function that notifies users of the latest local travel conditions in real time.

[0374] "Emotional analysis means" refers to a function for recognizing and analyzing the user's emotions, using user interfaces and sensor data.

[0375] The "proposal adjustment mechanism" is a function that dynamically adjusts travel plans to provide a travel experience that responds to the user's emotions.

[0376] The implementation of this system requires data collection means, external data acquisition means, artificial intelligence processing means, information notification means, sentiment analysis means, and proposal adjustment means.

[0377] The server collects information such as user preferences, budget, and travel style using data collection methods. This allows the server to understand the user's individualized requests. Subsequently, it obtains travel-related information from other travel booking platforms via external data acquisition methods. This external data includes destination attractions, accommodations, transportation options, and local events.

[0378] The device uses sensors such as cameras and microphones to collect emotions from the user's facial expressions and voice, and analyzes this data using emotion analysis tools. The results of this analysis are sent to a server, where artificial intelligence processing tools construct an optimal travel experience tailored to the user's emotions.

[0379] Based on user sentiment information, the server dynamically adjusts the travel plan and provides real-time feedback to the user through the terminal's information notification system. This makes it possible to provide the user with the most comfortable and satisfying travel experience.

[0380] For example, if the emotion analysis system determines that a user is experiencing stress at a particular tourist destination during a trip, the server can immediately suggest alternative tourist destinations or activities to alleviate the situation. Conversely, if the user is having a great time, suggestions will be made to encourage participation in events that will help maintain that positive feeling.

[0381] Using a generative AI model, an example of a prompt message for this system to function is: "Design a system that senses the user's emotional changes in real time during travel and suggests the most suitable sightseeing activities based on those emotions. Use facial expressions and voice data for emotion recognition."

[0382] This enables personalized travel experiences that cater to a range of emotions during the journey.

[0383] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0384] Step 1:

[0385] The server collects basic data about the user's preferences, budget, and travel style using data collection methods. At this stage, various information entered by the user through the application is stored in the database. The input data includes the user's preferences, budget, and travel style, and a user profile is formed based on this data.

[0386] Step 2:

[0387] The server collects comprehensive travel information related to the destination from other travel booking platforms via external data acquisition means. This information includes attractions, accommodations, transportation, and event information. This external information is analyzed to create a comprehensive list of travel options, preparing for the next process.

[0388] Step 3:

[0389] The device's sensing capabilities collect real-time emotional data through the user's facial expressions and voice. Using the camera and microphone, it acquires raw emotional data such as changes in the user's facial expressions and tone of voice. The input consists of visual and auditory data, which is processed by emotion analysis tools to identify the emotional state.

[0390] Step 4:

[0391] The server uses artificial intelligence processing to personalize the travel experience based on emotional data obtained through emotion analysis. Here, it combines the user's emotional state and preference profile to generate optimal sightseeing activities and itinerary modifications. The output is a new travel plan best suited to the user's current emotions.

[0392] Step 5:

[0393] The server notifies users in real time of new travel plans and sightseeing activities suggested by the server through the terminal's information notification system. Users receive these suggestions through screen displays and voice guidance and select their next action. In this step, the optimal travel options for the user are specifically presented as output.

[0394] Step 6:

[0395] The system is continuously optimized by collecting user feedback on the device and sending it back to the server. Users input their satisfaction with suggested activities and any new requests, which are then used to process and analyze the data again. This process enables further personalization and optimization of the experience.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] [Third Embodiment]

[0400] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0401] 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.

[0402] 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).

[0403] 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.

[0404] 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.

[0405] 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).

[0406] 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.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] 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.

[0411] 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".

[0412] The system according to the present invention enables the suggestion of optimized travel plans based on the user's preferences, budget, and travel style. This system consists of a server, a terminal, and user interaction.

[0413] The server generates a travel plan optimized for the user based on information provided by the user via their device. Specifically, the server collects information such as the user's travel preferences and budget, and uses this to retrieve relevant data from existing travel booking services. Using artificial intelligence processing, it analyzes this data and formulates the optimal travel plan for the user. This process includes selecting accommodations and flights, and recommending activities at the travel destination.

[0414] Meanwhile, the terminal assists users in inputting information through its user interface and displays optimized travel plans sent from the server. Furthermore, the terminal provides real-time information during the trip, informing users of local weather and event information.

[0415] Users can provide feedback on their travel plans to the server via their device. This allows the server to re-optimize the travel plan and dynamically adjust the itinerary to meet the user's needs. This interaction ensures that users always have an ideal travel experience.

[0416] As a concrete example, consider a scenario where a user wants to travel to Europe during their next vacation. The user uses their device to select the countries and cities they want to visit and set a budget. Based on the user's selections, the server retrieves necessary data from major travel booking services and develops a plan suggesting optimal accommodations and sightseeing activities. Furthermore, if any new events occur during the trip, the device provides the user with this information in real time, allowing for corresponding changes to the plan.

[0417] Thus, the present invention is designed to provide users with a smooth and efficient travel experience, enabling flexible planning tailored to individual needs and real-time information notifications.

[0418] The following describes the processing flow.

[0419] Step 1:

[0420] Users create an account and log in using their device. Users enter information such as their travel preferences, budget, and purpose.

[0421] Step 2:

[0422] The terminal recognizes the user's input information and sends it to the server. The server receives this information and stores it in its database.

[0423] Step 3:

[0424] The server collects relevant data through APIs of external travel booking services. This includes information on accommodations, transportation, and activities.

[0425] Step 4:

[0426] The server uses AI algorithms to analyze the collected information and generate travel plans optimized for the user's preferences and budget.

[0427] Step 5:

[0428] The server sends the generated travel plan to the user's terminal. The terminal receives it and displays it to the user.

[0429] Step 6:

[0430] Users review the displayed travel plan and provide feedback as needed, such as requesting changes or additions to specific activities.

[0431] Step 7:

[0432] The server receives feedback from the user and readjusts the travel plan. It generates new suggestions and resends them to the user's device.

[0433] Step 8:

[0434] During their trip, users request real-time information through their devices, including local weather and event information.

[0435] Step 9:

[0436] The server collects real-time information and sends it to the user's device. The device then presents this information to the user to assist in decision-making during their trip.

[0437] (Example 1)

[0438] 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."

[0439] Modern travelers spend a lot of time creating appropriate travel plans based on their individual preferences and budgets, and it is also difficult for them to quickly adapt to changing conditions during their trip. Furthermore, there are challenges in dynamically readjusting plans to reflect traveler feedback and providing information that takes into account the diverse cultural backgrounds of the local area.

[0440] 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.

[0441] In this invention, the server includes an information receiving means, an external information acquisition means, and an artificial intelligence analysis means. This allows travelers to obtain individually optimized travel plans based on their preferences and feedback, and enables them to flexibly respond to changes during their trip through the provision of real-time information.

[0442] "Information receiving means" refers to a means of receiving and recording travel-related information provided by users.

[0443] "External information acquisition means" refers to methods for collecting travel-related data from other databases and information sources to obtain necessary information.

[0444] "Artificial intelligence analysis means" refers to a method for analyzing acquired data and creating travel suggestions optimized for the user.

[0445] "Information provision methods" refer to means of providing users with the latest travel-related information in real time and supporting their travel experience.

[0446] "Update mechanisms" refer to methods for dynamically modifying existing travel plans based on user feedback and reconstructing improved plans.

[0447] The system according to the present invention aims to provide optimized travel plans based on the user's travel needs. This system consists of a server, a terminal, and interaction with the user.

[0448] The server collects data provided by users through information receiving means (such as travel destinations, budgets, and travel styles). Based on this information, it uses external information acquisition means to retrieve necessary information from travel-related databases on the internet. This data includes information on flights, accommodations, and tourist attractions. The server uses a generative AI model and artificial intelligence analysis means to process this information and generate the optimal travel plan for the user.

[0449] The terminal provides a user interface, allowing users to easily input information and view optimized travel plans sent from the server. It also features real-time information provision capabilities, providing users with local weather information, event information, and other relevant details during their trip.

[0450] Users can provide feedback on their travel plans to the server via their devices. The server receives this feedback and dynamically adjusts the travel plans using update mechanisms to respond to the user's changing needs.

[0451] For example, if a user wants to travel to various parts of Asia for their next vacation, they select the cities they want to visit (e.g., Tokyo, Seoul, Bangkok) and enter their budget via the device. Based on these conditions, the server collects relevant information from travel booking services and generates a plan suggesting the best flights, accommodations, and activities. Furthermore, if an event matching the user's interests occurs during the trip, the device provides that information in real time, making it easier to adjust the travel plan.

[0452] An example of a prompt sentence to input into a generative AI model might be: "I would like to visit Asia on my next vacation. Planned cities: Tokyo, Seoul, Bangkok. Budget: $1500. Activities of interest: Participating in local festivals, cooking experiences."

[0453] In this way, the combination of functions within this system allows users to always obtain the latest and most optimized travel experience.

[0454] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0455] Step 1:

[0456] Users use their devices to input their travel preferences. Specifically, they select and enter their destination, budget, and activities of interest. This information about the user's travel preferences is then saved on the device in a list format. This input forms the basis for sending data to the server.

[0457] Step 2:

[0458] The terminal sends the information entered by the user to the server. The server receives this information through an information receiving device. The data received by the server includes the name of the travel destination, the budget, and the type of activity. Based on this information, the server prepares to obtain the basic data necessary to generate a travel plan.

[0459] Step 3:

[0460] The server uses external information acquisition methods to collect information from travel-related databases on the internet. For example, it obtains hotel rates and availability for the selected travel destination, flight schedules, and details of tourist facilities. This acquired data will be used for analysis in the next step.

[0461] Step 4:

[0462] The server processes the acquired information using artificial intelligence analysis methods based on a generation AI model. This process combines the acquired data to generate the optimal travel plan that best matches the conditions specified by the user. For example, when selecting accommodation, the analysis considers price, location, and the user's interests (e.g., a night view). As a result, specific accommodations and activities are suggested.

[0463] Step 5:

[0464] The server sends the generated travel plan to the terminal. The terminal displays this visually to the user. The user can review the suggested accommodations, flights, and activities, and either accept them or request changes if necessary. This output forms the basis of the user's optimal itinerary.

[0465] Step 6:

[0466] Users send feedback on their travel plans to the server via their devices. This feedback includes requests for changes to accommodation dates and additional activities. The server receives the feedback, adjusts the plan using update mechanisms, and generates a revised plan. This re-optimizes the itinerary to suit the user's preferences.

[0467] Step 7:

[0468] Once the trip begins, the device uses real-time information delivery methods to notify the user of local weather and event information. This allows the user to check the latest information at their destination at any time and adjust their schedule as needed. This information enhances the user's travel experience.

[0469] (Application Example 1)

[0470] 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."

[0471] For travelers visiting urban areas, finding efficient and interesting sightseeing routes can be difficult. Furthermore, dynamic route adjustments that adapt to changing traffic conditions and weather are necessary, but current technology struggles to meet these needs. Additionally, there is a lack of multilingual local information and personalized recommendations based on user preferences.

[0472] 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.

[0473] In this invention, the server includes data collection means, external data acquisition means, artificial intelligence processing means, information notification means, and integrated information processing means that integrate urban tourism and traffic information and provide dynamic tourist routes. This allows travelers to obtain individually optimized tourist routes and to flexibly respond to changes in traffic conditions and weather.

[0474] "Data collection means" refers to devices or processes for collecting information such as users' preferences, budgets, and travel styles.

[0475] "External data acquisition means" refers to a device or process for acquiring travel-related information from other travel booking platforms or information sources.

[0476] "Artificial intelligence processing means" refers to a computer program or system that analyzes collected data and formulates personalized travel suggestions for users.

[0477] "Information notification means" refers to a device or process for providing users with the latest travel conditions and local information in real time.

[0478] "Integrated information processing means" refers to a device or process for integrating urban tourism information and traffic information to provide users with dynamic and optimized tourist routes.

[0479] To realize this invention, a system using a server and terminals is constructed. The server collects information about the user's preferences, budget, and travel style using data collection means. This includes data entered by the user into the terminal. The server also obtains travel-related information from other travel booking platforms using external data acquisition means. This process is achieved, for example, by obtaining the necessary data through an external API.

[0480] The server uses artificial intelligence processing to analyze the collected data and formulate personalized travel suggestions for users. For example, it might use AI frameworks such as TensorFlow to analyze the user's past choices and the trends of similar users.

[0481] Furthermore, the server provides users' devices with real-time local information and the latest travel conditions through information notification mechanisms. At this stage, push notifications are used to quickly communicate information about events and traffic changes occurring in the city where the user is traveling.

[0482] Through integrated information processing, the server combines urban tourism and traffic information to provide users with dynamic and optimized sightseeing routes. Real-time route changes are also possible, allowing users to enjoy the most efficient travel experience.

[0483] For example, if a user is visiting Tokyo, they would input their preferences, such as "I like sushi and want to visit interesting spots in Tokyo." Based on this information, the server would create an optimized sightseeing route and immediately notify the user's device. If the weather deteriorates, the plan can be changed to an indoor activity.

[0484] An example of a prompt to input into the generating AI model would be: "A user is planning a sightseeing route in Tokyo. They like sushi and have a budget of 10,000 yen. Please suggest the best route, taking into account alternatives for rainy weather."

[0485] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0486] Step 1:

[0487] Users input information about their preferences, budget, and travel style using a terminal. This entered data is sent to the server. The user's input clarifies their travel preferences and budget constraints, serving as the basis for the server to generate subsequent suggestions.

[0488] Step 2:

[0489] The server receives and stores information sent from users using data collection methods. Next, it obtains travel-related information from other travel booking platforms through external data acquisition methods. The server aggregates relevant travel information using APIs, thereby expanding travel options.

[0490] Step 3:

[0491] The server uses artificial intelligence processing to analyze user information and data acquired from external sources to generate personalized travel suggestions. Specifically, data calculations involve analyzing past user data and similar trends, and an optimized travel plan is created using a generative AI model. Suggestions are prepared to match the user's preferences and budget.

[0492] Step 4:

[0493] The server sends travel suggestions generated using an information notification system to the terminal. The user receives this and reviews the suggested plan. Information notifications are provided in real time, allowing users to select or modify their travel schedule.

[0494] Step 5:

[0495] The user reviews the proposed travel plan and provides feedback as needed. The server receives this feedback and dynamically modifies the travel plan. Based on travel conditions and user requests, the plan is recalculated and a new proposal is made.

[0496] Step 6:

[0497] During your trip, the server provides real-time local information through your device. Based on traffic conditions and weather changes, the server uses integrated information processing to dynamically adjust your sightseeing route. This ensures that you always have access to the optimal route.

[0498] Step 7:

[0499] After the trip ends, users provide detailed feedback on their travel experience. The server uses this information to optimize future trips, contributing to overall system accuracy improvements. This cycle enables a better user experience.

[0500] 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.

[0501] This invention further enhances the personalized travel experience by integrating an emotion engine that recognizes user emotions, in addition to conventional travel suggestion systems. This system consists of a server, a terminal, and user interaction.

[0502] First, the server receives information from the user, such as preferences, budget, and travel style, and stores it in a database. The terminal collects this information from the user and sends it to the server. The server also retrieves travel-related information from other travel booking platforms based on the user information and generates the optimal plan.

[0503] A distinctive feature of this invention is the incorporation of an emotion engine. The terminal uses a camera, microphone, and sensors to collect and analyze the emotions the user is experiencing during their trip. The server determines the user's current emotional state from the acquired emotion data and adjusts the travel experience provided to be optimized according to changes in emotions.

[0504] For example, if the emotion engine detects that a user is feeling dissatisfied at a certain point during their trip, the server can immediately restructure the plan and suggest alternative activities or sightseeing destinations. Similarly, if the server recognizes that the user is experiencing a very high level of emotion, it can make suggestions to maintain that emotion (e.g., tickets to a special event or recommendations for special interactions).

[0505] This kind of collaboration allows users to always enjoy a travel experience that matches their mood at any given time. The device notifies the user of updates from the server in real time and continuously provides appropriate feedback that reflects their emotional state. Through the collaboration of the server and the emotion engine, users can enjoy their travels with a higher level of satisfaction.

[0506] The following describes the processing flow.

[0507] Step 1:

[0508] The user enters travel information using a terminal. This includes various information such as preferences, budget, and travel style. The terminal collects this information and sends it to the server.

[0509] Step 2:

[0510] Based on the information received from the terminal, the server retrieves travel-related data from other travel booking platforms. This includes accommodation, transportation, and activity options.

[0511] Step 3:

[0512] The server uses artificial intelligence processing to analyze the acquired data and generate a travel plan optimized for the user's preferences and budget.

[0513] Step 4:

[0514] The emotion engine uses the device's camera and microphone to collect emotional data such as the user's voice and facial expressions. The device then sends this data to a server.

[0515] Step 5:

[0516] The server analyzes the received emotional data to determine the user's current emotional state. For example, if the user is feeling anxious, it identifies the cause and suggests activities that can help them relax.

[0517] Step 6:

[0518] The server readjusts the travel plan in response to changes in emotions. If necessary, it generates suggestions for new activities and tourist destinations and updates the plan.

[0519] Step 7:

[0520] The device receives update information from the server and notifies the user in real time. Based on this, the user can decide on their next course of action.

[0521] Step 8:

[0522] Users can provide feedback through their devices. The server uses this feedback to further refine the plan and continue to provide the best possible travel experience.

[0523] (Example 2)

[0524] 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."

[0525] Conventional travel suggestion systems could only offer suggestions based on users' fixed preferences and conditions, making it difficult to provide personalized services that could respond immediately to changes in users' emotions and circumstances during their trip. Furthermore, they lacked sufficient real-time information updates, making them unable to adapt to dynamic local conditions.

[0526] 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.

[0527] In this invention, the server includes information gathering means for generating an optimized travel plan based on the user's preferences, budget, and travel style; external information acquisition means for obtaining travel-related information from other booking platforms; and emotion detection means for detecting the user's emotional state and dynamically adjusting the plan accordingly. This makes it possible to provide a personalized travel experience that responds to changes in the user's emotions and circumstances.

[0528] "Information gathering means" refers to technologies or functions for efficiently collecting personal information such as users' preferences, budgets, and travel styles.

[0529] "External information acquisition means" refers to technologies or functions for obtaining travel-related information from other booking platforms or information sources.

[0530] "Artificial intelligence processing means" refers to AI technology or algorithms used to formulate personalized suggestions based on user information.

[0531] "Notification means" refers to technologies or functions that provide users with real-time local information and updates, and that reflect the latest conditions.

[0532] "Emotion detection means" refers to a technology or function that detects the user's emotional state and dynamically adjusts the travel plan based on that information.

[0533] This invention provides technology for a travel suggestion system that offers a personalized travel experience that takes into account the user's emotional state. This system is implemented through interaction between a server, a terminal, and the user.

[0534] First, the device collects information from the user about their preferences, budget, and travel style. This is done using an interface built into the device, which the user enters. This information is then encrypted and sent to the server.

[0535] The server stores the received information in a database and performs analysis. The server uses external information acquisition means to obtain travel-related information from other travel booking platforms. Furthermore, it uses artificial intelligence processing means to generate optimized travel plans based on user information. This system also includes emotion detection means to receive emotion data from the terminal. This allows the system to analyze the user's emotional state and dynamically adjust the travel plan.

[0536] As a concrete example, suppose a user uses a device and receives suggestions for potential tourist destinations and events they might visit while planning a trip. At this point, the device's camera and sensors collect the user's emotional data and send it to a server. The server analyzes this data, and if the user's emotions are heightened, it can suggest special events or activities to maintain those emotions.

[0537] For example, the following prompt could be used with a generative AI model: "The user is dissatisfied with their current trip. As an alternative, suggest a guided tour of a nearby nature park. Also, if they are excited, consider offering them VIP tickets to a local festival currently taking place at their destination."

[0538] Based on this prompt, the AI ​​model generates a new travel plan and notifies the user of the results in real time via their device. This allows users to enjoy the optimal travel experience tailored to their emotions and circumstances at the time.

[0539] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0540] Step 1:

[0541] The user enters information about their travel preferences, budget, and travel style into the device. The device collects, encrypts, and temporarily stores this information. The entered data includes details about the tourist destinations they want to visit and the activities they wish to do. This information is sent directly to the server for later analysis.

[0542] Step 2:

[0543] User information is sent from the terminal to the server. The server receives this data and stores it in a database. Based on the received information, the server begins data analysis and integrates information from external travel booking platforms. This transforms it into a comprehensive dataset that also takes into account the travel history of other users and current trends.

[0544] Step 3:

[0545] The server generates travel plans based on collected data. Using artificial intelligence processing, it analyzes past data and patterns to create optimized travel plans. The generated plans include planned tourist destinations, activities, and accommodations. Here, prompts are input into the AI ​​model to generate new ideas and suggestions.

[0546] Step 4:

[0547] The device collects user emotional data during travel. Using cameras, microphones, and sensors, it analyzes the user's facial expressions, voice, and physical reactions in real time. This data is sent to a server to evaluate the user's emotional state.

[0548] Step 5:

[0549] The server analyzes emotional data sent from the terminal. The server determines the user's emotions during the trip and dynamically reconfigures the travel plan based on the results. For example, if the user expresses dissatisfaction, it suggests alternative tourist destinations or activities. These suggestions are generated using a generative AI model.

[0550] Step 6:

[0551] The device notifies the user in real time of updated plans and suggestions. The user can review these and adjust their travel plans based on the new suggestions. Pop-up notifications appear on the device, and a voice assistant provides explanations, offering user-friendly feedback.

[0552] (Application Example 2)

[0553] 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."

[0554] Traditional travel suggestion systems have optimized travel plans based on user preferences and budgets, but they have a weakness in that they lack personalization that takes user emotions into account. In particular, the inability to dynamically optimize the travel experience in response to changes in emotions during the trip has been an obstacle to increasing user satisfaction.

[0555] 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.

[0556] In this invention, the server includes data collection means for generating an optimized travel plan based on the user's preferences, budget, and travel style; external data acquisition means for obtaining travel-related information from other travel booking platforms; and emotion analysis means for performing emotion recognition. This enables the dynamic optimization of the travel experience in response to the user's emotions.

[0557] "Data collection means" refers to functions for collecting information related to users' preferences, budgets, and travel styles.

[0558] "External data acquisition means" refers to a function that allows you to obtain information necessary for optimizing your travel plan from other travel booking platforms.

[0559] "Artificial intelligence processing means" refers to a function that processes data to formulate personalized travel suggestions based on acquired user information.

[0560] "Information notification means" refers to a function that notifies users of the latest local travel conditions in real time.

[0561] "Emotional analysis means" refers to a function for recognizing and analyzing the user's emotions, using user interfaces and sensor data.

[0562] The "proposal adjustment mechanism" is a function that dynamically adjusts travel plans to provide a travel experience that responds to the user's emotions.

[0563] The implementation of this system requires data collection means, external data acquisition means, artificial intelligence processing means, information notification means, sentiment analysis means, and proposal adjustment means.

[0564] The server collects information such as user preferences, budget, and travel style using data collection methods. This allows the server to understand the user's individualized requests. Subsequently, it obtains travel-related information from other travel booking platforms via external data acquisition methods. This external data includes destination attractions, accommodations, transportation options, and local events.

[0565] The device uses sensors such as cameras and microphones to collect emotions from the user's facial expressions and voice, and analyzes this data using emotion analysis tools. The results of this analysis are sent to a server, where artificial intelligence processing tools construct an optimal travel experience tailored to the user's emotions.

[0566] Based on user sentiment information, the server dynamically adjusts the travel plan and provides real-time feedback to the user through the terminal's information notification system. This makes it possible to provide the user with the most comfortable and satisfying travel experience.

[0567] For example, if the emotion analysis system determines that a user is experiencing stress at a particular tourist destination during a trip, the server can immediately suggest alternative tourist destinations or activities to alleviate the situation. Conversely, if the user is having a great time, suggestions will be made to encourage participation in events that will help maintain that positive feeling.

[0568] Using a generative AI model, an example of a prompt message for this system to function is: "Design a system that senses the user's emotional changes in real time during travel and suggests the most suitable sightseeing activities based on those emotions. Use facial expressions and voice data for emotion recognition."

[0569] This enables personalized travel experiences that cater to a range of emotions during the journey.

[0570] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0571] Step 1:

[0572] The server collects basic data about the user's preferences, budget, and travel style using data collection methods. At this stage, various information entered by the user through the application is stored in the database. The input data includes the user's preferences, budget, and travel style, and a user profile is formed based on this data.

[0573] Step 2:

[0574] The server collects comprehensive travel information related to the destination from other travel booking platforms via external data acquisition means. This information includes attractions, accommodations, transportation, and event information. This external information is analyzed to create a comprehensive list of travel options, preparing for the next process.

[0575] Step 3:

[0576] The device's sensing capabilities collect real-time emotional data through the user's facial expressions and voice. Using the camera and microphone, it acquires raw emotional data such as changes in the user's facial expressions and tone of voice. The input consists of visual and auditory data, which is processed by emotion analysis tools to identify the emotional state.

[0577] Step 4:

[0578] The server uses artificial intelligence processing to personalize the travel experience based on emotional data obtained through emotion analysis. Here, it combines the user's emotional state and preference profile to generate optimal sightseeing activities and itinerary modifications. The output is a new travel plan best suited to the user's current emotions.

[0579] Step 5:

[0580] The server notifies users in real time of new travel plans and sightseeing activities suggested by the server through the terminal's information notification system. Users receive these suggestions through screen displays and voice guidance and select their next action. In this step, the optimal travel options for the user are specifically presented as output.

[0581] Step 6:

[0582] The system is continuously optimized by collecting user feedback on the device and sending it back to the server. Users input their satisfaction with suggested activities and any new requests, which are then used to process and analyze the data again. This process enables further personalization and optimization of the experience.

[0583] 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.

[0584] 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.

[0585] 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.

[0586] [Fourth Embodiment]

[0587] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0588] 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.

[0589] 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).

[0590] 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.

[0591] 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.

[0592] 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).

[0593] 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.

[0594] 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.

[0595] 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.

[0596] 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.

[0597] 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.

[0598] 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.

[0599] 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".

[0600] The system according to the present invention enables the suggestion of optimized travel plans based on the user's preferences, budget, and travel style. This system consists of a server, a terminal, and user interaction.

[0601] The server generates a travel plan optimized for the user based on information provided by the user via their device. Specifically, the server collects information such as the user's travel preferences and budget, and uses this to retrieve relevant data from existing travel booking services. Using artificial intelligence processing, it analyzes this data and formulates the optimal travel plan for the user. This process includes selecting accommodations and flights, and recommending activities at the travel destination.

[0602] Meanwhile, the terminal assists users in inputting information through its user interface and displays optimized travel plans sent from the server. Furthermore, the terminal provides real-time information during the trip, informing users of local weather and event information.

[0603] Users can provide feedback on their travel plans to the server via their device. This allows the server to re-optimize the travel plan and dynamically adjust the itinerary to meet the user's needs. This interaction ensures that users always have an ideal travel experience.

[0604] As a concrete example, consider a scenario where a user wants to travel to Europe during their next vacation. The user uses their device to select the countries and cities they want to visit and set a budget. Based on the user's selections, the server retrieves necessary data from major travel booking services and develops a plan suggesting optimal accommodations and sightseeing activities. Furthermore, if any new events occur during the trip, the device provides the user with this information in real time, allowing for corresponding changes to the plan.

[0605] Thus, the present invention is designed to provide users with a smooth and efficient travel experience, enabling flexible planning tailored to individual needs and real-time information notifications.

[0606] The following describes the processing flow.

[0607] Step 1:

[0608] Users create an account and log in using their device. Users enter information such as their travel preferences, budget, and purpose.

[0609] Step 2:

[0610] The terminal recognizes the user's input information and sends it to the server. The server receives this information and stores it in its database.

[0611] Step 3:

[0612] The server collects relevant data through APIs of external travel booking services. This includes information on accommodations, transportation, and activities.

[0613] Step 4:

[0614] The server uses AI algorithms to analyze the collected information and generate travel plans optimized for the user's preferences and budget.

[0615] Step 5:

[0616] The server sends the generated travel plan to the user's terminal. The terminal receives it and displays it to the user.

[0617] Step 6:

[0618] Users review the displayed travel plan and provide feedback as needed, such as requesting changes or additions to specific activities.

[0619] Step 7:

[0620] The server receives feedback from the user and readjusts the travel plan. It generates new suggestions and resends them to the user's device.

[0621] Step 8:

[0622] During their trip, users request real-time information through their devices, including local weather and event information.

[0623] Step 9:

[0624] The server collects real-time information and sends it to the user's device. The device then presents this information to the user to assist in decision-making during their trip.

[0625] (Example 1)

[0626] 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".

[0627] Modern travelers spend a lot of time creating appropriate travel plans based on their individual preferences and budgets, and it is also difficult for them to quickly adapt to changing conditions during their trip. Furthermore, there are challenges in dynamically readjusting plans to reflect traveler feedback and providing information that takes into account the diverse cultural backgrounds of the local area.

[0628] 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.

[0629] In this invention, the server includes an information receiving means, an external information acquisition means, and an artificial intelligence analysis means. This allows travelers to obtain individually optimized travel plans based on their preferences and feedback, and enables them to flexibly respond to changes during their trip through the provision of real-time information.

[0630] "Information receiving means" refers to a means of receiving and recording travel-related information provided by users.

[0631] "External information acquisition means" refers to methods for collecting travel-related data from other databases and information sources to obtain necessary information.

[0632] "Artificial intelligence analysis means" refers to a method for analyzing acquired data and creating travel suggestions optimized for the user.

[0633] "Information provision methods" refer to means of providing users with the latest travel-related information in real time and supporting their travel experience.

[0634] "Update mechanisms" refer to methods for dynamically modifying existing travel plans based on user feedback and reconstructing improved plans.

[0635] The system according to the present invention aims to provide optimized travel plans based on the user's travel needs. This system consists of a server, a terminal, and interaction with the user.

[0636] The server collects data provided by users through information receiving means (such as travel destinations, budgets, and travel styles). Based on this information, it uses external information acquisition means to retrieve necessary information from travel-related databases on the internet. This data includes information on flights, accommodations, and tourist attractions. The server uses a generative AI model and artificial intelligence analysis means to process this information and generate the optimal travel plan for the user.

[0637] The terminal provides a user interface, allowing users to easily input information and view optimized travel plans sent from the server. It also features real-time information provision capabilities, providing users with local weather information, event information, and other relevant details during their trip.

[0638] Users can provide feedback on their travel plans to the server via their devices. The server receives this feedback and dynamically adjusts the travel plans using update mechanisms to respond to the user's changing needs.

[0639] For example, if a user wants to travel to various parts of Asia for their next vacation, they select the cities they want to visit (e.g., Tokyo, Seoul, Bangkok) and enter their budget via the device. Based on these conditions, the server collects relevant information from travel booking services and generates a plan suggesting the best flights, accommodations, and activities. Furthermore, if an event matching the user's interests occurs during the trip, the device provides that information in real time, making it easier to adjust the travel plan.

[0640] An example of a prompt sentence to input into a generative AI model might be: "I would like to visit Asia on my next vacation. Planned cities: Tokyo, Seoul, Bangkok. Budget: $1500. Activities of interest: Participating in local festivals, cooking experiences."

[0641] In this way, the combination of functions within this system allows users to always obtain the latest and most optimized travel experience.

[0642] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0643] Step 1:

[0644] Users use their devices to input their travel preferences. Specifically, they select and enter their destination, budget, and activities of interest. This information about the user's travel preferences is then saved on the device in a list format. This input forms the basis for sending data to the server.

[0645] Step 2:

[0646] The terminal sends the information entered by the user to the server. The server receives this information through an information receiving device. The data received by the server includes the name of the travel destination, the budget, and the type of activity. Based on this information, the server prepares to obtain the basic data necessary to generate a travel plan.

[0647] Step 3:

[0648] The server uses external information acquisition methods to collect information from travel-related databases on the internet. For example, it obtains hotel rates and availability for the selected travel destination, flight schedules, and details of tourist facilities. This acquired data will be used for analysis in the next step.

[0649] Step 4:

[0650] The server processes the acquired information using artificial intelligence analysis methods based on a generation AI model. This process combines the acquired data to generate the optimal travel plan that best matches the conditions specified by the user. For example, when selecting accommodation, the analysis considers price, location, and the user's interests (e.g., a night view). As a result, specific accommodations and activities are suggested.

[0651] Step 5:

[0652] The server sends the generated travel plan to the terminal. The terminal displays this visually to the user. The user can review the suggested accommodations, flights, and activities, and either accept them or request changes if necessary. This output forms the basis of the user's optimal itinerary.

[0653] Step 6:

[0654] Users send feedback on their travel plans to the server via their devices. This feedback includes requests for changes to accommodation dates and additional activities. The server receives the feedback, adjusts the plan using update mechanisms, and generates a revised plan. This re-optimizes the itinerary to suit the user's preferences.

[0655] Step 7:

[0656] Once the trip begins, the device uses real-time information delivery methods to notify the user of local weather and event information. This allows the user to check the latest information at their destination at any time and adjust their schedule as needed. This information enhances the user's travel experience.

[0657] (Application Example 1)

[0658] 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".

[0659] For travelers visiting urban areas, finding efficient and interesting sightseeing routes can be difficult. Furthermore, dynamic route adjustments that adapt to changing traffic conditions and weather are necessary, but current technology struggles to meet these needs. Additionally, there is a lack of multilingual local information and personalized recommendations based on user preferences.

[0660] 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.

[0661] In this invention, the server includes data collection means, external data acquisition means, artificial intelligence processing means, information notification means, and integrated information processing means that integrate urban tourism and traffic information and provide dynamic tourist routes. This allows travelers to obtain individually optimized tourist routes and to flexibly respond to changes in traffic conditions and weather.

[0662] "Data collection means" refers to devices or processes for collecting information such as users' preferences, budgets, and travel styles.

[0663] "External data acquisition means" refers to a device or process for acquiring travel-related information from other travel booking platforms or information sources.

[0664] "Artificial intelligence processing means" refers to a computer program or system that analyzes collected data and formulates personalized travel suggestions for users.

[0665] "Information notification means" refers to a device or process for providing users with the latest travel conditions and local information in real time.

[0666] "Integrated information processing means" refers to a device or process for integrating urban tourism information and traffic information to provide users with dynamic and optimized tourist routes.

[0667] To realize this invention, a system using a server and terminals is constructed. The server collects information about the user's preferences, budget, and travel style using data collection means. This includes data entered by the user into the terminal. The server also obtains travel-related information from other travel booking platforms using external data acquisition means. This process is achieved, for example, by obtaining the necessary data through an external API.

[0668] The server uses artificial intelligence processing to analyze the collected data and formulate personalized travel suggestions for users. For example, it might use AI frameworks such as TensorFlow to analyze the user's past choices and the trends of similar users.

[0669] Furthermore, the server provides users' devices with real-time local information and the latest travel conditions through information notification mechanisms. At this stage, push notifications are used to quickly communicate information about events and traffic changes occurring in the city where the user is traveling.

[0670] Through integrated information processing, the server combines urban tourism and traffic information to provide users with dynamic and optimized sightseeing routes. Real-time route changes are also possible, allowing users to enjoy the most efficient travel experience.

[0671] For example, if a user is visiting Tokyo, they would input their preferences, such as "I like sushi and want to visit interesting spots in Tokyo." Based on this information, the server would create an optimized sightseeing route and immediately notify the user's device. If the weather deteriorates, the plan can be changed to an indoor activity.

[0672] An example of a prompt to input into the generating AI model would be: "A user is planning a sightseeing route in Tokyo. They like sushi and have a budget of 10,000 yen. Please suggest the best route, taking into account alternatives for rainy weather."

[0673] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0674] Step 1:

[0675] Users input information about their preferences, budget, and travel style using a terminal. This entered data is sent to the server. The user's input clarifies their travel preferences and budget constraints, serving as the basis for the server to generate subsequent suggestions.

[0676] Step 2:

[0677] The server receives and stores information sent from users using data collection methods. Next, it obtains travel-related information from other travel booking platforms through external data acquisition methods. The server aggregates relevant travel information using APIs, thereby expanding travel options.

[0678] Step 3:

[0679] The server uses artificial intelligence processing to analyze user information and data acquired from external sources to generate personalized travel suggestions. Specifically, data calculations involve analyzing past user data and similar trends, and an optimized travel plan is created using a generative AI model. Suggestions are prepared to match the user's preferences and budget.

[0680] Step 4:

[0681] The server sends travel suggestions generated using an information notification system to the terminal. The user receives this and reviews the suggested plan. Information notifications are provided in real time, allowing users to select or modify their travel schedule.

[0682] Step 5:

[0683] The user reviews the proposed travel plan and provides feedback as needed. The server receives this feedback and dynamically modifies the travel plan. Based on travel conditions and user requests, the plan is recalculated and a new proposal is made.

[0684] Step 6:

[0685] During your trip, the server provides real-time local information through your device. Based on traffic conditions and weather changes, the server uses integrated information processing to dynamically adjust your sightseeing route. This ensures that you always have access to the optimal route.

[0686] Step 7:

[0687] After the trip ends, users provide detailed feedback on their travel experience. The server uses this information to optimize future trips, contributing to overall system accuracy improvements. This cycle enables a better user experience.

[0688] 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.

[0689] This invention further enhances the personalized travel experience by integrating an emotion engine that recognizes user emotions, in addition to conventional travel suggestion systems. This system consists of a server, a terminal, and user interaction.

[0690] First, the server receives information from the user, such as preferences, budget, and travel style, and stores it in a database. The terminal collects this information from the user and sends it to the server. The server also retrieves travel-related information from other travel booking platforms based on the user information and generates the optimal plan.

[0691] A distinctive feature of this invention is the incorporation of an emotion engine. The terminal uses a camera, microphone, and sensors to collect and analyze the emotions the user is experiencing during their trip. The server determines the user's current emotional state from the acquired emotion data and adjusts the travel experience provided to be optimized according to changes in emotions.

[0692] For example, if the emotion engine detects that a user is feeling dissatisfied at a certain point during their trip, the server can immediately restructure the plan and suggest alternative activities or sightseeing destinations. Similarly, if the server recognizes that the user is experiencing a very high level of emotion, it can make suggestions to maintain that emotion (e.g., tickets to a special event or recommendations for special interactions).

[0693] This kind of collaboration allows users to always enjoy a travel experience that matches their mood at any given time. The device notifies the user of updates from the server in real time and continuously provides appropriate feedback that reflects their emotional state. Through the collaboration of the server and the emotion engine, users can enjoy their travels with a higher level of satisfaction.

[0694] The following describes the processing flow.

[0695] Step 1:

[0696] The user enters travel information using a terminal. This includes various information such as preferences, budget, and travel style. The terminal collects this information and sends it to the server.

[0697] Step 2:

[0698] Based on the information received from the terminal, the server retrieves travel-related data from other travel booking platforms. This includes accommodation, transportation, and activity options.

[0699] Step 3:

[0700] The server uses artificial intelligence processing to analyze the acquired data and generate a travel plan optimized for the user's preferences and budget.

[0701] Step 4:

[0702] The emotion engine uses the device's camera and microphone to collect emotional data such as the user's voice and facial expressions. The device then sends this data to a server.

[0703] Step 5:

[0704] The server analyzes the received emotional data to determine the user's current emotional state. For example, if the user is feeling anxious, it identifies the cause and suggests activities that can help them relax.

[0705] Step 6:

[0706] The server readjusts the travel plan in response to changes in emotions. If necessary, it generates suggestions for new activities and tourist destinations and updates the plan.

[0707] Step 7:

[0708] The device receives update information from the server and notifies the user in real time. Based on this, the user can decide on their next course of action.

[0709] Step 8:

[0710] Users can provide feedback through their devices. The server uses this feedback to further refine the plan and continue to provide the best possible travel experience.

[0711] (Example 2)

[0712] 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".

[0713] Conventional travel suggestion systems could only offer suggestions based on users' fixed preferences and conditions, making it difficult to provide personalized services that could respond immediately to changes in users' emotions and circumstances during their trip. Furthermore, they lacked sufficient real-time information updates, making them unable to adapt to dynamic local conditions.

[0714] 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.

[0715] In this invention, the server includes information gathering means for generating an optimized travel plan based on the user's preferences, budget, and travel style; external information acquisition means for obtaining travel-related information from other booking platforms; and emotion detection means for detecting the user's emotional state and dynamically adjusting the plan accordingly. This makes it possible to provide a personalized travel experience that responds to changes in the user's emotions and circumstances.

[0716] "Information gathering means" refers to technologies or functions for efficiently collecting personal information such as users' preferences, budgets, and travel styles.

[0717] "External information acquisition means" refers to technologies or functions for obtaining travel-related information from other booking platforms or information sources.

[0718] "Artificial intelligence processing means" refers to AI technology or algorithms used to formulate personalized suggestions based on user information.

[0719] "Notification means" refers to technologies or functions that provide users with real-time local information and updates, and that reflect the latest conditions.

[0720] "Emotion detection means" refers to a technology or function that detects the user's emotional state and dynamically adjusts the travel plan based on that information.

[0721] This invention provides technology for a travel suggestion system that offers a personalized travel experience that takes into account the user's emotional state. This system is implemented through interaction between a server, a terminal, and the user.

[0722] First, the device collects information from the user about their preferences, budget, and travel style. This is done using an interface built into the device, which the user enters. This information is then encrypted and sent to the server.

[0723] The server stores the received information in a database and performs analysis. The server uses external information acquisition means to obtain travel-related information from other travel booking platforms. Furthermore, it uses artificial intelligence processing means to generate optimized travel plans based on user information. This system also includes emotion detection means to receive emotion data from the terminal. This allows the system to analyze the user's emotional state and dynamically adjust the travel plan.

[0724] As a concrete example, suppose a user uses a device and receives suggestions for potential tourist destinations and events they might visit while planning a trip. At this point, the device's camera and sensors collect the user's emotional data and send it to a server. The server analyzes this data, and if the user's emotions are heightened, it can suggest special events or activities to maintain those emotions.

[0725] For example, the following prompt could be used with a generative AI model: "The user is dissatisfied with their current trip. As an alternative, suggest a guided tour of a nearby nature park. Also, if they are excited, consider offering them VIP tickets to a local festival currently taking place at their destination."

[0726] Based on this prompt, the AI ​​model generates a new travel plan and notifies the user of the results in real time via their device. This allows users to enjoy the optimal travel experience tailored to their emotions and circumstances at the time.

[0727] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0728] Step 1:

[0729] The user enters information about their travel preferences, budget, and travel style into the device. The device collects, encrypts, and temporarily stores this information. The entered data includes details about the tourist destinations they want to visit and the activities they wish to do. This information is sent directly to the server for later analysis.

[0730] Step 2:

[0731] User information is sent from the terminal to the server. The server receives this data and stores it in a database. Based on the received information, the server begins data analysis and integrates information from external travel booking platforms. This transforms it into a comprehensive dataset that also takes into account the travel history of other users and current trends.

[0732] Step 3:

[0733] The server generates travel plans based on collected data. Using artificial intelligence processing, it analyzes past data and patterns to create optimized travel plans. The generated plans include planned tourist destinations, activities, and accommodations. Here, prompts are input into the AI ​​model to generate new ideas and suggestions.

[0734] Step 4:

[0735] The device collects user emotional data during travel. Using cameras, microphones, and sensors, it analyzes the user's facial expressions, voice, and physical reactions in real time. This data is sent to a server to evaluate the user's emotional state.

[0736] Step 5:

[0737] The server analyzes emotional data sent from the terminal. The server determines the user's emotions during the trip and dynamically reconfigures the travel plan based on the results. For example, if the user expresses dissatisfaction, it suggests alternative tourist destinations or activities. These suggestions are generated using a generative AI model.

[0738] Step 6:

[0739] The device notifies the user in real time of updated plans and suggestions. The user can review these and adjust their travel plans based on the new suggestions. Pop-up notifications appear on the device, and a voice assistant provides explanations, offering user-friendly feedback.

[0740] (Application Example 2)

[0741] 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".

[0742] Traditional travel suggestion systems have optimized travel plans based on user preferences and budgets, but they have a weakness in that they lack personalization that takes user emotions into account. In particular, the inability to dynamically optimize the travel experience in response to changes in emotions during the trip has been an obstacle to increasing user satisfaction.

[0743] 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.

[0744] In this invention, the server includes data collection means for generating an optimized travel plan based on the user's preferences, budget, and travel style; external data acquisition means for obtaining travel-related information from other travel booking platforms; and emotion analysis means for performing emotion recognition. This enables the dynamic optimization of the travel experience in response to the user's emotions.

[0745] "Data collection means" refers to functions for collecting information related to users' preferences, budgets, and travel styles.

[0746] "External data acquisition means" refers to a function that allows you to obtain information necessary for optimizing your travel plan from other travel booking platforms.

[0747] "Artificial intelligence processing means" refers to a function that processes data to formulate personalized travel suggestions based on acquired user information.

[0748] "Information notification means" refers to a function that notifies users of the latest local travel conditions in real time.

[0749] "Emotional analysis means" refers to a function for recognizing and analyzing the user's emotions, using user interfaces and sensor data.

[0750] The "proposal adjustment mechanism" is a function that dynamically adjusts travel plans to provide a travel experience that responds to the user's emotions.

[0751] The implementation of this system requires data collection means, external data acquisition means, artificial intelligence processing means, information notification means, sentiment analysis means, and proposal adjustment means.

[0752] The server collects information such as user preferences, budget, and travel style using data collection methods. This allows the server to understand the user's individualized requests. Subsequently, it obtains travel-related information from other travel booking platforms via external data acquisition methods. This external data includes destination attractions, accommodations, transportation options, and local events.

[0753] The device uses sensors such as cameras and microphones to collect emotions from the user's facial expressions and voice, and analyzes this data using emotion analysis tools. The results of this analysis are sent to a server, where artificial intelligence processing tools construct an optimal travel experience tailored to the user's emotions.

[0754] Based on user sentiment information, the server dynamically adjusts the travel plan and provides real-time feedback to the user through the terminal's information notification system. This makes it possible to provide the user with the most comfortable and satisfying travel experience.

[0755] For example, if the emotion analysis system determines that a user is experiencing stress at a particular tourist destination during a trip, the server can immediately suggest alternative tourist destinations or activities to alleviate the situation. Conversely, if the user is having a great time, suggestions will be made to encourage participation in events that will help maintain that positive feeling.

[0756] Using a generative AI model, an example of a prompt message for this system to function is: "Design a system that senses the user's emotional changes in real time during travel and suggests the most suitable sightseeing activities based on those emotions. Use facial expressions and voice data for emotion recognition."

[0757] This enables personalized travel experiences that cater to a range of emotions during the journey.

[0758] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0759] Step 1:

[0760] The server collects basic data about the user's preferences, budget, and travel style using data collection methods. At this stage, various information entered by the user through the application is stored in the database. The input data includes the user's preferences, budget, and travel style, and a user profile is formed based on this data.

[0761] Step 2:

[0762] The server collects comprehensive travel information related to the destination from other travel booking platforms via external data acquisition means. This information includes attractions, accommodations, transportation, and event information. This external information is analyzed to create a comprehensive list of travel options, preparing for the next process.

[0763] Step 3:

[0764] The device's sensing capabilities collect real-time emotional data through the user's facial expressions and voice. Using the camera and microphone, it acquires raw emotional data such as changes in the user's facial expressions and tone of voice. The input consists of visual and auditory data, which is processed by emotion analysis tools to identify the emotional state.

[0765] Step 4:

[0766] The server uses artificial intelligence processing to personalize the travel experience based on emotional data obtained through emotion analysis. Here, it combines the user's emotional state and preference profile to generate optimal sightseeing activities and itinerary modifications. The output is a new travel plan best suited to the user's current emotions.

[0767] Step 5:

[0768] The server notifies users in real time of new travel plans and sightseeing activities suggested by the server through the terminal's information notification system. Users receive these suggestions through screen displays and voice guidance and select their next action. In this step, the optimal travel options for the user are specifically presented as output.

[0769] Step 6:

[0770] The system is continuously optimized by collecting user feedback on the device and sending it back to the server. Users input their satisfaction with suggested activities and any new requests, which are then used to process and analyze the data again. This process enables further personalization and optimization of the experience.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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."

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] The following is further disclosed regarding the embodiments described above.

[0793] (Claim 1)

[0794] A data collection method for generating an optimized travel plan based on the user's preferences, budget, and travel style,

[0795] External data acquisition methods for obtaining travel-related information from other travel booking platforms,

[0796] An artificial intelligence processing system that formulates personalized travel suggestions based on user information,

[0797] A means of providing real-time local information and information notifications that reflect the latest travel conditions to users,

[0798] A system that includes this.

[0799] (Claim 2)

[0800] The system according to claim 1, characterized in that the artificial intelligence processing means dynamically modifies travel suggestions based on user feedback.

[0801] (Claim 3)

[0802] The system according to claim 1, characterized in that the information notification means provides information based on the local cultural context and includes multilingual support.

[0803] "Example 1"

[0804] (Claim 1)

[0805] Information receiving means for generating an optimized travel plan based on the user's preferences, budget, and travel style,

[0806] External information acquisition means for obtaining travel-related information from other databases,

[0807] An artificial intelligence analysis tool that formulates personalized travel suggestions based on user information,

[0808] A means of providing information that delivers local information in real time and reflects the latest travel conditions for users,

[0809] A means of updating the travel plan dynamically by receiving user feedback after the start of the itinerary,

[0810] A system that includes this.

[0811] (Claim 2)

[0812] The system according to claim 1, characterized in that the artificial intelligence analysis means optimizes the travel plan based on user feedback using a generated AI model.

[0813] (Claim 3)

[0814] The system according to claim 1, characterized in that the means of providing information includes providing information based on the local cultural background and includes multilingual support.

[0815] "Application Example 1"

[0816] (Claim 1)

[0817] A data collection method for generating an optimized travel plan based on the user's preferences, budget, and travel style,

[0818] External data acquisition methods for obtaining travel-related information from other travel booking platforms,

[0819] An artificial intelligence processing system that formulates personalized travel suggestions based on user information,

[0820] A means of providing real-time local information and information notifications that reflect the latest travel conditions to users,

[0821] An integrated information processing system that combines urban tourism and transportation information to provide dynamic tourist routes,

[0822] A system that includes this.

[0823] (Claim 2)

[0824] The system according to claim 1, characterized in that the artificial intelligence processing means dynamically modifies travel suggestions based on user feedback.

[0825] (Claim 3)

[0826] The system according to claim 1, characterized in that the information notification means provides information based on the local cultural context and includes multilingual support.

[0827] "Example 2 of combining an emotion engine"

[0828] (Claim 1)

[0829] Information gathering means for generating an optimized travel plan based on the user's preferences, budget, and travel style,

[0830] External information acquisition methods for obtaining travel-related information from other booking platforms,

[0831] An artificial intelligence processing method that formulates personalized suggestions based on user information,

[0832] A notification method that provides real-time local information and reflects the latest conditions to users,

[0833] An emotion detection means that detects the user's emotional state and dynamically adjusts the plan based on it,

[0834] A system that includes this.

[0835] (Claim 2)

[0836] The system according to claim 1, characterized in that the artificial intelligence processing means dynamically adjusts the proposal based on changes in emotional state.

[0837] (Claim 3)

[0838] The system according to claim 1, characterized in that the means of information notification provides information based on the local cultural context and includes multilingual support.

[0839] "Application example 2 when combining with an emotional engine"

[0840] (Claim 1)

[0841] A data collection method for generating an optimized travel plan based on the user's preferences, budget, and travel style,

[0842] External data acquisition methods for obtaining travel-related information from other travel booking platforms,

[0843] An artificial intelligence processing system that formulates personalized travel suggestions based on user information,

[0844] A means of providing real-time local information and information notifications that reflect the latest travel conditions to users,

[0845] A means of emotion analysis for performing emotion recognition,

[0846] A suggestion adjustment mechanism that dynamically optimizes the travel experience according to the user's emotions,

[0847] A system that includes this.

[0848] (Claim 2)

[0849] The system according to claim 1, characterized in that the artificial intelligence processing means dynamically modifies travel suggestions based on the user's emotional data.

[0850] (Claim 3)

[0851] The system according to claim 1, characterized in that the information notification means provides information based on the local cultural context and includes multilingual support. [Explanation of Symbols]

[0852] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data collection method for generating an optimized travel plan based on the user's preferences, budget, and travel style, External data acquisition methods for obtaining travel-related information from other travel booking platforms, An artificial intelligence processing system that formulates personalized travel suggestions based on user information, A means of providing real-time local information and information notifications that reflect the latest travel conditions to users, A system that includes this.

2. The system according to claim 1, characterized in that the artificial intelligence processing means dynamically modifies travel suggestions based on user feedback.

3. The system according to claim 1, characterized in that the information notification means provides information based on the local cultural context and includes multilingual support.

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