system

Abstract

We provide the system. [Solution] A terminal device for travelers to input their desired conditions, A server means that receives the desired conditions transmitted from the terminal means, A system means comprising a generation model for generating an optimal travel plan based on the aforementioned desired conditions, A data collection means for collecting real-time data in order to optimize the travel plan generated by the aforementioned generation model, A booking method that automatically makes reservations based on the optimized travel plan, 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, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Travelers have to spend a lot of time and effort on selecting a destination, budget management, arranging transportation and accommodation, etc. when planning a trip, and there is a problem that the travel plan is becoming complicated. Also, it is difficult to optimize a travel plan based on real-time information and individual needs of travelers, and there is also a problem that it is impossible to appropriately respond to changes in the situation during the trip.

Means for Solving the Problems

[0005] This invention provides a terminal means for travelers to input their desired conditions and a server means for receiving the desired conditions transmitted from the terminal means. Furthermore, it includes a system means that uses a generation model to generate an optimal travel plan based on the desired conditions, and optimizes the plan using a data collection means that collects real-time data. In addition, it includes a reservation means that automatically makes reservations based on the optimized plan, enabling more efficient travel planning and the provision of plans tailored to individual needs. Furthermore, it includes a function that provides advice in response to changes in circumstances during travel based on real-time data collected by the data collection means, and integrates sensor data to adjust the plan according to the traveler's health condition.

[0006] "Terminal means" refers to a device used by travelers to input their travel preferences and conditions, and to input and transmit information.

[0007] The term "server means" refers to a central computer system that receives and processes data transmitted from terminal means, and performs the calculations and data management necessary for generating travel plans.

[0008] A "generative model" refers to artificial intelligence or machine learning technology used to generate optimal travel plans based on the traveler's input preferences, proposing plans using past data and patterns.

[0009] "System means" refers to a set of hardware and software configurations for generating travel plans and integrating and managing related operations.

[0010] "Data collection means" refers to technologies or devices for collecting real-time information necessary for optimizing travel plans, and involves acquiring information from external databases or sensors.

[0011] "Booking method" refers to a system or method for automatically making the necessary travel arrangements based on an optimized travel plan, and which guarantees the completion of the booking.

[0012] "Advice tools" refer to technologies that provide travelers with appropriate guidance for various situations that may arise during their trip, offering suggestions in real time.

[0013] "Sensor data" refers to measurement data used to understand a traveler's health status and activity level, and is obtained from wearable devices and other sources. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

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

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

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

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

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

[0022] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0035] This invention is a system designed to streamline travel planning and reduce the burden on travelers, and in particular, utilizes AI technology to provide travelers with personalized travel plans. This system mainly consists of terminal means, server means, generative models, data collection means, reservation means, advice means, and integration of sensor data.

[0036] First, the user enters their travel preferences using a terminal device. This includes destination, budget, travel duration, and travel companion information. The terminal sends this information to the server. The server analyzes the received data and uses a generative model to generate the optimal travel plan that matches the user's conditions. This plan includes suggestions for flights, accommodations, sightseeing spots, activities, and more.

[0037] The server further collects real-time information using data collection methods and continuously optimizes the generated plan. This allows for adjustments in response to changes in weather, event information, and traffic conditions.

[0038] Once the user reviews and accepts the proposed plan, a booking request is sent from the device to the server. The server automatically completes the booking process using the booking method, including arranging flights and accommodations. If the booking is successfully completed, confirmation information is sent to the device and the user is notified.

[0039] During travel, the server uses advisory tools to provide travelers with real-time, situation-based advice. This allows travelers to continue their trip safely and comfortably. Furthermore, sensor data can be integrated to take into account the individual traveler's health condition, and travel plans can be adjusted as needed.

[0040] For example, if a user requests a plan for a 5-day trip to New York City with a budget of 200,000 yen for two people, the server will use that information to select the best flights and accommodations, and suggest popular tourist destinations and restaurants. Once the plan is accepted, the system will immediately execute the booking and automate the entire process until all arrangements are completed.

[0041] Thus, the present invention enables travelers to enjoy an efficient and personalized travel experience without having to spend time on detailed planning.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users enter their travel preferences through their device. These preferences include destination, budget, travel duration, and travel companion information, and this data is necessary for planning the trip.

[0045] Step 2:

[0046] The device sends the user's entered preferences to the server. This information is formatted as an API request and processed to ensure it reaches the server quickly and securely.

[0047] Step 3:

[0048] The server analyzes the data received from the terminal and generates the optimal travel plan using a generative model. The generative model utilizes historical data and algorithms to combine flights, accommodations, tourist destinations, and activities that match the budget and schedule.

[0049] Step 4:

[0050] The server uses data collection methods to gather real-time information and optimize the generated travel plan. Specifically, it adjusts the plan by considering factors such as weather forecasts, local events, and congestion information.

[0051] Step 5:

[0052] The server sends an optimized travel plan to the user's device and proposes it to them. The user can then review the plan details and make changes or approvals.

[0053] Step 6:

[0054] After the user approves the proposed plan, the device sends that information back to the server and requests that the reservation process begin.

[0055] Step 7:

[0056] The server uses the booking method to automatically make reservations for flights and accommodations based on the proposed plan. It collaborates with partner booking systems and retrieves confirmation information once the arrangements are complete.

[0057] Step 8:

[0058] The server notifies the terminal that the reservation is complete and provides the user with final confirmation information. This allows the user to confirm that all reservations have been completed without any problems.

[0059] Step 9:

[0060] During the trip, the server uses its advisory system to send appropriate advice to the user based on real-time data collected. This makes it easier for the user to cope with unexpected changes during their trip.

[0061] Step 10:

[0062] The server integrates sensor data to adjust the plan based on the user's health status and activity level, modifying the plan as needed. This adjustment ensures the user can continue their journey safely and comfortably.

[0063] (Example 1)

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

[0065] In travel planning, travelers face the challenge of having to spend considerable time and effort choosing the best plan from many options. Furthermore, during the actual trip, it is difficult to respond quickly to changing circumstances, adding to the difficulties. Additionally, effectively adjusting the plan while considering the traveler's health condition is also challenging.

[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 input mechanism for inputting the traveler's desired conditions, a component comprising a generation model for generating optimal travel suggestions based on those conditions, and an information gathering mechanism for collecting real-time information and optimizing the generated suggestions. This enables travelers to quickly and accurately formulate efficient and personalized travel plans, and to respond flexibly to changes in circumstances and health conditions during their trip.

[0068] An "information input mechanism" refers to a device or interface used by travelers to input their desired conditions.

[0069] An "information processing device" is a device that receives, analyzes, and processes data transmitted from an information input mechanism.

[0070] A "generative model" refers to an algorithm or data model used to generate optimal travel suggestions based on a traveler's preferences.

[0071] "Components" refer to the multiple technical or functional elements necessary to form a system.

[0072] The "information gathering mechanism" refers to a function that acquires necessary information in real time and optimizes the generated travel suggestions.

[0073] A "reservation system" refers to a system or device that automatically makes various arrangements based on travel proposals.

[0074] A "guidance body" is an organization that provides appropriate advice to travelers in response to changes in their circumstances during their trip.

[0075] "Sensor data" refers to numerical information obtained from various sensors, and this data is used to understand the health status of travelers.

[0076] This invention is a system that streamlines travelers' travel planning and provides personalized travel experiences. The system comprises an information input mechanism, an information processing device, a generation model, an information collection mechanism, a reservation mechanism, and a guidance mechanism.

[0077] First, the user uses a terminal to enter their travel preferences. For example, they enter specific information such as destination, budget, number of travel days, and number of companions. This information is entered as a prompt message in the format of "5-day trip to New York, budget 200,000 yen, 2 people." The terminal then sends this information to the server.

[0078] The server analyzes the input information received using an information processing device. Generative AI models are used for the analysis, employing AI frameworks such as TENSORFLOW® and PyTorch. The generative AI model generates travel suggestions that are optimal for the user's conditions. These suggestions include recommended lists of flights, accommodations, tourist destinations, and activities.

[0079] Furthermore, the server uses an information gathering mechanism to acquire real-time data and optimize the suggestions generated based on weather, event information, and traffic conditions. This allows the server to provide plans that match the user's needs and meet appropriate conditions.

[0080] Once the user accepts the generated proposal, a booking request is sent from the device to the server. The server automatically executes the booking using its booking mechanism. Specifically, it interacts with an external travel booking system via an API and performs the necessary booking procedures.

[0081] During travel, the server uses a guidance mechanism to provide users with real-time, situation-appropriate advice. This advice includes suggestions for tourist destinations to visit and information on events. It can also integrate sensor data from wearable devices and adjust travel plans based on the user's health condition.

[0082] In this way, the various components of the system work together, allowing users to experience efficient and comfortable travel.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] The user uses a terminal to enter their travel preferences. Specifically, this includes destination, budget, duration of trip, and information about travel companions. This information is entered as a prompt message such as "5-day trip to New York, budget 200,000 yen, 2 people." The entered data is then sent from the terminal to the server.

[0086] Step 2:

[0087] The server analyzes the prompt message received from the user using an information processing device. During the analysis process, a generative AI model is used to generate optimal travel suggestions, taking into account past data and trends. At this point, a list of flights and accommodations that match the user's criteria, along with suggested tourist destinations and activities, are output.

[0088] Step 3:

[0089] The server uses an information gathering mechanism to acquire real-time data from external resources. Specifically, it collects weather information, event information, traffic information, etc., and incorporates this into the generated suggestions. This improves the accuracy and timeliness of the suggestions, providing users with plans optimized for their needs.

[0090] Step 4:

[0091] The user reviews the suggested travel plan on their device. If they agree to the suggestion, the user sends a booking request from their device to the server. This request includes details of the selected flights and accommodations.

[0092] Step 5:

[0093] The server activates the reservation mechanism and automatically makes the necessary arrangements. Flight and accommodation reservations are made through integration with external travel reservation systems. Once the reservation is complete, the details are sent from the server to the terminal and notified to the user.

[0094] Step 6:

[0095] During travel, the server provides real-time advice to the user using a guidance mechanism. This includes optimal action suggestions based on current location information and real-time sensor data, as well as notifications regarding disaster information and emergency events. Information from the user's health devices is also integrated, allowing for adjustments to the plan based on their health status.

[0096] (Application Example 1)

[0097] 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."

[0098] Traditional travel planning systems struggled to fully meet individual needs, making the planning and arrangement process cumbersome and time-consuming for users. Furthermore, they lacked the flexibility to adjust plans based on real-time information, making it difficult to provide an efficient travel experience. Additionally, the automatic adjustment of plans to take into account the user's health condition was not present in previous systems.

[0099] 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.

[0100] In this invention, the server includes a dialogue device means for voice input of the user's desired conditions to an information processing device, an information processing means for generating an optimal travel plan using a generative model, and an information gathering means for acquiring current information. This enables the automatic generation of individual travel plans based on the user's voice input, flexible optimization and adjustment with real-time information, and the provision of an efficient and personalized travel experience without burdening the user.

[0101] A "dialogue device" is a device that allows users to input their desired conditions via voice and transmit them to an information processing device.

[0102] An "information processing device" is a device that generates a travel plan using a generative model based on the desired conditions received from a dialogue device.

[0103] A "generative model" is an algorithm or program used to create the optimal travel plan based on the user's desired conditions.

[0104] "Information gathering methods" refer to means of acquiring information related to the current challenges and optimizing the generated travel plan.

[0105] "Arrangement method" refers to a function or service that automatically makes travel-related arrangements based on an optimized travel plan.

[0106] "Advice methods" refer to means of providing advice based on current information obtained through information gathering methods, in response to changes in circumstances during travel.

[0107] "Sensor data" refers to data from sensors used to understand the user's health status.

[0108] Modes for carrying out the invention

[0109] The system for implementing this invention consists of a set of programs and hardware designed to efficiently personalize travel plans and reduce the burden on the user. The system primarily operates using the following hardware and software:

[0110] The interactive terminal serves the purpose of inputting travel preferences from the user via voice. This device converts the voice into text using speech recognition software such as Google® Speech-to-Text API and transmits it to the information processing device.

[0111] Based on the received text information, the information processing device generates a travel plan using a generative AI model (e.g., OpenAI® GPT-4®). The generated plan is optimized by incorporating current information obtained through information gathering means, such as weather information and event information. The information gathering means used here include using APIs from the internet and collecting sensor data.

[0112] As a means of arrangement, travel-related arrangements will be automated using the Amadeus API and other tools. This automation will free users from cumbersome procedures, making it easy to arrange the perfect trip.

[0113] Furthermore, the advisory system provides specific advice based on real-time data, adapting to changing circumstances during the trip. This is crucial for taking the best possible action in response to unexpected events that may occur locally and the user's health condition.

[0114] For example, if a user enters their preferences, such as "I want to take a family trip next weekend. I'd like a warm destination and a health-conscious itinerary," the system will provide a customized plan based on that information.

[0115] An example of a prompt message is: "The user is planning a family trip next weekend. The destination is a warm region, so please create a health-conscious plan. Please take the latest weather information into consideration."

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

[0117] Step 1:

[0118] The device receives the user's voice input. The user communicates their desired travel conditions to the device as voice. This voice data is converted into text data using speech recognition software (Google Speech-to-Text API). Here, the input is raw voice data, and the output is the desired conditions in text format.

[0119] Step 2:

[0120] The server receives desired travel conditions in text format from the terminal. Based on the received data, a generative AI model (OpenAI GPT-4) generates the optimal travel plan. The input is text data reflecting the user's travel conditions, and the output is an initial travel plan proposal.

[0121] Step 3:

[0122] The server uses information gathering methods to obtain current information. It utilizes APIs from the internet and sensor data, such as weather information and local event information. Using this data, it optimizes the plan based on the latest information. The input is real-time data from the internet and sensors, and the output is an optimized travel plan.

[0123] Step 4:

[0124] The server automatically makes the necessary travel arrangements using booking methods based on the optimized travel plan. Here, it uses the Amadeus API, among others, to book flights and accommodations. The input is the optimized travel plan, and the output is confirmation information of the completed arrangements.

[0125] Step 5:

[0126] The user confirms the completion of their travel plan and arrangements through their device. They receive confirmation information sent from the server and verify that the plan has been approved. The input is the confirmation information from the server, and the output is the notification to the user.

[0127] Step 6:

[0128] The server constantly utilizes information gathering methods to respond to changing circumstances during travel and provides real-time advice. It also adjusts plans based on health conditions and weather changes. The input is continuously collected real-time data, and the output is specific advice tailored to that situation.

[0129] 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.

[0130] This invention is a system that recognizes travelers' emotions and incorporates them into travel plans to provide a more satisfying travel experience. In addition to the basic configuration of conventional systems, this system incorporates an emotion engine to grasp the traveler's emotional state in real time and utilize it for plan generation and adjustment.

[0131] The user enters their travel preferences using a terminal. This input includes destination, budget, travel duration, and travel companion information. The terminal sends the input data to the server. The server uses this data to create a travel plan using a generative model. During this generation process, an emotion engine operates to analyze the traveler's emotional state. This emotional state is obtained by combining the data entered by the user with information obtained from external devices.

[0132] The server further utilizes data collection methods to aggregate external data in real time and optimize the plan. At this time, the emotion engine identifies and aligns factors such as the traveler's emotional satisfaction, thereby providing a travel plan that satisfies the traveler.

[0133] Furthermore, if the user provides feedback regarding their emotions or the plan, the plan will be adjusted. The device also sends emotional data to the server as part of the communication. The server uses this data to inform the emotion engine, which then initiates or modifies the plan to match the traveler's current emotional state.

[0134] In practice, for example, if a user creates a plan with conditions such as "a 7-day trip to London, budget of 300,000 yen, for 2 people," the server will create the optimal travel plan based on that information and emotional data. If the user's mood changes during the trip, for example, if it is determined that relaxation is needed, the server will suggest new events and sightseeing spots suitable for relaxation. Conversely, if the user wants to be active, the plan will be adjusted to include more sports events and activities.

[0135] This enables a highly personalized travel experience that reflects the user's actual emotional state. By integrating with an emotion engine, this system further enhances user travel satisfaction.

[0136] The following describes the processing flow.

[0137] Step 1:

[0138] Users enter basic travel information and preferences through their device. This includes destination, budget, travel duration, and information about travel companions.

[0139] Step 2:

[0140] The terminal sends the information entered by the user to the server. This transmitted data becomes the source data for creating the travel plan.

[0141] Step 3:

[0142] The server analyzes the received data and uses a generative model to create a basic travel plan. At this point, the user's emotional state is not yet taken into consideration.

[0143] Step 4:

[0144] The server activates the emotion engine and analyzes the user's emotional data. This emotional data includes facial recognition, voice analysis data, and vital signs information acquired in real time from terminals and wearable devices.

[0145] Step 5:

[0146] Based on the analysis results of the emotion engine, the server customizes the generated travel plan according to the user's emotional state. For example, if the user is experiencing high stress, a relaxing plan will be added.

[0147] Step 6:

[0148] The server further optimizes travel plans based on external data obtained in real time using data collection methods. This information includes weather changes and local event information.

[0149] Step 7:

[0150] The server sends the adjusted plan to the terminal and proposes it to the user. The user can review the plan and send feedback as needed.

[0151] Step 8:

[0152] Once the user accepts the plan, the device sends this information to the server and begins the reservation process.

[0153] Step 9:

[0154] The server automatically makes all travel reservations based on the pre-arranged plan using the reservation system. The user confirms the completed reservation information by receiving a notification on their device.

[0155] Step 10:

[0156] During the trip, the server continuously monitors the user using an emotion engine, dynamically adjusting the travel plan accordingly if there are any changes in the user's emotional state, providing the traveler with the best possible experience.

[0157] (Example 2)

[0158] 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".

[0159] Traditional travel planning systems struggle to take into account travelers' emotional states and real-time environmental changes, resulting in the provision of plans that are not optimal for the traveler. Furthermore, they lack the means to quickly respond to changing circumstances during travel and improve traveler satisfaction. This leads to the challenge of standardized travel experiences that fail to meet individual needs.

[0160] 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.

[0161] In this invention, the server includes an analysis means incorporating an emotion analysis engine for analyzing the emotional state of travelers in real time, a data collection means for aggregating data to optimize a travel plan generated by a generative artificial intelligence model based on emotional data and real-time data, and a reservation means for automatically making reservations based on the optimized travel plan. This makes it possible to provide a personalized travel experience that is tailored to the emotional state and environmental changes of each individual traveler.

[0162] "Information equipment" refers to devices that travelers use to input their desired conditions and transmit them to a server. Specifically, this includes smartphones, tablets, and personal computers.

[0163] "Computing device means" refers to a device that receives and processes data transmitted from information equipment means. Servers and cloud computing environments fall into this category.

[0164] A "generative artificial intelligence model" refers to a model that uses machine learning techniques to automatically generate travel plans based on input data.

[0165] A "emotion analysis engine" refers to a processing engine that analyzes a traveler's emotional state in real time and uses that data to adapt travel plans.

[0166] "Analysis means" refers to devices or programs used to extract and understand the emotional state of a user from data.

[0167] "Data collection methods" refer to means of aggregating real-time data on travelers' emotions and the environment, and using that data to optimize travel planning.

[0168] "Reservation method" refers to a system element that automatically makes reservations for various services and events based on an optimized travel plan.

[0169] This invention provides a system that generates travel plans that take into account the emotional state of travelers based on their desired conditions. Specifically, it uses a terminal, a server, and a generative AI model and emotion analysis engine that handle various types of data.

[0170] Users input their desired travel conditions, such as destination, budget, duration, and travel companion information, using information devices such as smartphones or personal computers. These information devices transmit the user's input data to the server. The data sent from the terminal is received by the server, which is a computing device.

[0171] The server uses a generative artificial intelligence model to generate a travel plan from the received data. This generative AI model utilizes machine learning techniques to generate the optimal travel plan for given conditions. During this process, an emotion analysis engine operates to analyze the user's emotional state in real time. The analyzed emotion data is acquired based on sensor information from external wearable devices and smartphones and incorporated into the travel plan.

[0172] Next, the server uses data collection methods to aggregate real-time data such as weather information and event information. This allows the travel plan to be optimized according to the user's emotional state. As part of the optimization process, if the user wants to relax, it suggests activities suitable for relaxation, and if they want to be active, it provides a plan that includes many sports events and activities.

[0173] For example, if a user enters the conditions "7-day trip to London, budget 300,000 yen, 2 people," the server will consider this information along with emotional data to generate the optimal travel plan. If it determines that relaxation is needed during the trip, it will suggest events and sightseeing spots suitable for relaxation; conversely, if the user wants to be active, it will suggest sports events and activities.

[0174] An example of a prompt for the generating AI model would be, "Based on the user's emotional data, please suggest a relaxing London travel plan. The budget is 300,000 yen, for 7 days, for 2 people." This embodiment of the present invention makes it possible to realize a personalized travel experience that matches the user's current emotions and preferences.

[0175] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0176] Step 1:

[0177] Users input their travel preferences using devices such as smartphones or computers. These preferences include destination, budget, travel duration, and travel companion information. The entered data is formatted as needed within the device and prepared as structured data. This structured data is then sent to the server via an HTTP request. The input consists of the user-specified preferences, while the output is structured data transferred to the server.

[0178] Step 2:

[0179] The server receives structured data sent from the terminal. The received data is parsed and prepared to be input into the generative AI model. The server uses the generative AI model to begin creating a travel plan based on the input data. The input data consists of desired conditions, and the output is a provisional travel plan. The generative AI model parses this data and proposes the optimal travel plan via prompt messages.

[0180] Step 3:

[0181] The server runs an emotion analysis engine to analyze the user's emotional state in real time. Based on biometric and behavioral data obtained from the terminal and wearable sensors, it evaluates the user's current emotional state. Biometric information from the terminal and wearable devices is used as input, and the analyzed emotion data is provided as output.

[0182] Step 4:

[0183] The server optimizes the initial travel plan by combining analyzed sentiment data with real-time data collected from external sources (weather, event information, etc.). Data collection methods gather this information and make adjustments to reflect it in the plan. The input includes sentiment data and external real-time information, and the output is an optimized travel plan. This process involves re-evaluating the generative AI model to provide a travel plan that is adapted to emotions and the environment.

[0184] Step 5:

[0185] If a user provides feedback during their trip, the device sends it to the server. The feedback is received as textual comments and ratings, and is then incorporated into the sentiment analysis engine's evaluation. The server then makes further adjustments to the travel plan based on the feedback received. The input is feedback information, and the output is a revised travel plan that reflects the feedback.

[0186] (Application Example 2)

[0187] 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".

[0188] The challenge lies in improving traveler satisfaction by recognizing travelers' emotional states in real time and providing travel itineraries that reflect this. Conventional travel plan generation systems have often failed to adequately respond to travelers' emotions and real-time changes in circumstances, resulting in an inability to provide the optimal travel experience. Therefore, there is a need for the generation and adjustment of dynamic travel itineraries that take travelers' emotions into consideration.

[0189] 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.

[0190] In this invention, the server includes a terminal device for inputting the traveler's desired requirements, an information processing device, and an emotion analysis device. This makes it possible to recognize the traveler's emotional state in real time, dynamically adjust the travel itinerary based on that, and provide a personalized and highly satisfying travel experience.

[0191] "Traveler's desired requirements" refer to the conditions that travelers have in mind when planning their trip, such as the destination, budget, number of days, and information about their travel companions.

[0192] A "terminal device" refers to an electronic device used by travelers to input their desired requirements, and includes smartphones, tablets, and other similar devices.

[0193] An "information processing device" refers to a server or computer system that receives input requests and generates travel plans.

[0194] "Generative methods" refer to algorithms and processes that automatically design the optimal travel itinerary based on the traveler's desired requirements.

[0195] An "information gathering device" refers to a device or system used to collect data necessary to understand the real-time situation during travel.

[0196] A "emotion analysis device" refers to a system that analyzes a traveler's emotional state in real time and uses the results to adjust the travel itinerary.

[0197] A "booking system" refers to a system that automatically makes reservations for accommodations, transportation, and other services based on an optimized travel itinerary.

[0198] An "advisory device" refers to a system that provides appropriate advice and suggestions based on a traveler's real-time data and emotional state.

[0199] This invention provides a system that recognizes a traveler's emotional state in real time and dynamically adjusts the travel plan based on that information. This system includes a terminal device for inputting the traveler's preferences, which the traveler inputs into a terminal device such as a smartphone or tablet. The terminal device communicates with an information processing device, i.e., a server, and transmits the input preferences to the server.

[0200] The server uses a generation method based on the received information to design the optimal travel itinerary. An AI model is used in the generation method to automatically formulate an itinerary that meets the user's desired requirements. Furthermore, the server acquires real-time data via information gathering devices and optimizes the plan by considering factors that may change during the trip.

[0201] Depending on the type of travel, the server uses an emotion analysis device to analyze the traveler's emotions. This device performs calculations based on sensor data from smart wearable devices, cameras, and other sources to understand the traveler's current emotional state.

[0202] This allows the server to suggest relaxation events if the traveler is in a relaxed state, and suggest active activities if the traveler is in an active state. Furthermore, a booking system with automated reservation capabilities ensures appropriate bookings are made and the traveler's wishes are fulfilled.

[0203] As a concrete example, consider a traveler planning a 7-day trip to London with a limited budget. In this case, a generative AI model can be used to design a plan that maximizes satisfaction. An example of a prompt would be, "I am planning a 7-day trip to London. What activities would an application with emotion recognition capabilities suggest based on whether the traveler wants to relax or be active?" In this way, it is possible to provide the optimal travel experience tailored to the user.

[0204] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0205] Step 1:

[0206] The user enters their travel plan requirements on a terminal. These requirements include destination, budget, duration, and number of travel companions. This input data is then sent from the terminal to the server.

[0207] Step 2:

[0208] The server uses a generation AI model to formulate an initial travel itinerary based on the received desired requirements. It executes a generation process based on the input requirements to construct a travel plan. A temporary travel plan is generated as output.

[0209] Step 3:

[0210] The server acquires real-time data from external sources via information gathering devices. This data includes weather information, event information, and congestion levels, and this data is used to optimize the plan.

[0211] Step 4:

[0212] The server uses an emotion analysis device to analyze the traveler's emotional state in real time. To do this, it collects sensor data from smart wearable devices or cameras and performs computational processing to identify the emotional state. This results in the traveler's current emotions being output.

[0213] Step 5:

[0214] The server combines collected real-time data with sentiment analysis results to adjust the travel plan. Based on the emotional state, it processes the data to add relaxation events or active activities to the plan. The adjusted travel plan is then output.

[0215] Step 6:

[0216] Based on the coordinated travel plan, the server's booking system automatically executes the necessary reservations. It books accommodations and arranges transportation, making the travel plan ready to be executed.

[0217] Step 7:

[0218] Users receive information about their current travel plan and suggested activities through their device. They can provide feedback on their travel plan as needed, and this feedback will be used to adjust future plans.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] This invention is a system designed to streamline travel planning and reduce the burden on travelers, and in particular, utilizes AI technology to provide travelers with personalized travel plans. This system mainly consists of terminal means, server means, generative models, data collection means, reservation means, advice means, and integration of sensor data.

[0236] First, the user enters their travel preferences using a terminal device. This includes destination, budget, travel duration, and travel companion information. The terminal sends this information to the server. The server analyzes the received data and uses a generative model to generate the optimal travel plan that matches the user's conditions. This plan includes suggestions for flights, accommodations, sightseeing spots, activities, and more.

[0237] The server further collects real-time information using data collection methods and continuously optimizes the generated plan. This allows for adjustments in response to changes in weather, event information, and traffic conditions.

[0238] Once the user reviews and accepts the proposed plan, a booking request is sent from the device to the server. The server automatically completes the booking process using the booking method, including arranging flights and accommodations. If the booking is successfully completed, confirmation information is sent to the device and the user is notified.

[0239] During travel, the server uses advisory tools to provide travelers with real-time, situation-based advice. This allows travelers to continue their trip safely and comfortably. Furthermore, sensor data can be integrated to take into account the individual traveler's health condition, and travel plans can be adjusted as needed.

[0240] For example, if a user requests a plan for a 5-day trip to New York City with a budget of 200,000 yen for two people, the server will use that information to select the best flights and accommodations, and suggest popular tourist destinations and restaurants. Once the plan is accepted, the system will immediately execute the booking and automate the entire process until all arrangements are completed.

[0241] Thus, the present invention enables travelers to enjoy an efficient and personalized travel experience without having to spend time on detailed planning.

[0242] The following describes the processing flow.

[0243] Step 1:

[0244] Users enter their travel preferences through their device. These preferences include destination, budget, travel duration, and travel companion information, and this data is necessary for planning the trip.

[0245] Step 2:

[0246] The device sends the user's entered preferences to the server. This information is formatted as an API request and processed to ensure it reaches the server quickly and securely.

[0247] Step 3:

[0248] The server analyzes the data received from the terminal and generates the optimal travel plan using a generative model. The generative model utilizes historical data and algorithms to combine flights, accommodations, tourist destinations, and activities that match the budget and schedule.

[0249] Step 4:

[0250] The server uses data collection methods to gather real-time information and optimize the generated travel plan. Specifically, it adjusts the plan by considering factors such as weather forecasts, local events, and congestion information.

[0251] Step 5:

[0252] The server sends an optimized travel plan to the user's device and proposes it to them. The user can then review the plan details and make changes or approvals.

[0253] Step 6:

[0254] After the user approves the proposed plan, the device sends that information back to the server and requests that the reservation process begin.

[0255] Step 7:

[0256] The server uses the booking method to automatically make reservations for flights and accommodations based on the proposed plan. It collaborates with partner booking systems and retrieves confirmation information once the arrangements are complete.

[0257] Step 8:

[0258] The server notifies the terminal that the reservation is complete and provides the user with final confirmation information. This allows the user to confirm that all reservations have been completed without any problems.

[0259] Step 9:

[0260] During the trip, the server uses its advisory system to send appropriate advice to the user based on real-time data collected. This makes it easier for the user to cope with unexpected changes during their trip.

[0261] Step 10:

[0262] The server integrates sensor data to adjust the plan based on the user's health status and activity level, modifying the plan as needed. This adjustment ensures the user can continue their journey safely and comfortably.

[0263] (Example 1)

[0264] 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."

[0265] In travel planning, travelers face the challenge of having to spend considerable time and effort choosing the best plan from many options. Furthermore, during the actual trip, it is difficult to respond quickly to changing circumstances, adding to the difficulties. Additionally, effectively adjusting the plan while considering the traveler's health condition is also challenging.

[0266] 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.

[0267] In this invention, the server includes an information input mechanism for inputting the traveler's desired conditions, a component comprising a generation model for generating optimal travel suggestions based on those conditions, and an information gathering mechanism for collecting real-time information and optimizing the generated suggestions. This enables travelers to quickly and accurately formulate efficient and personalized travel plans, and to respond flexibly to changes in circumstances and health conditions during their trip.

[0268] An "information input mechanism" refers to a device or interface used by travelers to input their desired conditions.

[0269] An "information processing device" is a device that receives, analyzes, and processes data transmitted from an information input mechanism.

[0270] A "generative model" refers to an algorithm or data model used to generate optimal travel suggestions based on a traveler's preferences.

[0271] "Components" refer to the multiple technical or functional elements necessary to form a system.

[0272] The "information gathering mechanism" refers to a function that acquires necessary information in real time and optimizes the generated travel suggestions.

[0273] A "reservation system" refers to a system or device that automatically makes various arrangements based on travel proposals.

[0274] A "guidance body" is an organization that provides appropriate advice to travelers in response to changes in their circumstances during their trip.

[0275] "Sensor data" refers to numerical information obtained from various sensors, and this data is used to understand the health status of travelers.

[0276] This invention is a system that streamlines travelers' travel planning and provides personalized travel experiences. The system comprises an information input mechanism, an information processing device, a generation model, an information collection mechanism, a reservation mechanism, and a guidance mechanism.

[0277] First, the user uses a terminal to enter their travel preferences. For example, they enter specific information such as destination, budget, number of travel days, and number of companions. This information is entered as a prompt message in the format of "5-day trip to New York, budget 200,000 yen, 2 people." The terminal then sends this information to the server.

[0278] The server analyzes the input information it receives using an information processing device. Generative AI models are used for this analysis, employing AI frameworks such as TensorFlow and PyTorch. The generative AI model generates travel suggestions that are optimal for the user's conditions. These suggestions include recommended lists of flights, accommodations, tourist destinations, and activities.

[0279] Furthermore, the server uses an information gathering mechanism to acquire real-time data and optimize the suggestions generated based on weather, event information, and traffic conditions. This allows the server to provide plans that match the user's needs and meet appropriate conditions.

[0280] Once the user accepts the generated proposal, a booking request is sent from the device to the server. The server automatically executes the booking using its booking mechanism. Specifically, it interacts with an external travel booking system via an API and performs the necessary booking procedures.

[0281] During travel, the server uses a guidance mechanism to provide users with real-time, situation-appropriate advice. This advice includes suggestions for tourist destinations to visit and information on events. It can also integrate sensor data from wearable devices and adjust travel plans based on the user's health condition.

[0282] In this way, by the cooperation of each component of the system, users can experience an efficient and comfortable journey.

[0283] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[0284] Step 1:

[0285] The user uses the terminal to input the desired conditions for the journey. Specifically, this includes information such as the destination, budget, number of travel days, and information about companions. These pieces of information are input as the prompt sentence "A 5-day trip to New York, budget of 200,000 yen, for 2 people". The input data is sent from the terminal to the server.

[0286] Step 2:

[0287] The server analyzes the prompt sentence received from the user using an information processing device. In the process of analysis, a generation AI model is utilized to generate an optimal travel proposal considering past data and trends. At this time, a list of air tickets and accommodation facilities that match the user's conditions, as well as candidate recommended tourist attractions and activities related thereto, are output.

[0288] Step 3:

[0289] The server uses an information collection mechanism to obtain real-time data from external resources. Specifically, weather information, event information, traffic information, etc. are collected and reflected in the generated proposal. Thereby, the accuracy and timeliness of the proposal are improved, and an optimized plan is provided to the user.

[0290] Step 4:

[0291] The user checks the proposed travel plan on the terminal. If the user agrees to the proposed content, the user sends a reservation request from the terminal to the server. This request includes details of the selected flight and accommodation facility.

[0292] Step 5:

[0293] The server activates the reservation mechanism and automatically makes the necessary arrangements. Flight and accommodation reservations are made through integration with external travel reservation systems. Once the reservation is complete, the details are sent from the server to the terminal and notified to the user.

[0294] Step 6:

[0295] During travel, the server provides real-time advice to the user using a guidance mechanism. This includes optimal action suggestions based on current location information and real-time sensor data, as well as notifications regarding disaster information and emergency events. Information from the user's health devices is also integrated, allowing for adjustments to the plan based on their health status.

[0296] (Application Example 1)

[0297] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0298] Traditional travel planning systems struggled to fully meet individual needs, making the planning and arrangement process cumbersome and time-consuming for users. Furthermore, they lacked the flexibility to adjust plans based on real-time information, making it difficult to provide an efficient travel experience. Additionally, the automatic adjustment of plans to take into account the user's health condition was not present in previous systems.

[0299] 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.

[0300] In this invention, the server includes an interactive device means for voice-inputting the user's desired conditions to the information processing device, an information processing means for generating an optimal travel plan using a generation model, and an information collection means for acquiring current information. As a result, it becomes possible to automatically generate an individual travel plan based on the user's voice input, flexibly optimize and adjust it with real-time information, and provide an efficient and personalized travel experience without burdening the user.

[0301] The "interactive device" is a device for the user to input desired conditions by voice and transmit them to the information processing device.

[0302] The "information processing device" is a device that generates a travel plan using a generation model based on the desired conditions received from the interactive device.

[0303] The "generation model" is an algorithm or program for creating an optimal travel plan based on the user's desired conditions.

[0304] The "information collection means" is means for acquiring information related to current issues and optimizing the generated travel plan.

[0305] The "arrangement means" is a function or service that automatically makes travel-related arrangements based on the optimized travel plan.

[0306] The "advisory means" is means for providing advice according to changes in the situation during travel based on the current information acquired by the information collection means.

[0307] The "sensor data" is data from sensors used to grasp the user's health status.

[0308] Embodiments for Implementing the Invention

[0309] The system for implementing this invention consists of a set of programs and hardware designed to efficiently personalize travel plans and reduce the burden on the user. The system primarily operates using the following hardware and software:

[0310] The interactive terminal serves the purpose of inputting travel preferences from the user via voice. This device converts the voice into text using speech recognition software such as the Google Speech-to-Text API and transmits it to the information processing device.

[0311] Based on the received text information, the information processing device generates a travel plan using a generative AI model (e.g., OpenAI GPT-4). The generated plan is optimized by incorporating current information obtained through information gathering means, such as weather information and event information. The information gathering means used here include using APIs from the internet and collecting sensor data.

[0312] As a means of arrangement, travel-related arrangements will be automated using the Amadeus API and other tools. This automation will free users from cumbersome procedures, making it easy to arrange the perfect trip.

[0313] Furthermore, the advisory system provides specific advice based on real-time data, adapting to changing circumstances during the trip. This is crucial for taking the best possible action in response to unexpected events that may occur locally and the user's health condition.

[0314] For example, if a user enters their preferences, such as "I want to take a family trip next weekend. I'd like a warm destination and a health-conscious itinerary," the system will provide a customized plan based on that information.

[0315] An example of a prompt message is: "The user is planning a family trip next weekend. The destination is a warm region, so please create a health-conscious plan. Please take the latest weather information into consideration."

[0316] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0317] Step 1:

[0318] The device receives the user's voice input. The user communicates their desired travel conditions to the device as voice. This voice data is converted into text data using speech recognition software (Google Speech-to-Text API). Here, the input is raw voice data, and the output is the desired conditions in text format.

[0319] Step 2:

[0320] The server receives desired travel conditions in text format from the terminal. Based on the received data, a generative AI model (OpenAI GPT-4) generates the optimal travel plan. The input is text data reflecting the user's travel conditions, and the output is an initial travel plan proposal.

[0321] Step 3:

[0322] The server uses information gathering methods to obtain current information. It utilizes APIs from the internet and sensor data, such as weather information and local event information. Using this data, it optimizes the plan based on the latest information. The input is real-time data from the internet and sensors, and the output is an optimized travel plan.

[0323] Step 4:

[0324] The server automatically makes the necessary travel arrangements using booking methods based on the optimized travel plan. Here, it uses the Amadeus API, among others, to book flights and accommodations. The input is the optimized travel plan, and the output is confirmation information of the completed arrangements.

[0325] Step 5:

[0326] The user confirms the completion of their travel plan and arrangements through their device. They receive confirmation information sent from the server and verify that the plan has been approved. The input is the confirmation information from the server, and the output is the notification to the user.

[0327] Step 6:

[0328] The server constantly utilizes information gathering methods to respond to changing circumstances during travel and provides real-time advice. It also adjusts plans based on health conditions and weather changes. The input is continuously collected real-time data, and the output is specific advice tailored to that situation.

[0329] 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.

[0330] This invention is a system that recognizes travelers' emotions and incorporates them into travel plans to provide a more satisfying travel experience. In addition to the basic configuration of conventional systems, this system incorporates an emotion engine to grasp the traveler's emotional state in real time and utilize it for plan generation and adjustment.

[0331] The user enters their travel preferences using a terminal. This input includes destination, budget, travel duration, and travel companion information. The terminal sends the input data to the server. The server uses this data to create a travel plan using a generative model. During this generation process, an emotion engine operates to analyze the traveler's emotional state. This emotional state is obtained by combining the data entered by the user with information obtained from external devices.

[0332] The server further utilizes data collection methods to aggregate external data in real time and optimize the plan. At this time, the emotion engine identifies and aligns factors such as the traveler's emotional satisfaction, thereby providing a travel plan that satisfies the traveler.

[0333] Furthermore, if the user provides feedback regarding their emotions or the plan, the plan will be adjusted. The device also sends emotional data to the server as part of the communication. The server uses this data to inform the emotion engine, which then initiates or modifies the plan to match the traveler's current emotional state.

[0334] In practice, for example, if a user creates a plan with conditions such as "a 7-day trip to London, budget of 300,000 yen, for 2 people," the server will create the optimal travel plan based on that information and emotional data. If the user's mood changes during the trip, for example, if it is determined that relaxation is needed, the server will suggest new events and sightseeing spots suitable for relaxation. Conversely, if the user wants to be active, the plan will be adjusted to include more sports events and activities.

[0335] This enables a highly personalized travel experience that reflects the user's actual emotional state. By integrating with an emotion engine, this system further enhances user travel satisfaction.

[0336] The following describes the processing flow.

[0337] Step 1:

[0338] Users enter basic travel information and preferences through their device. This includes destination, budget, travel duration, and information about travel companions.

[0339] Step 2:

[0340] The terminal sends the information entered by the user to the server. This transmitted data becomes the source data for creating the travel plan.

[0341] Step 3:

[0342] The server analyzes the received data and uses a generative model to create a basic travel plan. At this point, the user's emotional state is not yet taken into consideration.

[0343] Step 4:

[0344] The server activates the emotion engine and analyzes the user's emotional data. This emotional data includes facial recognition, voice analysis data, and vital signs information acquired in real time from terminals and wearable devices.

[0345] Step 5:

[0346] Based on the analysis results of the emotion engine, the server customizes the generated travel plan according to the user's emotional state. For example, if the user is experiencing high stress, a relaxing plan will be added.

[0347] Step 6:

[0348] The server further optimizes travel plans based on external data obtained in real time using data collection methods. This information includes weather changes and local event information.

[0349] Step 7:

[0350] The server sends the adjusted plan to the terminal and proposes it to the user. The user can review the plan and send feedback as needed.

[0351] Step 8:

[0352] Once the user accepts the plan, the device sends this information to the server and begins the reservation process.

[0353] Step 9:

[0354] The server automatically makes all travel reservations based on the pre-arranged plan using the reservation system. The user confirms the completed reservation information by receiving a notification on their device.

[0355] Step 10:

[0356] During the trip, the server continuously monitors the user using an emotion engine, dynamically adjusting the travel plan accordingly if there are any changes in the user's emotional state, providing the traveler with the best possible experience.

[0357] (Example 2)

[0358] 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".

[0359] Traditional travel planning systems struggle to take into account travelers' emotional states and real-time environmental changes, resulting in the provision of plans that are not optimal for the traveler. Furthermore, they lack the means to quickly respond to changing circumstances during travel and improve traveler satisfaction. This leads to the challenge of standardized travel experiences that fail to meet individual needs.

[0360] 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.

[0361] In this invention, the server includes an analysis means incorporating an emotion analysis engine for analyzing the emotional state of travelers in real time, a data collection means for aggregating data to optimize a travel plan generated by a generative artificial intelligence model based on emotional data and real-time data, and a reservation means for automatically making reservations based on the optimized travel plan. This makes it possible to provide a personalized travel experience that is tailored to the emotional state and environmental changes of each individual traveler.

[0362] "Information equipment" refers to devices that travelers use to input their desired conditions and transmit them to a server. Specifically, this includes smartphones, tablets, and personal computers.

[0363] "Computing device means" refers to a device that receives and processes data transmitted from information equipment means. Servers and cloud computing environments fall into this category.

[0364] A "generative artificial intelligence model" refers to a model that uses machine learning techniques to automatically generate travel plans based on input data.

[0365] A "emotion analysis engine" refers to a processing engine that analyzes a traveler's emotional state in real time and uses that data to adapt travel plans.

[0366] "Analysis means" refers to devices or programs used to extract and understand the emotional state of a user from data.

[0367] "Data collection methods" refer to means of aggregating real-time data on travelers' emotions and the environment, and using that data to optimize travel planning.

[0368] "Reservation method" refers to a system element that automatically makes reservations for various services and events based on an optimized travel plan.

[0369] This invention provides a system that generates travel plans that take into account the emotional state of travelers based on their desired conditions. Specifically, it uses a terminal, a server, and a generative AI model and emotion analysis engine that handle various types of data.

[0370] Users input their desired travel conditions, such as destination, budget, duration, and travel companion information, using information devices such as smartphones or personal computers. These information devices transmit the user's input data to the server. The data sent from the terminal is received by the server, which is a computing device.

[0371] The server uses a generative artificial intelligence model to generate a travel plan from the received data. This generative AI model utilizes machine learning techniques to generate the optimal travel plan for given conditions. During this process, an emotion analysis engine operates to analyze the user's emotional state in real time. The analyzed emotion data is acquired based on sensor information from external wearable devices and smartphones and incorporated into the travel plan.

[0372] Next, the server uses data collection methods to aggregate real-time data such as weather information and event information. This allows the travel plan to be optimized according to the user's emotional state. As part of the optimization process, if the user wants to relax, it suggests activities suitable for relaxation, and if they want to be active, it provides a plan that includes many sports events and activities.

[0373] For example, if a user enters the conditions "7-day trip to London, budget 300,000 yen, 2 people," the server will consider this information along with emotional data to generate the optimal travel plan. If it determines that relaxation is needed during the trip, it will suggest events and sightseeing spots suitable for relaxation; conversely, if the user wants to be active, it will suggest sports events and activities.

[0374] An example of a prompt for the generating AI model would be, "Based on the user's emotional data, please suggest a relaxing London travel plan. The budget is 300,000 yen, for 7 days, for 2 people." This embodiment of the present invention makes it possible to realize a personalized travel experience that matches the user's current emotions and preferences.

[0375] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0376] Step 1:

[0377] Users input their travel preferences using devices such as smartphones or computers. These preferences include destination, budget, travel duration, and travel companion information. The entered data is formatted as needed within the device and prepared as structured data. This structured data is then sent to the server via an HTTP request. The input consists of the user-specified preferences, while the output is structured data transferred to the server.

[0378] Step 2:

[0379] The server receives structured data sent from the terminal. The received data is parsed and prepared to be input into the generative AI model. The server uses the generative AI model to begin creating a travel plan based on the input data. The input data consists of desired conditions, and the output is a provisional travel plan. The generative AI model parses this data and proposes the optimal travel plan via prompt messages.

[0380] Step 3:

[0381] The server runs an emotion analysis engine to analyze the user's emotional state in real time. Based on biometric and behavioral data obtained from the terminal and wearable sensors, it evaluates the user's current emotional state. Biometric information from the terminal and wearable devices is used as input, and the analyzed emotion data is provided as output.

[0382] Step 4:

[0383] The server optimizes the initial travel plan by combining analyzed sentiment data with real-time data collected from external sources (weather, event information, etc.). Data collection methods gather this information and make adjustments to reflect it in the plan. The input includes sentiment data and external real-time information, and the output is an optimized travel plan. This process involves re-evaluating the generative AI model to provide a travel plan that is adapted to emotions and the environment.

[0384] Step 5:

[0385] If a user provides feedback during their trip, the device sends it to the server. The feedback is received as textual comments and ratings, and is then incorporated into the sentiment analysis engine's evaluation. The server then makes further adjustments to the travel plan based on the feedback received. The input is feedback information, and the output is a revised travel plan that reflects the feedback.

[0386] (Application Example 2)

[0387] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0388] The challenge lies in improving traveler satisfaction by recognizing travelers' emotional states in real time and providing travel itineraries that reflect this. Conventional travel plan generation systems have often failed to adequately respond to travelers' emotions and real-time changes in circumstances, resulting in an inability to provide the optimal travel experience. Therefore, there is a need for the generation and adjustment of dynamic travel itineraries that take travelers' emotions into consideration.

[0389] 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.

[0390] In this invention, the server includes a terminal device for inputting the traveler's desired requirements, an information processing device, and an emotion analysis device. This makes it possible to recognize the traveler's emotional state in real time, dynamically adjust the travel itinerary based on that, and provide a personalized and highly satisfying travel experience.

[0391] "Traveler's desired requirements" refer to the conditions that travelers have in mind when planning their trip, such as the destination, budget, number of days, and information about their travel companions.

[0392] A "terminal device" refers to an electronic device used by travelers to input their desired requirements, and includes smartphones, tablets, and other similar devices.

[0393] An "information processing device" refers to a server or computer system that receives input requests and generates travel plans.

[0394] "Generative methods" refer to algorithms and processes that automatically design the optimal travel itinerary based on the traveler's desired requirements.

[0395] An "information gathering device" refers to a device or system used to collect data necessary to understand the real-time situation during travel.

[0396] A "emotion analysis device" refers to a system that analyzes a traveler's emotional state in real time and uses the results to adjust the travel itinerary.

[0397] A "booking system" refers to a system that automatically makes reservations for accommodations, transportation, and other services based on an optimized travel itinerary.

[0398] An "advisory device" refers to a system that provides appropriate advice and suggestions based on a traveler's real-time data and emotional state.

[0399] This invention provides a system that recognizes a traveler's emotional state in real time and dynamically adjusts the travel plan based on that information. This system includes a terminal device for inputting the traveler's preferences, which the traveler inputs into a terminal device such as a smartphone or tablet. The terminal device communicates with an information processing device, i.e., a server, and transmits the input preferences to the server.

[0400] The server uses a generation method based on the received information to design the optimal travel itinerary. An AI model is used in the generation method to automatically formulate an itinerary that meets the user's desired requirements. Furthermore, the server acquires real-time data via information gathering devices and optimizes the plan by considering factors that may change during the trip.

[0401] Depending on the type of travel, the server uses an emotion analysis device to analyze the traveler's emotions. This device performs calculations based on sensor data from smart wearable devices, cameras, and other sources to understand the traveler's current emotional state.

[0402] This allows the server to suggest relaxation events if the traveler is in a relaxed state, and suggest active activities if the traveler is in an active state. Furthermore, a booking system with automated reservation capabilities ensures appropriate bookings are made and the traveler's wishes are fulfilled.

[0403] As a concrete example, consider a traveler planning a 7-day trip to London with a limited budget. In this case, a generative AI model can be used to design a plan that maximizes satisfaction. An example of a prompt would be, "I am planning a 7-day trip to London. What activities would an application with emotion recognition capabilities suggest based on whether the traveler wants to relax or be active?" In this way, it is possible to provide the optimal travel experience tailored to the user.

[0404] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0405] Step 1:

[0406] The user enters their travel plan requirements on a terminal. These requirements include destination, budget, duration, and number of travel companions. This input data is then sent from the terminal to the server.

[0407] Step 2:

[0408] The server uses a generation AI model to formulate an initial travel itinerary based on the received desired requirements. It executes a generation process based on the input requirements to construct a travel plan. A temporary travel plan is generated as output.

[0409] Step 3:

[0410] The server acquires real-time data from external sources via information gathering devices. This data includes weather information, event information, and congestion levels, and this data is used to optimize the plan.

[0411] Step 4:

[0412] The server uses an emotion analysis device to analyze the traveler's emotional state in real time. To do this, it collects sensor data from smart wearable devices or cameras and performs computational processing to identify the emotional state. This results in the traveler's current emotions being output.

[0413] Step 5:

[0414] The server combines collected real-time data with sentiment analysis results to adjust the travel plan. Based on the emotional state, it processes the data to add relaxation events or active activities to the plan. The adjusted travel plan is then output.

[0415] Step 6:

[0416] Based on the coordinated travel plan, the server's booking system automatically executes the necessary reservations. It books accommodations and arranges transportation, making the travel plan ready to be executed.

[0417] Step 7:

[0418] Users receive information about their current travel plan and suggested activities through their device. They can provide feedback on their travel plan as needed, and this feedback will be used to adjust future plans.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] [Third Embodiment]

[0423] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0424] 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.

[0425] 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).

[0426] 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.

[0427] 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.

[0428] 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).

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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".

[0435] This invention is a system designed to streamline travel planning and reduce the burden on travelers, and in particular, utilizes AI technology to provide travelers with personalized travel plans. This system mainly consists of terminal means, server means, generative models, data collection means, reservation means, advice means, and integration of sensor data.

[0436] First, the user enters their travel preferences using a terminal device. This includes destination, budget, travel duration, and travel companion information. The terminal sends this information to the server. The server analyzes the received data and uses a generative model to generate the optimal travel plan that matches the user's conditions. This plan includes suggestions for flights, accommodations, sightseeing spots, activities, and more.

[0437] The server further collects real-time information using data collection methods and continuously optimizes the generated plan. This allows for adjustments in response to changes in weather, event information, and traffic conditions.

[0438] Once the user reviews and accepts the proposed plan, a booking request is sent from the device to the server. The server automatically completes the booking process using the booking method, including arranging flights and accommodations. If the booking is successfully completed, confirmation information is sent to the device and the user is notified.

[0439] During travel, the server uses advisory tools to provide travelers with real-time, situation-based advice. This allows travelers to continue their trip safely and comfortably. Furthermore, sensor data can be integrated to take into account the individual traveler's health condition, and travel plans can be adjusted as needed.

[0440] For example, if a user requests a plan for a 5-day trip to New York City with a budget of 200,000 yen for two people, the server will use that information to select the best flights and accommodations, and suggest popular tourist destinations and restaurants. Once the plan is accepted, the system will immediately execute the booking and automate the entire process until all arrangements are completed.

[0441] Thus, the present invention enables travelers to enjoy an efficient and personalized travel experience without having to spend time on detailed planning.

[0442] The following describes the processing flow.

[0443] Step 1:

[0444] Users enter their travel preferences through their device. These preferences include destination, budget, travel duration, and travel companion information, and this data is necessary for planning the trip.

[0445] Step 2:

[0446] The device sends the user's entered preferences to the server. This information is formatted as an API request and processed to ensure it reaches the server quickly and securely.

[0447] Step 3:

[0448] The server analyzes the data received from the terminal and generates the optimal travel plan using a generative model. The generative model utilizes historical data and algorithms to combine flights, accommodations, tourist destinations, and activities that match the budget and schedule.

[0449] Step 4:

[0450] The server uses data collection methods to gather real-time information and optimize the generated travel plan. Specifically, it adjusts the plan by considering factors such as weather forecasts, local events, and congestion information.

[0451] Step 5:

[0452] The server sends an optimized travel plan to the user's device and proposes it to them. The user can then review the plan details and make changes or approvals.

[0453] Step 6:

[0454] After the user approves the proposed plan, the device sends that information back to the server and requests that the reservation process begin.

[0455] Step 7:

[0456] The server uses the booking method to automatically make reservations for flights and accommodations based on the proposed plan. It collaborates with partner booking systems and retrieves confirmation information once the arrangements are complete.

[0457] Step 8:

[0458] The server notifies the terminal that the reservation is complete and provides the user with final confirmation information. This allows the user to confirm that all reservations have been completed without any problems.

[0459] Step 9:

[0460] During the trip, the server uses its advisory system to send appropriate advice to the user based on real-time data collected. This makes it easier for the user to cope with unexpected changes during their trip.

[0461] Step 10:

[0462] The server integrates sensor data to adjust the plan based on the user's health status and activity level, modifying the plan as needed. This adjustment ensures the user can continue their journey safely and comfortably.

[0463] (Example 1)

[0464] 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."

[0465] In travel planning, travelers face the challenge of having to spend considerable time and effort choosing the best plan from many options. Furthermore, during the actual trip, it is difficult to respond quickly to changing circumstances, adding to the difficulties. Additionally, effectively adjusting the plan while considering the traveler's health condition is also challenging.

[0466] 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.

[0467] In this invention, the server includes an information input mechanism for inputting the traveler's desired conditions, a component comprising a generation model for generating optimal travel suggestions based on those conditions, and an information gathering mechanism for collecting real-time information and optimizing the generated suggestions. This enables travelers to quickly and accurately formulate efficient and personalized travel plans, and to respond flexibly to changes in circumstances and health conditions during their trip.

[0468] An "information input mechanism" refers to a device or interface used by travelers to input their desired conditions.

[0469] An "information processing device" is a device that receives, analyzes, and processes data transmitted from an information input mechanism.

[0470] A "generative model" refers to an algorithm or data model used to generate optimal travel suggestions based on a traveler's preferences.

[0471] "Components" refer to the multiple technical or functional elements necessary to form a system.

[0472] The "information gathering mechanism" refers to a function that acquires necessary information in real time and optimizes the generated travel suggestions.

[0473] A "reservation system" refers to a system or device that automatically makes various arrangements based on travel proposals.

[0474] A "guidance body" is an organization that provides appropriate advice to travelers in response to changes in their circumstances during their trip.

[0475] "Sensor data" refers to numerical information obtained from various sensors, and this data is used to understand the health status of travelers.

[0476] This invention is a system that streamlines travelers' travel planning and provides personalized travel experiences. The system comprises an information input mechanism, an information processing device, a generation model, an information collection mechanism, a reservation mechanism, and a guidance mechanism.

[0477] First, the user uses a terminal to enter their travel preferences. For example, they enter specific information such as destination, budget, number of travel days, and number of companions. This information is entered as a prompt message in the format of "5-day trip to New York, budget 200,000 yen, 2 people." The terminal then sends this information to the server.

[0478] The server analyzes the input information it receives using an information processing device. Generative AI models are used for this analysis, employing AI frameworks such as TensorFlow and PyTorch. The generative AI model generates travel suggestions that are optimal for the user's conditions. These suggestions include recommended lists of flights, accommodations, tourist destinations, and activities.

[0479] Furthermore, the server uses an information gathering mechanism to acquire real-time data and optimize the suggestions generated based on weather, event information, and traffic conditions. This allows the server to provide plans that match the user's needs and meet appropriate conditions.

[0480] Once the user accepts the generated proposal, a booking request is sent from the device to the server. The server automatically executes the booking using its booking mechanism. Specifically, it interacts with an external travel booking system via an API and performs the necessary booking procedures.

[0481] During travel, the server uses a guidance mechanism to provide users with real-time, situation-appropriate advice. This advice includes suggestions for tourist destinations to visit and information on events. It can also integrate sensor data from wearable devices and adjust travel plans based on the user's health condition.

[0482] In this way, the various components of the system work together, allowing users to experience efficient and comfortable travel.

[0483] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0484] Step 1:

[0485] The user uses a terminal to enter their travel preferences. Specifically, this includes destination, budget, duration of trip, and information about travel companions. This information is entered as a prompt message such as "5-day trip to New York, budget 200,000 yen, 2 people." The entered data is then sent from the terminal to the server.

[0486] Step 2:

[0487] The server analyzes the prompt message received from the user using an information processing device. During the analysis process, a generative AI model is used to generate optimal travel suggestions, taking into account past data and trends. At this point, a list of flights and accommodations that match the user's criteria, along with suggested tourist destinations and activities, are output.

[0488] Step 3:

[0489] The server uses an information gathering mechanism to acquire real-time data from external resources. Specifically, it collects weather information, event information, traffic information, etc., and incorporates this into the generated suggestions. This improves the accuracy and timeliness of the suggestions, providing users with plans optimized for their needs.

[0490] Step 4:

[0491] The user reviews the suggested travel plan on their device. If they agree to the suggestion, the user sends a booking request from their device to the server. This request includes details of the selected flights and accommodations.

[0492] Step 5:

[0493] The server activates the reservation mechanism and automatically makes the necessary arrangements. Flight and accommodation reservations are made through integration with external travel reservation systems. Once the reservation is complete, the details are sent from the server to the terminal and notified to the user.

[0494] Step 6:

[0495] During travel, the server provides real-time advice to the user using a guidance mechanism. This includes optimal action suggestions based on current location information and real-time sensor data, as well as notifications regarding disaster information and emergency events. Information from the user's health devices is also integrated, allowing for adjustments to the plan based on their health status.

[0496] (Application Example 1)

[0497] 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."

[0498] Traditional travel planning systems struggled to fully meet individual needs, making the planning and arrangement process cumbersome and time-consuming for users. Furthermore, they lacked the flexibility to adjust plans based on real-time information, making it difficult to provide an efficient travel experience. Additionally, the automatic adjustment of plans to take into account the user's health condition was not present in previous systems.

[0499] 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.

[0500] In this invention, the server includes a dialogue device means for voice input of the user's desired conditions to an information processing device, an information processing means for generating an optimal travel plan using a generative model, and an information gathering means for acquiring current information. This enables the automatic generation of individual travel plans based on the user's voice input, flexible optimization and adjustment with real-time information, and the provision of an efficient and personalized travel experience without burdening the user.

[0501] A "dialogue device" is a device that allows users to input their desired conditions via voice and transmit them to an information processing device.

[0502] An "information processing device" is a device that generates a travel plan using a generative model based on the desired conditions received from a dialogue device.

[0503] A "generative model" is an algorithm or program used to create the optimal travel plan based on the user's desired conditions.

[0504] "Information gathering methods" refer to means of acquiring information related to the current challenges and optimizing the generated travel plan.

[0505] "Arrangement method" refers to a function or service that automatically makes travel-related arrangements based on an optimized travel plan.

[0506] "Advice methods" refer to means of providing advice based on current information obtained through information gathering methods, in response to changes in circumstances during travel.

[0507] "Sensor data" refers to data from sensors used to understand the user's health status.

[0508] Modes for carrying out the invention

[0509] The system for implementing this invention consists of a set of programs and hardware designed to efficiently personalize travel plans and reduce the burden on the user. The system primarily operates using the following hardware and software:

[0510] The interactive terminal serves the purpose of inputting travel preferences from the user via voice. This device converts the voice into text using speech recognition software such as the Google Speech-to-Text API and transmits it to the information processing device.

[0511] Based on the received text information, the information processing device generates a travel plan using a generative AI model (e.g., OpenAI GPT-4). The generated plan is optimized by incorporating current information obtained through information gathering means, such as weather information and event information. The information gathering means used here include using APIs from the internet and collecting sensor data.

[0512] As a means of arrangement, travel-related arrangements will be automated using the Amadeus API and other tools. This automation will free users from cumbersome procedures, making it easy to arrange the perfect trip.

[0513] Furthermore, the advisory system provides specific advice based on real-time data, adapting to changing circumstances during the trip. This is crucial for taking the best possible action in response to unexpected events that may occur locally and the user's health condition.

[0514] For example, if a user enters their preferences, such as "I want to take a family trip next weekend. I'd like a warm destination and a health-conscious itinerary," the system will provide a customized plan based on that information.

[0515] An example of a prompt message is: "The user is planning a family trip next weekend. The destination is a warm region, so please create a health-conscious plan. Please take the latest weather information into consideration."

[0516] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0517] Step 1:

[0518] The device receives the user's voice input. The user communicates their desired travel conditions to the device as voice. This voice data is converted into text data using speech recognition software (Google Speech-to-Text API). Here, the input is raw voice data, and the output is the desired conditions in text format.

[0519] Step 2:

[0520] The server receives desired travel conditions in text format from the terminal. Based on the received data, a generative AI model (OpenAI GPT-4) generates the optimal travel plan. The input is text data reflecting the user's travel conditions, and the output is an initial travel plan proposal.

[0521] Step 3:

[0522] The server uses information gathering methods to obtain current information. It utilizes APIs from the internet and sensor data, such as weather information and local event information. Using this data, it optimizes the plan based on the latest information. The input is real-time data from the internet and sensors, and the output is an optimized travel plan.

[0523] Step 4:

[0524] The server automatically makes the necessary travel arrangements using booking methods based on the optimized travel plan. Here, it uses the Amadeus API, among others, to book flights and accommodations. The input is the optimized travel plan, and the output is confirmation information of the completed arrangements.

[0525] Step 5:

[0526] The user confirms the completion of their travel plan and arrangements through their device. They receive confirmation information sent from the server and verify that the plan has been approved. The input is the confirmation information from the server, and the output is the notification to the user.

[0527] Step 6:

[0528] The server constantly utilizes information gathering methods to respond to changing circumstances during travel and provides real-time advice. It also adjusts plans based on health conditions and weather changes. The input is continuously collected real-time data, and the output is specific advice tailored to that situation.

[0529] 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.

[0530] This invention is a system that recognizes travelers' emotions and incorporates them into travel plans to provide a more satisfying travel experience. In addition to the basic configuration of conventional systems, this system incorporates an emotion engine to grasp the traveler's emotional state in real time and utilize it for plan generation and adjustment.

[0531] The user enters their travel preferences using a terminal. This input includes destination, budget, travel duration, and travel companion information. The terminal sends the input data to the server. The server uses this data to create a travel plan using a generative model. During this generation process, an emotion engine operates to analyze the traveler's emotional state. This emotional state is obtained by combining the data entered by the user with information obtained from external devices.

[0532] The server further utilizes data collection methods to aggregate external data in real time and optimize the plan. At this time, the emotion engine identifies and aligns factors such as the traveler's emotional satisfaction, thereby providing a travel plan that satisfies the traveler.

[0533] Furthermore, if the user provides feedback regarding their emotions or the plan, the plan will be adjusted. The device also sends emotional data to the server as part of the communication. The server uses this data to inform the emotion engine, which then initiates or modifies the plan to match the traveler's current emotional state.

[0534] In practice, for example, if a user creates a plan with conditions such as "a 7-day trip to London, budget of 300,000 yen, for 2 people," the server will create the optimal travel plan based on that information and emotional data. If the user's mood changes during the trip, for example, if it is determined that relaxation is needed, the server will suggest new events and sightseeing spots suitable for relaxation. Conversely, if the user wants to be active, the plan will be adjusted to include more sports events and activities.

[0535] This enables a highly personalized travel experience that reflects the user's actual emotional state. By integrating with an emotion engine, this system further enhances user travel satisfaction.

[0536] The following describes the processing flow.

[0537] Step 1:

[0538] Users enter basic travel information and preferences through their device. This includes destination, budget, travel duration, and information about travel companions.

[0539] Step 2:

[0540] The terminal sends the information entered by the user to the server. This transmitted data becomes the source data for creating the travel plan.

[0541] Step 3:

[0542] The server analyzes the received data and uses a generative model to create a basic travel plan. At this point, the user's emotional state is not yet taken into consideration.

[0543] Step 4:

[0544] The server activates the emotion engine and analyzes the user's emotional data. This emotional data includes facial recognition, voice analysis data, and vital signs information acquired in real time from terminals and wearable devices.

[0545] Step 5:

[0546] Based on the analysis results of the emotion engine, the server customizes the generated travel plan according to the user's emotional state. For example, if the user is experiencing high stress, a relaxing plan will be added.

[0547] Step 6:

[0548] The server further optimizes travel plans based on external data obtained in real time using data collection methods. This information includes weather changes and local event information.

[0549] Step 7:

[0550] The server sends the adjusted plan to the terminal and proposes it to the user. The user can review the plan and send feedback as needed.

[0551] Step 8:

[0552] Once the user accepts the plan, the device sends this information to the server and begins the reservation process.

[0553] Step 9:

[0554] The server automatically makes all travel reservations based on the pre-arranged plan using the reservation system. The user confirms the completed reservation information by receiving a notification on their device.

[0555] Step 10:

[0556] During the trip, the server continuously monitors the user using an emotion engine, dynamically adjusting the travel plan accordingly if there are any changes in the user's emotional state, providing the traveler with the best possible experience.

[0557] (Example 2)

[0558] 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."

[0559] Traditional travel planning systems struggle to take into account travelers' emotional states and real-time environmental changes, resulting in the provision of plans that are not optimal for the traveler. Furthermore, they lack the means to quickly respond to changing circumstances during travel and improve traveler satisfaction. This leads to the challenge of standardized travel experiences that fail to meet individual needs.

[0560] 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.

[0561] In this invention, the server includes an analysis means incorporating an emotion analysis engine for analyzing the emotional state of travelers in real time, a data collection means for aggregating data to optimize a travel plan generated by a generative artificial intelligence model based on emotional data and real-time data, and a reservation means for automatically making reservations based on the optimized travel plan. This makes it possible to provide a personalized travel experience that is tailored to the emotional state and environmental changes of each individual traveler.

[0562] "Information equipment" refers to devices that travelers use to input their desired conditions and transmit them to a server. Specifically, this includes smartphones, tablets, and personal computers.

[0563] "Computing device means" refers to a device that receives and processes data transmitted from information equipment means. Servers and cloud computing environments fall into this category.

[0564] A "generative artificial intelligence model" refers to a model that uses machine learning techniques to automatically generate travel plans based on input data.

[0565] A "emotion analysis engine" refers to a processing engine that analyzes a traveler's emotional state in real time and uses that data to adapt travel plans.

[0566] "Analysis means" refers to devices or programs used to extract and understand the emotional state of a user from data.

[0567] "Data collection methods" refer to means of aggregating real-time data on travelers' emotions and the environment, and using that data to optimize travel planning.

[0568] "Reservation method" refers to a system element that automatically makes reservations for various services and events based on an optimized travel plan.

[0569] This invention provides a system that generates travel plans that take into account the emotional state of travelers based on their desired conditions. Specifically, it uses a terminal, a server, and a generative AI model and emotion analysis engine that handle various types of data.

[0570] Users input their desired travel conditions, such as destination, budget, duration, and travel companion information, using information devices such as smartphones or personal computers. These information devices transmit the user's input data to the server. The data sent from the terminal is received by the server, which is a computing device.

[0571] The server uses a generative artificial intelligence model to generate a travel plan from the received data. This generative AI model utilizes machine learning techniques to generate the optimal travel plan for given conditions. During this process, an emotion analysis engine operates to analyze the user's emotional state in real time. The analyzed emotion data is acquired based on sensor information from external wearable devices and smartphones and incorporated into the travel plan.

[0572] Next, the server uses data collection methods to aggregate real-time data such as weather information and event information. This allows the travel plan to be optimized according to the user's emotional state. As part of the optimization process, if the user wants to relax, it suggests activities suitable for relaxation, and if they want to be active, it provides a plan that includes many sports events and activities.

[0573] For example, if a user enters the conditions "7-day trip to London, budget 300,000 yen, 2 people," the server will consider this information along with emotional data to generate the optimal travel plan. If it determines that relaxation is needed during the trip, it will suggest events and sightseeing spots suitable for relaxation; conversely, if the user wants to be active, it will suggest sports events and activities.

[0574] An example of a prompt for the generating AI model would be, "Based on the user's emotional data, please suggest a relaxing London travel plan. The budget is 300,000 yen, for 7 days, for 2 people." This embodiment of the present invention makes it possible to realize a personalized travel experience that matches the user's current emotions and preferences.

[0575] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0576] Step 1:

[0577] Users input their travel preferences using devices such as smartphones or computers. These preferences include destination, budget, travel duration, and travel companion information. The entered data is formatted as needed within the device and prepared as structured data. This structured data is then sent to the server via an HTTP request. The input consists of the user-specified preferences, while the output is structured data transferred to the server.

[0578] Step 2:

[0579] The server receives structured data sent from the terminal. The received data is parsed and prepared to be input into the generative AI model. The server uses the generative AI model to begin creating a travel plan based on the input data. The input data consists of desired conditions, and the output is a provisional travel plan. The generative AI model parses this data and proposes the optimal travel plan via prompt messages.

[0580] Step 3:

[0581] The server runs an emotion analysis engine to analyze the user's emotional state in real time. Based on biometric and behavioral data obtained from the terminal and wearable sensors, it evaluates the user's current emotional state. Biometric information from the terminal and wearable devices is used as input, and the analyzed emotion data is provided as output.

[0582] Step 4:

[0583] The server optimizes the initial travel plan by combining analyzed sentiment data with real-time data collected from external sources (weather, event information, etc.). Data collection methods gather this information and make adjustments to reflect it in the plan. The input includes sentiment data and external real-time information, and the output is an optimized travel plan. This process involves re-evaluating the generative AI model to provide a travel plan that is adapted to emotions and the environment.

[0584] Step 5:

[0585] If a user provides feedback during their trip, the device sends it to the server. The feedback is received as textual comments and ratings, and is then incorporated into the sentiment analysis engine's evaluation. The server then makes further adjustments to the travel plan based on the feedback received. The input is feedback information, and the output is a revised travel plan that reflects the feedback.

[0586] (Application Example 2)

[0587] 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."

[0588] The challenge lies in improving traveler satisfaction by recognizing travelers' emotional states in real time and providing travel itineraries that reflect this. Conventional travel plan generation systems have often failed to adequately respond to travelers' emotions and real-time changes in circumstances, resulting in an inability to provide the optimal travel experience. Therefore, there is a need for the generation and adjustment of dynamic travel itineraries that take travelers' emotions into consideration.

[0589] 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.

[0590] In this invention, the server includes a terminal device for inputting the traveler's desired requirements, an information processing device, and an emotion analysis device. This makes it possible to recognize the traveler's emotional state in real time, dynamically adjust the travel itinerary based on that, and provide a personalized and highly satisfying travel experience.

[0591] "Traveler's desired requirements" refer to the conditions that travelers have in mind when planning their trip, such as the destination, budget, number of days, and information about their travel companions.

[0592] A "terminal device" refers to an electronic device used by travelers to input their desired requirements, and includes smartphones, tablets, and other similar devices.

[0593] An "information processing device" refers to a server or computer system that receives input requests and generates travel plans.

[0594] "Generative methods" refer to algorithms and processes that automatically design the optimal travel itinerary based on the traveler's desired requirements.

[0595] An "information gathering device" refers to a device or system used to collect data necessary to understand the real-time situation during travel.

[0596] A "emotion analysis device" refers to a system that analyzes a traveler's emotional state in real time and uses the results to adjust the travel itinerary.

[0597] A "booking system" refers to a system that automatically makes reservations for accommodations, transportation, and other services based on an optimized travel itinerary.

[0598] An "advisory device" refers to a system that provides appropriate advice and suggestions based on a traveler's real-time data and emotional state.

[0599] This invention provides a system that recognizes a traveler's emotional state in real time and dynamically adjusts the travel plan based on that information. This system includes a terminal device for inputting the traveler's preferences, which the traveler inputs into a terminal device such as a smartphone or tablet. The terminal device communicates with an information processing device, i.e., a server, and transmits the input preferences to the server.

[0600] The server uses a generation method based on the received information to design the optimal travel itinerary. An AI model is used in the generation method to automatically formulate an itinerary that meets the user's desired requirements. Furthermore, the server acquires real-time data via information gathering devices and optimizes the plan by considering factors that may change during the trip.

[0601] Depending on the type of travel, the server uses an emotion analysis device to analyze the traveler's emotions. This device performs calculations based on sensor data from smart wearable devices, cameras, and other sources to understand the traveler's current emotional state.

[0602] This allows the server to suggest relaxation events if the traveler is in a relaxed state, and suggest active activities if the traveler is in an active state. Furthermore, a booking system with automated reservation capabilities ensures appropriate bookings are made and the traveler's wishes are fulfilled.

[0603] As a concrete example, consider a traveler planning a 7-day trip to London with a limited budget. In this case, a generative AI model can be used to design a plan that maximizes satisfaction. An example of a prompt would be, "I am planning a 7-day trip to London. What activities would an application with emotion recognition capabilities suggest based on whether the traveler wants to relax or be active?" In this way, it is possible to provide the optimal travel experience tailored to the user.

[0604] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0605] Step 1:

[0606] The user enters their travel plan requirements on a terminal. These requirements include destination, budget, duration, and number of travel companions. This input data is then sent from the terminal to the server.

[0607] Step 2:

[0608] The server uses a generation AI model to formulate an initial travel itinerary based on the received desired requirements. It executes a generation process based on the input requirements to construct a travel plan. A temporary travel plan is generated as output.

[0609] Step 3:

[0610] The server acquires real-time data from external sources via information gathering devices. This data includes weather information, event information, and congestion levels, and this data is used to optimize the plan.

[0611] Step 4:

[0612] The server uses an emotion analysis device to analyze the traveler's emotional state in real time. To do this, it collects sensor data from smart wearable devices or cameras and performs computational processing to identify the emotional state. This results in the traveler's current emotions being output.

[0613] Step 5:

[0614] The server combines collected real-time data with sentiment analysis results to adjust the travel plan. Based on the emotional state, it processes the data to add relaxation events or active activities to the plan. The adjusted travel plan is then output.

[0615] Step 6:

[0616] Based on the coordinated travel plan, the server's booking system automatically executes the necessary reservations. It books accommodations and arranges transportation, making the travel plan ready to be executed.

[0617] Step 7:

[0618] Users receive information about their current travel plan and suggested activities through their device. They can provide feedback on their travel plan as needed, and this feedback will be used to adjust future plans.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] [Fourth Embodiment]

[0623] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0624] 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.

[0625] 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).

[0626] 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.

[0627] 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.

[0628] 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).

[0629] 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.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] 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.

[0634] 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.

[0635] 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".

[0636] This invention is a system designed to streamline travel planning and reduce the burden on travelers, and in particular, utilizes AI technology to provide travelers with personalized travel plans. This system mainly consists of terminal means, server means, generative models, data collection means, reservation means, advice means, and integration of sensor data.

[0637] First, the user enters their travel preferences using a terminal device. This includes destination, budget, travel duration, and travel companion information. The terminal sends this information to the server. The server analyzes the received data and uses a generative model to generate the optimal travel plan that matches the user's conditions. This plan includes suggestions for flights, accommodations, sightseeing spots, activities, and more.

[0638] The server further collects real-time information using data collection methods and continuously optimizes the generated plan. This allows for adjustments in response to changes in weather, event information, and traffic conditions.

[0639] Once the user reviews and accepts the proposed plan, a booking request is sent from the device to the server. The server automatically completes the booking process using the booking method, including arranging flights and accommodations. If the booking is successfully completed, confirmation information is sent to the device and the user is notified.

[0640] During travel, the server uses advisory tools to provide travelers with real-time, situation-based advice. This allows travelers to continue their trip safely and comfortably. Furthermore, sensor data can be integrated to take into account the individual traveler's health condition, and travel plans can be adjusted as needed.

[0641] For example, if a user requests a plan for a 5-day trip to New York City with a budget of 200,000 yen for two people, the server will use that information to select the best flights and accommodations, and suggest popular tourist destinations and restaurants. Once the plan is accepted, the system will immediately execute the booking and automate the entire process until all arrangements are completed.

[0642] Thus, the present invention enables travelers to enjoy an efficient and personalized travel experience without having to spend time on detailed planning.

[0643] The following describes the processing flow.

[0644] Step 1:

[0645] Users enter their travel preferences through their device. These preferences include destination, budget, travel duration, and travel companion information, and this data is necessary for planning the trip.

[0646] Step 2:

[0647] The device sends the user's entered preferences to the server. This information is formatted as an API request and processed to ensure it reaches the server quickly and securely.

[0648] Step 3:

[0649] The server analyzes the data received from the terminal and generates the optimal travel plan using a generative model. The generative model utilizes historical data and algorithms to combine flights, accommodations, tourist destinations, and activities that match the budget and schedule.

[0650] Step 4:

[0651] The server uses data collection methods to gather real-time information and optimize the generated travel plan. Specifically, it adjusts the plan by considering factors such as weather forecasts, local events, and congestion information.

[0652] Step 5:

[0653] The server sends an optimized travel plan to the user's device and proposes it to them. The user can then review the plan details and make changes or approvals.

[0654] Step 6:

[0655] After the user approves the proposed plan, the device sends that information back to the server and requests that the reservation process begin.

[0656] Step 7:

[0657] The server uses the booking method to automatically make reservations for flights and accommodations based on the proposed plan. It collaborates with partner booking systems and retrieves confirmation information once the arrangements are complete.

[0658] Step 8:

[0659] The server notifies the terminal that the reservation is complete and provides the user with final confirmation information. This allows the user to confirm that all reservations have been completed without any problems.

[0660] Step 9:

[0661] During the trip, the server uses its advisory system to send appropriate advice to the user based on real-time data collected. This makes it easier for the user to cope with unexpected changes during their trip.

[0662] Step 10:

[0663] The server integrates sensor data to adjust the plan based on the user's health status and activity level, modifying the plan as needed. This adjustment ensures the user can continue their journey safely and comfortably.

[0664] (Example 1)

[0665] 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".

[0666] In travel planning, travelers face the challenge of having to spend considerable time and effort choosing the best plan from many options. Furthermore, during the actual trip, it is difficult to respond quickly to changing circumstances, adding to the difficulties. Additionally, effectively adjusting the plan while considering the traveler's health condition is also challenging.

[0667] 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.

[0668] In this invention, the server includes an information input mechanism for inputting the traveler's desired conditions, a component comprising a generation model for generating optimal travel suggestions based on those conditions, and an information gathering mechanism for collecting real-time information and optimizing the generated suggestions. This enables travelers to quickly and accurately formulate efficient and personalized travel plans, and to respond flexibly to changes in circumstances and health conditions during their trip.

[0669] An "information input mechanism" refers to a device or interface used by travelers to input their desired conditions.

[0670] An "information processing device" is a device that receives, analyzes, and processes data transmitted from an information input mechanism.

[0671] A "generative model" refers to an algorithm or data model used to generate optimal travel suggestions based on a traveler's preferences.

[0672] "Components" refer to the multiple technical or functional elements necessary to form a system.

[0673] The "information gathering mechanism" refers to a function that acquires necessary information in real time and optimizes the generated travel suggestions.

[0674] A "reservation system" refers to a system or device that automatically makes various arrangements based on travel proposals.

[0675] A "guidance body" is an organization that provides appropriate advice to travelers in response to changes in their circumstances during their trip.

[0676] "Sensor data" refers to numerical information obtained from various sensors, and this data is used to understand the health status of travelers.

[0677] This invention is a system that streamlines travelers' travel planning and provides personalized travel experiences. The system comprises an information input mechanism, an information processing device, a generation model, an information collection mechanism, a reservation mechanism, and a guidance mechanism.

[0678] First, the user uses a terminal to enter their travel preferences. For example, they enter specific information such as destination, budget, number of travel days, and number of companions. This information is entered as a prompt message in the format of "5-day trip to New York, budget 200,000 yen, 2 people." The terminal then sends this information to the server.

[0679] The server analyzes the input information it receives using an information processing device. Generative AI models are used for this analysis, employing AI frameworks such as TensorFlow and PyTorch. The generative AI model generates travel suggestions that are optimal for the user's conditions. These suggestions include recommended lists of flights, accommodations, tourist destinations, and activities.

[0680] Furthermore, the server uses an information gathering mechanism to acquire real-time data and optimize the suggestions generated based on weather, event information, and traffic conditions. This allows the server to provide plans that match the user's needs and meet appropriate conditions.

[0681] Once the user accepts the generated proposal, a booking request is sent from the device to the server. The server automatically executes the booking using its booking mechanism. Specifically, it interacts with an external travel booking system via an API and performs the necessary booking procedures.

[0682] During travel, the server uses a guidance mechanism to provide users with real-time, situation-appropriate advice. This advice includes suggestions for tourist destinations to visit and information on events. It can also integrate sensor data from wearable devices and adjust travel plans based on the user's health condition.

[0683] In this way, the various components of the system work together, allowing users to experience efficient and comfortable travel.

[0684] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0685] Step 1:

[0686] The user uses a terminal to enter their travel preferences. Specifically, this includes destination, budget, duration of trip, and information about travel companions. This information is entered as a prompt message such as "5-day trip to New York, budget 200,000 yen, 2 people." The entered data is then sent from the terminal to the server.

[0687] Step 2:

[0688] The server analyzes the prompt message received from the user using an information processing device. During the analysis process, a generative AI model is used to generate optimal travel suggestions, taking into account past data and trends. At this point, a list of flights and accommodations that match the user's criteria, along with suggested tourist destinations and activities, are output.

[0689] Step 3:

[0690] The server uses an information gathering mechanism to acquire real-time data from external resources. Specifically, it collects weather information, event information, traffic information, etc., and incorporates this into the generated suggestions. This improves the accuracy and timeliness of the suggestions, providing users with plans optimized for their needs.

[0691] Step 4:

[0692] The user reviews the suggested travel plan on their device. If they agree to the suggestion, the user sends a booking request from their device to the server. This request includes details of the selected flights and accommodations.

[0693] Step 5:

[0694] The server activates the reservation mechanism and automatically makes the necessary arrangements. Flight and accommodation reservations are made through integration with external travel reservation systems. Once the reservation is complete, the details are sent from the server to the terminal and notified to the user.

[0695] Step 6:

[0696] During travel, the server provides real-time advice to the user using a guidance mechanism. This includes optimal action suggestions based on current location information and real-time sensor data, as well as notifications regarding disaster information and emergency events. Information from the user's health devices is also integrated, allowing for adjustments to the plan based on their health status.

[0697] (Application Example 1)

[0698] 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".

[0699] Traditional travel planning systems struggled to fully meet individual needs, making the planning and arrangement process cumbersome and time-consuming for users. Furthermore, they lacked the flexibility to adjust plans based on real-time information, making it difficult to provide an efficient travel experience. Additionally, the automatic adjustment of plans to take into account the user's health condition was not present in previous systems.

[0700] 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.

[0701] In this invention, the server includes a dialogue device means for voice input of the user's desired conditions to an information processing device, an information processing means for generating an optimal travel plan using a generative model, and an information gathering means for acquiring current information. This enables the automatic generation of individual travel plans based on the user's voice input, flexible optimization and adjustment with real-time information, and the provision of an efficient and personalized travel experience without burdening the user.

[0702] A "dialogue device" is a device that allows users to input their desired conditions via voice and transmit them to an information processing device.

[0703] An "information processing device" is a device that generates a travel plan using a generative model based on the desired conditions received from a dialogue device.

[0704] A "generative model" is an algorithm or program used to create the optimal travel plan based on the user's desired conditions.

[0705] "Information gathering methods" refer to means of acquiring information related to the current challenges and optimizing the generated travel plan.

[0706] "Arrangement method" refers to a function or service that automatically makes travel-related arrangements based on an optimized travel plan.

[0707] "Advice methods" refer to means of providing advice based on current information obtained through information gathering methods, in response to changes in circumstances during travel.

[0708] "Sensor data" refers to data from sensors used to understand the user's health status.

[0709] Modes for carrying out the invention

[0710] The system for implementing this invention consists of a set of programs and hardware designed to efficiently personalize travel plans and reduce the burden on the user. The system primarily operates using the following hardware and software:

[0711] The interactive terminal serves the purpose of inputting travel preferences from the user via voice. This device converts the voice into text using speech recognition software such as the Google Speech-to-Text API and transmits it to the information processing device.

[0712] Based on the received text information, the information processing device generates a travel plan using a generative AI model (e.g., OpenAI GPT-4). The generated plan is optimized by incorporating current information obtained through information gathering means, such as weather information and event information. The information gathering means used here include using APIs from the internet and collecting sensor data.

[0713] As a means of arrangement, travel-related arrangements will be automated using the Amadeus API and other tools. This automation will free users from cumbersome procedures, making it easy to arrange the perfect trip.

[0714] Furthermore, the advisory system provides specific advice based on real-time data, adapting to changing circumstances during the trip. This is crucial for taking the best possible action in response to unexpected events that may occur locally and the user's health condition.

[0715] For example, if a user enters their preferences, such as "I want to take a family trip next weekend. I'd like a warm destination and a health-conscious itinerary," the system will provide a customized plan based on that information.

[0716] An example of a prompt message is: "The user is planning a family trip next weekend. The destination is a warm region, so please create a health-conscious plan. Please take the latest weather information into consideration."

[0717] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0718] Step 1:

[0719] The device receives the user's voice input. The user communicates their desired travel conditions to the device as voice. This voice data is converted into text data using speech recognition software (Google Speech-to-Text API). Here, the input is raw voice data, and the output is the desired conditions in text format.

[0720] Step 2:

[0721] The server receives desired travel conditions in text format from the terminal. Based on the received data, a generative AI model (OpenAI GPT-4) generates the optimal travel plan. The input is text data reflecting the user's travel conditions, and the output is an initial travel plan proposal.

[0722] Step 3:

[0723] The server uses information gathering methods to obtain current information. It utilizes APIs from the internet and sensor data, such as weather information and local event information. Using this data, it optimizes the plan based on the latest information. The input is real-time data from the internet and sensors, and the output is an optimized travel plan.

[0724] Step 4:

[0725] The server automatically makes the necessary travel arrangements using booking methods based on the optimized travel plan. Here, it uses the Amadeus API, among others, to book flights and accommodations. The input is the optimized travel plan, and the output is confirmation information of the completed arrangements.

[0726] Step 5:

[0727] The user confirms the completion of their travel plan and arrangements through their device. They receive confirmation information sent from the server and verify that the plan has been approved. The input is the confirmation information from the server, and the output is the notification to the user.

[0728] Step 6:

[0729] The server constantly utilizes information gathering methods to respond to changing circumstances during travel and provides real-time advice. It also adjusts plans based on health conditions and weather changes. The input is continuously collected real-time data, and the output is specific advice tailored to that situation.

[0730] 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.

[0731] This invention is a system that recognizes travelers' emotions and incorporates them into travel plans to provide a more satisfying travel experience. In addition to the basic configuration of conventional systems, this system incorporates an emotion engine to grasp the traveler's emotional state in real time and utilize it for plan generation and adjustment.

[0732] The user enters their travel preferences using a terminal. This input includes destination, budget, travel duration, and travel companion information. The terminal sends the input data to the server. The server uses this data to create a travel plan using a generative model. During this generation process, an emotion engine operates to analyze the traveler's emotional state. This emotional state is obtained by combining the data entered by the user with information obtained from external devices.

[0733] The server further utilizes data collection methods to aggregate external data in real time and optimize the plan. At this time, the emotion engine identifies and aligns factors such as the traveler's emotional satisfaction, thereby providing a travel plan that satisfies the traveler.

[0734] Furthermore, if the user provides feedback regarding their emotions or the plan, the plan will be adjusted. The device also sends emotional data to the server as part of the communication. The server uses this data to inform the emotion engine, which then initiates or modifies the plan to match the traveler's current emotional state.

[0735] In practice, for example, if a user creates a plan with conditions such as "a 7-day trip to London, budget of 300,000 yen, for 2 people," the server will create the optimal travel plan based on that information and emotional data. If the user's mood changes during the trip, for example, if it is determined that relaxation is needed, the server will suggest new events and sightseeing spots suitable for relaxation. Conversely, if the user wants to be active, the plan will be adjusted to include more sports events and activities.

[0736] This enables a highly personalized travel experience that reflects the user's actual emotional state. By integrating with an emotion engine, this system further enhances user travel satisfaction.

[0737] The following describes the processing flow.

[0738] Step 1:

[0739] Users enter basic travel information and preferences through their device. This includes destination, budget, travel duration, and information about travel companions.

[0740] Step 2:

[0741] The terminal sends the information entered by the user to the server. This transmitted data becomes the source data for creating the travel plan.

[0742] Step 3:

[0743] The server analyzes the received data and uses a generative model to create a basic travel plan. At this point, the user's emotional state is not yet taken into consideration.

[0744] Step 4:

[0745] The server activates the emotion engine and analyzes the user's emotional data. This emotional data includes facial recognition, voice analysis data, and vital signs information acquired in real time from terminals and wearable devices.

[0746] Step 5:

[0747] Based on the analysis results of the emotion engine, the server customizes the generated travel plan according to the user's emotional state. For example, if the user is experiencing high stress, a relaxing plan will be added.

[0748] Step 6:

[0749] The server further optimizes travel plans based on external data obtained in real time using data collection methods. This information includes weather changes and local event information.

[0750] Step 7:

[0751] The server sends the adjusted plan to the terminal and proposes it to the user. The user can review the plan and send feedback as needed.

[0752] Step 8:

[0753] Once the user accepts the plan, the device sends this information to the server and begins the reservation process.

[0754] Step 9:

[0755] The server automatically makes all travel reservations based on the pre-arranged plan using the reservation system. The user confirms the completed reservation information by receiving a notification on their device.

[0756] Step 10:

[0757] During the trip, the server continuously monitors the user using an emotion engine, dynamically adjusting the travel plan accordingly if there are any changes in the user's emotional state, providing the traveler with the best possible experience.

[0758] (Example 2)

[0759] 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".

[0760] Traditional travel planning systems struggle to take into account travelers' emotional states and real-time environmental changes, resulting in the provision of plans that are not optimal for the traveler. Furthermore, they lack the means to quickly respond to changing circumstances during travel and improve traveler satisfaction. This leads to the challenge of standardized travel experiences that fail to meet individual needs.

[0761] 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.

[0762] In this invention, the server includes an analysis means incorporating an emotion analysis engine for analyzing the emotional state of travelers in real time, a data collection means for aggregating data to optimize a travel plan generated by a generative artificial intelligence model based on emotional data and real-time data, and a reservation means for automatically making reservations based on the optimized travel plan. This makes it possible to provide a personalized travel experience that is tailored to the emotional state and environmental changes of each individual traveler.

[0763] "Information equipment" refers to devices that travelers use to input their desired conditions and transmit them to a server. Specifically, this includes smartphones, tablets, and personal computers.

[0764] "Computing device means" refers to a device that receives and processes data transmitted from information equipment means. Servers and cloud computing environments fall into this category.

[0765] A "generative artificial intelligence model" refers to a model that uses machine learning techniques to automatically generate travel plans based on input data.

[0766] A "emotion analysis engine" refers to a processing engine that analyzes a traveler's emotional state in real time and uses that data to adapt travel plans.

[0767] "Analysis means" refers to devices or programs used to extract and understand the emotional state of a user from data.

[0768] "Data collection methods" refer to means of aggregating real-time data on travelers' emotions and the environment, and using that data to optimize travel planning.

[0769] "Reservation method" refers to a system element that automatically makes reservations for various services and events based on an optimized travel plan.

[0770] This invention provides a system that generates travel plans that take into account the emotional state of travelers based on their desired conditions. Specifically, it uses a terminal, a server, and a generative AI model and emotion analysis engine that handle various types of data.

[0771] Users input their desired travel conditions, such as destination, budget, duration, and travel companion information, using information devices such as smartphones or personal computers. These information devices transmit the user's input data to the server. The data sent from the terminal is received by the server, which is a computing device.

[0772] The server uses a generative artificial intelligence model to generate a travel plan from the received data. This generative AI model utilizes machine learning techniques to generate the optimal travel plan for given conditions. During this process, an emotion analysis engine operates to analyze the user's emotional state in real time. The analyzed emotion data is acquired based on sensor information from external wearable devices and smartphones and incorporated into the travel plan.

[0773] Next, the server uses data collection methods to aggregate real-time data such as weather information and event information. This allows the travel plan to be optimized according to the user's emotional state. As part of the optimization process, if the user wants to relax, it suggests activities suitable for relaxation, and if they want to be active, it provides a plan that includes many sports events and activities.

[0774] For example, if a user enters the conditions "7-day trip to London, budget 300,000 yen, 2 people," the server will consider this information along with emotional data to generate the optimal travel plan. If it determines that relaxation is needed during the trip, it will suggest events and sightseeing spots suitable for relaxation; conversely, if the user wants to be active, it will suggest sports events and activities.

[0775] An example of a prompt for the generating AI model would be, "Based on the user's emotional data, please suggest a relaxing London travel plan. The budget is 300,000 yen, for 7 days, for 2 people." This embodiment of the present invention makes it possible to realize a personalized travel experience that matches the user's current emotions and preferences.

[0776] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0777] Step 1:

[0778] Users input their travel preferences using devices such as smartphones or computers. These preferences include destination, budget, travel duration, and travel companion information. The entered data is formatted as needed within the device and prepared as structured data. This structured data is then sent to the server via an HTTP request. The input consists of the user-specified preferences, while the output is structured data transferred to the server.

[0779] Step 2:

[0780] The server receives structured data sent from the terminal. The received data is parsed and prepared to be input into the generative AI model. The server uses the generative AI model to begin creating a travel plan based on the input data. The input data consists of desired conditions, and the output is a provisional travel plan. The generative AI model parses this data and proposes the optimal travel plan via prompt messages.

[0781] Step 3:

[0782] The server runs an emotion analysis engine to analyze the user's emotional state in real time. Based on biometric and behavioral data obtained from the terminal and wearable sensors, it evaluates the user's current emotional state. Biometric information from the terminal and wearable devices is used as input, and the analyzed emotion data is provided as output.

[0783] Step 4:

[0784] The server optimizes the initial travel plan by combining analyzed sentiment data with real-time data collected from external sources (weather, event information, etc.). Data collection methods gather this information and make adjustments to reflect it in the plan. The input includes sentiment data and external real-time information, and the output is an optimized travel plan. This process involves re-evaluating the generative AI model to provide a travel plan that is adapted to emotions and the environment.

[0785] Step 5:

[0786] If a user provides feedback during their trip, the device sends it to the server. The feedback is received as textual comments and ratings, and is then incorporated into the sentiment analysis engine's evaluation. The server then makes further adjustments to the travel plan based on the feedback received. The input is feedback information, and the output is a revised travel plan that reflects the feedback.

[0787] (Application Example 2)

[0788] 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".

[0789] The challenge lies in improving traveler satisfaction by recognizing travelers' emotional states in real time and providing travel itineraries that reflect this. Conventional travel plan generation systems have often failed to adequately respond to travelers' emotions and real-time changes in circumstances, resulting in an inability to provide the optimal travel experience. Therefore, there is a need for the generation and adjustment of dynamic travel itineraries that take travelers' emotions into consideration.

[0790] 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.

[0791] In this invention, the server includes a terminal device for inputting the traveler's desired requirements, an information processing device, and an emotion analysis device. This makes it possible to recognize the traveler's emotional state in real time, dynamically adjust the travel itinerary based on that, and provide a personalized and highly satisfying travel experience.

[0792] "Traveler's desired requirements" refer to the conditions that travelers have in mind when planning their trip, such as the destination, budget, number of days, and information about their travel companions.

[0793] A "terminal device" refers to an electronic device used by travelers to input their desired requirements, and includes smartphones, tablets, and other similar devices.

[0794] An "information processing device" refers to a server or computer system that receives input requests and generates travel plans.

[0795] "Generative methods" refer to algorithms and processes that automatically design the optimal travel itinerary based on the traveler's desired requirements.

[0796] An "information gathering device" refers to a device or system used to collect data necessary to understand the real-time situation during travel.

[0797] A "emotion analysis device" refers to a system that analyzes a traveler's emotional state in real time and uses the results to adjust the travel itinerary.

[0798] A "booking system" refers to a system that automatically makes reservations for accommodations, transportation, and other services based on an optimized travel itinerary.

[0799] An "advisory device" refers to a system that provides appropriate advice and suggestions based on a traveler's real-time data and emotional state.

[0800] This invention provides a system that recognizes a traveler's emotional state in real time and dynamically adjusts the travel plan based on that information. This system includes a terminal device for inputting the traveler's preferences, which the traveler inputs into a terminal device such as a smartphone or tablet. The terminal device communicates with an information processing device, i.e., a server, and transmits the input preferences to the server.

[0801] The server uses a generation method based on the received information to design the optimal travel itinerary. An AI model is used in the generation method to automatically formulate an itinerary that meets the user's desired requirements. Furthermore, the server acquires real-time data via information gathering devices and optimizes the plan by considering factors that may change during the trip.

[0802] Depending on the type of travel, the server uses an emotion analysis device to analyze the traveler's emotions. This device performs calculations based on sensor data from smart wearable devices, cameras, and other sources to understand the traveler's current emotional state.

[0803] This allows the server to suggest relaxation events if the traveler is in a relaxed state, and suggest active activities if the traveler is in an active state. Furthermore, a booking system with automated reservation capabilities ensures appropriate bookings are made and the traveler's wishes are fulfilled.

[0804] As a concrete example, consider a traveler planning a 7-day trip to London with a limited budget. In this case, a generative AI model can be used to design a plan that maximizes satisfaction. An example of a prompt would be, "I am planning a 7-day trip to London. What activities would an application with emotion recognition capabilities suggest based on whether the traveler wants to relax or be active?" In this way, it is possible to provide the optimal travel experience tailored to the user.

[0805] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0806] Step 1:

[0807] The user enters their travel plan requirements on a terminal. These requirements include destination, budget, duration, and number of travel companions. This input data is then sent from the terminal to the server.

[0808] Step 2:

[0809] The server uses a generation AI model to formulate an initial travel itinerary based on the received desired requirements. It executes a generation process based on the input requirements to construct a travel plan. A temporary travel plan is generated as output.

[0810] Step 3:

[0811] The server acquires real-time data from external sources via information gathering devices. This data includes weather information, event information, and congestion levels, and this data is used to optimize the plan.

[0812] Step 4:

[0813] The server uses an emotion analysis device to analyze the traveler's emotional state in real time. To do this, it collects sensor data from smart wearable devices or cameras and performs computational processing to identify the emotional state. This results in the traveler's current emotions being output.

[0814] Step 5:

[0815] The server combines collected real-time data with sentiment analysis results to adjust the travel plan. Based on the emotional state, it processes the data to add relaxation events or active activities to the plan. The adjusted travel plan is then output.

[0816] Step 6:

[0817] Based on the coordinated travel plan, the server's booking system automatically executes the necessary reservations. It books accommodations and arranges transportation, making the travel plan ready to be executed.

[0818] Step 7:

[0819] Users receive information about their current travel plan and suggested activities through their device. They can provide feedback on their travel plan as needed, and this feedback will be used to adjust future plans.

[0820] 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.

[0821] 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.

[0822] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0823] 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.

[0824] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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."

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0841] The following is further disclosed regarding the embodiments described above.

[0842] (Claim 1)

[0843] A terminal device for travelers to input their desired conditions,

[0844] A server means that receives the desired conditions transmitted from the terminal means,

[0845] A system means comprising a generation model for generating an optimal travel plan based on the aforementioned desired conditions,

[0846] A data collection means for collecting real-time data in order to optimize the travel plan generated by the aforementioned generation model,

[0847] A booking method that automatically makes reservations based on the optimized travel plan,

[0848] A system that includes this.

[0849] (Claim 2)

[0850] The system according to claim 1, further comprising an advice means that provides advice in response to changes in circumstances during travel, based on real-time data acquired by the data collection means.

[0851] (Claim 3)

[0852] The system according to claim 1, wherein the generation model comprises means for integrating sensor data to adjust the travel plan based on the traveler's health condition.

[0853] "Example 1"

[0854] (Claim 1)

[0855] An information input mechanism for travelers to enter their desired conditions,

[0856] An information processing device that receives desired conditions transmitted from the information input mechanism,

[0857] A component comprising a generation model for generating optimal travel proposals based on the aforementioned desired conditions,

[0858] An information gathering mechanism that collects real-time information in order to optimize the travel proposals generated by the aforementioned generation model,

[0859] A reservation system that automatically makes reservations based on the optimized travel suggestions,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, further comprising a guidance mechanism that provides advice in response to changes in circumstances during travel, based on real-time information acquired by the aforementioned information gathering mechanism.

[0863] (Claim 3)

[0864] The system according to claim 1, wherein the generation model comprises means for integrating sensor data to adjust travel suggestions based on the traveler's health status.

[0865] "Application Example 1"

[0866] (Claim 1)

[0867] A dialogue device for voice input of the user's desired conditions,

[0868] An information processing device that receives desired conditions transmitted from the aforementioned dialogue device,

[0869] Information processing means equipped with a generation model for generating an optimal travel plan based on the aforementioned desired conditions,

[0870] Information gathering means for acquiring current information in order to optimize the travel plan generated by the aforementioned generation model,

[0871] A means for making arrangements automatically based on the optimized travel plan,

[0872] A system that includes this.

[0873] (Claim 2)

[0874] The system according to claim 1, further comprising an advisory means that provides advice in response to changes in circumstances during travel, based on the current information obtained by the aforementioned information gathering means.

[0875] (Claim 3)

[0876] The system according to claim 1, wherein the generation model comprises means for integrating sensor data to adjust the travel plan based on the user's health status.

[0877] "Example 2 of combining an emotion engine"

[0878] (Claim 1)

[0879] Information equipment for inputting the traveler's desired conditions,

[0880] A computing device means that receives desired conditions transmitted from the aforementioned information device means,

[0881] A system means comprising a generative artificial intelligence model for generating an optimal travel plan based on the aforementioned desired conditions,

[0882] An analysis method incorporating an emotion analysis engine to analyze the emotional state of travelers in real time,

[0883] A data collection means for aggregating data in order to optimize the travel plan generated by the aforementioned artificial intelligence model based on emotional data and real-time data,

[0884] A booking means that automatically makes reservations based on the optimized travel plan,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, further comprising an advice means that provides advice in response to changes in the situation during travel, based on real-time data acquired by the data collection means and emotional data from an emotion analysis engine.

[0888] (Claim 3)

[0889] The system according to claim 1, wherein the generating artificial intelligence model comprises means for integrating sensor data to adjust the travel plan based on the traveler's emotional state and health condition.

[0890] "Application example 2 when combining with an emotional engine"

[0891] (Claim 1)

[0892] A terminal device for introducing the traveler's preferences,

[0893] An information processing device that receives the desired requirements transmitted from the terminal device,

[0894] A configuration means equipped with a generation method for generating an optimal travel itinerary based on the aforementioned desired requirements,

[0895] An information gathering device that collects dynamic data in order to optimize the travel itinerary generated by the above generation method,

[0896] An emotion analysis device that recognizes the emotional state of travelers in real time and adjusts the travel itinerary based on that emotional state,

[0897] A booking device that automatically makes arrangements based on the optimized travel itinerary,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, further comprising an advisory device that provides advice in response to environmental changes during travel, based on dynamic data and emotional states acquired by the information gathering device.

[0901] (Claim 3)

[0902] The system according to claim 1, wherein the generation method comprises means for integrating sensor data to adjust the travel itinerary based on the traveler's emotional state and health condition. [Explanation of symbols]

[0903] 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 terminal device for travelers to input their desired conditions, A server means that receives the desired conditions transmitted from the terminal means, A system means comprising a generation model for generating an optimal travel plan based on the aforementioned desired conditions, A data collection means for collecting real-time data in order to optimize the travel plan generated by the aforementioned generation model, A booking method that automatically makes reservations based on the optimized travel plan, A system that includes this.

2. The system according to claim 1, further comprising an advice means that provides advice in response to changes in circumstances during travel, based on real-time data acquired by the data collection means.

3. The system according to claim 1, wherein the generation model comprises means for integrating sensor data to adjust the travel plan based on the traveler's health condition.

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