system

Abstract

We provide the system. [Solution] A means of obtaining travel information entered by the user, A means for analyzing acquired travel information and generating a travel plan based on user requests, A means for optimizing the generated travel plan and providing the optimized travel plan to the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, 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] When planning a family trip, it is very complicated to create a highly satisfactory travel plan within the budget while adjusting the schedules of all family members with different age groups and wishes. This process requires a lot of labor and time, such as information collection in the planning stage, arrangement of transportation means and accommodation, and selection of tourist attractions. Moreover, if the plan is changed during various adjustments, the accompanying adjustment work will overlap, which will impose a heavy burden on travelers. There is a need to reduce the labor involved in such family trip planning and enable the construction of an effective travel plan that reflects the desires of all participants.

Means for Solving the Problems

[0005] The present invention solves the above problems by providing a system that includes means for acquiring travel information entered by a user, means for analyzing the acquired travel information to generate a travel plan that meets the user's wishes, and means for optimizing and providing the generated travel plan. This system efficiently and quickly processes user input and automatically generates a customized travel plan based on multiple parameters. Furthermore, by incorporating the latest information from external sources, it simplifies adjustments when changes are needed, enabling the creation of more flexible and practical travel plans. In addition, since the provided travel plan can be easily checked and fine-tuned by the user on their terminal, the burden during the travel planning stage can be greatly reduced.

[0006] A "user" is an individual or group that uses the system to plan a trip.

[0007] "Travel information" refers to data that includes various conditions related to the trip, such as the travel itinerary, budget, destinations, number of participants, and any special requests.

[0008] "Means of acquisition" refers to the process or function for incorporating travel information provided by users into the system.

[0009] "Means of analysis" refers to data processing functions that evaluate user requests and conditions based on acquired travel information and reflect them in travel plans.

[0010] A "travel plan" is a document or draft that includes a travel schedule, transportation, accommodation, and sightseeing spots, based on the user's preferences.

[0011] "Generating means" refers to the processes and algorithms used to create a specific travel plan based on user input information and analysis results.

[0012] "Optimization means" refers to functions or technologies that adjust and improve generated travel plans with maximum efficiency and user satisfaction in mind.

[0013] "Means of provision" refers to the mechanisms and methods for presenting and making an optimized travel plan accessible to the user.

[0014] A "terminal" is a device that a user uses to access a system, enter information, or check travel plans.

[0015] "External information sources" refer to information providers or databases located on the internet or other communication networks that provide up-to-date data related to travel planning. [Brief explanation of the drawing]

[0016] [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] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 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

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

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

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

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

[0021] 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.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention, the AI ​​Family Travel Planner, is a system that provides a travel plan tailored to the user's preferences while reducing the user's burden. The embodiments of this system are described below.

[0038] Users access a dedicated interface via their device and input details such as their travel dates, budget, desired destinations, and the names of the participants. This information is sent to the system's underlying server. Upon receiving this data, the server uses an AI model to analyze it and generate an optimal travel plan tailored to the user's preferences.

[0039] The AI ​​model embedded in the server learns from past travel data and relevant external sources, allowing it to flexibly respond to different user requests. In this process, the server not only creates the most efficient schedule within a given timeframe but also performs real-time price comparisons to suggest the best options within the user's budget.

[0040] For example, if a user enters a request such as, "My family of four wants to take a 5-night, 6-day domestic trip during summer vacation. Our budget is 200,000 yen, and we want to enjoy nature in addition to famous tourist spots," the server will respond by selecting tourist destinations that can be visited within the budget and proposing a travel schedule for each day. For example, it might plan a trip to famous tourist spots in urban areas on the first day, and to enjoy nature in suburban areas on the second and third days, and also provide information on accommodations and transportation.

[0041] The terminal displays the plan generated by this server in detail. The user can review this plan and make fine adjustments on the terminal if necessary. In this way, the cumbersome tasks of travel planning are fully automated, and a trip tailored to the individual user's wishes is quickly planned.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users access a dedicated interface from their device and enter travel information such as travel dates, budget, desired destinations, and participant information. This information forms the basis of the travel plan, so it is required to be entered in as much detail as possible.

[0045] Step 2:

[0046] The terminal sends the information entered by the user to the server as data packets. At this time, the input data is structured and formatted to facilitate analysis by the server.

[0047] Step 3:

[0048] The server sends the received travel information to an analysis engine, which generates a travel plan that takes the user's preferences into account. This analysis considers factors such as weather at the destination, event information, transportation options, and accommodation availability to create the optimal schedule.

[0049] Step 4:

[0050] The server accesses external information sources to obtain the latest tourist attraction and pricing information and integrates it into the travel plan. This process is performed in real time based on the user's preferences and aims to improve the accuracy of the plan.

[0051] Step 5:

[0052] The server optimizes accommodations and transportation to ensure maximum satisfaction within the budget. Here, the most suitable plan is calculated based on AI-driven budget allocation and the user's preferences.

[0053] Step 6:

[0054] The generated travel plan is sent from the server to the terminal and displayed to the user in a visually easy-to-understand format. This includes the schedule for each day, information on destinations, and details of transportation.

[0055] Step 7:

[0056] Users can review the provided travel plan through their device and make adjustments as needed. For example, they can add specific tourist destinations or change the order of visit dates.

[0057] (Example 1)

[0058] 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."

[0059] The challenge lies in reducing the cumbersome tasks users face when planning a trip, while simultaneously generating optimal travel plans tailored to various conditions. In particular, sophisticated planning that responds immediately to individual conditions such as travel dates and budgets, and reflects real-time information, is required.

[0060] 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.

[0061] In this invention, the server includes means for acquiring travel information, including itinerary information and budget information, obtained through a device operated by the user; means for analyzing the acquired travel information and generating a travel plan through an information processing model using past travel data; and means for optimizing the generated travel plan using the latest information, including price information, by linking with an external information source. This makes it possible to efficiently create and present an optimal travel plan that suits the user's conditions.

[0062] A "user-operated device" is an electronic device used by a user to input information and transmit it to a server through an interface.

[0063] "Itinerary information" refers to information about the start and end dates and specific times of a trip, and forms the basis of a travel plan.

[0064] "Budget information" refers to information about the maximum amount of money set for travel expenses, and an appropriate travel plan is created based on this information.

[0065] "Travel information" refers to comprehensive data that includes details related to a trip, such as the itinerary, budget, destinations, and participants.

[0066] An "information processing model" refers to an algorithm that learns from past data and generates an optimal travel plan tailored to the user's needs.

[0067] "External information sources" refer to external data providers that offer information necessary for travel planning, such as real-time prices and booking status.

[0068] "Optimization" is the process of creating the most efficient and effective travel plan, taking into account available resources and conditions.

[0069] "Travel plan" refers to a detailed plan of the trip, including the schedule, destinations, means of transportation, and accommodations, which is created based on the information entered by the user.

[0070] The following system configuration is considered as an embodiment of this invention. When planning a trip, the user accesses a dedicated interface from an internet-connected terminal and inputs detailed information such as the trip itinerary, budget, places to visit, and participants. The terminal transmits this information to the server via the HTTPS protocol.

[0071] The server activates an internal AI model based on the received travel information, and uses historical travel data and real-time pricing information from external sources to generate an optimal travel plan tailored to the user's needs. In this process, the server performs various data analyses to efficiently schedule the trip within the specified travel period and develop a plan that provides the greatest value within the budget.

[0072] As a concrete example, consider a scenario where a user inputs a prompt such as, "My family of four wants to take a 5-night, 6-day domestic trip during summer vacation. Our budget is 200,000 yen, and we want to enjoy nature in addition to famous tourist spots." Based on the conditions received from the user, the server uses artificial intelligence to automatically select suitable tourist destinations and proposes a specific schedule for each day of the trip. For example, it might create a plan to visit famous tourist spots in urban areas on the first day, and then visit suburban areas where nature can be enjoyed on the second and third days, and also provide detailed information on accommodations and transportation.

[0073] The generated travel plan is displayed on the device, allowing the user to review and make adjustments as needed. Once adjustments are complete on the device, the final travel plan is sent back to the server for storage. This allows the user to review the plan before their trip and smoothly prepare for departure.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The user enters detailed travel plan information into the device. Specifically, they input travel dates, budget, destination, and participant information into a dedicated interface. This information is stored on the device as input data to create a travel plan that reflects the user's preferences.

[0077] Step 2:

[0078] The device sends saved travel information to the server via HTTPS. Input data includes user-specified itinerary information, budget information, and desired destinations, and this data is securely transmitted to the server.

[0079] Step 3:

[0080] The server activates a generation AI model based on the received data. The process involves analyzing the user's input data and automatically generating a travel plan that matches the user's preferences, while obtaining real-time information from past travel databases and external sources. This outputs a proposed itinerary, destinations, and accommodation options as part of the travel plan.

[0081] Step 4:

[0082] The server optimizes the generated travel plan. Specifically, it collaborates with external sources to obtain the latest pricing and booking information and incorporates it into the travel plan. This process makes it possible to present the best options within the user's budget.

[0083] Step 5:

[0084] The generated plan is sent from the server to the device. The device displays this optimized travel plan in detail to the user. The user reviews the displayed plan and makes adjustments to the itinerary and destinations as needed.

[0085] Step 6:

[0086] Once the user has finalized their plan, that information is sent from their device to the server, and the final travel plan is confirmed. The server saves this travel plan in a database so that it can be reviewed and modified later. At this stage, all steps are complete.

[0087] (Application Example 1)

[0088] 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."

[0089] Traditional travel planning systems required users to manually input detailed information and manually review and adjust their plans, resulting in a heavy user burden and a time-consuming planning process. Furthermore, interactive travel planning adjustments using household electronic devices were not considered, making it difficult to respond quickly to user situations and preferences.

[0090] 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.

[0091] In this invention, the server includes means for acquiring travel information entered by the user, means for analyzing the acquired travel information and generating a travel plan based on the user's requests, means for optimizing the generated travel plan and providing the optimized travel plan to the user, means for recognizing the user's voice input and outputting information related to the travel plan based on the recognition results, and means for interacting with the user through a home appliance and performing adjustments to the travel plan in real time. This enables the user to intuitively and quickly plan and adjust their travel plan via voice.

[0092] A "user" is an individual or legal entity that uses the system to plan or adjust travel plans.

[0093] "Travel information" refers to data such as the itinerary, budget, desired destinations, and detailed information about the participants.

[0094] "Means of acquisition" means a method or device for accurately receiving and recording information provided by the user.

[0095] "Means for analysis and generation" refers to a method or apparatus for analyzing acquired data to create a travel plan that meets the user's preferences.

[0096] "Means of optimization and delivery" refers to a method or device that adjusts a generated travel plan to best match the user's conditions and informs the user of that plan.

[0097] "Means for recognizing voice input" means a method or device that analyzes the user's voice, converts it into text data, and makes it available for processing within the system.

[0098] "Household machinery and equipment" refers to mechanical or electronic devices used within the home that enable interaction with the user.

[0099] "Means for dialogue and adjustment" refers to methods or devices for changing or updating travel plans through communication with users.

[0100] A system implementing this invention acquires travel information entered by the user via voice or a terminal, automatically creates a travel plan using a generated AI model based on that information, and provides it to the user interactively through a home appliance.

[0101] The system first collects the user's voice input using a home electronic device and converts it into text data using speech recognition software (e.g., Google® Cloud Speech-to-Text). This converted data is sent to a server where it is analyzed using a machine learning library (e.g., TENSORFLOW®). The server then generates a travel plan based on the analysis results. In doing so, it uses external APIs (e.g., Google Maps API) to obtain the latest tourist destination information and weather information and incorporates it into the plan.

[0102] Furthermore, the generated travel plan is optimized using an algorithm to suit the user's budget and preferences, and is provided to the user via voice and screen display through a home device. The user can review this plan and, if necessary, instruct the home device to change the plan in real time. This instruction is also received by voice, analyzed again on the server, and an updated plan is provided.

[0103] For example, if a user uses voice input to say, "I'm planning a 3-night, 4-day family trip next weekend. My budget is 250,000 yen, and I'd like to visit historical sites and natural attractions," the server will analyze this and suggest appropriate destinations. For instance, it might suggest a schedule such as visiting historical sites on day 1 and natural attractions on day 2.

[0104] An example of a prompt message for a generative AI model would be: "My family of four is planning a weekend trip. Our budget is 200,000 yen, and we want a good balance of sightseeing in urban and rural areas. Please create a schedule for us."

[0105] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0106] Step 1:

[0107] Users input travel information using voice or a device. During this process, users provide details such as their travel itinerary, budget, and desired destinations. The entered information is then converted into text data through a voice recognition system.

[0108] Step 2:

[0109] The terminal sends the converted text data to the server. The server receives this data and performs analysis using a machine learning library. Specifically, it analyzes the user's requests and processes the data to generate a travel plan based on them.

[0110] Step 3:

[0111] The server uses a generative AI model to create travel plans that meet the user's requests. Based on the results of the input data analysis, it selects relevant tourist destinations and accommodations and creates a specific itinerary.

[0112] Step 4:

[0113] The server uses external information sources (e.g., APIs) to retrieve the latest information on tourist destinations, weather, and transportation. This retrieved external data is then incorporated into the travel plan and adjusted to fit the itinerary and budget.

[0114] Step 5:

[0115] The generated travel plan is optimized by the server. Based on the user's conditions, budget, and preferences, an optimization algorithm is applied to create the most efficient and satisfying plan.

[0116] Step 6:

[0117] The device provides the user with an optimized travel plan. Details of the travel plan are displayed via voice and on the screen through the home electronic device. The user can visually and audibly review the plan's overview.

[0118] Step 7:

[0119] If a user wishes to change or adjust their plan, they can provide instructions in real time via their device. The device then sends these instructions back to the server, which recalculates and adjusts the travel plan based on the instructions and provides the user with an updated plan.

[0120] 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.

[0121] This invention aims to build a system that provides travel plans that take user emotions into consideration. By incorporating an emotion engine, the system recognizes the user's emotional state and optimizes the travel plan based on that state.

[0122] Users use their devices to input detailed travel information. This includes not only dates, budgets, and places they want to visit, but also the ability to express their wishes and preferences through voice. The device sends the collected data to a server. During this process, the voice and text data are analyzed by an emotion engine to detect and evaluate the user's current emotions. The emotion engine determines emotions through text phrasing, tone of voice, and even quick questionnaire-style interactions.

[0123] Based on emotional data, the server analyzes the user's emotional state, such as whether they are seeking relaxation or adventure, and generates a travel plan accordingly. Emotion-responsive planning proceeds in parallel with the normal travel plan generation process. For example, if the emotion engine detects that the user is feeling stressed, the server will prioritize suggesting tourist spots and activities that are likely to have a relaxing effect (such as visiting a hot spring resort or choosing a hotel with massage services).

[0124] For example, if a user voice-inputs "I want to be freed from my busy life," and the emotion engine detects the need for relaxation, the server will use that information to create a travel plan that includes accommodation in a quiet natural environment. This plan will primarily feature quiet resorts and spas in the countryside rather than urban tourist spots, ensuring that the user can refresh both their mind and body.

[0125] Ultimately, the device provides the user with these optimized travel plans, allowing them to review the details and make adjustments as needed. This system enables more personalized travel planning that also takes the user's emotional needs into consideration.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] Users input their travel plans and preferences through their device. In addition to text input, they can use the device's voice input function to convey emotional elements of their wishes and expectations (e.g., wanting to relax, wanting adventure). The device packages this data and sends it to the server.

[0129] Step 2:

[0130] The server analyzes the received data and activates the emotion engine. The emotion engine uses natural language processing and speech analysis techniques to evaluate the user's emotions in order to generate emotion indicators from the user's written and spoken content. It detects and classifies emotional states such as positive, negative, and neutral.

[0131] Step 3:

[0132] In generating travel plans, the server considers emotional indicators obtained from the emotion engine. For example, if a user indicates stress, the server prioritizes suggesting tourist destinations and activities that include many relaxing elements. Conversely, if a user indicates enthusiasm, it creates a plan that includes adventurous tours and activities that offer new experiences.

[0133] Step 4:

[0134] By utilizing external information sources, the system obtains real-time, up-to-date information on tourist destinations, events, and accommodation availability. The server integrates this information to create an optimal plan that matches the user's emotional state.

[0135] Step 5:

[0136] The server sends the completed travel plan to the terminal, making it accessible to the user. The travel plan clearly displays options and recommendations tailored to the user's preferences.

[0137] Step 6:

[0138] Users can review the travel plan provided on their device and adjust details as needed. Feedback from the emotion engine provides additional information to determine if the user is satisfied with the plan, and further adjustments can be made based on their response.

[0139] (Example 2)

[0140] 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".

[0141] Traditional travel planning systems typically provide plans based on the user's explicit requests. However, these systems often fail to consider the user's emotional state, making it difficult to provide a truly personalized experience. Specifically, if a user is experiencing stress, they may not receive suggestions tailored to their emotions, potentially resulting in a less-than-satisfactory travel experience.

[0142] 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.

[0143] In this invention, the server includes a computing device for performing emotion analysis, means for generating a travel plan based on the user's emotions, means for identifying travel destinations and activities that promote relaxation according to the emotional state, and means for optimizing the generated travel plan and providing it to the user. This makes it possible to provide a more personalized travel plan that takes the user's emotional state into consideration.

[0144] A "user" is an individual or group that provides and receives travel planning information from the system.

[0145] "Travel information" refers to specific travel data provided by the user, such as itinerary, budget, and desired destinations.

[0146] "Emotional state" refers to a user's inner feelings and psychological tendencies, and is an element that is reflected in their travel plan.

[0147] "Emotion analysis" is a technical process that processes a user's voice and text data to determine their emotional state.

[0148] A "travel plan" is a specific itinerary for carrying out a trip, generated based on the user's requests and emotional state.

[0149] A "computational unit" is a device within a system consisting of a computer that performs emotion analysis and determines the user's emotional state.

[0150] "Optimization" is the process of adjusting the generated travel plan according to the user's emotional state and requests, enabling the best possible suggestions.

[0151] "Travel destinations and activities that promote relaxation" refer to travel destinations or activities aimed at reducing user stress and enhancing their refreshing effect.

[0152] This invention is a system that provides travel plans that take into account the user's emotional state, and is realized through the coordinated operation of the user, terminal, and server.

[0153] First, the user enters travel-related information into the device. This includes specific details such as the travel itinerary, budget, and places they want to visit. In addition, through voice input, the user can express their wishes and preferences in a natural way.

[0154] The device transmits the collected information to the server. This data includes text and audio data, and encryption technology is used during the transmission process to ensure data security. After the data is transmitted, the server receives it and uses a computing device for sentiment analysis to determine the user's emotional state. This analysis uses natural language processing technology and speech analysis algorithms to precisely evaluate the user's voice tone and word choice.

[0155] Based on the results of the emotion analysis, the server uses a generative AI model to generate a travel plan that matches the user's emotions. The generated plan may include destinations and activities that promote relaxation for the user. For example, if a user voice-inputs "I want to escape from my busy life," and the emotion analysis determines that relaxation is needed, the server can offer a lodging plan at a quiet resort away from the city.

[0156] Ultimately, the device presents the user with an optimized travel plan generated by the server. The user can review this plan and make adjustments as needed. This system enables the provision of a more personalized travel experience that also takes the user's emotional state into account.

[0157] A concrete example of a prompt to input into a generative AI model is, "Suggest a relaxing travel plan based on an analysis of the user's emotions." Using this prompt, the generative AI model will make the most suitable suggestion from a number of options.

[0158] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0159] Step 1:

[0160] Users input detailed information such as travel dates, budget, and desired destinations through their devices. Furthermore, they can use voice input to naturally express their preferences and desires. This input data is standardized across devices and prepared as a data stream. The input includes both text and voice data, resulting in data ready for transmission to the server as output.

[0161] Step 2:

[0162] The terminal sends standardized data to the server. During transmission, an encryption process is performed to ensure data security. In this process, data is transmitted to the server via encrypted communication and stored as output in a temporary storage area on the server.

[0163] Step 3:

[0164] The server passes the received data to a computing unit for sentiment analysis. Using a sentiment engine, natural language processing techniques and speech analysis algorithms are applied. The input consists of speech and text data stored on the server, and the user's emotional state is analyzed through this data processing. The output is numerical data or categorical information indicating the emotional state.

[0165] Step 4:

[0166] The server uses a generative AI model to generate a travel plan that aligns with the user's emotions, based on the results of the emotion analysis. By inputting the prompt "Suggest a relaxing travel plan based on the user's emotion analysis" to the generative AI model, the server will generate suggestions for optimal travel destinations and activities. The input consists of the emotion analysis results and the user's travel requirements, and the output is the proposed travel plan.

[0167] Step 5:

[0168] The server adjusts the suggested travel plan through an optimization process to create a plan that best matches the user's wishes and emotions. It then selects and discards parts of the generated travel plan, prioritizing, for example, visits to places that promote relaxation. The input is the initial travel plan and user emotion data, and the output is the optimized travel plan.

[0169] Step 6:

[0170] The device receives an optimized travel plan from the server and provides it to the user. The user can review this provided plan and make adjustments or changes through an interactive UI. The input is the optimized travel plan, and the output is the final travel plan reviewed by the user.

[0171] (Application Example 2)

[0172] 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".

[0173] Traditional travel planning systems could generate travel plans based on user requests and conditions, but they struggled to provide optimized plans that took into account the user's emotional state. Furthermore, they were unable to respond to real-time emotional changes during travel, making it challenging to flexibly provide plans that truly met the user's needs.

[0174] 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.

[0175] In this invention, the server includes means for acquiring travel information entered by the user, means for analyzing the acquired travel information and identifying the user's emotional state, and means for generating a travel plan according to the acquired emotional information. This makes it possible to provide a flexible and personalized travel plan that is tailored to the user's emotional state.

[0176] "User-inputted travel information" refers to information provided by the user, such as travel requests, itinerary, budget, and destination.

[0177] "Means for analysis and identification of the user's emotional state" refers to methods and technologies for processing input data and detecting the user's emotions.

[0178] "Means for generating travel plans based on emotional information" refers to methods and technologies for constructing optimal travel plans based on the emotions of identified users.

[0179] "Means of optimizing and providing users with optimized travel plans" refers to methods and technologies that adjust generated travel plans to suit the user's wishes and circumstances, and present them in a more appropriate format.

[0180] "A means of dynamically suggesting appropriate information based on user sentiment data regarding travel plans" refers to methods and technologies that recommend optimal tourist destinations and activities in real time according to the user's sentiment data.

[0181] "Acquiring information from external sources and incorporating it into the generated travel plan" means taking the latest travel-related information from external databases and services and integrating it into the travel plan.

[0182] "The ability to fine-tune based on emotional data" means that travel plans can be re-evaluated and modified as needed in response to changes in the user's emotional state.

[0183] The system that implements this application provides travel plans based on the user's emotional state. A specific embodiment is shown below.

[0184] The server retrieves travel information entered by the user using a terminal. This travel information includes details such as itinerary, budget, destination, and desired activities. User voice input is also possible, and this voice data is converted to text using speech recognition technology such as SpeechRecognition. The sentiment engine analyzes the converted text and directly entered text data. This analysis uses NLP libraries such as spaCy and machine learning frameworks such as TensorFlow. In this way, the user's emotional state is identified.

[0185] Based on the identified emotional state, the server generates a travel plan. For example, if the emotion engine determines that the user is seeking relaxation, the server creates a plan that considers relaxing places such as natural tourist attractions and spas. The created plan is further optimized by using a tourism information API (e.g., TriPad® visor API) to obtain the latest tourism information from external sources.

[0186] Users can review the travel plan provided through their device and make adjustments based on their emotional state as needed. This results in a personalized travel plan that takes both the user's emotions and desires into consideration.

[0187] As a concrete example, consider a scenario where a user voice-inputs, "I want to escape from my busy daily life." The emotion engine determines that the user is stressed and needs relaxation. Based on this information, the server generates and presents a travel plan that includes a quiet rural resort or spa. An example of a prompt in this case would be the instruction, "If the user needs relaxation, please suggest a quiet tourist destination nearby." In this way, a travel plan that meets the user's emotional needs is provided.

[0188] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0189] Step 1:

[0190] Users enter travel information using a terminal. This information includes itinerary, budget, desired destinations, and preferred activities. Voice input is also available, and the data is converted into text using speech recognition technology. The entered information is sent to the server.

[0191] Step 2:

[0192] The server analyzes the received text data and uses an emotion engine to identify the user's emotional state. Here, an NLP library (e.g., spaCy) is used to analyze phrasing, keywords, and tone of voice within the text. The input is text data, and the output is the user's emotional state (e.g., needs to relax, adventurous).

[0193] Step 3:

[0194] The server generates a travel plan based on the identified emotional state. For example, if it determines that the user is seeking relaxation, it prioritizes selecting tourist destinations and activities with relaxation effects. The input data is the emotional state, and the output is an initial travel plan. The generating AI model considers the latest tourist information and complements the plan.

[0195] Step 4:

[0196] The server retrieves the latest information from external sources (e.g., a tourism information API) and optimizes the generated travel plan. The input is the initial travel plan, and the output is an improved travel plan that reflects the latest information. Here, an API is used to retrieve opening hours and event information for tourist attractions and incorporate it into the travel plan.

[0197] Step 5:

[0198] The system provides users with optimized travel plans. Users can view the plans on their devices and adjust them according to their emotional state and preferences. The input is an optimized travel plan, and the output is the final plan after user adjustments. Users can further refine their plans by changing options or adding comments based on the suggested plan.

[0199] 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.

[0200] 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.

[0201] 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.

[0202] [Second Embodiment]

[0203] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0204] 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.

[0205] 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).

[0206] 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.

[0207] 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.

[0208] 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).

[0209] 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.

[0210] 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.

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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".

[0215] This invention, the AI ​​Family Travel Planner, is a system that provides a travel plan tailored to the user's preferences while reducing the user's burden. The embodiments of this system are described below.

[0216] Users access a dedicated interface via their device and input details such as their travel dates, budget, desired destinations, and the names of the participants. This information is sent to the system's underlying server. Upon receiving this data, the server uses an AI model to analyze it and generate an optimal travel plan tailored to the user's preferences.

[0217] The AI ​​model embedded in the server learns from past travel data and relevant external sources, allowing it to flexibly respond to different user requests. In this process, the server not only creates the most efficient schedule within a given timeframe but also performs real-time price comparisons to suggest the best options within the user's budget.

[0218] For example, if a user enters a request such as, "My family of four wants to take a 5-night, 6-day domestic trip during summer vacation. Our budget is 200,000 yen, and we want to enjoy nature in addition to famous tourist spots," the server will respond by selecting tourist destinations that can be visited within the budget and proposing a travel schedule for each day. For example, it might plan a trip to famous tourist spots in urban areas on the first day, and to enjoy nature in suburban areas on the second and third days, and also provide information on accommodations and transportation.

[0219] The terminal displays the plan generated by this server in detail. The user can review this plan and make fine adjustments on the terminal if necessary. In this way, the cumbersome tasks of travel planning are fully automated, and a trip tailored to the individual user's wishes is quickly planned.

[0220] The following describes the processing flow.

[0221] Step 1:

[0222] Users access a dedicated interface from their device and enter travel information such as travel dates, budget, desired destinations, and participant information. This information forms the basis of the travel plan, so it is required to be entered in as much detail as possible.

[0223] Step 2:

[0224] The terminal sends the information entered by the user to the server as data packets. At this time, the input data is structured and formatted to facilitate analysis by the server.

[0225] Step 3:

[0226] The server sends the received travel information to an analysis engine, which generates a travel plan that takes the user's preferences into account. This analysis considers factors such as weather at the destination, event information, transportation options, and accommodation availability to create the optimal schedule.

[0227] Step 4:

[0228] The server accesses external information sources to obtain the latest tourist attraction and pricing information and integrates it into the travel plan. This process is performed in real time based on the user's preferences and aims to improve the accuracy of the plan.

[0229] Step 5:

[0230] The server optimizes accommodations and transportation to ensure maximum satisfaction within the budget. Here, the most suitable plan is calculated based on AI-driven budget allocation and the user's preferences.

[0231] Step 6:

[0232] The generated travel plan is sent from the server to the terminal and displayed to the user in a visually easy-to-understand format. This includes the schedule for each day, information on destinations, and details of transportation.

[0233] Step 7:

[0234] Users can review the provided travel plan through their device and make adjustments as needed. For example, they can add specific tourist destinations or change the order of visit dates.

[0235] (Example 1)

[0236] 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."

[0237] The challenge lies in reducing the cumbersome tasks users face when planning a trip, while simultaneously generating optimal travel plans tailored to various conditions. In particular, sophisticated planning that responds immediately to individual conditions such as travel dates and budgets, and reflects real-time information, is required.

[0238] 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.

[0239] In this invention, the server includes means for acquiring travel information, including itinerary information and budget information, obtained through a device operated by the user; means for analyzing the acquired travel information and generating a travel plan through an information processing model using past travel data; and means for optimizing the generated travel plan using the latest information, including price information, by linking with an external information source. This makes it possible to efficiently create and present an optimal travel plan that suits the user's conditions.

[0240] A "user-operated device" is an electronic device used by a user to input information and transmit it to a server through an interface.

[0241] "Itinerary information" refers to information about the start and end dates and specific times of a trip, and forms the basis of a travel plan.

[0242] "Budget information" refers to information about the maximum amount of money set for travel expenses, and an appropriate travel plan is created based on this information.

[0243] "Travel information" refers to comprehensive data that includes details related to a trip, such as the itinerary, budget, destinations, and participants.

[0244] An "information processing model" refers to an algorithm that learns from past data and generates an optimal travel plan tailored to the user's needs.

[0245] "External information sources" refer to external data providers that offer information necessary for travel planning, such as real-time prices and booking status.

[0246] "Optimization" is the process of creating the most efficient and effective travel plan, taking into account available resources and conditions.

[0247] "Travel plan" refers to a detailed plan of the trip, including the schedule, destinations, means of transportation, and accommodations, which is created based on the information entered by the user.

[0248] The following system configuration is considered as an embodiment of this invention. When planning a trip, the user accesses a dedicated interface from an internet-connected terminal and inputs detailed information such as the trip itinerary, budget, places to visit, and participants. The terminal transmits this information to the server via the HTTPS protocol.

[0249] The server activates an internal AI model based on the received travel information, and uses historical travel data and real-time pricing information from external sources to generate an optimal travel plan tailored to the user's needs. In this process, the server performs various data analyses to efficiently schedule the trip within the specified travel period and develop a plan that provides the greatest value within the budget.

[0250] As a concrete example, consider a scenario where a user inputs a prompt such as, "My family of four wants to take a 5-night, 6-day domestic trip during summer vacation. Our budget is 200,000 yen, and we want to enjoy nature in addition to famous tourist spots." Based on the conditions received from the user, the server uses artificial intelligence to automatically select suitable tourist destinations and proposes a specific schedule for each day of the trip. For example, it might create a plan to visit famous tourist spots in urban areas on the first day, and then visit suburban areas where nature can be enjoyed on the second and third days, and also provide detailed information on accommodations and transportation.

[0251] The generated travel plan is displayed on the device, allowing the user to review and make adjustments as needed. Once adjustments are complete on the device, the final travel plan is sent back to the server for storage. This allows the user to review the plan before their trip and smoothly prepare for departure.

[0252] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0253] Step 1:

[0254] The user enters detailed travel plan information into the device. Specifically, they input travel dates, budget, destination, and participant information into a dedicated interface. This information is stored on the device as input data to create a travel plan that reflects the user's preferences.

[0255] Step 2:

[0256] The device sends saved travel information to the server via HTTPS. Input data includes user-specified itinerary information, budget information, and desired destinations, and this data is securely transmitted to the server.

[0257] Step 3:

[0258] The server activates a generation AI model based on the received data. The process involves analyzing the user's input data and automatically generating a travel plan that matches the user's preferences, while obtaining real-time information from past travel databases and external sources. This outputs a proposed itinerary, destinations, and accommodation options as part of the travel plan.

[0259] Step 4:

[0260] The server optimizes the generated travel plan. Specifically, it collaborates with external sources to obtain the latest pricing and booking information and incorporates it into the travel plan. This process makes it possible to present the best options within the user's budget.

[0261] Step 5:

[0262] The generated plan is sent from the server to the device. The device displays this optimized travel plan in detail to the user. The user reviews the displayed plan and makes adjustments to the itinerary and destinations as needed.

[0263] Step 6:

[0264] Once the user has finalized their plan, that information is sent from their device to the server, and the final travel plan is confirmed. The server saves this travel plan in a database so that it can be reviewed and modified later. At this stage, all steps are complete.

[0265] (Application Example 1)

[0266] 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."

[0267] Traditional travel planning systems required users to manually input detailed information and manually review and adjust their plans, resulting in a heavy user burden and a time-consuming planning process. Furthermore, interactive travel planning adjustments using household electronic devices were not considered, making it difficult to respond quickly to user situations and preferences.

[0268] 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.

[0269] In this invention, the server includes means for acquiring travel information entered by the user, means for analyzing the acquired travel information and generating a travel plan based on the user's requests, means for optimizing the generated travel plan and providing the optimized travel plan to the user, means for recognizing the user's voice input and outputting information related to the travel plan based on the recognition results, and means for interacting with the user through a home appliance and performing adjustments to the travel plan in real time. This enables the user to intuitively and quickly plan and adjust their travel plan via voice.

[0270] A "user" is an individual or legal entity that uses the system to plan or adjust travel plans.

[0271] "Travel information" refers to data such as the itinerary, budget, desired destinations, and detailed information about the participants.

[0272] "Means of acquisition" means a method or device for accurately receiving and recording information provided by the user.

[0273] "Means for analysis and generation" refers to a method or apparatus for analyzing acquired data to create a travel plan that meets the user's preferences.

[0274] "Means of optimization and delivery" refers to a method or device that adjusts a generated travel plan to best match the user's conditions and informs the user of that plan.

[0275] "Means for recognizing voice input" means a method or device that analyzes the user's voice, converts it into text data, and makes it available for processing within the system.

[0276] "Household machinery and equipment" refers to mechanical or electronic devices used within the home that enable interaction with the user.

[0277] "Means for dialogue and adjustment" refers to methods or devices for changing or updating travel plans through communication with users.

[0278] A system implementing this invention acquires travel information entered by the user via voice or a terminal, automatically creates a travel plan using a generated AI model based on that information, and provides it to the user interactively through a home appliance.

[0279] The system first collects the user's voice input using a home device and converts it into text data using speech recognition software (e.g., Google Cloud Speech-to-Text). This converted data is sent to a server, where it is analyzed using a machine learning library (e.g., TensorFlow). The server then generates a travel plan based on the analysis results. In doing so, it uses external APIs (e.g., Google Maps API) to obtain the latest tourist information and weather information and incorporates it into the plan.

[0280] Furthermore, the generated travel plan is optimized using an algorithm to suit the user's budget and preferences, and is provided to the user via voice and screen display through a home device. The user can review this plan and, if necessary, instruct the home device to change the plan in real time. This instruction is also received by voice, analyzed again on the server, and an updated plan is provided.

[0281] For example, if a user uses voice input to say, "I'm planning a 3-night, 4-day family trip next weekend. My budget is 250,000 yen, and I'd like to visit historical sites and natural attractions," the server will analyze this and suggest appropriate destinations. For instance, it might suggest a schedule such as visiting historical sites on day 1 and natural attractions on day 2.

[0282] Examples of prompt texts for generating an AI model include "We are a family of four planning a weekend trip. The budget is 200,000 yen, and we want to do some sightseeing with a good balance between the city and the countryside. Please make a schedule."

[0283] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0284] Step 1:

[0285] The user inputs travel information using voice or a terminal. At this time, the user provides details such as the travel schedule, budget, and desired destinations. The input information is converted into text data through a speech recognition system.

[0286] Step 2:

[0287] The terminal sends the converted text data to the server. The server receives this data and performs analysis using a machine learning library. Specifically, the server analyzes the user's requests and performs data processing to generate a travel plan based on this.

[0288] Step 3:

[0289] [[ID=2,8]]The server uses the generative AI model to create a travel plan that meets the user's needs. Based on the results of the input data analysis, relevant tourist attractions and accommodation facilities are selected, and a specific schedule proposal is created.

[0290] Step 4:

[0291] The server uses an external information source (e.g., API) to obtain data on the latest tourist attraction information, weather, and transportation means. The obtained external data is reflected in the travel plan and adjusted to fit the schedule and budget.

[0292] Step 5:

[0293] The generated travel plan is optimized by the server. Based on the user's conditions, budget, and preferences, an optimization algorithm is applied to create the most efficient and satisfying plan.

[0294] Step 6:

[0295] The device provides the user with an optimized travel plan. Details of the travel plan are displayed via voice and on the screen through the home electronic device. The user can visually and audibly review the plan's overview.

[0296] Step 7:

[0297] If a user wishes to change or adjust their plan, they can provide instructions in real time via their device. The device then sends these instructions back to the server, which recalculates and adjusts the travel plan based on the instructions and provides the user with an updated plan.

[0298] 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.

[0299] This invention aims to build a system that provides travel plans that take user emotions into consideration. By incorporating an emotion engine, the system recognizes the user's emotional state and optimizes the travel plan based on that state.

[0300] Users use their devices to input detailed travel information. This includes not only dates, budgets, and places they want to visit, but also the ability to express their wishes and preferences through voice. The device sends the collected data to a server. During this process, the voice and text data are analyzed by an emotion engine to detect and evaluate the user's current emotions. The emotion engine determines emotions through text phrasing, tone of voice, and even quick questionnaire-style interactions.

[0301] Based on the emotional data, the server analyzes the emotional state of the user, such as whether the user is seeking relaxation or adventure, and generates a corresponding travel plan. Parallel to the normal travel plan generation process, emotion-responsive planning proceeds. For example, if the emotion engine recognizes that the user is feeling stressed, the server will preferentially propose tourist spots and activities with a high relaxation effect (such as visiting a hot spring resort or choosing a hotel with a massage).

[0302] As a specific example, if the user makes a voice input of "want to be liberated from a busy life" and the emotion engine detects the need for relaxation, the server will create a travel plan based on this result, including an accommodation plan in a quiet natural environment. This plan mainly incorporates quiet resorts and spas in the countryside rather than tourist spots in the city, taking into account that the user can refresh both physically and mentally.

[0303] Finally, the terminal provides these optimized travel plans to the user, and the user can check the details and make adjustments if necessary. With this system, a more personalized travel plan that also takes into account the user's emotional needs becomes possible.

[0304] The following explains the processing flow.

[0305] Step 1:

[0306] The user inputs the hopes and conditions for a travel plan through the terminal. At this time, in addition to text input, the voice input function of the terminal can be used to convey the emotional elements that the user hopes and expects (e.g., want to relax, want to have an adventure). The terminal packages these data and sends them to the server.

[0307] Step 2:

[0308] The server analyzes the received data and activates the emotion engine. The emotion engine uses natural language processing and speech analysis techniques to evaluate the user's emotions in order to generate emotion indicators from the user's written and spoken content. It detects and classifies emotional states such as positive, negative, and neutral.

[0309] Step 3:

[0310] In generating travel plans, the server considers emotional indicators obtained from the emotion engine. For example, if a user indicates stress, the server prioritizes suggesting tourist destinations and activities that include many relaxing elements. Conversely, if a user indicates enthusiasm, it creates a plan that includes adventurous tours and activities that offer new experiences.

[0311] Step 4:

[0312] By utilizing external information sources, the system obtains real-time, up-to-date information on tourist destinations, events, and accommodation availability. The server integrates this information to create an optimal plan that matches the user's emotional state.

[0313] Step 5:

[0314] The server sends the completed travel plan to the terminal, making it accessible to the user. The travel plan clearly displays options and recommendations tailored to the user's preferences.

[0315] Step 6:

[0316] Users can review the travel plan provided on their device and adjust details as needed. Feedback from the emotion engine provides additional information to determine if the user is satisfied with the plan, and further adjustments can be made based on their response.

[0317] (Example 2)

[0318] 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".

[0319] Traditional travel planning systems typically provide plans based on the user's explicit requests. However, these systems often fail to consider the user's emotional state, making it difficult to provide a truly personalized experience. Specifically, if a user is experiencing stress, they may not receive suggestions tailored to their emotions, potentially resulting in a less-than-satisfactory travel experience.

[0320] 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.

[0321] In this invention, the server includes a computing device for performing emotion analysis, means for generating a travel plan based on the user's emotions, means for identifying travel destinations and activities that promote relaxation according to the emotional state, and means for optimizing the generated travel plan and providing it to the user. This makes it possible to provide a more personalized travel plan that takes the user's emotional state into consideration.

[0322] A "user" is an individual or group that provides and receives travel planning information from the system.

[0323] "Travel information" refers to specific travel data provided by the user, such as itinerary, budget, and desired destinations.

[0324] "Emotional state" refers to a user's inner feelings and psychological tendencies, and is an element that is reflected in their travel plan.

[0325] "Emotion analysis" is a technical process that processes a user's voice and text data to determine their emotional state.

[0326] A "travel plan" is a specific itinerary for carrying out a trip, generated based on the user's requests and emotional state.

[0327] A "computational unit" is a device within a system consisting of a computer that performs emotion analysis and determines the user's emotional state.

[0328] "Optimization" is the process of adjusting the generated travel plan according to the user's emotional state and requests, enabling the best possible suggestions.

[0329] "Travel destinations and activities that promote relaxation" refer to travel destinations or activities aimed at reducing user stress and enhancing their refreshing effect.

[0330] This invention is a system that provides travel plans that take into account the user's emotional state, and is realized through the coordinated operation of the user, terminal, and server.

[0331] First, the user enters travel-related information into the device. This includes specific details such as the travel itinerary, budget, and places they want to visit. In addition, through voice input, the user can express their wishes and preferences in a natural way.

[0332] The device transmits the collected information to the server. This data includes text and audio data, and encryption technology is used during the transmission process to ensure data security. After the data is transmitted, the server receives it and uses a computing device for sentiment analysis to determine the user's emotional state. This analysis uses natural language processing technology and speech analysis algorithms to precisely evaluate the user's voice tone and word choice.

[0333] Based on the results of the emotion analysis, the server uses a generative AI model to generate a travel plan that matches the user's emotions. The generated plan may include destinations and activities that promote relaxation for the user. For example, if a user voice-inputs "I want to escape from my busy life," and the emotion analysis determines that relaxation is needed, the server can offer a lodging plan at a quiet resort away from the city.

[0334] Ultimately, the device presents the user with an optimized travel plan generated by the server. The user can review this plan and make adjustments as needed. This system enables the provision of a more personalized travel experience that also takes the user's emotional state into account.

[0335] A concrete example of a prompt to input into a generative AI model is, "Suggest a relaxing travel plan based on an analysis of the user's emotions." Using this prompt, the generative AI model will make the most suitable suggestion from a number of options.

[0336] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0337] Step 1:

[0338] Users input detailed information such as travel dates, budget, and desired destinations through their devices. Furthermore, they can use voice input to naturally express their preferences and desires. This input data is standardized across devices and prepared as a data stream. The input includes both text and voice data, resulting in data ready for transmission to the server as output.

[0339] Step 2:

[0340] The terminal sends standardized data to the server. During transmission, an encryption process is performed to ensure data security. In this process, data is transmitted to the server via encrypted communication and stored as output in a temporary storage area on the server.

[0341] Step 3:

[0342] The server passes the received data to a computing unit for sentiment analysis. Using a sentiment engine, natural language processing techniques and speech analysis algorithms are applied. The input consists of speech and text data stored on the server, and the user's emotional state is analyzed through this data processing. The output is numerical data or categorical information indicating the emotional state.

[0343] Step 4:

[0344] The server uses a generative AI model to generate a travel plan that aligns with the user's emotions, based on the results of the emotion analysis. By inputting the prompt "Suggest a relaxing travel plan based on the user's emotion analysis" to the generative AI model, the server will generate suggestions for optimal travel destinations and activities. The input consists of the emotion analysis results and the user's travel requirements, and the output is the proposed travel plan.

[0345] Step 5:

[0346] The server adjusts the suggested travel plan through an optimization process to create a plan that best matches the user's wishes and emotions. It then selects and discards parts of the generated travel plan, prioritizing, for example, visits to places that promote relaxation. The input is the initial travel plan and user emotion data, and the output is the optimized travel plan.

[0347] Step 6:

[0348] The device receives an optimized travel plan from the server and provides it to the user. The user can review this provided plan and make adjustments or changes through an interactive UI. The input is the optimized travel plan, and the output is the final travel plan reviewed by the user.

[0349] (Application Example 2)

[0350] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0351] Traditional travel planning systems could generate travel plans based on user requests and conditions, but they struggled to provide optimized plans that took into account the user's emotional state. Furthermore, they were unable to respond to real-time emotional changes during travel, making it challenging to flexibly provide plans that truly met the user's needs.

[0352] 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.

[0353] In this invention, the server includes means for acquiring travel information entered by the user, means for analyzing the acquired travel information and identifying the user's emotional state, and means for generating a travel plan according to the acquired emotional information. This makes it possible to provide a flexible and personalized travel plan that is tailored to the user's emotional state.

[0354] "User-inputted travel information" refers to information provided by the user, such as travel requests, itinerary, budget, and destination.

[0355] "Means for analysis and identification of the user's emotional state" refers to methods and technologies for processing input data and detecting the user's emotions.

[0356] "Means for generating travel plans based on emotional information" refers to methods and technologies for constructing optimal travel plans based on the emotions of identified users.

[0357] "Means of optimizing and providing users with optimized travel plans" refers to methods and technologies that adjust generated travel plans to suit the user's wishes and circumstances, and present them in a more appropriate format.

[0358] "A means of dynamically suggesting appropriate information based on user sentiment data regarding travel plans" refers to methods and technologies that recommend optimal tourist destinations and activities in real time according to the user's sentiment data.

[0359] "Acquiring information from external sources and incorporating it into the generated travel plan" means taking the latest travel-related information from external databases and services and integrating it into the travel plan.

[0360] "The ability to fine-tune based on emotional data" means that travel plans can be re-evaluated and modified as needed in response to changes in the user's emotional state.

[0361] The system that implements this application provides travel plans based on the user's emotional state. A specific embodiment is shown below.

[0362] The server retrieves travel information entered by the user using a terminal. This travel information includes details such as itinerary, budget, destination, and desired activities. User voice input is also possible, and this voice data is converted to text using speech recognition technology such as SpeechRecognition. The sentiment engine analyzes the converted text and directly entered text data. This analysis uses NLP libraries such as spaCy and machine learning frameworks such as TensorFlow. In this way, the user's emotional state is identified.

[0363] Based on the identified emotional state, the server generates a travel plan. For example, if the emotion engine determines that the user is seeking relaxation, the server will create a plan that considers relaxing places such as natural tourist attractions and spas. The created plan is further optimized by using a travel information API (e.g., TripAdvisor API) to obtain the latest travel information from external sources.

[0364] Users can review the travel plan provided through their device and make adjustments based on their emotional state as needed. This results in a personalized travel plan that takes both the user's emotions and desires into consideration.

[0365] As a concrete example, consider a scenario where a user voice-inputs, "I want to escape from my busy daily life." The emotion engine determines that the user is stressed and needs relaxation. Based on this information, the server generates and presents a travel plan that includes a quiet rural resort or spa. An example of a prompt in this case would be the instruction, "If the user needs relaxation, please suggest a quiet tourist destination nearby." In this way, a travel plan that meets the user's emotional needs is provided.

[0366] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0367] Step 1:

[0368] Users enter travel information using a terminal. This information includes itinerary, budget, desired destinations, and preferred activities. Voice input is also available, and the data is converted into text using speech recognition technology. The entered information is sent to the server.

[0369] Step 2:

[0370] The server analyzes the received text data and uses an emotion engine to identify the user's emotional state. Here, an NLP library (e.g., spaCy) is used to analyze phrasing, keywords, and tone of voice within the text. The input is text data, and the output is the user's emotional state (e.g., needs to relax, adventurous).

[0371] Step 3:

[0372] The server generates a travel plan based on the identified emotional state. For example, if it determines that the user is seeking relaxation, it prioritizes selecting tourist destinations and activities with relaxation effects. The input data is the emotional state, and the output is an initial travel plan. The generating AI model considers the latest tourist information and complements the plan.

[0373] Step 4:

[0374] The server retrieves the latest information from external sources (e.g., a tourism information API) and optimizes the generated travel plan. The input is the initial travel plan, and the output is an improved travel plan that reflects the latest information. Here, an API is used to retrieve opening hours and event information for tourist attractions and incorporate it into the travel plan.

[0375] Step 5:

[0376] The system provides users with optimized travel plans. Users can view the plans on their devices and adjust them according to their emotional state and preferences. The input is an optimized travel plan, and the output is the final plan after user adjustments. Users can further refine their plans by changing options or adding comments based on the suggested plan.

[0377] 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.

[0378] 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.

[0379] 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.

[0380] [Third Embodiment]

[0381] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0382] 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.

[0383] 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).

[0384] 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.

[0385] 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.

[0386] 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).

[0387] 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.

[0388] 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.

[0389] 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.

[0390] 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.

[0391] 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.

[0392] 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".

[0393] This invention, the AI ​​Family Travel Planner, is a system that provides a travel plan tailored to the user's preferences while reducing the user's burden. The embodiments of this system are described below.

[0394] Users access a dedicated interface via their device and input details such as their travel dates, budget, desired destinations, and the names of the participants. This information is sent to the system's underlying server. Upon receiving this data, the server uses an AI model to analyze it and generate an optimal travel plan tailored to the user's preferences.

[0395] The AI ​​model embedded in the server learns from past travel data and relevant external sources, allowing it to flexibly respond to different user requests. In this process, the server not only creates the most efficient schedule within a given timeframe but also performs real-time price comparisons to suggest the best options within the user's budget.

[0396] For example, if a user enters a request such as, "My family of four wants to take a 5-night, 6-day domestic trip during summer vacation. Our budget is 200,000 yen, and we want to enjoy nature in addition to famous tourist spots," the server will respond by selecting tourist destinations that can be visited within the budget and proposing a travel schedule for each day. For example, it might plan a trip to famous tourist spots in urban areas on the first day, and to enjoy nature in suburban areas on the second and third days, and also provide information on accommodations and transportation.

[0397] The terminal displays the plan generated by this server in detail. The user can review this plan and make fine adjustments on the terminal if necessary. In this way, the cumbersome tasks of travel planning are fully automated, and a trip tailored to the individual user's wishes is quickly planned.

[0398] The following describes the processing flow.

[0399] Step 1:

[0400] Users access a dedicated interface from their device and enter travel information such as travel dates, budget, desired destinations, and participant information. This information forms the basis of the travel plan, so it is required to be entered in as much detail as possible.

[0401] Step 2:

[0402] The terminal sends the information entered by the user to the server as data packets. At this time, the input data is structured and formatted to facilitate analysis by the server.

[0403] Step 3:

[0404] The server sends the received travel information to an analysis engine, which generates a travel plan that takes the user's preferences into account. This analysis considers factors such as weather at the destination, event information, transportation options, and accommodation availability to create the optimal schedule.

[0405] Step 4:

[0406] The server accesses external information sources to obtain the latest tourist attraction and pricing information and integrates it into the travel plan. This process is performed in real time based on the user's preferences and aims to improve the accuracy of the plan.

[0407] Step 5:

[0408] The server optimizes accommodations and transportation to ensure maximum satisfaction within the budget. Here, the most suitable plan is calculated based on AI-driven budget allocation and the user's preferences.

[0409] Step 6:

[0410] The generated travel plan is sent from the server to the terminal and displayed to the user in a visually easy-to-understand format. This includes the schedule for each day, information on destinations, and details of transportation.

[0411] Step 7:

[0412] Users can review the provided travel plan through their device and make adjustments as needed. For example, they can add specific tourist destinations or change the order of visit dates.

[0413] (Example 1)

[0414] 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."

[0415] The challenge lies in reducing the cumbersome tasks users face when planning a trip, while simultaneously generating optimal travel plans tailored to various conditions. In particular, sophisticated planning that responds immediately to individual conditions such as travel dates and budgets, and reflects real-time information, is required.

[0416] 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.

[0417] In this invention, the server includes means for acquiring travel information, including itinerary information and budget information, obtained through a device operated by the user; means for analyzing the acquired travel information and generating a travel plan through an information processing model using past travel data; and means for optimizing the generated travel plan using the latest information, including price information, by linking with an external information source. This makes it possible to efficiently create and present an optimal travel plan that suits the user's conditions.

[0418] A "user-operated device" is an electronic device used by a user to input information and transmit it to a server through an interface.

[0419] "Itinerary information" refers to information about the start and end dates and specific times of a trip, and forms the basis of a travel plan.

[0420] "Budget information" refers to information about the maximum amount of money set for travel expenses, and an appropriate travel plan is created based on this information.

[0421] "Travel information" refers to comprehensive data that includes details related to a trip, such as the itinerary, budget, destinations, and participants.

[0422] An "information processing model" refers to an algorithm that learns from past data and generates an optimal travel plan tailored to the user's needs.

[0423] "External information sources" refer to external data providers that offer information necessary for travel planning, such as real-time prices and booking status.

[0424] "Optimization" is the process of creating the most efficient and effective travel plan, taking into account available resources and conditions.

[0425] "Travel plan" refers to a detailed plan of the trip, including the schedule, destinations, means of transportation, and accommodations, which is created based on the information entered by the user.

[0426] The following system configuration is considered as an embodiment of this invention. When planning a trip, the user accesses a dedicated interface from an internet-connected terminal and inputs detailed information such as the trip itinerary, budget, places to visit, and participants. The terminal transmits this information to the server via the HTTPS protocol.

[0427] The server activates an internal AI model based on the received travel information, and uses historical travel data and real-time pricing information from external sources to generate an optimal travel plan tailored to the user's needs. In this process, the server performs various data analyses to efficiently schedule the trip within the specified travel period and develop a plan that provides the greatest value within the budget.

[0428] As a concrete example, consider a scenario where a user inputs a prompt such as, "My family of four wants to take a 5-night, 6-day domestic trip during summer vacation. Our budget is 200,000 yen, and we want to enjoy nature in addition to famous tourist spots." Based on the conditions received from the user, the server uses artificial intelligence to automatically select suitable tourist destinations and proposes a specific schedule for each day of the trip. For example, it might create a plan to visit famous tourist spots in urban areas on the first day, and then visit suburban areas where nature can be enjoyed on the second and third days, and also provide detailed information on accommodations and transportation.

[0429] The generated travel plan is displayed on the device, allowing the user to review and make adjustments as needed. Once adjustments are complete on the device, the final travel plan is sent back to the server for storage. This allows the user to review the plan before their trip and smoothly prepare for departure.

[0430] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0431] Step 1:

[0432] The user enters detailed travel plan information into the device. Specifically, they input travel dates, budget, destination, and participant information into a dedicated interface. This information is stored on the device as input data to create a travel plan that reflects the user's preferences.

[0433] Step 2:

[0434] The device sends saved travel information to the server via HTTPS. Input data includes user-specified itinerary information, budget information, and desired destinations, and this data is securely transmitted to the server.

[0435] Step 3:

[0436] The server activates a generation AI model based on the received data. The process involves analyzing the user's input data and automatically generating a travel plan that matches the user's preferences, while obtaining real-time information from past travel databases and external sources. This outputs a proposed itinerary, destinations, and accommodation options as part of the travel plan.

[0437] Step 4:

[0438] The server optimizes the generated travel plan. Specifically, it collaborates with external sources to obtain the latest pricing and booking information and incorporates it into the travel plan. This process makes it possible to present the best options within the user's budget.

[0439] Step 5:

[0440] The generated plan is sent from the server to the device. The device displays this optimized travel plan in detail to the user. The user reviews the displayed plan and makes adjustments to the itinerary and destinations as needed.

[0441] Step 6:

[0442] Once the user has finalized their plan, that information is sent from their device to the server, and the final travel plan is confirmed. The server saves this travel plan in a database so that it can be reviewed and modified later. At this stage, all steps are complete.

[0443] (Application Example 1)

[0444] 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."

[0445] Traditional travel planning systems required users to manually input detailed information and manually review and adjust their plans, resulting in a heavy user burden and a time-consuming planning process. Furthermore, interactive travel planning adjustments using household electronic devices were not considered, making it difficult to respond quickly to user situations and preferences.

[0446] 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.

[0447] In this invention, the server includes means for acquiring travel information entered by the user, means for analyzing the acquired travel information and generating a travel plan based on the user's requests, means for optimizing the generated travel plan and providing the optimized travel plan to the user, means for recognizing the user's voice input and outputting information related to the travel plan based on the recognition results, and means for interacting with the user through a home appliance and performing adjustments to the travel plan in real time. This enables the user to intuitively and quickly plan and adjust their travel plan via voice.

[0448] A "user" is an individual or legal entity that uses the system to plan or adjust travel plans.

[0449] "Travel information" refers to data such as the itinerary, budget, desired destinations, and detailed information about the participants.

[0450] "Means of acquisition" means a method or device for accurately receiving and recording information provided by the user.

[0451] "Means for analysis and generation" refers to a method or apparatus for analyzing acquired data to create a travel plan that meets the user's preferences.

[0452] "Means of optimization and delivery" refers to a method or device that adjusts a generated travel plan to best match the user's conditions and informs the user of that plan.

[0453] "Means for recognizing voice input" means a method or device that analyzes the user's voice, converts it into text data, and makes it available for processing within the system.

[0454] "Household machinery and equipment" refers to mechanical or electronic devices used within the home that enable interaction with the user.

[0455] "Means for dialogue and adjustment" refers to methods or devices for changing or updating travel plans through communication with users.

[0456] A system implementing this invention acquires travel information entered by the user via voice or a terminal, automatically creates a travel plan using a generated AI model based on that information, and provides it to the user interactively through a home appliance.

[0457] The system first collects the user's voice input using a home device and converts it into text data using speech recognition software (e.g., Google Cloud Speech-to-Text). This converted data is sent to a server, where it is analyzed using a machine learning library (e.g., TensorFlow). The server then generates a travel plan based on the analysis results. In doing so, it uses external APIs (e.g., Google Maps API) to obtain the latest tourist information and weather information and incorporates it into the plan.

[0458] Furthermore, the generated travel plan is optimized using an algorithm to suit the user's budget and preferences, and is provided to the user via voice and screen display through a home device. The user can review this plan and, if necessary, instruct the home device to change the plan in real time. This instruction is also received by voice, analyzed again on the server, and an updated plan is provided.

[0459] For example, if a user uses voice input to say, "I'm planning a 3-night, 4-day family trip next weekend. My budget is 250,000 yen, and I'd like to visit historical sites and natural attractions," the server will analyze this and suggest appropriate destinations. For instance, it might suggest a schedule such as visiting historical sites on day 1 and natural attractions on day 2.

[0460] An example of a prompt message for a generative AI model would be: "My family of four is planning a weekend trip. Our budget is 200,000 yen, and we want a good balance of sightseeing in urban and rural areas. Please create a schedule for us."

[0461] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0462] Step 1:

[0463] Users input travel information using voice or a device. During this process, users provide details such as their travel itinerary, budget, and desired destinations. The entered information is then converted into text data through a voice recognition system.

[0464] Step 2:

[0465] The terminal sends the converted text data to the server. The server receives this data and performs analysis using a machine learning library. Specifically, it analyzes the user's requests and processes the data to generate a travel plan based on them.

[0466] Step 3:

[0467] The server uses a generative AI model to create travel plans that meet the user's requests. Based on the results of the input data analysis, it selects relevant tourist destinations and accommodations and creates a specific itinerary.

[0468] Step 4:

[0469] The server uses external information sources (e.g., APIs) to retrieve the latest information on tourist destinations, weather, and transportation. This retrieved external data is then incorporated into the travel plan and adjusted to fit the itinerary and budget.

[0470] Step 5:

[0471] The generated travel plan is optimized by the server. Based on the user's conditions, budget, and preferences, an optimization algorithm is applied to create the most efficient and satisfying plan.

[0472] Step 6:

[0473] The device provides the user with an optimized travel plan. Details of the travel plan are displayed via voice and on the screen through the home electronic device. The user can visually and audibly review the plan's overview.

[0474] Step 7:

[0475] If a user wishes to change or adjust their plan, they can provide instructions in real time via their device. The device then sends these instructions back to the server, which recalculates and adjusts the travel plan based on the instructions and provides the user with an updated plan.

[0476] 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.

[0477] This invention aims to build a system that provides travel plans that take user emotions into consideration. By incorporating an emotion engine, the system recognizes the user's emotional state and optimizes the travel plan based on that state.

[0478] Users use their devices to input detailed travel information. This includes not only dates, budgets, and places they want to visit, but also the ability to express their wishes and preferences through voice. The device sends the collected data to a server. During this process, the voice and text data are analyzed by an emotion engine to detect and evaluate the user's current emotions. The emotion engine determines emotions through text phrasing, tone of voice, and even quick questionnaire-style interactions.

[0479] Based on emotional data, the server analyzes the user's emotional state, such as whether they are seeking relaxation or adventure, and generates a travel plan accordingly. Emotion-responsive planning proceeds in parallel with the normal travel plan generation process. For example, if the emotion engine detects that the user is feeling stressed, the server will prioritize suggesting tourist spots and activities that are likely to have a relaxing effect (such as visiting a hot spring resort or choosing a hotel with massage services).

[0480] For example, if a user voice-inputs "I want to be freed from my busy life," and the emotion engine detects the need for relaxation, the server will use that information to create a travel plan that includes accommodation in a quiet natural environment. This plan will primarily feature quiet resorts and spas in the countryside rather than urban tourist spots, ensuring that the user can refresh both their mind and body.

[0481] Ultimately, the device provides the user with these optimized travel plans, allowing them to review the details and make adjustments as needed. This system enables more personalized travel planning that also takes the user's emotional needs into consideration.

[0482] The following describes the processing flow.

[0483] Step 1:

[0484] Users input their travel plans and preferences through their device. In addition to text input, they can use the device's voice input function to convey emotional elements of their wishes and expectations (e.g., wanting to relax, wanting adventure). The device packages this data and sends it to the server.

[0485] Step 2:

[0486] The server analyzes the received data and activates the emotion engine. The emotion engine uses natural language processing and speech analysis techniques to evaluate the user's emotions in order to generate emotion indicators from the user's written and spoken content. It detects and classifies emotional states such as positive, negative, and neutral.

[0487] Step 3:

[0488] In generating travel plans, the server considers emotional indicators obtained from the emotion engine. For example, if a user indicates stress, the server prioritizes suggesting tourist destinations and activities that include many relaxing elements. Conversely, if a user indicates enthusiasm, it creates a plan that includes adventurous tours and activities that offer new experiences.

[0489] Step 4:

[0490] By utilizing external information sources, the system obtains real-time, up-to-date information on tourist destinations, events, and accommodation availability. The server integrates this information to create an optimal plan that matches the user's emotional state.

[0491] Step 5:

[0492] The server sends the completed travel plan to the terminal, making it accessible to the user. The travel plan clearly displays options and recommendations tailored to the user's preferences.

[0493] Step 6:

[0494] Users can review the travel plan provided on their device and adjust details as needed. Feedback from the emotion engine provides additional information to determine if the user is satisfied with the plan, and further adjustments can be made based on their response.

[0495] (Example 2)

[0496] 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."

[0497] Traditional travel planning systems typically provide plans based on the user's explicit requests. However, these systems often fail to consider the user's emotional state, making it difficult to provide a truly personalized experience. Specifically, if a user is experiencing stress, they may not receive suggestions tailored to their emotions, potentially resulting in a less-than-satisfactory travel experience.

[0498] 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.

[0499] In this invention, the server includes a computing device for performing emotion analysis, means for generating a travel plan based on the user's emotions, means for identifying travel destinations and activities that promote relaxation according to the emotional state, and means for optimizing the generated travel plan and providing it to the user. This makes it possible to provide a more personalized travel plan that takes the user's emotional state into consideration.

[0500] A "user" is an individual or group that provides and receives travel planning information from the system.

[0501] "Travel information" refers to specific travel data provided by the user, such as itinerary, budget, and desired destinations.

[0502] "Emotional state" refers to a user's inner feelings and psychological tendencies, and is an element that is reflected in their travel plan.

[0503] "Emotion analysis" is a technical process that processes a user's voice and text data to determine their emotional state.

[0504] A "travel plan" is a specific itinerary for carrying out a trip, generated based on the user's requests and emotional state.

[0505] A "computational unit" is a device within a system consisting of a computer that performs emotion analysis and determines the user's emotional state.

[0506] "Optimization" is the process of adjusting the generated travel plan according to the user's emotional state and requests, enabling the best possible suggestions.

[0507] "Travel destinations and activities that promote relaxation" refer to travel destinations or activities aimed at reducing user stress and enhancing their refreshing effect.

[0508] This invention is a system that provides travel plans that take into account the user's emotional state, and is realized through the coordinated operation of the user, terminal, and server.

[0509] First, the user enters travel-related information into the device. This includes specific details such as the travel itinerary, budget, and places they want to visit. In addition, through voice input, the user can express their wishes and preferences in a natural way.

[0510] The device transmits the collected information to the server. This data includes text and audio data, and encryption technology is used during the transmission process to ensure data security. After the data is transmitted, the server receives it and uses a computing device for sentiment analysis to determine the user's emotional state. This analysis uses natural language processing technology and speech analysis algorithms to precisely evaluate the user's voice tone and word choice.

[0511] Based on the results of the emotion analysis, the server uses a generative AI model to generate a travel plan that matches the user's emotions. The generated plan may include destinations and activities that promote relaxation for the user. For example, if a user voice-inputs "I want to escape from my busy life," and the emotion analysis determines that relaxation is needed, the server can offer a lodging plan at a quiet resort away from the city.

[0512] Ultimately, the device presents the user with an optimized travel plan generated by the server. The user can review this plan and make adjustments as needed. This system enables the provision of a more personalized travel experience that also takes the user's emotional state into account.

[0513] A concrete example of a prompt to input into a generative AI model is, "Suggest a relaxing travel plan based on an analysis of the user's emotions." Using this prompt, the generative AI model will make the most suitable suggestion from a number of options.

[0514] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0515] Step 1:

[0516] Users input detailed information such as travel dates, budget, and desired destinations through their devices. Furthermore, they can use voice input to naturally express their preferences and desires. This input data is standardized across devices and prepared as a data stream. The input includes both text and voice data, resulting in data ready for transmission to the server as output.

[0517] Step 2:

[0518] The terminal sends standardized data to the server. During transmission, an encryption process is performed to ensure data security. In this process, data is transmitted to the server via encrypted communication and stored as output in a temporary storage area on the server.

[0519] Step 3:

[0520] The server passes the received data to a computing unit for sentiment analysis. Using a sentiment engine, natural language processing techniques and speech analysis algorithms are applied. The input consists of speech and text data stored on the server, and the user's emotional state is analyzed through this data processing. The output is numerical data or categorical information indicating the emotional state.

[0521] Step 4:

[0522] The server uses a generative AI model to generate a travel plan that aligns with the user's emotions, based on the results of the emotion analysis. By inputting the prompt "Suggest a relaxing travel plan based on the user's emotion analysis" to the generative AI model, the server will generate suggestions for optimal travel destinations and activities. The input consists of the emotion analysis results and the user's travel requirements, and the output is the proposed travel plan.

[0523] Step 5:

[0524] The server adjusts the suggested travel plan through an optimization process to create a plan that best matches the user's wishes and emotions. It then selects and discards parts of the generated travel plan, prioritizing, for example, visits to places that promote relaxation. The input is the initial travel plan and user emotion data, and the output is the optimized travel plan.

[0525] Step 6:

[0526] The device receives an optimized travel plan from the server and provides it to the user. The user can review this provided plan and make adjustments or changes through an interactive UI. The input is the optimized travel plan, and the output is the final travel plan reviewed by the user.

[0527] (Application Example 2)

[0528] 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."

[0529] Traditional travel planning systems could generate travel plans based on user requests and conditions, but they struggled to provide optimized plans that took into account the user's emotional state. Furthermore, they were unable to respond to real-time emotional changes during travel, making it challenging to flexibly provide plans that truly met the user's needs.

[0530] 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.

[0531] In this invention, the server includes means for acquiring travel information entered by the user, means for analyzing the acquired travel information and identifying the user's emotional state, and means for generating a travel plan according to the acquired emotional information. This makes it possible to provide a flexible and personalized travel plan that is tailored to the user's emotional state.

[0532] "User-inputted travel information" refers to information provided by the user, such as travel requests, itinerary, budget, and destination.

[0533] "Means for analysis and identification of the user's emotional state" refers to methods and technologies for processing input data and detecting the user's emotions.

[0534] "Means for generating travel plans based on emotional information" refers to methods and technologies for constructing optimal travel plans based on the emotions of identified users.

[0535] "Means of optimizing and providing users with optimized travel plans" refers to methods and technologies that adjust generated travel plans to suit the user's wishes and circumstances, and present them in a more appropriate format.

[0536] "A means of dynamically suggesting appropriate information based on user sentiment data regarding travel plans" refers to methods and technologies that recommend optimal tourist destinations and activities in real time according to the user's sentiment data.

[0537] "Acquiring information from external sources and incorporating it into the generated travel plan" means taking the latest travel-related information from external databases and services and integrating it into the travel plan.

[0538] "The ability to fine-tune based on emotional data" means that travel plans can be re-evaluated and modified as needed in response to changes in the user's emotional state.

[0539] The system that implements this application provides travel plans based on the user's emotional state. A specific embodiment is shown below.

[0540] The server retrieves travel information entered by the user using a terminal. This travel information includes details such as itinerary, budget, destination, and desired activities. User voice input is also possible, and this voice data is converted to text using speech recognition technology such as SpeechRecognition. The sentiment engine analyzes the converted text and directly entered text data. This analysis uses NLP libraries such as spaCy and machine learning frameworks such as TensorFlow. In this way, the user's emotional state is identified.

[0541] Based on the identified emotional state, the server generates a travel plan. For example, if the emotion engine determines that the user is seeking relaxation, the server will create a plan that considers relaxing places such as natural tourist attractions and spas. The created plan is further optimized by using a travel information API (e.g., TripAdvisor API) to obtain the latest travel information from external sources.

[0542] Users can review the travel plan provided through their device and make adjustments based on their emotional state as needed. This results in a personalized travel plan that takes both the user's emotions and desires into consideration.

[0543] As a concrete example, consider a scenario where a user voice-inputs, "I want to escape from my busy daily life." The emotion engine determines that the user is stressed and needs relaxation. Based on this information, the server generates and presents a travel plan that includes a quiet rural resort or spa. An example of a prompt in this case would be the instruction, "If the user needs relaxation, please suggest a quiet tourist destination nearby." In this way, a travel plan that meets the user's emotional needs is provided.

[0544] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0545] Step 1:

[0546] Users enter travel information using a terminal. This information includes itinerary, budget, desired destinations, and preferred activities. Voice input is also available, and the data is converted into text using speech recognition technology. The entered information is sent to the server.

[0547] Step 2:

[0548] The server analyzes the received text data and uses an emotion engine to identify the user's emotional state. Here, an NLP library (e.g., spaCy) is used to analyze phrasing, keywords, and tone of voice within the text. The input is text data, and the output is the user's emotional state (e.g., needs to relax, adventurous).

[0549] Step 3:

[0550] The server generates a travel plan based on the identified emotional state. For example, if it determines that the user is seeking relaxation, it prioritizes selecting tourist destinations and activities with relaxation effects. The input data is the emotional state, and the output is an initial travel plan. The generating AI model considers the latest tourist information and complements the plan.

[0551] Step 4:

[0552] The server retrieves the latest information from external sources (e.g., a tourism information API) and optimizes the generated travel plan. The input is the initial travel plan, and the output is an improved travel plan that reflects the latest information. Here, an API is used to retrieve opening hours and event information for tourist attractions and incorporate it into the travel plan.

[0553] Step 5:

[0554] The system provides users with optimized travel plans. Users can view the plans on their devices and adjust them according to their emotional state and preferences. The input is an optimized travel plan, and the output is the final plan after user adjustments. Users can further refine their plans by changing options or adding comments based on the suggested plan.

[0555] 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.

[0556] 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.

[0557] 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.

[0558] [Fourth Embodiment]

[0559] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0560] 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.

[0561] 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).

[0562] 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.

[0563] 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.

[0564] 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).

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] 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.

[0571] 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".

[0572] This invention, the AI ​​Family Travel Planner, is a system that provides a travel plan tailored to the user's preferences while reducing the user's burden. The embodiments of this system are described below.

[0573] Users access a dedicated interface via their device and input details such as their travel dates, budget, desired destinations, and the names of the participants. This information is sent to the system's underlying server. Upon receiving this data, the server uses an AI model to analyze it and generate an optimal travel plan tailored to the user's preferences.

[0574] The AI ​​model embedded in the server learns from past travel data and relevant external sources, allowing it to flexibly respond to different user requests. In this process, the server not only creates the most efficient schedule within a given timeframe but also performs real-time price comparisons to suggest the best options within the user's budget.

[0575] For example, if a user enters a request such as, "My family of four wants to take a 5-night, 6-day domestic trip during summer vacation. Our budget is 200,000 yen, and we want to enjoy nature in addition to famous tourist spots," the server will respond by selecting tourist destinations that can be visited within the budget and proposing a travel schedule for each day. For example, it might plan a trip to famous tourist spots in urban areas on the first day, and to enjoy nature in suburban areas on the second and third days, and also provide information on accommodations and transportation.

[0576] The terminal displays the plan generated by this server in detail. The user can review this plan and make fine adjustments on the terminal if necessary. In this way, the cumbersome tasks of travel planning are fully automated, and a trip tailored to the individual user's wishes is quickly planned.

[0577] The following describes the processing flow.

[0578] Step 1:

[0579] Users access a dedicated interface from their device and enter travel information such as travel dates, budget, desired destinations, and participant information. This information forms the basis of the travel plan, so it is required to be entered in as much detail as possible.

[0580] Step 2:

[0581] The terminal sends the information entered by the user to the server as data packets. At this time, the input data is structured and formatted to facilitate analysis by the server.

[0582] Step 3:

[0583] The server sends the received travel information to an analysis engine, which generates a travel plan that takes the user's preferences into account. This analysis considers factors such as weather at the destination, event information, transportation options, and accommodation availability to create the optimal schedule.

[0584] Step 4:

[0585] The server accesses external information sources to obtain the latest tourist attraction and pricing information and integrates it into the travel plan. This process is performed in real time based on the user's preferences and aims to improve the accuracy of the plan.

[0586] Step 5:

[0587] The server optimizes accommodations and transportation to ensure maximum satisfaction within the budget. Here, the most suitable plan is calculated based on AI-driven budget allocation and the user's preferences.

[0588] Step 6:

[0589] The generated travel plan is sent from the server to the terminal and displayed to the user in a visually easy-to-understand format. This includes the schedule for each day, information on destinations, and details of transportation.

[0590] Step 7:

[0591] Users can review the provided travel plan through their device and make adjustments as needed. For example, they can add specific tourist destinations or change the order of visit dates.

[0592] (Example 1)

[0593] 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".

[0594] The challenge lies in reducing the cumbersome tasks users face when planning a trip, while simultaneously generating optimal travel plans tailored to various conditions. In particular, sophisticated planning that responds immediately to individual conditions such as travel dates and budgets, and reflects real-time information, is required.

[0595] 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.

[0596] In this invention, the server includes means for acquiring travel information, including itinerary information and budget information, obtained through a device operated by the user; means for analyzing the acquired travel information and generating a travel plan through an information processing model using past travel data; and means for optimizing the generated travel plan using the latest information, including price information, by linking with an external information source. This makes it possible to efficiently create and present an optimal travel plan that suits the user's conditions.

[0597] A "user-operated device" is an electronic device used by a user to input information and transmit it to a server through an interface.

[0598] "Itinerary information" refers to information about the start and end dates and specific times of a trip, and forms the basis of a travel plan.

[0599] "Budget information" refers to information about the maximum amount of money set for travel expenses, and an appropriate travel plan is created based on this information.

[0600] "Travel information" refers to comprehensive data that includes details related to a trip, such as the itinerary, budget, destinations, and participants.

[0601] An "information processing model" refers to an algorithm that learns from past data and generates an optimal travel plan tailored to the user's needs.

[0602] "External information sources" refer to external data providers that offer information necessary for travel planning, such as real-time prices and booking status.

[0603] "Optimization" is the process of creating the most efficient and effective travel plan, taking into account available resources and conditions.

[0604] "Travel plan" refers to a detailed plan of the trip, including the schedule, destinations, means of transportation, and accommodations, which is created based on the information entered by the user.

[0605] The following system configuration is considered as an embodiment of this invention. When planning a trip, the user accesses a dedicated interface from an internet-connected terminal and inputs detailed information such as the trip itinerary, budget, places to visit, and participants. The terminal transmits this information to the server via the HTTPS protocol.

[0606] The server activates an internal AI model based on the received travel information, and uses historical travel data and real-time pricing information from external sources to generate an optimal travel plan tailored to the user's needs. In this process, the server performs various data analyses to efficiently schedule the trip within the specified travel period and develop a plan that provides the greatest value within the budget.

[0607] As a concrete example, consider a scenario where a user inputs a prompt such as, "My family of four wants to take a 5-night, 6-day domestic trip during summer vacation. Our budget is 200,000 yen, and we want to enjoy nature in addition to famous tourist spots." Based on the conditions received from the user, the server uses artificial intelligence to automatically select suitable tourist destinations and proposes a specific schedule for each day of the trip. For example, it might create a plan to visit famous tourist spots in urban areas on the first day, and then visit suburban areas where nature can be enjoyed on the second and third days, and also provide detailed information on accommodations and transportation.

[0608] The generated travel plan is displayed on the device, allowing the user to review and make adjustments as needed. Once adjustments are complete on the device, the final travel plan is sent back to the server for storage. This allows the user to review the plan before their trip and smoothly prepare for departure.

[0609] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0610] Step 1:

[0611] The user enters detailed travel plan information into the device. Specifically, they input travel dates, budget, destination, and participant information into a dedicated interface. This information is stored on the device as input data to create a travel plan that reflects the user's preferences.

[0612] Step 2:

[0613] The device sends saved travel information to the server via HTTPS. Input data includes user-specified itinerary information, budget information, and desired destinations, and this data is securely transmitted to the server.

[0614] Step 3:

[0615] The server activates a generation AI model based on the received data. The process involves analyzing the user's input data and automatically generating a travel plan that matches the user's preferences, while obtaining real-time information from past travel databases and external sources. This outputs a proposed itinerary, destinations, and accommodation options as part of the travel plan.

[0616] Step 4:

[0617] The server optimizes the generated travel plan. Specifically, it collaborates with external sources to obtain the latest pricing and booking information and incorporates it into the travel plan. This process makes it possible to present the best options within the user's budget.

[0618] Step 5:

[0619] The generated plan is sent from the server to the device. The device displays this optimized travel plan in detail to the user. The user reviews the displayed plan and makes adjustments to the itinerary and destinations as needed.

[0620] Step 6:

[0621] Once the user has finalized their plan, that information is sent from their device to the server, and the final travel plan is confirmed. The server saves this travel plan in a database so that it can be reviewed and modified later. At this stage, all steps are complete.

[0622] (Application Example 1)

[0623] 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".

[0624] Traditional travel planning systems required users to manually input detailed information and manually review and adjust their plans, resulting in a heavy user burden and a time-consuming planning process. Furthermore, interactive travel planning adjustments using household electronic devices were not considered, making it difficult to respond quickly to user situations and preferences.

[0625] 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.

[0626] In this invention, the server includes means for acquiring travel information entered by the user, means for analyzing the acquired travel information and generating a travel plan based on the user's requests, means for optimizing the generated travel plan and providing the optimized travel plan to the user, means for recognizing the user's voice input and outputting information related to the travel plan based on the recognition results, and means for interacting with the user through a home appliance and performing adjustments to the travel plan in real time. This enables the user to intuitively and quickly plan and adjust their travel plan via voice.

[0627] A "user" is an individual or legal entity that uses the system to plan or adjust travel plans.

[0628] "Travel information" refers to data such as the itinerary, budget, desired destinations, and detailed information about the participants.

[0629] "Means of acquisition" means a method or device for accurately receiving and recording information provided by the user.

[0630] "Means for analysis and generation" refers to a method or apparatus for analyzing acquired data to create a travel plan that meets the user's preferences.

[0631] "Means of optimization and delivery" refers to a method or device that adjusts a generated travel plan to best match the user's conditions and informs the user of that plan.

[0632] "Means for recognizing voice input" means a method or device that analyzes the user's voice, converts it into text data, and makes it available for processing within the system.

[0633] "Household machinery and equipment" refers to mechanical or electronic devices used within the home that enable interaction with the user.

[0634] "Means for dialogue and adjustment" refers to methods or devices for changing or updating travel plans through communication with users.

[0635] A system implementing this invention acquires travel information entered by the user via voice or a terminal, automatically creates a travel plan using a generated AI model based on that information, and provides it to the user interactively through a home appliance.

[0636] The system first collects the user's voice input using a home device and converts it into text data using speech recognition software (e.g., Google Cloud Speech-to-Text). This converted data is sent to a server, where it is analyzed using a machine learning library (e.g., TensorFlow). The server then generates a travel plan based on the analysis results. In doing so, it uses external APIs (e.g., Google Maps API) to obtain the latest tourist information and weather information and incorporates it into the plan.

[0637] Furthermore, the generated travel plan is optimized using an algorithm to suit the user's budget and preferences, and is provided to the user via voice and screen display through a home device. The user can review this plan and, if necessary, instruct the home device to change the plan in real time. This instruction is also received by voice, analyzed again on the server, and an updated plan is provided.

[0638] For example, if a user uses voice input to say, "I'm planning a 3-night, 4-day family trip next weekend. My budget is 250,000 yen, and I'd like to visit historical sites and natural attractions," the server will analyze this and suggest appropriate destinations. For instance, it might suggest a schedule such as visiting historical sites on day 1 and natural attractions on day 2.

[0639] An example of a prompt message for a generative AI model would be: "My family of four is planning a weekend trip. Our budget is 200,000 yen, and we want a good balance of sightseeing in urban and rural areas. Please create a schedule for us."

[0640] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0641] Step 1:

[0642] Users input travel information using voice or a device. During this process, users provide details such as their travel itinerary, budget, and desired destinations. The entered information is then converted into text data through a voice recognition system.

[0643] Step 2:

[0644] The terminal sends the converted text data to the server. The server receives this data and performs analysis using a machine learning library. Specifically, it analyzes the user's requests and processes the data to generate a travel plan based on them.

[0645] Step 3:

[0646] The server uses a generative AI model to create travel plans that meet the user's requests. Based on the results of the input data analysis, it selects relevant tourist destinations and accommodations and creates a specific itinerary.

[0647] Step 4:

[0648] The server uses external information sources (e.g., APIs) to retrieve the latest information on tourist destinations, weather, and transportation. This retrieved external data is then incorporated into the travel plan and adjusted to fit the itinerary and budget.

[0649] Step 5:

[0650] The generated travel plan is optimized by the server. Based on the user's conditions, budget, and preferences, an optimization algorithm is applied to create the most efficient and satisfying plan.

[0651] Step 6:

[0652] The device provides the user with an optimized travel plan. Details of the travel plan are displayed via voice and on the screen through the home electronic device. The user can visually and audibly review the plan's overview.

[0653] Step 7:

[0654] If a user wishes to change or adjust their plan, they can provide instructions in real time via their device. The device then sends these instructions back to the server, which recalculates and adjusts the travel plan based on the instructions and provides the user with an updated plan.

[0655] 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.

[0656] This invention aims to build a system that provides travel plans that take user emotions into consideration. By incorporating an emotion engine, the system recognizes the user's emotional state and optimizes the travel plan based on that state.

[0657] Users use their devices to input detailed travel information. This includes not only dates, budgets, and places they want to visit, but also the ability to express their wishes and preferences through voice. The device sends the collected data to a server. During this process, the voice and text data are analyzed by an emotion engine to detect and evaluate the user's current emotions. The emotion engine determines emotions through text phrasing, tone of voice, and even quick questionnaire-style interactions.

[0658] Based on emotional data, the server analyzes the user's emotional state, such as whether they are seeking relaxation or adventure, and generates a travel plan accordingly. Emotion-responsive planning proceeds in parallel with the normal travel plan generation process. For example, if the emotion engine detects that the user is feeling stressed, the server will prioritize suggesting tourist spots and activities that are likely to have a relaxing effect (such as visiting a hot spring resort or choosing a hotel with massage services).

[0659] For example, if a user voice-inputs "I want to be freed from my busy life," and the emotion engine detects the need for relaxation, the server will use that information to create a travel plan that includes accommodation in a quiet natural environment. This plan will primarily feature quiet resorts and spas in the countryside rather than urban tourist spots, ensuring that the user can refresh both their mind and body.

[0660] Ultimately, the device provides the user with these optimized travel plans, allowing them to review the details and make adjustments as needed. This system enables more personalized travel planning that also takes the user's emotional needs into consideration.

[0661] The following describes the processing flow.

[0662] Step 1:

[0663] Users input their travel plans and preferences through their device. In addition to text input, they can use the device's voice input function to convey emotional elements of their wishes and expectations (e.g., wanting to relax, wanting adventure). The device packages this data and sends it to the server.

[0664] Step 2:

[0665] The server analyzes the received data and activates the emotion engine. The emotion engine uses natural language processing and speech analysis techniques to evaluate the user's emotions in order to generate emotion indicators from the user's written and spoken content. It detects and classifies emotional states such as positive, negative, and neutral.

[0666] Step 3:

[0667] In generating travel plans, the server considers emotional indicators obtained from the emotion engine. For example, if a user indicates stress, the server prioritizes suggesting tourist destinations and activities that include many relaxing elements. Conversely, if a user indicates enthusiasm, it creates a plan that includes adventurous tours and activities that offer new experiences.

[0668] Step 4:

[0669] By utilizing external information sources, the system obtains real-time, up-to-date information on tourist destinations, events, and accommodation availability. The server integrates this information to create an optimal plan that matches the user's emotional state.

[0670] Step 5:

[0671] The server sends the completed travel plan to the terminal, making it accessible to the user. The travel plan clearly displays options and recommendations tailored to the user's preferences.

[0672] Step 6:

[0673] Users can review the travel plan provided on their device and adjust details as needed. Feedback from the emotion engine provides additional information to determine if the user is satisfied with the plan, and further adjustments can be made based on their response.

[0674] (Example 2)

[0675] 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".

[0676] Traditional travel planning systems typically provide plans based on the user's explicit requests. However, these systems often fail to consider the user's emotional state, making it difficult to provide a truly personalized experience. Specifically, if a user is experiencing stress, they may not receive suggestions tailored to their emotions, potentially resulting in a less-than-satisfactory travel experience.

[0677] 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.

[0678] In this invention, the server includes a computing device for performing emotion analysis, means for generating a travel plan based on the user's emotions, means for identifying travel destinations and activities that promote relaxation according to the emotional state, and means for optimizing the generated travel plan and providing it to the user. This makes it possible to provide a more personalized travel plan that takes the user's emotional state into consideration.

[0679] A "user" is an individual or group that provides and receives travel planning information from the system.

[0680] "Travel information" refers to specific travel data provided by the user, such as itinerary, budget, and desired destinations.

[0681] "Emotional state" refers to a user's inner feelings and psychological tendencies, and is an element that is reflected in their travel plan.

[0682] "Emotion analysis" is a technical process that processes a user's voice and text data to determine their emotional state.

[0683] A "travel plan" is a specific itinerary for carrying out a trip, generated based on the user's requests and emotional state.

[0684] A "computational unit" is a device within a system consisting of a computer that performs emotion analysis and determines the user's emotional state.

[0685] "Optimization" is the process of adjusting the generated travel plan according to the user's emotional state and requests, enabling the best possible suggestions.

[0686] "Travel destinations and activities that promote relaxation" refer to travel destinations or activities aimed at reducing user stress and enhancing their refreshing effect.

[0687] This invention is a system that provides travel plans that take into account the user's emotional state, and is realized through the coordinated operation of the user, terminal, and server.

[0688] First, the user enters travel-related information into the device. This includes specific details such as the travel itinerary, budget, and places they want to visit. In addition, through voice input, the user can express their wishes and preferences in a natural way.

[0689] The device transmits the collected information to the server. This data includes text and audio data, and encryption technology is used during the transmission process to ensure data security. After the data is transmitted, the server receives it and uses a computing device for sentiment analysis to determine the user's emotional state. This analysis uses natural language processing technology and speech analysis algorithms to precisely evaluate the user's voice tone and word choice.

[0690] Based on the results of the emotion analysis, the server uses a generative AI model to generate a travel plan that matches the user's emotions. The generated plan may include destinations and activities that promote relaxation for the user. For example, if a user voice-inputs "I want to escape from my busy life," and the emotion analysis determines that relaxation is needed, the server can offer a lodging plan at a quiet resort away from the city.

[0691] Ultimately, the device presents the user with an optimized travel plan generated by the server. The user can review this plan and make adjustments as needed. This system enables the provision of a more personalized travel experience that also takes the user's emotional state into account.

[0692] A concrete example of a prompt to input into a generative AI model is, "Suggest a relaxing travel plan based on an analysis of the user's emotions." Using this prompt, the generative AI model will make the most suitable suggestion from a number of options.

[0693] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0694] Step 1:

[0695] Users input detailed information such as travel dates, budget, and desired destinations through their devices. Furthermore, they can use voice input to naturally express their preferences and desires. This input data is standardized across devices and prepared as a data stream. The input includes both text and voice data, resulting in data ready for transmission to the server as output.

[0696] Step 2:

[0697] The terminal sends standardized data to the server. During transmission, an encryption process is performed to ensure data security. In this process, data is transmitted to the server via encrypted communication and stored as output in a temporary storage area on the server.

[0698] Step 3:

[0699] The server passes the received data to a computing unit for sentiment analysis. Using a sentiment engine, natural language processing techniques and speech analysis algorithms are applied. The input consists of speech and text data stored on the server, and the user's emotional state is analyzed through this data processing. The output is numerical data or categorical information indicating the emotional state.

[0700] Step 4:

[0701] The server uses a generative AI model to generate a travel plan that aligns with the user's emotions, based on the results of the emotion analysis. By inputting the prompt "Suggest a relaxing travel plan based on the user's emotion analysis" to the generative AI model, the server will generate suggestions for optimal travel destinations and activities. The input consists of the emotion analysis results and the user's travel requirements, and the output is the proposed travel plan.

[0702] Step 5:

[0703] The server adjusts the suggested travel plan through an optimization process to create a plan that best matches the user's wishes and emotions. It then selects and discards parts of the generated travel plan, prioritizing, for example, visits to places that promote relaxation. The input is the initial travel plan and user emotion data, and the output is the optimized travel plan.

[0704] Step 6:

[0705] The device receives an optimized travel plan from the server and provides it to the user. The user can review this provided plan and make adjustments or changes through an interactive UI. The input is the optimized travel plan, and the output is the final travel plan reviewed by the user.

[0706] (Application Example 2)

[0707] 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".

[0708] Traditional travel planning systems could generate travel plans based on user requests and conditions, but they struggled to provide optimized plans that took into account the user's emotional state. Furthermore, they were unable to respond to real-time emotional changes during travel, making it challenging to flexibly provide plans that truly met the user's needs.

[0709] 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.

[0710] In this invention, the server includes means for acquiring travel information entered by the user, means for analyzing the acquired travel information and identifying the user's emotional state, and means for generating a travel plan according to the acquired emotional information. This makes it possible to provide a flexible and personalized travel plan that is tailored to the user's emotional state.

[0711] "User-inputted travel information" refers to information provided by the user, such as travel requests, itinerary, budget, and destination.

[0712] "Means for analysis and identification of the user's emotional state" refers to methods and technologies for processing input data and detecting the user's emotions.

[0713] "Means for generating travel plans based on emotional information" refers to methods and technologies for constructing optimal travel plans based on the emotions of identified users.

[0714] "Means of optimizing and providing users with optimized travel plans" refers to methods and technologies that adjust generated travel plans to suit the user's wishes and circumstances, and present them in a more appropriate format.

[0715] "A means of dynamically suggesting appropriate information based on user sentiment data regarding travel plans" refers to methods and technologies that recommend optimal tourist destinations and activities in real time according to the user's sentiment data.

[0716] "Acquiring information from external sources and incorporating it into the generated travel plan" means taking the latest travel-related information from external databases and services and integrating it into the travel plan.

[0717] "The ability to fine-tune based on emotional data" means that travel plans can be re-evaluated and modified as needed in response to changes in the user's emotional state.

[0718] The system that implements this application provides travel plans based on the user's emotional state. A specific embodiment is shown below.

[0719] The server retrieves travel information entered by the user using a terminal. This travel information includes details such as itinerary, budget, destination, and desired activities. User voice input is also possible, and this voice data is converted to text using speech recognition technology such as SpeechRecognition. The sentiment engine analyzes the converted text and directly entered text data. This analysis uses NLP libraries such as spaCy and machine learning frameworks such as TensorFlow. In this way, the user's emotional state is identified.

[0720] Based on the identified emotional state, the server generates a travel plan. For example, if the emotion engine determines that the user is seeking relaxation, the server will create a plan that considers relaxing places such as natural tourist attractions and spas. The created plan is further optimized by using a travel information API (e.g., TripAdvisor API) to obtain the latest travel information from external sources.

[0721] Users can review the travel plan provided through their device and make adjustments based on their emotional state as needed. This results in a personalized travel plan that takes both the user's emotions and desires into consideration.

[0722] As a concrete example, consider a scenario where a user voice-inputs, "I want to escape from my busy daily life." The emotion engine determines that the user is stressed and needs relaxation. Based on this information, the server generates and presents a travel plan that includes a quiet rural resort or spa. An example of a prompt in this case would be the instruction, "If the user needs relaxation, please suggest a quiet tourist destination nearby." In this way, a travel plan that meets the user's emotional needs is provided.

[0723] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0724] Step 1:

[0725] Users enter travel information using a terminal. This information includes itinerary, budget, desired destinations, and preferred activities. Voice input is also available, and the data is converted into text using speech recognition technology. The entered information is sent to the server.

[0726] Step 2:

[0727] The server analyzes the received text data and uses an emotion engine to identify the user's emotional state. Here, an NLP library (e.g., spaCy) is used to analyze phrasing, keywords, and tone of voice within the text. The input is text data, and the output is the user's emotional state (e.g., needs to relax, adventurous).

[0728] Step 3:

[0729] The server generates a travel plan based on the identified emotional state. For example, if it determines that the user is seeking relaxation, it prioritizes selecting tourist destinations and activities with relaxation effects. The input data is the emotional state, and the output is an initial travel plan. The generating AI model considers the latest tourist information and complements the plan.

[0730] Step 4:

[0731] The server retrieves the latest information from external sources (e.g., a tourism information API) and optimizes the generated travel plan. The input is the initial travel plan, and the output is an improved travel plan that reflects the latest information. Here, an API is used to retrieve opening hours and event information for tourist attractions and incorporate it into the travel plan.

[0732] Step 5:

[0733] The system provides users with optimized travel plans. Users can view the plans on their devices and adjust them according to their emotional state and preferences. The input is an optimized travel plan, and the output is the final plan after user adjustments. Users can further refine their plans by changing options or adding comments based on the suggested plan.

[0734] 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.

[0735] 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.

[0736] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0737] 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.

[0738] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] 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."

[0743] 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.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0755] The following is further disclosed regarding the embodiments described above.

[0756] (Claim 1)

[0757] A means of obtaining travel information entered by the user,

[0758] A means for analyzing acquired travel information and generating a travel plan based on user requests,

[0759] A means for optimizing the generated travel plan and providing the optimized travel plan to the user,

[0760] A system that includes this.

[0761] (Claim 2)

[0762] The system according to claim 1, which obtains the latest information from external sources according to the conditions of travel and reflects it in the generated travel plan.

[0763] (Claim 3)

[0764] The system according to claim 1, which allows a user to review and fine-tune a travel plan provided on a terminal.

[0765] "Example 1"

[0766] (Claim 1)

[0767] A means for acquiring travel information, including itinerary information and budget information, obtained through a device operated by the user,

[0768] A means of analyzing acquired travel information and generating travel plans through an information processing model using past travel data,

[0769] A means of optimizing the generated travel plan using the latest information, including pricing information, by linking with external information sources,

[0770] A means of presenting users with optimized travel plans,

[0771] A means for storing travel plans determined based on user adjustments,

[0772] A system that includes this.

[0773] (Claim 2)

[0774] The system according to claim 1, which acquires information in real time from external sources based on travel constraints and applies it to a generated travel plan.

[0775] (Claim 3)

[0776] The system according to claim 1, which allows the user to review a travel plan provided on a device operated by the user and adjust the details as needed.

[0777] "Application Example 1"

[0778] (Claim 1)

[0779] A means of obtaining travel information entered by the user,

[0780] A means for analyzing acquired travel information and generating a travel plan based on user requests,

[0781] A means for optimizing the generated travel plan and providing the optimized travel plan to the user,

[0782] A means for recognizing user voice input and outputting information related to travel planning based on the recognition results,

[0783] A means of interacting with users through home-use machinery and adjusting travel plans in real time,

[0784] A system that includes this.

[0785] (Claim 2)

[0786] The system according to claim 1, which obtains the latest information from external sources according to the conditions of travel and reflects it in the generated travel plan.

[0787] (Claim 3)

[0788] The system according to claim 1, which allows a user to review and fine-tune a travel plan provided on a terminal.

[0789] "Example 2 of combining an emotion engine"

[0790] (Claim 1)

[0791] A means of obtaining travel information entered by the user,

[0792] A means for analyzing acquired travel information and emotional state, and generating a travel plan based on the user's emotions,

[0793] A means for optimizing the generated travel plan and providing the optimized travel plan to the user,

[0794] A computing device for performing emotion analysis,

[0795] A means of identifying travel destinations and activities that promote relaxation according to emotional state,

[0796] A system that includes this.

[0797] (Claim 2)

[0798] The system according to claim 1, which obtains the latest information from external sources and reflects it in the generated travel plan, depending on the travel conditions and the user's feelings.

[0799] (Claim 3)

[0800] The system according to claim 1, which allows the user to review and fine-tune a travel plan provided on their device, and which includes a recommended plan based on their emotional state.

[0801] "Application example 2 when combining with an emotional engine"

[0802] (Claim 1)

[0803] A means of obtaining travel information entered by the user,

[0804] A means for analyzing acquired travel information and identifying the user's emotional state,

[0805] A means for generating a travel plan based on acquired emotional information,

[0806] A means for optimizing the generated travel plan and providing the optimized travel plan to the user,

[0807] A means of dynamically suggesting appropriate information based on the user's emotional data regarding travel plans,

[0808] A system that includes this.

[0809] (Claim 2)

[0810] The system according to claim 1, which obtains the optimal activity location from an external source according to the travel conditions and the user's emotional state, and reflects it in the generated travel plan.

[0811] (Claim 3)

[0812] The system according to claim 1, which allows a user to review and fine-tune a travel plan provided on a device based on sentiment data. [Explanation of Symbols]

[0813] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining travel information entered by the user, A means for analyzing acquired travel information and generating a travel plan based on user requests, A means for optimizing the generated travel plan and providing the optimized travel plan to the user, A system that includes this.

2. The system according to claim 1, which obtains the latest information from external sources according to the conditions of travel and reflects it in the generated travel plan.

3. The system according to claim 1, which allows a user to review and fine-tune a travel plan provided on a terminal.

Images