system

Abstract

We provide the system. [Solution] A means of receiving user profile information and storing it in a database, A means of receiving destination and schedule information entered by the user each time, Means for obtaining real-time traffic information, weather information, and facility availability information from external sources, A means for generating the optimal route and schedule based on user profile information, input data, and external information using a generation algorithm, A means of notifying the user of the generated route and schedule, A means to dynamically regenerate routes and schedules based on user feedback, 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 the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, there has been a demand for providing personalized travel plans tailored to individual users. However, existing route search systems and navigation systems cannot fully utilize individual user information and real-time external data, making it difficult to propose optimal routes and schedules suitable for users' needs and situations. In addition, there is also a lack of a mechanism to effectively incorporate local information and events, resulting in limited contribution to the local economy. Solving these problems and providing a highly convenient travel experience for users is an object of the present invention.

Means for Solving the Problems

[0005] This invention includes means for receiving user profile information and storing it in a database, and further means for receiving destination and schedule information entered by the user each time. In addition, it includes means for acquiring real-time traffic information, weather information, and facility availability information from external sources, and integrates this information using a generation algorithm to generate the optimal route and schedule. It also includes means for notifying the user of the generated route and schedule and dynamically regenerating the route and schedule based on user feedback. Furthermore, by incorporating means for suggesting local events and points of interest, and means for revitalizing the local economy through data linkage with external organizations, it provides an attractive travel experience that utilizes local information while responding to the diverse needs of users.

[0006] "User profile information" refers to personalized information that users register in advance, including their address, favorite places, family structure, hobbies, food preferences, allergy information, preferred modes of transportation, and payment methods.

[0007] A "database" is a storage method within a system that systematically stores user profile information and data entered as needed, and allows for immediate retrieval of that information as required.

[0008] "Data entered each time" refers to a series of pieces of information that users enter into the application at specific points in time when traveling or making plans, such as destination, order of visits, budget, and number of people.

[0009] "External information sources" refer to services and databases that provide real-time data obtained from outside the system, such as traffic information, weather information, and facility availability information.

[0010] A "generation algorithm" is a method for automatically calculating and generating the optimal route and schedule by processing user profile information, input data, and real-time data obtained from external sources.

[0011] "Route and schedule" refers to a plan that includes the route the user will take, as well as suggested dates and time allocations to reach each destination.

[0012] "Feedback" refers to information provided by users through the application, including their opinions and requests regarding suggested routes and schedules.

[0013] "Data sharing with external organizations" refers to the process of communication and connection for the mutual use or provision of data related to regional information and economic activities with external organizations and systems. [Brief explanation of the drawing]

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

Modes for Carrying Out the Invention

[0015] 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.

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

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be 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.

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

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

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

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

[0022] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0035] This invention is a system for providing users with personalized travel plans. This system leverages the user's prior profile information to generate optimized routes and schedules, and dynamically reconfigures the plan in response to real-time changes in circumstances, thereby providing users with a stress-free travel experience.

[0036] First, users register profile information through the application, such as their address, favorite places, family structure, hobbies, favorite foods, allergy information, preferred mode of transportation, and payment method. This allows for personalization tailored to individual needs.

[0037] Next, for travel or daily commutes, users input information into the application such as their destination and order of activities for the day, budget, and the number of people traveling with them. This data is then sent from the device to the server, which initiates a real-time search based on this information.

[0038] The server retrieves real-time data from external sources, such as traffic conditions, weather conditions, and facility congestion. This information is combined with the user's profile information and data entered as needed, and a generation algorithm creates the optimal travel route and schedule plan.

[0039] This system can also provide users with a richer experience by incorporating local event information and recommended places to visit. This can contribute to the revitalization of the local economy.

[0040] For example, a user planning a family trip for the weekend would input several tourist spots they want to visit into the app. The system would then take into account the user's situation (traveling with children) and their preferred mode of transportation (car), prioritizing car routes and suggesting a schedule that includes a picnic in a park and a stop at a popular local restaurant. The suggested plan would reflect real-time traffic congestion and weather conditions, and could be adjusted multiple times in advance.

[0041] Thus, the present invention takes various factors into comprehensive consideration to enable convenient and less burdensome travel for the user.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] When a user launches the application, they first enter their address, favorite places, family structure, hobbies, favorite foods, allergy information, preferred mode of transportation, and payment method on an input screen. This information is saved as profile information.

[0045] Step 2:

[0046] The device connects to the server to organize the profile information entered by the user and send it to the database. The server receives this data and securely stores it in the database.

[0047] Step 3:

[0048] Users input data into the application each time they need to travel, such as the day of travel, destination, order of visits, budget, and number of people. This data is sent to the server separately from their profile information.

[0049] Step 4:

[0050] The server checks for data reception each time and collects necessary external information in real time. This external information includes traffic conditions, weather forecasts, and destination congestion information. The server obtains this information from external APIs.

[0051] Step 5:

[0052] The server integrates pre-registered profile information, user-entered data, and real-time data acquired from external sources, and uses a generation algorithm to generate the optimal travel route and schedule. During this process, the plan is adjusted based on factors such as traffic convenience, congestion levels, and user preferences.

[0053] Step 6:

[0054] The server sends the generated route and schedule to the terminal. The user can view the plan details and schedule on the terminal. If the user wishes, they can request the server to regenerate the route through feedback.

[0055] Step 7:

[0056] The AI ​​agent generates new suggestions based on external information and user feedback. These new suggestions are then presented to the user via the server, allowing the user to review and decide on the latest suggestions.

[0057] Step 8:

[0058] The server collects local event information and points of interest through collaboration with external organizations and integrates them into the user's plan. This provides users with a rich, locally-focused experience.

[0059] (Example 1)

[0060] 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."

[0061] In modern society, planning a trip involves the time-consuming task of individually researching real-time information such as traffic conditions and weather, and then constructing the optimal route and schedule that takes this into account. Furthermore, dynamically reconfiguring the plan in response to changing circumstances during the journey is required, which is difficult to do manually. Additionally, suggestions for local events and points of interest are rarely provided in an integrated manner, limiting the user's travel experience. Therefore, a system is needed that can solve these problems and provide users with a stress-free travel experience.

[0062] 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.

[0063] In this invention, the server includes means for receiving general user information and storing it in an information collection, means for receiving destination and action plan information entered by the user from time to time, and means for acquiring real-time travel data, environmental data, and facility status information from external information sources. This enables the dynamic generation of personalized and optimal travel routes and plans according to the user's purpose, and their reconfiguration in response to real-time circumstances.

[0064] "User general information" refers to a series of personal data that users register in the system, such as their address, hobbies and preferences, and family structure.

[0065] An "information collection" refers to a database or storage system used by a system to store and manage users' general information and other related data.

[0066] "Destination and activity plan information entered as needed" refers to detailed information such as the necessary destinations, order of visits, and budget that the user enters when traveling.

[0067] "External information sources" refer to public or private data providers that provide real-time data such as traffic conditions, weather conditions, and facility congestion levels.

[0068] "Real-time travel data" refers to information that is acquired and updated instantly based on the user's location, such as current traffic conditions and travel time.

[0069] "Environmental data" refers to information that includes natural conditions related to travel, such as weather conditions, temperature, and precipitation on the day of travel.

[0070] "Facility status information" refers to the latest information regarding the congestion level, availability, and operating hours of the facility you plan to visit.

[0071] "Dynamic generation" refers to the process of modifying and restructuring travel routes and schedules in real time in response to changing environments and circumstances.

[0072] This invention relates to a system that provides users with personalized travel plans. This system makes user travel smoother and less burdensome.

[0073] Users register their personal information, such as address, hobbies, family structure, and favorite foods, through the application. This information is sent from the device to the server and stored in an information repository on the server. The server uses this general information to form a foundation for developing travel plans that are best suited to the user's needs.

[0074] For travel and daily commutes, users input destinations, itinerary, budget, and the number of companions into the application. This information is also transmitted to the server via the device. The server obtains real-time data such as traffic conditions, weather conditions, and facility congestion from external sources. Public API services and private data provision platforms are used for this information collection.

[0075] The server combines acquired real-time travel data, environmental data, and facility status information with the user's profile information, and uses a generated AI model to create the optimal travel route and schedule. This AI model dynamically optimizes the plan by taking into account user-specified conditions and real-time data, such as avoiding traffic congestion and considering weather conditions.

[0076] As a concrete example, consider a user planning a weekend family trip. This user enters the tourist destinations they want to visit and the restaurants they want to stop at along the way into the application. The server optimizes the route considering car travel and incorporates parks suitable for picnics and popular restaurants into the schedule as needed. Because the proposed plan takes real-time traffic conditions and weather information into account, the user can enjoy their trip with peace of mind.

[0077] Furthermore, the proposed travel plan can be reconstructed any number of times based on user feedback. An example of a prompt using the generative AI model is: "User: I would like to visit tourist spots B and C in the afternoon. I would like to have lunch at cafe A, so please suggest a schedule that fits that."

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] Users enter profile information through the application. This information includes address, hobbies, family structure, and allergy information. The device converts this information into a digital format, structures it electronically, and sends it to the server. This information is stored in the server's data repository and associated with the user's personal ID.

[0081] Step 2:

[0082] The user enters details about a specific travel plan into the application. This includes the destination for the day, the order of visits, the budget, and information about travel companions. The terminal receives these details and sends them to the server as a temporary request. The server parses the received data, tags the entered travel plan with a unique identifier, and stores it.

[0083] Step 3:

[0084] The server collects necessary real-time data from external sources. Here, APIs are used to obtain traffic conditions, weather conditions, facility congestion, and other data. The server receives this raw data and performs formatting and normalization to combine it with user input data. This process integrates real-time environmental data with travel planning.

[0085] Step 4:

[0086] The server uses integrated data to drive a generative AI model that generates the optimal travel route and schedule. This step dynamically plans based on real-time data, taking into account the characteristics of each user. The generative AI model algorithmically calculates multiple routes under given conditions and selects the optimal one. The output is an optimized travel schedule.

[0087] Step 5:

[0088] The server sends the generated schedule to the terminal and presents it to the user on the application. The user reviews the presented plan and provides feedback as needed. For example, they can add specific spots or request adjustments to times. This feedback is sent back to the server, triggering the plan regeneration process. This allows the user to ultimately obtain a travel plan that best suits their preferences.

[0089] (Application Example 1)

[0090] 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."

[0091] In recent years, with the advancement of urbanization, traffic congestion and overcrowding have become serious problems, making it difficult for individual citizens to travel efficiently and comfortably. Furthermore, the inability to efficiently obtain region-specific information has resulted in a lack of enriching lifestyle experiences. Traditional methods face the challenge of providing optimal travel plans in real time while considering individual circumstances and preferences.

[0092] 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.

[0093] In this invention, the server includes means for receiving user attribute information and storing it in a data storage device, means for receiving destination and plan information from the user based on real-time input, and means for obtaining the latest travel information, weather information, and facility availability from external information sources. This makes it possible to provide travel plans optimized for individual citizens in real time.

[0094] "User attribute information" refers to information about the user as an individual, such as address, interests, and preferred modes of transportation, which is necessary for personalizing travel plans.

[0095] A "data storage device" is an information processing device that stores user attribute information, movement history, and other data, and allows users to retrieve it as needed.

[0096] "Occasional input information" refers to specific information that users enter each time, such as destinations and plans, and is information that should be reflected in daily travel and trip planning.

[0097] "External information sources" refer to various data sources that provide real-time information such as traffic, weather, and facility usage.

[0098] "Route and schedule" refers to the optimal travel route at a specific time and the schedule based on it.

[0099] "Responses" refer to information collected as evaluations, opinions, or feedback that users give to the provided plan or to the application.

[0100] "Real-time information for the entire city" refers to information that encompasses traffic conditions, events, weather, and other factors that change moment by moment throughout the entire city.

[0101] "Information sharing" is a process that involves exchanging data with external organizations to connect various services and information, enabling the provision of more advanced information.

[0102] "Regional industries" refer to a collection of businesses and service industries that conduct economic activities in a specific region, and their revitalization contributes to the economic development of that region.

[0103] To realize this system, the user's smart device and the server play a central role. Users input their attribute information in advance using an application on their smartphone and store it in a data storage device. When planning travel in real time, they transmit destination and plan information from their smart device. The server is responsible for obtaining the latest travel information, weather information, and facility usage status from external sources and generating the optimal route and schedule based on this information.

[0104] The server performs multi-stage data processing and calculations based on the acquired data. In particular, it uses complex algorithms to generate dynamic and optimized travel plans by combining user attribute information with external real-time information. The software used includes Python and various APIs to enable real-time data processing.

[0105] The generated travel plan is notified to the user's smart device, and if the user responds, the server regenerates the plan based on that response. This process ensures that the user always has a travel experience that is up-to-date.

[0106] As a concrete example, a user planning a sightseeing trip within a city with their family enters information using a smartphone application, including destination, desired visit time, and budget. Based on this information, the system obtains real-time traffic and weather data to generate and provide an optimal travel plan. It also notifies the user of suggested sightseeing spots and event information, providing a richer experience.

[0107] An example of a prompt message for the generating AI model would be: "Please suggest some tourist destinations that my family can enjoy this afternoon. We will be starting from the central station, and please take weather and crowd conditions into consideration."

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] Users input attribute information using smart devices, and the device stores this information in a data storage device. This input includes the user's address, interests, and preferred modes of transportation, and is stored as foundational data to provide personalized experiences.

[0111] Step 2:

[0112] The user inputs their destination and plan information into the terminal, which then sends this information to the server. Specifically, this includes the places they want to visit, the time, and their budget, and this becomes the input data for creating the next optimal route.

[0113] Step 3:

[0114] The server retrieves the latest travel information, weather information, and facility availability from external sources. In this step, it utilizes traffic information APIs and weather information APIs to collect real-time data and prepares to combine it with the user's current status.

[0115] Step 4:

[0116] The server inputs user attribute information, timely input information, and external real-time information into a generative AI model to generate the optimal route and schedule. Here, the generative AI model performs complex data processing and algorithmic calculations, outputting a dynamically optimized travel plan.

[0117] Step 5:

[0118] The generated travel plan is sent from the server to the terminal. The notification the user receives includes recommended routes, places to visit, and event information, which the user can use to begin their journey.

[0119] Step 6:

[0120] Based on user feedback, the device sends information to the server, which then uses the feedback information to regenerate the optimal route using an AI model. This process ensures that users always receive the latest plan that adapts to changing circumstances.

[0121] 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.

[0122] This invention is a system for providing users with personalized travel plans, and by incorporating an emotion engine, it enables more detailed planning that dynamically reflects the user's emotions. This system utilizes the user's pre-registered profile information and external data acquired in real time to incorporate the user's emotional state, thereby providing a more comfortable and stress-free travel experience.

[0123] Users enter their basic information through the application, which is then stored on the server as profile information. When traveling, users enter information such as desired destinations, dates, and budget, and this information is also processed via the server. The server obtains real-time information from external sources, such as traffic information, weather forecasts, and facility congestion levels, to generate the optimal travel route and schedule that suits the user's conditions.

[0124] The emotion engine analyzes voice, facial expressions, and physical data acquired from the user's device while on the move to identify the user's emotional state. This information is transferred to a server, where a generation algorithm reconstructs a plan that is more emotionally appropriate. For example, if the user is feeling stressed, the route may be designed to include relaxing locations or events.

[0125] For example, if a user on a business trip is experiencing time-related stress, the emotion engine can detect this and prioritize less crowded routes, while also suggesting cafes or parks along the way for relaxation. In this process, congestion information and facility availability data from external sources are incorporated to provide the user with a highly accurate plan.

[0126] Through this mechanism, the present invention can smoothly provide travel plans that take into account both the individual needs and real-time emotional states of users, thereby reducing stress and contributing to the revitalization of the local economy.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] Users launch the application and enter personal profile information such as address, places of interest, family structure, favorite foods, and allergy information. It is important that this information is entered accurately, as it will be used for later personalization.

[0130] Step 2:

[0131] The device sends the profile information entered by the user to the server. The server receives this information and securely stores it in its database.

[0132] Step 3:

[0133] When traveling or moving around, users input data such as their destination for the day, the order of visits, budget, and the number of people traveling with them. This information forms the basis for creating the optimal route and schedule for that day.

[0134] Step 4:

[0135] Each time, the terminal sends this data to the server, which then prepares to process it.

[0136] Step 5:

[0137] The server uses external APIs to retrieve real-time traffic conditions, weather information, and facility availability at destinations. This data is immediately reflected in the user's travel plan.

[0138] Step 6:

[0139] The server uses a generation algorithm to integrate profile information, real-time data, and external real-time data to generate the optimal route and schedule. This plan aims to maximize convenience.

[0140] Step 7:

[0141] The device receives the route and schedule, and the user confirms it. If there are any changes or feedback instructed by the user, it sends them back to the server.

[0142] Step 8:

[0143] The device's emotion engine analyzes the user's voice, facial expressions, and actions to determine their emotional state. For example, if stress or fatigue is detected, that information is sent to the server.

[0144] Step 9:

[0145] The server re-executes the generation algorithm based on data from the emotion engine, reconfiguring the route and schedule to suit the user's emotions. This makes it possible to provide the user with the optimal travel experience.

[0146] Step 10:

[0147] The server retrieves data on local events and places of interest, and suggests places that might interest the user based on their emotional state. This provides enjoyment and relaxation, and contributes to the revitalization of the local economy.

[0148] Thus, the present invention provides users with a personalized and comfortable travel experience through dynamic route generation that takes user emotions into consideration.

[0149] (Example 2)

[0150] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0151] Conventional travel plan generation systems generate plans considering user profiles and real-time external information, but they struggle to incorporate the user's emotional state. As a result, there is a challenge in providing appropriate support when users experience stress or anxiety during their travels. Furthermore, they are not sufficient in effectively utilizing region-specific information to provide plans based on the user's interests and concerns.

[0152] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0153] In this invention, the server includes means for receiving user characteristic information and storing it on a recording medium, means including a computation method for dynamically detecting the user's emotional state and reconstructing the route and schedule based on it, and means for providing information based on the user's interests through data linkage with external organizations to revitalize the local economy. This makes it possible to realize a more detailed travel experience that is tailored to the user's emotions and interests, thereby reducing stress and revitalizing the local economy.

[0154] A "user" is an entity that uses the system to receive travel plans and possesses individual profile information and emotional states.

[0155] A "server" is a central computing device that receives user information, retrieves external information, and generates and reconfigures the optimal travel route and schedule.

[0156] "Characteristic information" refers to data necessary for customizing travel plans, such as personal information, preferences, and travel purposes provided by the user.

[0157] "Emotional state" refers to the user's psychological or physical condition, which is detected through the analysis of voice, facial expressions, and bodily data.

[0158] A "recording medium" refers to a device or system for storing data, and is used to retain user characteristic information and past plans.

[0159] "Real-time external information" refers to dynamically changing data, including current traffic conditions, weather information, facility availability, and local event information, which are necessary for optimizing travel plans.

[0160] "Calculation methods" refer to algorithms and processes for calculating the optimal travel route and schedule based on user characteristics, emotional state, and external information.

[0161] "Revitalizing the local economy" refers to using this system to provide region-specific information, thereby promoting consumption and tourism within the region and supporting economic development.

[0162] In this system, users first install a dedicated application on their smart device. The application has the function of receiving characteristic information from the user and saving it to a storage medium. Users input detailed information about their travels and journeys, such as destinations, schedules, and budgets. This information is transmitted to the server in real time.

[0163] The server utilizes a cloud computing environment to deliver powerful computing capabilities. It obtains real-time traffic, weather, and facility availability information from external sources via APIs. This includes transportation service information, weather data, and congestion levels at tourist facilities. Using this data and sophisticated computational methods, the server generates optimal travel routes and schedules.

[0164] The device uses sensors to collect voice, facial, and physical data to detect the user's emotional state. This data is analyzed in real time to identify the user's emotional state. This information is sent to a server, which dynamically reconfigures the travel plan based on it. For example, if the user is feeling stressed, a relaxing facility might be incorporated into the route.

[0165] For example, to ensure that busy business travelers can travel with peace of mind, the system can suggest routes that avoid congestion and recommend relaxing cafes or parks along the way. In this process, the server reflects real-time information to provide a highly accurate plan.

[0166] An example of a prompt message is: "Please suggest a relaxing sightseeing plan for the user. The conditions are: sunny weather, budget of 10,000 yen or less, and destination of Tokyo." This format can be used to instruct the AI ​​model.

[0167] In this way, an intelligent system combining servers and terminals allows users to receive travel plans tailored to their individual emotions and needs, thereby reducing stress and contributing to the revitalization of the local economy.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The user launches the application on their smart device and enters personal information and travel-related information (destination, schedule, budget, etc.). The input data is sent from the device to the server. The server stores this data on a storage medium and prepares it for later use in generating travel plans.

[0171] Step 2:

[0172] The server obtains real-time traffic information, weather information, and facility availability information from external sources via APIs. This includes operating schedules, weather forecasts, and congestion levels. The acquired data is analyzed using computational methods and integrated with user input data to generate the optimal route and schedule. The generated plan is kept as a provisional plan.

[0173] Step 3:

[0174] While the user is on the move, the device uses its built-in sensors to collect the user's voice, facial expressions, and physical data in real time. Based on this information, the device analyzes the user's emotional state. The analysis results are immediately transmitted to the server and recorded in a database as the user's emotional state.

[0175] Step 4:

[0176] The server re-evaluates the generated travel plan based on the received emotional state data. If necessary, facilities and services appropriate to the emotional state are added to the plan. For example, if the user is feeling anxious, a relaxing cafe might be added to the route. The restructured plan is then sent to the user's device.

[0177] Step 5:

[0178] The user confirms the final travel plan notified on their device and begins their journey. The user can input evaluations and feedback at any time during the journey, which are sent to the server via their device. The server uses this feedback to further refine the plan and improve the user experience.

[0179] Through the processing steps described above, it becomes possible to provide users with stress-free and optimized travel plans that are tailored to their emotions.

[0180] (Application Example 2)

[0181] 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".

[0182] In modern life, individual users often experience stress associated with travel. In particular, traffic congestion and navigating unfamiliar areas make finding effective travel routes difficult, which can be a source of stress. Furthermore, providing personalized travel plans that adapt to changes in a user's emotional state during travel is currently challenging with existing technology. Therefore, the challenge lies in realizing the provision of real-time travel plans that respond to the user's emotions.

[0183] 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.

[0184] In this invention, the server includes means for receiving user profile data and storing it in a storage device, means for receiving purpose information and itinerary information entered by the user each time, and means for obtaining real-time travel information, weather information, and facility availability from external information sources. This makes it possible to dynamically regenerate routes and time allocations based on the user's emotional state.

[0185] "User profile data" refers to the basic information of each user, including information such as age, occupation, and usual means of transportation.

[0186] "Purpose information" refers to information about the destination or purpose that the user sets when traveling.

[0187] "Itinerary information" refers to information about the schedule and time allocation that a user plans for their travels.

[0188] A "memory device" is a mechanism for electronically storing information, and is used to accumulate information in databases such as servers.

[0189] "Real-time travel information" refers to information that allows users to instantly obtain information on the operation of available transportation methods and road congestion levels.

[0190] "Climate information" refers to environmental information such as weather forecasts, temperature, and precipitation that may affect users' travel.

[0191] "Facility availability" refers to information about the operating status and level of congestion of a facility that a user intends to visit.

[0192] The "generation method" is an algorithm that calculates the optimal travel route and time allocation based on user input data and information obtained from external sources.

[0193] "Emotional state" refers to a user's mental response, encompassing psychological states such as joy, anger, sadness, and happiness.

[0194] "Dynamic route and time allocation regeneration" is a process that reconfigures travel routes and schedules in real time based on the detected emotional state of the user.

[0195] This invention begins with the user inputting destination and itinerary information via a smartphone or other digital device. The device transmits this information to a server, along with the user's profile data. The server stores this data in its storage device.

[0196] The server retrieves travel information, weather information, and facility availability from external sources in real time. This process requires an internet connection to ensure that the information is always up-to-date. Using this data, the server calculates the optimal travel route and time allocation that matches the user's conditions, using a generation method on the server.

[0197] The system collects voice, facial expressions, and physical data through sensors on the device while the user is on the move, and analyzes their emotional state. This analysis utilizes software called an emotion engine. This makes it possible to understand how the user's emotions are changing in real time.

[0198] If the emotion engine determines that the user is experiencing stress, the server immediately regenerates the route and time allocation. This may include adding relaxing spots. Ultimately, the user is notified of an optimized travel plan through their device. This process is dynamically repeated and continuously updated to reflect the user's state.

[0199] As a concrete example, a business user on a business trip inputs using their smartphone that they need to travel from Shinjuku to Shibuya. While they would normally choose the train as their mode of transport, the server considers congestion information and suggests a less stressful route. It also suggests a relaxing cafe along the way.

[0200] An example of a prompt in a generative AI model is, "Generate a travel plan that suggests places where you can relax when you feel stressed while traveling for a business trip." Based on this prompt, the generative AI model will suggest a relevant travel plan.

[0201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0202] Step 1:

[0203] The user uses a terminal to input information about their travel purpose and itinerary. This data includes destination, dates, and budget. This data is then transmitted from the terminal to the server.

[0204] Step 2:

[0205] The server stores the received user profile data and input data in storage. This information helps analyze the user's past movement patterns and preferences. At this point, the entered data is recorded in the database.

[0206] Step 3:

[0207] The server retrieves real-time travel information, weather information, and facility availability from external sources. This data is obtained via API and processed within the server. This allows the server to maintain up-to-date traffic and weather information.

[0208] Step 4:

[0209] The server generates the optimal travel route and time allocation based on user information and external information entered using a generation method. During this process, an algorithm is applied to compare and select multiple route plans. The output is a route and schedule proposed to the user.

[0210] Step 5:

[0211] While in motion, the device uses various sensors to collect data on the user's voice, facial expressions, and body language. This data is sent to an emotion engine to analyze the user's emotional state. This analysis identifies the user's emotional state in real time.

[0212] Step 6:

[0213] The emotion engine analyzes the user's emotional state, and if it detects stress or fatigue, the server dynamically regenerates the route and time allocation. This generates a new plan that includes relaxing facilities and spots.

[0214] Step 7:

[0215] The device notifies the user of the newly generated travel plan, which includes recommendations such as relaxation spots tailored to their emotional state. Instructions for the user to proceed to the next step are provided immediately.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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".

[0232] This invention is a system for providing users with personalized travel plans. This system leverages the user's prior profile information to generate optimized routes and schedules, and dynamically reconfigures the plan in response to real-time changes in circumstances, thereby providing users with a stress-free travel experience.

[0233] First, users register profile information through the application, such as their address, favorite places, family structure, hobbies, favorite foods, allergy information, preferred mode of transportation, and payment method. This allows for personalization tailored to individual needs.

[0234] Next, for travel or daily commutes, users input information into the application such as their destination and order of activities for the day, budget, and the number of people traveling with them. This data is then sent from the device to the server, which initiates a real-time search based on this information.

[0235] The server retrieves real-time data from external sources, such as traffic conditions, weather conditions, and facility congestion. This information is combined with the user's profile information and data entered as needed, and a generation algorithm creates the optimal travel route and schedule plan.

[0236] This system can also provide users with a richer experience by incorporating local event information and recommended places to visit. This can contribute to the revitalization of the local economy.

[0237] For example, a user planning a family trip for the weekend would input several tourist spots they want to visit into the app. The system would then take into account the user's situation (traveling with children) and their preferred mode of transportation (car), prioritizing car routes and suggesting a schedule that includes a picnic in a park and a stop at a popular local restaurant. The suggested plan would reflect real-time traffic congestion and weather conditions, and could be adjusted multiple times in advance.

[0238] Thus, the present invention takes various factors into comprehensive consideration to enable convenient and less burdensome travel for the user.

[0239] The following describes the processing flow.

[0240] Step 1:

[0241] When a user launches the application, they first enter their address, favorite places, family structure, hobbies, favorite foods, allergy information, preferred mode of transportation, and payment method on an input screen. This information is saved as profile information.

[0242] Step 2:

[0243] The device connects to the server to organize the profile information entered by the user and send it to the database. The server receives this data and securely stores it in the database.

[0244] Step 3:

[0245] Users input data into the application each time they need to travel, such as the day of travel, destination, order of visits, budget, and number of people. This data is sent to the server separately from their profile information.

[0246] Step 4:

[0247] The server checks for data reception each time and collects necessary external information in real time. This external information includes traffic conditions, weather forecasts, and destination congestion information. The server obtains this information from external APIs.

[0248] Step 5:

[0249] The server integrates pre-registered profile information, user-entered data, and real-time data acquired from external sources, and uses a generation algorithm to generate the optimal travel route and schedule. During this process, the plan is adjusted based on factors such as traffic convenience, congestion levels, and user preferences.

[0250] Step 6:

[0251] The server sends the generated route and schedule to the terminal. The user can view the plan details and schedule on the terminal. If the user wishes, they can request the server to regenerate the route through feedback.

[0252] Step 7:

[0253] The AI ​​agent generates new suggestions based on external information and user feedback. These new suggestions are then presented to the user via the server, allowing the user to review and decide on the latest suggestions.

[0254] Step 8:

[0255] The server collects local event information and points of interest through collaboration with external organizations and integrates them into the user's plan. This provides users with a rich, locally-focused experience.

[0256] (Example 1)

[0257] 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."

[0258] In modern society, planning a trip involves the time-consuming task of individually researching real-time information such as traffic conditions and weather, and then constructing the optimal route and schedule that takes this into account. Furthermore, dynamically reconfiguring the plan in response to changing circumstances during the journey is required, which is difficult to do manually. Additionally, suggestions for local events and points of interest are rarely provided in an integrated manner, limiting the user's travel experience. Therefore, a system is needed that can solve these problems and provide users with a stress-free travel experience.

[0259] 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.

[0260] In this invention, the server includes means for receiving general user information and storing it in an information collection, means for receiving destination and action plan information entered by the user from time to time, and means for acquiring real-time travel data, environmental data, and facility status information from external information sources. This enables the dynamic generation of personalized and optimal travel routes and plans according to the user's purpose, and their reconfiguration in response to real-time circumstances.

[0261] "User general information" refers to a series of personal data that users register in the system, such as their address, hobbies and preferences, and family structure.

[0262] An "information collection" refers to a database or storage system used by a system to store and manage users' general information and other related data.

[0263] "Destination and activity plan information entered as needed" refers to detailed information such as the necessary destinations, order of visits, and budget that the user enters when traveling.

[0264] "External information sources" refer to public or private data providers that provide real-time data such as traffic conditions, weather conditions, and facility congestion levels.

[0265] "Real-time travel data" refers to information that is acquired and updated instantly based on the user's location, such as current traffic conditions and travel time.

[0266] "Environmental data" refers to information that includes natural conditions related to travel, such as weather conditions, temperature, and precipitation on the day of travel.

[0267] "Facility status information" refers to the latest information regarding the congestion level, availability, and operating hours of the facility you plan to visit.

[0268] "Dynamic generation" refers to the process of modifying and restructuring travel routes and schedules in real time in response to changing environments and circumstances.

[0269] This invention relates to a system that provides users with personalized travel plans. This system makes user travel smoother and less burdensome.

[0270] Users register their personal information, such as address, hobbies, family structure, and favorite foods, through the application. This information is sent from the device to the server and stored in an information repository on the server. The server uses this general information to form a foundation for developing travel plans that are best suited to the user's needs.

[0271] For travel and daily commutes, users input destinations, itinerary, budget, and the number of companions into the application. This information is also transmitted to the server via the device. The server obtains real-time data such as traffic conditions, weather conditions, and facility congestion from external sources. Public API services and private data provision platforms are used for this information collection.

[0272] The server combines acquired real-time travel data, environmental data, and facility status information with the user's profile information, and uses a generated AI model to create the optimal travel route and schedule. This AI model dynamically optimizes the plan by taking into account user-specified conditions and real-time data, such as avoiding traffic congestion and considering weather conditions.

[0273] As a concrete example, consider a user planning a weekend family trip. This user enters the tourist destinations they want to visit and the restaurants they want to stop at along the way into the application. The server optimizes the route considering car travel and incorporates parks suitable for picnics and popular restaurants into the schedule as needed. Because the proposed plan takes real-time traffic conditions and weather information into account, the user can enjoy their trip with peace of mind.

[0274] Furthermore, the proposed travel plan can be reconstructed any number of times based on user feedback. An example of a prompt using the generative AI model is: "User: I would like to visit tourist spots B and C in the afternoon. I would like to have lunch at cafe A, so please suggest a schedule that fits that."

[0275] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0276] Step 1:

[0277] Users enter profile information through the application. This information includes address, hobbies, family structure, and allergy information. The device converts this information into a digital format, structures it electronically, and sends it to the server. This information is stored in the server's data repository and associated with the user's personal ID.

[0278] Step 2:

[0279] The user enters details about a specific travel plan into the application. This includes the destination for the day, the order of visits, the budget, and information about travel companions. The terminal receives these details and sends them to the server as a temporary request. The server parses the received data, tags the entered travel plan with a unique identifier, and stores it.

[0280] Step 3:

[0281] The server collects necessary real-time data from external sources. Here, APIs are used to obtain traffic conditions, weather conditions, facility congestion, and other data. The server receives this raw data and performs formatting and normalization to combine it with user input data. This process integrates real-time environmental data with travel planning.

[0282] Step 4:

[0283] The server drives a generative AI model using integrated data to generate an optimal travel route and schedule. In this step, a dynamic plan is formulated based on real-time data while considering the characteristics of each user. The generative AI model algorithmically calculates multiple routes under given conditions and selects the optimal one from them. The output result is an optimized travel schedule.

[0284] Step 5:

[0285] The server sends the generated schedule to the terminal and presents it to the user on the application. The user checks the presented plan and inputs feedback if necessary. For example, specific spots can be added or time adjustments can be requested. This feedback is sent back to the server, triggering the process of regenerating the plan. As a result, the user can finally obtain a travel plan that best suits their preferences.

[0286] (Application Example 1)

[0287] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0288] In recent years, with the progress of urbanization, traffic congestion and overcrowding have become more serious, making it difficult for individual citizens to move efficiently and comfortably. In addition, it is difficult to efficiently obtain region-specific information, and there is a lack of providing rich life experiences. Conventional methods have the problem that it is difficult to provide an optimal travel plan in real time while considering individual situations and preferences.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0290] In this invention, the server includes means for receiving user attribute information and storing it in a data storage device, means for receiving destination and plan information from the user based on real-time input, and means for obtaining the latest travel information, weather information, and facility availability from external information sources. This makes it possible to provide travel plans optimized for individual citizens in real time.

[0291] "User attribute information" refers to information about the user as an individual, such as address, interests, and preferred modes of transportation, which is necessary for personalizing travel plans.

[0292] A "data storage device" is an information processing device that stores user attribute information, movement history, and other data, and allows users to retrieve it as needed.

[0293] "Occasional input information" refers to specific information that users enter each time, such as destinations and plans, and is information that should be reflected in daily travel and trip planning.

[0294] "External information sources" refer to various data sources that provide real-time information such as traffic, weather, and facility usage.

[0295] "Route and schedule" refers to the optimal travel route at a specific time and the schedule based on it.

[0296] "Responses" refer to information collected as evaluations, opinions, or feedback that users give to the provided plan or to the application.

[0297] "Real-time information for the entire city" refers to information that encompasses traffic conditions, events, weather, and other factors that change moment by moment throughout the entire city.

[0298] "Information sharing" is a process that involves exchanging data with external organizations to connect various services and information, enabling the provision of more advanced information.

[0299] "Regional industries" refer to a collection of businesses and service industries that conduct economic activities in a specific region, and their revitalization contributes to the economic development of that region.

[0300] To realize this system, the user's smart device and the server play a central role. Users input their attribute information in advance using an application on their smartphone and store it in a data storage device. When planning travel in real time, they transmit destination and plan information from their smart device. The server is responsible for obtaining the latest travel information, weather information, and facility usage status from external sources and generating the optimal route and schedule based on this information.

[0301] The server performs multi-stage data processing and calculations based on the acquired data. In particular, it uses complex algorithms to generate dynamic and optimized travel plans by combining user attribute information with external real-time information. The software used includes Python and various APIs to enable real-time data processing.

[0302] The generated travel plan is notified to the user's smart device, and if the user responds, the server regenerates the plan based on that response. This process ensures that the user always has a travel experience that is up-to-date.

[0303] As a concrete example, a user planning a sightseeing trip within a city with their family enters information using a smartphone application, including destination, desired visit time, and budget. Based on this information, the system obtains real-time traffic and weather data to generate and provide an optimal travel plan. It also notifies the user of suggested sightseeing spots and event information, providing a richer experience.

[0304] As an example of a prompt sentence for the generation AI model, it can be input in the form of "Please propose several tourist destinations where you can enjoy with your family this afternoon. The departure point is the central station, and please consider the weather and congestion situation."

[0305] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0306] Step 1:

[0307] The user uses a smart device to input attribute information, and the terminal stores this information in the data storage device. As inputs, there are the user's address, interests, preference for means of transportation, etc., which are accumulated as basic data for providing a personalized experience.

[0308] Step 2:

[0309] The user inputs the current destination and planned information into the terminal, and the terminal sends this information to the server. Specifically, it includes the place, time, budget, etc. to be visited, which becomes the input data for the next optimal route creation.

[0310] Step 3:

[0311] The server obtains the latest travel information, weather information, and facility availability from external information sources. In this step, traffic information APIs and weather information APIs are utilized to accumulate real-time data and prepare to combine it with the user's current situation.

[0312] Step 4:

[0313] The server inputs the user's attribute information, occasional input information, and external real-time information into the generation AI model to generate an optimal route and schedule. Here, complex data processing and algorithm operations are performed using the generation AI model, and a dynamically optimized travel plan is output. [[ID= ]]

[0314] Step 5:

[0315] The generated travel plan is sent from the server to the terminal. The notification the user receives includes recommended routes, places to visit, and event information, which the user can use to begin their journey.

[0316] Step 6:

[0317] Based on user feedback, the device sends information to the server, which then uses the feedback information to regenerate the optimal route using an AI model. This process ensures that users always receive the latest plan that adapts to changing circumstances.

[0318] 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.

[0319] This invention is a system for providing users with personalized travel plans, and by incorporating an emotion engine, it enables more detailed planning that dynamically reflects the user's emotions. This system utilizes the user's pre-registered profile information and external data acquired in real time to incorporate the user's emotional state, thereby providing a more comfortable and stress-free travel experience.

[0320] Users enter their basic information through the application, which is then stored on the server as profile information. When traveling, users enter information such as desired destinations, dates, and budget, and this information is also processed via the server. The server obtains real-time information from external sources, such as traffic information, weather forecasts, and facility congestion levels, to generate the optimal travel route and schedule that suits the user's conditions.

[0321] The emotion engine analyzes voice, facial expressions, and physical data acquired from the user's device while on the move to identify the user's emotional state. This information is transferred to a server, where a generation algorithm reconstructs a plan that is more emotionally appropriate. For example, if the user is feeling stressed, the route may be designed to include relaxing locations or events.

[0322] For example, if a user on a business trip is experiencing time-related stress, the emotion engine can detect this and prioritize less crowded routes, while also suggesting cafes or parks along the way for relaxation. In this process, congestion information and facility availability data from external sources are incorporated to provide the user with a highly accurate plan.

[0323] Through this mechanism, the present invention can smoothly provide travel plans that take into account both the individual needs and real-time emotional states of users, thereby reducing stress and contributing to the revitalization of the local economy.

[0324] The following describes the processing flow.

[0325] Step 1:

[0326] Users launch the application and enter personal profile information such as address, places of interest, family structure, favorite foods, and allergy information. It is important that this information is entered accurately, as it will be used for later personalization.

[0327] Step 2:

[0328] The device sends the profile information entered by the user to the server. The server receives this information and securely stores it in its database.

[0329] Step 3:

[0330] When traveling or moving around, users input data such as their destination for the day, the order of visits, budget, and the number of people traveling with them. This information forms the basis for creating the optimal route and schedule for that day.

[0331] Step 4:

[0332] Each time, the terminal sends this data to the server, which then prepares to process it.

[0333] Step 5:

[0334] The server uses external APIs to retrieve real-time traffic conditions, weather information, and facility availability at destinations. This data is immediately reflected in the user's travel plan.

[0335] Step 6:

[0336] The server uses a generation algorithm to integrate profile information, real-time data, and external real-time data to generate the optimal route and schedule. This plan aims to maximize convenience.

[0337] Step 7:

[0338] The device receives the route and schedule, and the user confirms it. If there are any changes or feedback instructed by the user, it sends them back to the server.

[0339] Step 8:

[0340] The device's emotion engine analyzes the user's voice, facial expressions, and actions to determine their emotional state. For example, if stress or fatigue is detected, that information is sent to the server.

[0341] Step 9:

[0342] The server re-executes the generation algorithm based on data from the emotion engine, reconfiguring the route and schedule to suit the user's emotions. This makes it possible to provide the user with the optimal travel experience.

[0343] Step 10:

[0344] The server retrieves data on local events and places of interest, and suggests places that might interest the user based on their emotional state. This provides enjoyment and relaxation, and contributes to the revitalization of the local economy.

[0345] Thus, the present invention provides users with a personalized and comfortable travel experience through dynamic route generation that takes user emotions into consideration.

[0346] (Example 2)

[0347] 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".

[0348] Conventional travel plan generation systems generate plans considering user profiles and real-time external information, but they struggle to incorporate the user's emotional state. As a result, there is a challenge in providing appropriate support when users experience stress or anxiety during their travels. Furthermore, they are not sufficient in effectively utilizing region-specific information to provide plans based on the user's interests and concerns.

[0349] 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.

[0350] In this invention, the server includes means for receiving user characteristic information and storing it on a recording medium, means including a computation method for dynamically detecting the user's emotional state and reconstructing the route and schedule based on it, and means for providing information based on the user's interests through data linkage with external organizations to revitalize the local economy. This makes it possible to realize a more detailed travel experience that is tailored to the user's emotions and interests, thereby reducing stress and revitalizing the local economy.

[0351] A "user" is an entity that uses the system to receive travel plans and possesses individual profile information and emotional states.

[0352] A "server" is a central computing device that receives user information, retrieves external information, and generates and reconfigures the optimal travel route and schedule.

[0353] "Characteristic information" refers to data necessary for customizing travel plans, such as personal information, preferences, and travel purposes provided by the user.

[0354] "Emotional state" refers to the user's psychological or physical condition, which is detected through the analysis of voice, facial expressions, and bodily data.

[0355] A "recording medium" refers to a device or system for storing data, and is used to retain user characteristic information and past plans.

[0356] "Real-time external information" refers to dynamically changing data, including current traffic conditions, weather information, facility availability, and local event information, which are necessary for optimizing travel plans.

[0357] "Calculation methods" refer to algorithms and processes for calculating the optimal travel route and schedule based on user characteristics, emotional state, and external information.

[0358] "Revitalizing the local economy" refers to using this system to provide region-specific information, thereby promoting consumption and tourism within the region and supporting economic development.

[0359] In this system, users first install a dedicated application on their smart device. The application has the function of receiving characteristic information from the user and saving it to a storage medium. Users input detailed information about their travels and journeys, such as destinations, schedules, and budgets. This information is transmitted to the server in real time.

[0360] The server utilizes a cloud computing environment to deliver powerful computing capabilities. It obtains real-time traffic, weather, and facility availability information from external sources via APIs. This includes transportation service information, weather data, and congestion levels at tourist facilities. Using this data and sophisticated computational methods, the server generates optimal travel routes and schedules.

[0361] The device uses sensors to collect voice, facial, and physical data to detect the user's emotional state. This data is analyzed in real time to identify the user's emotional state. This information is sent to a server, which dynamically reconfigures the travel plan based on it. For example, if the user is feeling stressed, a relaxing facility might be incorporated into the route.

[0362] For example, to ensure that busy business travelers can travel with peace of mind, the system can suggest routes that avoid congestion and recommend relaxing cafes or parks along the way. In this process, the server reflects real-time information to provide a highly accurate plan.

[0363] An example of a prompt message is: "Please suggest a relaxing sightseeing plan for the user. The conditions are: sunny weather, budget of 10,000 yen or less, and destination of Tokyo." This format can be used to instruct the AI ​​model.

[0364] In this way, an intelligent system combining servers and terminals allows users to receive travel plans tailored to their individual emotions and needs, thereby reducing stress and contributing to the revitalization of the local economy.

[0365] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0366] Step 1:

[0367] The user launches the application on their smart device and enters personal information and travel-related information (destination, schedule, budget, etc.). The input data is sent from the device to the server. The server stores this data on a storage medium and prepares it for later use in generating travel plans.

[0368] Step 2:

[0369] The server obtains real-time traffic information, weather information, and facility availability information from external sources via APIs. This includes operating schedules, weather forecasts, and congestion levels. The acquired data is analyzed using computational methods and integrated with user input data to generate the optimal route and schedule. The generated plan is kept as a provisional plan.

[0370] Step 3:

[0371] While the user is on the move, the device uses its built-in sensors to collect the user's voice, facial expressions, and physical data in real time. Based on this information, the device analyzes the user's emotional state. The analysis results are immediately transmitted to the server and recorded in a database as the user's emotional state.

[0372] Step 4:

[0373] The server re-evaluates the generated travel plan based on the received emotional state data. If necessary, facilities and services appropriate to the emotional state are added to the plan. For example, if the user is feeling anxious, a relaxing cafe might be added to the route. The restructured plan is then sent to the user's device.

[0374] Step 5:

[0375] The user confirms the final travel plan notified on their device and begins their journey. The user can input evaluations and feedback at any time during the journey, which are sent to the server via their device. The server uses this feedback to further refine the plan and improve the user experience.

[0376] Through the processing steps described above, it becomes possible to provide users with stress-free and optimized travel plans that are tailored to their emotions.

[0377] (Application Example 2)

[0378] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0379] In modern life, individual users often experience stress associated with travel. In particular, traffic congestion and navigating unfamiliar areas make finding effective travel routes difficult, which can be a source of stress. Furthermore, providing personalized travel plans that adapt to changes in a user's emotional state during travel is currently challenging with existing technology. Therefore, the challenge lies in realizing the provision of real-time travel plans that respond to the user's emotions.

[0380] 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.

[0381] In this invention, the server includes means for receiving user profile data and storing it in a storage device, means for receiving purpose information and itinerary information entered by the user each time, and means for obtaining real-time travel information, weather information, and facility availability from external information sources. This makes it possible to dynamically regenerate routes and time allocations based on the user's emotional state.

[0382] "User profile data" refers to the basic information of each user, including information such as age, occupation, and usual means of transportation.

[0383] "Purpose information" refers to information about the destination or purpose that the user sets when traveling.

[0384] "Itinerary information" refers to information about the schedule and time allocation that a user plans for their travels.

[0385] A "memory device" is a mechanism for electronically storing information, and is used to accumulate information in databases such as servers.

[0386] "Real-time travel information" refers to information that allows users to instantly obtain information on the operation of available transportation methods and road congestion levels.

[0387] "Climate information" refers to environmental information such as weather forecasts, temperature, and precipitation that may affect users' travel.

[0388] "Facility availability" refers to information about the operating status and level of congestion of a facility that a user intends to visit.

[0389] The "generation method" is an algorithm that calculates the optimal travel route and time allocation based on user input data and information obtained from external sources.

[0390] "Emotional state" refers to a user's mental response, encompassing psychological states such as joy, anger, sadness, and happiness.

[0391] "Dynamic route and time allocation regeneration" is a process that reconfigures travel routes and schedules in real time based on the detected emotional state of the user.

[0392] This invention begins with the user inputting destination and itinerary information via a smartphone or other digital device. The device transmits this information to a server, along with the user's profile data. The server stores this data in its storage device.

[0393] The server retrieves travel information, weather information, and facility availability from external sources in real time. This process requires an internet connection to ensure that the information is always up-to-date. Using this data, the server calculates the optimal travel route and time allocation that matches the user's conditions, using a generation method on the server.

[0394] The system collects voice, facial expressions, and physical data through sensors on the device while the user is on the move, and analyzes their emotional state. This analysis utilizes software called an emotion engine. This makes it possible to understand how the user's emotions are changing in real time.

[0395] If the emotion engine determines that the user is experiencing stress, the server immediately regenerates the route and time allocation. This may include adding relaxing spots. Ultimately, the user is notified of an optimized travel plan through their device. This process is dynamically repeated and continuously updated to reflect the user's state.

[0396] As a concrete example, a business user on a business trip inputs using their smartphone that they need to travel from Shinjuku to Shibuya. While they would normally choose the train as their mode of transport, the server considers congestion information and suggests a less stressful route. It also suggests a relaxing cafe along the way.

[0397] An example of a prompt in a generative AI model is, "Generate a travel plan that suggests places where you can relax when you feel stressed while traveling for a business trip." Based on this prompt, the generative AI model will suggest a relevant travel plan.

[0398] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0399] Step 1:

[0400] The user uses a terminal to input information about their travel purpose and itinerary. This data includes destination, dates, and budget. This data is then transmitted from the terminal to the server.

[0401] Step 2:

[0402] The server stores the received user profile data and input data in storage. This information helps analyze the user's past movement patterns and preferences. At this point, the entered data is recorded in the database.

[0403] Step 3:

[0404] The server retrieves real-time travel information, weather information, and facility availability from external sources. This data is obtained via API and processed within the server. This allows the server to maintain up-to-date traffic and weather information.

[0405] Step 4:

[0406] The server generates the optimal travel route and time allocation based on user information and external information entered using a generation method. During this process, an algorithm is applied to compare and select multiple route plans. The output is a route and schedule proposed to the user.

[0407] Step 5:

[0408] While in motion, the device uses various sensors to collect data on the user's voice, facial expressions, and body language. This data is sent to an emotion engine to analyze the user's emotional state. This analysis identifies the user's emotional state in real time.

[0409] Step 6:

[0410] The emotion engine analyzes the user's emotional state, and if it detects stress or fatigue, the server dynamically regenerates the route and time allocation. This generates a new plan that includes relaxing facilities and spots.

[0411] Step 7:

[0412] The device notifies the user of the newly generated travel plan, which includes recommendations such as relaxation spots tailored to their emotional state. Instructions for the user to proceed to the next step are provided immediately.

[0413] 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.

[0414] 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.

[0415] 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.

[0416] [Third Embodiment]

[0417] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0418] 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.

[0419] 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).

[0420] 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.

[0421] 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.

[0422] 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).

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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".

[0429] This invention is a system for providing users with personalized travel plans. This system leverages the user's prior profile information to generate optimized routes and schedules, and dynamically reconfigures the plan in response to real-time changes in circumstances, thereby providing users with a stress-free travel experience.

[0430] First, users register profile information through the application, such as their address, favorite places, family structure, hobbies, favorite foods, allergy information, preferred mode of transportation, and payment method. This allows for personalization tailored to individual needs.

[0431] Next, for travel or daily commutes, users input information into the application such as their destination and order of activities for the day, budget, and the number of people traveling with them. This data is then sent from the device to the server, which initiates a real-time search based on this information.

[0432] The server retrieves real-time data from external sources, such as traffic conditions, weather conditions, and facility congestion. This information is combined with the user's profile information and data entered as needed, and a generation algorithm creates the optimal travel route and schedule plan.

[0433] This system can also provide users with a richer experience by incorporating local event information and recommended places to visit. This can contribute to the revitalization of the local economy.

[0434] For example, a user planning a family trip for the weekend would input several tourist spots they want to visit into the app. The system would then take into account the user's situation (traveling with children) and their preferred mode of transportation (car), prioritizing car routes and suggesting a schedule that includes a picnic in a park and a stop at a popular local restaurant. The suggested plan would reflect real-time traffic congestion and weather conditions, and could be adjusted multiple times in advance.

[0435] Thus, the present invention takes various factors into comprehensive consideration to enable convenient and less burdensome travel for the user.

[0436] The following describes the processing flow.

[0437] Step 1:

[0438] When a user launches the application, they first enter their address, favorite places, family structure, hobbies, favorite foods, allergy information, preferred mode of transportation, and payment method on an input screen. This information is saved as profile information.

[0439] Step 2:

[0440] The device connects to the server to organize the profile information entered by the user and send it to the database. The server receives this data and securely stores it in the database.

[0441] Step 3:

[0442] Users input data into the application each time they need to travel, such as the day of travel, destination, order of visits, budget, and number of people. This data is sent to the server separately from their profile information.

[0443] Step 4:

[0444] The server checks for data reception each time and collects necessary external information in real time. This external information includes traffic conditions, weather forecasts, and destination congestion information. The server obtains this information from external APIs.

[0445] Step 5:

[0446] The server integrates pre-registered profile information, user-entered data, and real-time data acquired from external sources, and uses a generation algorithm to generate the optimal travel route and schedule. During this process, the plan is adjusted based on factors such as traffic convenience, congestion levels, and user preferences.

[0447] Step 6:

[0448] The server sends the generated route and schedule to the terminal. The user can view the plan details and schedule on the terminal. If the user wishes, they can request the server to regenerate the route through feedback.

[0449] Step 7:

[0450] The AI ​​agent generates new suggestions based on external information and user feedback. These new suggestions are then presented to the user via the server, allowing the user to review and decide on the latest suggestions.

[0451] Step 8:

[0452] The server collects local event information and points of interest through collaboration with external organizations and integrates them into the user's plan. This provides users with a rich, locally-focused experience.

[0453] (Example 1)

[0454] 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."

[0455] In modern society, planning a trip involves the time-consuming task of individually researching real-time information such as traffic conditions and weather, and then constructing the optimal route and schedule that takes this into account. Furthermore, dynamically reconfiguring the plan in response to changing circumstances during the journey is required, which is difficult to do manually. Additionally, suggestions for local events and points of interest are rarely provided in an integrated manner, limiting the user's travel experience. Therefore, a system is needed that can solve these problems and provide users with a stress-free travel experience.

[0456] 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.

[0457] In this invention, the server includes means for receiving general user information and storing it in an information collection, means for receiving destination and action plan information entered by the user from time to time, and means for acquiring real-time travel data, environmental data, and facility status information from external information sources. This enables the dynamic generation of personalized and optimal travel routes and plans according to the user's purpose, and their reconfiguration in response to real-time circumstances.

[0458] "User general information" refers to a series of personal data that users register in the system, such as their address, hobbies and preferences, and family structure.

[0459] An "information collection" refers to a database or storage system used by a system to store and manage users' general information and other related data.

[0460] "Destination and activity plan information entered as needed" refers to detailed information such as the necessary destinations, order of visits, and budget that the user enters when traveling.

[0461] "External information sources" refer to public or private data providers that provide real-time data such as traffic conditions, weather conditions, and facility congestion levels.

[0462] "Real-time travel data" refers to information that is acquired and updated instantly based on the user's location, such as current traffic conditions and travel time.

[0463] "Environmental data" refers to information that includes natural conditions related to travel, such as weather conditions, temperature, and precipitation on the day of travel.

[0464] "Facility status information" refers to the latest information regarding the congestion level, availability, and operating hours of the facility you plan to visit.

[0465] "Dynamic generation" refers to the process of modifying and restructuring travel routes and schedules in real time in response to changing environments and circumstances.

[0466] This invention relates to a system that provides users with personalized travel plans. This system makes user travel smoother and less burdensome.

[0467] Users register their personal information, such as address, hobbies, family structure, and favorite foods, through the application. This information is sent from the device to the server and stored in an information repository on the server. The server uses this general information to form a foundation for developing travel plans that are best suited to the user's needs.

[0468] For travel and daily commutes, users input destinations, itinerary, budget, and the number of companions into the application. This information is also transmitted to the server via the device. The server obtains real-time data such as traffic conditions, weather conditions, and facility congestion from external sources. Public API services and private data provision platforms are used for this information collection.

[0469] The server combines acquired real-time travel data, environmental data, and facility status information with the user's profile information, and uses a generated AI model to create the optimal travel route and schedule. This AI model dynamically optimizes the plan by taking into account user-specified conditions and real-time data, such as avoiding traffic congestion and considering weather conditions.

[0470] As a concrete example, consider a user planning a weekend family trip. This user enters the tourist destinations they want to visit and the restaurants they want to stop at along the way into the application. The server optimizes the route considering car travel and incorporates parks suitable for picnics and popular restaurants into the schedule as needed. Because the proposed plan takes real-time traffic conditions and weather information into account, the user can enjoy their trip with peace of mind.

[0471] Furthermore, the proposed travel plan can be reconstructed any number of times based on user feedback. An example of a prompt using the generative AI model is: "User: I would like to visit tourist spots B and C in the afternoon. I would like to have lunch at cafe A, so please suggest a schedule that fits that."

[0472] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0473] Step 1:

[0474] Users enter profile information through the application. This information includes address, hobbies, family structure, and allergy information. The device converts this information into a digital format, structures it electronically, and sends it to the server. This information is stored in the server's data repository and associated with the user's personal ID.

[0475] Step 2:

[0476] The user enters details about a specific travel plan into the application. This includes the destination for the day, the order of visits, the budget, and information about travel companions. The terminal receives these details and sends them to the server as a temporary request. The server parses the received data, tags the entered travel plan with a unique identifier, and stores it.

[0477] Step 3:

[0478] The server collects necessary real-time data from external sources. Here, APIs are used to obtain traffic conditions, weather conditions, facility congestion, and other data. The server receives this raw data and performs formatting and normalization to combine it with user input data. This process integrates real-time environmental data with travel planning.

[0479] Step 4:

[0480] The server uses integrated data to drive a generative AI model that generates the optimal travel route and schedule. This step dynamically plans based on real-time data, taking into account the characteristics of each user. The generative AI model algorithmically calculates multiple routes under given conditions and selects the optimal one. The output is an optimized travel schedule.

[0481] Step 5:

[0482] The server sends the generated schedule to the terminal and presents it to the user on the application. The user reviews the presented plan and provides feedback as needed. For example, they can add specific spots or request adjustments to times. This feedback is sent back to the server, triggering the plan regeneration process. This allows the user to ultimately obtain a travel plan that best suits their preferences.

[0483] (Application Example 1)

[0484] 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."

[0485] In recent years, with the advancement of urbanization, traffic congestion and overcrowding have become serious problems, making it difficult for individual citizens to travel efficiently and comfortably. Furthermore, the inability to efficiently obtain region-specific information has resulted in a lack of enriching lifestyle experiences. Traditional methods face the challenge of providing optimal travel plans in real time while considering individual circumstances and preferences.

[0486] 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.

[0487] In this invention, the server includes means for receiving user attribute information and storing it in a data storage device, means for receiving destination and plan information from the user based on real-time input, and means for obtaining the latest travel information, weather information, and facility availability from external information sources. This makes it possible to provide travel plans optimized for individual citizens in real time.

[0488] "User attribute information" refers to information about the user as an individual, such as address, interests, and preferred modes of transportation, which is necessary for personalizing travel plans.

[0489] A "data storage device" is an information processing device that stores user attribute information, movement history, and other data, and allows users to retrieve it as needed.

[0490] "Occasional input information" refers to specific information that users enter each time, such as destinations and plans, and is information that should be reflected in daily travel and trip planning.

[0491] "External information sources" refer to various data sources that provide real-time information such as traffic, weather, and facility usage.

[0492] "Route and schedule" refers to the optimal travel route at a specific time and the schedule based on it.

[0493] "Responses" refer to information collected as evaluations, opinions, or feedback that users give to the provided plan or to the application.

[0494] "Real-time information for the entire city" refers to information that encompasses traffic conditions, events, weather, and other factors that change moment by moment throughout the entire city.

[0495] "Information sharing" is a process that involves exchanging data with external organizations to connect various services and information, enabling the provision of more advanced information.

[0496] "Regional industries" refer to a collection of businesses and service industries that conduct economic activities in a specific region, and their revitalization contributes to the economic development of that region.

[0497] To realize this system, the user's smart device and the server play a central role. Users input their attribute information in advance using an application on their smartphone and store it in a data storage device. When planning travel in real time, they transmit destination and plan information from their smart device. The server is responsible for obtaining the latest travel information, weather information, and facility usage status from external sources and generating the optimal route and schedule based on this information.

[0498] The server performs multi-stage data processing and calculations based on the acquired data. In particular, it uses complex algorithms to generate dynamic and optimized travel plans by combining user attribute information with external real-time information. The software used includes Python and various APIs to enable real-time data processing.

[0499] The generated travel plan is notified to the user's smart device, and if the user responds, the server regenerates the plan based on that response. This process ensures that the user always has a travel experience that is up-to-date.

[0500] As a concrete example, a user planning a sightseeing trip within a city with their family enters information using a smartphone application, including destination, desired visit time, and budget. Based on this information, the system obtains real-time traffic and weather data to generate and provide an optimal travel plan. It also notifies the user of suggested sightseeing spots and event information, providing a richer experience.

[0501] An example of a prompt message for the generating AI model would be: "Please suggest some tourist destinations that my family can enjoy this afternoon. We will be starting from the central station, and please take weather and crowd conditions into consideration."

[0502] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0503] Step 1:

[0504] Users input attribute information using smart devices, and the device stores this information in a data storage device. This input includes the user's address, interests, and preferred modes of transportation, and is stored as foundational data to provide personalized experiences.

[0505] Step 2:

[0506] The user inputs their destination and plan information into the terminal, which then sends this information to the server. Specifically, this includes the places they want to visit, the time, and their budget, and this becomes the input data for creating the next optimal route.

[0507] Step 3:

[0508] The server retrieves the latest travel information, weather information, and facility availability from external sources. In this step, it utilizes traffic information APIs and weather information APIs to collect real-time data and prepares to combine it with the user's current status.

[0509] Step 4:

[0510] The server inputs user attribute information, timely input information, and external real-time information into a generative AI model to generate the optimal route and schedule. Here, the generative AI model performs complex data processing and algorithmic calculations, outputting a dynamically optimized travel plan.

[0511] Step 5:

[0512] The generated travel plan is sent from the server to the terminal. The notification the user receives includes recommended routes, places to visit, and event information, which the user can use to begin their journey.

[0513] Step 6:

[0514] Based on user feedback, the device sends information to the server, which then uses the feedback information to regenerate the optimal route using an AI model. This process ensures that users always receive the latest plan that adapts to changing circumstances.

[0515] 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.

[0516] This invention is a system for providing users with personalized travel plans, and by incorporating an emotion engine, it enables more detailed planning that dynamically reflects the user's emotions. This system utilizes the user's pre-registered profile information and external data acquired in real time to incorporate the user's emotional state, thereby providing a more comfortable and stress-free travel experience.

[0517] Users enter their basic information through the application, which is then stored on the server as profile information. When traveling, users enter information such as desired destinations, dates, and budget, and this information is also processed via the server. The server obtains real-time information from external sources, such as traffic information, weather forecasts, and facility congestion levels, to generate the optimal travel route and schedule that suits the user's conditions.

[0518] The emotion engine analyzes voice, facial expressions, and physical data acquired from the user's device while on the move to identify the user's emotional state. This information is transferred to a server, where a generation algorithm reconstructs a plan that is more emotionally appropriate. For example, if the user is feeling stressed, the route may be designed to include relaxing locations or events.

[0519] For example, if a user on a business trip is experiencing time-related stress, the emotion engine can detect this and prioritize less crowded routes, while also suggesting cafes or parks along the way for relaxation. In this process, congestion information and facility availability data from external sources are incorporated to provide the user with a highly accurate plan.

[0520] Through this mechanism, the present invention can smoothly provide travel plans that take into account both the individual needs and real-time emotional states of users, thereby reducing stress and contributing to the revitalization of the local economy.

[0521] The following describes the processing flow.

[0522] Step 1:

[0523] Users launch the application and enter personal profile information such as address, places of interest, family structure, favorite foods, and allergy information. It is important that this information is entered accurately, as it will be used for later personalization.

[0524] Step 2:

[0525] The device sends the profile information entered by the user to the server. The server receives this information and securely stores it in its database.

[0526] Step 3:

[0527] When traveling or moving around, users input data such as their destination for the day, the order of visits, budget, and the number of people traveling with them. This information forms the basis for creating the optimal route and schedule for that day.

[0528] Step 4:

[0529] Each time, the terminal sends this data to the server, which then prepares to process it.

[0530] Step 5:

[0531] The server uses external APIs to retrieve real-time traffic conditions, weather information, and facility availability at destinations. This data is immediately reflected in the user's travel plan.

[0532] Step 6:

[0533] The server uses a generation algorithm to integrate profile information, real-time data, and external real-time data to generate the optimal route and schedule. This plan aims to maximize convenience.

[0534] Step 7:

[0535] The device receives the route and schedule, and the user confirms it. If there are any changes or feedback instructed by the user, it sends them back to the server.

[0536] Step 8:

[0537] The device's emotion engine analyzes the user's voice, facial expressions, and actions to determine their emotional state. For example, if stress or fatigue is detected, that information is sent to the server.

[0538] Step 9:

[0539] The server re-executes the generation algorithm based on data from the emotion engine, reconfiguring the route and schedule to suit the user's emotions. This makes it possible to provide the user with the optimal travel experience.

[0540] Step 10:

[0541] The server retrieves data on local events and places of interest, and suggests places that might interest the user based on their emotional state. This provides enjoyment and relaxation, and contributes to the revitalization of the local economy.

[0542] Thus, the present invention provides users with a personalized and comfortable travel experience through dynamic route generation that takes user emotions into consideration.

[0543] (Example 2)

[0544] 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."

[0545] Conventional travel plan generation systems generate plans considering user profiles and real-time external information, but they struggle to incorporate the user's emotional state. As a result, there is a challenge in providing appropriate support when users experience stress or anxiety during their travels. Furthermore, they are not sufficient in effectively utilizing region-specific information to provide plans based on the user's interests and concerns.

[0546] 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.

[0547] In this invention, the server includes means for receiving user characteristic information and storing it on a recording medium, means including a computation method for dynamically detecting the user's emotional state and reconstructing the route and schedule based on it, and means for providing information based on the user's interests through data linkage with external organizations to revitalize the local economy. This makes it possible to realize a more detailed travel experience that is tailored to the user's emotions and interests, thereby reducing stress and revitalizing the local economy.

[0548] A "user" is an entity that uses the system to receive travel plans and possesses individual profile information and emotional states.

[0549] A "server" is a central computing device that receives user information, retrieves external information, and generates and reconfigures the optimal travel route and schedule.

[0550] "Characteristic information" refers to data necessary for customizing travel plans, such as personal information, preferences, and travel purposes provided by the user.

[0551] "Emotional state" refers to the user's psychological or physical condition, which is detected through the analysis of voice, facial expressions, and bodily data.

[0552] A "recording medium" refers to a device or system for storing data, and is used to retain user characteristic information and past plans.

[0553] "Real-time external information" refers to dynamically changing data, including current traffic conditions, weather information, facility availability, and local event information, which are necessary for optimizing travel plans.

[0554] "Calculation methods" refer to algorithms and processes for calculating the optimal travel route and schedule based on user characteristics, emotional state, and external information.

[0555] "Revitalizing the local economy" refers to using this system to provide region-specific information, thereby promoting consumption and tourism within the region and supporting economic development.

[0556] In this system, users first install a dedicated application on their smart device. The application has the function of receiving characteristic information from the user and saving it to a storage medium. Users input detailed information about their travels and journeys, such as destinations, schedules, and budgets. This information is transmitted to the server in real time.

[0557] The server utilizes a cloud computing environment to deliver powerful computing capabilities. It obtains real-time traffic, weather, and facility availability information from external sources via APIs. This includes transportation service information, weather data, and congestion levels at tourist facilities. Using this data and sophisticated computational methods, the server generates optimal travel routes and schedules.

[0558] The device uses sensors to collect voice, facial, and physical data to detect the user's emotional state. This data is analyzed in real time to identify the user's emotional state. This information is sent to a server, which dynamically reconfigures the travel plan based on it. For example, if the user is feeling stressed, a relaxing facility might be incorporated into the route.

[0559] For example, to ensure that busy business travelers can travel with peace of mind, the system can suggest routes that avoid congestion and recommend relaxing cafes or parks along the way. In this process, the server reflects real-time information to provide a highly accurate plan.

[0560] An example of a prompt message is: "Please suggest a relaxing sightseeing plan for the user. The conditions are: sunny weather, budget of 10,000 yen or less, and destination of Tokyo." This format can be used to instruct the AI ​​model.

[0561] In this way, an intelligent system combining servers and terminals allows users to receive travel plans tailored to their individual emotions and needs, thereby reducing stress and contributing to the revitalization of the local economy.

[0562] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0563] Step 1:

[0564] The user launches the application on their smart device and enters personal information and travel-related information (destination, schedule, budget, etc.). The input data is sent from the device to the server. The server stores this data on a storage medium and prepares it for later use in generating travel plans.

[0565] Step 2:

[0566] The server obtains real-time traffic information, weather information, and facility availability information from external sources via APIs. This includes operating schedules, weather forecasts, and congestion levels. The acquired data is analyzed using computational methods and integrated with user input data to generate the optimal route and schedule. The generated plan is kept as a provisional plan.

[0567] Step 3:

[0568] While the user is on the move, the device uses its built-in sensors to collect the user's voice, facial expressions, and physical data in real time. Based on this information, the device analyzes the user's emotional state. The analysis results are immediately transmitted to the server and recorded in a database as the user's emotional state.

[0569] Step 4:

[0570] The server re-evaluates the generated travel plan based on the received emotional state data. If necessary, facilities and services appropriate to the emotional state are added to the plan. For example, if the user is feeling anxious, a relaxing cafe might be added to the route. The restructured plan is then sent to the user's device.

[0571] Step 5:

[0572] The user confirms the final travel plan notified on their device and begins their journey. The user can input evaluations and feedback at any time during the journey, which are sent to the server via their device. The server uses this feedback to further refine the plan and improve the user experience.

[0573] Through the processing steps described above, it becomes possible to provide users with stress-free and optimized travel plans that are tailored to their emotions.

[0574] (Application Example 2)

[0575] 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."

[0576] In modern life, individual users often experience stress associated with travel. In particular, traffic congestion and navigating unfamiliar areas make finding effective travel routes difficult, which can be a source of stress. Furthermore, providing personalized travel plans that adapt to changes in a user's emotional state during travel is currently challenging with existing technology. Therefore, the challenge lies in realizing the provision of real-time travel plans that respond to the user's emotions.

[0577] 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.

[0578] In this invention, the server includes means for receiving user profile data and storing it in a storage device, means for receiving purpose information and itinerary information entered by the user each time, and means for obtaining real-time travel information, weather information, and facility availability from external information sources. This makes it possible to dynamically regenerate routes and time allocations based on the user's emotional state.

[0579] "User profile data" refers to the basic information of each user, including information such as age, occupation, and usual means of transportation.

[0580] "Purpose information" refers to information about the destination or purpose that the user sets when traveling.

[0581] "Itinerary information" refers to information about the schedule and time allocation that a user plans for their travels.

[0582] A "memory device" is a mechanism for electronically storing information, and is used to accumulate information in databases such as servers.

[0583] "Real-time travel information" refers to information that allows users to instantly obtain information on the operation of available transportation methods and road congestion levels.

[0584] "Climate information" refers to environmental information such as weather forecasts, temperature, and precipitation that may affect users' travel.

[0585] "Facility availability" refers to information about the operating status and level of congestion of a facility that a user intends to visit.

[0586] The "generation method" is an algorithm that calculates the optimal travel route and time allocation based on user input data and information obtained from external sources.

[0587] "Emotional state" refers to a user's mental response, encompassing psychological states such as joy, anger, sadness, and happiness.

[0588] "Dynamic route and time allocation regeneration" is a process that reconfigures travel routes and schedules in real time based on the detected emotional state of the user.

[0589] This invention begins with the user inputting destination and itinerary information via a smartphone or other digital device. The device transmits this information to a server, along with the user's profile data. The server stores this data in its storage device.

[0590] The server retrieves travel information, weather information, and facility availability from external sources in real time. This process requires an internet connection to ensure that the information is always up-to-date. Using this data, the server calculates the optimal travel route and time allocation that matches the user's conditions, using a generation method on the server.

[0591] The system collects voice, facial expressions, and physical data through sensors on the device while the user is on the move, and analyzes their emotional state. This analysis utilizes software called an emotion engine. This makes it possible to understand how the user's emotions are changing in real time.

[0592] If the emotion engine determines that the user is experiencing stress, the server immediately regenerates the route and time allocation. This may include adding relaxing spots. Ultimately, the user is notified of an optimized travel plan through their device. This process is dynamically repeated and continuously updated to reflect the user's state.

[0593] As a concrete example, a business user on a business trip inputs using their smartphone that they need to travel from Shinjuku to Shibuya. While they would normally choose the train as their mode of transport, the server considers congestion information and suggests a less stressful route. It also suggests a relaxing cafe along the way.

[0594] An example of a prompt in a generative AI model is, "Generate a travel plan that suggests places where you can relax when you feel stressed while traveling for a business trip." Based on this prompt, the generative AI model will suggest a relevant travel plan.

[0595] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0596] Step 1:

[0597] The user uses a terminal to input information about their travel purpose and itinerary. This data includes destination, dates, and budget. This data is then transmitted from the terminal to the server.

[0598] Step 2:

[0599] The server stores the received user profile data and input data in storage. This information helps analyze the user's past movement patterns and preferences. At this point, the entered data is recorded in the database.

[0600] Step 3:

[0601] The server retrieves real-time travel information, weather information, and facility availability from external sources. This data is obtained via API and processed within the server. This allows the server to maintain up-to-date traffic and weather information.

[0602] Step 4:

[0603] The server generates the optimal travel route and time allocation based on user information and external information entered using a generation method. During this process, an algorithm is applied to compare and select multiple route plans. The output is a route and schedule proposed to the user.

[0604] Step 5:

[0605] While in motion, the device uses various sensors to collect data on the user's voice, facial expressions, and body language. This data is sent to an emotion engine to analyze the user's emotional state. This analysis identifies the user's emotional state in real time.

[0606] Step 6:

[0607] The emotion engine analyzes the user's emotional state, and if it detects stress or fatigue, the server dynamically regenerates the route and time allocation. This generates a new plan that includes relaxing facilities and spots.

[0608] Step 7:

[0609] The device notifies the user of the newly generated travel plan, which includes recommendations such as relaxation spots tailored to their emotional state. Instructions for the user to proceed to the next step are provided immediately.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] [Fourth Embodiment]

[0614] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0615] 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.

[0616] 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).

[0617] 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.

[0618] 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.

[0619] 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).

[0620] 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.

[0621] 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.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] 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".

[0627] This invention is a system for providing users with personalized travel plans. This system leverages the user's prior profile information to generate optimized routes and schedules, and dynamically reconfigures the plan in response to real-time changes in circumstances, thereby providing users with a stress-free travel experience.

[0628] First, users register profile information through the application, such as their address, favorite places, family structure, hobbies, favorite foods, allergy information, preferred mode of transportation, and payment method. This allows for personalization tailored to individual needs.

[0629] Next, for travel or daily commutes, users input information into the application such as their destination and order of activities for the day, budget, and the number of people traveling with them. This data is then sent from the device to the server, which initiates a real-time search based on this information.

[0630] The server retrieves real-time data from external sources, such as traffic conditions, weather conditions, and facility congestion. This information is combined with the user's profile information and data entered as needed, and a generation algorithm creates the optimal travel route and schedule plan.

[0631] This system can also provide users with a richer experience by incorporating local event information and recommended places to visit. This can contribute to the revitalization of the local economy.

[0632] For example, a user planning a family trip for the weekend would input several tourist spots they want to visit into the app. The system would then take into account the user's situation (traveling with children) and their preferred mode of transportation (car), prioritizing car routes and suggesting a schedule that includes a picnic in a park and a stop at a popular local restaurant. The suggested plan would reflect real-time traffic congestion and weather conditions, and could be adjusted multiple times in advance.

[0633] Thus, the present invention takes various factors into comprehensive consideration to enable convenient and less burdensome travel for the user.

[0634] The following describes the processing flow.

[0635] Step 1:

[0636] When a user launches the application, they first enter their address, favorite places, family structure, hobbies, favorite foods, allergy information, preferred mode of transportation, and payment method on an input screen. This information is saved as profile information.

[0637] Step 2:

[0638] The device connects to the server to organize the profile information entered by the user and send it to the database. The server receives this data and securely stores it in the database.

[0639] Step 3:

[0640] Users input data into the application each time they need to travel, such as the day of travel, destination, order of visits, budget, and number of people. This data is sent to the server separately from their profile information.

[0641] Step 4:

[0642] The server checks for data reception each time and collects necessary external information in real time. This external information includes traffic conditions, weather forecasts, and destination congestion information. The server obtains this information from external APIs.

[0643] Step 5:

[0644] The server integrates pre-registered profile information, user-entered data, and real-time data acquired from external sources, and uses a generation algorithm to generate the optimal travel route and schedule. During this process, the plan is adjusted based on factors such as traffic convenience, congestion levels, and user preferences.

[0645] Step 6:

[0646] The server sends the generated route and schedule to the terminal. The user can view the plan details and schedule on the terminal. If the user wishes, they can request the server to regenerate the route through feedback.

[0647] Step 7:

[0648] The AI ​​agent generates new suggestions based on external information and user feedback. These new suggestions are then presented to the user via the server, allowing the user to review and decide on the latest suggestions.

[0649] Step 8:

[0650] The server collects local event information and points of interest through collaboration with external organizations and integrates them into the user's plan. This provides users with a rich, locally-focused experience.

[0651] (Example 1)

[0652] 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".

[0653] In modern society, planning a trip involves the time-consuming task of individually researching real-time information such as traffic conditions and weather, and then constructing the optimal route and schedule that takes this into account. Furthermore, dynamically reconfiguring the plan in response to changing circumstances during the journey is required, which is difficult to do manually. Additionally, suggestions for local events and points of interest are rarely provided in an integrated manner, limiting the user's travel experience. Therefore, a system is needed that can solve these problems and provide users with a stress-free travel experience.

[0654] 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.

[0655] In this invention, the server includes means for receiving general user information and storing it in an information collection, means for receiving destination and action plan information entered by the user from time to time, and means for acquiring real-time travel data, environmental data, and facility status information from external information sources. This enables the dynamic generation of personalized and optimal travel routes and plans according to the user's purpose, and their reconfiguration in response to real-time circumstances.

[0656] "User general information" refers to a series of personal data that users register in the system, such as their address, hobbies and preferences, and family structure.

[0657] An "information collection" refers to a database or storage system used by a system to store and manage users' general information and other related data.

[0658] "Destination and activity plan information entered as needed" refers to detailed information such as the necessary destinations, order of visits, and budget that the user enters when traveling.

[0659] "External information sources" refer to public or private data providers that provide real-time data such as traffic conditions, weather conditions, and facility congestion levels.

[0660] "Real-time travel data" refers to information that is acquired and updated instantly based on the user's location, such as current traffic conditions and travel time.

[0661] "Environmental data" refers to information that includes natural conditions related to travel, such as weather conditions, temperature, and precipitation on the day of travel.

[0662] "Facility status information" refers to the latest information regarding the congestion level, availability, and operating hours of the facility you plan to visit.

[0663] "Dynamic generation" refers to the process of modifying and restructuring travel routes and schedules in real time in response to changing environments and circumstances.

[0664] This invention relates to a system that provides users with personalized travel plans. This system makes user travel smoother and less burdensome.

[0665] Users register their personal information, such as address, hobbies, family structure, and favorite foods, through the application. This information is sent from the device to the server and stored in an information repository on the server. The server uses this general information to form a foundation for developing travel plans that are best suited to the user's needs.

[0666] For travel and daily commutes, users input destinations, itinerary, budget, and the number of companions into the application. This information is also transmitted to the server via the device. The server obtains real-time data such as traffic conditions, weather conditions, and facility congestion from external sources. Public API services and private data provision platforms are used for this information collection.

[0667] The server combines acquired real-time travel data, environmental data, and facility status information with the user's profile information, and uses a generated AI model to create the optimal travel route and schedule. This AI model dynamically optimizes the plan by taking into account user-specified conditions and real-time data, such as avoiding traffic congestion and considering weather conditions.

[0668] As a concrete example, consider a user planning a weekend family trip. This user enters the tourist destinations they want to visit and the restaurants they want to stop at along the way into the application. The server optimizes the route considering car travel and incorporates parks suitable for picnics and popular restaurants into the schedule as needed. Because the proposed plan takes real-time traffic conditions and weather information into account, the user can enjoy their trip with peace of mind.

[0669] Furthermore, the proposed travel plan can be reconstructed any number of times based on user feedback. An example of a prompt using the generative AI model is: "User: I would like to visit tourist spots B and C in the afternoon. I would like to have lunch at cafe A, so please suggest a schedule that fits that."

[0670] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0671] Step 1:

[0672] Users enter profile information through the application. This information includes address, hobbies, family structure, and allergy information. The device converts this information into a digital format, structures it electronically, and sends it to the server. This information is stored in the server's data repository and associated with the user's personal ID.

[0673] Step 2:

[0674] The user enters details about a specific travel plan into the application. This includes the destination for the day, the order of visits, the budget, and information about travel companions. The terminal receives these details and sends them to the server as a temporary request. The server parses the received data, tags the entered travel plan with a unique identifier, and stores it.

[0675] Step 3:

[0676] The server collects necessary real-time data from external sources. Here, APIs are used to obtain traffic conditions, weather conditions, facility congestion, and other data. The server receives this raw data and performs formatting and normalization to combine it with user input data. This process integrates real-time environmental data with travel planning.

[0677] Step 4:

[0678] The server uses integrated data to drive a generative AI model that generates the optimal travel route and schedule. This step dynamically plans based on real-time data, taking into account the characteristics of each user. The generative AI model algorithmically calculates multiple routes under given conditions and selects the optimal one. The output is an optimized travel schedule.

[0679] Step 5:

[0680] The server sends the generated schedule to the terminal and presents it to the user on the application. The user reviews the presented plan and provides feedback as needed. For example, they can add specific spots or request adjustments to times. This feedback is sent back to the server, triggering the plan regeneration process. This allows the user to ultimately obtain a travel plan that best suits their preferences.

[0681] (Application Example 1)

[0682] 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".

[0683] In recent years, with the advancement of urbanization, traffic congestion and overcrowding have become serious problems, making it difficult for individual citizens to travel efficiently and comfortably. Furthermore, the inability to efficiently obtain region-specific information has resulted in a lack of enriching lifestyle experiences. Traditional methods face the challenge of providing optimal travel plans in real time while considering individual circumstances and preferences.

[0684] 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.

[0685] In this invention, the server includes means for receiving user attribute information and storing it in a data storage device, means for receiving destination and plan information from the user based on real-time input, and means for obtaining the latest travel information, weather information, and facility availability from external information sources. This makes it possible to provide travel plans optimized for individual citizens in real time.

[0686] "User attribute information" refers to information about the user as an individual, such as address, interests, and preferred modes of transportation, which is necessary for personalizing travel plans.

[0687] A "data storage device" is an information processing device that stores user attribute information, movement history, and other data, and allows users to retrieve it as needed.

[0688] "Occasional input information" refers to specific information that users enter each time, such as destinations and plans, and is information that should be reflected in daily travel and trip planning.

[0689] "External information sources" refer to various data sources that provide real-time information such as traffic, weather, and facility usage.

[0690] "Route and schedule" refers to the optimal travel route at a specific time and the schedule based on it.

[0691] "Responses" refer to information collected as evaluations, opinions, or feedback that users give to the provided plan or to the application.

[0692] "Real-time information for the entire city" refers to information that encompasses traffic conditions, events, weather, and other factors that change moment by moment throughout the entire city.

[0693] "Information sharing" is a process that involves exchanging data with external organizations to connect various services and information, enabling the provision of more advanced information.

[0694] "Regional industries" refer to a collection of businesses and service industries that conduct economic activities in a specific region, and their revitalization contributes to the economic development of that region.

[0695] To realize this system, the user's smart device and the server play a central role. Users input their attribute information in advance using an application on their smartphone and store it in a data storage device. When planning travel in real time, they transmit destination and plan information from their smart device. The server is responsible for obtaining the latest travel information, weather information, and facility usage status from external sources and generating the optimal route and schedule based on this information.

[0696] The server performs multi-stage data processing and calculations based on the acquired data. In particular, it uses complex algorithms to generate dynamic and optimized travel plans by combining user attribute information with external real-time information. The software used includes Python and various APIs to enable real-time data processing.

[0697] The generated travel plan is notified to the user's smart device, and if the user responds, the server regenerates the plan based on that response. This process ensures that the user always has a travel experience that is up-to-date.

[0698] As a concrete example, a user planning a sightseeing trip within a city with their family enters information using a smartphone application, including destination, desired visit time, and budget. Based on this information, the system obtains real-time traffic and weather data to generate and provide an optimal travel plan. It also notifies the user of suggested sightseeing spots and event information, providing a richer experience.

[0699] An example of a prompt message for the generating AI model would be: "Please suggest some tourist destinations that my family can enjoy this afternoon. We will be starting from the central station, and please take weather and crowd conditions into consideration."

[0700] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0701] Step 1:

[0702] Users input attribute information using smart devices, and the device stores this information in a data storage device. This input includes the user's address, interests, and preferred modes of transportation, and is stored as foundational data to provide personalized experiences.

[0703] Step 2:

[0704] The user inputs their destination and plan information into the terminal, which then sends this information to the server. Specifically, this includes the places they want to visit, the time, and their budget, and this becomes the input data for creating the next optimal route.

[0705] Step 3:

[0706] The server retrieves the latest travel information, weather information, and facility availability from external sources. In this step, it utilizes traffic information APIs and weather information APIs to collect real-time data and prepares to combine it with the user's current status.

[0707] Step 4:

[0708] The server inputs user attribute information, timely input information, and external real-time information into a generative AI model to generate the optimal route and schedule. Here, the generative AI model performs complex data processing and algorithmic calculations, outputting a dynamically optimized travel plan.

[0709] Step 5:

[0710] The generated travel plan is sent from the server to the terminal. The notification the user receives includes recommended routes, places to visit, and event information, which the user can use to begin their journey.

[0711] Step 6:

[0712] Based on user feedback, the device sends information to the server, which then uses the feedback information to regenerate the optimal route using an AI model. This process ensures that users always receive the latest plan that adapts to changing circumstances.

[0713] 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.

[0714] This invention is a system for providing users with personalized travel plans, and by incorporating an emotion engine, it enables more detailed planning that dynamically reflects the user's emotions. This system utilizes the user's pre-registered profile information and external data acquired in real time to incorporate the user's emotional state, thereby providing a more comfortable and stress-free travel experience.

[0715] Users enter their basic information through the application, which is then stored on the server as profile information. When traveling, users enter information such as desired destinations, dates, and budget, and this information is also processed via the server. The server obtains real-time information from external sources, such as traffic information, weather forecasts, and facility congestion levels, to generate the optimal travel route and schedule that suits the user's conditions.

[0716] The emotion engine analyzes voice, facial expressions, and physical data acquired from the user's device while on the move to identify the user's emotional state. This information is transferred to a server, where a generation algorithm reconstructs a plan that is more emotionally appropriate. For example, if the user is feeling stressed, the route may be designed to include relaxing locations or events.

[0717] For example, if a user on a business trip is experiencing time-related stress, the emotion engine can detect this and prioritize less crowded routes, while also suggesting cafes or parks along the way for relaxation. In this process, congestion information and facility availability data from external sources are incorporated to provide the user with a highly accurate plan.

[0718] Through this mechanism, the present invention can smoothly provide travel plans that take into account both the individual needs and real-time emotional states of users, thereby reducing stress and contributing to the revitalization of the local economy.

[0719] The following describes the processing flow.

[0720] Step 1:

[0721] Users launch the application and enter personal profile information such as address, places of interest, family structure, favorite foods, and allergy information. It is important that this information is entered accurately, as it will be used for later personalization.

[0722] Step 2:

[0723] The device sends the profile information entered by the user to the server. The server receives this information and securely stores it in its database.

[0724] Step 3:

[0725] When traveling or moving around, users input data such as their destination for the day, the order of visits, budget, and the number of people traveling with them. This information forms the basis for creating the optimal route and schedule for that day.

[0726] Step 4:

[0727] Each time, the terminal sends this data to the server, which then prepares to process it.

[0728] Step 5:

[0729] The server uses external APIs to retrieve real-time traffic conditions, weather information, and facility availability at destinations. This data is immediately reflected in the user's travel plan.

[0730] Step 6:

[0731] The server uses a generation algorithm to integrate profile information, real-time data, and external real-time data to generate the optimal route and schedule. This plan aims to maximize convenience.

[0732] Step 7:

[0733] The device receives the route and schedule, and the user confirms it. If there are any changes or feedback instructed by the user, it sends them back to the server.

[0734] Step 8:

[0735] The device's emotion engine analyzes the user's voice, facial expressions, and actions to determine their emotional state. For example, if stress or fatigue is detected, that information is sent to the server.

[0736] Step 9:

[0737] The server re-executes the generation algorithm based on data from the emotion engine, reconfiguring the route and schedule to suit the user's emotions. This makes it possible to provide the user with the optimal travel experience.

[0738] Step 10:

[0739] The server retrieves data on local events and places of interest, and suggests places that might interest the user based on their emotional state. This provides enjoyment and relaxation, and contributes to the revitalization of the local economy.

[0740] Thus, the present invention provides users with a personalized and comfortable travel experience through dynamic route generation that takes user emotions into consideration.

[0741] (Example 2)

[0742] 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".

[0743] Conventional travel plan generation systems generate plans considering user profiles and real-time external information, but they struggle to incorporate the user's emotional state. As a result, there is a challenge in providing appropriate support when users experience stress or anxiety during their travels. Furthermore, they are not sufficient in effectively utilizing region-specific information to provide plans based on the user's interests and concerns.

[0744] 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.

[0745] In this invention, the server includes means for receiving user characteristic information and storing it on a recording medium, means including a computation method for dynamically detecting the user's emotional state and reconstructing the route and schedule based on it, and means for providing information based on the user's interests through data linkage with external organizations to revitalize the local economy. This makes it possible to realize a more detailed travel experience that is tailored to the user's emotions and interests, thereby reducing stress and revitalizing the local economy.

[0746] A "user" is an entity that uses the system to receive travel plans and possesses individual profile information and emotional states.

[0747] A "server" is a central computing device that receives user information, retrieves external information, and generates and reconfigures the optimal travel route and schedule.

[0748] "Characteristic information" refers to data necessary for customizing travel plans, such as personal information, preferences, and travel purposes provided by the user.

[0749] "Emotional state" refers to the user's psychological or physical condition, which is detected through the analysis of voice, facial expressions, and bodily data.

[0750] A "recording medium" refers to a device or system for storing data, and is used to retain user characteristic information and past plans.

[0751] "Real-time external information" refers to dynamically changing data, including current traffic conditions, weather information, facility availability, and local event information, which are necessary for optimizing travel plans.

[0752] "Calculation methods" refer to algorithms and processes for calculating the optimal travel route and schedule based on user characteristics, emotional state, and external information.

[0753] "Revitalizing the local economy" refers to using this system to provide region-specific information, thereby promoting consumption and tourism within the region and supporting economic development.

[0754] In this system, users first install a dedicated application on their smart device. The application has the function of receiving characteristic information from the user and saving it to a storage medium. Users input detailed information about their travels and journeys, such as destinations, schedules, and budgets. This information is transmitted to the server in real time.

[0755] The server utilizes a cloud computing environment to deliver powerful computing capabilities. It obtains real-time traffic, weather, and facility availability information from external sources via APIs. This includes transportation service information, weather data, and congestion levels at tourist facilities. Using this data and sophisticated computational methods, the server generates optimal travel routes and schedules.

[0756] The device uses sensors to collect voice, facial, and physical data to detect the user's emotional state. This data is analyzed in real time to identify the user's emotional state. This information is sent to a server, which dynamically reconfigures the travel plan based on it. For example, if the user is feeling stressed, a relaxing facility might be incorporated into the route.

[0757] For example, to ensure that busy business travelers can travel with peace of mind, the system can suggest routes that avoid congestion and recommend relaxing cafes or parks along the way. In this process, the server reflects real-time information to provide a highly accurate plan.

[0758] An example of a prompt message is: "Please suggest a relaxing sightseeing plan for the user. The conditions are: sunny weather, budget of 10,000 yen or less, and destination of Tokyo." This format can be used to instruct the AI ​​model.

[0759] In this way, an intelligent system combining servers and terminals allows users to receive travel plans tailored to their individual emotions and needs, thereby reducing stress and contributing to the revitalization of the local economy.

[0760] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0761] Step 1:

[0762] The user launches the application on their smart device and enters personal information and travel-related information (destination, schedule, budget, etc.). The input data is sent from the device to the server. The server stores this data on a storage medium and prepares it for later use in generating travel plans.

[0763] Step 2:

[0764] The server obtains real-time traffic information, weather information, and facility availability information from external sources via APIs. This includes operating schedules, weather forecasts, and congestion levels. The acquired data is analyzed using computational methods and integrated with user input data to generate the optimal route and schedule. The generated plan is kept as a provisional plan.

[0765] Step 3:

[0766] While the user is on the move, the device uses its built-in sensors to collect the user's voice, facial expressions, and physical data in real time. Based on this information, the device analyzes the user's emotional state. The analysis results are immediately transmitted to the server and recorded in a database as the user's emotional state.

[0767] Step 4:

[0768] The server re-evaluates the generated travel plan based on the received emotional state data. If necessary, facilities and services appropriate to the emotional state are added to the plan. For example, if the user is feeling anxious, a relaxing cafe might be added to the route. The restructured plan is then sent to the user's device.

[0769] Step 5:

[0770] The user confirms the final travel plan notified on their device and begins their journey. The user can input evaluations and feedback at any time during the journey, which are sent to the server via their device. The server uses this feedback to further refine the plan and improve the user experience.

[0771] Through the processing steps described above, it becomes possible to provide users with stress-free and optimized travel plans that are tailored to their emotions.

[0772] (Application Example 2)

[0773] 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".

[0774] In modern life, individual users often experience stress associated with travel. In particular, traffic congestion and navigating unfamiliar areas make finding effective travel routes difficult, which can be a source of stress. Furthermore, providing personalized travel plans that adapt to changes in a user's emotional state during travel is currently challenging with existing technology. Therefore, the challenge lies in realizing the provision of real-time travel plans that respond to the user's emotions.

[0775] 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.

[0776] In this invention, the server includes means for receiving user profile data and storing it in a storage device, means for receiving purpose information and itinerary information entered by the user each time, and means for obtaining real-time travel information, weather information, and facility availability from external information sources. This makes it possible to dynamically regenerate routes and time allocations based on the user's emotional state.

[0777] "User profile data" refers to the basic information of each user, including information such as age, occupation, and usual means of transportation.

[0778] "Purpose information" refers to information about the destination or purpose that the user sets when traveling.

[0779] "Itinerary information" refers to information about the schedule and time allocation that a user plans for their travels.

[0780] A "memory device" is a mechanism for electronically storing information, and is used to accumulate information in databases such as servers.

[0781] "Real-time travel information" refers to information that allows users to instantly obtain information on the operation of available transportation methods and road congestion levels.

[0782] "Climate information" refers to environmental information such as weather forecasts, temperature, and precipitation that may affect users' travel.

[0783] "Facility availability" refers to information about the operating status and level of congestion of a facility that a user intends to visit.

[0784] The "generation method" is an algorithm that calculates the optimal travel route and time allocation based on user input data and information obtained from external sources.

[0785] "Emotional state" refers to a user's mental response, encompassing psychological states such as joy, anger, sadness, and happiness.

[0786] "Dynamic route and time allocation regeneration" is a process that reconfigures travel routes and schedules in real time based on the detected emotional state of the user.

[0787] This invention begins with the user inputting destination and itinerary information via a smartphone or other digital device. The device transmits this information to a server, along with the user's profile data. The server stores this data in its storage device.

[0788] The server retrieves travel information, weather information, and facility availability from external sources in real time. This process requires an internet connection to ensure that the information is always up-to-date. Using this data, the server calculates the optimal travel route and time allocation that matches the user's conditions, using a generation method on the server.

[0789] The system collects voice, facial expressions, and physical data through sensors on the device while the user is on the move, and analyzes their emotional state. This analysis utilizes software called an emotion engine. This makes it possible to understand how the user's emotions are changing in real time.

[0790] If the emotion engine determines that the user is experiencing stress, the server immediately regenerates the route and time allocation. This may include adding relaxing spots. Ultimately, the user is notified of an optimized travel plan through their device. This process is dynamically repeated and continuously updated to reflect the user's state.

[0791] As a concrete example, a business user on a business trip inputs using their smartphone that they need to travel from Shinjuku to Shibuya. While they would normally choose the train as their mode of transport, the server considers congestion information and suggests a less stressful route. It also suggests a relaxing cafe along the way.

[0792] An example of a prompt in a generative AI model is, "Generate a travel plan that suggests places where you can relax when you feel stressed while traveling for a business trip." Based on this prompt, the generative AI model will suggest a relevant travel plan.

[0793] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0794] Step 1:

[0795] The user uses a terminal to input information about their travel purpose and itinerary. This data includes destination, dates, and budget. This data is then transmitted from the terminal to the server.

[0796] Step 2:

[0797] The server stores the received user profile data and input data in storage. This information helps analyze the user's past movement patterns and preferences. At this point, the entered data is recorded in the database.

[0798] Step 3:

[0799] The server retrieves real-time travel information, weather information, and facility availability from external sources. This data is obtained via API and processed within the server. This allows the server to maintain up-to-date traffic and weather information.

[0800] Step 4:

[0801] The server generates the optimal travel route and time allocation based on user information and external information entered using a generation method. During this process, an algorithm is applied to compare and select multiple route plans. The output is a route and schedule proposed to the user.

[0802] Step 5:

[0803] While in motion, the device uses various sensors to collect data on the user's voice, facial expressions, and body language. This data is sent to an emotion engine to analyze the user's emotional state. This analysis identifies the user's emotional state in real time.

[0804] Step 6:

[0805] The emotion engine analyzes the user's emotional state, and if it detects stress or fatigue, the server dynamically regenerates the route and time allocation. This generates a new plan that includes relaxing facilities and spots.

[0806] Step 7:

[0807] The device notifies the user of the newly generated travel plan, which includes recommendations such as relaxation spots tailored to their emotional state. Instructions for the user to proceed to the next step are provided immediately.

[0808] 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.

[0809] 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.

[0810] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0811] 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.

[0812] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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."

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0829] The following is further disclosed regarding the embodiments described above.

[0830] (Claim 1)

[0831] A means of receiving user profile information and storing it in a database,

[0832] A means of receiving destination and schedule information entered by the user each time,

[0833] Means for obtaining real-time traffic information, weather information, and facility availability information from external sources,

[0834] A means for generating the optimal route and schedule based on user profile information, input data, and external information using a generation algorithm,

[0835] A means of notifying the user of the generated route and schedule,

[0836] A means to dynamically regenerate routes and schedules based on user feedback,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, further comprising means for acquiring local information and suggesting local events and places to visit to the user.

[0840] (Claim 3)

[0841] The system according to claim 1, further comprising means of providing information based on user interests and revitalizing the local economy through data sharing with external organizations.

[0842] "Example 1"

[0843] (Claim 1)

[0844] A means of receiving general user information and storing it in an information collection,

[0845] A means of receiving destination and activity plan information entered by users as needed,

[0846] Means for acquiring real-time mobility data, environmental data, and facility status information from external information sources,

[0847] A means for generating an optimal travel route and plan based on the user's general information, input data at any time, and external information using a generation process,

[0848] Means for notifying the user of the generated travel route and plan,

[0849] A means for dynamically regenerating travel routes and plans based on user responses,

[0850] A system that includes this.

[0851] (Claim 2)

[0852] The system according to claim 1, further comprising means for acquiring local information and suggesting local events and places to visit to the user.

[0853] (Claim 3)

[0854] The system according to claim 1, further comprising means of providing information based on user interests and revitalizing the local economy through information sharing with external organizations.

[0855] "Application Example 1"

[0856] (Claim 1)

[0857] A device that receives user attribute information and stores it in a data storage device,

[0858] A device that receives destination and plan information from the user based on real-time input,

[0859] A device that acquires the latest mobility information, weather information, and facility availability status from external sources,

[0860] A device that uses a generation process to generate the optimal route and schedule based on user attribute information, input information at any given time, and external information,

[0861] A device that notifies the user of the generated route and schedule,

[0862] A device that dynamically regenerates routes and schedules based on user feedback,

[0863] A device that integrates real-time information from across the entire city and provides individually optimized travel plans,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, further comprising a device that acquires local information and suggests local events and places to visit to the user.

[0867] (Claim 3)

[0868] The system according to claim 1, further comprising a device that provides information based on user interests and revitalizes local industries through information sharing with external organizations.

[0869] "Example 2 of combining an emotion engine"

[0870] (Claim 1)

[0871] A means of receiving user characteristic information and storing it on a recording medium,

[0872] A means of receiving destination and schedule information entered by the user each time,

[0873] Means for obtaining time-based travel information, weather conditions, and facility availability information from external sources,

[0874] A means for generating the optimal route and schedule based on user characteristic information, input data, and external information using computational methods,

[0875] A means including a computational method for dynamically detecting the user's emotional state and reconstructing the route and schedule based on it,

[0876] A means of notifying the user of the generated route and schedule,

[0877] A means to dynamically regenerate routes and schedules based on user feedback,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, further comprising means for acquiring local information and suggesting local activities and places of interest to the user.

[0881] (Claim 3)

[0882] The system according to claim 1, further comprising means of providing information based on user interests and revitalizing the local economy through data linkage with external organizations.

[0883] "Application example 2 of combining emotional engines"

[0884] (Claim 1)

[0885] A means of receiving user profile data and saving it to a storage device,

[0886] A means of receiving purpose information and itinerary information entered by the user each time,

[0887] Means for obtaining real-time travel information, weather information, and facility availability from external sources,

[0888] A means for generating the optimal route and time allocation based on user profile data, input data, and external information using a generation method,

[0889] A means of notifying the user of the generated route and time allocation,

[0890] A means of detecting the user's emotional state by analyzing voice, facial expressions, and physical data obtainable from the user's device,

[0891] Means for dynamically regenerating the route and time allocation based on the detected emotional state,

[0892] A system that includes this.

[0893] (Claim 2)

[0894] The system according to claim 1, further comprising means for acquiring regional data and suggesting region-specific events and places of interest that are appropriate to the user's emotional state.

[0895] (Claim 3)

[0896] The system according to claim 1, further comprising means of promoting the local economy tailored to the emotional state of users, through information sharing with external organizations, and providing information based on user interests. [Explanation of Symbols]

[0897] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving user profile information and storing it in a database, A means of receiving destination and schedule information entered by the user each time, Means for obtaining real-time traffic information, weather information, and facility availability information from external sources, A means for generating the optimal route and schedule based on user profile information, input data, and external information using a generation algorithm, A means of notifying the user of the generated route and schedule, A means to dynamically regenerate routes and schedules based on user feedback, A system that includes this.

2. The system according to claim 1, further comprising means for acquiring local information and suggesting local events and places to visit to the user.

3. The system according to claim 1, further comprising means of providing information based on user interests and revitalizing the local economy through data sharing with external organizations.

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