system

Abstract

Provide a system. A means for inputting travel preferences from a user; means for transmitting the travel preference information to a server; A server uses an artificial intelligence model to generate a travel plan based on the travel preference information; means for transmitting the generated travel plan to a terminal; means for the terminal to display the travel plan to the user; means for a user to customize the displayed itinerary; means for retransmitting the customized information to a server, and the server regenerating a travel plan; and means for ultimately displaying said regenerated travel plan to a user.

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method 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 a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional travel reservation systems mainly offer package tours, making it difficult for travelers to choose a plan that perfectly matches their interests and preferences. Furthermore, there are few flexible systems that can quickly respond to individual customization requests. As a result, travelers often spend a great deal of time and effort planning their trips. Furthermore, multiple revisions to a travel plan must be made manually, resulting in inefficiency. [Means for solving the problem]

[0005] The present invention solves the above problem by providing a system including: means for inputting travel preferences from a user; means for transmitting the travel preference information to a server; means for the server to generate a travel plan based on the travel preference information using an artificial intelligence model; means for transmitting the generated travel plan to a terminal; means for the terminal to display the travel plan to the user; means for the user to customize the displayed travel plan; means for resending the customized information to the server, which causes the server to regenerate the travel plan; and means for finally displaying the regenerated travel plan to the user.

[0006] In this way, a user can quickly and effectively obtain a customizable travel plan according to his or her wishes, and a flexible travel planning system that can also accommodate multiple customizations can be realized.

[0007] "User" means an individual or organization that uses the system to create a travel plan.

[0008] "Travel preference information" is information about a trip entered by a user, such as a destination, a schedule, a budget, and activities in which the user is interested.

[0009] A "terminal" is a computing device through which a user inputs travel preferences and displays the generated travel plan.

[0010] A "server" is a central computer that receives travel preferences submitted by users and generates travel plans using artificial intelligence models.

[0011] An "artificial intelligence model" is a mathematical model that generates travel plans based on historical data and predictive algorithms.

[0012] A "travel plan" is a plan that includes a travel schedule and suggestions for places to visit, which is generated by the server based on the user's desired travel information.

[0013] "Customization" refers to the act of a user adding additional requests or changes to the displayed travel plan.

[0014] "Communication means" refers to a network connection that allows the terminal and the server to communicate with each other.

[0015] "Regeneration" refers to the process by which the server recreates the travel plan based on the customized travel preferences. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

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

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

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

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

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

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

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

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

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

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

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0037] This invention relates to a system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal displays the travel plan to the user. To implement this system, the following procedures and requirements must be met:

[0038] First, to start planning a trip, the user inputs desired travel information into the terminal. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit (e.g., tourist attractions and restaurants). The terminal provides an interface for inputting this information.

[0039] Example: A user types into a terminal, "I want to plan a 5-day trip to Tokyo. My budget is under 100,000 yen, and I want to visit tourist attractions and good restaurants."

[0040] The device then generates an API request to send the entered travel preferences to a server, which receives and analyzes the request and installs an artificial intelligence model to generate a travel plan based on the user's preferences.

[0041] The server preprocesses the desired information and then inputs it into an artificial intelligence model that is capable of generating an optimal travel plan based on the input parameters. The model considers past travel data, user history, and available resources to suggest optimal schedules and places to visit at the destination.

[0042] Example: The server generates a detailed "5-day Tokyo travel plan" that includes visiting Asakusa and Skytree on the first day, Ueno Zoo and Ameyoko Market on the second day, etc.

[0043] The server then sends the generated itinerary to the device, which then displays it to the user. The user can review the displayed itinerary and make additional customizations as needed. For example, if the user wants to visit Odaiba instead of Ueno Zoo, they can input that change into the device.

[0044] The device compiles this customization information and sends it back to the server, which again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is then sent back to the device and displayed to the user as the final plan.

[0045] Example: If a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[0046] In this way, the present invention realizes a system that quickly provides flexible travel plans based on the user's wishes and can accommodate multiple customizations.

[0047] The processing flow will be explained below.

[0048] Step 1:

[0049] The user inputs travel preferences into the terminal, such as destination, travel dates, budget, and activities of interest.

[0050] Step 2:

[0051] The device collects the travel preference information entered and converts the data into a single data set.

[0052] Step 3:

[0053] The device sends the compiled data set to the server, and generates an API request and sends it to the server.

[0054] Step 4:

[0055] The server receives the API request, analyzes the request, and extracts travel preference information.

[0056] Step 5:

[0057] The server pre-processes the travel preference information, for example checking the data for consistency and converting it into a format suitable for artificial intelligence models.

[0058] Step 6:

[0059] The server inputs the preprocessed data into an artificial intelligence model, which then generates an optimal travel plan based on the input data.

[0060] Step 7:

[0061] The server compiles the generated itinerary into a dataset, for example creating a detailed schedule for each day.

[0062] Step 8:

[0063] The server sends the generated travel plan to the device. The travel plan is sent as an API response.

[0064] Step 9:

[0065] The device receives the travel plan from the server, analyzes the data, and displays it to the user.

[0066] Step 10:

[0067] The user can customize the displayed travel plan by entering any corrections or additions they wish to make into the device.

[0068] Step 11:

[0069] The device collects the user customization information and creates a new dataset.

[0070] Step 12:

[0071] The device resends the customized data set to the server, and generates another API request and sends it to the server.

[0072] Step 13:

[0073] The server receives the API request again and analyzes the new request information.

[0074] Step 14:

[0075] The server preprocesses the new request information, performs data integrity checks, and converts it into a format suitable for artificial intelligence models.

[0076] Step 15:

[0077] The server then feeds the preprocessed data back into the artificial intelligence model, which then generates a customized itinerary based on the new data.

[0078] Step 16:

[0079] The server compiles the regenerated itinerary into a dataset, e.g., creating a detailed schedule that reflects the changes.

[0080] Step 17:

[0081] The server sends the regenerated travel plan to the device and the final plan as an API response.

[0082] Step 18:

[0083] The terminal receives the regenerated travel plan from the server, analyzes the data, and displays the final plan to the user.

[0084] Through this series of steps, the user can obtain a travel plan that meets their needs, and a system is realized that can flexibly accommodate additional customization.

[0085] Example 1

[0086] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0087] Conventional travel plan creation systems have had the challenge of responding quickly and flexibly to user requests. Creating the optimal plan based on the user's desired travel information requires advanced data analysis and individual customization, which conventional systems find difficult. It is also difficult to respond quickly to user requests for changes, and multiple customization processes must proceed smoothly.

[0088] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0089] In this invention, the server includes means for inputting travel preference information from a user, means for transmitting the travel preference information to the server, means for generating a travel plan based on the travel preference information using an artificial intelligence model, means for transmitting the generated travel plan to a terminal, means for the terminal to display the travel plan to the user, means for the user to customize the displayed travel plan, means for retransmitting the customized information to the server and causing the server to regenerate the travel plan, and means for finally displaying the regenerated travel plan to the user. This makes it possible to provide flexible and prompt travel plans based on the user's preferences.

[0090] "User" refers to an individual or organization who inputs desired information to create a travel plan and reviews and customizes the generated plan.

[0091] "Desired information" refers to detailed information entered by the user, such as travel destination, travel itinerary, budget, and activities desired to visit.

[0092] "Terminal" refers to a device used by a user to input desired information, and includes smartphones, tablets, PCs, etc.

[0093] "Server" refers to the central computing system that receives, analyzes, processes, and generates travel plans based on user-submitted preferences.

[0094] "Artificial intelligence model" refers to the algorithms and computational models that generate optimal travel plans based on input data, and are built using deep learning libraries, etc.

[0095] An "API request" is a standardized form of digital communication that allows a device to send desired information to a server.

[0096] A "travel plan" refers to a plan that includes a specific travel schedule and suggestions of places to visit, which is generated by the server based on the user's desired information.

[0097] "Customization" refers to the user making additional changes or adjustments to the generated itinerary.

[0098] "Network" refers to a connection means such as the Internet or a local area network that allows servers and terminals to communicate with each other.

[0099] "Historical Travel Data" refers to data previously collected about other users' travel information and travel plans.

[0100] "History data" refers to data that records information about past trips and behavioral patterns of a particular user.

[0101] This invention is a system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal displays the travel plan to the user. To implement the system, several pieces of software and hardware are required.

[0102] First, to start planning a trip, the user inputs desired travel information into the device. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they would like to visit. The device provides an interface for inputting this information. For example, an input form is used on the screen of a smartphone, tablet, or PC. For example, the user might input, "I would like to plan a five-day trip to Tokyo. My budget is within 100,000 yen, and I would like to visit tourist attractions and good restaurants."

[0103] Next, the device generates an API request to send the entered travel preferences to a server. Software on the device (e.g., a mobile app or web browser) organizes these preferences and sends them over the network to the server. The server receives and analyzes the request. An artificial intelligence model is installed on the server to generate a travel plan based on the user's preferences. This is done using deep learning libraries (e.g., TENSORFLOW (registered trademark) and PyTorch).

[0104] The server preprocesses the desired information and then inputs it into an AI model. Preprocessing includes reformatting the data and adding necessary information. The AI ​​model generates an optimal travel plan based on the input parameters. The model considers past travel data, the user's history, and available resources to suggest the optimal schedule and places to visit at the destination. For example, the server might generate a detailed "5-day Tokyo travel plan" that includes visits to Asakusa and Skytree on the first day, Ueno Zoo and Ameyoko Market on the second day, and so on.

[0105] The server then sends the generated travel plan to the device, which then displays it to the user. The user can review the displayed plan and make additional customizations as needed. For example, if the user wants to go to Odaiba instead of Ueno Zoo, they can enter that change into the device. The user interface is designed to allow the user to easily make changes.

[0106] The device compiles this customization information and sends it back to the server. The server again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is sent back to the device and displayed to the user as the final plan. For example, if the user inputs, "I want to go to Odaiba instead of Ueno Zoo on day 3," the server generates a new plan that includes Odaiba, and the device displays that final plan.

[0107] As described above, the present invention is a system that quickly provides flexible travel plans based on the user's wishes and can accommodate multiple customizations. This system allows users to easily create satisfactory travel plans.

[0108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0109] Step 1:

[0110] The user inputs desired travel information into the terminal.

[0111] Input: Details such as your travel destination, travel dates, budget, and activities you want to visit.

[0112] Specific behavior: Using the user interface, enter the required information into the specified form. For example, enter "I want to plan a 5-day trip to Tokyo, with a budget of 100,000 yen or less, and would like to visit tourist attractions and good restaurants."

[0113] Step 2:

[0114] The device generates an API request based on the travel preference information entered.

[0115] Input: Travel preference information entered by the user.

[0116] Data processing: Converting input information into an appropriate format, such as JSON, and packaging it as an API request.

[0117] Output: The API request to send to the server.

[0118] What it does: The device application organizes the desired information and generates a request, such as a JSON object containing data about the travel destination, itinerary, budget, and activities.

[0119] Step 3:

[0120] The device sends the generated API request to the server.

[0121] Input: API request.

[0122] What happens: The device uses a network connection (Wi-Fi, cellular, etc.) to send a request to the server, often via an HTTP POST request.

[0123] Step 4:

[0124] The server receives the API request and analyzes it.

[0125] Input: The API request sent from the device.

[0126] Data processing: Analyze the request content, extract the user's desired information, and save it as structured data.

[0127] Output: Parsed user preference information.

[0128] How it works: A server-side program receives the request, analyzes it, and extracts the necessary data, such as destination, itinerary, and budget, and stores them in the appropriate database fields.

[0129] Step 5:

[0130] The server preprocesses the user's desired information and inputs it into the artificial intelligence model.

[0131] Input: Parsed user preference information.

[0132] Data processing: Normalize data, fill in missing values, and convert to the appropriate format.

[0133] Output: Preprocessed data.

[0134] What happens: A data preprocessing script is executed to convert the user's desired information into a format that is easy for the AI ​​model to use, such as tokenizing text data and standardizing numeric data.

[0135] Step 6:

[0136] The server generates the itinerary using an artificial intelligence model.

[0137] Input: Preprocessed user preference information.

[0138] Data calculations: An artificial intelligence model calculates the optimal travel plan based on input data and generates suggested itineraries and places to visit.

[0139] Output: The generated itinerary.

[0140] What it does: An artificial intelligence model (e.g., a model implemented in TensorFlow or PyTorch) is run to generate a travel plan, including a daily schedule and details of the places to visit.

[0141] Step 7:

[0142] The server transmits the generated travel plan to the terminal.

[0143] Input: The generated itinerary.

[0144] Specific operation: The server sends the travel plan to the device as an API response, which is often an HTTP response.

[0145] Step 8:

[0146] The terminal displays the travel plan to the user.

[0147] Input: The itinerary sent from the server.

[0148] Output: The itinerary displayed to the user.

[0149] Specific operation: The application on the device receives the response and displays the itinerary in the user interface, for example, showing the schedule by day and details of the places to visit.

[0150] Step 9:

[0151] The user customizes the travel plan.

[0152] Input: The displayed itinerary.

[0153] Specific behavior: The user uses the interface to input changes to the travel plan and enters corrections or additional information. For example, the user enters, "I would like to go to Odaiba instead of Ueno Zoo on the third day."

[0154] Step 10:

[0155] The terminal collects the customization information and transmits it to the server again.

[0156] Input: Customization information entered by the user.

[0157] Data processing: Convert the customization information into an appropriate format, such as JSON, and package it as a resubmission request.

[0158] Output: The API request to resend to the server.

[0159] Specific operation: The device organizes the desired changes, generates a new request, and sends it to the server. For example, it generates a JSON object containing data about the updated schedule and places to visit.

[0160] Step 11:

[0161] The server receives the request again, analyzes it, and inputs it into the artificial intelligence model.

[0162] Input: The resubmitted API request.

[0163] Data processing: Analyze the request content to extract new customization information and preprocess it into a form suitable for model input.

[0164] Output: The new preprocessed customization information.

[0165] Specific operation: The server receives the retransmission request, analyzes the content to extract the change information, and executes the data preprocessing script to format it for model input.

[0166] Step 12:

[0167] The server again uses the artificial intelligence model to generate a new itinerary.

[0168] Input: The preprocessed new customization information.

[0169] Data computation: Artificial intelligence models recalculate optimal travel plans based on new information and generate revised itineraries and destinations.

[0170] Output: The regenerated itinerary.

[0171] Specific operation: The AI ​​model is run again to generate a new itinerary, for example, one that includes a new stop at Odaiba.

[0172] Step 13:

[0173] The server sends the regenerated itinerary to the terminal and finally displays it to the user.

[0174] Input: The regenerated itinerary.

[0175] Output: The final itinerary that is displayed to the user.

[0176] Specific operation: The server sends the new travel plan to the device as an API response, the device receives it, and displays the final plan on the user interface.

[0177] (Application example 1)

[0178] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0179] When planning a trip, it is important to provide users with their desired travel plans quickly and flexibly. There is also a growing need to obtain real-time tourist information and information on nearby brick-and-mortar stores while traveling, but conventional systems cannot adequately meet these needs. In particular, when customizing travel plans and providing real-time information, it is necessary to quickly provide optimal suggestions while taking into account the user's current location information. Therefore, a system is needed that can provide flexible travel plans based on the user's preferences, as well as efficiently provide real-time tourist information and information on nearby brick-and-mortar stores while traveling.

[0180] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0181] In this invention, the server includes means for inputting travel preferences from a user, means for transmitting the travel preference information to the server, means for the server to generate a travel plan based on the travel preference information using an artificial intelligence model, means for transmitting the generated travel plan to a terminal, means for the terminal to display the travel plan to the user, means for the user to customize the displayed travel plan, means for retransmitting the customized information to the server and causing the server to re-generate the travel plan, means for finally displaying the re-generated travel plan to the user, means for providing real-time tourist information and information on nearby brick-and-mortar stores based on the user's location information, and means for displaying the real-time information on the user's smartphone. This enables a system that utilizes the user's location information to provide real-time tourist information and information on brick-and-mortar stores and quickly respond to customization of travel plans.

[0182] "User" means an individual or entity that uses the system to plan a trip.

[0183] "Travel preference information" is detailed information about the trip the user wants to plan, including the destination, date, budget, activities they want to visit, and so on.

[0184] A "server" is a computing device that receives and analyzes travel preference information submitted by users and generates and regenerates travel plans using artificial intelligence models.

[0185] An "artificial intelligence model" is a computational algorithm that generates optimal travel plans based on past travel data and user history data.

[0186] A "travel plan" is a detailed itinerary and suggested destinations generated based on the user's travel preferences.

[0187] A "terminal" is an electronic device that a user uses to view and customize their travel plan, including a smartphone.

[0188] "Customization" refers to the act of a user making changes to a displayed itinerary, including changing specific attractions or schedules.

[0189] "Real-time information" refers to tourist information and brick-and-mortar store information provided based on the user's current location, and is characterized by its immediacy.

[0190] A "physical store" is a physical store that a user can visit while traveling, including restaurants, shops, etc.

[0191] A "smartphone" is a mobile phone that can connect to the Internet and use applications, and in many cases is equipped with GPS functionality.

[0192] This invention relates to a travel support system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal presents and customizes the plan to the user in real time. Specific implementation methods of this system are described below.

[0193] Key components of the system

[0194] 1. User device (smartphone)

[0195] The user terminal is the device that the user uses to input desired travel information and review and customize the generated travel plan. A smartphone is usually used, but tablets and PCs can also be used.

[0196] 2. Server

[0197] The server receives travel information sent from the user's device and generates and regenerates travel plans based on that information. A generative AI model is used to generate travel plans.

[0198] 3. Generative AI Models

[0199] The generative AI model runs on a server and is an algorithm that generates optimal travel plans based on the travel preferences entered, while referencing past travel data and user history.

[0200] 4. Network

[0201] The Internet is used as a network for communication between user terminals and servers.

[0202] Specific methods for carrying out the invention

[0203] 1. User Input

[0204] Users input their travel preferences through an application on their smartphone, including destination, travel dates, budget, and activities they would like to visit.

[0205] Example prompt sentence:

[0206] Destination: Kyoto

[0207] Start date (YYYY-MM-DD):2023-11-01

[0208] End date (YYYY-MM-DD):2023-11-05

[0209] Budget: 100,000

[0210] Activities you would like to visit (separated by commas): Kiyomizu-dera Temple, Kinkaku-ji Temple, Gion, Arashiyama

[0211] 2. Data transmission and analysis

[0212] The user device sends the entered travel preference information to the server, which then analyzes the travel preference information sent to the server as an API request.

[0213] 3. Generate a travel plan

[0214] The generative AI model on the server generates an optimal travel plan based on the user's travel preferences. The generated plan is a detailed itinerary that reflects the user's preferences.

[0215] Examples:

[0216] The schedule for each day is detailed, with a visit to Kiyomizu-dera Temple on the first day and Kinkaku-ji Temple on the second day.

[0217] 4. View and customize your plan

[0218] The server sends the generated travel plan to the user's device, where the user can view the plan on their smartphone. Users can also customize the plan, for example, by changing the destinations or schedule.

[0219] 5. Real-time information provision

[0220] While traveling, real-time tourist information and information on nearby physical stores are provided based on the user's location information, allowing users to receive the most appropriate tourist information, restaurant and shop information, etc. based on their current location.

[0221] This system allows users to easily create, check, and customize travel plans that suit their preferences, and also provides real-time information during their trip, resulting in a more satisfying travel experience for users.

[0222] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0223] Specific processing steps of the program

[0224] Step 1:

[0225] The user inputs desired travel information into their smartphone. Input items include the destination, travel dates, budget, and activities they want to visit. For example, information such as "Kyoto," "2023-11-01 ~ 2023-11-05," "budget 100,000 yen," and "Kiyomizu-dera Temple, Kinkaku-ji Temple, Gion, Arashiyama" is input. The input information is preprocessed for the next process.

[0226] Input: Destination, travel dates, budget, activities you want to visit

[0227] Output: The desired information formatted from the input information

[0228] Step 2:

[0229] The device sends the desired information obtained in step 1 to the server as an API request. The request is sent using an HTTP POST request, and the request data is serialized in JSON format. The server receives this request.

[0230] Input: Travel preference information (JSON format)

[0231] Output: The data sent as a request to the server.

[0232] Step 3:

[0233] The server receives travel preferences and inputs them into the generative AI model. The generative AI model generates an optimal travel plan based on the preferences, referencing past travel data and the user's history data. The AI ​​model considers different parameters to create a detailed itinerary. For example, a specific schedule is generated such as "Day 1: Visit Kiyomizu-dera Temple in the morning, stroll through Gion in the afternoon."

[0234] Input: Travel preference information

[0235] Output: Generated itinerary

[0236] Step 4:

[0237] The server serializes the generated itinerary in JSON format and sends it to the device, which receives the data, parses it, and displays it in a format that the user can view.

[0238] Input: Generated travel plan (JSON format)

[0239] Output: The travel plan displayed on the user's device

[0240] Step 5:

[0241] The user checks the displayed itinerary and customizes it as necessary. For example, the user may make changes such as "I want to cancel Kinkaku-ji Temple on the second day and visit Arashiyama instead." This information is then sent back to the server from the device.

[0242] Input: Customization information

[0243] Output: Customization data sent from the device to the server

[0244] Step 6:

[0245] The server receives the resubmitted customization information and uses the generative AI model again to generate a new travel plan that reflects the user's latest requests.

[0246] Input: Customization information

[0247] Output: Regenerated itinerary

[0248] Step 7:

[0249] The server serializes the regenerated itinerary into JSON format and resends it to the device, which parses the data and displays it again to the user, thus finalizing the itinerary.

[0250] Input: Regenerated itinerary (JSON format)

[0251] Output: The final itinerary displayed on the user's device

[0252] Step 8:

[0253] During a trip, real-time tourist information and information on nearby brick-and-mortar stores are provided using the user's location information. The user's current location is periodically sent to the server using the GPS function of the user's device. Based on this location information, the server generates information on nearby tourist attractions, restaurants, and shops and provides it to the user.

[0254] Input: User's location

[0255] Output: Real-time tourist information and brick-and-mortar store information

[0256] The above are the processing steps of the specific program for carrying out the present invention.

[0257] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0258] This invention relates to a system that generates personalized travel plans by combining a user's desired travel information with an emotion engine that recognizes the user's emotions. To implement this system, the following procedures and requirements must be met:

[0259] First, to start planning a trip, the user inputs desired travel information into the terminal. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit (e.g., tourist attractions and restaurants). The terminal provides an interface for inputting this information.

[0260] Example: A user types into a terminal, "I want to plan a 5-day trip to Tokyo. My budget is under 100,000 yen, and I want to visit tourist attractions and good restaurants."

[0261] The emotion engine then analyzes the user's input and non-verbal data (e.g., voice tone, facial expressions), identifies the user's emotional state (e.g., excited, relaxed, tired), and sends that information to the server.

[0262] For example, if a user inputs the emotion "excitement" into the device, the emotion engine will analyze the emotion and determine that the user is in an "excited" state.

[0263] The device generates an API request to send travel preference information and emotion data analyzed by the emotion engine to the server. The server receives and analyzes this request. The server is installed with an artificial intelligence model that generates a travel plan based on the user's preference information and emotion information.

[0264] The server preprocesses the desired information and emotional information and then inputs it into an artificial intelligence model. This artificial intelligence model is capable of generating an optimal travel plan based on the input parameters. The model considers past travel data, user history information, and available resources to propose an optimal schedule and places to visit at the destination. Furthermore, by reflecting emotional information, the model proposes a plan that is tailored to the user's emotional state.

[0265] Example: The server creates a "5-day Tokyo travel plan" and suggests exciting tourist spots (Asakusa and Skytree) on the first day to accommodate an excited user, and calm places (Ueno Zoo and Ameyoko Market) on the second day to accommodate a relaxed user.

[0266] The server then sends the generated itinerary to the device, which then displays it to the user. The user can review the displayed itinerary and make additional customizations as needed. For example, if the user wants to visit Odaiba instead of Ueno Zoo, they can input that change into the device.

[0267] The device compiles this customization information and sends it back to the server, which again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is then sent back to the device and displayed to the user as the final plan.

[0268] Example: If a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[0269] In this way, the present invention realizes a system that improves the quality of travel plans by quickly providing flexible travel plans based on the user's wishes and making personalized suggestions that are tailored to the user's emotional state.

[0270] The processing flow will be explained below.

[0271] Step 1:

[0272] The user inputs travel preferences into the terminal, such as destination, travel dates, budget, and activities of interest.

[0273] Step 2:

[0274] The emotion engine analyzes user input and non-verbal data (e.g., vocal tone, facial expression) to identify emotional states.

[0275] Step 3:

[0276] The device compiles travel preference information and analyzed emotion data and converts it into a dataset.

[0277] Step 4:

[0278] The device generates an API request to send the compiled data set to the server, including travel preference information and emotion data.

[0279] Step 5:

[0280] The server receives the API request, analyzes the request, and extracts travel preference information and emotion data.

[0281] Step 6:

[0282] The server pre-processes the travel preference and emotion data, for example by checking the data integrity and converting it into a format suitable for the artificial intelligence model.

[0283] Step 7:

[0284] The server inputs the preprocessed data into an artificial intelligence model, which then generates an optimal travel plan based on the input data.

[0285] Step 8:

[0286] The server compiles the generated itinerary into a dataset, for example creating a detailed schedule for each day.

[0287] Step 9:

[0288] An API response is generated to send the travel plan generated by the server to the terminal.

[0289] Step 10:

[0290] The device receives the API response from the server, analyzes the received data, and displays it to the user.

[0291] Step 11:

[0292] The user reviews the displayed itinerary, customizes it as needed, and inputs any corrections or additions they wish to make into the device.

[0293] Step 12:

[0294] The device collects the user's customization information and creates a new data set.

[0295] Step 13:

[0296] The device resends the customized data set to the server, and generates another API request and sends it to the server.

[0297] Step 14:

[0298] The server receives the API request again and parses the new preferences, extracting customized travel preferences and sentiment data.

[0299] Step 15:

[0300] The server pre-processes the customized travel preference and emotion data, performs data integrity checks, and converts it into a format suitable for artificial intelligence models.

[0301] Step 16:

[0302] The server then feeds the preprocessed data back into the artificial intelligence model, which then generates a customized itinerary based on the new data.

[0303] Step 17:

[0304] The server compiles the regenerated itinerary into a dataset, e.g., creating a detailed schedule that reflects the changes.

[0305] Step 18:

[0306] The server generates the final API response to send the regenerated itinerary to the device.

[0307] Step 19:

[0308] The device receives the regenerated API response from the server, parses the received data, and displays the final plan to the user.

[0309] Through this series of steps, the system allows users to obtain a travel plan that meets their needs and can also provide personalized suggestions based on their emotional state.

[0310] Example 2

[0311] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0312] In modern travel planning, there is a need to quickly and accurately generate personalized itineraries that reflect users' diverse desires and emotions. However, conventional systems have difficulty incorporating users' specific desires and real-time emotions, which makes it difficult to increase user satisfaction.

[0313] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0314] In this invention, the server includes means for inputting travel preference information from a user, means for collecting data for identifying the user's emotions, means for transmitting the travel preference information and the collected emotion data to the server, means for the server to generate an itinerary based on the travel preference information and emotion data using an artificial intelligence model, means for transmitting the generated itinerary to a terminal, means for the terminal to display the itinerary to the user, means for the user to customize the displayed itinerary, means for retransmitting the customized information to the server and the server to generate a new itinerary, and means for finally displaying the regenerated itinerary to the user. This makes it possible to quickly and accurately generate a personalized itinerary that reflects the user's specific preferences and real-time emotions.

[0315] "User's desired travel information" is detailed information about the user's desired trip, such as travel destination, travel itinerary, budget, and activities at the destination.

[0316] "Data for identifying the user's emotions" refers to data that includes non-verbal information about the user, such as tone of voice and facial expressions.

[0317] The "server" is a central processing system that receives the user's travel preferences and emotion data and generates a travel plan using a generative AI model.

[0318] A "generative AI model" is an artificial intelligence algorithm that references past travel data and user history information to create optimal travel plans based on the user's preferences and emotional data.

[0319] A "terminal" is a device that allows a user to input desired travel information and display a travel plan sent from a server.

[0320] An "API request" is a request for data transmission made from a terminal to a server, and includes travel preference information and emotion data.

[0321] A "travel plan" is a plan that includes specific travel itineraries, destinations, recommended activities, etc., generated based on the user's desired information and emotional state.

[0322] "Customization" refers to the user making changes or additions to the displayed travel plan.

[0323] "Historical Trip Data" means details about previously recorded trips that are used to create similar trip itineraries.

[0324] "User history information" is history data for each user, such as trips the user has taken in the past and travel preferences that the user has entered up to now.

[0325] The present invention relates to a system that generates a more personalized travel plan by inputting user travel preferences and recognizing the user's emotions. The system includes a terminal, a server, and an emotion engine.

[0326] First, to start planning a trip, the user inputs their desired travel information into the device. Using the device interface, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit. The device collects this information and prepares it for the next process.

[0327] For example, consider the case where a user inputs, "I want to plan a 5-day trip to Tokyo, with a budget of 100,000 yen or less, and want to visit tourist attractions and good restaurants."

[0328] The device then analyzes the user's emotions using an emotion engine, which collects and analyzes the user's non-verbal data (voice tone and facial expressions) in real time to determine the user's emotional state, such as whether they are excited, relaxed, or tired.

[0329] For example, if the user utters the word "fun" in an excited tone, the emotion engine will interpret this as the user being "excited."

[0330] The device sends the user's travel preference information and analyzed emotion data together to the server as an API request, and the server receives the request and analyzes the data.

[0331] The server inputs the user's desired information and emotional data into an AI model to generate the optimal travel plan. This generative AI model then uses past travel data and user history information to create a travel plan that suits the user's preferences.

[0332] For example, the server might create a "5-day Tokyo travel plan" and suggest sightseeing in Asakusa and Skytree on the first day, in response to a user's excited state, and then suggest visiting Ueno Zoo and Ameyoko Market on the second day, in response to a user's relaxed state.

[0333] The server sends the generated travel plan to the terminal, which then displays the plan to the user, who can review the displayed plan and make further customizations as needed.

[0334] Now, if the user decides to visit Odaiba instead of Ueno Zoo, they enter that change into their device. The device compiles the customization information and sends it back to the server. The server again uses the generative AI model to regenerate a customized itinerary based on the new data. The regenerated itinerary is sent back to the device and displayed to the user as the final itinerary.

[0335] For example, if a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[0336] In this way, the present invention realizes a system that improves the quality of travel plans by quickly providing flexible travel plans based on the user's wishes and making personalized suggestions that are tailored to the user's emotional state.

[0337] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0338] (Processing flow)

[0339] Step 1: Enter user travel information

[0340] The user inputs their travel preferences. Using the device interface, the user inputs detailed information such as their destination, travel dates, budget, and activities they would like to visit.

[0341] Input: destination, travel dates, budget, activities you want to visit, etc.

[0342] Specific behavior: A user enters information using text boxes and drop-down menus on the device.

[0343] Output: Travel preference data is saved on the device

[0344] Step 2: Collect and analyze emotion data

[0345] The device analyzes the user's emotions using an emotion engine, which collects and analyzes non-verbal data such as voice tone and facial expressions.

[0346] Input: Non-verbal data such as tone of voice, facial expressions, etc.

[0347] Specific operation: Collects the user's voice and facial expressions in real time using the device's built-in camera and microphone.

[0348] Data processing: Emotion engine uses voice and image analysis algorithms to determine emotional state

[0349] Output: User emotion data

[0350] Step 3: Send the data

[0351] The device sends travel preference information and emotion data to the server as an API request.

[0352] Input: Travel preference data, emotion data

[0353] Specific operation: The device converts the data into JSON format and sends it to the server using the HTTP protocol.

[0354] Data manipulation: structuring and encoding data

[0355] Output: The API request received by the server

[0356] Step 4: Generate your itinerary

[0357] The server analyzes the received data and generates an optimal travel plan using an artificial intelligence model.

[0358] Input: Travel preference information, emotional data

[0359] How it works: The server analyzes the data and uses past travel data and user history information to feed the generative AI model.

[0360] Data computation: Generative AI models run algorithms to create optimal travel plans

[0361] Output: Generated itinerary data

[0362] Step 5: View your plan

[0363] The server transmits the generated travel plan to the terminal, which displays it to the user.

[0364] Input: Generated itinerary data

[0365] Specific operation: The server sends a travel plan in JSON format to the device, which parses the plan and displays it on the interface.

[0366] Data processing: building and encoding plans, parsing for UI display

[0367] Output: A displayed itinerary

[0368] Step 6: Customize and Regenerate

[0369] The user then performs additional customizations on the displayed travel plan, and the customization information is sent from the device back to the server, which then generates a new plan using the artificial intelligence model again.

[0370] Input: Customization information

[0371] What happens: The user enters plan changes using the device interface, and the device sends the information to the server.

[0372] Data Processing: Collecting and Sending Customization Information

[0373] Output: Customization information received by the server, regenerated itinerary

[0374] This process flow allows users to quickly obtain and further customize a personalized travel plan that is tailored to their desires and feelings.

[0375] (Application example 2)

[0376] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0377] Conventional shopping systems lack personalized product suggestions that take into account the user's emotional state and lack mechanisms to improve user satisfaction. As a result, it takes time to find the optimal product that corresponds to a specific emotional state, making it difficult to provide an efficient shopping experience.

[0378] The specification process by the specification processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server has a means for the user to input a desired product,

[0379] means for transmitting the desired product information to a server;

[0380] a means for the emotion engine to analyze the user's emotion;

[0381] means for transmitting the analyzed emotion information to a server;

[0382] a means for generating product suggestions based on the desired product information and emotion information by using an artificial intelligence model in a server;

[0383] means for transmitting the generated product proposal to a terminal;

[0384] means for the terminal to display the product proposal to the user;

[0385] means for a user to customize the displayed product suggestions;

[0386] means for retransmitting the customized information to a server, and the server generating product suggestions again;

[0387] The method further includes means for finally displaying the regenerated product suggestions to the user, thereby enabling personalized product suggestions according to the user's emotional state.

[0388] "Desired product information" refers to detailed information such as the type of product the user wishes to purchase, their budget, and their preferred style.

[0389] "Emotion engine" refers to software or hardware for analyzing a user's emotional state.

[0390] "Analyzed emotional information" refers to data about a user's emotional state that has been analyzed by the emotion engine.

[0391] "Artificial intelligence model" refers to a system that includes an algorithm for generating optimal product suggestions based on a user's desired product information and emotional information.

[0392] "Product suggestions" refers to specific product lists and suggestions provided to users based on desired product information and analyzed emotional information.

[0393] "Customization" refers to an operation in which a user adds conditions or makes changes based on the displayed product proposals.

[0394] "Regeneration" refers to the process of recreating product proposals using an artificial intelligence model based on customized information.

[0395] This invention relates to a shopping assistant system that analyzes user emotions and generates personalized product recommendations. The system runs on devices such as smartphones, smart glasses, or head-mounted displays, and recommends optimal products to users.

[0396] The main components of the system are:

[0397] 1. A means for users to input desired products: Users use their smartphones or other devices to provide desired product information through a form to input information about the products they want to purchase (e.g., type, budget, style) or through a voice assistant.

[0398] 2. Emotion Engine: A software component that detects and analyzes the user's vocal tone and facial expressions. Specific software used is Google® Cloud's Speech-to-Text API and Microsoft® Azure® Cognitive Services.

[0399] 3. Means for transmitting the sales information and analyzed sentiment information to the server: This information is transmitted in real time to the server for further processing. Data is sent and received using API requests over the network.

[0400] 4. Artificial intelligence model on the server: The server is installed with artificial intelligence models such as TensorFlow and GPT-4 (registered trademark), which generate product suggestions based on the user's desired product information and emotional information. Based on this information, the server selects the most suitable product, taking into account past purchase data and user history data.

[0401] 5. Generating and sending product suggestions to the terminal: The generated product suggestions are sent to the terminal and presented visually or audibly to the user.

[0402] 6. Customizing Product Proposals: The user can input further conditions or modifications based on the displayed product proposals. This feedback is sent back to the server, and an updated proposal is generated.

[0403] 7. Displaying the final product proposal: The updated product proposal is resent to the terminal and finally provided to the user.

[0404] For example, if a user enters the desired product information as "I want a candle with a relaxing scent, but my budget is under 2,000 yen. I'm also looking for calming sweets," and the emotion engine analyzes the user's relaxed state, the server will generate suggestions for candles and sweets with a relaxing effect based on that emotional state.The user can then exclude products they don't like from the suggested products or add more specific conditions, and a re-optimized product list will be provided.

[0405] Examples of prompts:

[0406] "I want a candle with a relaxing scent, but my budget is under 2000 yen. I'm also looking for some calming sweets."

[0407] In this way, the present invention provides a system that takes into account the user's emotional state and can quickly provide personalized product suggestions, helping to make the shopping experience more satisfying.

[0408] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0409] Step 1:

[0410] Users input desired product information using a smartphone or other device, providing the type of product they want to purchase, their budget, and preferred style via text form or voice input.

[0411] Input: Desired product information (e.g., "I'd like a candle with a relaxing scent, but my budget is under 2000 yen. I'm also looking for some relaxing sweets.")

[0412] Output: Desired product information processed on the user's device

[0413] Step 2:

[0414] The device activates an emotion engine that analyzes the user's voice tone and facial expressions in real time via the camera and microphone, and uses Google Cloud's Speech-to-Text API and Microsoft Azure Cognitive Services to analyze the user's emotional state.

[0415] Input: User's voice tone, facial expression

[0416] Output: Analyzed emotional information (e.g., relaxed state)

[0417] Step 3:

[0418] The device sends the desired product information and analyzed emotion information to the server via the network as an API request.

[0419] Input: Desired product information, analyzed emotion information

[0420] Output: API request sent to the server

[0421] Step 4:

[0422] The server receives the desired product information and sentiment information, and preprocesses this information before inputting it into an artificial intelligence model (TensorFlow or GPT-4). Preprocessing includes data conversion and transformation into a unified format.

[0423] Input: Desired product information, analyzed emotion information

[0424] Output: Preprocessed data

[0425] Step 5:

[0426] The server inputs the preprocessed data into an AI model to generate optimal product suggestions. The AI ​​model also takes into account past purchase data and user history data to make more accurate suggestions.

[0427] Input: Preprocessed data, historical purchase data, user history data

[0428] Output: Product suggestions (e.g., relaxing candles, sweets)

[0429] Step 6:

[0430] The server transmits the generated product proposals to the terminal via the network.

[0431] Input: Product proposal

[0432] Output: Send request to user terminal

[0433] Step 7:

[0434] The terminal presents the received product proposal to the user visually or audibly, and the user inputs further conditions or changes based on the displayed product proposal.

[0435] Input: Product proposal

[0436] Output: User feedback (e.g., "Show me more products of a specific brand")

[0437] Step 8:

[0438] The user's feedback is resubmitted from the terminal to the server, which again uses the artificial intelligence model to generate updated product suggestions.

[0439] Input: User feedback

[0440] Output: Regenerated product suggestions

[0441] Step 9:

[0442] The server transmits the regenerated product proposals to the terminal via the network, and finally provides them to the user.

[0443] Input: Regenerated product suggestions

[0444] Output: Display of final product suggestions

[0445] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0446] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0447] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0448] [Second embodiment]

[0449] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0450] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0451] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0452] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0453] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0454] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0455] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0456] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0457] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0458] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0459] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0460] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0461] This invention relates to a system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal displays the travel plan to the user. To implement this system, the following procedures and requirements must be met:

[0462] First, to start planning a trip, the user inputs desired travel information into the terminal. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit (e.g., tourist attractions and restaurants). The terminal provides an interface for inputting this information.

[0463] Example: A user types into a terminal, "I want to plan a 5-day trip to Tokyo. My budget is under 100,000 yen, and I want to visit tourist attractions and good restaurants."

[0464] The device then generates an API request to send the entered travel preferences to a server, which receives and analyzes the request and installs an artificial intelligence model to generate a travel plan based on the user's preferences.

[0465] The server preprocesses the desired information and then inputs it into an artificial intelligence model that is capable of generating an optimal travel plan based on the input parameters. The model considers past travel data, user history, and available resources to suggest optimal schedules and places to visit at the destination.

[0466] Example: The server generates a detailed "5-day Tokyo travel plan" that includes visiting Asakusa and Skytree on the first day, Ueno Zoo and Ameyoko Market on the second day, etc.

[0467] The server then sends the generated itinerary to the device, which then displays it to the user. The user can review the displayed itinerary and make additional customizations as needed. For example, if the user wants to visit Odaiba instead of Ueno Zoo, they can input that change into the device.

[0468] The device compiles this customization information and sends it back to the server, which again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is then sent back to the device and displayed to the user as the final plan.

[0469] Example: If a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[0470] In this way, the present invention realizes a system that quickly provides flexible travel plans based on the user's wishes and can accommodate multiple customizations.

[0471] The processing flow will be explained below.

[0472] Step 1:

[0473] The user inputs travel preferences into the terminal, such as destination, travel dates, budget, and activities of interest.

[0474] Step 2:

[0475] The device collects the travel preference information entered and converts the data into a single data set.

[0476] Step 3:

[0477] The device sends the compiled data set to the server, and generates an API request and sends it to the server.

[0478] Step 4:

[0479] The server receives the API request, analyzes the request, and extracts travel preference information.

[0480] Step 5:

[0481] The server pre-processes the travel preference information, for example checking the data for consistency and converting it into a format suitable for artificial intelligence models.

[0482] Step 6:

[0483] The server inputs the preprocessed data into an artificial intelligence model, which then generates an optimal travel plan based on the input data.

[0484] Step 7:

[0485] The server compiles the generated itinerary into a dataset, for example creating a detailed schedule for each day.

[0486] Step 8:

[0487] The server sends the generated travel plan to the device. The travel plan is sent as an API response.

[0488] Step 9:

[0489] The device receives the travel plan from the server, analyzes the data, and displays it to the user.

[0490] Step 10:

[0491] The user can customize the displayed travel plan by entering any corrections or additions they wish to make into the device.

[0492] Step 11:

[0493] The device collects the user customization information and creates a new dataset.

[0494] Step 12:

[0495] The device resends the customized data set to the server, and generates another API request and sends it to the server.

[0496] Step 13:

[0497] The server receives the API request again and analyzes the new request information.

[0498] Step 14:

[0499] The server preprocesses the new request information, performs data integrity checks, and converts it into a format suitable for artificial intelligence models.

[0500] Step 15:

[0501] The server then feeds the preprocessed data back into the artificial intelligence model, which then generates a customized itinerary based on the new data.

[0502] Step 16:

[0503] The server compiles the regenerated itinerary into a dataset, e.g., creating a detailed schedule that reflects the changes.

[0504] Step 17:

[0505] The server sends the regenerated travel plan to the device and the final plan as an API response.

[0506] Step 18:

[0507] The terminal receives the regenerated travel plan from the server, analyzes the data, and displays the final plan to the user.

[0508] Through this series of steps, the user can obtain a travel plan that meets their needs, and a system is realized that can flexibly accommodate additional customization.

[0509] Example 1

[0510] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0511] Conventional travel plan creation systems have had the challenge of responding quickly and flexibly to user requests. Creating the optimal plan based on the user's desired travel information requires advanced data analysis and individual customization, which conventional systems find difficult. It is also difficult to respond quickly to user requests for changes, and multiple customization processes must proceed smoothly.

[0512] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0513] In this invention, the server includes means for inputting travel preference information from a user, means for transmitting the travel preference information to the server, means for generating a travel plan based on the travel preference information using an artificial intelligence model, means for transmitting the generated travel plan to a terminal, means for the terminal to display the travel plan to the user, means for the user to customize the displayed travel plan, means for retransmitting the customized information to the server and causing the server to regenerate the travel plan, and means for finally displaying the regenerated travel plan to the user. This makes it possible to provide flexible and prompt travel plans based on the user's preferences.

[0514] "User" refers to an individual or organization who inputs desired information to create a travel plan and reviews and customizes the generated plan.

[0515] "Desired information" refers to detailed information entered by the user, such as travel destination, travel itinerary, budget, and activities desired to visit.

[0516] "Terminal" refers to a device used by a user to input desired information, and includes smartphones, tablets, PCs, etc.

[0517] "Server" refers to the central computing system that receives, analyzes, processes, and generates travel plans based on user-submitted preferences.

[0518] "Artificial intelligence model" refers to the algorithms and computational models that generate optimal travel plans based on input data, and are built using deep learning libraries, etc.

[0519] An "API request" is a standardized form of digital communication that allows a device to send desired information to a server.

[0520] A "travel plan" refers to a plan that includes a specific travel schedule and suggestions of places to visit, which is generated by the server based on the user's desired information.

[0521] "Customization" refers to the user making additional changes or adjustments to the generated itinerary.

[0522] "Network" refers to a connection means such as the Internet or a local area network that allows servers and terminals to communicate with each other.

[0523] "Historical Travel Data" refers to data previously collected about other users' travel information and travel plans.

[0524] "History data" refers to data that records information about past trips and behavioral patterns of a particular user.

[0525] This invention is a system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal displays the travel plan to the user. To implement the system, several pieces of software and hardware are required.

[0526] First, to start planning a trip, the user inputs desired travel information into the device. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they would like to visit. The device provides an interface for inputting this information. For example, an input form is used on the screen of a smartphone, tablet, or PC. For example, the user might input, "I would like to plan a five-day trip to Tokyo. My budget is within 100,000 yen, and I would like to visit tourist attractions and good restaurants."

[0527] The device then generates an API request to send the entered travel preferences to a server. Software on the device (e.g., a mobile app or web browser) organizes these preferences and sends them over the network to the server. The server receives and analyzes the request. The server has an artificial intelligence model installed that generates a travel plan based on the user's preferences. This is done using deep learning libraries (e.g., TensorFlow and PyTorch).

[0528] The server preprocesses the desired information and then inputs it into an AI model. Preprocessing includes reformatting the data and adding necessary information. The AI ​​model generates an optimal travel plan based on the input parameters. The model considers past travel data, the user's history, and available resources to suggest the optimal schedule and places to visit at the destination. For example, the server might generate a detailed "5-day Tokyo travel plan" that includes visits to Asakusa and Skytree on the first day, Ueno Zoo and Ameyoko Market on the second day, and so on.

[0529] The server then sends the generated travel plan to the device, which then displays it to the user. The user can review the displayed plan and make additional customizations as needed. For example, if the user wants to go to Odaiba instead of Ueno Zoo, they can enter that change into the device. The user interface is designed to allow the user to easily make changes.

[0530] The device compiles this customization information and sends it back to the server. The server again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is sent back to the device and displayed to the user as the final plan. For example, if the user inputs, "I want to go to Odaiba instead of Ueno Zoo on day 3," the server generates a new plan that includes Odaiba, and the device displays that final plan.

[0531] As described above, the present invention is a system that quickly provides flexible travel plans based on the user's wishes and can accommodate multiple customizations. This system allows users to easily create satisfactory travel plans.

[0532] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0533] Step 1:

[0534] The user inputs desired travel information into the terminal.

[0535] Input: Details such as your travel destination, travel dates, budget, and activities you want to visit.

[0536] Specific behavior: Using the user interface, enter the required information into the specified form. For example, enter "I want to plan a 5-day trip to Tokyo, with a budget of 100,000 yen or less, and would like to visit tourist attractions and good restaurants."

[0537] Step 2:

[0538] The device generates an API request based on the travel preference information entered.

[0539] Input: Travel preference information entered by the user.

[0540] Data processing: Converting input information into an appropriate format, such as JSON, and packaging it as an API request.

[0541] Output: The API request to send to the server.

[0542] What it does: The device application organizes the desired information and generates a request, such as a JSON object containing data about the travel destination, itinerary, budget, and activities.

[0543] Step 3:

[0544] The device sends the generated API request to the server.

[0545] Input: API request.

[0546] What happens: The device uses a network connection (Wi-Fi, cellular, etc.) to send a request to the server, often via an HTTP POST request.

[0547] Step 4:

[0548] The server receives the API request and analyzes it.

[0549] Input: The API request sent from the device.

[0550] Data processing: Analyze the request content, extract the user's desired information, and save it as structured data.

[0551] Output: Parsed user preference information.

[0552] How it works: A server-side program receives the request, analyzes it, and extracts the necessary data, such as destination, itinerary, and budget, and stores them in the appropriate database fields.

[0553] Step 5:

[0554] The server preprocesses the user's desired information and inputs it into the artificial intelligence model.

[0555] Input: Parsed user preference information.

[0556] Data processing: Normalize data, fill in missing values, and convert to the appropriate format.

[0557] Output: Preprocessed data.

[0558] What happens: A data preprocessing script is executed to convert the user's desired information into a format that is easy for the AI ​​model to use, such as tokenizing text data and standardizing numeric data.

[0559] Step 6:

[0560] The server generates the itinerary using an artificial intelligence model.

[0561] Input: Preprocessed user preference information.

[0562] Data calculations: An artificial intelligence model calculates the optimal travel plan based on input data and generates suggested itineraries and places to visit.

[0563] Output: The generated itinerary.

[0564] What it does: An artificial intelligence model (e.g., a model implemented in TensorFlow or PyTorch) is run to generate a travel plan, including a daily schedule and details of the places to visit.

[0565] Step 7:

[0566] The server transmits the generated travel plan to the terminal.

[0567] Input: The generated itinerary.

[0568] Specific operation: The server sends the travel plan to the device as an API response, which is often an HTTP response.

[0569] Step 8:

[0570] The terminal displays the travel plan to the user.

[0571] Input: The itinerary sent from the server.

[0572] Output: The itinerary displayed to the user.

[0573] Specific operation: The application on the device receives the response and displays the itinerary in the user interface, for example, showing the schedule by day and details of the places to visit.

[0574] Step 9:

[0575] The user customizes the travel plan.

[0576] Input: The displayed itinerary.

[0577] Specific behavior: The user uses the interface to input changes to the travel plan and enters corrections or additional information. For example, the user enters, "I would like to go to Odaiba instead of Ueno Zoo on the third day."

[0578] Step 10:

[0579] The terminal collects the customization information and transmits it to the server again.

[0580] Input: Customization information entered by the user.

[0581] Data processing: Convert the customization information into an appropriate format, such as JSON, and package it as a resubmission request.

[0582] Output: The API request to resend to the server.

[0583] Specific operation: The device organizes the desired changes, generates a new request, and sends it to the server. For example, it generates a JSON object containing data about the updated schedule and places to visit.

[0584] Step 11:

[0585] The server receives the request again, analyzes it, and inputs it into the artificial intelligence model.

[0586] Input: The resubmitted API request.

[0587] Data processing: Analyze the request content to extract new customization information and preprocess it into a form suitable for model input.

[0588] Output: The new preprocessed customization information.

[0589] Specific operation: The server receives the retransmission request, analyzes the content to extract the change information, and executes the data preprocessing script to format it for model input.

[0590] Step 12:

[0591] The server again uses the artificial intelligence model to generate a new itinerary.

[0592] Input: The preprocessed new customization information.

[0593] Data computation: Artificial intelligence models recalculate optimal travel plans based on new information and generate revised itineraries and destinations.

[0594] Output: The regenerated itinerary.

[0595] Specific operation: The AI ​​model is run again to generate a new itinerary, for example, one that includes a new stop at Odaiba.

[0596] Step 13:

[0597] The server sends the regenerated itinerary to the terminal and finally displays it to the user.

[0598] Input: The regenerated itinerary.

[0599] Output: The final itinerary that is displayed to the user.

[0600] Specific operation: The server sends the new travel plan to the device as an API response, the device receives it, and displays the final plan on the user interface.

[0601] (Application example 1)

[0602] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0603] When planning a trip, it is important to provide users with their desired travel plans quickly and flexibly. There is also a growing need to obtain real-time tourist information and information on nearby brick-and-mortar stores while traveling, but conventional systems cannot adequately meet these needs. In particular, when customizing travel plans and providing real-time information, it is necessary to quickly provide optimal suggestions while taking into account the user's current location information. Therefore, a system is needed that can provide flexible travel plans based on the user's preferences, as well as efficiently provide real-time tourist information and information on nearby brick-and-mortar stores while traveling.

[0604] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0605] In this invention, the server includes means for inputting travel preferences from a user, means for transmitting the travel preference information to the server, means for the server to generate a travel plan based on the travel preference information using an artificial intelligence model, means for transmitting the generated travel plan to a terminal, means for the terminal to display the travel plan to the user, means for the user to customize the displayed travel plan, means for retransmitting the customized information to the server and causing the server to re-generate the travel plan, means for finally displaying the re-generated travel plan to the user, means for providing real-time tourist information and information on nearby brick-and-mortar stores based on the user's location information, and means for displaying the real-time information on the user's smartphone. This enables a system that utilizes the user's location information to provide real-time tourist information and information on brick-and-mortar stores and quickly respond to customization of travel plans.

[0606] "User" means an individual or entity that uses the system to plan a trip.

[0607] "Travel preference information" is detailed information about the trip the user wants to plan, including the destination, date, budget, activities they want to visit, and so on.

[0608] A "server" is a computing device that receives and analyzes travel preference information submitted by users and generates and regenerates travel plans using artificial intelligence models.

[0609] An "artificial intelligence model" is a computational algorithm that generates optimal travel plans based on past travel data and user history data.

[0610] A "travel plan" is a detailed itinerary and suggested destinations generated based on the user's travel preferences.

[0611] A "terminal" is an electronic device that a user uses to view and customize their travel plan, including a smartphone.

[0612] "Customization" refers to the act of a user making changes to a displayed itinerary, including changing specific attractions or schedules.

[0613] "Real-time information" refers to tourist information and brick-and-mortar store information provided based on the user's current location, and is characterized by its immediacy.

[0614] A "physical store" is a physical store that a user can visit while traveling, including restaurants, shops, etc.

[0615] A "smartphone" is a mobile phone that can connect to the Internet and use applications, and in many cases is equipped with GPS functionality.

[0616] This invention relates to a travel support system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal presents and customizes the plan to the user in real time. Specific implementation methods of this system are described below.

[0617] Key components of the system

[0618] 1. User device (smartphone)

[0619] The user terminal is the device that the user uses to input desired travel information and review and customize the generated travel plan. A smartphone is usually used, but tablets and PCs can also be used.

[0620] 2. Server

[0621] The server receives travel information sent from the user's device and generates and regenerates travel plans based on that information. A generative AI model is used to generate travel plans.

[0622] 3. Generative AI Models

[0623] The generative AI model runs on a server and is an algorithm that generates optimal travel plans based on the travel preferences entered, while referencing past travel data and user history.

[0624] 4. Network

[0625] The Internet is used as a network for communication between user terminals and servers.

[0626] Specific methods for carrying out the invention

[0627] 1. User Input

[0628] Users input their travel preferences through an application on their smartphone, including destination, travel dates, budget, and activities they would like to visit.

[0629] Example prompt sentence:

[0630] Destination: Kyoto

[0631] Start date (YYYY-MM-DD):2023-11-01

[0632] End date (YYYY-MM-DD):2023-11-05

[0633] Budget: 100,000

[0634] Activities you would like to visit (separated by commas): Kiyomizu-dera Temple, Kinkaku-ji Temple, Gion, Arashiyama

[0635] 2. Data transmission and analysis

[0636] The user device sends the entered travel preference information to the server, which then analyzes the travel preference information sent to the server as an API request.

[0637] 3. Generate a travel plan

[0638] The generative AI model on the server generates an optimal travel plan based on the user's travel preferences. The generated plan is a detailed itinerary that reflects the user's preferences.

[0639] Examples:

[0640] The schedule for each day is detailed, with a visit to Kiyomizu-dera Temple on the first day and Kinkaku-ji Temple on the second day.

[0641] 4. View and customize your plan

[0642] The server sends the generated travel plan to the user's device, where the user can view the plan on their smartphone. Users can also customize the plan, for example, by changing the destinations or schedule.

[0643] 5. Real-time information provision

[0644] While traveling, real-time tourist information and information on nearby physical stores are provided based on the user's location information, allowing users to receive the most appropriate tourist information, restaurant and shop information, etc. based on their current location.

[0645] This system allows users to easily create, check, and customize travel plans that suit their preferences, and also provides real-time information during their trip, resulting in a more satisfying travel experience for users.

[0646] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0647] Specific processing steps of the program

[0648] Step 1:

[0649] The user inputs desired travel information into their smartphone. Input items include the destination, travel dates, budget, and activities they want to visit. For example, information such as "Kyoto," "2023-11-01 ~ 2023-11-05," "budget 100,000 yen," and "Kiyomizu-dera Temple, Kinkaku-ji Temple, Gion, Arashiyama" is input. The input information is preprocessed for the next process.

[0650] Input: Destination, travel dates, budget, activities you want to visit

[0651] Output: The desired information formatted from the input information

[0652] Step 2:

[0653] The device sends the desired information obtained in step 1 to the server as an API request. The request is sent using an HTTP POST request, and the request data is serialized in JSON format. The server receives this request.

[0654] Input: Travel preference information (JSON format)

[0655] Output: The data sent as a request to the server.

[0656] Step 3:

[0657] The server receives travel preferences and inputs them into the generative AI model. The generative AI model generates an optimal travel plan based on the preferences, referencing past travel data and the user's history data. The AI ​​model considers different parameters to create a detailed itinerary. For example, a specific schedule is generated such as "Day 1: Visit Kiyomizu-dera Temple in the morning, stroll through Gion in the afternoon."

[0658] Input: Travel preference information

[0659] Output: Generated itinerary

[0660] Step 4:

[0661] The server serializes the generated itinerary in JSON format and sends it to the device, which receives the data, parses it, and displays it in a format that the user can view.

[0662] Input: Generated travel plan (JSON format)

[0663] Output: The travel plan displayed on the user's device

[0664] Step 5:

[0665] The user checks the displayed itinerary and customizes it as necessary. For example, the user may make changes such as "I want to cancel Kinkaku-ji Temple on the second day and visit Arashiyama instead." This information is then sent back to the server from the device.

[0666] Input: Customization information

[0667] Output: Customization data sent from the device to the server

[0668] Step 6:

[0669] The server receives the resubmitted customization information and uses the generative AI model again to generate a new travel plan that reflects the user's latest requests.

[0670] Input: Customization information

[0671] Output: Regenerated itinerary

[0672] Step 7:

[0673] The server serializes the regenerated itinerary into JSON format and resends it to the device, which parses the data and displays it again to the user, thus finalizing the itinerary.

[0674] Input: Regenerated itinerary (JSON format)

[0675] Output: The final itinerary displayed on the user's device

[0676] Step 8:

[0677] During a trip, real-time tourist information and information on nearby brick-and-mortar stores are provided using the user's location information. The user's current location is periodically sent to the server using the GPS function of the user's device. Based on this location information, the server generates information on nearby tourist attractions, restaurants, and shops and provides it to the user.

[0678] Input: User's location

[0679] Output: Real-time tourist information and brick-and-mortar store information

[0680] The above are the processing steps of the specific program for carrying out the present invention.

[0681] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0682] This invention relates to a system that generates personalized travel plans by combining a user's desired travel information with an emotion engine that recognizes the user's emotions. To implement this system, the following procedures and requirements must be met:

[0683] First, to start planning a trip, the user inputs desired travel information into the terminal. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit (e.g., tourist attractions and restaurants). The terminal provides an interface for inputting this information.

[0684] Example: A user types into a terminal, "I want to plan a 5-day trip to Tokyo. My budget is under 100,000 yen, and I want to visit tourist attractions and good restaurants."

[0685] The emotion engine then analyzes the user's input and non-verbal data (e.g., voice tone, facial expressions), identifies the user's emotional state (e.g., excited, relaxed, tired), and sends that information to the server.

[0686] For example, if a user inputs the emotion "excitement" into the device, the emotion engine will analyze the emotion and determine that the user is in an "excited" state.

[0687] The device generates an API request to send travel preference information and emotion data analyzed by the emotion engine to the server. The server receives and analyzes this request. The server is installed with an artificial intelligence model that generates a travel plan based on the user's preference information and emotion information.

[0688] The server preprocesses the desired information and emotional information and then inputs it into an artificial intelligence model. This artificial intelligence model is capable of generating an optimal travel plan based on the input parameters. The model considers past travel data, user history information, and available resources to propose an optimal schedule and places to visit at the destination. Furthermore, by reflecting emotional information, the model proposes a plan that is tailored to the user's emotional state.

[0689] Example: The server creates a "5-day Tokyo travel plan" and suggests exciting tourist spots (Asakusa and Skytree) on the first day to accommodate an excited user, and calm places (Ueno Zoo and Ameyoko Market) on the second day to accommodate a relaxed user.

[0690] The server then sends the generated itinerary to the device, which then displays it to the user. The user can review the displayed itinerary and make additional customizations as needed. For example, if the user wants to visit Odaiba instead of Ueno Zoo, they can input that change into the device.

[0691] The device compiles this customization information and sends it back to the server, which again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is then sent back to the device and displayed to the user as the final plan.

[0692] Example: If a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[0693] In this way, the present invention realizes a system that improves the quality of travel plans by quickly providing flexible travel plans based on the user's wishes and making personalized suggestions that are tailored to the user's emotional state.

[0694] The processing flow will be explained below.

[0695] Step 1:

[0696] The user inputs travel preferences into the terminal, such as destination, travel dates, budget, and activities of interest.

[0697] Step 2:

[0698] The emotion engine analyzes user input and non-verbal data (e.g., vocal tone, facial expression) to identify emotional states.

[0699] Step 3:

[0700] The device compiles travel preference information and analyzed emotion data and converts it into a dataset.

[0701] Step 4:

[0702] The device generates an API request to send the compiled data set to the server, including travel preference information and emotion data.

[0703] Step 5:

[0704] The server receives the API request, analyzes the request, and extracts travel preference information and emotion data.

[0705] Step 6:

[0706] The server pre-processes the travel preference and emotion data, for example by checking the data integrity and converting it into a format suitable for the artificial intelligence model.

[0707] Step 7:

[0708] The server inputs the preprocessed data into an artificial intelligence model, which then generates an optimal travel plan based on the input data.

[0709] Step 8:

[0710] The server compiles the generated itinerary into a dataset, for example creating a detailed schedule for each day.

[0711] Step 9:

[0712] An API response is generated to send the travel plan generated by the server to the terminal.

[0713] Step 10:

[0714] The device receives the API response from the server, analyzes the received data, and displays it to the user.

[0715] Step 11:

[0716] The user reviews the displayed itinerary, customizes it as needed, and inputs any corrections or additions they wish to make into the device.

[0717] Step 12:

[0718] The device collects the user's customization information and creates a new data set.

[0719] Step 13:

[0720] The device resends the customized data set to the server, and generates another API request and sends it to the server.

[0721] Step 14:

[0722] The server receives the API request again and parses the new preferences, extracting customized travel preferences and sentiment data.

[0723] Step 15:

[0724] The server pre-processes the customized travel preference and emotion data, performs data integrity checks, and converts it into a format suitable for artificial intelligence models.

[0725] Step 16:

[0726] The server then feeds the preprocessed data back into the artificial intelligence model, which then generates a customized itinerary based on the new data.

[0727] Step 17:

[0728] The server compiles the regenerated itinerary into a dataset, e.g., creating a detailed schedule that reflects the changes.

[0729] Step 18:

[0730] The server generates the final API response to send the regenerated itinerary to the device.

[0731] Step 19:

[0732] The device receives the regenerated API response from the server, parses the received data, and displays the final plan to the user.

[0733] Through this series of steps, the system allows users to obtain a travel plan that meets their needs and can also provide personalized suggestions based on their emotional state.

[0734] Example 2

[0735] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0736] In modern travel planning, there is a need to quickly and accurately generate personalized itineraries that reflect users' diverse desires and emotions. However, conventional systems have difficulty incorporating users' specific desires and real-time emotions, which makes it difficult to increase user satisfaction.

[0737] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0738] In this invention, the server includes means for inputting travel preference information from a user, means for collecting data for identifying the user's emotions, means for transmitting the travel preference information and the collected emotion data to the server, means for the server to generate an itinerary based on the travel preference information and emotion data using an artificial intelligence model, means for transmitting the generated itinerary to a terminal, means for the terminal to display the itinerary to the user, means for the user to customize the displayed itinerary, means for retransmitting the customized information to the server and the server to generate a new itinerary, and means for finally displaying the regenerated itinerary to the user. This makes it possible to quickly and accurately generate a personalized itinerary that reflects the user's specific preferences and real-time emotions.

[0739] "User's desired travel information" is detailed information about the user's desired trip, such as travel destination, travel itinerary, budget, and activities at the destination.

[0740] "Data for identifying the user's emotions" refers to data that includes non-verbal information about the user, such as tone of voice and facial expressions.

[0741] The "server" is a central processing system that receives the user's travel preferences and emotion data and generates a travel plan using a generative AI model.

[0742] A "generative AI model" is an artificial intelligence algorithm that references past travel data and user history information to create optimal travel plans based on the user's preferences and emotional data.

[0743] A "terminal" is a device that allows a user to input desired travel information and display a travel plan sent from a server.

[0744] An "API request" is a request for data transmission made from a terminal to a server, and includes travel preference information and emotion data.

[0745] A "travel plan" is a plan that includes specific travel itineraries, destinations, recommended activities, etc., generated based on the user's desired information and emotional state.

[0746] "Customization" refers to the user making changes or additions to the displayed travel plan.

[0747] "Historical Trip Data" means details about previously recorded trips that are used to create similar trip itineraries.

[0748] "User history information" is history data for each user, such as trips the user has taken in the past and travel preferences that the user has entered up to now.

[0749] The present invention relates to a system that generates a more personalized travel plan by inputting user travel preferences and recognizing the user's emotions. The system includes a terminal, a server, and an emotion engine.

[0750] First, to start planning a trip, the user inputs their desired travel information into the device. Using the device interface, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit. The device collects this information and prepares it for the next process.

[0751] For example, consider the case where a user inputs, "I want to plan a 5-day trip to Tokyo, with a budget of 100,000 yen or less, and want to visit tourist attractions and good restaurants."

[0752] The device then analyzes the user's emotions using an emotion engine, which collects and analyzes the user's non-verbal data (voice tone and facial expressions) in real time to determine the user's emotional state, such as whether they are excited, relaxed, or tired.

[0753] For example, if the user utters the word "fun" in an excited tone, the emotion engine will interpret this as the user being "excited."

[0754] The device sends the user's travel preference information and analyzed emotion data together to the server as an API request, and the server receives the request and analyzes the data.

[0755] The server inputs the user's desired information and emotional data into an AI model to generate the optimal travel plan. This generative AI model then uses past travel data and user history information to create a travel plan that suits the user's preferences.

[0756] For example, the server might create a "5-day Tokyo travel plan" and suggest sightseeing in Asakusa and Skytree on the first day, in response to a user's excited state, and then suggest visiting Ueno Zoo and Ameyoko Market on the second day, in response to a user's relaxed state.

[0757] The server sends the generated travel plan to the terminal, which then displays the plan to the user, who can review the displayed plan and make further customizations as needed.

[0758] Now, if the user decides to visit Odaiba instead of Ueno Zoo, they enter that change into their device. The device compiles the customization information and sends it back to the server. The server again uses the generative AI model to regenerate a customized itinerary based on the new data. The regenerated itinerary is sent back to the device and displayed to the user as the final itinerary.

[0759] For example, if a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[0760] In this way, the present invention realizes a system that improves the quality of travel plans by quickly providing flexible travel plans based on the user's wishes and making personalized suggestions that are tailored to the user's emotional state.

[0761] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0762] (Processing flow)

[0763] Step 1: Enter user travel information

[0764] The user inputs their travel preferences. Using the device interface, the user inputs detailed information such as their destination, travel dates, budget, and activities they would like to visit.

[0765] Input: destination, travel dates, budget, activities you want to visit, etc.

[0766] Specific behavior: A user enters information using text boxes and drop-down menus on the device.

[0767] Output: Travel preference data is saved on the device

[0768] Step 2: Collect and analyze emotion data

[0769] The device analyzes the user's emotions using an emotion engine, which collects and analyzes non-verbal data such as voice tone and facial expressions.

[0770] Input: Non-verbal data such as tone of voice, facial expressions, etc.

[0771] Specific operation: Collects the user's voice and facial expressions in real time using the device's built-in camera and microphone.

[0772] Data processing: Emotion engine uses voice and image analysis algorithms to determine emotional state

[0773] Output: User emotion data

[0774] Step 3: Send the data

[0775] The device sends travel preference information and emotion data to the server as an API request.

[0776] Input: Travel preference data, emotion data

[0777] Specific operation: The device converts the data into JSON format and sends it to the server using the HTTP protocol.

[0778] Data manipulation: structuring and encoding data

[0779] Output: The API request received by the server

[0780] Step 4: Generate your itinerary

[0781] The server analyzes the received data and generates an optimal travel plan using an artificial intelligence model.

[0782] Input: Travel preference information, emotional data

[0783] How it works: The server analyzes the data and uses past travel data and user history information to feed the generative AI model.

[0784] Data computation: Generative AI models run algorithms to create optimal travel plans

[0785] Output: Generated itinerary data

[0786] Step 5: View your plan

[0787] The server transmits the generated travel plan to the terminal, which displays it to the user.

[0788] Input: Generated itinerary data

[0789] Specific operation: The server sends a travel plan in JSON format to the device, which parses the plan and displays it on the interface.

[0790] Data processing: building and encoding plans, parsing for UI display

[0791] Output: A displayed itinerary

[0792] Step 6: Customize and Regenerate

[0793] The user then performs additional customizations on the displayed travel plan, and the customization information is sent from the device back to the server, which then generates a new plan using the artificial intelligence model again.

[0794] Input: Customization information

[0795] What happens: The user enters plan changes using the device interface, and the device sends the information to the server.

[0796] Data Processing: Collecting and Sending Customization Information

[0797] Output: Customization information received by the server, regenerated itinerary

[0798] This process flow allows users to quickly obtain and further customize a personalized travel plan that is tailored to their desires and feelings.

[0799] (Application example 2)

[0800] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0801] Conventional shopping systems lack personalized product suggestions that take into account the user's emotional state and lack mechanisms to improve user satisfaction. As a result, it takes time to find the optimal product that corresponds to a specific emotional state, making it difficult to provide an efficient shopping experience.

[0802] The specification process by the specification processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server has a means for the user to input a desired product,

[0803] means for transmitting the desired product information to a server;

[0804] a means for the emotion engine to analyze the user's emotion;

[0805] means for transmitting the analyzed emotion information to a server;

[0806] a means for generating product suggestions based on the desired product information and emotion information by using an artificial intelligence model in a server;

[0807] means for transmitting the generated product proposal to a terminal;

[0808] means for the terminal to display the product proposal to the user;

[0809] means for a user to customize the displayed product suggestions;

[0810] means for retransmitting the customized information to a server, and the server generating product suggestions again;

[0811] The method further includes means for finally displaying the regenerated product suggestions to the user, thereby enabling personalized product suggestions according to the user's emotional state.

[0812] "Desired product information" refers to detailed information such as the type of product the user wishes to purchase, their budget, and their preferred style.

[0813] "Emotion engine" refers to software or hardware for analyzing a user's emotional state.

[0814] "Analyzed emotional information" refers to data about a user's emotional state that has been analyzed by the emotion engine.

[0815] "Artificial intelligence model" refers to a system that includes an algorithm for generating optimal product suggestions based on a user's desired product information and emotional information.

[0816] "Product suggestions" refers to specific product lists and suggestions provided to users based on desired product information and analyzed emotional information.

[0817] "Customization" refers to an operation in which a user adds conditions or makes changes based on the displayed product proposals.

[0818] "Regeneration" refers to the process of recreating product proposals using an artificial intelligence model based on customized information.

[0819] This invention relates to a shopping assistant system that analyzes user emotions and generates personalized product recommendations. The system runs on devices such as smartphones, smart glasses, or head-mounted displays, and recommends optimal products to users.

[0820] The main components of the system are:

[0821] 1. A means for users to input desired products: Users use their smartphones or other devices to provide desired product information through a form to input information about the products they want to purchase (e.g., type, budget, style) or through a voice assistant.

[0822] 2. Emotion Engine: This is a software component that detects and analyzes the user's voice tone and facial expressions. Specific software used is Google Cloud's Speech-to-Text API and Microsoft Azure Cognitive Services.

[0823] 3. Means for transmitting the sales information and analyzed sentiment information to the server: This information is transmitted in real time to the server for further processing. Data is sent and received using API requests over the network.

[0824] 4. Artificial intelligence model on the server: The server is equipped with artificial intelligence models such as TensorFlow and GPT-4, which generate product suggestions based on the user's desired product information and emotional information. Based on this information, the server selects the most suitable product, taking into account past purchase data and user history data.

[0825] 5. Generating and sending product suggestions to the terminal: The generated product suggestions are sent to the terminal and presented visually or audibly to the user.

[0826] 6. Customizing Product Proposals: The user can input further conditions or modifications based on the displayed product proposals. This feedback is sent back to the server, and an updated proposal is generated.

[0827] 7. Displaying the final product proposal: The updated product proposal is resent to the terminal and finally provided to the user.

[0828] For example, if a user enters the desired product information as "I want a candle with a relaxing scent, but my budget is under 2,000 yen. I'm also looking for calming sweets," and the emotion engine analyzes the user's relaxed state, the server will generate suggestions for candles and sweets with a relaxing effect based on that emotional state.The user can then exclude products they don't like from the suggested products or add more specific conditions, and a re-optimized product list will be provided.

[0829] Examples of prompts:

[0830] "I want a candle with a relaxing scent, but my budget is under 2000 yen. I'm also looking for some calming sweets."

[0831] In this way, the present invention provides a system that takes into account the user's emotional state and can quickly provide personalized product suggestions, helping to make the shopping experience more satisfying.

[0832] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0833] Step 1:

[0834] Users input desired product information using a smartphone or other device, providing the type of product they want to purchase, their budget, and preferred style via text form or voice input.

[0835] Input: Desired product information (e.g., "I'd like a candle with a relaxing scent, but my budget is under 2000 yen. I'm also looking for some relaxing sweets.")

[0836] Output: Desired product information processed on the user's device

[0837] Step 2:

[0838] The device activates an emotion engine that analyzes the user's voice tone and facial expressions in real time via the camera and microphone, and uses Google Cloud's Speech-to-Text API and Microsoft Azure Cognitive Services to analyze the user's emotional state.

[0839] Input: User's voice tone, facial expression

[0840] Output: Analyzed emotional information (e.g., relaxed state)

[0841] Step 3:

[0842] The device sends the desired product information and analyzed emotion information to the server via the network as an API request.

[0843] Input: Desired product information, analyzed emotion information

[0844] Output: API request sent to the server

[0845] Step 4:

[0846] The server receives the desired product information and sentiment information, and preprocesses this information before inputting it into an artificial intelligence model (TensorFlow or GPT-4). Preprocessing includes data conversion and transformation into a unified format.

[0847] Input: Desired product information, analyzed emotion information

[0848] Output: Preprocessed data

[0849] Step 5:

[0850] The server inputs the preprocessed data into an AI model to generate optimal product suggestions. The AI ​​model also takes into account past purchase data and user history data to make more accurate suggestions.

[0851] Input: Preprocessed data, historical purchase data, user history data

[0852] Output: Product suggestions (e.g., relaxing candles, sweets)

[0853] Step 6:

[0854] The server transmits the generated product proposals to the terminal via the network.

[0855] Input: Product proposal

[0856] Output: Send request to user terminal

[0857] Step 7:

[0858] The terminal presents the received product proposal to the user visually or audibly, and the user inputs further conditions or changes based on the displayed product proposal.

[0859] Input: Product proposal

[0860] Output: User feedback (e.g., "Show me more products of a specific brand")

[0861] Step 8:

[0862] The user's feedback is resubmitted from the terminal to the server, which again uses the artificial intelligence model to generate updated product suggestions.

[0863] Input: User feedback

[0864] Output: Regenerated product suggestions

[0865] Step 9:

[0866] The server transmits the regenerated product proposals to the terminal via the network, and finally provides them to the user.

[0867] Input: Regenerated product suggestions

[0868] Output: Display of final product suggestions

[0869] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0870] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0871] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0872] [Third embodiment]

[0873] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0874] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0875] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0876] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0877] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0878] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0879] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0880] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0881] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0882] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0883] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0884] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0885] This invention relates to a system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal displays the travel plan to the user. To implement this system, the following procedures and requirements must be met:

[0886] First, to start planning a trip, the user inputs desired travel information into the terminal. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit (e.g., tourist attractions and restaurants). The terminal provides an interface for inputting this information.

[0887] Example: A user types into a terminal, "I want to plan a 5-day trip to Tokyo. My budget is under 100,000 yen, and I want to visit tourist attractions and good restaurants."

[0888] The device then generates an API request to send the entered travel preferences to a server, which receives and analyzes the request and installs an artificial intelligence model to generate a travel plan based on the user's preferences.

[0889] The server preprocesses the desired information and then inputs it into an artificial intelligence model that is capable of generating an optimal travel plan based on the input parameters. The model considers past travel data, user history, and available resources to suggest optimal schedules and places to visit at the destination.

[0890] Example: The server generates a detailed "5-day Tokyo travel plan" that includes visiting Asakusa and Skytree on the first day, Ueno Zoo and Ameyoko Market on the second day, etc.

[0891] The server then sends the generated itinerary to the device, which then displays it to the user. The user can review the displayed itinerary and make additional customizations as needed. For example, if the user wants to visit Odaiba instead of Ueno Zoo, they can input that change into the device.

[0892] The device compiles this customization information and sends it back to the server, which again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is then sent back to the device and displayed to the user as the final plan.

[0893] Example: If a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[0894] In this way, the present invention realizes a system that quickly provides flexible travel plans based on the user's wishes and can accommodate multiple customizations.

[0895] The processing flow will be explained below.

[0896] Step 1:

[0897] The user inputs travel preferences into the terminal, such as destination, travel dates, budget, and activities of interest.

[0898] Step 2:

[0899] The device collects the travel preference information entered and converts the data into a single data set.

[0900] Step 3:

[0901] The device sends the compiled data set to the server, and generates an API request and sends it to the server.

[0902] Step 4:

[0903] The server receives the API request, analyzes the request, and extracts travel preference information.

[0904] Step 5:

[0905] The server pre-processes the travel preference information, for example checking the data for consistency and converting it into a format suitable for artificial intelligence models.

[0906] Step 6:

[0907] The server inputs the preprocessed data into an artificial intelligence model, which then generates an optimal travel plan based on the input data.

[0908] Step 7:

[0909] The server compiles the generated itinerary into a dataset, for example creating a detailed schedule for each day.

[0910] Step 8:

[0911] The server sends the generated travel plan to the device. The travel plan is sent as an API response.

[0912] Step 9:

[0913] The device receives the travel plan from the server, analyzes the data, and displays it to the user.

[0914] Step 10:

[0915] The user can customize the displayed travel plan by entering any corrections or additions they wish to make into the device.

[0916] Step 11:

[0917] The device collects the user customization information and creates a new dataset.

[0918] Step 12:

[0919] The device resends the customized data set to the server, and generates another API request and sends it to the server.

[0920] Step 13:

[0921] The server receives the API request again and analyzes the new request information.

[0922] Step 14:

[0923] The server preprocesses the new request information, performs data integrity checks, and converts it into a format suitable for artificial intelligence models.

[0924] Step 15:

[0925] The server then feeds the preprocessed data back into the artificial intelligence model, which then generates a customized itinerary based on the new data.

[0926] Step 16:

[0927] The server compiles the regenerated itinerary into a dataset, e.g., creating a detailed schedule that reflects the changes.

[0928] Step 17:

[0929] The server sends the regenerated travel plan to the device and the final plan as an API response.

[0930] Step 18:

[0931] The terminal receives the regenerated travel plan from the server, analyzes the data, and displays the final plan to the user.

[0932] Through this series of steps, the user can obtain a travel plan that meets their needs, and a system is realized that can flexibly accommodate additional customization.

[0933] Example 1

[0934] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0935] Conventional travel plan creation systems have had the challenge of responding quickly and flexibly to user requests. Creating the optimal plan based on the user's desired travel information requires advanced data analysis and individual customization, which conventional systems find difficult. It is also difficult to respond quickly to user requests for changes, and multiple customization processes must proceed smoothly.

[0936] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0937] In this invention, the server includes means for inputting travel preference information from a user, means for transmitting the travel preference information to the server, means for generating a travel plan based on the travel preference information using an artificial intelligence model, means for transmitting the generated travel plan to a terminal, means for the terminal to display the travel plan to the user, means for the user to customize the displayed travel plan, means for retransmitting the customized information to the server and causing the server to regenerate the travel plan, and means for finally displaying the regenerated travel plan to the user. This makes it possible to provide flexible and prompt travel plans based on the user's preferences.

[0938] "User" refers to an individual or organization who inputs desired information to create a travel plan and reviews and customizes the generated plan.

[0939] "Desired information" refers to detailed information entered by the user, such as travel destination, travel itinerary, budget, and activities desired to visit.

[0940] "Terminal" refers to a device used by a user to input desired information, and includes smartphones, tablets, PCs, etc.

[0941] "Server" refers to the central computing system that receives, analyzes, processes, and generates travel plans based on user-submitted preferences.

[0942] "Artificial intelligence model" refers to the algorithms and computational models that generate optimal travel plans based on input data, and are built using deep learning libraries, etc.

[0943] An "API request" is a standardized form of digital communication that allows a device to send desired information to a server.

[0944] A "travel plan" refers to a plan that includes a specific travel schedule and suggestions of places to visit, which is generated by the server based on the user's desired information.

[0945] "Customization" refers to the user making additional changes or adjustments to the generated itinerary.

[0946] "Network" refers to a connection means such as the Internet or a local area network that allows servers and terminals to communicate with each other.

[0947] "Historical Travel Data" refers to data previously collected about other users' travel information and travel plans.

[0948] "History data" refers to data that records information about past trips and behavioral patterns of a particular user.

[0949] This invention is a system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal displays the travel plan to the user. To implement the system, several pieces of software and hardware are required.

[0950] First, to start planning a trip, the user inputs desired travel information into the device. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they would like to visit. The device provides an interface for inputting this information. For example, an input form is used on the screen of a smartphone, tablet, or PC. For example, the user might input, "I would like to plan a five-day trip to Tokyo. My budget is within 100,000 yen, and I would like to visit tourist attractions and good restaurants."

[0951] The device then generates an API request to send the entered travel preferences to a server. Software on the device (e.g., a mobile app or web browser) organizes these preferences and sends them over the network to the server. The server receives and analyzes the request. The server has an artificial intelligence model installed that generates a travel plan based on the user's preferences. This is done using deep learning libraries (e.g., TensorFlow and PyTorch).

[0952] The server preprocesses the desired information and then inputs it into an AI model. Preprocessing includes reformatting the data and adding necessary information. The AI ​​model generates an optimal travel plan based on the input parameters. The model considers past travel data, the user's history, and available resources to suggest the optimal schedule and places to visit at the destination. For example, the server might generate a detailed "5-day Tokyo travel plan" that includes visits to Asakusa and Skytree on the first day, Ueno Zoo and Ameyoko Market on the second day, and so on.

[0953] The server then sends the generated travel plan to the device, which then displays it to the user. The user can review the displayed plan and make additional customizations as needed. For example, if the user wants to go to Odaiba instead of Ueno Zoo, they can enter that change into the device. The user interface is designed to allow the user to easily make changes.

[0954] The device compiles this customization information and sends it back to the server. The server again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is sent back to the device and displayed to the user as the final plan. For example, if the user inputs, "I want to go to Odaiba instead of Ueno Zoo on day 3," the server generates a new plan that includes Odaiba, and the device displays that final plan.

[0955] As described above, the present invention is a system that quickly provides flexible travel plans based on the user's wishes and can accommodate multiple customizations. This system allows users to easily create satisfactory travel plans.

[0956] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0957] Step 1:

[0958] The user inputs desired travel information into the terminal.

[0959] Input: Details such as your travel destination, travel dates, budget, and activities you want to visit.

[0960] Specific behavior: Using the user interface, enter the required information into the specified form. For example, enter "I want to plan a 5-day trip to Tokyo, with a budget of 100,000 yen or less, and would like to visit tourist attractions and good restaurants."

[0961] Step 2:

[0962] The device generates an API request based on the travel preference information entered.

[0963] Input: Travel preference information entered by the user.

[0964] Data processing: Converting input information into an appropriate format, such as JSON, and packaging it as an API request.

[0965] Output: The API request to send to the server.

[0966] What it does: The device application organizes the desired information and generates a request, such as a JSON object containing data about the travel destination, itinerary, budget, and activities.

[0967] Step 3:

[0968] The device sends the generated API request to the server.

[0969] Input: API request.

[0970] What happens: The device uses a network connection (Wi-Fi, cellular, etc.) to send a request to the server, often via an HTTP POST request.

[0971] Step 4:

[0972] The server receives the API request and analyzes it.

[0973] Input: The API request sent from the device.

[0974] Data processing: Analyze the request content, extract the user's desired information, and save it as structured data.

[0975] Output: Parsed user preference information.

[0976] How it works: A server-side program receives the request, analyzes it, and extracts the necessary data, such as destination, itinerary, and budget, and stores them in the appropriate database fields.

[0977] Step 5:

[0978] The server preprocesses the user's desired information and inputs it into the artificial intelligence model.

[0979] Input: Parsed user preference information.

[0980] Data processing: Normalize data, fill in missing values, and convert to the appropriate format.

[0981] Output: Preprocessed data.

[0982] What happens: A data preprocessing script is executed to convert the user's desired information into a format that is easy for the AI ​​model to use, such as tokenizing text data and standardizing numeric data.

[0983] Step 6:

[0984] The server generates the itinerary using an artificial intelligence model.

[0985] Input: Preprocessed user preference information.

[0986] Data calculations: An artificial intelligence model calculates the optimal travel plan based on input data and generates suggested itineraries and places to visit.

[0987] Output: The generated itinerary.

[0988] What it does: An artificial intelligence model (e.g., a model implemented in TensorFlow or PyTorch) is run to generate a travel plan, including a daily schedule and details of the places to visit.

[0989] Step 7:

[0990] The server transmits the generated travel plan to the terminal.

[0991] Input: The generated itinerary.

[0992] Specific operation: The server sends the travel plan to the device as an API response, which is often an HTTP response.

[0993] Step 8:

[0994] The terminal displays the travel plan to the user.

[0995] Input: The itinerary sent from the server.

[0996] Output: The itinerary displayed to the user.

[0997] Specific operation: The application on the device receives the response and displays the itinerary in the user interface, for example, showing the schedule by day and details of the places to visit.

[0998] Step 9:

[0999] The user customizes the travel plan.

[1000] Input: The displayed itinerary.

[1001] Specific behavior: The user uses the interface to input changes to the travel plan and enters corrections or additional information. For example, the user enters, "I would like to go to Odaiba instead of Ueno Zoo on the third day."

[1002] Step 10:

[1003] The terminal collects the customization information and transmits it to the server again.

[1004] Input: Customization information entered by the user.

[1005] Data processing: Convert the customization information into an appropriate format, such as JSON, and package it as a resubmission request.

[1006] Output: The API request to resend to the server.

[1007] Specific operation: The device organizes the desired changes, generates a new request, and sends it to the server. For example, it generates a JSON object containing data about the updated schedule and places to visit.

[1008] Step 11:

[1009] The server receives the request again, analyzes it, and inputs it into the artificial intelligence model.

[1010] Input: The resubmitted API request.

[1011] Data processing: Analyze the request content to extract new customization information and preprocess it into a form suitable for model input.

[1012] Output: The new preprocessed customization information.

[1013] Specific operation: The server receives the retransmission request, analyzes the content to extract the change information, and executes the data preprocessing script to format it for model input.

[1014] Step 12:

[1015] The server again uses the artificial intelligence model to generate a new itinerary.

[1016] Input: The preprocessed new customization information.

[1017] Data computation: Artificial intelligence models recalculate optimal travel plans based on new information and generate revised itineraries and destinations.

[1018] Output: The regenerated itinerary.

[1019] Specific operation: The AI ​​model is run again to generate a new itinerary, for example, one that includes a new stop at Odaiba.

[1020] Step 13:

[1021] The server sends the regenerated itinerary to the terminal and finally displays it to the user.

[1022] Input: The regenerated itinerary.

[1023] Output: The final itinerary that is displayed to the user.

[1024] Specific operation: The server sends the new travel plan to the device as an API response, the device receives it, and displays the final plan on the user interface.

[1025] (Application example 1)

[1026] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1027] When planning a trip, it is important to provide users with their desired travel plans quickly and flexibly. There is also a growing need to obtain real-time tourist information and information on nearby brick-and-mortar stores while traveling, but conventional systems cannot adequately meet these needs. In particular, when customizing travel plans and providing real-time information, it is necessary to quickly provide optimal suggestions while taking into account the user's current location information. Therefore, a system is needed that can provide flexible travel plans based on the user's preferences, as well as efficiently provide real-time tourist information and information on nearby brick-and-mortar stores while traveling.

[1028] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1029] In this invention, the server includes means for inputting travel preferences from a user, means for transmitting the travel preference information to the server, means for the server to generate a travel plan based on the travel preference information using an artificial intelligence model, means for transmitting the generated travel plan to a terminal, means for the terminal to display the travel plan to the user, means for the user to customize the displayed travel plan, means for retransmitting the customized information to the server and causing the server to re-generate the travel plan, means for finally displaying the re-generated travel plan to the user, means for providing real-time tourist information and information on nearby brick-and-mortar stores based on the user's location information, and means for displaying the real-time information on the user's smartphone. This enables a system that utilizes the user's location information to provide real-time tourist information and information on brick-and-mortar stores and quickly respond to customization of travel plans.

[1030] "User" means an individual or entity that uses the system to plan a trip.

[1031] "Travel preference information" is detailed information about the trip the user wants to plan, including the destination, date, budget, activities they want to visit, and so on.

[1032] A "server" is a computing device that receives and analyzes travel preference information submitted by users and generates and regenerates travel plans using artificial intelligence models.

[1033] An "artificial intelligence model" is a computational algorithm that generates optimal travel plans based on past travel data and user history data.

[1034] A "travel plan" is a detailed itinerary and suggested destinations generated based on the user's travel preferences.

[1035] A "terminal" is an electronic device that a user uses to view and customize their travel plan, including a smartphone.

[1036] "Customization" refers to the act of a user making changes to a displayed itinerary, including changing specific attractions or schedules.

[1037] "Real-time information" refers to tourist information and brick-and-mortar store information provided based on the user's current location, and is characterized by its immediacy.

[1038] A "physical store" is a physical store that a user can visit while traveling, including restaurants, shops, etc.

[1039] A "smartphone" is a mobile phone that can connect to the Internet and use applications, and in many cases is equipped with GPS functionality.

[1040] This invention relates to a travel support system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal presents and customizes the plan to the user in real time. Specific implementation methods of this system are described below.

[1041] Key components of the system

[1042] 1. User device (smartphone)

[1043] The user terminal is the device that the user uses to input desired travel information and review and customize the generated travel plan. A smartphone is usually used, but tablets and PCs can also be used.

[1044] 2. Server

[1045] The server receives travel information sent from the user's device and generates and regenerates travel plans based on that information. A generative AI model is used to generate travel plans.

[1046] 3. Generative AI Models

[1047] The generative AI model runs on a server and is an algorithm that generates optimal travel plans based on the travel preferences entered, while referencing past travel data and user history.

[1048] 4. Network

[1049] The Internet is used as a network for communication between user terminals and servers.

[1050] Specific methods for carrying out the invention

[1051] 1. User Input

[1052] Users input their travel preferences through an application on their smartphone, including destination, travel dates, budget, and activities they would like to visit.

[1053] Example prompt sentence:

[1054] Destination: Kyoto

[1055] Start date (YYYY-MM-DD):2023-11-01

[1056] End date (YYYY-MM-DD):2023-11-05

[1057] Budget: 100,000

[1058] Activities you would like to visit (separated by commas): Kiyomizu-dera Temple, Kinkaku-ji Temple, Gion, Arashiyama

[1059] 2. Data transmission and analysis

[1060] The user device sends the entered travel preference information to the server, which then analyzes the travel preference information sent to the server as an API request.

[1061] 3. Generate a travel plan

[1062] The generative AI model on the server generates an optimal travel plan based on the user's travel preferences. The generated plan is a detailed itinerary that reflects the user's preferences.

[1063] Examples:

[1064] The schedule for each day is detailed, with a visit to Kiyomizu-dera Temple on the first day and Kinkaku-ji Temple on the second day.

[1065] 4. View and customize your plan

[1066] The server sends the generated travel plan to the user's device, where the user can view the plan on their smartphone. Users can also customize the plan, for example, by changing the destinations or schedule.

[1067] 5. Real-time information provision

[1068] While traveling, real-time tourist information and information on nearby physical stores are provided based on the user's location information, allowing users to receive the most appropriate tourist information, restaurant and shop information, etc. based on their current location.

[1069] This system allows users to easily create, check, and customize travel plans that suit their preferences, and also provides real-time information during their trip, resulting in a more satisfying travel experience for users.

[1070] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1071] Specific processing steps of the program

[1072] Step 1:

[1073] The user inputs desired travel information into their smartphone. Input items include the destination, travel dates, budget, and activities they want to visit. For example, information such as "Kyoto," "2023-11-01 ~ 2023-11-05," "budget 100,000 yen," and "Kiyomizu-dera Temple, Kinkaku-ji Temple, Gion, Arashiyama" is input. The input information is preprocessed for the next process.

[1074] Input: Destination, travel dates, budget, activities you want to visit

[1075] Output: The desired information formatted from the input information

[1076] Step 2:

[1077] The device sends the desired information obtained in step 1 to the server as an API request. The request is sent using an HTTP POST request, and the request data is serialized in JSON format. The server receives this request.

[1078] Input: Travel preference information (JSON format)

[1079] Output: The data sent as a request to the server.

[1080] Step 3:

[1081] The server receives travel preferences and inputs them into the generative AI model. The generative AI model generates an optimal travel plan based on the preferences, referencing past travel data and the user's history data. The AI ​​model considers different parameters to create a detailed itinerary. For example, a specific schedule is generated such as "Day 1: Visit Kiyomizu-dera Temple in the morning, stroll through Gion in the afternoon."

[1082] Input: Travel preference information

[1083] Output: Generated itinerary

[1084] Step 4:

[1085] The server serializes the generated itinerary in JSON format and sends it to the device, which receives the data, parses it, and displays it in a format that the user can view.

[1086] Input: Generated travel plan (JSON format)

[1087] Output: The travel plan displayed on the user's device

[1088] Step 5:

[1089] The user checks the displayed itinerary and customizes it as necessary. For example, the user may make changes such as "I want to cancel Kinkaku-ji Temple on the second day and visit Arashiyama instead." This information is then sent back to the server from the device.

[1090] Input: Customization information

[1091] Output: Customization data sent from the device to the server

[1092] Step 6:

[1093] The server receives the resubmitted customization information and uses the generative AI model again to generate a new travel plan that reflects the user's latest requests.

[1094] Input: Customization information

[1095] Output: Regenerated itinerary

[1096] Step 7:

[1097] The server serializes the regenerated itinerary into JSON format and resends it to the device, which parses the data and displays it again to the user, thus finalizing the itinerary.

[1098] Input: Regenerated itinerary (JSON format)

[1099] Output: The final itinerary displayed on the user's device

[1100] Step 8:

[1101] During a trip, real-time tourist information and information on nearby brick-and-mortar stores are provided using the user's location information. The user's current location is periodically sent to the server using the GPS function of the user's device. Based on this location information, the server generates information on nearby tourist attractions, restaurants, and shops and provides it to the user.

[1102] Input: User's location

[1103] Output: Real-time tourist information and brick-and-mortar store information

[1104] The above are the processing steps of the specific program for carrying out the present invention.

[1105] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1106] This invention relates to a system that generates personalized travel plans by combining a user's desired travel information with an emotion engine that recognizes the user's emotions. To implement this system, the following procedures and requirements must be met:

[1107] First, to start planning a trip, the user inputs desired travel information into the terminal. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit (e.g., tourist attractions and restaurants). The terminal provides an interface for inputting this information.

[1108] Example: A user types into a terminal, "I want to plan a 5-day trip to Tokyo. My budget is under 100,000 yen, and I want to visit tourist attractions and good restaurants."

[1109] The emotion engine then analyzes the user's input and non-verbal data (e.g., voice tone, facial expressions), identifies the user's emotional state (e.g., excited, relaxed, tired), and sends that information to the server.

[1110] For example, if a user inputs the emotion "excitement" into the device, the emotion engine will analyze the emotion and determine that the user is in an "excited" state.

[1111] The device generates an API request to send travel preference information and emotion data analyzed by the emotion engine to the server. The server receives and analyzes this request. The server is installed with an artificial intelligence model that generates a travel plan based on the user's preference information and emotion information.

[1112] The server preprocesses the desired information and emotional information and then inputs it into an artificial intelligence model. This artificial intelligence model is capable of generating an optimal travel plan based on the input parameters. The model considers past travel data, user history information, and available resources to propose an optimal schedule and places to visit at the destination. Furthermore, by reflecting emotional information, the model proposes a plan that is tailored to the user's emotional state.

[1113] Example: The server creates a "5-day Tokyo travel plan" and suggests exciting tourist spots (Asakusa and Skytree) on the first day to accommodate an excited user, and calm places (Ueno Zoo and Ameyoko Market) on the second day to accommodate a relaxed user.

[1114] The server then sends the generated itinerary to the device, which then displays it to the user. The user can review the displayed itinerary and make additional customizations as needed. For example, if the user wants to visit Odaiba instead of Ueno Zoo, they can input that change into the device.

[1115] The device compiles this customization information and sends it back to the server, which again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is then sent back to the device and displayed to the user as the final plan.

[1116] Example: If a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[1117] In this way, the present invention realizes a system that improves the quality of travel plans by quickly providing flexible travel plans based on the user's wishes and making personalized suggestions that are tailored to the user's emotional state.

[1118] The processing flow will be explained below.

[1119] Step 1:

[1120] The user inputs travel preferences into the terminal, such as destination, travel dates, budget, and activities of interest.

[1121] Step 2:

[1122] The emotion engine analyzes user input and non-verbal data (e.g., vocal tone, facial expression) to identify emotional states.

[1123] Step 3:

[1124] The device compiles travel preference information and analyzed emotion data and converts it into a dataset.

[1125] Step 4:

[1126] The device generates an API request to send the compiled data set to the server, including travel preference information and emotion data.

[1127] Step 5:

[1128] The server receives the API request, analyzes the request, and extracts travel preference information and emotion data.

[1129] Step 6:

[1130] The server pre-processes the travel preference and emotion data, for example by checking the data integrity and converting it into a format suitable for the artificial intelligence model.

[1131] Step 7:

[1132] The server inputs the preprocessed data into an artificial intelligence model, which then generates an optimal travel plan based on the input data.

[1133] Step 8:

[1134] The server compiles the generated itinerary into a dataset, for example creating a detailed schedule for each day.

[1135] Step 9:

[1136] An API response is generated to send the travel plan generated by the server to the terminal.

[1137] Step 10:

[1138] The device receives the API response from the server, analyzes the received data, and displays it to the user.

[1139] Step 11:

[1140] The user reviews the displayed itinerary, customizes it as needed, and inputs any corrections or additions they wish to make into the device.

[1141] Step 12:

[1142] The device collects the user's customization information and creates a new data set.

[1143] Step 13:

[1144] The device resends the customized data set to the server, and generates another API request and sends it to the server.

[1145] Step 14:

[1146] The server receives the API request again and parses the new preferences, extracting customized travel preferences and sentiment data.

[1147] Step 15:

[1148] The server pre-processes the customized travel preference and emotion data, performs data integrity checks, and converts it into a format suitable for artificial intelligence models.

[1149] Step 16:

[1150] The server then feeds the preprocessed data back into the artificial intelligence model, which then generates a customized itinerary based on the new data.

[1151] Step 17:

[1152] The server compiles the regenerated itinerary into a dataset, e.g., creating a detailed schedule that reflects the changes.

[1153] Step 18:

[1154] The server generates the final API response to send the regenerated itinerary to the device.

[1155] Step 19:

[1156] The device receives the regenerated API response from the server, parses the received data, and displays the final plan to the user.

[1157] Through this series of steps, the system allows users to obtain a travel plan that meets their needs and can also provide personalized suggestions based on their emotional state.

[1158] Example 2

[1159] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1160] In modern travel planning, there is a need to quickly and accurately generate personalized itineraries that reflect users' diverse desires and emotions. However, conventional systems have difficulty incorporating users' specific desires and real-time emotions, which makes it difficult to increase user satisfaction.

[1161] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1162] In this invention, the server includes means for inputting travel preference information from a user, means for collecting data for identifying the user's emotions, means for transmitting the travel preference information and the collected emotion data to the server, means for the server to generate an itinerary based on the travel preference information and emotion data using an artificial intelligence model, means for transmitting the generated itinerary to a terminal, means for the terminal to display the itinerary to the user, means for the user to customize the displayed itinerary, means for retransmitting the customized information to the server and the server to generate a new itinerary, and means for finally displaying the regenerated itinerary to the user. This makes it possible to quickly and accurately generate a personalized itinerary that reflects the user's specific preferences and real-time emotions.

[1163] "User's desired travel information" is detailed information about the user's desired trip, such as travel destination, travel itinerary, budget, and activities at the destination.

[1164] "Data for identifying the user's emotions" refers to data that includes non-verbal information about the user, such as tone of voice and facial expressions.

[1165] The "server" is a central processing system that receives the user's travel preferences and emotion data and generates a travel plan using a generative AI model.

[1166] A "generative AI model" is an artificial intelligence algorithm that references past travel data and user history information to create optimal travel plans based on the user's preferences and emotional data.

[1167] A "terminal" is a device that allows a user to input desired travel information and display a travel plan sent from a server.

[1168] An "API request" is a request for data transmission made from a terminal to a server, and includes travel preference information and emotion data.

[1169] A "travel plan" is a plan that includes specific travel itineraries, destinations, recommended activities, etc., generated based on the user's desired information and emotional state.

[1170] "Customization" refers to the user making changes or additions to the displayed travel plan.

[1171] "Historical Trip Data" means details about previously recorded trips that are used to create similar trip itineraries.

[1172] "User history information" is history data for each user, such as trips the user has taken in the past and travel preferences that the user has entered up to now.

[1173] The present invention relates to a system that generates a more personalized travel plan by inputting user travel preferences and recognizing the user's emotions. The system includes a terminal, a server, and an emotion engine.

[1174] First, to start planning a trip, the user inputs their desired travel information into the device. Using the device interface, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit. The device collects this information and prepares it for the next process.

[1175] For example, consider the case where a user inputs, "I want to plan a 5-day trip to Tokyo, with a budget of 100,000 yen or less, and want to visit tourist attractions and good restaurants."

[1176] The device then analyzes the user's emotions using an emotion engine, which collects and analyzes the user's non-verbal data (voice tone and facial expressions) in real time to determine the user's emotional state, such as whether they are excited, relaxed, or tired.

[1177] For example, if the user utters the word "fun" in an excited tone, the emotion engine will interpret this as the user being "excited."

[1178] The device sends the user's travel preference information and analyzed emotion data together to the server as an API request, and the server receives the request and analyzes the data.

[1179] The server inputs the user's desired information and emotional data into an AI model to generate the optimal travel plan. This generative AI model then uses past travel data and user history information to create a travel plan that suits the user's preferences.

[1180] For example, the server might create a "5-day Tokyo travel plan" and suggest sightseeing in Asakusa and Skytree on the first day, in response to a user's excited state, and then suggest visiting Ueno Zoo and Ameyoko Market on the second day, in response to a user's relaxed state.

[1181] The server sends the generated travel plan to the terminal, which then displays the plan to the user, who can review the displayed plan and make further customizations as needed.

[1182] Now, if the user decides to visit Odaiba instead of Ueno Zoo, they enter that change into their device. The device compiles the customization information and sends it back to the server. The server again uses the generative AI model to regenerate a customized itinerary based on the new data. The regenerated itinerary is sent back to the device and displayed to the user as the final itinerary.

[1183] For example, if a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[1184] In this way, the present invention realizes a system that improves the quality of travel plans by quickly providing flexible travel plans based on the user's wishes and making personalized suggestions that are tailored to the user's emotional state.

[1185] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1186] (Processing flow)

[1187] Step 1: Enter user travel information

[1188] The user inputs their travel preferences. Using the device interface, the user inputs detailed information such as their destination, travel dates, budget, and activities they would like to visit.

[1189] Input: destination, travel dates, budget, activities you want to visit, etc.

[1190] Specific behavior: A user enters information using text boxes and drop-down menus on the device.

[1191] Output: Travel preference data is saved on the device

[1192] Step 2: Collect and analyze emotion data

[1193] The device analyzes the user's emotions using an emotion engine, which collects and analyzes non-verbal data such as voice tone and facial expressions.

[1194] Input: Non-verbal data such as tone of voice, facial expressions, etc.

[1195] Specific operation: Collects the user's voice and facial expressions in real time using the device's built-in camera and microphone.

[1196] Data processing: Emotion engine uses voice and image analysis algorithms to determine emotional state

[1197] Output: User emotion data

[1198] Step 3: Send the data

[1199] The device sends travel preference information and emotion data to the server as an API request.

[1200] Input: Travel preference data, emotion data

[1201] Specific operation: The device converts the data into JSON format and sends it to the server using the HTTP protocol.

[1202] Data manipulation: structuring and encoding data

[1203] Output: The API request received by the server

[1204] Step 4: Generate your itinerary

[1205] The server analyzes the received data and generates an optimal travel plan using an artificial intelligence model.

[1206] Input: Travel preference information, emotional data

[1207] How it works: The server analyzes the data and uses past travel data and user history information to feed the generative AI model.

[1208] Data computation: Generative AI models run algorithms to create optimal travel plans

[1209] Output: Generated itinerary data

[1210] Step 5: View your plan

[1211] The server transmits the generated travel plan to the terminal, which displays it to the user.

[1212] Input: Generated itinerary data

[1213] Specific operation: The server sends a travel plan in JSON format to the device, which parses the plan and displays it on the interface.

[1214] Data processing: building and encoding plans, parsing for UI display

[1215] Output: A displayed itinerary

[1216] Step 6: Customize and Regenerate

[1217] The user then performs additional customizations on the displayed travel plan, and the customization information is sent from the device back to the server, which then generates a new plan using the artificial intelligence model again.

[1218] Input: Customization information

[1219] What happens: The user enters plan changes using the device interface, and the device sends the information to the server.

[1220] Data Processing: Collecting and Sending Customization Information

[1221] Output: Customization information received by the server, regenerated itinerary

[1222] This process flow allows users to quickly obtain and further customize a personalized travel plan that is tailored to their desires and feelings.

[1223] (Application example 2)

[1224] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1225] Conventional shopping systems lack personalized product suggestions that take into account the user's emotional state and lack mechanisms to improve user satisfaction. As a result, it takes time to find the optimal product that corresponds to a specific emotional state, making it difficult to provide an efficient shopping experience.

[1226] The specification process by the specification processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server has a means for the user to input a desired product,

[1227] means for transmitting the desired product information to a server;

[1228] a means for the emotion engine to analyze the user's emotion;

[1229] means for transmitting the analyzed emotion information to a server;

[1230] a means for generating product suggestions based on the desired product information and emotion information by using an artificial intelligence model in a server;

[1231] means for transmitting the generated product proposal to a terminal;

[1232] means for the terminal to display the product proposal to the user;

[1233] means for a user to customize the displayed product suggestions;

[1234] means for retransmitting the customized information to a server, and the server generating product suggestions again;

[1235] The method further includes means for finally displaying the regenerated product suggestions to the user, thereby enabling personalized product suggestions according to the user's emotional state.

[1236] "Desired product information" refers to detailed information such as the type of product the user wishes to purchase, their budget, and their preferred style.

[1237] "Emotion engine" refers to software or hardware for analyzing a user's emotional state.

[1238] "Analyzed emotional information" refers to data about a user's emotional state that has been analyzed by the emotion engine.

[1239] "Artificial intelligence model" refers to a system that includes an algorithm for generating optimal product suggestions based on a user's desired product information and emotional information.

[1240] "Product suggestions" refers to specific product lists and suggestions provided to users based on desired product information and analyzed emotional information.

[1241] "Customization" refers to an operation in which a user adds conditions or makes changes based on the displayed product proposals.

[1242] "Regeneration" refers to the process of recreating product proposals using an artificial intelligence model based on customized information.

[1243] This invention relates to a shopping assistant system that analyzes user emotions and generates personalized product recommendations. The system runs on devices such as smartphones, smart glasses, or head-mounted displays, and recommends optimal products to users.

[1244] The main components of the system are:

[1245] 1. A means for users to input desired products: Users use their smartphones or other devices to provide desired product information through a form to input information about the products they want to purchase (e.g., type, budget, style) or through a voice assistant.

[1246] 2. Emotion Engine: This is a software component that detects and analyzes the user's voice tone and facial expressions. Specific software used is Google Cloud's Speech-to-Text API and Microsoft Azure Cognitive Services.

[1247] 3. Means for transmitting the sales information and analyzed sentiment information to the server: This information is transmitted in real time to the server for further processing. Data is sent and received using API requests over the network.

[1248] 4. Artificial intelligence model on the server: The server is equipped with artificial intelligence models such as TensorFlow and GPT-4, which generate product suggestions based on the user's desired product information and emotional information. Based on this information, the server selects the most suitable product, taking into account past purchase data and user history data.

[1249] 5. Generating and sending product suggestions to the terminal: The generated product suggestions are sent to the terminal and presented visually or audibly to the user.

[1250] 6. Customizing Product Proposals: The user can input further conditions or modifications based on the displayed product proposals. This feedback is sent back to the server, and an updated proposal is generated.

[1251] 7. Displaying the final product proposal: The updated product proposal is resent to the terminal and finally provided to the user.

[1252] For example, if a user enters the desired product information as "I want a candle with a relaxing scent, but my budget is under 2,000 yen. I'm also looking for calming sweets," and the emotion engine analyzes the user's relaxed state, the server will generate suggestions for candles and sweets with a relaxing effect based on that emotional state.The user can then exclude products they don't like from the suggested products or add more specific conditions, and a re-optimized product list will be provided.

[1253] Examples of prompts:

[1254] "I want a candle with a relaxing scent, but my budget is under 2000 yen. I'm also looking for some calming sweets."

[1255] In this way, the present invention provides a system that takes into account the user's emotional state and can quickly provide personalized product suggestions, helping to make the shopping experience more satisfying.

[1256] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1257] Step 1:

[1258] Users input desired product information using a smartphone or other device, providing the type of product they want to purchase, their budget, and preferred style via text form or voice input.

[1259] Input: Desired product information (e.g., "I'd like a candle with a relaxing scent, but my budget is under 2000 yen. I'm also looking for some relaxing sweets.")

[1260] Output: Desired product information processed on the user's device

[1261] Step 2:

[1262] The device activates an emotion engine that analyzes the user's voice tone and facial expressions in real time via the camera and microphone, and uses Google Cloud's Speech-to-Text API and Microsoft Azure Cognitive Services to analyze the user's emotional state.

[1263] Input: User's voice tone, facial expression

[1264] Output: Analyzed emotional information (e.g., relaxed state)

[1265] Step 3:

[1266] The device sends the desired product information and analyzed emotion information to the server via the network as an API request.

[1267] Input: Desired product information, analyzed emotion information

[1268] Output: API request sent to the server

[1269] Step 4:

[1270] The server receives the desired product information and sentiment information, and preprocesses this information before inputting it into an artificial intelligence model (TensorFlow or GPT-4). Preprocessing includes data conversion and transformation into a unified format.

[1271] Input: Desired product information, analyzed emotion information

[1272] Output: Preprocessed data

[1273] Step 5:

[1274] The server inputs the preprocessed data into an AI model to generate optimal product suggestions. The AI ​​model also takes into account past purchase data and user history data to make more accurate suggestions.

[1275] Input: Preprocessed data, historical purchase data, user history data

[1276] Output: Product suggestions (e.g., relaxing candles, sweets)

[1277] Step 6:

[1278] The server transmits the generated product proposals to the terminal via the network.

[1279] Input: Product proposal

[1280] Output: Send request to user terminal

[1281] Step 7:

[1282] The terminal presents the received product proposal to the user visually or audibly, and the user inputs further conditions or changes based on the displayed product proposal.

[1283] Input: Product proposal

[1284] Output: User feedback (e.g., "Show me more products of a specific brand")

[1285] Step 8:

[1286] The user's feedback is resubmitted from the terminal to the server, which again uses the artificial intelligence model to generate updated product suggestions.

[1287] Input: User feedback

[1288] Output: Regenerated product suggestions

[1289] Step 9:

[1290] The server transmits the regenerated product proposals to the terminal via the network, and finally provides them to the user.

[1291] Input: Regenerated product suggestions

[1292] Output: Display of final product suggestions

[1293] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1294] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1295] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1296] [Fourth embodiment]

[1297] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1298] 7, a 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.

[1299] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1300] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1301] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1302] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1303] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1304] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1305] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1306] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1307] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1308] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1309] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1310] This invention relates to a system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal displays the travel plan to the user. To implement this system, the following procedures and requirements must be met:

[1311] First, to start planning a trip, the user inputs desired travel information into the terminal. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit (e.g., tourist attractions and restaurants). The terminal provides an interface for inputting this information.

[1312] Example: A user types into a terminal, "I want to plan a 5-day trip to Tokyo. My budget is under 100,000 yen, and I want to visit tourist attractions and good restaurants."

[1313] The device then generates an API request to send the entered travel preferences to a server, which receives and analyzes the request and installs an artificial intelligence model to generate a travel plan based on the user's preferences.

[1314] The server preprocesses the desired information and then inputs it into an artificial intelligence model that is capable of generating an optimal travel plan based on the input parameters. The model considers past travel data, user history, and available resources to suggest optimal schedules and places to visit at the destination.

[1315] Example: The server generates a detailed "5-day Tokyo travel plan" that includes visiting Asakusa and Skytree on the first day, Ueno Zoo and Ameyoko Market on the second day, etc.

[1316] The server then sends the generated itinerary to the device, which then displays it to the user. The user can review the displayed itinerary and make additional customizations as needed. For example, if the user wants to visit Odaiba instead of Ueno Zoo, they can input that change into the device.

[1317] The device compiles this customization information and sends it back to the server, which again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is then sent back to the device and displayed to the user as the final plan.

[1318] Example: If a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[1319] In this way, the present invention realizes a system that quickly provides flexible travel plans based on the user's wishes and can accommodate multiple customizations.

[1320] The processing flow will be explained below.

[1321] Step 1:

[1322] The user inputs travel preferences into the terminal, such as destination, travel dates, budget, and activities of interest.

[1323] Step 2:

[1324] The device collects the travel preference information entered and converts the data into a single data set.

[1325] Step 3:

[1326] The device sends the compiled data set to the server, and generates an API request and sends it to the server.

[1327] Step 4:

[1328] The server receives the API request, analyzes the request, and extracts travel preference information.

[1329] Step 5:

[1330] The server pre-processes the travel preference information, for example checking the data for consistency and converting it into a format suitable for artificial intelligence models.

[1331] Step 6:

[1332] The server inputs the preprocessed data into an artificial intelligence model, which then generates an optimal travel plan based on the input data.

[1333] Step 7:

[1334] The server compiles the generated itinerary into a dataset, for example creating a detailed schedule for each day.

[1335] Step 8:

[1336] The server sends the generated travel plan to the device. The travel plan is sent as an API response.

[1337] Step 9:

[1338] The device receives the travel plan from the server, analyzes the data, and displays it to the user.

[1339] Step 10:

[1340] The user can customize the displayed travel plan by entering any corrections or additions they wish to make into the device.

[1341] Step 11:

[1342] The device collects the user customization information and creates a new dataset.

[1343] Step 12:

[1344] The device resends the customized data set to the server, and generates another API request and sends it to the server.

[1345] Step 13:

[1346] The server receives the API request again and analyzes the new request information.

[1347] Step 14:

[1348] The server preprocesses the new request information, performs data integrity checks, and converts it into a format suitable for artificial intelligence models.

[1349] Step 15:

[1350] The server then feeds the preprocessed data back into the artificial intelligence model, which then generates a customized itinerary based on the new data.

[1351] Step 16:

[1352] The server compiles the regenerated itinerary into a dataset, e.g., creating a detailed schedule that reflects the changes.

[1353] Step 17:

[1354] The server sends the regenerated travel plan to the device and the final plan as an API response.

[1355] Step 18:

[1356] The terminal receives the regenerated travel plan from the server, analyzes the data, and displays the final plan to the user.

[1357] Through this series of steps, the user can obtain a travel plan that meets their needs, and a system is realized that can flexibly accommodate additional customization.

[1358] Example 1

[1359] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1360] Conventional travel plan creation systems have had the challenge of responding quickly and flexibly to user requests. Creating the optimal plan based on the user's desired travel information requires advanced data analysis and individual customization, which conventional systems find difficult. It is also difficult to respond quickly to user requests for changes, and multiple customization processes must proceed smoothly.

[1361] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1362] In this invention, the server includes means for inputting travel preference information from a user, means for transmitting the travel preference information to the server, means for generating a travel plan based on the travel preference information using an artificial intelligence model, means for transmitting the generated travel plan to a terminal, means for the terminal to display the travel plan to the user, means for the user to customize the displayed travel plan, means for retransmitting the customized information to the server and causing the server to regenerate the travel plan, and means for finally displaying the regenerated travel plan to the user. This makes it possible to provide flexible and prompt travel plans based on the user's preferences.

[1363] "User" refers to an individual or organization who inputs desired information to create a travel plan and reviews and customizes the generated plan.

[1364] "Desired information" refers to detailed information entered by the user, such as travel destination, travel itinerary, budget, and activities desired to visit.

[1365] "Terminal" refers to a device used by a user to input desired information, and includes smartphones, tablets, PCs, etc.

[1366] "Server" refers to the central computing system that receives, analyzes, processes, and generates travel plans based on user-submitted preferences.

[1367] "Artificial intelligence model" refers to the algorithms and computational models that generate optimal travel plans based on input data, and are built using deep learning libraries, etc.

[1368] An "API request" is a standardized form of digital communication that allows a device to send desired information to a server.

[1369] A "travel plan" refers to a plan that includes a specific travel schedule and suggestions of places to visit, which is generated by the server based on the user's desired information.

[1370] "Customization" refers to the user making additional changes or adjustments to the generated itinerary.

[1371] "Network" refers to a connection means such as the Internet or a local area network that allows servers and terminals to communicate with each other.

[1372] "Historical Travel Data" refers to data previously collected about other users' travel information and travel plans.

[1373] "History data" refers to data that records information about past trips and behavioral patterns of a particular user.

[1374] This invention is a system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal displays the travel plan to the user. To implement the system, several pieces of software and hardware are required.

[1375] First, to start planning a trip, the user inputs desired travel information into the device. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they would like to visit. The device provides an interface for inputting this information. For example, an input form is used on the screen of a smartphone, tablet, or PC. For example, the user might input, "I would like to plan a five-day trip to Tokyo. My budget is within 100,000 yen, and I would like to visit tourist attractions and good restaurants."

[1376] The device then generates an API request to send the entered travel preferences to a server. Software on the device (e.g., a mobile app or web browser) organizes these preferences and sends them over the network to the server. The server receives and analyzes the request. The server has an artificial intelligence model installed that generates a travel plan based on the user's preferences. This is done using deep learning libraries (e.g., TensorFlow and PyTorch).

[1377] The server preprocesses the desired information and then inputs it into an AI model. Preprocessing includes reformatting the data and adding necessary information. The AI ​​model generates an optimal travel plan based on the input parameters. The model considers past travel data, the user's history, and available resources to suggest the optimal schedule and places to visit at the destination. For example, the server might generate a detailed "5-day Tokyo travel plan" that includes visits to Asakusa and Skytree on the first day, Ueno Zoo and Ameyoko Market on the second day, and so on.

[1378] The server then sends the generated travel plan to the device, which then displays it to the user. The user can review the displayed plan and make additional customizations as needed. For example, if the user wants to go to Odaiba instead of Ueno Zoo, they can enter that change into the device. The user interface is designed to allow the user to easily make changes.

[1379] The device compiles this customization information and sends it back to the server. The server again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is sent back to the device and displayed to the user as the final plan. For example, if the user inputs, "I want to go to Odaiba instead of Ueno Zoo on day 3," the server generates a new plan that includes Odaiba, and the device displays that final plan.

[1380] As described above, the present invention is a system that quickly provides flexible travel plans based on the user's wishes and can accommodate multiple customizations. This system allows users to easily create satisfactory travel plans.

[1381] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1382] Step 1:

[1383] The user inputs desired travel information into the terminal.

[1384] Input: Details such as your travel destination, travel dates, budget, and activities you want to visit.

[1385] Specific behavior: Using the user interface, enter the required information into the specified form. For example, enter "I want to plan a 5-day trip to Tokyo, with a budget of 100,000 yen or less, and would like to visit tourist attractions and good restaurants."

[1386] Step 2:

[1387] The device generates an API request based on the travel preference information entered.

[1388] Input: Travel preference information entered by the user.

[1389] Data processing: Converting input information into an appropriate format, such as JSON, and packaging it as an API request.

[1390] Output: The API request to send to the server.

[1391] What it does: The device application organizes the desired information and generates a request, such as a JSON object containing data about the travel destination, itinerary, budget, and activities.

[1392] Step 3:

[1393] The device sends the generated API request to the server.

[1394] Input: API request.

[1395] What happens: The device uses a network connection (Wi-Fi, cellular, etc.) to send a request to the server, often via an HTTP POST request.

[1396] Step 4:

[1397] The server receives the API request and analyzes it.

[1398] Input: The API request sent from the device.

[1399] Data processing: Analyze the request content, extract the user's desired information, and save it as structured data.

[1400] Output: Parsed user preference information.

[1401] How it works: A server-side program receives the request, analyzes it, and extracts the necessary data, such as destination, itinerary, and budget, and stores them in the appropriate database fields.

[1402] Step 5:

[1403] The server preprocesses the user's desired information and inputs it into the artificial intelligence model.

[1404] Input: Parsed user preference information.

[1405] Data processing: Normalize data, fill in missing values, and convert to the appropriate format.

[1406] Output: Preprocessed data.

[1407] What happens: A data preprocessing script is executed to convert the user's desired information into a format that is easy for the AI ​​model to use, such as tokenizing text data and standardizing numeric data.

[1408] Step 6:

[1409] The server generates the itinerary using an artificial intelligence model.

[1410] Input: Preprocessed user preference information.

[1411] Data calculations: An artificial intelligence model calculates the optimal travel plan based on input data and generates suggested itineraries and places to visit.

[1412] Output: The generated itinerary.

[1413] What it does: An artificial intelligence model (e.g., a model implemented in TensorFlow or PyTorch) is run to generate a travel plan, including a daily schedule and details of the places to visit.

[1414] Step 7:

[1415] The server transmits the generated travel plan to the terminal.

[1416] Input: The generated itinerary.

[1417] Specific operation: The server sends the travel plan to the device as an API response, which is often an HTTP response.

[1418] Step 8:

[1419] The terminal displays the travel plan to the user.

[1420] Input: The itinerary sent from the server.

[1421] Output: The itinerary displayed to the user.

[1422] Specific operation: The application on the device receives the response and displays the itinerary in the user interface, for example, showing the schedule by day and details of the places to visit.

[1423] Step 9:

[1424] The user customizes the travel plan.

[1425] Input: The displayed itinerary.

[1426] Specific behavior: The user uses the interface to input changes to the travel plan and enters corrections or additional information. For example, the user enters, "I would like to go to Odaiba instead of Ueno Zoo on the third day."

[1427] Step 10:

[1428] The terminal collects the customization information and transmits it to the server again.

[1429] Input: Customization information entered by the user.

[1430] Data processing: Convert the customization information into an appropriate format, such as JSON, and package it as a resubmission request.

[1431] Output: The API request to resend to the server.

[1432] Specific operation: The device organizes the desired changes, generates a new request, and sends it to the server. For example, it generates a JSON object containing data about the updated schedule and places to visit.

[1433] Step 11:

[1434] The server receives the request again, analyzes it, and inputs it into the artificial intelligence model.

[1435] Input: The resubmitted API request.

[1436] Data processing: Analyze the request content to extract new customization information and preprocess it into a form suitable for model input.

[1437] Output: The new preprocessed customization information.

[1438] Specific operation: The server receives the retransmission request, analyzes the content to extract the change information, and executes the data preprocessing script to format it for model input.

[1439] Step 12:

[1440] The server again uses the artificial intelligence model to generate a new itinerary.

[1441] Input: The preprocessed new customization information.

[1442] Data computation: Artificial intelligence models recalculate optimal travel plans based on new information and generate revised itineraries and destinations.

[1443] Output: The regenerated itinerary.

[1444] Specific operation: The AI ​​model is run again to generate a new itinerary, for example, one that includes a new stop at Odaiba.

[1445] Step 13:

[1446] The server sends the regenerated itinerary to the terminal and finally displays it to the user.

[1447] Input: The regenerated itinerary.

[1448] Output: The final itinerary that is displayed to the user.

[1449] Specific operation: The server sends the new travel plan to the device as an API response, the device receives it, and displays the final plan on the user interface.

[1450] (Application example 1)

[1451] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1452] When planning a trip, it is important to provide users with their desired travel plans quickly and flexibly. There is also a growing need to obtain real-time tourist information and information on nearby brick-and-mortar stores while traveling, but conventional systems cannot adequately meet these needs. In particular, when customizing travel plans and providing real-time information, it is necessary to quickly provide optimal suggestions while taking into account the user's current location information. Therefore, a system is needed that can provide flexible travel plans based on the user's preferences, as well as efficiently provide real-time tourist information and information on nearby brick-and-mortar stores while traveling.

[1453] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1454] In this invention, the server includes means for inputting travel preferences from a user, means for transmitting the travel preference information to the server, means for the server to generate a travel plan based on the travel preference information using an artificial intelligence model, means for transmitting the generated travel plan to a terminal, means for the terminal to display the travel plan to the user, means for the user to customize the displayed travel plan, means for retransmitting the customized information to the server and causing the server to re-generate the travel plan, means for finally displaying the re-generated travel plan to the user, means for providing real-time tourist information and information on nearby brick-and-mortar stores based on the user's location information, and means for displaying the real-time information on the user's smartphone. This enables a system that utilizes the user's location information to provide real-time tourist information and information on brick-and-mortar stores and quickly respond to customization of travel plans.

[1455] "User" means an individual or entity that uses the system to plan a trip.

[1456] "Travel preference information" is detailed information about the trip the user wants to plan, including the destination, date, budget, activities they want to visit, and so on.

[1457] A "server" is a computing device that receives and analyzes travel preference information submitted by users and generates and regenerates travel plans using artificial intelligence models.

[1458] An "artificial intelligence model" is a computational algorithm that generates optimal travel plans based on past travel data and user history data.

[1459] A "travel plan" is a detailed itinerary and suggested destinations generated based on the user's travel preferences.

[1460] A "terminal" is an electronic device that a user uses to view and customize their travel plan, including a smartphone.

[1461] "Customization" refers to the act of a user making changes to a displayed itinerary, including changing specific attractions or schedules.

[1462] "Real-time information" refers to tourist information and brick-and-mortar store information provided based on the user's current location, and is characterized by its immediacy.

[1463] A "physical store" is a physical store that a user can visit while traveling, including restaurants, shops, etc.

[1464] A "smartphone" is a mobile phone that can connect to the Internet and use applications, and in many cases is equipped with GPS functionality.

[1465] This invention relates to a travel support system in which a user inputs desired travel information, a server generates a travel plan using an artificial intelligence model, and a terminal presents and customizes the plan to the user in real time. Specific implementation methods of this system are described below.

[1466] Key components of the system

[1467] 1. User device (smartphone)

[1468] The user terminal is the device that the user uses to input desired travel information and review and customize the generated travel plan. A smartphone is usually used, but tablets and PCs can also be used.

[1469] 2. Server

[1470] The server receives travel information sent from the user's device and generates and regenerates travel plans based on that information. A generative AI model is used to generate travel plans.

[1471] 3. Generative AI Models

[1472] The generative AI model runs on a server and is an algorithm that generates optimal travel plans based on the travel preferences entered, while referencing past travel data and user history.

[1473] 4. Network

[1474] The Internet is used as a network for communication between user terminals and servers.

[1475] Specific methods for carrying out the invention

[1476] 1. User Input

[1477] Users input their travel preferences through an application on their smartphone, including destination, travel dates, budget, and activities they would like to visit.

[1478] Example prompt sentence:

[1479] Destination: Kyoto

[1480] Start date (YYYY-MM-DD):2023-11-01

[1481] End date (YYYY-MM-DD):2023-11-05

[1482] Budget: 100,000

[1483] Activities you would like to visit (separated by commas): Kiyomizu-dera Temple, Kinkaku-ji Temple, Gion, Arashiyama

[1484] 2. Data transmission and analysis

[1485] The user device sends the entered travel preference information to the server, which then analyzes the travel preference information sent to the server as an API request.

[1486] 3. Generate a travel plan

[1487] The generative AI model on the server generates an optimal travel plan based on the user's travel preferences. The generated plan is a detailed itinerary that reflects the user's preferences.

[1488] Examples:

[1489] The schedule for each day is detailed, with a visit to Kiyomizu-dera Temple on the first day and Kinkaku-ji Temple on the second day.

[1490] 4. View and customize your plan

[1491] The server sends the generated travel plan to the user's device, where the user can view the plan on their smartphone. Users can also customize the plan, for example, by changing the destinations or schedule.

[1492] 5. Real-time information provision

[1493] While traveling, real-time tourist information and information on nearby physical stores are provided based on the user's location information, allowing users to receive the most appropriate tourist information, restaurant and shop information, etc. based on their current location.

[1494] This system allows users to easily create, check, and customize travel plans that suit their preferences, and also provides real-time information during their trip, resulting in a more satisfying travel experience for users.

[1495] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1496] Specific processing steps of the program

[1497] Step 1:

[1498] The user inputs desired travel information into their smartphone. Input items include the destination, travel dates, budget, and activities they want to visit. For example, information such as "Kyoto," "2023-11-01 ~ 2023-11-05," "budget 100,000 yen," and "Kiyomizu-dera Temple, Kinkaku-ji Temple, Gion, Arashiyama" is input. The input information is preprocessed for the next process.

[1499] Input: Destination, travel dates, budget, activities you want to visit

[1500] Output: The desired information formatted from the input information

[1501] Step 2:

[1502] The device sends the desired information obtained in step 1 to the server as an API request. The request is sent using an HTTP POST request, and the request data is serialized in JSON format. The server receives this request.

[1503] Input: Travel preference information (JSON format)

[1504] Output: The data sent as a request to the server.

[1505] Step 3:

[1506] The server receives travel preferences and inputs them into the generative AI model. The generative AI model generates an optimal travel plan based on the preferences, referencing past travel data and the user's history data. The AI ​​model considers different parameters to create a detailed itinerary. For example, a specific schedule is generated such as "Day 1: Visit Kiyomizu-dera Temple in the morning, stroll through Gion in the afternoon."

[1507] Input: Travel preference information

[1508] Output: Generated itinerary

[1509] Step 4:

[1510] The server serializes the generated itinerary in JSON format and sends it to the device, which receives the data, parses it, and displays it in a format that the user can view.

[1511] Input: Generated travel plan (JSON format)

[1512] Output: The travel plan displayed on the user's device

[1513] Step 5:

[1514] The user checks the displayed itinerary and customizes it as necessary. For example, the user may make changes such as "I want to cancel Kinkaku-ji Temple on the second day and visit Arashiyama instead." This information is then sent back to the server from the device.

[1515] Input: Customization information

[1516] Output: Customization data sent from the device to the server

[1517] Step 6:

[1518] The server receives the resubmitted customization information and uses the generative AI model again to generate a new travel plan that reflects the user's latest requests.

[1519] Input: Customization information

[1520] Output: Regenerated itinerary

[1521] Step 7:

[1522] The server serializes the regenerated itinerary into JSON format and resends it to the device, which parses the data and displays it again to the user, thus finalizing the itinerary.

[1523] Input: Regenerated itinerary (JSON format)

[1524] Output: The final itinerary displayed on the user's device

[1525] Step 8:

[1526] During a trip, real-time tourist information and information on nearby brick-and-mortar stores are provided using the user's location information. The user's current location is periodically sent to the server using the GPS function of the user's device. Based on this location information, the server generates information on nearby tourist attractions, restaurants, and shops and provides it to the user.

[1527] Input: User's location

[1528] Output: Real-time tourist information and brick-and-mortar store information

[1529] The above are the processing steps of the specific program for carrying out the present invention.

[1530] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1531] This invention relates to a system that generates personalized travel plans by combining a user's desired travel information with an emotion engine that recognizes the user's emotions. To implement this system, the following procedures and requirements must be met:

[1532] First, to start planning a trip, the user inputs desired travel information into the terminal. Specifically, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit (e.g., tourist attractions and restaurants). The terminal provides an interface for inputting this information.

[1533] Example: A user types into a terminal, "I want to plan a 5-day trip to Tokyo. My budget is under 100,000 yen, and I want to visit tourist attractions and good restaurants."

[1534] The emotion engine then analyzes the user's input and non-verbal data (e.g., voice tone, facial expressions), identifies the user's emotional state (e.g., excited, relaxed, tired), and sends that information to the server.

[1535] For example, if a user inputs the emotion "excitement" into the device, the emotion engine will analyze the emotion and determine that the user is in an "excited" state.

[1536] The device generates an API request to send travel preference information and emotion data analyzed by the emotion engine to the server. The server receives and analyzes this request. The server is installed with an artificial intelligence model that generates a travel plan based on the user's preference information and emotion information.

[1537] The server preprocesses the desired information and emotional information and then inputs it into an artificial intelligence model. This artificial intelligence model is capable of generating an optimal travel plan based on the input parameters. The model considers past travel data, user history information, and available resources to propose an optimal schedule and places to visit at the destination. Furthermore, by reflecting emotional information, the model proposes a plan that is tailored to the user's emotional state.

[1538] Example: The server creates a "5-day Tokyo travel plan" and suggests exciting tourist spots (Asakusa and Skytree) on the first day to accommodate an excited user, and calm places (Ueno Zoo and Ameyoko Market) on the second day to accommodate a relaxed user.

[1539] The server then sends the generated itinerary to the device, which then displays it to the user. The user can review the displayed itinerary and make additional customizations as needed. For example, if the user wants to visit Odaiba instead of Ueno Zoo, they can input that change into the device.

[1540] The device compiles this customization information and sends it back to the server, which again uses the artificial intelligence model to regenerate a customized travel plan based on the new data. The regenerated plan is then sent back to the device and displayed to the user as the final plan.

[1541] Example: If a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[1542] In this way, the present invention realizes a system that improves the quality of travel plans by quickly providing flexible travel plans based on the user's wishes and making personalized suggestions that are tailored to the user's emotional state.

[1543] The processing flow will be explained below.

[1544] Step 1:

[1545] The user inputs travel preferences into the terminal, such as destination, travel dates, budget, and activities of interest.

[1546] Step 2:

[1547] The emotion engine analyzes user input and non-verbal data (e.g., vocal tone, facial expression) to identify emotional states.

[1548] Step 3:

[1549] The device compiles travel preference information and analyzed emotion data and converts it into a dataset.

[1550] Step 4:

[1551] The device generates an API request to send the compiled data set to the server, including travel preference information and emotion data.

[1552] Step 5:

[1553] The server receives the API request, analyzes the request, and extracts travel preference information and emotion data.

[1554] Step 6:

[1555] The server pre-processes the travel preference and emotion data, for example by checking the data integrity and converting it into a format suitable for the artificial intelligence model.

[1556] Step 7:

[1557] The server inputs the preprocessed data into an artificial intelligence model, which then generates an optimal travel plan based on the input data.

[1558] Step 8:

[1559] The server compiles the generated itinerary into a dataset, for example creating a detailed schedule for each day.

[1560] Step 9:

[1561] An API response is generated to send the travel plan generated by the server to the terminal.

[1562] Step 10:

[1563] The device receives the API response from the server, analyzes the received data, and displays it to the user.

[1564] Step 11:

[1565] The user reviews the displayed itinerary, customizes it as needed, and inputs any corrections or additions they wish to make into the device.

[1566] Step 12:

[1567] The device collects the user's customization information and creates a new data set.

[1568] Step 13:

[1569] The device resends the customized data set to the server, and generates another API request and sends it to the server.

[1570] Step 14:

[1571] The server receives the API request again and parses the new preferences, extracting customized travel preferences and sentiment data.

[1572] Step 15:

[1573] The server pre-processes the customized travel preference and emotion data, performs data integrity checks, and converts it into a format suitable for artificial intelligence models.

[1574] Step 16:

[1575] The server then feeds the preprocessed data back into the artificial intelligence model, which then generates a customized itinerary based on the new data.

[1576] Step 17:

[1577] The server compiles the regenerated itinerary into a dataset, e.g., creating a detailed schedule that reflects the changes.

[1578] Step 18:

[1579] The server generates the final API response to send the regenerated itinerary to the device.

[1580] Step 19:

[1581] The device receives the regenerated API response from the server, parses the received data, and displays the final plan to the user.

[1582] Through this series of steps, the system allows users to obtain a travel plan that meets their needs and can also provide personalized suggestions based on their emotional state.

[1583] Example 2

[1584] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1585] In modern travel planning, there is a need to quickly and accurately generate personalized itineraries that reflect users' diverse desires and emotions. However, conventional systems have difficulty incorporating users' specific desires and real-time emotions, which makes it difficult to increase user satisfaction.

[1586] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1587] In this invention, the server includes means for inputting travel preference information from a user, means for collecting data for identifying the user's emotions, means for transmitting the travel preference information and the collected emotion data to the server, means for the server to generate an itinerary based on the travel preference information and emotion data using an artificial intelligence model, means for transmitting the generated itinerary to a terminal, means for the terminal to display the itinerary to the user, means for the user to customize the displayed itinerary, means for retransmitting the customized information to the server and the server to generate a new itinerary, and means for finally displaying the regenerated itinerary to the user. This makes it possible to quickly and accurately generate a personalized itinerary that reflects the user's specific preferences and real-time emotions.

[1588] "User's desired travel information" is detailed information about the user's desired trip, such as travel destination, travel itinerary, budget, and activities at the destination.

[1589] "Data for identifying the user's emotions" refers to data that includes non-verbal information about the user, such as tone of voice and facial expressions.

[1590] The "server" is a central processing system that receives the user's travel preferences and emotion data and generates a travel plan using a generative AI model.

[1591] A "generative AI model" is an artificial intelligence algorithm that references past travel data and user history information to create optimal travel plans based on the user's preferences and emotional data.

[1592] A "terminal" is a device that allows a user to input desired travel information and display a travel plan sent from a server.

[1593] An "API request" is a request for data transmission made from a terminal to a server, and includes travel preference information and emotion data.

[1594] A "travel plan" is a plan that includes specific travel itineraries, destinations, recommended activities, etc., generated based on the user's desired information and emotional state.

[1595] "Customization" refers to the user making changes or additions to the displayed travel plan.

[1596] "Historical Trip Data" means details about previously recorded trips that are used to create similar trip itineraries.

[1597] "User history information" is history data for each user, such as trips the user has taken in the past and travel preferences that the user has entered up to now.

[1598] The present invention relates to a system that generates a more personalized travel plan by inputting user travel preferences and recognizing the user's emotions. The system includes a terminal, a server, and an emotion engine.

[1599] First, to start planning a trip, the user inputs their desired travel information into the device. Using the device interface, the user inputs detailed information such as the destination, travel dates, budget, and activities they want to visit. The device collects this information and prepares it for the next process.

[1600] For example, consider the case where a user inputs, "I want to plan a 5-day trip to Tokyo, with a budget of 100,000 yen or less, and want to visit tourist attractions and good restaurants."

[1601] The device then analyzes the user's emotions using an emotion engine, which collects and analyzes the user's non-verbal data (voice tone and facial expressions) in real time to determine the user's emotional state, such as whether they are excited, relaxed, or tired.

[1602] For example, if the user utters the word "fun" in an excited tone, the emotion engine will interpret this as the user being "excited."

[1603] The device sends the user's travel preference information and analyzed emotion data together to the server as an API request, and the server receives the request and analyzes the data.

[1604] The server inputs the user's desired information and emotional data into an AI model to generate the optimal travel plan. This generative AI model then uses past travel data and user history information to create a travel plan that suits the user's preferences.

[1605] For example, the server might create a "5-day Tokyo travel plan" and suggest sightseeing in Asakusa and Skytree on the first day, in response to a user's excited state, and then suggest visiting Ueno Zoo and Ameyoko Market on the second day, in response to a user's relaxed state.

[1606] The server sends the generated travel plan to the terminal, which then displays the plan to the user, who can review the displayed plan and make further customizations as needed.

[1607] Now, if the user decides to visit Odaiba instead of Ueno Zoo, they enter that change into their device. The device compiles the customization information and sends it back to the server. The server again uses the generative AI model to regenerate a customized itinerary based on the new data. The regenerated itinerary is sent back to the device and displayed to the user as the final itinerary.

[1608] For example, if a user inputs "I want to go to Odaiba instead of Ueno Zoo on the third day," the server will generate a new plan that includes Odaiba, and the device will display the final plan.

[1609] In this way, the present invention realizes a system that improves the quality of travel plans by quickly providing flexible travel plans based on the user's wishes and making personalized suggestions that are tailored to the user's emotional state.

[1610] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1611] (Processing flow)

[1612] Step 1: Enter user travel information

[1613] The user inputs their travel preferences. Using the device interface, the user inputs detailed information such as their destination, travel dates, budget, and activities they would like to visit.

[1614] Input: destination, travel dates, budget, activities you want to visit, etc.

[1615] Specific behavior: A user enters information using text boxes and drop-down menus on the device.

[1616] Output: Travel preference data is saved on the device

[1617] Step 2: Collect and analyze emotion data

[1618] The device analyzes the user's emotions using an emotion engine, which collects and analyzes non-verbal data such as voice tone and facial expressions.

[1619] Input: Non-verbal data such as tone of voice, facial expressions, etc.

[1620] Specific operation: Collects the user's voice and facial expressions in real time using the device's built-in camera and microphone.

[1621] Data processing: Emotion engine uses voice and image analysis algorithms to determine emotional state

[1622] Output: User emotion data

[1623] Step 3: Send the data

[1624] The device sends travel preference information and emotion data to the server as an API request.

[1625] Input: Travel preference data, emotion data

[1626] Specific operation: The device converts the data into JSON format and sends it to the server using the HTTP protocol.

[1627] Data manipulation: structuring and encoding data

[1628] Output: The API request received by the server

[1629] Step 4: Generate your itinerary

[1630] The server analyzes the received data and generates an optimal travel plan using an artificial intelligence model.

[1631] Input: Travel preference information, emotional data

[1632] How it works: The server analyzes the data and uses past travel data and user history information to feed the generative AI model.

[1633] Data computation: Generative AI models run algorithms to create optimal travel plans

[1634] Output: Generated itinerary data

[1635] Step 5: View your plan

[1636] The server transmits the generated travel plan to the terminal, which displays it to the user.

[1637] Input: Generated itinerary data

[1638] Specific operation: The server sends a travel plan in JSON format to the device, which parses the plan and displays it on the interface.

[1639] Data processing: building and encoding plans, parsing for UI display

[1640] Output: A displayed itinerary

[1641] Step 6: Customize and Regenerate

[1642] The user then performs additional customizations on the displayed travel plan, and the customization information is sent from the device back to the server, which then generates a new plan using the artificial intelligence model again.

[1643] Input: Customization information

[1644] What happens: The user enters plan changes using the device interface, and the device sends the information to the server.

[1645] Data Processing: Collecting and Sending Customization Information

[1646] Output: Customization information received by the server, regenerated itinerary

[1647] This process flow allows users to quickly obtain and further customize a personalized travel plan that is tailored to their desires and feelings.

[1648] (Application example 2)

[1649] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1650] Conventional shopping systems lack personalized product suggestions that take into account the user's emotional state and lack mechanisms to improve user satisfaction. As a result, it takes time to find the optimal product that corresponds to a specific emotional state, making it difficult to provide an efficient shopping experience.

[1651] The specification process by the specification processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server has a means for the user to input a desired product,

[1652] means for transmitting the desired product information to a server;

[1653] a means for the emotion engine to analyze the user's emotion;

[1654] means for transmitting the analyzed emotion information to a server;

[1655] a means for generating product suggestions based on the desired product information and emotion information by using an artificial intelligence model in a server;

[1656] means for transmitting the generated product proposal to a terminal;

[1657] means for the terminal to display the product proposal to the user;

[1658] means for a user to customize the displayed product suggestions;

[1659] means for retransmitting the customized information to a server, and the server generating product suggestions again;

[1660] The method further includes means for finally displaying the regenerated product suggestions to the user, thereby enabling personalized product suggestions according to the user's emotional state.

[1661] "Desired product information" refers to detailed information such as the type of product the user wishes to purchase, their budget, and their preferred style.

[1662] "Emotion engine" refers to software or hardware for analyzing a user's emotional state.

[1663] "Analyzed emotional information" refers to data about a user's emotional state that has been analyzed by the emotion engine.

[1664] "Artificial intelligence model" refers to a system that includes an algorithm for generating optimal product suggestions based on a user's desired product information and emotional information.

[1665] "Product suggestions" refers to specific product lists and suggestions provided to users based on desired product information and analyzed emotional information.

[1666] "Customization" refers to an operation in which a user adds conditions or makes changes based on the displayed product proposals.

[1667] "Regeneration" refers to the process of recreating product proposals using an artificial intelligence model based on customized information.

[1668] This invention relates to a shopping assistant system that analyzes user emotions and generates personalized product recommendations. The system runs on devices such as smartphones, smart glasses, or head-mounted displays, and recommends optimal products to users.

[1669] The main components of the system are:

[1670] 1. A means for users to input desired products: Users use their smartphones or other devices to provide desired product information through a form to input information about the products they want to purchase (e.g., type, budget, style) or through a voice assistant.

[1671] 2. Emotion Engine: This is a software component that detects and analyzes the user's voice tone and facial expressions. Specific software used is Google Cloud's Speech-to-Text API and Microsoft Azure Cognitive Services.

[1672] 3. Means for transmitting the sales information and analyzed sentiment information to the server: This information is transmitted in real time to the server for further processing. Data is sent and received using API requests over the network.

[1673] 4. Artificial intelligence model on the server: The server is equipped with artificial intelligence models such as TensorFlow and GPT-4, which generate product suggestions based on the user's desired product information and emotional information. Based on this information, the server selects the most suitable product, taking into account past purchase data and user history data.

[1674] 5. Generating and sending product suggestions to the terminal: The generated product suggestions are sent to the terminal and presented visually or audibly to the user.

[1675] 6. Customizing Product Proposals: The user can input further conditions or modifications based on the displayed product proposals. This feedback is sent back to the server, and an updated proposal is generated.

[1676] 7. Displaying the final product proposal: The updated product proposal is resent to the terminal and finally provided to the user.

[1677] For example, if a user enters the desired product information as "I want a candle with a relaxing scent, but my budget is under 2,000 yen. I'm also looking for calming sweets," and the emotion engine analyzes the user's relaxed state, the server will generate suggestions for candles and sweets with a relaxing effect based on that emotional state.The user can then exclude products they don't like from the suggested products or add more specific conditions, and a re-optimized product list will be provided.

[1678] Examples of prompts:

[1679] "I want a candle with a relaxing scent, but my budget is under 2000 yen. I'm also looking for some calming sweets."

[1680] In this way, the present invention provides a system that takes into account the user's emotional state and can quickly provide personalized product suggestions, helping to make the shopping experience more satisfying.

[1681] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1682] Step 1:

[1683] Users input desired product information using a smartphone or other device, providing the type of product they want to purchase, their budget, and preferred style via text form or voice input.

[1684] Input: Desired product information (e.g., "I'd like a candle with a relaxing scent, but my budget is under 2000 yen. I'm also looking for some relaxing sweets.")

[1685] Output: Desired product information processed on the user's device

[1686] Step 2:

[1687] The device activates an emotion engine that analyzes the user's voice tone and facial expressions in real time via the camera and microphone, and uses Google Cloud's Speech-to-Text API and Microsoft Azure Cognitive Services to analyze the user's emotional state.

[1688] Input: User's voice tone, facial expression

[1689] Output: Analyzed emotional information (e.g., relaxed state)

[1690] Step 3:

[1691] The device sends the desired product information and analyzed emotion information to the server via the network as an API request.

[1692] Input: Desired product information, analyzed emotion information

[1693] Output: API request sent to the server

[1694] Step 4:

[1695] The server receives the desired product information and sentiment information, and preprocesses this information before inputting it into an artificial intelligence model (TensorFlow or GPT-4). Preprocessing includes data conversion and transformation into a unified format.

[1696] Input: Desired product information, analyzed emotion information

[1697] Output: Preprocessed data

[1698] Step 5:

[1699] The server inputs the preprocessed data into an AI model to generate optimal product suggestions. The AI ​​model also takes into account past purchase data and user history data to make more accurate suggestions.

[1700] Input: Preprocessed data, historical purchase data, user history data

[1701] Output: Product suggestions (e.g., relaxing candles, sweets)

[1702] Step 6:

[1703] The server transmits the generated product proposals to the terminal via the network.

[1704] Input: Product proposal

[1705] Output: Send request to user terminal

[1706] Step 7:

[1707] The terminal presents the received product proposal to the user visually or audibly, and the user inputs further conditions or changes based on the displayed product proposal.

[1708] Input: Product proposal

[1709] Output: User feedback (e.g., "Show me more products of a specific brand")

[1710] Step 8:

[1711] The user's feedback is resubmitted from the terminal to the server, which again uses the artificial intelligence model to generate updated product suggestions.

[1712] Input: User feedback

[1713] Output: Regenerated product suggestions

[1714] Step 9:

[1715] The server transmits the regenerated product proposals to the terminal via the network, and finally provides them to the user.

[1716] Input: Regenerated product suggestions

[1717] Output: Display of final product suggestions

[1718] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1719] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1720] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1721] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1722] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1723] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1724] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1725] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1726] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1727] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1728] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1729] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1730] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1731] 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.

[1732] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1733] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1734] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1735] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1736] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1737] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1738] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1739] The following is further disclosed regarding the above embodiment.

[1740] (Claim 1)

[1741] means for inputting travel preferences from a user;

[1742] means for transmitting the travel preference information to a server;

[1743] A server uses an artificial intelligence model to generate a travel plan based on the travel preference information;

[1744] means for transmitting the generated travel plan to a terminal;

[1745] means for the terminal to display the travel plan to the user;

[1746] means for a user to customize the displayed itinerary;

[1747] means for retransmitting the customized information to a server, and the server regenerating a travel plan;

[1748] and means for ultimately displaying said regenerated travel plan to a user.

[1749] (Claim 2)

[1750] 2. The system according to claim 1, further comprising a connection means via a network for allowing the server and the terminal to communicate with each other.

[1751] (Claim 3)

[1752] 10. The system of claim 1, further comprising means for referencing past travel data and user history data when the server generates and regenerates travel plans.

[1753] "Example 1"

[1754] (Claim 1)

[1755] A means for a user to input desired travel information;

[1756] means for transmitting the travel preference information to a server;

[1757] A server uses an artificial intelligence model to generate a travel plan based on the travel preference information;

[1758] means for transmitting the generated travel plan to a terminal;

[1759] means for the terminal to display the travel plan to the user;

[1760] means for a user to customize the displayed itinerary;

[1761] means for retransmitting the customized information to the server, and causing the server to generate the travel plan again;

[1762] and means for ultimately displaying said regenerated travel plan to a user.

[1763] (Claim 2)

[1764] 2. The system according to claim 1, further comprising a connection means via a network for allowing the server and the terminal to communicate with each other.

[1765] (Claim 3)

[1766] 10. The system of claim 1, further comprising means for referencing past travel data and user history data when the server generates and regenerates travel plans.

[1767] "Application Example 1"

[1768] (Claim 1)

[1769] means for inputting travel preferences from a user;

[1770] means for transmitting the travel preference information to a server;

[1771] A server uses an artificial intelligence model to generate a travel plan based on the travel preference information;

[1772] means for transmitting the generated travel plan to a terminal;

[1773] means for the terminal to display the travel plan to the user;

[1774] means for a user to customize the displayed itinerary;

[1775] means for retransmitting the customized information to a server, and the server regenerating a travel plan;

[1776] means for finally displaying the regenerated travel plan to a user;

[1777] A means for providing real-time tourist information and information on nearby brick-and-mortar stores based on the user's location information;

[1778] The system includes a means for displaying the real-time information on a user's smartphone.

[1779] (Claim 2)

[1780] 2. The system according to claim 1, further comprising a connection means via a network for allowing the server and the terminal to communicate with each other.

[1781] (Claim 3)

[1782] 10. The system of claim 1, further comprising means for referencing past travel data and user history data when the server generates and regenerates travel plans.

[1783] "Example 2: Combining Emotion Engines"

[1784] (Claim 1)

[1785] A means for a user to input desired travel information;

[1786] means for collecting data for identifying a user's emotion;

[1787] means for transmitting the travel preference information and collected emotion data to a server;

[1788] a server using an artificial intelligence model to generate a travel plan based on the travel preference information and emotion data;

[1789] means for transmitting the generated travel plan to a terminal;

[1790] means for the terminal to display the travel plan to the user;

[1791] means for a user to customize the displayed itinerary;

[1792] means for retransmitting the customized information to a server, and the server regenerating a travel plan;

[1793] and means for ultimately displaying said regenerated travel plan to a user.

[1794] (Claim 2)

[1795] 2. The system according to claim 1, further comprising a connection means via a network for allowing the server and the terminal to communicate with each other.

[1796] (Claim 3)

[1797] 10. The system of claim 1, further comprising means for referencing past travel data and user history data when the server generates and regenerates travel plans.

[1798] "Application example 2 when combining emotion engines"

[1799] (Claim 1)

[1800] A means for a user to input a desired product;

[1801] means for transmitting the desired product information to a server;

[1802] a means for the emotion engine to analyze the user's emotion;

[1803] means for transmitting the analyzed emotion information to a server;

[1804] a means for generating product suggestions based on the desired product information and emotion information by using an artificial intelligence model in a server;

[1805] means for transmitting the generated product proposal to a terminal;

[1806] means for the terminal to display the product proposal to the user;

[1807] means for a user to customize the displayed product suggestions;

[1808] means for retransmitting the customized information to a server, and the server generating product suggestions again;

[1809] and means for ultimately displaying said regenerated product suggestions to a user.

[1810] (Claim 2)

[1811] 2. The system according to claim 1, further comprising a connection means via a network for allowing the server and the terminal to communicate with each other.

[1812] (Claim 3)

[1813] 2. The system of claim 1, further comprising means for referencing past purchase data and user history data when the server generates and regenerates product suggestions. [Explanation of symbols]

[1814] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for inputting travel preferences from a user; means for transmitting the travel preference information to a server; A server uses an artificial intelligence model to generate a travel plan based on the travel preference information; means for transmitting the generated travel plan to a terminal; means for the terminal to display the travel plan to the user; means for a user to customize the displayed itinerary; means for retransmitting the customized information to a server, and the server regenerating a travel plan; and means for ultimately displaying said regenerated travel plan to a user.

2. 2. The system according to claim 1, further comprising a connection means via a network for allowing the server and the terminal to communicate with each other.

3. 2. The system of claim 1, further comprising means for referencing past travel data and user history data when the server generates and regenerates travel plans.

Images